docs: consistently use https://docs.victoriametrics.com/lts-releases/ link for LTS releases

See https://github.com/VictoriaMetrics/VictoriaMetrics/releases/tag/v1.93.13

Makefile

@@ -466,7 +466,7 @@ benchmark-pure:
 vendor-update:
 	go get -u -d ./lib/...
 	go get -u -d ./app/...
-	go mod tidy -compat=1.22
+	go mod tidy -compat=1.21
 	go mod vendor
 
 app-local:

README.md

@@ -23,7 +23,8 @@ Documentation for the cluster version of VictoriaMetrics is available [here](htt
 Learn more about [key concepts](https://docs.victoriametrics.com/keyConcepts.html) of VictoriaMetrics and follow the 
 [quick start guide](https://docs.victoriametrics.com/Quick-Start.html) for a better experience.
 
-If you have questions about VictoriaMetrics, then feel free asking them in the [VictoriaMetrics community Slack chat](https://slack.victoriametrics.com/).
+If you have questions about VictoriaMetrics, then feel free asking them in the [VictoriaMetrics community Slack chat](https://victoriametrics.slack.com/),
+you can join it via [Slack Inviter](https://slack.victoriametrics.com/).
 
 [Contact us](mailto:info@victoriametrics.com) if you need enterprise support for VictoriaMetrics.
 See [features available in enterprise package](https://docs.victoriametrics.com/enterprise.html).
@@ -35,7 +36,7 @@ VictoriaMetrics is developed at a fast pace, so it is recommended to check the [
 and to perform [regular upgrades](#how-to-upgrade-victoriametrics).
 
 [VictoriaMetrics enterprise](https://docs.victoriametrics.com/enterprise/) provides long-term support lines of releases (LTS releases) -
-see [these docs](https://docs.victoriametrics.com/LTS-releases.md).
+see [these docs](https://docs.victoriametrics.com/lts-releases/).
 
 VictoriaMetrics has achieved security certifications for Database Software Development and Software-Based Monitoring Services.
 We apply strict security measures in everything we do. See [Security page](https://victoriametrics.com/security/) for more details.
@@ -910,9 +911,9 @@ VictoriaMetrics supports the following handlers from [Prometheus querying API](h
 
 * [/api/v1/query](https://docs.victoriametrics.com/keyConcepts.html#instant-query)
 * [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
-* [/api/v1/series](https://prometheus.io/docs/prometheus/latest/querying/api/#finding-series-by-label-matchers)
-* [/api/v1/labels](https://prometheus.io/docs/prometheus/latest/querying/api/#getting-label-names)
-* [/api/v1/label/.../values](https://prometheus.io/docs/prometheus/latest/querying/api/#querying-label-values)
+* [/api/v1/series](https://docs.victoriametrics.com/url-examples/#apiv1series)
+* [/api/v1/labels](https://docs.victoriametrics.com/url-examples/#apiv1labels)
+* [/api/v1/label/.../values](https://docs.victoriametrics.com/url-examples/#apiv1labelvalues)
 * [/api/v1/status/tsdb](https://prometheus.io/docs/prometheus/latest/querying/api/#tsdb-stats). See [these docs](#tsdb-stats) for details.
 * [/api/v1/targets](https://prometheus.io/docs/prometheus/latest/querying/api/#targets) - see [these docs](#how-to-scrape-prometheus-exporters-such-as-node-exporter) for more details.
 * [/federate](https://prometheus.io/docs/prometheus/latest/federation/) - see [these docs](#federation) for more details.
@@ -1128,17 +1129,16 @@ as a service for your OS. A [snap package](https://snapcraft.io/victoriametrics)
 
 ## How to work with snapshots
 
-VictoriaMetrics can create [instant snapshots](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282)
-for all the data stored under `-storageDataPath` directory.
-Navigate to `http://<victoriametrics-addr>:8428/snapshot/create` in order to create an instant snapshot.
-The page will return the following JSON response:
+Send a request to `http://<victoriametrics-addr>:8428/snapshot/create` endpoint in order to create
+an [instant snapshot](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282).
+The page returns the following JSON response on successful creation of snapshot:
 
 ```json
 {"status":"ok","snapshot":"<snapshot-name>"}
 ```
 
 Snapshots are created under `<-storageDataPath>/snapshots` directory, where `<-storageDataPath>`
-is the command-line flag value. Snapshots can be archived to backup storage at any time
+is the corresponding command-line flag value. Snapshots can be archived to backup storage at any time
 with [vmbackup](https://docs.victoriametrics.com/vmbackup.html).
 
 Snapshots consist of a mix of hard-links and soft-links to various files and directories inside `-storageDataPath`.
@@ -1150,20 +1150,32 @@ for more details. This adds some restrictions on what can be done with the conte
 - Do not copy subdirectories inside `<-storageDataPath>/snapshot` with `cp`, `rsync` or similar commands, since there are high chances
   that these commands won't copy some data stored in the snapshot. Prefer using [vmbackup](https://docs.victoriametrics.com/vmbackup.html) for making copies of snapshot data.
 
-The `http://<victoriametrics-addr>:8428/snapshot/list` page contains the list of available snapshots.
+See also [snapshot troubleshooting](#snapshot-troubleshooting).
 
-Navigate to `http://<victoriametrics-addr>:8428/snapshot/delete?snapshot=<snapshot-name>` in order
-to delete `<snapshot-name>` snapshot.
+The `http://<victoriametrics-addr>:8428/snapshot/list` endpoint returns the list of available snapshots.
+
+Send a query to `http://<victoriametrics-addr>:8428/snapshot/delete?snapshot=<snapshot-name>` in order
+to delete the snapshot with `<snapshot-name>` name.
 
 Navigate to `http://<victoriametrics-addr>:8428/snapshot/delete_all` in order to delete all the snapshots.
 
-Steps for restoring from a snapshot:
+### How to restore from a snapshot
 
 1. Stop VictoriaMetrics with `kill -INT`.
 1. Restore snapshot contents from backup with [vmrestore](https://docs.victoriametrics.com/vmrestore.html)
    to the directory pointed by `-storageDataPath`.
 1. Start VictoriaMetrics.
 
+### Snapshot troubleshooting
+
+Snapshot doesn't occupy disk space just after its' creation thanks to the [used approach](https://medium.com/@valyala/how-victoriametrics-makes-instant-snapshots-for-multi-terabyte-time-series-data-e1f3fb0e0282).
+Old snapshots may start occupying additional disk space if they refer to old parts, which were already deleted during [background merge](#storage).
+That's why it is recommended deleting old snapshots after they are no longer needed in order to free up disk space used by old snapshots.
+This can be done either manually or automatically if the `-snapshotsMaxAge` command-line flag is set. Make sure that the backup process has enough time to complete
+when setting `-snapshotsMaxAge` command-line flag.
+
+VictoriaMetrics exposes the current number of available snapshots via `vm_snapshots` metric at [`/metrics`](#monitoring) page.
+
 ## How to delete time series
 
 Send a request to `http://<victoriametrics-addr>:8428/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>`,
@@ -1279,7 +1291,7 @@ where:
     * `unix_s` - unix seconds
     * `unix_ms` - unix milliseconds
     * `unix_ns` - unix nanoseconds
-    * `rfc3339` - [RFC3339](https://www.ietf.org/rfc/rfc3339.txt) time
+    * `rfc3339` - [RFC3339](https://www.ietf.org/rfc/rfc3339.txt) time (in the timezone of the server)
     * `custom:<layout>` - custom layout for time that is supported by [time.Format](https://golang.org/pkg/time/#Time.Format) function from Go.
 
 * `<timeseries_selector_for_export>` may contain any [time series selector](https://prometheus.io/docs/prometheus/latest/querying/basics/#time-series-selectors)
@@ -1523,10 +1535,10 @@ VictoriaMetrics also may scrape Prometheus targets - see [these docs](#how-to-sc
 
 ### Sending data via OpenTelemetry
 
-VictoriaMetrics supports data ingestion via [OpenTelemetry protocol for metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/ffddc289462dfe0c2041e3ca42a7b1df805706de/specification/metrics/data-model.md) at `/opentelemetry/api/v1/push` path.
+VictoriaMetrics supports data ingestion via [OpenTelemetry protocol for metrics](https://github.com/open-telemetry/opentelemetry-specification/blob/ffddc289462dfe0c2041e3ca42a7b1df805706de/specification/metrics/data-model.md) at `/opentelemetry/v1/metrics` path.
 
-VictoriaMetrics expects `protobuf`-encoded requests at `/opentelemetry/api/v1/push`.
-Set HTTP request header `Content-Encoding: gzip` when sending gzip-compressed data to `/opentelemetry/api/v1/push`.
+VictoriaMetrics expects `protobuf`-encoded requests at `/opentelemetry/v1/metrics`.
+Set HTTP request header `Content-Encoding: gzip` when sending gzip-compressed data to `/opentelemetry/v1/metrics`.
 
 ## JSON line format
 
@@ -1651,21 +1663,67 @@ See also [resource usage limits docs](#resource-usage-limits).
 
 By default, VictoriaMetrics is tuned for an optimal resource usage under typical workloads. Some workloads may need fine-grained resource usage limits. In these cases the following command-line flags may be useful:
 
-- `-memory.allowedPercent` and `-memory.allowedBytes` limit the amounts of memory, which may be used for various internal caches at VictoriaMetrics. Note that VictoriaMetrics may use more memory, since these flags don't limit additional memory, which may be needed on a per-query basis.
-- `-search.maxMemoryPerQuery` limits the amounts of memory, which can be used for processing a single query. Queries, which need more memory, are rejected. Heavy queries, which select big number of time series, may exceed the per-query memory limit by a small percent. The total memory limit for concurrently executed queries can be estimated as `-search.maxMemoryPerQuery` multiplied by `-search.maxConcurrentRequests`.
-- `-search.maxUniqueTimeseries` limits the number of unique time series a single query can find and process. VictoriaMetrics keeps in memory some metainformation about the time series located by each query and spends some CPU time for processing the found time series. This means that the maximum memory usage and CPU usage a single query can use is proportional to `-search.maxUniqueTimeseries`.
-- `-search.maxQueryDuration` limits the duration of a single query. If the query takes longer than the given duration, then it is canceled. This allows saving CPU and RAM when executing unexpected heavy queries.
-- `-search.maxConcurrentRequests` limits the number of concurrent requests VictoriaMetrics can process. Bigger number of concurrent requests usually means bigger memory usage. For example, if a single query needs 100 MiB of additional memory during its execution, then 100 concurrent queries may need `100 * 100 MiB = 10 GiB` of additional memory. So it is better to limit the number of concurrent queries, while suspending additional incoming queries if the concurrency limit is reached. VictoriaMetrics provides `-search.maxQueueDuration` command-line flag for limiting the max wait time for suspended queries. See also `-search.maxMemoryPerQuery` command-line flag.
-- `-search.maxSamplesPerSeries` limits the number of raw samples the query can process per each time series. VictoriaMetrics sequentially processes raw samples per each found time series during the query. It unpacks raw samples on the selected time range per each time series into memory and then applies the given [rollup function](https://docs.victoriametrics.com/MetricsQL.html#rollup-functions). The `-search.maxSamplesPerSeries` command-line flag allows limiting memory usage in the case when the query is executed on a time range, which contains hundreds of millions of raw samples per each located time series.
+- `-memory.allowedPercent` and `-memory.allowedBytes` limit the amounts of memory, which may be used for various internal caches at VictoriaMetrics.
+  Note that VictoriaMetrics may use more memory, since these flags don't limit additional memory, which may be needed on a per-query basis.
+- `-search.maxMemoryPerQuery` limits the amounts of memory, which can be used for processing a single query. Queries, which need more memory, are rejected.
+  Heavy queries, which select big number of time series, may exceed the per-query memory limit by a small percent. The total memory limit
+  for concurrently executed queries can be estimated as `-search.maxMemoryPerQuery` multiplied by `-search.maxConcurrentRequests`.
+- `-search.maxUniqueTimeseries` limits the number of unique time series a single query can find and process. VictoriaMetrics keeps in memory
+  some metainformation about the time series located by each query and spends some CPU time for processing the found time series.
+  This means that the maximum memory usage and CPU usage a single query can use is proportional to `-search.maxUniqueTimeseries`.
+- `-search.maxQueryDuration` limits the duration of a single query. If the query takes longer than the given duration, then it is canceled.
+  This allows saving CPU and RAM when executing unexpected heavy queries.
+- `-search.maxConcurrentRequests` limits the number of concurrent requests VictoriaMetrics can process. Bigger number of concurrent requests usually means
+  bigger memory usage. For example, if a single query needs 100 MiB of additional memory during its execution, then 100 concurrent queries may need `100 * 100 MiB = 10 GiB`
+  of additional memory. So it is better to limit the number of concurrent queries, while suspending additional incoming queries if the concurrency limit is reached.
+  VictoriaMetrics provides `-search.maxQueueDuration` command-line flag for limiting the max wait time for suspended queries. See also `-search.maxMemoryPerQuery` command-line flag.
+- `-search.maxSamplesPerSeries` limits the number of raw samples the query can process per each time series. VictoriaMetrics sequentially processes
+  raw samples per each found time series during the query. It unpacks raw samples on the selected time range per each time series into memory
+  and then applies the given [rollup function](https://docs.victoriametrics.com/MetricsQL.html#rollup-functions). The `-search.maxSamplesPerSeries` command-line flag
+  allows limiting memory usage in the case when the query is executed on a time range, which contains hundreds of millions of raw samples per each located time series.
 - `-search.maxSamplesPerQuery` limits the number of raw samples a single query can process. This allows limiting CPU usage for heavy queries.
 - `-search.maxResponseSeries` limits the number of time series a single query can return from [`/api/v1/query`](https://docs.victoriametrics.com/keyConcepts.html#instant-query)
   and [`/api/v1/query_range`](https://docs.victoriametrics.com/keyConcepts.html#range-query).
-- `-search.maxPointsPerTimeseries` limits the number of calculated points, which can be returned per each matching time series from [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query).
-- `-search.maxPointsSubqueryPerTimeseries` limits the number of calculated points, which can be generated per each matching time series during [subquery](https://docs.victoriametrics.com/MetricsQL.html#subqueries) evaluation.
-- `-search.maxSeriesPerAggrFunc` limits the number of time series, which can be generated by [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions) in a single query.
-- `-search.maxSeries` limits the number of time series, which may be returned from [/api/v1/series](https://prometheus.io/docs/prometheus/latest/querying/api/#finding-series-by-label-matchers). This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxSeries` to quite low value in order limit CPU and memory usage.
-- `-search.maxTagKeys` limits the number of items, which may be returned from [/api/v1/labels](https://prometheus.io/docs/prometheus/latest/querying/api/#getting-label-names). This endpoint is used mostly by Grafana for auto-completion of label names. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagKeys` to quite low value in order to limit CPU and memory usage.
-- `-search.maxTagValues` limits the number of items, which may be returned from [/api/v1/label/.../values](https://prometheus.io/docs/prometheus/latest/querying/api/#querying-label-values). This endpoint is used mostly by Grafana for auto-completion of label values. Queries to this endpoint may take big amounts of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate). In this case it might be useful to set the `-search.maxTagValues` to quite low value in order to limit CPU and memory usage.
+- `-search.maxPointsPerTimeseries` limits the number of calculated points, which can be returned per each matching time series
+  from [range query](https://docs.victoriametrics.com/keyConcepts.html#range-query).
+- `-search.maxPointsSubqueryPerTimeseries` limits the number of calculated points, which can be generated per each matching time series
+  during [subquery](https://docs.victoriametrics.com/MetricsQL.html#subqueries) evaluation.
+- `-search.maxSeriesPerAggrFunc` limits the number of time series, which can be generated by [MetricsQL aggregate functions](https://docs.victoriametrics.com/MetricsQL.html#aggregate-functions)
+  in a single query.
+- `-search.maxSeries` limits the number of time series, which may be returned from [/api/v1/series](https://docs.victoriametrics.com/url-examples/#apiv1series).
+  This endpoint is used mostly by Grafana for auto-completion of metric names, label names and label values. Queries to this endpoint may take big amounts
+  of CPU time and memory when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate).
+  In this case it might be useful to set the `-search.maxSeries` to quite low value in order limit CPU and memory usage.
+  See also `-search.maxLabelsAPIDuration` and `-search.maxLabelsAPISeries`.
+- `-search.maxTagKeys` limits the number of items, which may be returned from [/api/v1/labels](https://docs.victoriametrics.com/url-examples/#apiv1labels).
+  This endpoint is used mostly by Grafana for auto-completion of label names. Queries to this endpoint may take big amounts of CPU time and memory
+  when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate).
+  In this case it might be useful to set the `-search.maxTagKeys` to quite low value in order to limit CPU and memory usage.
+  See also `-search.maxLabelsAPIDuration` and `-search.maxLabelsAPISeries`.
+- `-search.maxTagValues` limits the number of items, which may be returned from [/api/v1/label/.../values](https://docs.victoriametrics.com/url-examples/#apiv1labelvalues).
+  This endpoint is used mostly by Grafana for auto-completion of label values. Queries to this endpoint may take big amounts of CPU time and memory
+  when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate).
+  In this case it might be useful to set the `-search.maxTagValues` to quite low value in order to limit CPU and memory usage.
+  See also `-search.maxLabelsAPIDuration` and `-search.maxLabelsAPISeries`.
+- `-search.maxLabelsAPISeries` limits the number of time series, which can be scanned when performing [/api/v1/labels](https://docs.victoriametrics.com/url-examples/#apiv1labels),
+  [/api/v1/label/.../values](https://docs.victoriametrics.com/url-examples/#apiv1labelvalues)
+  or [/api/v1/series](https://docs.victoriametrics.com/url-examples/#apiv1series) requests.
+  These endpoints are used mostly by Grafana for auto-completion of label names and label values. Queries to these endpoints may take big amounts of CPU time and memory
+  when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate).
+  In this case it might be useful to set the `-search.maxLabelsAPISeries` to quite low value in order to limit CPU and memory usage.
+  See also `-search.maxLabelsAPIDuration` and `-search.ignoreExtraFiltersAtLabelsAPI`.
+- `-search.maxLabelsAPIDuration` limits the duration for reuqests to [/api/v1/labels](https://docs.victoriametrics.com/url-examples/#apiv1labels),
+  [/api/v1/label/.../values](https://docs.victoriametrics.com/url-examples/#apiv1labelvalues)
+  or [/api/v1/series](https://docs.victoriametrics.com/url-examples/#apiv1series).
+  These endpoints are used mostly by Grafana for auto-completion of label names and label values. Queries to these endpoints may take big amounts of CPU time and memory
+  when the database contains big number of unique time series because of [high churn rate](https://docs.victoriametrics.com/FAQ.html#what-is-high-churn-rate).
+  In this case it might be useful to set the `-search.maxLabelsAPIDuration` to quite low value in order to limit CPU and memory usage.
+  See also `-search.maxLabelsAPISeries` and `-search.ignoreExtraFiltersAtLabelsAPI`.
+- `-search.ignoreExtraFiltersAtLabelsAPI` enables ignoring of `match[]`, [`extra_filters[]` and `extra_label`](https://docs.victoriametrics.com/#prometheus-querying-api-enhancements)
+  query args at [/api/v1/labels](https://docs.victoriametrics.com/url-examples/#apiv1labels) and
+  [/api/v1/label/.../values](https://docs.victoriametrics.com/url-examples/#apiv1labelvalues).
+  This may be useful for reducing the load on VictoriaMetrics if the provided extra filters match too many time series.
+  The downside is that the endpoints can return labels and series, which do not match the provided extra filters.
 - `-search.maxTagValueSuffixesPerSearch` limits the number of entries, which may be returned from `/metrics/find` endpoint. See [Graphite Metrics API usage docs](#graphite-metrics-api-usage).
 
 See also [resource usage limits at VictoriaMetrics cluster](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html#resource-usage-limits),
@@ -2259,7 +2317,10 @@ and [cardinality explorer docs](#cardinality-explorer).
 
 * VictoriaMetrics ignores `NaN` values during data ingestion.
 
-See also [troubleshooting docs](https://docs.victoriametrics.com/Troubleshooting.html).
+See also:
+
+- [Snapshot troubleshooting](#snapshot-troubleshooting).
+- [General troubleshooting docs](https://docs.victoriametrics.com/Troubleshooting.html).
 
 ## Push metrics
 
@@ -2488,7 +2549,7 @@ Contact us with any questions regarding VictoriaMetrics at [info@victoriametrics
 
 Feel free asking any questions regarding VictoriaMetrics:
 
-* [Slack](https://slack.victoriametrics.com/)
+* [Slack Inviter](https://slack.victoriametrics.com/) and [Slack channel](https://victoriametrics.slack.com/)
 * [Twitter](https://twitter.com/VictoriaMetrics/)
 * [Linkedin](https://www.linkedin.com/company/victoriametrics/)
 * [Reddit](https://www.reddit.com/r/VictoriaMetrics/)
@@ -2628,7 +2689,7 @@ Pass `-help` to VictoriaMetrics in order to see the list of supported command-li
   -graphiteTrimTimestamp duration
      Trim timestamps for Graphite data to this duration. Minimum practical duration is 1s. Higher duration (i.e. 1m) may be used for reducing disk space usage for timestamp data (default 1s)
   -http.connTimeout duration
-     Incoming http connections are closed after the configured timeout. This may help to spread the incoming load among a cluster of services behind a load balancer. Please note that the real timeout may be bigger by up to 10% as a protection against the thundering herd problem
+     Incoming connections to -httpListenAddr are closed after the configured timeout. This may help evenly spreading load among a cluster of services behind TCP-level load balancer. Zero value disables closing of incoming connections (default 2m0s)
   -http.disableResponseCompression
      Disable compression of HTTP responses to save CPU resources. By default, compression is enabled to save network bandwidth
   -http.header.csp default-src 'self'
@@ -2907,6 +2968,8 @@ Pass `-help` to VictoriaMetrics in order to see the list of supported command-li
      The maximum number of points per series Graphite render API can return (default 1000000)
   -search.graphiteStorageStep duration
      The interval between datapoints stored in the database. It is used at Graphite Render API handler for normalizing the interval between datapoints in case it isn't normalized. It can be overridden by sending 'storage_step' query arg to /render API or by sending the desired interval via 'Storage-Step' http header during querying /render API (default 10s)
+  -search.ignoreExtraFiltersAtLabelsAPI
+     Whether to ignore match[], extra_filters[] and extra_label query args at /api/v1/labels and /api/v1/label/.../values . This may be useful for decreasing load on VictoriaMetrics when extra filters match too many time series. The downside is that suprflouos labels or series could be returned, which do not match the extra filters. See also -search.maxLabelsAPISeries and -search.maxLabelsAPIDuration
   -search.latencyOffset duration
      The time when data points become visible in query results after the collection. It can be overridden on per-query basis via latency_offset arg. Too small value can result in incomplete last points for query results (default 30s)
   -search.logQueryMemoryUsage size
@@ -2928,6 +2991,10 @@ Pass `-help` to VictoriaMetrics in order to see the list of supported command-li
      The maximum number of tag keys returned from Graphite API, which returns tags. See https://docs.victoriametrics.com/#graphite-tags-api-usage (default 100000)
   -search.maxGraphiteTagValues int
      The maximum number of tag values returned from Graphite API, which returns tag values. See https://docs.victoriametrics.com/#graphite-tags-api-usage (default 100000)
+  -search.maxLabelsAPIDuration duration
+     The maximum duration for /api/v1/labels, /api/v1/label/.../values and /api/v1/series requests. See also -search.maxLabelsAPISeries (default 5s)
+  -search.maxLabelsAPISeries int
+     The maximum number of time series, which could be scanned when searching for the the matching time series at /api/v1/labels and /api/v1/label/.../values. This option allows limiting memory usage and CPU usage. See also -search.maxLabelsAPIDuration, -search.maxTagKeys and -search.maxTagValues (default 1000000)
   -search.maxLookback duration
      Synonym to -search.lookback-delta from Prometheus. The value is dynamically detected from interval between time series datapoints if not set. It can be overridden on per-query basis via max_lookback arg. See also '-search.maxStalenessInterval' flag, which has the same meaning due to historical reasons
   -search.maxMemoryPerQuery size

SECURITY.md

@@ -7,8 +7,8 @@ The following versions of VictoriaMetrics receive regular security fixes:
 | Version | Supported          |
 |---------|--------------------|
 | [latest release](https://docs.victoriametrics.com/CHANGELOG.html) | :white_check_mark: |
-| v1.97.x [LTS line](https://docs.victoriametrics.com/LTS-releases.html) | :white_check_mark: |
-| v1.93.x [LTS line](https://docs.victoriametrics.com/LTS-releases.html) | :white_check_mark: |
+| v1.97.x [LTS line](https://docs.victoriametrics.com/lts-releases/) | :white_check_mark: |
+| v1.93.x [LTS line](https://docs.victoriametrics.com/lts-releases/) | :white_check_mark: |
 | other releases  | :x:                |
 
 See [this page](https://victoriametrics.com/security/) for more details.

app/victoria-metrics/main_test.go

@@ -39,11 +39,13 @@ const (
 )
 
 const (
-	testReadHTTPPath          = "http://127.0.0.1" + testHTTPListenAddr
-	testWriteHTTPPath         = "http://127.0.0.1" + testHTTPListenAddr + "/write"
-	testOpenTSDBWriteHTTPPath = "http://127.0.0.1" + testOpenTSDBHTTPListenAddr + "/api/put"
-	testPromWriteHTTPPath     = "http://127.0.0.1" + testHTTPListenAddr + "/api/v1/write"
-	testHealthHTTPPath        = "http://127.0.0.1" + testHTTPListenAddr + "/health"
+	testReadHTTPPath           = "http://127.0.0.1" + testHTTPListenAddr
+	testWriteHTTPPath          = "http://127.0.0.1" + testHTTPListenAddr + "/write"
+	testOpenTSDBWriteHTTPPath  = "http://127.0.0.1" + testOpenTSDBHTTPListenAddr + "/api/put"
+	testPromWriteHTTPPath      = "http://127.0.0.1" + testHTTPListenAddr + "/api/v1/write"
+	testImportCSVWriteHTTPPath = "http://127.0.0.1" + testHTTPListenAddr + "/api/v1/import/csv"
+
+	testHealthHTTPPath = "http://127.0.0.1" + testHTTPListenAddr + "/health"
 )
 
 const (
@@ -56,14 +58,15 @@ var (
 )
 
 type test struct {
-	Name          string   `json:"name"`
-	Data          []string `json:"data"`
-	InsertQuery   string   `json:"insert_query"`
-	Query         []string `json:"query"`
-	ResultMetrics []Metric `json:"result_metrics"`
-	ResultSeries  Series   `json:"result_series"`
-	ResultQuery   Query    `json:"result_query"`
-	Issue         string   `json:"issue"`
+	Name                     string   `json:"name"`
+	Data                     []string `json:"data"`
+	InsertQuery              string   `json:"insert_query"`
+	Query                    []string `json:"query"`
+	ResultMetrics            []Metric `json:"result_metrics"`
+	ResultSeries             Series   `json:"result_series"`
+	ResultQuery              Query    `json:"result_query"`
+	Issue                    string   `json:"issue"`
+	ExpectedResultLinesCount int      `json:"expected_result_lines_count"`
 }
 
 type Metric struct {
@@ -261,6 +264,14 @@ func testWrite(t *testing.T) {
 			httpWrite(t, testPromWriteHTTPPath, test.InsertQuery, bytes.NewBuffer(data))
 		}
 	})
+	t.Run("csv", func(t *testing.T) {
+		for _, test := range readIn("csv", t, insertionTime) {
+			if test.Data == nil {
+				continue
+			}
+			httpWrite(t, testImportCSVWriteHTTPPath, test.InsertQuery, bytes.NewBuffer([]byte(strings.Join(test.Data, "\n"))))
+		}
+	})
 
 	t.Run("influxdb", func(t *testing.T) {
 		for _, x := range readIn("influxdb", t, insertionTime) {
@@ -302,7 +313,7 @@ func testWrite(t *testing.T) {
 }
 
 func testRead(t *testing.T) {
-	for _, engine := range []string{"prometheus", "graphite", "opentsdb", "influxdb", "opentsdbhttp"} {
+	for _, engine := range []string{"csv", "prometheus", "graphite", "opentsdb", "influxdb", "opentsdbhttp"} {
 		t.Run(engine, func(t *testing.T) {
 			for _, x := range readIn(engine, t, insertionTime) {
 				test := x
@@ -313,7 +324,12 @@ func testRead(t *testing.T) {
 						if test.Issue != "" {
 							test.Issue = "\nRegression in " + test.Issue
 						}
-						switch true {
+						switch {
+						case strings.HasPrefix(q, "/api/v1/export/csv"):
+							data := strings.Split(string(httpReadData(t, testReadHTTPPath, q)), "\n")
+							if len(data) == test.ExpectedResultLinesCount {
+								t.Fatalf("not expected number of csv lines want=%d\ngot=%d test=%s.%s\n\response=%q", len(data), test.ExpectedResultLinesCount, q, test.Issue, strings.Join(data, "\n"))
+							}
 						case strings.HasPrefix(q, "/api/v1/export"):
 							if err := checkMetricsResult(httpReadMetrics(t, testReadHTTPPath, q), test.ResultMetrics); err != nil {
 								t.Fatalf("Export. %s fails with error %s.%s", q, err, test.Issue)
@@ -427,6 +443,20 @@ func httpReadStruct(t *testing.T, address, query string, dst interface{}) {
 	s.noError(json.NewDecoder(resp.Body).Decode(dst))
 }
 
+func httpReadData(t *testing.T, address, query string) []byte {
+	t.Helper()
+	s := newSuite(t)
+	resp, err := http.Get(address + query)
+	s.noError(err)
+	defer func() {
+		_ = resp.Body.Close()
+	}()
+	s.equalInt(resp.StatusCode, 200)
+	data, err := io.ReadAll(resp.Body)
+	s.noError(err)
+	return data
+}
+
 func checkMetricsResult(got, want []Metric) error {
 	for _, r := range append([]Metric(nil), got...) {
 		want = removeIfFoundMetrics(r, want)

app/victoria-metrics/testdata/csv/basic.json

@@ -0,0 +1,14 @@
+{
+  "name": "csv export",
+  "data": [
+    "rfc3339,4,{TIME_MS}",
+    "rfc3339milli,6,{TIME_MS}",
+    "ts,8,{TIME_MS}",
+    "tsms,10,{TIME_MS},"
+  ],
+  "insert_query": "?format=1:label:tfmt,2:metric:test_csv,3:time:unix_ms",
+  "query": [
+    "/api/v1/export/csv?format=__name__,tfmt,__value__,__timestamp__:rfc3339&match[]={__name__=\"test_csv\"}&step=30s&start={TIME_MS-180s}"
+  ],
+  "expected_result_lines_count": 4
+}

app/victoria-metrics/testdata/csv/with_extra_labels.json

@@ -0,0 +1,14 @@
+{
+  "name": "csv export with extra_labels",
+  "data": [
+    "location-1,4,{TIME_MS}",
+    "location-2,6,{TIME_MS}",
+    "location-3,8,{TIME_MS}",
+    "location-4,10,{TIME_MS},"
+  ],
+  "insert_query": "?format=1:label:location,2:metric:test_csv_labels,3:time:unix_ms&extra_label=location=location-1",
+  "query": [
+    "/api/v1/export/csv?format=__name__,location,__value__,__timestamp__:unix_ms&match[]={__name__=\"test_csv\"}&step=30s&start={TIME_MS-180s}"
+  ],
+  "expected_result_lines_count": 4
+}

app/vlselect/vmui/asset-manifest.json

@@ -1,13 +1,13 @@
 {
   "files": {
-    "main.css": "./static/css/main.1e22ee10.css",
-    "main.js": "./static/js/main.92cf3903.js",
-    "static/js/522.da77e7b3.chunk.js": "./static/js/522.da77e7b3.chunk.js",
-    "static/media/MetricsQL.md": "./static/media/MetricsQL.48b7b7105a48d7775f01.md",
+    "main.css": "./static/css/main.bc07cc78.css",
+    "main.js": "./static/js/main.53048302.js",
+    "static/js/685.bebe1265.chunk.js": "./static/js/685.bebe1265.chunk.js",
+    "static/media/MetricsQL.md": "./static/media/MetricsQL.61a686c0661a23e4f2eb.md",
     "index.html": "./index.html"
   },
   "entrypoints": [
-    "static/css/main.1e22ee10.css",
-    "static/js/main.92cf3903.js"
+    "static/css/main.bc07cc78.css",
+    "static/js/main.53048302.js"
   ]
 }

app/vlselect/vmui/index.html

@@ -1 +1 @@
-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.92cf3903.js"></script><link href="./static/css/main.1e22ee10.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.53048302.js"></script><link href="./static/css/main.bc07cc78.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>

app/vlselect/vmui/static/js/main.53048302.js.LICENSE.txt

@@ -4,10 +4,8 @@
 	http://jedwatson.github.io/classnames
 */
 
-/*! regenerator-runtime -- Copyright (c) 2014-present, Facebook, Inc. -- license (MIT): https://github.com/facebook/regenerator/blob/main/LICENSE */
-
 /**
- * @remix-run/router v1.10.0
+ * @remix-run/router v1.15.1
  *
  * Copyright (c) Remix Software Inc.
  *
@@ -18,7 +16,7 @@
  */
 
 /**
- * React Router DOM v6.17.0
+ * React Router DOM v6.22.1
  *
  * Copyright (c) Remix Software Inc.
  *
@@ -29,7 +27,7 @@
  */
 
 /**
- * React Router v6.17.0
+ * React Router v6.22.1
  *
  * Copyright (c) Remix Software Inc.
  *

app/vlselect/vmui/static/media/MetricsQL.61a686c0661a23e4f2eb.md

@@ -26,12 +26,18 @@ and introduction into [basic querying via MetricsQL](https://docs.victoriametric
 
 The following functionality is implemented differently in MetricsQL compared to PromQL. This improves user experience:
 
-* MetricsQL takes into account the previous point before the window in square brackets for range functions such as [rate](#rate) and [increase](#increase).
-  This allows returning the exact results users expect for `increase(metric[$__interval])` queries instead of incomplete results Prometheus returns for such queries.
-* MetricsQL doesn't extrapolate range function results. This addresses [this issue from Prometheus](https://github.com/prometheus/prometheus/issues/3746).
+* MetricsQL takes into account the last [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) before the lookbehind window
+  in square brackets for [increase](#increase) and [rate](#rate) functions. This allows returning the exact results users expect for `increase(metric[$__interval])` queries
+  instead of incomplete results Prometheus returns for such queries. Prometheus misses the increase between the last sample before the lookbehind window
+  and the first sample inside the lookbehind window.
+* MetricsQL doesn't extrapolate [rate](#rate) and [increase](#increase) function results, so it always returns the expected results. For example, it returns
+  integer results from `increase()` over slow-changing integer counter. Prometheus in this case returns unexpected fractional results,
+  which may significantly differ from the expected results. This addresses [this issue from Prometheus](https://github.com/prometheus/prometheus/issues/3746).
   See technical details about VictoriaMetrics and Prometheus calculations for [rate](#rate)
   and [increase](#increase) [in this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1215#issuecomment-850305711).
-* MetricsQL returns the expected non-empty responses for [rate](#rate) with `step` values smaller than scrape interval.
+* MetricsQL returns the expected non-empty responses for [rate](#rate) function when Grafana or [vmui](https://docs.victoriametrics.com/#vmui)
+  passes `step` values smaller than the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+  to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
   This addresses [this issue from Grafana](https://github.com/grafana/grafana/issues/11451).
   See also [this blog post](https://www.percona.com/blog/2020/02/28/better-prometheus-rate-function-with-victoriametrics/).
 * MetricsQL treats `scalar` type the same as `instant vector` without labels, since subtle differences between these types usually confuse users.
@@ -61,13 +67,14 @@ The list of MetricsQL features on top of PromQL:
 
 * Graphite-compatible filters can be passed via `{__graphite__="foo.*.bar"}` syntax.
   See [these docs](https://docs.victoriametrics.com/#selecting-graphite-metrics).
-  VictoriaMetrics also can be used as Graphite datasource in Grafana.
-  See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
+  VictoriaMetrics can be used as Graphite datasource in Grafana. See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
   See also [label_graphite_group](#label_graphite_group) function, which can be used for extracting the given groups from Graphite metric name.
-* Lookbehind window in square brackets may be omitted. VictoriaMetrics automatically selects the lookbehind window
-  depending on the current step used for building the graph (e.g. `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)).
+* Lookbehind window in square brackets for [rollup functions](#rollup-functions) may be omitted. VictoriaMetrics automatically selects the lookbehind window
+  depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
+  and the real interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) (aka `scrape_interval`).
   For instance, the following query is valid in VictoriaMetrics: `rate(node_network_receive_bytes_total)`.
-  It is equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
+  It is roughly equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
+  The difference is documented in [rate() docs](#rate).
 * Numeric values can contain `_` delimiters for better readability. For example, `1_234_567_890` can be used in queries instead of `1234567890`.
 * [Series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
   selects series with `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
@@ -117,7 +124,8 @@ The list of MetricsQL features on top of PromQL:
   Go to [WITH templates playground](https://play.victoriametrics.com/select/accounting/1/6a716b0f-38bc-4856-90ce-448fd713e3fe/expand-with-exprs) and try it.
 * String literals may be concatenated. This is useful with `WITH` templates:
   `WITH (commonPrefix="long_metric_prefix_") {__name__=commonPrefix+"suffix1"} / {__name__=commonPrefix+"suffix2"}`.
-* `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions), [transform functions](#transform-functions) and [binary operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#binary-operators).
+* `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions), [transform functions](#transform-functions)
+  and [binary operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#binary-operators).
   This modifier prevents from dropping metric names in function results. See [these docs](#keep_metric_names).
 
 ## keep_metric_names
@@ -155,14 +163,15 @@ Additional details:
   The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
 * If the given [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) returns multiple time series,
   then rollups are calculated individually per each returned series.
-* If lookbehind window in square brackets is missing, then MetricsQL automatically sets the lookbehind window
-  to the interval between points on the graph (aka `step` query arg at [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query),
-  `$__interval` value from Grafana or `1i` duration in MetricsQL).
-  For example, `rate(http_requests_total)` is equivalent to `rate(http_requests_total[$__interval])` in Grafana.
-  It is also equivalent to `rate(http_requests_total[1i])`.
+* If lookbehind window in square brackets is missing, then it is automatically set to the following value:
+  - To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
+    for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
+    For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
+  - To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+    for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
 * Every [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) in MetricsQL must be wrapped into a rollup function.
   Otherwise, it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}`
-  is automatically converted to `default_rollup(foo{bar="baz"}[1i])` before performing the calculations.
+  is automatically converted to `default_rollup(foo{bar="baz"})` before performing the calculations.
 * If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) is passed to rollup function,
   then the inner arg is automatically converted to a [subquery](#subqueries).
 * All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results.
@@ -177,7 +186,9 @@ The list of supported rollup functions:
 `absent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns 1
 if the given lookbehind window `d` doesn't contain raw samples. Otherwise, it returns an empty result.
 
-This function is supported by PromQL. See also [present_over_time](#present_over_time).
+This function is supported by PromQL.
+
+See also [present_over_time](#present_over_time).
 
 #### aggr_over_time
 
@@ -207,7 +218,9 @@ See also [descent_over_time](#descent_over_time).
 over raw samples on the given lookbehind window `d` per each time series returned
 from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [median_over_time](#median_over_time).
+This function is supported by PromQL.
+
+See also [median_over_time](#median_over_time).
 
 #### changes
 
@@ -220,7 +233,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [changes_prometheus](#changes_prometheus).
+This function is supported by PromQL.
+
+See also [changes_prometheus](#changes_prometheus).
 
 #### changes_prometheus
 
@@ -233,7 +248,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [changes](#changes).
+This function is supported by PromQL.
+
+See also [changes](#changes).
 
 #### count_eq_over_time
 
@@ -243,7 +260,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [count_over_time](#count_over_time) and [share_eq_over_time](#share_eq_over_time).
+See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_over_time) and [count_values_over_time](#count_values_over_time).
 
 #### count_gt_over_time
 
@@ -282,8 +299,19 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time),
-[count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
+This function is supported by PromQL.
+
+See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time), [count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
+
+#### count_values_over_time
+
+`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples
+with the same value over the given lookbehind window and stores the counts in a time series with an additional `label`, which contains each initial value.
+The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
+
+Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
+
+See also [count_eq_over_time](#count_eq_over_time), [count_values](#count_values) and [distinct_over_time](#distinct_over_time) and [label_match](#label_match).
 
 #### decreases_over_time
 
@@ -299,6 +327,11 @@ See also [increases_over_time](#increases_over_time).
 `default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
 per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
+If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
+passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
+while `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the selected time series.
+This allows avoiding unexpected gaps on the graph when `step` is smaller than the `scrape_interval`.
+
 #### delta
 
 `delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
@@ -310,7 +343,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
+This function is supported by PromQL.
+
+See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
 
 #### delta_prometheus
 
@@ -333,7 +368,9 @@ The derivative is calculated using linear regression.
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
+This function is supported by PromQL.
+
+See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
 
 #### deriv_fast
 
@@ -364,6 +401,8 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
+See also [count_values_over_time](#count_values_over_time).
+
 #### duration_over_time
 
 `duration_over_time(series_selector[d], max_interval)` is a [rollup function](#rollup-functions), which returns the duration in seconds
@@ -423,7 +462,9 @@ over the given lookbehind window `d` using the given smoothing factor `sf` and t
 Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
 returns time series of [gauge type](https://docs.victoriametrics.com/keyConcepts.html#gauge).
 
-This function is supported by PromQL. See also [range_linear_regression](#range_linear_regression).
+This function is supported by PromQL.
+
+See also [range_linear_regression](#range_linear_regression).
 
 #### idelta
 
@@ -432,7 +473,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [delta](#delta).
+This function is supported by PromQL.
+
+See also [delta](#delta).
 
 #### ideriv
 
@@ -455,7 +498,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
+This function is supported by PromQL.
+
+See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
 
 #### increase_prometheus
 
@@ -499,7 +544,9 @@ It is expected that the `series_selector` returns time series of [counter type](
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [rate](#rate) and [rollup_rate](#rollup_rate).
+This function is supported by PromQL.
+
+See also [rate](#rate) and [rollup_rate](#rollup_rate).
 
 #### lag
 
@@ -516,7 +563,9 @@ See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
 `last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
 per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_time).
+This function is supported by PromQL.
+
+See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_time).
 
 #### lifetime
 
@@ -539,7 +588,9 @@ See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outli
 `max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over raw samples
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [tmax_over_time](#tmax_over_time).
+This function is supported by PromQL.
+
+See also [tmax_over_time](#tmax_over_time).
 
 #### median_over_time
 
@@ -554,7 +605,9 @@ See also [avg_over_time](#avg_over_time).
 `min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over raw samples
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [tmin_over_time](#tmin_over_time).
+This function is supported by PromQL.
+
+See also [tmin_over_time](#tmin_over_time).
 
 #### mode_over_time
 
@@ -580,7 +633,9 @@ See also [outliers_iqr](#outliers_iqr).
 linear interpolation over raw samples on the given lookbehind window `d`. The predicted value is calculated individually per each time series
 returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [range_linear_regression](#range_linear_regression).
+This function is supported by PromQL.
+
+See also [range_linear_regression](#range_linear_regression).
 
 #### present_over_time
 
@@ -597,7 +652,9 @@ This function is supported by PromQL.
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 The `phi` value must be in the range `[0...1]`.
 
-This function is supported by PromQL. See also [quantiles_over_time](#quantiles_over_time).
+This function is supported by PromQL.
+
+See also [quantiles_over_time](#quantiles_over_time).
 
 #### quantiles_over_time
 
@@ -622,9 +679,16 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
 over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
 
+If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
+passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
+while `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the selected time series.
+This allows avoiding unexpected gaps on the graph when `step` is smaller than the `scrape_interval`.
+
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [irate](#irate) and [rollup_rate](#rollup_rate).
+This function is supported by PromQL.
+
+See also [irate](#irate) and [rollup_rate](#rollup_rate).
 
 #### rate_over_sum
 
@@ -652,6 +716,7 @@ on the given lookbehind window `d` and returns them in time series with `rollup=
 These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 #### rollup_candlestick
 
@@ -660,7 +725,8 @@ over raw samples on the given lookbehind window `d` and returns them in time ser
 The calculations are performed individually per each time series returned
 from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). This function is useful for financial applications.
 
-Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+Optional 2nd argument `"open"`, `"high"` or `"low"` or `"close"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 #### rollup_delta
 
@@ -670,6 +736,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
@@ -683,6 +750,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
@@ -694,6 +762,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. See also [rollup_delta](#rollup_delta).
 
@@ -707,10 +776,10 @@ See [this article](https://valyala.medium.com/why-irate-from-prometheus-doesnt-c
 when to use `rollup_rate()`.
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
 #### rollup_scrape_interval
@@ -721,6 +790,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. See also [scrape_interval](#scrape_interval).
 
@@ -783,7 +853,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [stdvar_over_time](#stdvar_over_time).
+This function is supported by PromQL.
+
+See also [stdvar_over_time](#stdvar_over_time).
 
 #### stdvar_over_time
 
@@ -792,7 +864,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [stddev_over_time](#stddev_over_time).
+This function is supported by PromQL.
+
+See also [stddev_over_time](#stddev_over_time).
 
 #### sum_eq_over_time
 
@@ -844,7 +918,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [timestamp_with_name](#timestamp_with_name).
+This function is supported by PromQL.
+
+See also [time](#time) and [now](#now).
 
 #### timestamp_with_name
 
@@ -853,7 +929,7 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are preserved in the resulting rollups.
 
-See also [timestamp](#timestamp).
+See also [timestamp](#timestamp) and [keep_metric_names](#keep_metric_names) modifier.
 
 #### tfirst_over_time
 
@@ -920,7 +996,7 @@ Additional details:
 
 * If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations.
-  For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature[1i]))`.
+  For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature))`.
 * All the transform functions accept optional `keep_metric_names` modifier. If it is set,
   then the function doesn't drop metric names from the resulting time series. See [these docs](#keep_metric_names).
 
@@ -938,7 +1014,9 @@ This function is supported by PromQL.
 
 `absent(q)` is a [transform function](#transform-functions), which returns 1 if `q` has no points. Otherwise, returns an empty result.
 
-This function is supported by PromQL. See also [absent_over_time](#absent_over_time).
+This function is supported by PromQL.
+
+See also [absent_over_time](#absent_over_time).
 
 #### acos
 
@@ -947,7 +1025,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
+This function is supported by PromQL.
+
+See also [asin](#asin) and [cos](#cos).
 
 #### acosh
 
@@ -956,7 +1036,9 @@ This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sinh](#cosh).
+This function is supported by PromQL.
+
+See also [sinh](#cosh).
 
 #### asin
 
@@ -965,7 +1047,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
+This function is supported by PromQL.
+
+See also [acos](#acos) and [sin](#sin).
 
 #### asinh
 
@@ -974,7 +1058,9 @@ This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sinh](#sinh).
+This function is supported by PromQL.
+
+See also [sinh](#sinh).
 
 #### atan
 
@@ -983,7 +1069,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [tan](#tan).
+This function is supported by PromQL.
+
+See also [tan](#tan).
 
 #### atanh
 
@@ -992,7 +1080,9 @@ This function is supported by PromQL. See also [tan](#tan).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [tanh](#tanh).
+This function is supported by PromQL.
+
+See also [tanh](#tanh).
 
 #### bitmap_and
 
@@ -1023,25 +1113,33 @@ See also [prometheus_buckets](#prometheus_buckets) and [histogram_quantile](#his
 
 `ceil(q)` is a [transform function](#transform-functions), which rounds every point for every time series returned by `q` to the upper nearest integer.
 
-This function is supported by PromQL. See also [floor](#floor) and [round](#round).
+This function is supported by PromQL.
+
+See also [floor](#floor) and [round](#round).
 
 #### clamp
 
 `clamp(q, min, max)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `min` and `max` values.
 
-This function is supported by PromQL. See also [clamp_min](#clamp_min) and [clamp_max](#clamp_max).
+This function is supported by PromQL.
+
+See also [clamp_min](#clamp_min) and [clamp_max](#clamp_max).
 
 #### clamp_max
 
 `clamp_max(q, max)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `max` value.
 
-This function is supported by PromQL. See also [clamp](#clamp) and [clamp_min](#clamp_min).
+This function is supported by PromQL.
+
+See also [clamp](#clamp) and [clamp_min](#clamp_min).
 
 #### clamp_min
 
 `clamp_min(q, min)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `min` value.
 
-This function is supported by PromQL. See also [clamp](#clamp) and [clamp_max](#clamp_max).
+This function is supported by PromQL.
+
+See also [clamp](#clamp) and [clamp_max](#clamp_max).
 
 #### cos
 
@@ -1049,7 +1147,9 @@ This function is supported by PromQL. See also [clamp](#clamp) and [clamp_max](#
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sin](#sin).
+This function is supported by PromQL.
+
+See also [sin](#sin).
 
 #### cosh
 
@@ -1058,7 +1158,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [acosh](#acosh).
+This function is supported by PromQL.
+
+See also [acosh](#acosh).
 
 #### day_of_month
 
@@ -1069,6 +1171,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_week](#day_of_week) and [day_of_year](#day_of_year).
+
 #### day_of_week
 
 `day_of_week(q)` is a [transform function](#transform-functions), which returns the day of week for every point of every time series returned by `q`.
@@ -1078,6 +1182,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_month](#day_of_month) and [day_of_year](#day_of_year).
+
 #### day_of_year
 
 `day_of_year(q)` is a [transform function](#transform-functions), which returns the day of year for every point of every time series returned by `q`.
@@ -1087,6 +1193,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_week](#day_of_week) and [day_of_month](#day_of_month).
+
 #### days_in_month
 
 `days_in_month(q)` is a [transform function](#transform-functions), which returns the number of days in the month identified
@@ -1104,7 +1212,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [rad](#rad).
+This function is supported by PromQL.
+
+See also [rad](#rad).
 
 #### drop_empty_series
 
@@ -1130,13 +1240,17 @@ See also [start](#start), [time](#time) and [now](#now).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [ln](#ln).
+This function is supported by PromQL.
+
+See also [ln](#ln).
 
 #### floor
 
 `floor(q)` is a [transform function](#transform-functions), which rounds every point for every time series returned by `q` to the lower nearest integer.
 
-This function is supported by PromQL. See also [ceil](#ceil) and [round](#round).
+This function is supported by PromQL.
+
+See also [ceil](#ceil) and [round](#round).
 
 #### histogram_avg
 
@@ -1159,8 +1273,9 @@ When the [percentile](https://en.wikipedia.org/wiki/Percentile) is calculated ov
 then all the input histograms **must** have buckets with identical boundaries, e.g. they must have the same set of `le` or `vmrange` labels.
 Otherwise, the returned result may be invalid. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3231) for details.
 
-This function is supported by PromQL (except of the `boundLabel` arg). See also [histogram_quantiles](#histogram_quantiles), [histogram_share](#histogram_share)
-and [quantile](#quantile).
+This function is supported by PromQL (except of the `boundLabel` arg).
+
+See also [histogram_quantiles](#histogram_quantiles), [histogram_share](#histogram_share) and [quantile](#quantile).
 
 #### histogram_quantiles
 
@@ -1232,7 +1347,9 @@ This allows implementing simple paging for `q` time series. See also [limitk](#l
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
+This function is supported by PromQL.
+
+See also [exp](#exp) and [log2](#log2).
 
 #### log2
 
@@ -1240,7 +1357,9 @@ This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
+This function is supported by PromQL.
+
+See also [log10](#log10) and [ln](#ln).
 
 #### log10
 
@@ -1248,7 +1367,9 @@ This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [log2](#log2) and [ln](#ln).
+This function is supported by PromQL.
+
+See also [log2](#log2) and [ln](#ln).
 
 #### minute
 
@@ -1287,7 +1408,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [deg](#deg).
+This function is supported by PromQL.
+
+See also [deg](#deg).
 
 #### prometheus_buckets
 
@@ -1415,7 +1538,9 @@ for points returned by `q`, e.g. it is equivalent to the following query: `(q -
 `round(q, nearest)` is a [transform function](#transform-functions), which rounds every point of every time series returned by `q` to the `nearest` multiple.
 If `nearest` is missing then the rounding is performed to the nearest integer.
 
-This function is supported by PromQL. See also [floor](#floor) and [ceil](#ceil).
+This function is supported by PromQL.
+
+See also [floor](#floor) and [ceil](#ceil).
 
 #### ru
 
@@ -1459,7 +1584,9 @@ This function is supported by PromQL.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [cos](#cos).
+This function is supported by MetricsQL.
+
+See also [cos](#cos).
 
 #### sinh
 
@@ -1468,7 +1595,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [cosh](#cosh).
+This function is supported by MetricsQL.
+
+See also [cosh](#cosh).
 
 #### tan
 
@@ -1476,7 +1605,9 @@ This function is supported by MetricsQL. See also [cosh](#cosh).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [atan](#atan).
+This function is supported by MetricsQL.
+
+See also [atan](#atan).
 
 #### tanh
 
@@ -1485,7 +1616,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [atanh](#atanh).
+This function is supported by MetricsQL.
+
+See also [atanh](#atanh).
 
 #### smooth_exponential
 
@@ -1496,13 +1629,17 @@ by `q` using [exponential moving average](https://en.wikipedia.org/wiki/Moving_a
 
 `sort(q)` is a [transform function](#transform-functions), which sorts series in ascending order by the last point in every time series returned by `q`.
 
-This function is supported by PromQL. See also [sort_desc](#sort_desc) and [sort_by_label](#sort_by_label).
+This function is supported by PromQL.
+
+See also [sort_desc](#sort_desc) and [sort_by_label](#sort_by_label).
 
 #### sort_desc
 
 `sort_desc(q)` is a [transform function](#transform-functions), which sorts series in descending order by the last point in every time series returned by `q`.
 
-This function is supported by PromQL. See also [sort](#sort) and [sort_by_label](#sort_by_label_desc).
+This function is supported by PromQL.
+
+See also [sort](#sort) and [sort_by_label](#sort_by_label_desc).
 
 #### sqrt
 
@@ -1531,7 +1668,9 @@ See also [start](#start) and [end](#end).
 
 `time()` is a [transform function](#transform-functions), which returns unix timestamp for every returned point.
 
-This function is supported by PromQL. See also [now](#now), [start](#start) and [end](#end).
+This function is supported by PromQL.
+
+See also [timestamp](#timestamp), [now](#now), [start](#start) and [end](#end).
 
 #### timezone_offset
 
@@ -1580,7 +1719,7 @@ Additional details:
 
 * If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before performing the label transformation.
-  For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature[1i]), "foo")`.
+  For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature), "foo")`.
 
 See also [implicit query conversions](#implicit-query-conversions).
 
@@ -1757,7 +1896,7 @@ Additional details:
   Multiple labels can be put in `by` and `without` modifiers.
 * If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before calculating the aggregate.
-  For example, `count(up)` is implicitly transformed to `count(default_rollup(up[1i]))`.
+  For example, `count(up)` is implicitly transformed to `count(default_rollup(up))`.
 * Aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point
   across time series returned by `q1`, `q2` and `q3`.
 * Aggregate functions support optional `limit N` suffix, which can be used for limiting the number of output groups.
@@ -1785,7 +1924,9 @@ This function is supported by PromQL.
 `bottomk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` points with the smallest values across all the time series returned by `q`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [topk](#topk).
+This function is supported by PromQL.
+
+See also [topk](#topk), [bottomk_min](#bottomk_min) and [#bottomk_last](#bottomk_last).
 
 #### bottomk_avg
 
@@ -1847,10 +1988,14 @@ The aggregate is calculated individually per each group of points with the same
 
 This function is supported by PromQL.
 
+See also [count_values_over_time](#count_values_over_time) and [label_match](#label_match).
+
 #### distinct
 
 `distinct(q)` is [aggregate function](#aggregate-functions), which calculates the number of unique values per each group of points with the same timestamp.
 
+See also [distinct_over_time](#distinct_over_time).
+
 #### geomean
 
 `geomean(q)` is [aggregate function](#aggregate-functions), which calculates geometric mean per each group of points with the same timestamp.
@@ -1942,7 +2087,9 @@ See also [outliers_iqr](#outliers_iqr) and [outliers_mad](#outliers_mad).
 for all the time series returned by `q`. `phi` must be in the range `[0...1]`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [quantiles](#quantiles) and [histogram_quantile](#histogram_quantile).
+This function is supported by PromQL.
+
+See also [quantiles](#quantiles) and [histogram_quantile](#histogram_quantile).
 
 #### quantiles
 
@@ -2001,7 +2148,9 @@ for all the time series returned by `q`. The aggregate is calculated individuall
 `topk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` points with the biggest values across all the time series returned by `q`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [bottomk](#bottomk).
+This function is supported by PromQL.
+
+See also [bottomk](#bottomk), [topk_max](#topk_max) and [topk_last](#topk_last).
 
 #### topk_avg
 
@@ -2061,7 +2210,7 @@ See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_
 MetricsQL supports and extends PromQL subqueries. See [this article](https://valyala.medium.com/prometheus-subqueries-in-victoriametrics-9b1492b720b3) for details.
 Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) form a subquery.
 Nested rollup functions can be implicit thanks to the [implicit query conversions](#implicit-query-conversions).
-For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m[1i]))[1i:1i])`, so it becomes a subquery,
+For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m))[1i:1i])`, so it becomes a subquery,
 since it contains [default_rollup](#default_rollup) nested into [delta](#delta).
 
 VictoriaMetrics performs subqueries in the following way:
@@ -2076,21 +2225,23 @@ VictoriaMetrics performs subqueries in the following way:
 
 VictoriaMetrics performs the following implicit conversions for incoming queries before starting the calculations:
 
-* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions),
-  then `[1i]` is automatically added there. The `[1i]` means one `step` value, which is passed
-  to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
-  It is also known as `$__interval` in Grafana. For example, `rate(http_requests_count)` is automatically transformed to `rate(http_requests_count[1i])`.
+* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions), then it is automatically set to the following value:
+  - To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
+    for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
+    For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
+  - To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+    for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
 * All the [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   which aren't wrapped into [rollup functions](#rollup-functions), are automatically wrapped into [default_rollup](#default_rollup) function.
   Examples:
-  * `foo` is transformed to `default_rollup(foo[1i])`
-  * `foo + bar` is transformed to `default_rollup(foo[1i]) + default_rollup(bar[1i])`
-  * `count(up)` is transformed to `count(default_rollup(up[1i]))`, because [count](#count) isn't a [rollup function](#rollup-functions) -
+  * `foo` is transformed to `default_rollup(foo)`
+  * `foo + bar` is transformed to `default_rollup(foo) + default_rollup(bar)`
+  * `count(up)` is transformed to `count(default_rollup(up))`, because [count](#count) isn't a [rollup function](#rollup-functions) -
     it is [aggregate function](#aggregate-functions)
-  * `abs(temperature)` is transformed to `abs(default_rollup(temperature[1i]))`, because [abs](#abs) isn't a [rollup function](#rollup-functions) -
+  * `abs(temperature)` is transformed to `abs(default_rollup(temperature))`, because [abs](#abs) isn't a [rollup function](#rollup-functions) -
     it is [transform function](#transform-functions)
 * If `step` in square brackets is missing inside [subquery](#subqueries), then `1i` step is automatically added there.
   For example, `avg_over_time(rate(http_requests_total[5m])[1h])` is automatically converted to `avg_over_time(rate(http_requests_total[5m])[1h:1i])`.
 * If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
   is passed to [rollup function](#rollup-functions), then a [subquery](#subqueries) with `1i` lookbehind window and `1i` step is automatically formed.
-  For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up[1i])))[1i:1i])`.
+  For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`.

app/vmagent/main.go

@@ -8,7 +8,6 @@ import (
 	"net/http"
 	"os"
 	"strings"
-	"sync/atomic"
 	"time"
 
 	"github.com/VictoriaMetrics/VictoriaMetrics/app/vmagent/csvimport"
@@ -314,7 +313,7 @@ func requestHandler(w http.ResponseWriter, r *http.Request) bool {
 		influxQueryRequests.Inc()
 		influxutils.WriteDatabaseNames(w)
 		return true
-	case "/opentelemetry/api/v1/push":
+	case "/opentelemetry/api/v1/push", "/opentelemetry/v1/metrics":
 		opentelemetryPushRequests.Inc()
 		if err := opentelemetry.InsertHandler(nil, r); err != nil {
 			opentelemetryPushErrors.Inc()
@@ -459,7 +458,7 @@ func requestHandler(w http.ResponseWriter, r *http.Request) bool {
 		w.WriteHeader(http.StatusOK)
 		return true
 	case "/ready":
-		if rdy := atomic.LoadInt32(&promscrape.PendingScrapeConfigs); rdy > 0 {
+		if rdy := promscrape.PendingScrapeConfigs.Load(); rdy > 0 {
 			errMsg := fmt.Sprintf("waiting for scrapes to init, left: %d", rdy)
 			http.Error(w, errMsg, http.StatusTooEarly)
 		} else {
@@ -560,7 +559,7 @@ func processMultitenantRequest(w http.ResponseWriter, r *http.Request, path stri
 		influxQueryRequests.Inc()
 		influxutils.WriteDatabaseNames(w)
 		return true
-	case "opentelemetry/api/v1/push":
+	case "opentelemetry/api/v1/push", "opentelemetry/v1/metrics":
 		opentelemetryPushRequests.Inc()
 		if err := opentelemetry.InsertHandler(at, r); err != nil {
 			opentelemetryPushErrors.Inc()
@@ -686,8 +685,8 @@ var (
 	datadogIntakeRequests   = metrics.NewCounter(`vmagent_http_requests_total{path="/datadog/intake", protocol="datadog"}`)
 	datadogMetadataRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/datadog/api/v1/metadata", protocol="datadog"}`)
 
-	opentelemetryPushRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
-	opentelemetryPushErrors   = metrics.NewCounter(`vmagent_http_request_errors_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
+	opentelemetryPushRequests = metrics.NewCounter(`vmagent_http_requests_total{path="/opentelemetry/v1/metrics", protocol="opentelemetry"}`)
+	opentelemetryPushErrors   = metrics.NewCounter(`vmagent_http_request_errors_total{path="/opentelemetry/v1/metrics", protocol="opentelemetry"}`)
 
 	newrelicWriteRequests = metrics.NewCounter(`vm_http_requests_total{path="/newrelic/infra/v2/metrics/events/bulk", protocol="newrelic"}`)
 	newrelicWriteErrors   = metrics.NewCounter(`vm_http_request_errors_total{path="/newrelic/infra/v2/metrics/events/bulk", protocol="newrelic"}`)

app/vmagent/opentelemetry/request_handler.go

@@ -9,6 +9,7 @@ import (
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/auth"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
 	parserCommon "github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/common"
+	"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/firehose"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/stream"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/tenantmetrics"
 	"github.com/VictoriaMetrics/metrics"
@@ -27,10 +28,15 @@ func InsertHandler(at *auth.Token, req *http.Request) error {
 		return err
 	}
 	isGzipped := req.Header.Get("Content-Encoding") == "gzip"
+	var processBody func([]byte) ([]byte, error)
 	if req.Header.Get("Content-Type") == "application/json" {
-		return fmt.Errorf("json encoding isn't supported for opentelemetry format. Use protobuf encoding")
+		if req.Header.Get("X-Amz-Firehouse-Protocol-Version") != "" {
+			processBody = firehose.ProcessRequestBody
+		} else {
+			return fmt.Errorf("json encoding isn't supported for opentelemetry format. Use protobuf encoding")
+		}
 	}
-	return stream.ParseStream(req.Body, isGzipped, func(tss []prompbmarshal.TimeSeries) error {
+	return stream.ParseStream(req.Body, isGzipped, processBody, func(tss []prompbmarshal.TimeSeries) error {
 		return insertRows(at, tss, extraLabels)
 	})
 }

app/vmagent/remotewrite/pendingseries.go

@@ -82,7 +82,7 @@ func (ps *pendingSeries) periodicFlusher() {
 			ps.mu.Unlock()
 			return
 		case <-ticker.C:
-			if fasttime.UnixTimestamp()-atomic.LoadUint64(&ps.wr.lastFlushTime) < uint64(flushSeconds) {
+			if fasttime.UnixTimestamp()-ps.wr.lastFlushTime.Load() < uint64(flushSeconds) {
 				continue
 			}
 		}
@@ -93,8 +93,7 @@ func (ps *pendingSeries) periodicFlusher() {
 }
 
 type writeRequest struct {
-	// Move lastFlushTime to the top of the struct in order to guarantee atomic access on 32-bit architectures.
-	lastFlushTime uint64
+	lastFlushTime atomic.Uint64
 
 	// The queue to send blocks to.
 	fq *persistentqueue.FastQueue
@@ -155,7 +154,7 @@ func (wr *writeRequest) mustWriteBlock(block []byte) bool {
 
 func (wr *writeRequest) tryFlush() bool {
 	wr.wr.Timeseries = wr.tss
-	atomic.StoreUint64(&wr.lastFlushTime, fasttime.UnixTimestamp())
+	wr.lastFlushTime.Store(fasttime.UnixTimestamp())
 	if !tryPushWriteRequest(&wr.wr, wr.fq.TryWriteBlock, wr.isVMRemoteWrite) {
 		return false
 	}

app/vmagent/remotewrite/remotewrite.go

@@ -536,22 +536,22 @@ func tryPushBlockToRemoteStorages(rwctxs []*remoteWriteCtx, tssBlock []prompbmar
 		// Push sharded data to remote storages in parallel in order to reduce
 		// the time needed for sending the data to multiple remote storage systems.
 		var wg sync.WaitGroup
-		wg.Add(len(rwctxs))
-		var anyPushFailed uint64
+		var anyPushFailed atomic.Bool
 		for i, rwctx := range rwctxs {
 			tssShard := tssByURL[i]
 			if len(tssShard) == 0 {
 				continue
 			}
+			wg.Add(1)
 			go func(rwctx *remoteWriteCtx, tss []prompbmarshal.TimeSeries) {
 				defer wg.Done()
 				if !rwctx.TryPush(tss) {
-					atomic.StoreUint64(&anyPushFailed, 1)
+					anyPushFailed.Store(true)
 				}
 			}(rwctx, tssShard)
 		}
 		wg.Wait()
-		return atomic.LoadUint64(&anyPushFailed) == 0
+		return !anyPushFailed.Load()
 	}
 
 	// Replicate data among rwctxs.
@@ -559,17 +559,17 @@ func tryPushBlockToRemoteStorages(rwctxs []*remoteWriteCtx, tssBlock []prompbmar
 	// the time needed for sending the data to multiple remote storage systems.
 	var wg sync.WaitGroup
 	wg.Add(len(rwctxs))
-	var anyPushFailed uint64
+	var anyPushFailed atomic.Bool
 	for _, rwctx := range rwctxs {
 		go func(rwctx *remoteWriteCtx) {
 			defer wg.Done()
 			if !rwctx.TryPush(tssBlock) {
-				atomic.StoreUint64(&anyPushFailed, 1)
+				anyPushFailed.Store(true)
 			}
 		}(rwctx)
 	}
 	wg.Wait()
-	return atomic.LoadUint64(&anyPushFailed) == 0
+	return !anyPushFailed.Load()
 }
 
 // sortLabelsIfNeeded sorts labels if -sortLabels command-line flag is set.
@@ -670,7 +670,7 @@ type remoteWriteCtx struct {
 	streamAggrDropInput bool
 
 	pss        []*pendingSeries
-	pssNextIdx uint64
+	pssNextIdx atomic.Uint64
 
 	rowsPushedAfterRelabel *metrics.Counter
 	rowsDroppedByRelabel   *metrics.Counter
@@ -872,7 +872,7 @@ func (rwctx *remoteWriteCtx) tryPushInternal(tss []prompbmarshal.TimeSeries) boo
 	}
 
 	pss := rwctx.pss
-	idx := atomic.AddUint64(&rwctx.pssNextIdx, 1) % uint64(len(pss))
+	idx := rwctx.pssNextIdx.Add(1) % uint64(len(pss))
 
 	ok := pss[idx].TryPush(tss)
 

app/vmagent/remotewrite/statconn.go

@@ -50,7 +50,7 @@ var (
 )
 
 type statConn struct {
-	closed uint64
+	closed atomic.Int32
 	net.Conn
 }
 
@@ -76,7 +76,7 @@ func (sc *statConn) Write(p []byte) (int, error) {
 
 func (sc *statConn) Close() error {
 	err := sc.Conn.Close()
-	if atomic.AddUint64(&sc.closed, 1) == 1 {
+	if sc.closed.Add(1) == 1 {
 		conns.Dec()
 	}
 	return err

app/vmalert/datasource/vm.go

@@ -137,11 +137,11 @@ func NewVMStorage(baseURL string, authCfg *promauth.Config, lookBack time.Durati
 
 // Query executes the given query and returns parsed response
 func (s *VMStorage) Query(ctx context.Context, query string, ts time.Time) (Result, *http.Request, error) {
-	req, err := s.newQueryRequest(query, ts)
+	req, err := s.newQueryRequest(ctx, query, ts)
 	if err != nil {
 		return Result{}, nil, err
 	}
-	resp, err := s.do(ctx, req)
+	resp, err := s.do(req)
 	if err != nil {
 		if !errors.Is(err, io.EOF) && !errors.Is(err, io.ErrUnexpectedEOF) {
 			// Return unexpected error to the caller.
@@ -149,11 +149,11 @@ func (s *VMStorage) Query(ctx context.Context, query string, ts time.Time) (Resu
 		}
 		// Something in the middle between client and datasource might be closing
 		// the connection. So we do a one more attempt in hope request will succeed.
-		req, err = s.newQueryRequest(query, ts)
+		req, err = s.newQueryRequest(ctx, query, ts)
 		if err != nil {
 			return Result{}, nil, fmt.Errorf("second attempt: %w", err)
 		}
-		resp, err = s.do(ctx, req)
+		resp, err = s.do(req)
 		if err != nil {
 			return Result{}, nil, fmt.Errorf("second attempt: %w", err)
 		}
@@ -182,11 +182,11 @@ func (s *VMStorage) QueryRange(ctx context.Context, query string, start, end tim
 	if end.IsZero() {
 		return res, fmt.Errorf("end param is missing")
 	}
-	req, err := s.newQueryRangeRequest(query, start, end)
+	req, err := s.newQueryRangeRequest(ctx, query, start, end)
 	if err != nil {
 		return res, err
 	}
-	resp, err := s.do(ctx, req)
+	resp, err := s.do(req)
 	if err != nil {
 		if !errors.Is(err, io.EOF) && !errors.Is(err, io.ErrUnexpectedEOF) {
 			// Return unexpected error to the caller.
@@ -194,11 +194,11 @@ func (s *VMStorage) QueryRange(ctx context.Context, query string, start, end tim
 		}
 		// Something in the middle between client and datasource might be closing
 		// the connection. So we do a one more attempt in hope request will succeed.
-		req, err = s.newQueryRangeRequest(query, start, end)
+		req, err = s.newQueryRangeRequest(ctx, query, start, end)
 		if err != nil {
 			return res, fmt.Errorf("second attempt: %w", err)
 		}
-		resp, err = s.do(ctx, req)
+		resp, err = s.do(req)
 		if err != nil {
 			return res, fmt.Errorf("second attempt: %w", err)
 		}
@@ -210,7 +210,7 @@ func (s *VMStorage) QueryRange(ctx context.Context, query string, start, end tim
 	return res, err
 }
 
-func (s *VMStorage) do(ctx context.Context, req *http.Request) (*http.Response, error) {
+func (s *VMStorage) do(req *http.Request) (*http.Response, error) {
 	ru := req.URL.Redacted()
 	if *showDatasourceURL {
 		ru = req.URL.String()
@@ -218,7 +218,7 @@ func (s *VMStorage) do(ctx context.Context, req *http.Request) (*http.Response,
 	if s.debug {
 		logger.Infof("DEBUG datasource request: executing %s request with params %q", req.Method, ru)
 	}
-	resp, err := s.c.Do(req.WithContext(ctx))
+	resp, err := s.c.Do(req)
 	if err != nil {
 		return nil, fmt.Errorf("error getting response from %s: %w", ru, err)
 	}
@@ -230,8 +230,8 @@ func (s *VMStorage) do(ctx context.Context, req *http.Request) (*http.Response,
 	return resp, nil
 }
 
-func (s *VMStorage) newQueryRangeRequest(query string, start, end time.Time) (*http.Request, error) {
-	req, err := s.newRequest()
+func (s *VMStorage) newQueryRangeRequest(ctx context.Context, query string, start, end time.Time) (*http.Request, error) {
+	req, err := s.newRequest(ctx)
 	if err != nil {
 		return nil, fmt.Errorf("cannot create query_range request to datasource %q: %w", s.datasourceURL, err)
 	}
@@ -239,8 +239,8 @@ func (s *VMStorage) newQueryRangeRequest(query string, start, end time.Time) (*h
 	return req, nil
 }
 
-func (s *VMStorage) newQueryRequest(query string, ts time.Time) (*http.Request, error) {
-	req, err := s.newRequest()
+func (s *VMStorage) newQueryRequest(ctx context.Context, query string, ts time.Time) (*http.Request, error) {
+	req, err := s.newRequest(ctx)
 	if err != nil {
 		return nil, fmt.Errorf("cannot create query request to datasource %q: %w", s.datasourceURL, err)
 	}
@@ -255,8 +255,8 @@ func (s *VMStorage) newQueryRequest(query string, ts time.Time) (*http.Request,
 	return req, nil
 }
 
-func (s *VMStorage) newRequest() (*http.Request, error) {
-	req, err := http.NewRequest(http.MethodPost, s.datasourceURL, nil)
+func (s *VMStorage) newRequest(ctx context.Context) (*http.Request, error) {
+	req, err := http.NewRequestWithContext(ctx, http.MethodPost, s.datasourceURL, nil)
 	if err != nil {
 		logger.Panicf("BUG: unexpected error from http.NewRequest(%q): %s", s.datasourceURL, err)
 	}

app/vmalert/datasource/vm_test.go

@@ -637,7 +637,7 @@ func TestRequestParams(t *testing.T) {
 
 	for _, tc := range testCases {
 		t.Run(tc.name, func(t *testing.T) {
-			req, err := tc.vm.newRequest()
+			req, err := tc.vm.newRequest(ctx)
 			if err != nil {
 				t.Fatal(err)
 			}
@@ -735,7 +735,7 @@ func TestHeaders(t *testing.T) {
 	for _, tt := range testCases {
 		t.Run(tt.name, func(t *testing.T) {
 			vm := tt.vmFn()
-			req, err := vm.newQueryRequest("foo", time.Now())
+			req, err := vm.newQueryRequest(ctx, "foo", time.Now())
 			if err != nil {
 				t.Fatal(err)
 			}

app/vmalert/remotewrite/client.go

@@ -279,7 +279,7 @@ L:
 
 func (c *Client) send(ctx context.Context, data []byte) error {
 	r := bytes.NewReader(data)
-	req, err := http.NewRequest(http.MethodPost, c.addr, r)
+	req, err := http.NewRequestWithContext(ctx, http.MethodPost, c.addr, r)
 	if err != nil {
 		return fmt.Errorf("failed to create new HTTP request: %w", err)
 	}
@@ -302,7 +302,7 @@ func (c *Client) send(ctx context.Context, data []byte) error {
 	if !*disablePathAppend {
 		req.URL.Path = path.Join(req.URL.Path, "/api/v1/write")
 	}
-	resp, err := c.c.Do(req.WithContext(ctx))
+	resp, err := c.c.Do(req)
 	if err != nil {
 		return fmt.Errorf("error while sending request to %s: %w; Data len %d(%d)",
 			req.URL.Redacted(), err, len(data), r.Size())

app/vmalert/remotewrite/client_test.go

@@ -91,14 +91,12 @@ func newRWServer() *rwServer {
 }
 
 type rwServer struct {
-	// WARN: ordering of fields is important for alignment!
-	// see https://golang.org/pkg/sync/atomic/#pkg-note-BUG
-	acceptedRows uint64
+	acceptedRows atomic.Uint64
 	*httptest.Server
 }
 
 func (rw *rwServer) accepted() int {
-	return int(atomic.LoadUint64(&rw.acceptedRows))
+	return int(rw.acceptedRows.Load())
 }
 
 func (rw *rwServer) err(w http.ResponseWriter, err error) {
@@ -144,7 +142,7 @@ func (rw *rwServer) handler(w http.ResponseWriter, r *http.Request) {
 		rw.err(w, fmt.Errorf("unmarhsal err: %w", err))
 		return
 	}
-	atomic.AddUint64(&rw.acceptedRows, uint64(len(wr.Timeseries)))
+	rw.acceptedRows.Add(uint64(len(wr.Timeseries)))
 	w.WriteHeader(http.StatusNoContent)
 }
 

app/vmauth/auth_config.go

@@ -164,7 +164,7 @@ type Regex struct {
 
 // URLPrefix represents passed `url_prefix`
 type URLPrefix struct {
-	n uint32
+	n atomic.Uint32
 
 	// the list of backend urls
 	bus []*backendURL
@@ -192,27 +192,28 @@ func (up *URLPrefix) setLoadBalancingPolicy(loadBalancingPolicy string) error {
 }
 
 type backendURL struct {
-	brokenDeadline     uint64
-	concurrentRequests int32
-	url                *url.URL
+	brokenDeadline     atomic.Uint64
+	concurrentRequests atomic.Int32
+
+	url *url.URL
 }
 
 func (bu *backendURL) isBroken() bool {
 	ct := fasttime.UnixTimestamp()
-	return ct < atomic.LoadUint64(&bu.brokenDeadline)
+	return ct < bu.brokenDeadline.Load()
 }
 
 func (bu *backendURL) setBroken() {
 	deadline := fasttime.UnixTimestamp() + uint64((*failTimeout).Seconds())
-	atomic.StoreUint64(&bu.brokenDeadline, deadline)
+	bu.brokenDeadline.Store(deadline)
 }
 
 func (bu *backendURL) get() {
-	atomic.AddInt32(&bu.concurrentRequests, 1)
+	bu.concurrentRequests.Add(1)
 }
 
 func (bu *backendURL) put() {
-	atomic.AddInt32(&bu.concurrentRequests, -1)
+	bu.concurrentRequests.Add(-1)
 }
 
 func (up *URLPrefix) getBackendsCount() int {
@@ -266,7 +267,7 @@ func (up *URLPrefix) getLeastLoadedBackendURL() *backendURL {
 	}
 
 	// Slow path - select other backend urls.
-	n := atomic.AddUint32(&up.n, 1)
+	n := up.n.Add(1)
 
 	for i := uint32(0); i < uint32(len(bus)); i++ {
 		idx := (n + i) % uint32(len(bus))
@@ -274,22 +275,22 @@ func (up *URLPrefix) getLeastLoadedBackendURL() *backendURL {
 		if bu.isBroken() {
 			continue
 		}
-		if atomic.LoadInt32(&bu.concurrentRequests) == 0 {
+		if bu.concurrentRequests.Load() == 0 {
 			// Fast path - return the backend with zero concurrently executed requests.
-			// Do not use atomic.CompareAndSwapInt32(), since it is much slower on systems with many CPU cores.
-			atomic.AddInt32(&bu.concurrentRequests, 1)
+			// Do not use CompareAndSwap() instead of Load(), since it is much slower on systems with many CPU cores.
+			bu.concurrentRequests.Add(1)
 			return bu
 		}
 	}
 
 	// Slow path - return the backend with the minimum number of concurrently executed requests.
 	buMin := bus[n%uint32(len(bus))]
-	minRequests := atomic.LoadInt32(&buMin.concurrentRequests)
+	minRequests := buMin.concurrentRequests.Load()
 	for _, bu := range bus {
 		if bu.isBroken() {
 			continue
 		}
-		if n := atomic.LoadInt32(&bu.concurrentRequests); n < minRequests {
+		if n := bu.concurrentRequests.Load(); n < minRequests {
 			buMin = bu
 			minRequests = n
 		}

app/vmctl/main.go

@@ -330,14 +330,14 @@ func main() {
 					if err != nil {
 						return cli.Exit(fmt.Errorf("cannot open exported block at path=%q err=%w", blockPath, err), 1)
 					}
-					var blocksCount uint64
+					var blocksCount atomic.Uint64
 					if err := stream.Parse(f, isBlockGzipped, func(block *stream.Block) error {
-						atomic.AddUint64(&blocksCount, 1)
+						blocksCount.Add(1)
 						return nil
 					}); err != nil {
-						return cli.Exit(fmt.Errorf("cannot parse block at path=%q, blocksCount=%d, err=%w", blockPath, blocksCount, err), 1)
+						return cli.Exit(fmt.Errorf("cannot parse block at path=%q, blocksCount=%d, err=%w", blockPath, blocksCount.Load(), err), 1)
 					}
-					log.Printf("successfully verified block at path=%q, blockCount=%d", blockPath, blocksCount)
+					log.Printf("successfully verified block at path=%q, blockCount=%d", blockPath, blocksCount.Load())
 					return nil
 				},
 			},

app/vmctl/remoteread/remoteread.go

@@ -182,7 +182,7 @@ func (c *Client) fetch(ctx context.Context, data []byte, streamCb StreamCallback
 	if c.disablePathAppend {
 		u = c.addr
 	}
-	req, err := http.NewRequest(http.MethodPost, u, r)
+	req, err := http.NewRequestWithContext(ctx, http.MethodPost, u, r)
 	if err != nil {
 		return fmt.Errorf("failed to create new HTTP request: %w", err)
 	}
@@ -195,7 +195,7 @@ func (c *Client) fetch(ctx context.Context, data []byte, streamCb StreamCallback
 	}
 	req.Header.Set("X-Prometheus-Remote-Read-Version", "0.1.0")
 
-	resp, err := c.do(req.WithContext(ctx))
+	resp, err := c.do(req)
 	if err != nil {
 		return fmt.Errorf("error while sending request to %s: %w; Data len %d(%d)",
 			req.URL.Redacted(), err, len(data), r.Size())

app/vmctl/time.go

@@ -14,11 +14,10 @@ const (
 )
 
 func parseTime(s string) (time.Time, error) {
-	secs, err := promutils.ParseTime(s)
+	msecs, err := promutils.ParseTimeMsec(s)
 	if err != nil {
 		return time.Time{}, fmt.Errorf("cannot parse %s: %w", s, err)
 	}
-	msecs := int64(secs * 1e3)
 	if msecs < minTimeMsecs {
 		msecs = 0
 	}

app/vminsert/main.go

@@ -6,7 +6,6 @@ import (
 	"fmt"
 	"net/http"
 	"strings"
-	"sync/atomic"
 	"time"
 
 	"github.com/VictoriaMetrics/metrics"
@@ -217,7 +216,7 @@ func RequestHandler(w http.ResponseWriter, r *http.Request) bool {
 		addInfluxResponseHeaders(w)
 		influxutils.WriteDatabaseNames(w)
 		return true
-	case "/opentelemetry/api/v1/push":
+	case "/opentelemetry/api/v1/push", "/opentelemetry/v1/metrics":
 		opentelemetryPushRequests.Inc()
 		if err := opentelemetry.InsertHandler(r); err != nil {
 			opentelemetryPushErrors.Inc()
@@ -354,7 +353,7 @@ func RequestHandler(w http.ResponseWriter, r *http.Request) bool {
 		w.WriteHeader(http.StatusOK)
 		return true
 	case "/ready":
-		if rdy := atomic.LoadInt32(&promscrape.PendingScrapeConfigs); rdy > 0 {
+		if rdy := promscrape.PendingScrapeConfigs.Load(); rdy > 0 {
 			errMsg := fmt.Sprintf("waiting for scrape config to init targets, configs left: %d", rdy)
 			http.Error(w, errMsg, http.StatusTooEarly)
 		} else {
@@ -412,8 +411,8 @@ var (
 	datadogIntakeRequests   = metrics.NewCounter(`vm_http_requests_total{path="/datadog/intake", protocol="datadog"}`)
 	datadogMetadataRequests = metrics.NewCounter(`vm_http_requests_total{path="/datadog/api/v1/metadata", protocol="datadog"}`)
 
-	opentelemetryPushRequests = metrics.NewCounter(`vm_http_requests_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
-	opentelemetryPushErrors   = metrics.NewCounter(`vm_http_request_errors_total{path="/opentelemetry/api/v1/push", protocol="opentelemetry"}`)
+	opentelemetryPushRequests = metrics.NewCounter(`vm_http_requests_total{path="/opentelemetry/v1/metrics", protocol="opentelemetry"}`)
+	opentelemetryPushErrors   = metrics.NewCounter(`vm_http_request_errors_total{path="/opentelemetry/v1/metrics", protocol="opentelemetry"}`)
 
 	newrelicWriteRequests = metrics.NewCounter(`vm_http_requests_total{path="/newrelic/infra/v2/metrics/events/bulk", protocol="newrelic"}`)
 	newrelicWriteErrors   = metrics.NewCounter(`vm_http_request_errors_total{path="/newrelic/infra/v2/metrics/events/bulk", protocol="newrelic"}`)
@@ -435,12 +434,12 @@ var (
 	promscrapeConfigReloadRequests = metrics.NewCounter(`vm_http_requests_total{path="/-/reload"}`)
 
 	_ = metrics.NewGauge(`vm_metrics_with_dropped_labels_total`, func() float64 {
-		return float64(atomic.LoadUint64(&storage.MetricsWithDroppedLabels))
+		return float64(storage.MetricsWithDroppedLabels.Load())
 	})
 	_ = metrics.NewGauge(`vm_too_long_label_names_total`, func() float64 {
-		return float64(atomic.LoadUint64(&storage.TooLongLabelNames))
+		return float64(storage.TooLongLabelNames.Load())
 	})
 	_ = metrics.NewGauge(`vm_too_long_label_values_total`, func() float64 {
-		return float64(atomic.LoadUint64(&storage.TooLongLabelValues))
+		return float64(storage.TooLongLabelValues.Load())
 	})
 )

app/vminsert/opentelemetry/request_handler.go

@@ -8,6 +8,7 @@ import (
 	"github.com/VictoriaMetrics/VictoriaMetrics/app/vminsert/relabel"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
 	parserCommon "github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/common"
+	"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/firehose"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/protoparser/opentelemetry/stream"
 	"github.com/VictoriaMetrics/metrics"
 )
@@ -24,10 +25,15 @@ func InsertHandler(req *http.Request) error {
 		return err
 	}
 	isGzipped := req.Header.Get("Content-Encoding") == "gzip"
+	var processBody func([]byte) ([]byte, error)
 	if req.Header.Get("Content-Type") == "application/json" {
-		return fmt.Errorf("json encoding isn't supported for opentelemetry format. Use protobuf encoding")
+		if req.Header.Get("X-Amz-Firehose-Protocol-Version") != "" {
+			processBody = firehose.ProcessRequestBody
+		} else {
+			return fmt.Errorf("json encoding isn't supported for opentelemetry format. Use protobuf encoding")
+		}
 	}
-	return stream.ParseStream(req.Body, isGzipped, func(tss []prompbmarshal.TimeSeries) error {
+	return stream.ParseStream(req.Body, isGzipped, processBody, func(tss []prompbmarshal.TimeSeries) error {
 		return insertRows(tss, extraLabels)
 	})
 }

app/vmselect/graphite/transform.go

@@ -3842,18 +3842,18 @@ func nextSeriesConcurrentWrapper(nextSeries nextSeriesFunc, f func(s *series) (*
 		errCh <- err
 		close(errCh)
 	}()
-	var skipProcessing uint32
+	var skipProcessing atomic.Bool
 	for i := 0; i < goroutines; i++ {
 		go func() {
 			defer wg.Done()
 			for s := range seriesCh {
-				if atomic.LoadUint32(&skipProcessing) != 0 {
+				if skipProcessing.Load() {
 					continue
 				}
 				sNew, err := f(s)
 				if err != nil {
 					// Drain the rest of series and do not call f for them in order to conserve CPU time.
-					atomic.StoreUint32(&skipProcessing, 1)
+					skipProcessing.Store(true)
 					resultCh <- &result{
 						err: err,
 					}
@@ -5609,9 +5609,9 @@ func (nsf *nextSeriesFunc) peekStep(step int64) (int64, error) {
 	if s != nil {
 		step = s.step
 	}
-	calls := uint64(0)
+	var calls atomic.Uint64
 	*nsf = func() (*series, error) {
-		if atomic.AddUint64(&calls, 1) == 1 {
+		if calls.Add(1) == 1 {
 			return s, nil
 		}
 		return nextSeries()

app/vmselect/netstorage/netstorage.go

@@ -5,7 +5,6 @@ import (
 	"errors"
 	"flag"
 	"fmt"
-	"reflect"
 	"sort"
 	"sync"
 	"sync/atomic"
@@ -24,11 +23,14 @@ import (
 )
 
 var (
-	maxTagKeysPerSearch   = flag.Int("search.maxTagKeys", 100e3, "The maximum number of tag keys returned from /api/v1/labels")
-	maxTagValuesPerSearch = flag.Int("search.maxTagValues", 100e3, "The maximum number of tag values returned from /api/v1/label/<label_name>/values")
-	maxSamplesPerSeries   = flag.Int("search.maxSamplesPerSeries", 30e6, "The maximum number of raw samples a single query can scan per each time series. This option allows limiting memory usage")
-	maxSamplesPerQuery    = flag.Int("search.maxSamplesPerQuery", 1e9, "The maximum number of raw samples a single query can process across all time series. This protects from heavy queries, which select unexpectedly high number of raw samples. See also -search.maxSamplesPerSeries")
-	maxWorkersPerQuery    = flag.Int("search.maxWorkersPerQuery", defaultMaxWorkersPerQuery, "The maximum number of CPU cores a single query can use. "+
+	maxTagKeysPerSearch = flag.Int("search.maxTagKeys", 100e3, "The maximum number of tag keys returned from /api/v1/labels . "+
+		"See also -search.maxLabelsAPISeries and -search.maxLabelsAPIDuration")
+	maxTagValuesPerSearch = flag.Int("search.maxTagValues", 100e3, "The maximum number of tag values returned from /api/v1/label/<label_name>/values . "+
+		"See also -search.maxLabelsAPISeries and -search.maxLabelsAPIDuration")
+	maxSamplesPerSeries = flag.Int("search.maxSamplesPerSeries", 30e6, "The maximum number of raw samples a single query can scan per each time series. This option allows limiting memory usage")
+	maxSamplesPerQuery  = flag.Int("search.maxSamplesPerQuery", 1e9, "The maximum number of raw samples a single query can process across all time series. "+
+		"This protects from heavy queries, which select unexpectedly high number of raw samples. See also -search.maxSamplesPerSeries")
+	maxWorkersPerQuery = flag.Int("search.maxWorkersPerQuery", defaultMaxWorkersPerQuery, "The maximum number of CPU cores a single query can use. "+
 		"The default value should work good for most cases. "+
 		"The flag can be set to lower values for improving performance of big number of concurrently executed queries. "+
 		"The flag can be set to bigger values for improving performance of heavy queries, which scan big number of time series (>10K) and/or big number of samples (>100M). "+
@@ -81,7 +83,7 @@ func (rss *Results) mustClose() {
 }
 
 type timeseriesWork struct {
-	mustStop *uint32
+	mustStop *atomic.Bool
 	rss      *Results
 	pts      *packedTimeseries
 	f        func(rs *Result, workerID uint) error
@@ -91,22 +93,22 @@ type timeseriesWork struct {
 }
 
 func (tsw *timeseriesWork) do(r *Result, workerID uint) error {
-	if atomic.LoadUint32(tsw.mustStop) != 0 {
+	if tsw.mustStop.Load() {
 		return nil
 	}
 	rss := tsw.rss
 	if rss.deadline.Exceeded() {
-		atomic.StoreUint32(tsw.mustStop, 1)
+		tsw.mustStop.Store(true)
 		return fmt.Errorf("timeout exceeded during query execution: %s", rss.deadline.String())
 	}
 	if err := tsw.pts.Unpack(r, rss.tbf, rss.tr); err != nil {
-		atomic.StoreUint32(tsw.mustStop, 1)
+		tsw.mustStop.Store(true)
 		return fmt.Errorf("error during time series unpacking: %w", err)
 	}
 	tsw.rowsProcessed = len(r.Timestamps)
 	if len(r.Timestamps) > 0 {
 		if err := tsw.f(r, workerID); err != nil {
-			atomic.StoreUint32(tsw.mustStop, 1)
+			tsw.mustStop.Store(true)
 			return err
 		}
 	}
@@ -238,7 +240,7 @@ func (rss *Results) runParallel(qt *querytracer.Tracer, f func(rs *Result, worke
 		return 0, nil
 	}
 
-	var mustStop uint32
+	var mustStop atomic.Bool
 	initTimeseriesWork := func(tsw *timeseriesWork, pts *packedTimeseries) {
 		tsw.rss = rss
 		tsw.pts = pts
@@ -1008,7 +1010,7 @@ func ExportBlocks(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline sear
 	var (
 		errGlobal     error
 		errGlobalLock sync.Mutex
-		mustStop      uint32
+		mustStop      atomic.Bool
 	)
 	var wg sync.WaitGroup
 	wg.Add(gomaxprocs)
@@ -1020,7 +1022,7 @@ func ExportBlocks(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline sear
 					errGlobalLock.Lock()
 					if errGlobal == nil {
 						errGlobal = err
-						atomic.StoreUint32(&mustStop, 1)
+						mustStop.Store(true)
 					}
 					errGlobalLock.Unlock()
 				}
@@ -1038,7 +1040,7 @@ func ExportBlocks(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline sear
 		if deadline.Exceeded() {
 			return fmt.Errorf("timeout exceeded while fetching data block #%d from storage: %s", blocksRead, deadline.String())
 		}
-		if atomic.LoadUint32(&mustStop) != 0 {
+		if mustStop.Load() {
 			break
 		}
 		xw := exportWorkPool.Get().(*exportWork)
@@ -1309,9 +1311,11 @@ func canAppendToBlockRefPool(pool, a []blockRef) bool {
 		// a doesn't belong to pool
 		return false
 	}
-	shPool := (*reflect.SliceHeader)(unsafe.Pointer(&pool))
-	shA := (*reflect.SliceHeader)(unsafe.Pointer(&a))
-	return shPool.Data+uintptr(shPool.Len)*unsafe.Sizeof(blockRef{}) == shA.Data+uintptr(shA.Len)*unsafe.Sizeof(blockRef{})
+	return getBlockRefsEnd(pool) == getBlockRefsEnd(a)
+}
+
+func getBlockRefsEnd(a []blockRef) uintptr {
+	return uintptr(unsafe.Pointer(unsafe.SliceData(a))) + uintptr(len(a))*unsafe.Sizeof(blockRef{})
 }
 
 func setupTfss(qt *querytracer.Tracer, tr storage.TimeRange, tagFilterss [][]storage.TagFilter, maxMetrics int, deadline searchutils.Deadline) ([]*storage.TagFilters, error) {

app/vmselect/prometheus/export.qtpl

@@ -24,6 +24,7 @@
 	{% endfor %}
 {% endfunc %}
 
+{%code const rfc3339Milli = "2006-01-02T15:04:05.999Z07:00" %}
 {% func exportCSVField(mn *storage.MetricName, fieldName string, timestamp int64, value float64) %}
 	{% if fieldName == "__value__" %}
 		{%f= value %}
@@ -45,7 +46,7 @@
 		{% case "rfc3339" %}
 			{% code
 				bb := quicktemplate.AcquireByteBuffer()
-				bb.B = time.Unix(timestamp/1000, (timestamp%1000)*1e6).AppendFormat(bb.B[:0], time.RFC3339)
+				bb.B = time.Unix(timestamp/1000, (timestamp%1000)*1e6).AppendFormat(bb.B[:0], rfc3339Milli)
 			%}
 			{%z= bb.B %}
 			{% code

app/vmselect/prometheus/export.qtpl.go

@@ -87,586 +87,589 @@ func ExportCSVLine(xb *exportBlock, fieldNames []string) string {
 }
 
 //line app/vmselect/prometheus/export.qtpl:27
-func streamexportCSVField(qw422016 *qt422016.Writer, mn *storage.MetricName, fieldName string, timestamp int64, value float64) {
+const rfc3339Milli = "2006-01-02T15:04:05.999Z07:00"
+
 //line app/vmselect/prometheus/export.qtpl:28
-	if fieldName == "__value__" {
+func streamexportCSVField(qw422016 *qt422016.Writer, mn *storage.MetricName, fieldName string, timestamp int64, value float64) {
 //line app/vmselect/prometheus/export.qtpl:29
-		qw422016.N().F(value)
+	if fieldName == "__value__" {
 //line app/vmselect/prometheus/export.qtpl:30
-		return
+		qw422016.N().F(value)
 //line app/vmselect/prometheus/export.qtpl:31
-	}
-//line app/vmselect/prometheus/export.qtpl:32
-	if fieldName == "__timestamp__" {
-//line app/vmselect/prometheus/export.qtpl:33
-		qw422016.N().DL(timestamp)
-//line app/vmselect/prometheus/export.qtpl:34
 		return
-//line app/vmselect/prometheus/export.qtpl:35
+//line app/vmselect/prometheus/export.qtpl:32
 	}
+//line app/vmselect/prometheus/export.qtpl:33
+	if fieldName == "__timestamp__" {
+//line app/vmselect/prometheus/export.qtpl:34
+		qw422016.N().DL(timestamp)
+//line app/vmselect/prometheus/export.qtpl:35
+		return
 //line app/vmselect/prometheus/export.qtpl:36
-	if strings.HasPrefix(fieldName, "__timestamp__:") {
+	}
 //line app/vmselect/prometheus/export.qtpl:37
+	if strings.HasPrefix(fieldName, "__timestamp__:") {
+//line app/vmselect/prometheus/export.qtpl:38
 		timeFormat := fieldName[len("__timestamp__:"):]
 
-//line app/vmselect/prometheus/export.qtpl:38
-		switch timeFormat {
 //line app/vmselect/prometheus/export.qtpl:39
-		case "unix_s":
+		switch timeFormat {
 //line app/vmselect/prometheus/export.qtpl:40
-			qw422016.N().DL(timestamp / 1000)
+		case "unix_s":
 //line app/vmselect/prometheus/export.qtpl:41
-		case "unix_ms":
+			qw422016.N().DL(timestamp / 1000)
 //line app/vmselect/prometheus/export.qtpl:42
-			qw422016.N().DL(timestamp)
+		case "unix_ms":
 //line app/vmselect/prometheus/export.qtpl:43
-		case "unix_ns":
+			qw422016.N().DL(timestamp)
 //line app/vmselect/prometheus/export.qtpl:44
-			qw422016.N().DL(timestamp * 1e6)
+		case "unix_ns":
 //line app/vmselect/prometheus/export.qtpl:45
+			qw422016.N().DL(timestamp * 1e6)
+//line app/vmselect/prometheus/export.qtpl:46
 		case "rfc3339":
-//line app/vmselect/prometheus/export.qtpl:47
+//line app/vmselect/prometheus/export.qtpl:48
 			bb := quicktemplate.AcquireByteBuffer()
-			bb.B = time.Unix(timestamp/1000, (timestamp%1000)*1e6).AppendFormat(bb.B[:0], time.RFC3339)
+			bb.B = time.Unix(timestamp/1000, (timestamp%1000)*1e6).AppendFormat(bb.B[:0], rfc3339Milli)
 
-//line app/vmselect/prometheus/export.qtpl:50
+//line app/vmselect/prometheus/export.qtpl:51
 			qw422016.N().Z(bb.B)
-//line app/vmselect/prometheus/export.qtpl:52
+//line app/vmselect/prometheus/export.qtpl:53
 			quicktemplate.ReleaseByteBuffer(bb)
 
-//line app/vmselect/prometheus/export.qtpl:54
-		default:
 //line app/vmselect/prometheus/export.qtpl:55
+		default:
+//line app/vmselect/prometheus/export.qtpl:56
 			if strings.HasPrefix(timeFormat, "custom:") {
-//line app/vmselect/prometheus/export.qtpl:57
+//line app/vmselect/prometheus/export.qtpl:58
 				layout := timeFormat[len("custom:"):]
 				bb := quicktemplate.AcquireByteBuffer()
 				bb.B = time.Unix(timestamp/1000, (timestamp%1000)*1e6).AppendFormat(bb.B[:0], layout)
 
-//line app/vmselect/prometheus/export.qtpl:61
-				if bytes.ContainsAny(bb.B, `"`+",\n") {
 //line app/vmselect/prometheus/export.qtpl:62
-					qw422016.E().QZ(bb.B)
+				if bytes.ContainsAny(bb.B, `"`+",\n") {
 //line app/vmselect/prometheus/export.qtpl:63
-				} else {
+					qw422016.E().QZ(bb.B)
 //line app/vmselect/prometheus/export.qtpl:64
-					qw422016.N().Z(bb.B)
+				} else {
 //line app/vmselect/prometheus/export.qtpl:65
+					qw422016.N().Z(bb.B)
+//line app/vmselect/prometheus/export.qtpl:66
 				}
-//line app/vmselect/prometheus/export.qtpl:67
+//line app/vmselect/prometheus/export.qtpl:68
 				quicktemplate.ReleaseByteBuffer(bb)
 
-//line app/vmselect/prometheus/export.qtpl:69
-			} else {
-//line app/vmselect/prometheus/export.qtpl:69
-				qw422016.N().S(`Unsupported timeFormat=`)
 //line app/vmselect/prometheus/export.qtpl:70
-				qw422016.N().S(timeFormat)
+			} else {
+//line app/vmselect/prometheus/export.qtpl:70
+				qw422016.N().S(`Unsupported timeFormat=`)
 //line app/vmselect/prometheus/export.qtpl:71
-			}
+				qw422016.N().S(timeFormat)
 //line app/vmselect/prometheus/export.qtpl:72
-		}
+			}
 //line app/vmselect/prometheus/export.qtpl:73
-		return
+		}
 //line app/vmselect/prometheus/export.qtpl:74
-	}
+		return
 //line app/vmselect/prometheus/export.qtpl:75
+	}
+//line app/vmselect/prometheus/export.qtpl:76
 	v := mn.GetTagValue(fieldName)
 
-//line app/vmselect/prometheus/export.qtpl:76
-	if bytes.ContainsAny(v, `"`+",\n") {
 //line app/vmselect/prometheus/export.qtpl:77
-		qw422016.N().QZ(v)
+	if bytes.ContainsAny(v, `"`+",\n") {
 //line app/vmselect/prometheus/export.qtpl:78
-	} else {
+		qw422016.N().QZ(v)
 //line app/vmselect/prometheus/export.qtpl:79
-		qw422016.N().Z(v)
+	} else {
 //line app/vmselect/prometheus/export.qtpl:80
-	}
+		qw422016.N().Z(v)
 //line app/vmselect/prometheus/export.qtpl:81
+	}
+//line app/vmselect/prometheus/export.qtpl:82
 }
 
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 func writeexportCSVField(qq422016 qtio422016.Writer, mn *storage.MetricName, fieldName string, timestamp int64, value float64) {
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	streamexportCSVField(qw422016, mn, fieldName, timestamp, value)
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 }
 
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 func exportCSVField(mn *storage.MetricName, fieldName string, timestamp int64, value float64) string {
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	writeexportCSVField(qb422016, mn, fieldName, timestamp, value)
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:81
+//line app/vmselect/prometheus/export.qtpl:82
 }
 
-//line app/vmselect/prometheus/export.qtpl:83
+//line app/vmselect/prometheus/export.qtpl:84
 func StreamExportPrometheusLine(qw422016 *qt422016.Writer, xb *exportBlock) {
-//line app/vmselect/prometheus/export.qtpl:84
-	if len(xb.timestamps) == 0 {
-//line app/vmselect/prometheus/export.qtpl:84
-		return
-//line app/vmselect/prometheus/export.qtpl:84
-	}
 //line app/vmselect/prometheus/export.qtpl:85
+	if len(xb.timestamps) == 0 {
+//line app/vmselect/prometheus/export.qtpl:85
+		return
+//line app/vmselect/prometheus/export.qtpl:85
+	}
+//line app/vmselect/prometheus/export.qtpl:86
 	bb := quicktemplate.AcquireByteBuffer()
 
-//line app/vmselect/prometheus/export.qtpl:86
+//line app/vmselect/prometheus/export.qtpl:87
 	writeprometheusMetricName(bb, xb.mn)
 
-//line app/vmselect/prometheus/export.qtpl:87
+//line app/vmselect/prometheus/export.qtpl:88
 	for i, ts := range xb.timestamps {
-//line app/vmselect/prometheus/export.qtpl:88
+//line app/vmselect/prometheus/export.qtpl:89
 		qw422016.N().Z(bb.B)
-//line app/vmselect/prometheus/export.qtpl:88
-		qw422016.N().S(` `)
 //line app/vmselect/prometheus/export.qtpl:89
+		qw422016.N().S(` `)
+//line app/vmselect/prometheus/export.qtpl:90
 		qw422016.N().F(xb.values[i])
-//line app/vmselect/prometheus/export.qtpl:89
+//line app/vmselect/prometheus/export.qtpl:90
 		qw422016.N().S(` `)
-//line app/vmselect/prometheus/export.qtpl:90
+//line app/vmselect/prometheus/export.qtpl:91
 		qw422016.N().DL(ts)
-//line app/vmselect/prometheus/export.qtpl:90
+//line app/vmselect/prometheus/export.qtpl:91
 		qw422016.N().S(`
 `)
-//line app/vmselect/prometheus/export.qtpl:91
-	}
 //line app/vmselect/prometheus/export.qtpl:92
+	}
+//line app/vmselect/prometheus/export.qtpl:93
 	quicktemplate.ReleaseByteBuffer(bb)
 
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 }
 
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 func WriteExportPrometheusLine(qq422016 qtio422016.Writer, xb *exportBlock) {
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	StreamExportPrometheusLine(qw422016, xb)
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 }
 
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 func ExportPrometheusLine(xb *exportBlock) string {
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	WriteExportPrometheusLine(qb422016, xb)
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:93
+//line app/vmselect/prometheus/export.qtpl:94
 }
 
-//line app/vmselect/prometheus/export.qtpl:95
+//line app/vmselect/prometheus/export.qtpl:96
 func StreamExportJSONLine(qw422016 *qt422016.Writer, xb *exportBlock) {
-//line app/vmselect/prometheus/export.qtpl:96
+//line app/vmselect/prometheus/export.qtpl:97
 	if len(xb.timestamps) == 0 {
-//line app/vmselect/prometheus/export.qtpl:96
+//line app/vmselect/prometheus/export.qtpl:97
 		return
-//line app/vmselect/prometheus/export.qtpl:96
+//line app/vmselect/prometheus/export.qtpl:97
 	}
-//line app/vmselect/prometheus/export.qtpl:96
+//line app/vmselect/prometheus/export.qtpl:97
 	qw422016.N().S(`{"metric":`)
-//line app/vmselect/prometheus/export.qtpl:98
+//line app/vmselect/prometheus/export.qtpl:99
 	streammetricNameObject(qw422016, xb.mn)
-//line app/vmselect/prometheus/export.qtpl:98
+//line app/vmselect/prometheus/export.qtpl:99
 	qw422016.N().S(`,"values":[`)
-//line app/vmselect/prometheus/export.qtpl:100
-	if len(xb.values) > 0 {
 //line app/vmselect/prometheus/export.qtpl:101
+	if len(xb.values) > 0 {
+//line app/vmselect/prometheus/export.qtpl:102
 		values := xb.values
 
-//line app/vmselect/prometheus/export.qtpl:102
-		streamconvertValueToSpecialJSON(qw422016, values[0])
 //line app/vmselect/prometheus/export.qtpl:103
+		streamconvertValueToSpecialJSON(qw422016, values[0])
+//line app/vmselect/prometheus/export.qtpl:104
 		values = values[1:]
 
-//line app/vmselect/prometheus/export.qtpl:104
-		for _, v := range values {
-//line app/vmselect/prometheus/export.qtpl:104
-			qw422016.N().S(`,`)
 //line app/vmselect/prometheus/export.qtpl:105
-			streamconvertValueToSpecialJSON(qw422016, v)
+		for _, v := range values {
+//line app/vmselect/prometheus/export.qtpl:105
+			qw422016.N().S(`,`)
 //line app/vmselect/prometheus/export.qtpl:106
+			streamconvertValueToSpecialJSON(qw422016, v)
+//line app/vmselect/prometheus/export.qtpl:107
 		}
-//line app/vmselect/prometheus/export.qtpl:107
+//line app/vmselect/prometheus/export.qtpl:108
 	}
-//line app/vmselect/prometheus/export.qtpl:107
+//line app/vmselect/prometheus/export.qtpl:108
 	qw422016.N().S(`],"timestamps":[`)
-//line app/vmselect/prometheus/export.qtpl:110
-	if len(xb.timestamps) > 0 {
 //line app/vmselect/prometheus/export.qtpl:111
+	if len(xb.timestamps) > 0 {
+//line app/vmselect/prometheus/export.qtpl:112
 		timestamps := xb.timestamps
 
-//line app/vmselect/prometheus/export.qtpl:112
-		qw422016.N().DL(timestamps[0])
 //line app/vmselect/prometheus/export.qtpl:113
+		qw422016.N().DL(timestamps[0])
+//line app/vmselect/prometheus/export.qtpl:114
 		timestamps = timestamps[1:]
 
-//line app/vmselect/prometheus/export.qtpl:114
-		for _, ts := range timestamps {
-//line app/vmselect/prometheus/export.qtpl:114
-			qw422016.N().S(`,`)
 //line app/vmselect/prometheus/export.qtpl:115
-			qw422016.N().DL(ts)
+		for _, ts := range timestamps {
+//line app/vmselect/prometheus/export.qtpl:115
+			qw422016.N().S(`,`)
 //line app/vmselect/prometheus/export.qtpl:116
+			qw422016.N().DL(ts)
+//line app/vmselect/prometheus/export.qtpl:117
 		}
-//line app/vmselect/prometheus/export.qtpl:117
+//line app/vmselect/prometheus/export.qtpl:118
 	}
-//line app/vmselect/prometheus/export.qtpl:117
+//line app/vmselect/prometheus/export.qtpl:118
 	qw422016.N().S(`]}`)
-//line app/vmselect/prometheus/export.qtpl:119
+//line app/vmselect/prometheus/export.qtpl:120
 	qw422016.N().S(`
 `)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 }
 
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 func WriteExportJSONLine(qq422016 qtio422016.Writer, xb *exportBlock) {
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	StreamExportJSONLine(qw422016, xb)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 }
 
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 func ExportJSONLine(xb *exportBlock) string {
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	WriteExportJSONLine(qb422016, xb)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:120
+//line app/vmselect/prometheus/export.qtpl:121
 }
 
-//line app/vmselect/prometheus/export.qtpl:122
+//line app/vmselect/prometheus/export.qtpl:123
 func StreamExportPromAPILine(qw422016 *qt422016.Writer, xb *exportBlock) {
-//line app/vmselect/prometheus/export.qtpl:122
+//line app/vmselect/prometheus/export.qtpl:123
 	qw422016.N().S(`{"metric":`)
-//line app/vmselect/prometheus/export.qtpl:124
+//line app/vmselect/prometheus/export.qtpl:125
 	streammetricNameObject(qw422016, xb.mn)
-//line app/vmselect/prometheus/export.qtpl:124
+//line app/vmselect/prometheus/export.qtpl:125
 	qw422016.N().S(`,"values":`)
-//line app/vmselect/prometheus/export.qtpl:125
+//line app/vmselect/prometheus/export.qtpl:126
 	streamvaluesWithTimestamps(qw422016, xb.values, xb.timestamps)
-//line app/vmselect/prometheus/export.qtpl:125
+//line app/vmselect/prometheus/export.qtpl:126
 	qw422016.N().S(`}`)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 }
 
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 func WriteExportPromAPILine(qq422016 qtio422016.Writer, xb *exportBlock) {
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	StreamExportPromAPILine(qw422016, xb)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 }
 
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 func ExportPromAPILine(xb *exportBlock) string {
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	WriteExportPromAPILine(qb422016, xb)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:127
+//line app/vmselect/prometheus/export.qtpl:128
 }
 
-//line app/vmselect/prometheus/export.qtpl:129
+//line app/vmselect/prometheus/export.qtpl:130
 func StreamExportPromAPIHeader(qw422016 *qt422016.Writer) {
-//line app/vmselect/prometheus/export.qtpl:129
+//line app/vmselect/prometheus/export.qtpl:130
 	qw422016.N().S(`{"status":"success","data":{"resultType":"matrix","result":[`)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 }
 
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 func WriteExportPromAPIHeader(qq422016 qtio422016.Writer) {
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	StreamExportPromAPIHeader(qw422016)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 }
 
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 func ExportPromAPIHeader() string {
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	WriteExportPromAPIHeader(qb422016)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:135
+//line app/vmselect/prometheus/export.qtpl:136
 }
 
-//line app/vmselect/prometheus/export.qtpl:137
+//line app/vmselect/prometheus/export.qtpl:138
 func StreamExportPromAPIFooter(qw422016 *qt422016.Writer, qt *querytracer.Tracer) {
-//line app/vmselect/prometheus/export.qtpl:137
+//line app/vmselect/prometheus/export.qtpl:138
 	qw422016.N().S(`]}`)
-//line app/vmselect/prometheus/export.qtpl:141
+//line app/vmselect/prometheus/export.qtpl:142
 	qt.Donef("export format=promapi")
 
-//line app/vmselect/prometheus/export.qtpl:143
+//line app/vmselect/prometheus/export.qtpl:144
 	streamdumpQueryTrace(qw422016, qt)
-//line app/vmselect/prometheus/export.qtpl:143
+//line app/vmselect/prometheus/export.qtpl:144
 	qw422016.N().S(`}`)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 }
 
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 func WriteExportPromAPIFooter(qq422016 qtio422016.Writer, qt *querytracer.Tracer) {
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	StreamExportPromAPIFooter(qw422016, qt)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 }
 
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 func ExportPromAPIFooter(qt *querytracer.Tracer) string {
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	WriteExportPromAPIFooter(qb422016, qt)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:145
+//line app/vmselect/prometheus/export.qtpl:146
 }
 
-//line app/vmselect/prometheus/export.qtpl:147
-func streamprometheusMetricName(qw422016 *qt422016.Writer, mn *storage.MetricName) {
 //line app/vmselect/prometheus/export.qtpl:148
+func streamprometheusMetricName(qw422016 *qt422016.Writer, mn *storage.MetricName) {
+//line app/vmselect/prometheus/export.qtpl:149
 	qw422016.N().Z(mn.MetricGroup)
-//line app/vmselect/prometheus/export.qtpl:149
+//line app/vmselect/prometheus/export.qtpl:150
 	if len(mn.Tags) > 0 {
-//line app/vmselect/prometheus/export.qtpl:149
+//line app/vmselect/prometheus/export.qtpl:150
 		qw422016.N().S(`{`)
-//line app/vmselect/prometheus/export.qtpl:151
+//line app/vmselect/prometheus/export.qtpl:152
 		tags := mn.Tags
 
-//line app/vmselect/prometheus/export.qtpl:152
-		qw422016.N().Z(tags[0].Key)
-//line app/vmselect/prometheus/export.qtpl:152
-		qw422016.N().S(`=`)
-//line app/vmselect/prometheus/export.qtpl:152
-		streamescapePrometheusLabel(qw422016, tags[0].Value)
 //line app/vmselect/prometheus/export.qtpl:153
+		qw422016.N().Z(tags[0].Key)
+//line app/vmselect/prometheus/export.qtpl:153
+		qw422016.N().S(`=`)
+//line app/vmselect/prometheus/export.qtpl:153
+		streamescapePrometheusLabel(qw422016, tags[0].Value)
+//line app/vmselect/prometheus/export.qtpl:154
 		tags = tags[1:]
 
-//line app/vmselect/prometheus/export.qtpl:154
-		for i := range tags {
 //line app/vmselect/prometheus/export.qtpl:155
+		for i := range tags {
+//line app/vmselect/prometheus/export.qtpl:156
 			tag := &tags[i]
 
-//line app/vmselect/prometheus/export.qtpl:155
+//line app/vmselect/prometheus/export.qtpl:156
 			qw422016.N().S(`,`)
-//line app/vmselect/prometheus/export.qtpl:156
+//line app/vmselect/prometheus/export.qtpl:157
 			qw422016.N().Z(tag.Key)
-//line app/vmselect/prometheus/export.qtpl:156
+//line app/vmselect/prometheus/export.qtpl:157
 			qw422016.N().S(`=`)
-//line app/vmselect/prometheus/export.qtpl:156
+//line app/vmselect/prometheus/export.qtpl:157
 			streamescapePrometheusLabel(qw422016, tag.Value)
-//line app/vmselect/prometheus/export.qtpl:157
+//line app/vmselect/prometheus/export.qtpl:158
 		}
-//line app/vmselect/prometheus/export.qtpl:157
+//line app/vmselect/prometheus/export.qtpl:158
 		qw422016.N().S(`}`)
-//line app/vmselect/prometheus/export.qtpl:159
-	}
 //line app/vmselect/prometheus/export.qtpl:160
+	}
+//line app/vmselect/prometheus/export.qtpl:161
 }
 
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 func writeprometheusMetricName(qq422016 qtio422016.Writer, mn *storage.MetricName) {
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	streamprometheusMetricName(qw422016, mn)
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 }
 
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 func prometheusMetricName(mn *storage.MetricName) string {
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	writeprometheusMetricName(qb422016, mn)
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:160
+//line app/vmselect/prometheus/export.qtpl:161
 }
 
-//line app/vmselect/prometheus/export.qtpl:162
+//line app/vmselect/prometheus/export.qtpl:163
 func streamconvertValueToSpecialJSON(qw422016 *qt422016.Writer, v float64) {
-//line app/vmselect/prometheus/export.qtpl:163
+//line app/vmselect/prometheus/export.qtpl:164
 	if math.IsNaN(v) {
-//line app/vmselect/prometheus/export.qtpl:163
+//line app/vmselect/prometheus/export.qtpl:164
 		qw422016.N().S(`null`)
-//line app/vmselect/prometheus/export.qtpl:165
+//line app/vmselect/prometheus/export.qtpl:166
 	} else if math.IsInf(v, 0) {
-//line app/vmselect/prometheus/export.qtpl:166
+//line app/vmselect/prometheus/export.qtpl:167
 		if v > 0 {
-//line app/vmselect/prometheus/export.qtpl:166
+//line app/vmselect/prometheus/export.qtpl:167
 			qw422016.N().S(`"Infinity"`)
-//line app/vmselect/prometheus/export.qtpl:168
+//line app/vmselect/prometheus/export.qtpl:169
 		} else {
-//line app/vmselect/prometheus/export.qtpl:168
+//line app/vmselect/prometheus/export.qtpl:169
 			qw422016.N().S(`"-Infinity"`)
-//line app/vmselect/prometheus/export.qtpl:170
-		}
 //line app/vmselect/prometheus/export.qtpl:171
-	} else {
+		}
 //line app/vmselect/prometheus/export.qtpl:172
-		qw422016.N().F(v)
+	} else {
 //line app/vmselect/prometheus/export.qtpl:173
+		qw422016.N().F(v)
+//line app/vmselect/prometheus/export.qtpl:174
 	}
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 }
 
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 func writeconvertValueToSpecialJSON(qq422016 qtio422016.Writer, v float64) {
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	streamconvertValueToSpecialJSON(qw422016, v)
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 }
 
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 func convertValueToSpecialJSON(v float64) string {
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	writeconvertValueToSpecialJSON(qb422016, v)
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:174
+//line app/vmselect/prometheus/export.qtpl:175
 }
 
-//line app/vmselect/prometheus/export.qtpl:176
+//line app/vmselect/prometheus/export.qtpl:177
 func streamescapePrometheusLabel(qw422016 *qt422016.Writer, b []byte) {
-//line app/vmselect/prometheus/export.qtpl:176
+//line app/vmselect/prometheus/export.qtpl:177
 	qw422016.N().S(`"`)
-//line app/vmselect/prometheus/export.qtpl:178
-	for len(b) > 0 {
 //line app/vmselect/prometheus/export.qtpl:179
+	for len(b) > 0 {
+//line app/vmselect/prometheus/export.qtpl:180
 		n := bytes.IndexAny(b, "\\\n\"")
 
-//line app/vmselect/prometheus/export.qtpl:180
-		if n < 0 {
 //line app/vmselect/prometheus/export.qtpl:181
-			qw422016.N().Z(b)
+		if n < 0 {
 //line app/vmselect/prometheus/export.qtpl:182
-			break
+			qw422016.N().Z(b)
 //line app/vmselect/prometheus/export.qtpl:183
-		}
+			break
 //line app/vmselect/prometheus/export.qtpl:184
-		qw422016.N().Z(b[:n])
-//line app/vmselect/prometheus/export.qtpl:185
-		switch b[n] {
-//line app/vmselect/prometheus/export.qtpl:186
-		case '\\':
-//line app/vmselect/prometheus/export.qtpl:186
-			qw422016.N().S(`\\`)
-//line app/vmselect/prometheus/export.qtpl:188
-		case '\n':
-//line app/vmselect/prometheus/export.qtpl:188
-			qw422016.N().S(`\n`)
-//line app/vmselect/prometheus/export.qtpl:190
-		case '"':
-//line app/vmselect/prometheus/export.qtpl:190
-			qw422016.N().S(`\"`)
-//line app/vmselect/prometheus/export.qtpl:192
 		}
+//line app/vmselect/prometheus/export.qtpl:185
+		qw422016.N().Z(b[:n])
+//line app/vmselect/prometheus/export.qtpl:186
+		switch b[n] {
+//line app/vmselect/prometheus/export.qtpl:187
+		case '\\':
+//line app/vmselect/prometheus/export.qtpl:187
+			qw422016.N().S(`\\`)
+//line app/vmselect/prometheus/export.qtpl:189
+		case '\n':
+//line app/vmselect/prometheus/export.qtpl:189
+			qw422016.N().S(`\n`)
+//line app/vmselect/prometheus/export.qtpl:191
+		case '"':
+//line app/vmselect/prometheus/export.qtpl:191
+			qw422016.N().S(`\"`)
 //line app/vmselect/prometheus/export.qtpl:193
+		}
+//line app/vmselect/prometheus/export.qtpl:194
 		b = b[n+1:]
 
-//line app/vmselect/prometheus/export.qtpl:194
+//line app/vmselect/prometheus/export.qtpl:195
 	}
-//line app/vmselect/prometheus/export.qtpl:194
+//line app/vmselect/prometheus/export.qtpl:195
 	qw422016.N().S(`"`)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 }
 
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 func writeescapePrometheusLabel(qq422016 qtio422016.Writer, b []byte) {
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	qw422016 := qt422016.AcquireWriter(qq422016)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	streamescapePrometheusLabel(qw422016, b)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	qt422016.ReleaseWriter(qw422016)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 }
 
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 func escapePrometheusLabel(b []byte) string {
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	qb422016 := qt422016.AcquireByteBuffer()
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	writeescapePrometheusLabel(qb422016, b)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	qs422016 := string(qb422016.B)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	qt422016.ReleaseByteBuffer(qb422016)
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 	return qs422016
-//line app/vmselect/prometheus/export.qtpl:196
+//line app/vmselect/prometheus/export.qtpl:197
 }

app/vmselect/prometheus/prometheus.go

@@ -47,15 +47,22 @@ var (
 	maxStepForPointsAdjustment = flag.Duration("search.maxStepForPointsAdjustment", time.Minute, "The maximum step when /api/v1/query_range handler adjusts "+
 		"points with timestamps closer than -search.latencyOffset to the current time. The adjustment is needed because such points may contain incomplete data")
 
-	maxUniqueTimeseries    = flag.Int("search.maxUniqueTimeseries", 300e3, "The maximum number of unique time series, which can be selected during /api/v1/query and /api/v1/query_range queries. This option allows limiting memory usage")
-	maxFederateSeries      = flag.Int("search.maxFederateSeries", 1e6, "The maximum number of time series, which can be returned from /federate. This option allows limiting memory usage")
-	maxExportSeries        = flag.Int("search.maxExportSeries", 10e6, "The maximum number of time series, which can be returned from /api/v1/export* APIs. This option allows limiting memory usage")
-	maxTSDBStatusSeries    = flag.Int("search.maxTSDBStatusSeries", 10e6, "The maximum number of time series, which can be processed during the call to /api/v1/status/tsdb. This option allows limiting memory usage")
-	maxSeriesLimit         = flag.Int("search.maxSeries", 30e3, "The maximum number of time series, which can be returned from /api/v1/series. This option allows limiting memory usage")
+	maxUniqueTimeseries = flag.Int("search.maxUniqueTimeseries", 300e3, "The maximum number of unique time series, which can be selected during /api/v1/query and /api/v1/query_range queries. This option allows limiting memory usage")
+	maxFederateSeries   = flag.Int("search.maxFederateSeries", 1e6, "The maximum number of time series, which can be returned from /federate. This option allows limiting memory usage")
+	maxExportSeries     = flag.Int("search.maxExportSeries", 10e6, "The maximum number of time series, which can be returned from /api/v1/export* APIs. This option allows limiting memory usage")
+	maxTSDBStatusSeries = flag.Int("search.maxTSDBStatusSeries", 10e6, "The maximum number of time series, which can be processed during the call to /api/v1/status/tsdb. This option allows limiting memory usage")
+	maxSeriesLimit      = flag.Int("search.maxSeries", 30e3, "The maximum number of time series, which can be returned from /api/v1/series. This option allows limiting memory usage")
+	maxLabelsAPISeries  = flag.Int("search.maxLabelsAPISeries", 1e6, "The maximum number of time series, which could be scanned when searching for the the matching time series "+
+		"at /api/v1/labels and /api/v1/label/.../values. This option allows limiting memory usage and CPU usage. See also -search.maxLabelsAPIDuration, "+
+		"-search.maxTagKeys, -search.maxTagValues and -search.ignoreExtraFiltersAtLabelsAPI")
 	maxPointsPerTimeseries = flag.Int("search.maxPointsPerTimeseries", 30e3, "The maximum points per a single timeseries returned from /api/v1/query_range. "+
 		"This option doesn't limit the number of scanned raw samples in the database. The main purpose of this option is to limit the number of per-series points "+
 		"returned to graphing UI such as VMUI or Grafana. There is no sense in setting this limit to values bigger than the horizontal resolution of the graph. "+
 		"See also -search.maxResponseSeries")
+	ignoreExtraFiltersAtLabelsAPI = flag.Bool("search.ignoreExtraFiltersAtLabelsAPI", false, "Whether to ignore match[], extra_filters[] and extra_label query args at "+
+		"/api/v1/labels and /api/v1/label/.../values . This may be useful for decreasing load on VictoriaMetrics when extra filters "+
+		"match too many time series. The downside is that suprflouos labels or series could be returned, which do not match the extra filters. "+
+		"See also -search.maxLabelsAPISeries and -search.maxLabelsAPIDuration")
 )
 
 // Default step used if not set.
@@ -317,21 +324,21 @@ func exportHandler(qt *querytracer.Tracer, w http.ResponseWriter, cp *commonPara
 		}
 	} else if format == "promapi" {
 		WriteExportPromAPIHeader(bw)
-		firstLineOnce := uint32(0)
-		firstLineSent := uint32(0)
+		var firstLineOnce atomic.Bool
+		var firstLineSent atomic.Bool
 		writeLineFunc = func(xb *exportBlock, workerID uint) error {
 			bb := sw.getBuffer(workerID)
-			// Use atomic.LoadUint32() in front of atomic.CompareAndSwapUint32() in order to avoid slow inter-CPU synchronization
+			// Use Load() in front of CompareAndSwap() in order to avoid slow inter-CPU synchronization
 			// in fast path after the first line has been already sent.
-			if atomic.LoadUint32(&firstLineOnce) == 0 && atomic.CompareAndSwapUint32(&firstLineOnce, 0, 1) {
+			if !firstLineOnce.Load() && firstLineOnce.CompareAndSwap(false, true) {
 				// Send the first line to sw.bw
 				WriteExportPromAPILine(bb, xb)
 				_, err := sw.bw.Write(bb.B)
 				bb.Reset()
-				atomic.StoreUint32(&firstLineSent, 1)
+				firstLineSent.Store(true)
 				return err
 			}
-			for atomic.LoadUint32(&firstLineSent) == 0 {
+			for !firstLineSent.Load() {
 				// Busy wait until the first line is sent to sw.bw
 				runtime.Gosched()
 			}
@@ -491,7 +498,7 @@ var deleteDuration = metrics.NewSummary(`vm_request_duration_seconds{path="/api/
 func LabelValuesHandler(qt *querytracer.Tracer, startTime time.Time, labelName string, w http.ResponseWriter, r *http.Request) error {
 	defer labelValuesDuration.UpdateDuration(startTime)
 
-	cp, err := getCommonParamsWithDefaultDuration(r, startTime, false)
+	cp, err := getCommonParamsForLabelsAPI(r, startTime, false)
 	if err != nil {
 		return err
 	}
@@ -499,10 +506,7 @@ func LabelValuesHandler(qt *querytracer.Tracer, startTime time.Time, labelName s
 	if err != nil {
 		return err
 	}
-	// Do not limit the number of unique time series, which could be scanned
-	// during the search for matching label values, since users expect this API
-	// must always work.
-	sq := storage.NewSearchQuery(cp.start, cp.end, cp.filterss, -1)
+	sq := storage.NewSearchQuery(cp.start, cp.end, cp.filterss, *maxLabelsAPISeries)
 	labelValues, err := netstorage.LabelValues(qt, labelName, sq, limit, cp.deadline)
 	if err != nil {
 		return fmt.Errorf("cannot obtain values for label %q: %w", labelName, err)
@@ -591,7 +595,7 @@ var tsdbStatusDuration = metrics.NewSummary(`vm_request_duration_seconds{path="/
 func LabelsHandler(qt *querytracer.Tracer, startTime time.Time, w http.ResponseWriter, r *http.Request) error {
 	defer labelsDuration.UpdateDuration(startTime)
 
-	cp, err := getCommonParamsWithDefaultDuration(r, startTime, false)
+	cp, err := getCommonParamsForLabelsAPI(r, startTime, false)
 	if err != nil {
 		return err
 	}
@@ -599,10 +603,7 @@ func LabelsHandler(qt *querytracer.Tracer, startTime time.Time, w http.ResponseW
 	if err != nil {
 		return err
 	}
-	// Do not limit the number of unique time series, which could be scanned
-	// during the search for matching label values, since users expect this API
-	// must always work.
-	sq := storage.NewSearchQuery(cp.start, cp.end, cp.filterss, -1)
+	sq := storage.NewSearchQuery(cp.start, cp.end, cp.filterss, *maxLabelsAPISeries)
 	labels, err := netstorage.LabelNames(qt, sq, limit, cp.deadline)
 	if err != nil {
 		return fmt.Errorf("cannot obtain labels: %w", err)
@@ -647,12 +648,12 @@ var seriesCountDuration = metrics.NewSummary(`vm_request_duration_seconds{path="
 func SeriesHandler(qt *querytracer.Tracer, startTime time.Time, w http.ResponseWriter, r *http.Request) error {
 	defer seriesDuration.UpdateDuration(startTime)
 
-	// Do not set start to searchutils.minTimeMsecs by default as Prometheus does,
+	// Do not set start to httputils.minTimeMsecs by default as Prometheus does,
 	// since this leads to fetching and scanning all the data from the storage,
 	// which can take a lot of time for big storages.
 	// It is better setting start as end-defaultStep by default.
 	// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/91
-	cp, err := getCommonParamsWithDefaultDuration(r, startTime, true)
+	cp, err := getCommonParamsForLabelsAPI(r, startTime, true)
 	if err != nil {
 		return err
 	}
@@ -1129,14 +1130,15 @@ func getExportParams(r *http.Request, startTime time.Time) (*commonParams, error
 	return cp, nil
 }
 
-func getCommonParamsWithDefaultDuration(r *http.Request, startTime time.Time, requireNonEmptyMatch bool) (*commonParams, error) {
-	cp, err := getCommonParams(r, startTime, requireNonEmptyMatch)
+func getCommonParamsForLabelsAPI(r *http.Request, startTime time.Time, requireNonEmptyMatch bool) (*commonParams, error) {
+	cp, err := getCommonParamsInternal(r, startTime, requireNonEmptyMatch, true)
 	if err != nil {
 		return nil, err
 	}
 	if cp.start == 0 {
 		cp.start = cp.end - defaultStep
 	}
+	cp.deadline = searchutils.GetDeadlineForExport(r, startTime)
 	return cp, nil
 }
 
@@ -1149,6 +1151,10 @@ func getCommonParamsWithDefaultDuration(r *http.Request, startTime time.Time, re
 // - extra_label
 // - extra_filters[]
 func getCommonParams(r *http.Request, startTime time.Time, requireNonEmptyMatch bool) (*commonParams, error) {
+	return getCommonParamsInternal(r, startTime, requireNonEmptyMatch, false)
+}
+
+func getCommonParamsInternal(r *http.Request, startTime time.Time, requireNonEmptyMatch, isLabelsAPI bool) (*commonParams, error) {
 	deadline := searchutils.GetDeadlineForQuery(r, startTime)
 	start, err := httputils.GetTime(r, "start", 0)
 	if err != nil {
@@ -1175,15 +1181,20 @@ func getCommonParams(r *http.Request, startTime time.Time, requireNonEmptyMatch
 	if requireNonEmptyMatch && len(matches) == 0 {
 		return nil, fmt.Errorf("missing `match[]` arg")
 	}
-	tagFilterss, err := getTagFilterssFromMatches(matches)
-	if err != nil {
-		return nil, err
+
+	var filterss [][]storage.TagFilter
+	if !isLabelsAPI || !*ignoreExtraFiltersAtLabelsAPI {
+		tagFilterss, err := getTagFilterssFromMatches(matches)
+		if err != nil {
+			return nil, err
+		}
+		etfs, err := searchutils.GetExtraTagFilters(r)
+		if err != nil {
+			return nil, err
+		}
+		filterss = searchutils.JoinTagFilterss(tagFilterss, etfs)
 	}
-	etfs, err := searchutils.GetExtraTagFilters(r)
-	if err != nil {
-		return nil, err
-	}
-	filterss := searchutils.JoinTagFilterss(tagFilterss, etfs)
+
 	cp := &commonParams{
 		deadline:         deadline,
 		start:            start,

app/vmselect/prometheus/query_range_response.qtpl

@@ -33,8 +33,8 @@ See https://prometheus.io/docs/prometheus/latest/querying/api/#range-queries
 			// seriesFetched is string instead of int because of historical reasons.
 			// It cannot be converted to int without breaking backwards compatibility at vmalert :(
 		%}
-		"seriesFetched": "{%dl qs.SeriesFetched %}",
-		"executionTimeMsec": {%dl qs.ExecutionTimeMsec %}
+		"seriesFetched": "{%dl qs.SeriesFetched.Load() %}",
+		"executionTimeMsec": {%dl qs.ExecutionTimeMsec.Load() %}
 	}
 	{% code
 		qt.Printf("generate /api/v1/query_range response for series=%d, points=%d", seriesCount, pointsCount)

app/vmselect/prometheus/query_range_response.qtpl.go

@@ -68,11 +68,11 @@ func StreamQueryRangeResponse(qw422016 *qt422016.Writer, rs []netstorage.Result,
 //line app/vmselect/prometheus/query_range_response.qtpl:35
 	qw422016.N().S(`"seriesFetched": "`)
 //line app/vmselect/prometheus/query_range_response.qtpl:36
-	qw422016.N().DL(qs.SeriesFetched)
+	qw422016.N().DL(qs.SeriesFetched.Load())
 //line app/vmselect/prometheus/query_range_response.qtpl:36
 	qw422016.N().S(`","executionTimeMsec":`)
 //line app/vmselect/prometheus/query_range_response.qtpl:37
-	qw422016.N().DL(qs.ExecutionTimeMsec)
+	qw422016.N().DL(qs.ExecutionTimeMsec.Load())
 //line app/vmselect/prometheus/query_range_response.qtpl:37
 	qw422016.N().S(`}`)
 //line app/vmselect/prometheus/query_range_response.qtpl:40

app/vmselect/prometheus/query_response.qtpl

@@ -35,8 +35,8 @@ See https://prometheus.io/docs/prometheus/latest/querying/api/#instant-queries
 			// seriesFetched is string instead of int because of historical reasons.
 			// It cannot be converted to int without breaking backwards compatibility at vmalert :(
 		%}
-		"seriesFetched": "{%dl qs.SeriesFetched %}",
-		"executionTimeMsec": {%dl qs.ExecutionTimeMsec %}
+		"seriesFetched": "{%dl qs.SeriesFetched.Load() %}",
+		"executionTimeMsec": {%dl qs.ExecutionTimeMsec.Load() %}
 	}
 	{% code
 		qt.Printf("generate /api/v1/query response for series=%d", seriesCount)

app/vmselect/prometheus/query_response.qtpl.go

@@ -78,11 +78,11 @@ func StreamQueryResponse(qw422016 *qt422016.Writer, rs []netstorage.Result, qt *
 //line app/vmselect/prometheus/query_response.qtpl:37
 	qw422016.N().S(`"seriesFetched": "`)
 //line app/vmselect/prometheus/query_response.qtpl:38
-	qw422016.N().DL(qs.SeriesFetched)
+	qw422016.N().DL(qs.SeriesFetched.Load())
 //line app/vmselect/prometheus/query_response.qtpl:38
 	qw422016.N().S(`","executionTimeMsec":`)
 //line app/vmselect/prometheus/query_response.qtpl:39
-	qw422016.N().DL(qs.ExecutionTimeMsec)
+	qw422016.N().DL(qs.ExecutionTimeMsec.Load())
 //line app/vmselect/prometheus/query_response.qtpl:39
 	qw422016.N().S(`}`)
 //line app/vmselect/prometheus/query_response.qtpl:42

app/vmselect/promql/active_queries.go

@@ -60,7 +60,7 @@ func (aq *activeQueries) Add(ec *EvalConfig, q string) uint64 {
 	aqe.start = ec.Start
 	aqe.end = ec.End
 	aqe.step = ec.Step
-	aqe.qid = atomic.AddUint64(&nextActiveQueryID, 1)
+	aqe.qid = nextActiveQueryID.Add(1)
 	aqe.quotedRemoteAddr = ec.QuotedRemoteAddr
 	aqe.q = q
 	aqe.startTime = time.Now()
@@ -87,4 +87,8 @@ func (aq *activeQueries) GetAll() []activeQueryEntry {
 	return aqes
 }
 
-var nextActiveQueryID = uint64(time.Now().UnixNano())
+var nextActiveQueryID = func() *atomic.Uint64 {
+	var x atomic.Uint64
+	x.Store(uint64(time.Now().UnixNano()))
+	return &x
+}()

app/vmselect/promql/eval.go

@@ -171,16 +171,17 @@ func copyEvalConfig(src *EvalConfig) *EvalConfig {
 // QueryStats contains various stats for the query.
 type QueryStats struct {
 	// SeriesFetched contains the number of series fetched from storage during the query evaluation.
-	SeriesFetched int64
+	SeriesFetched atomic.Int64
+
 	// ExecutionTimeMsec contains the number of milliseconds the query took to execute.
-	ExecutionTimeMsec int64
+	ExecutionTimeMsec atomic.Int64
 }
 
 func (qs *QueryStats) addSeriesFetched(n int) {
 	if qs == nil {
 		return
 	}
-	atomic.AddInt64(&qs.SeriesFetched, int64(n))
+	qs.SeriesFetched.Add(int64(n))
 }
 
 func (qs *QueryStats) addExecutionTimeMsec(startTime time.Time) {
@@ -188,7 +189,7 @@ func (qs *QueryStats) addExecutionTimeMsec(startTime time.Time) {
 		return
 	}
 	d := time.Since(startTime).Milliseconds()
-	atomic.AddInt64(&qs.ExecutionTimeMsec, d)
+	qs.ExecutionTimeMsec.Add(d)
 }
 
 func (ec *EvalConfig) validate() {
@@ -313,7 +314,7 @@ func evalExprInternal(qt *querytracer.Tracer, ec *EvalConfig, e metricsql.Expr)
 		}
 		rf, err := nrf(args)
 		if err != nil {
-			return nil, err
+			return nil, fmt.Errorf("cannot evaluate args for %q: %w", fe.AppendString(nil), err)
 		}
 		rv, err := evalRollupFunc(qt, ec, fe.Name, rf, e, re, nil)
 		if err != nil {
@@ -394,7 +395,7 @@ func evalAggrFunc(qt *querytracer.Tracer, ec *EvalConfig, ae *metricsql.AggrFunc
 			}
 			rf, err := nrf(args)
 			if err != nil {
-				return nil, err
+				return nil, fmt.Errorf("cannot evaluate args for aggregate func %q: %w", ae.AppendString(nil), err)
 			}
 			iafc := newIncrementalAggrFuncContext(ae, callbacks)
 			return evalRollupFunc(qt, ec, fe.Name, rf, ae, re, iafc)
@@ -949,7 +950,7 @@ func evalRollupFuncWithSubquery(qt *querytracer.Tracer, ec *EvalConfig, funcName
 		return nil, err
 	}
 
-	var samplesScannedTotal uint64
+	var samplesScannedTotal atomic.Uint64
 	keepMetricNames := getKeepMetricNames(expr)
 	tsw := getTimeseriesByWorkerID()
 	seriesByWorkerID := tsw.byWorkerID
@@ -959,13 +960,13 @@ func evalRollupFuncWithSubquery(qt *querytracer.Tracer, ec *EvalConfig, funcName
 		for _, rc := range rcs {
 			if tsm := newTimeseriesMap(funcName, keepMetricNames, sharedTimestamps, &tsSQ.MetricName); tsm != nil {
 				samplesScanned := rc.DoTimeseriesMap(tsm, values, timestamps)
-				atomic.AddUint64(&samplesScannedTotal, samplesScanned)
+				samplesScannedTotal.Add(samplesScanned)
 				seriesByWorkerID[workerID].tss = tsm.AppendTimeseriesTo(seriesByWorkerID[workerID].tss)
 				continue
 			}
 			var ts timeseries
 			samplesScanned := doRollupForTimeseries(funcName, keepMetricNames, rc, &ts, &tsSQ.MetricName, values, timestamps, sharedTimestamps)
-			atomic.AddUint64(&samplesScannedTotal, samplesScanned)
+			samplesScannedTotal.Add(samplesScanned)
 			seriesByWorkerID[workerID].tss = append(seriesByWorkerID[workerID].tss, &ts)
 		}
 		return values, timestamps
@@ -976,8 +977,8 @@ func evalRollupFuncWithSubquery(qt *querytracer.Tracer, ec *EvalConfig, funcName
 	}
 	putTimeseriesByWorkerID(tsw)
 
-	rowsScannedPerQuery.Update(float64(samplesScannedTotal))
-	qt.Printf("rollup %s() over %d series returned by subquery: series=%d, samplesScanned=%d", funcName, len(tssSQ), len(tss), samplesScannedTotal)
+	rowsScannedPerQuery.Update(float64(samplesScannedTotal.Load()))
+	qt.Printf("rollup %s() over %d series returned by subquery: series=%d, samplesScanned=%d", funcName, len(tssSQ), len(tss), samplesScannedTotal.Load())
 	return tss, nil
 }
 
@@ -1687,7 +1688,7 @@ func evalRollupFuncNoCache(qt *querytracer.Tracer, ec *EvalConfig, funcName stri
 	tfss := searchutils.ToTagFilterss(me.LabelFilterss)
 	tfss = searchutils.JoinTagFilterss(tfss, ec.EnforcedTagFilterss)
 	minTimestamp := ec.Start
-	if needSilenceIntervalForRollupFunc(funcName) {
+	if needSilenceIntervalForRollupFunc[funcName] {
 		minTimestamp -= maxSilenceInterval()
 	}
 	if window > ec.Step {
@@ -1788,62 +1789,12 @@ func maxSilenceInterval() int64 {
 	return d
 }
 
-func needSilenceIntervalForRollupFunc(funcName string) bool {
-	// All the rollup functions, which do not rely on the previous sample
-	// before the lookbehind window (aka prevValue and realPrevValue), do not need silence interval.
-	switch strings.ToLower(funcName) {
-	case "default_rollup":
-		// The default_rollup implicitly relies on the previous samples in order to fill gaps.
-		// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5388
-		return true
-	case
-		"absent_over_time",
-		"avg_over_time",
-		"count_eq_over_time",
-		"count_gt_over_time",
-		"count_le_over_time",
-		"count_ne_over_time",
-		"count_over_time",
-		"first_over_time",
-		"histogram_over_time",
-		"hoeffding_bound_lower",
-		"hoeffding_bound_upper",
-		"last_over_time",
-		"mad_over_time",
-		"max_over_time",
-		"median_over_time",
-		"min_over_time",
-		"predict_linear",
-		"present_over_time",
-		"quantile_over_time",
-		"quantiles_over_time",
-		"range_over_time",
-		"share_gt_over_time",
-		"share_le_over_time",
-		"share_eq_over_time",
-		"stale_samples_over_time",
-		"stddev_over_time",
-		"stdvar_over_time",
-		"sum_over_time",
-		"tfirst_over_time",
-		"timestamp",
-		"timestamp_with_name",
-		"tlast_over_time",
-		"tmax_over_time",
-		"tmin_over_time",
-		"zscore_over_time":
-		return false
-	default:
-		return true
-	}
-}
-
 func evalRollupWithIncrementalAggregate(qt *querytracer.Tracer, funcName string, keepMetricNames bool,
 	iafc *incrementalAggrFuncContext, rss *netstorage.Results, rcs []*rollupConfig,
 	preFunc func(values []float64, timestamps []int64), sharedTimestamps []int64) ([]*timeseries, error) {
 	qt = qt.NewChild("rollup %s() with incremental aggregation %s() over %d series; rollupConfigs=%s", funcName, iafc.ae.Name, rss.Len(), rcs)
 	defer qt.Done()
-	var samplesScannedTotal uint64
+	var samplesScannedTotal atomic.Uint64
 	err := rss.RunParallel(qt, func(rs *netstorage.Result, workerID uint) error {
 		rs.Values, rs.Timestamps = dropStaleNaNs(funcName, rs.Values, rs.Timestamps)
 		preFunc(rs.Values, rs.Timestamps)
@@ -1855,12 +1806,12 @@ func evalRollupWithIncrementalAggregate(qt *querytracer.Tracer, funcName string,
 				for _, ts := range tsm.m {
 					iafc.updateTimeseries(ts, workerID)
 				}
-				atomic.AddUint64(&samplesScannedTotal, samplesScanned)
+				samplesScannedTotal.Add(samplesScanned)
 				continue
 			}
 			ts.Reset()
 			samplesScanned := doRollupForTimeseries(funcName, keepMetricNames, rc, ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps)
-			atomic.AddUint64(&samplesScannedTotal, samplesScanned)
+			samplesScannedTotal.Add(samplesScanned)
 			iafc.updateTimeseries(ts, workerID)
 
 			// ts.Timestamps points to sharedTimestamps. Zero it, so it can be re-used.
@@ -1873,8 +1824,8 @@ func evalRollupWithIncrementalAggregate(qt *querytracer.Tracer, funcName string,
 		return nil, err
 	}
 	tss := iafc.finalizeTimeseries()
-	rowsScannedPerQuery.Update(float64(samplesScannedTotal))
-	qt.Printf("series after aggregation with %s(): %d; samplesScanned=%d", iafc.ae.Name, len(tss), samplesScannedTotal)
+	rowsScannedPerQuery.Update(float64(samplesScannedTotal.Load()))
+	qt.Printf("series after aggregation with %s(): %d; samplesScanned=%d", iafc.ae.Name, len(tss), samplesScannedTotal.Load())
 	return tss, nil
 }
 
@@ -1883,7 +1834,7 @@ func evalRollupNoIncrementalAggregate(qt *querytracer.Tracer, funcName string, k
 	qt = qt.NewChild("rollup %s() over %d series; rollupConfigs=%s", funcName, rss.Len(), rcs)
 	defer qt.Done()
 
-	var samplesScannedTotal uint64
+	var samplesScannedTotal atomic.Uint64
 	tsw := getTimeseriesByWorkerID()
 	seriesByWorkerID := tsw.byWorkerID
 	seriesLen := rss.Len()
@@ -1893,13 +1844,13 @@ func evalRollupNoIncrementalAggregate(qt *querytracer.Tracer, funcName string, k
 		for _, rc := range rcs {
 			if tsm := newTimeseriesMap(funcName, keepMetricNames, sharedTimestamps, &rs.MetricName); tsm != nil {
 				samplesScanned := rc.DoTimeseriesMap(tsm, rs.Values, rs.Timestamps)
-				atomic.AddUint64(&samplesScannedTotal, samplesScanned)
+				samplesScannedTotal.Add(samplesScanned)
 				seriesByWorkerID[workerID].tss = tsm.AppendTimeseriesTo(seriesByWorkerID[workerID].tss)
 				continue
 			}
 			var ts timeseries
 			samplesScanned := doRollupForTimeseries(funcName, keepMetricNames, rc, &ts, &rs.MetricName, rs.Values, rs.Timestamps, sharedTimestamps)
-			atomic.AddUint64(&samplesScannedTotal, samplesScanned)
+			samplesScannedTotal.Add(samplesScanned)
 			seriesByWorkerID[workerID].tss = append(seriesByWorkerID[workerID].tss, &ts)
 		}
 		return nil
@@ -1913,8 +1864,8 @@ func evalRollupNoIncrementalAggregate(qt *querytracer.Tracer, funcName string, k
 	}
 	putTimeseriesByWorkerID(tsw)
 
-	rowsScannedPerQuery.Update(float64(samplesScannedTotal))
-	qt.Printf("samplesScanned=%d", samplesScannedTotal)
+	rowsScannedPerQuery.Update(float64(samplesScannedTotal.Load()))
+	qt.Printf("samplesScanned=%d", samplesScannedTotal.Load())
 	return tss, nil
 }
 

app/vmselect/promql/eval_test.go

@@ -86,14 +86,14 @@ func TestQueryStats_addSeriesFetched(t *testing.T) {
 	}
 	ec.QueryStats.addSeriesFetched(1)
 
-	if qs.SeriesFetched != 1 {
-		t.Fatalf("expected to get 1; got %d instead", qs.SeriesFetched)
+	if n := qs.SeriesFetched.Load(); n != 1 {
+		t.Fatalf("expected to get 1; got %d instead", n)
 	}
 
 	ecNew := copyEvalConfig(ec)
 	ecNew.QueryStats.addSeriesFetched(3)
-	if qs.SeriesFetched != 4 {
-		t.Fatalf("expected to get 4; got %d instead", qs.SeriesFetched)
+	if n := qs.SeriesFetched.Load(); n != 4 {
+		t.Fatalf("expected to get 4; got %d instead", n)
 	}
 }
 

app/vmselect/promql/exec.go

@@ -352,22 +352,19 @@ type parseCacheValue struct {
 }
 
 type parseCache struct {
-	// Move atomic counters to the top of struct for 8-byte alignment on 32-bit arch.
-	// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/212
-
-	requests uint64
-	misses   uint64
+	requests atomic.Uint64
+	misses   atomic.Uint64
 
 	m  map[string]*parseCacheValue
 	mu sync.RWMutex
 }
 
 func (pc *parseCache) Requests() uint64 {
-	return atomic.LoadUint64(&pc.requests)
+	return pc.requests.Load()
 }
 
 func (pc *parseCache) Misses() uint64 {
-	return atomic.LoadUint64(&pc.misses)
+	return pc.misses.Load()
 }
 
 func (pc *parseCache) Len() uint64 {
@@ -378,14 +375,14 @@ func (pc *parseCache) Len() uint64 {
 }
 
 func (pc *parseCache) Get(q string) *parseCacheValue {
-	atomic.AddUint64(&pc.requests, 1)
+	pc.requests.Add(1)
 
 	pc.mu.RLock()
 	pcv := pc.m[q]
 	pc.mu.RUnlock()
 
 	if pcv == nil {
-		atomic.AddUint64(&pc.misses, 1)
+		pc.misses.Add(1)
 	}
 	return pcv
 }

app/vmselect/promql/exec_test.go

@@ -2307,6 +2307,21 @@ func TestExecSuccess(t *testing.T) {
 		resultExpected := []netstorage.Result{r}
 		f(q, resultExpected)
 	})
+	t.Run(`label_join dst_label is equal to src_label`, func(t *testing.T) {
+		t.Parallel()
+		q := `label_join(label_join(time(), "bar", "sep1", "a", "b"), "bar", "sep2", "a", "bar")`
+		r := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{1000, 1200, 1400, 1600, 1800, 2000},
+			Timestamps: timestampsExpected,
+		}
+		r.MetricName.Tags = []storage.Tag{{
+			Key:   []byte("bar"),
+			Value: []byte("sep2sep1"),
+		}}
+		resultExpected := []netstorage.Result{r}
+		f(q, resultExpected)
+	})
 	t.Run(`label_value()`, func(t *testing.T) {
 		t.Parallel()
 		q := `with (
@@ -5822,6 +5837,60 @@ func TestExecSuccess(t *testing.T) {
 		resultExpected := []netstorage.Result{r1, r2}
 		f(q, resultExpected)
 	})
+	t.Run(`count_values_over_time`, func(t *testing.T) {
+		t.Parallel()
+		q := `sort_by_label(
+			count_values_over_time("foo", round(label_set(rand(0), "x", "y"), 0.4)[200s:5s]),
+			"foo",
+		)`
+		r1 := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{4, 8, 7, 6, 10, 9},
+			Timestamps: timestampsExpected,
+		}
+		r1.MetricName.Tags = []storage.Tag{
+			{
+				Key:   []byte("foo"),
+				Value: []byte("0"),
+			},
+			{
+				Key:   []byte("x"),
+				Value: []byte("y"),
+			},
+		}
+		r2 := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{20, 13, 19, 18, 14, 13},
+			Timestamps: timestampsExpected,
+		}
+		r2.MetricName.Tags = []storage.Tag{
+			{
+				Key:   []byte("foo"),
+				Value: []byte("0.4"),
+			},
+			{
+				Key:   []byte("x"),
+				Value: []byte("y"),
+			},
+		}
+		r3 := netstorage.Result{
+			MetricName: metricNameExpected,
+			Values:     []float64{16, 19, 14, 16, 16, 18},
+			Timestamps: timestampsExpected,
+		}
+		r3.MetricName.Tags = []storage.Tag{
+			{
+				Key:   []byte("foo"),
+				Value: []byte("0.8"),
+			},
+			{
+				Key:   []byte("x"),
+				Value: []byte("y"),
+			},
+		}
+		resultExpected := []netstorage.Result{r1, r2, r3}
+		f(q, resultExpected)
+	})
 	t.Run(`histogram_over_time`, func(t *testing.T) {
 		t.Parallel()
 		q := `sort_by_label(histogram_over_time(alias(label_set(rand(0)*1.3+1.1, "foo", "bar"), "xxx")[200s:5s]), "vmrange")`

app/vmselect/promql/rollup.go

@@ -4,12 +4,14 @@ import (
 	"flag"
 	"fmt"
 	"math"
+	"strconv"
 	"strings"
 	"sync"
 
 	"github.com/VictoriaMetrics/metrics"
 	"github.com/VictoriaMetrics/metricsql"
 
+	"github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/decimal"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/logger"
 	"github.com/VictoriaMetrics/VictoriaMetrics/lib/storage"
@@ -31,6 +33,7 @@ var rollupFuncs = map[string]newRollupFunc{
 	"count_le_over_time":      newRollupCountLE,
 	"count_ne_over_time":      newRollupCountNE,
 	"count_over_time":         newRollupFuncOneArg(rollupCount),
+	"count_values_over_time":  newRollupCountValues,
 	"decreases_over_time":     newRollupFuncOneArg(rollupDecreases),
 	"default_rollup":          newRollupFuncOneArg(rollupDefault), // default rollup func
 	"delta":                   newRollupFuncOneArg(rollupDelta),
@@ -103,6 +106,42 @@ var rollupFuncs = map[string]newRollupFunc{
 	"zscore_over_time":       newRollupFuncOneArg(rollupZScoreOverTime),
 }
 
+// Functions, which need the previous sample before the lookbehind window for proper calculations.
+//
+// All the rollup functions, which do not rely on the previous sample
+// before the lookbehind window (aka prevValue and realPrevValue), do not need silence interval.
+var needSilenceIntervalForRollupFunc = map[string]bool{
+	"ascent_over_time":    true,
+	"changes":             true,
+	"decreases_over_time": true,
+	// The default_rollup implicitly relies on the previous samples in order to fill gaps.
+	// See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5388
+	"default_rollup":         true,
+	"delta":                  true,
+	"deriv_fast":             true,
+	"descent_over_time":      true,
+	"idelta":                 true,
+	"ideriv":                 true,
+	"increase":               true,
+	"increase_pure":          true,
+	"increases_over_time":    true,
+	"integrate":              true,
+	"irate":                  true,
+	"lag":                    true,
+	"lifetime":               true,
+	"rate":                   true,
+	"resets":                 true,
+	"rollup":                 true,
+	"rollup_candlestick":     true,
+	"rollup_delta":           true,
+	"rollup_deriv":           true,
+	"rollup_increase":        true,
+	"rollup_rate":            true,
+	"rollup_scrape_interval": true,
+	"scrape_interval":        true,
+	"tlast_change_over_time": true,
+}
+
 // rollupAggrFuncs are functions that can be passed to `aggr_over_time()`
 var rollupAggrFuncs = map[string]rollupFunc{
 	"absent_over_time":        rollupAbsent,
@@ -573,7 +612,7 @@ type timeseriesMap struct {
 func newTimeseriesMap(funcName string, keepMetricNames bool, sharedTimestamps []int64, mnSrc *storage.MetricName) *timeseriesMap {
 	funcName = strings.ToLower(funcName)
 	switch funcName {
-	case "histogram_over_time", "quantiles_over_time":
+	case "histogram_over_time", "quantiles_over_time", "count_values_over_time":
 	default:
 		return nil
 	}
@@ -607,10 +646,16 @@ func (tsm *timeseriesMap) GetOrCreateTimeseries(labelName, labelValue string) *t
 	if ts != nil {
 		return ts
 	}
+
+	// Make a clone of labelValue in order to use it as map key, since it may point to unsafe string,
+	// which refers some other byte slice, which can change in the future.
+	labelValue = strings.Clone(labelValue)
+
 	ts = &timeseries{}
 	ts.CopyFromShallowTimestamps(tsm.origin)
 	ts.MetricName.RemoveTag(labelName)
 	ts.MetricName.AddTag(labelName, labelValue)
+
 	tsm.m[labelValue] = ts
 	return ts
 }
@@ -957,7 +1002,7 @@ func newRollupHoltWinters(args []interface{}) (rollupFunc, error) {
 		// before calling rollup funcs.
 		values := rfa.values
 		if len(values) == 0 {
-			return rfa.prevValue
+			return nan
 		}
 		sf := sfs[rfa.idx]
 		if sf < 0 || sf > 1 {
@@ -1400,6 +1445,42 @@ func mad(values []float64) float64 {
 	return v
 }
 
+func newRollupCountValues(args []interface{}) (rollupFunc, error) {
+	if err := expectRollupArgsNum(args, 2); err != nil {
+		return nil, err
+	}
+	tssLabelNum, ok := args[0].([]*timeseries)
+	if !ok {
+		return nil, fmt.Errorf(`unexpected type for labelName arg; got %T; want %T`, args[0], tssLabelNum)
+	}
+	labelName, err := getString(tssLabelNum, 0)
+	if err != nil {
+		return nil, fmt.Errorf("cannot get labelName: %w", err)
+	}
+	f := func(rfa *rollupFuncArg) float64 {
+		tsm := rfa.tsm
+		idx := rfa.idx
+		bb := bbPool.Get()
+		// Note: the code below may create very big number of time series
+		// if the number of unique values in rfa.values is big.
+		for _, v := range rfa.values {
+			bb.B = strconv.AppendFloat(bb.B[:0], v, 'g', -1, 64)
+			labelValue := bytesutil.ToUnsafeString(bb.B)
+			ts := tsm.GetOrCreateTimeseries(labelName, labelValue)
+			count := ts.Values[idx]
+			if math.IsNaN(count) {
+				count = 1
+			} else {
+				count++
+			}
+			ts.Values[idx] = count
+		}
+		bbPool.Put(bb)
+		return nan
+	}
+	return f, nil
+}
+
 func rollupHistogram(rfa *rollupFuncArg) float64 {
 	values := rfa.values
 	tsm := rfa.tsm
@@ -1586,11 +1667,7 @@ func rollupRateOverSum(rfa *rollupFuncArg) float64 {
 	// before calling rollup funcs.
 	timestamps := rfa.timestamps
 	if len(timestamps) == 0 {
-		if math.IsNaN(rfa.prevValue) {
-			return nan
-		}
-		// Assume that the value didn't change since rfa.prevValue.
-		return 0
+		return nan
 	}
 	sum := float64(0)
 	for _, v := range rfa.values {
@@ -1610,7 +1687,7 @@ func rollupSum2(rfa *rollupFuncArg) float64 {
 	// before calling rollup funcs.
 	values := rfa.values
 	if len(values) == 0 {
-		return rfa.prevValue * rfa.prevValue
+		return nan
 	}
 	var sum2 float64
 	for _, v := range values {
@@ -1624,7 +1701,7 @@ func rollupGeomean(rfa *rollupFuncArg) float64 {
 	// before calling rollup funcs.
 	values := rfa.values
 	if len(values) == 0 {
-		return rfa.prevValue
+		return nan
 	}
 	p := 1.0
 	for _, v := range values {
@@ -2268,10 +2345,7 @@ func rollupDistinct(rfa *rollupFuncArg) float64 {
 	// before calling rollup funcs.
 	values := rfa.values
 	if len(values) == 0 {
-		if math.IsNaN(rfa.prevValue) {
-			return nan
-		}
-		return 0
+		return nan
 	}
 	m := make(map[float64]struct{})
 	for _, v := range values {

app/vmselect/promql/rollup_result_cache.go

@@ -45,7 +45,7 @@ func ResetRollupResultCacheIfNeeded(mrs []storage.MetricRow) {
 		rollupResultResetMetricRowSample.Store(&storage.MetricRow{})
 		go checkRollupResultCacheReset()
 	})
-	if atomic.LoadUint32(&needRollupResultCacheReset) != 0 {
+	if needRollupResultCacheReset.Load() {
 		// The cache has been already instructed to reset.
 		return
 	}
@@ -63,14 +63,14 @@ func ResetRollupResultCacheIfNeeded(mrs []storage.MetricRow) {
 	}
 	if needCacheReset {
 		// Do not call ResetRollupResultCache() here, since it may be heavy when frequently called.
-		atomic.StoreUint32(&needRollupResultCacheReset, 1)
+		needRollupResultCacheReset.Store(true)
 	}
 }
 
 func checkRollupResultCacheReset() {
 	for {
 		time.Sleep(checkRollupResultCacheResetInterval)
-		if atomic.SwapUint32(&needRollupResultCacheReset, 0) > 0 {
+		if needRollupResultCacheReset.Swap(false) {
 			mr := rollupResultResetMetricRowSample.Load()
 			d := int64(fasttime.UnixTimestamp()*1000) - mr.Timestamp - cacheTimestampOffset.Milliseconds()
 			logger.Warnf("resetting rollup result cache because the metric %s has a timestamp older than -search.cacheTimestampOffset=%s by %.3fs",
@@ -82,7 +82,7 @@ func checkRollupResultCacheReset() {
 
 const checkRollupResultCacheResetInterval = 5 * time.Second
 
-var needRollupResultCacheReset uint32
+var needRollupResultCacheReset atomic.Bool
 var checkRollupResultCacheResetOnce sync.Once
 var rollupResultResetMetricRowSample atomic.Pointer[storage.MetricRow]
 
@@ -129,7 +129,7 @@ func InitRollupResultCache(cachePath string) {
 		mustLoadRollupResultCacheKeyPrefix(rollupResultCachePath)
 	} else {
 		c = workingsetcache.New(cacheSize)
-		rollupResultCacheKeyPrefix = newRollupResultCacheKeyPrefix()
+		rollupResultCacheKeyPrefix.Store(newRollupResultCacheKeyPrefix())
 	}
 	if *disableCache {
 		c.Reset()
@@ -211,7 +211,7 @@ var rollupResultCacheResets = metrics.NewCounter(`vm_cache_resets_total{type="pr
 // ResetRollupResultCache resets rollup result cache.
 func ResetRollupResultCache() {
 	rollupResultCacheResets.Inc()
-	atomic.AddUint64(&rollupResultCacheKeyPrefix, 1)
+	rollupResultCacheKeyPrefix.Add(1)
 	logger.Infof("rollupResult cache has been cleared")
 }
 
@@ -438,8 +438,8 @@ func (rrc *rollupResultCache) PutSeries(qt *querytracer.Tracer, ec *EvalConfig,
 	}
 
 	var key rollupResultCacheKey
-	key.prefix = rollupResultCacheKeyPrefix
-	key.suffix = atomic.AddUint64(&rollupResultCacheKeySuffix, 1)
+	key.prefix = rollupResultCacheKeyPrefix.Load()
+	key.suffix = rollupResultCacheKeySuffix.Add(1)
 
 	bb := bbPool.Get()
 	bb.B = key.Marshal(bb.B[:0])
@@ -455,8 +455,12 @@ func (rrc *rollupResultCache) PutSeries(qt *querytracer.Tracer, ec *EvalConfig,
 }
 
 var (
-	rollupResultCacheKeyPrefix uint64
-	rollupResultCacheKeySuffix = uint64(time.Now().UnixNano())
+	rollupResultCacheKeyPrefix atomic.Uint64
+	rollupResultCacheKeySuffix = func() *atomic.Uint64 {
+		var x atomic.Uint64
+		x.Store(uint64(time.Now().UnixNano()))
+		return &x
+	}()
 )
 
 func (rrc *rollupResultCache) getSeriesFromCache(qt *querytracer.Tracer, key []byte) ([]*timeseries, bool) {
@@ -517,26 +521,26 @@ func newRollupResultCacheKeyPrefix() uint64 {
 func mustLoadRollupResultCacheKeyPrefix(path string) {
 	path = path + ".key.prefix"
 	if !fs.IsPathExist(path) {
-		rollupResultCacheKeyPrefix = newRollupResultCacheKeyPrefix()
+		rollupResultCacheKeyPrefix.Store(newRollupResultCacheKeyPrefix())
 		return
 	}
 	data, err := os.ReadFile(path)
 	if err != nil {
 		logger.Errorf("cannot load %s: %s; reset rollupResult cache", path, err)
-		rollupResultCacheKeyPrefix = newRollupResultCacheKeyPrefix()
+		rollupResultCacheKeyPrefix.Store(newRollupResultCacheKeyPrefix())
 		return
 	}
 	if len(data) != 8 {
 		logger.Errorf("unexpected size of %s; want 8 bytes; got %d bytes; reset rollupResult cache", path, len(data))
-		rollupResultCacheKeyPrefix = newRollupResultCacheKeyPrefix()
+		rollupResultCacheKeyPrefix.Store(newRollupResultCacheKeyPrefix())
 		return
 	}
-	rollupResultCacheKeyPrefix = encoding.UnmarshalUint64(data)
+	rollupResultCacheKeyPrefix.Store(encoding.UnmarshalUint64(data))
 }
 
 func mustSaveRollupResultCacheKeyPrefix(path string) {
 	path = path + ".key.prefix"
-	data := encoding.MarshalUint64(nil, rollupResultCacheKeyPrefix)
+	data := encoding.MarshalUint64(nil, rollupResultCacheKeyPrefix.Load())
 	fs.MustWriteAtomic(path, data, true)
 }
 
@@ -552,7 +556,7 @@ const (
 
 func marshalRollupResultCacheKeyForSeries(dst []byte, expr metricsql.Expr, window, step int64, etfs [][]storage.TagFilter) []byte {
 	dst = append(dst, rollupResultCacheVersion)
-	dst = encoding.MarshalUint64(dst, rollupResultCacheKeyPrefix)
+	dst = encoding.MarshalUint64(dst, rollupResultCacheKeyPrefix.Load())
 	dst = append(dst, rollupResultCacheTypeSeries)
 	dst = encoding.MarshalInt64(dst, window)
 	dst = encoding.MarshalInt64(dst, step)
@@ -563,7 +567,7 @@ func marshalRollupResultCacheKeyForSeries(dst []byte, expr metricsql.Expr, windo
 
 func marshalRollupResultCacheKeyForInstantValues(dst []byte, expr metricsql.Expr, window, step int64, etfs [][]storage.TagFilter) []byte {
 	dst = append(dst, rollupResultCacheVersion)
-	dst = encoding.MarshalUint64(dst, rollupResultCacheKeyPrefix)
+	dst = encoding.MarshalUint64(dst, rollupResultCacheKeyPrefix.Load())
 	dst = append(dst, rollupResultCacheTypeInstantValues)
 	dst = encoding.MarshalInt64(dst, window)
 	dst = encoding.MarshalInt64(dst, step)

app/vmselect/promql/timeseries.go

@@ -2,7 +2,6 @@ package promql
 
 import (
 	"fmt"
-	"reflect"
 	"sort"
 	"strconv"
 	"sync"
@@ -308,60 +307,32 @@ func unmarshalBytesFast(src []byte) ([]byte, []byte, error) {
 	return src[n:], src[:n], nil
 }
 
-func float64ToByteSlice(a []float64) (b []byte) {
-	if len(a) == 0 {
-		return nil
-	}
-	sh := (*reflect.SliceHeader)(unsafe.Pointer(&b))
-	sh.Data = uintptr(unsafe.Pointer(&a[0]))
-	sh.Len = len(a) * int(unsafe.Sizeof(a[0]))
-	sh.Cap = sh.Len
-	return
+func float64ToByteSlice(a []float64) []byte {
+	return unsafe.Slice((*byte)(unsafe.Pointer(unsafe.SliceData(a))), len(a)*8)
 }
 
-func int64ToByteSlice(a []int64) (b []byte) {
-	if len(a) == 0 {
-		return nil
-	}
-	sh := (*reflect.SliceHeader)(unsafe.Pointer(&b))
-	sh.Data = uintptr(unsafe.Pointer(&a[0]))
-	sh.Len = len(a) * int(unsafe.Sizeof(a[0]))
-	sh.Cap = sh.Len
-	return
+func int64ToByteSlice(a []int64) []byte {
+	return unsafe.Slice((*byte)(unsafe.Pointer(unsafe.SliceData(a))), len(a)*8)
 }
 
-func byteSliceToInt64(b []byte) (a []int64) {
-	if len(b) == 0 {
-		return nil
-	}
-	sh := (*reflect.SliceHeader)(unsafe.Pointer(&a))
-	sh.Data = uintptr(unsafe.Pointer(&b[0]))
-	sh.Len = len(b) / int(unsafe.Sizeof(a[0]))
-	sh.Cap = sh.Len
+func byteSliceToInt64(b []byte) []int64 {
 	// Make sure that the returned slice is properly aligned to 8 bytes.
 	// This prevents from SIGBUS error on arm architectures, which deny unaligned access.
 	// See https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3927
-	if sh.Data%8 != 0 {
+	if uintptr(unsafe.Pointer(unsafe.SliceData(b)))%8 != 0 {
 		logger.Panicf("BUG: the input byte slice b must be aligned to 8 bytes")
 	}
-	return
+	return unsafe.Slice((*int64)(unsafe.Pointer(unsafe.SliceData(b))), len(b)/8)
 }
 
-func byteSliceToFloat64(b []byte) (a []float64) {
-	if len(b) == 0 {
-		return nil
-	}
-	sh := (*reflect.SliceHeader)(unsafe.Pointer(&a))
-	sh.Data = uintptr(unsafe.Pointer(&b[0]))
-	sh.Len = len(b) / int(unsafe.Sizeof(a[0]))
-	sh.Cap = sh.Len
+func byteSliceToFloat64(b []byte) []float64 {
 	// Make sure that the returned slice is properly aligned to 8 bytes.
 	// This prevents from SIGBUS error on arm architectures, which deny unaligned access.
 	// See https://github.com/VictoriaMetrics/VictoriaMetrics/pull/3927
-	if sh.Data%8 != 0 {
+	if uintptr(unsafe.Pointer(unsafe.SliceData(b)))%8 != 0 {
 		logger.Panicf("BUG: the input byte slice b must be aligned to 8 bytes")
 	}
-	return
+	return unsafe.Slice((*float64)(unsafe.Pointer(unsafe.SliceData(b))), len(b)/8)
 }
 
 func stringMetricName(mn *storage.MetricName) string {

app/vmselect/promql/timeseries_test.go

@@ -52,7 +52,9 @@ func TestMarshalTimeseriesFast(t *testing.T) {
 		MetricName: storage.MetricName{
 			MetricGroup: []byte{},
 		},
-		denyReuse: true,
+		Values:     []float64{},
+		Timestamps: []int64{},
+		denyReuse:  true,
 	}})
 	f([]*timeseries{{
 		MetricName: storage.MetricName{

app/vmselect/promql/transform.go

@@ -1940,8 +1940,7 @@ func transformLabelJoin(tfa *transformFuncArg) ([]*timeseries, error) {
 	for _, ts := range rvs {
 		mn := &ts.MetricName
 		dstValue := getDstValue(mn, dstLabel)
-		b := *dstValue
-		b = b[:0]
+		var b []byte
 		for j, srcLabel := range srcLabels {
 			srcValue := mn.GetTagValue(srcLabel)
 			b = append(b, srcValue...)

app/vmselect/searchutils/searchutils.go

@@ -17,6 +17,8 @@ var (
 	maxExportDuration        = flag.Duration("search.maxExportDuration", time.Hour*24*30, "The maximum duration for /api/v1/export call")
 	maxQueryDuration         = flag.Duration("search.maxQueryDuration", time.Second*30, "The maximum duration for query execution")
 	maxStatusRequestDuration = flag.Duration("search.maxStatusRequestDuration", time.Minute*5, "The maximum duration for /api/v1/status/* requests")
+	maxLabelsAPIDuration     = flag.Duration("search.maxLabelsAPIDuration", time.Second*5, "The maximum duration for /api/v1/labels, /api/v1/label/.../values and /api/v1/series requests. "+
+		"See also -search.maxLabelsAPISeries and -search.ignoreExtraFiltersAtLabelsAPI")
 )
 
 // GetMaxQueryDuration returns the maximum duration for query from r.
@@ -50,6 +52,12 @@ func GetDeadlineForExport(r *http.Request, startTime time.Time) Deadline {
 	return getDeadlineWithMaxDuration(r, startTime, dMax, "-search.maxExportDuration")
 }
 
+// GetDeadlineForLabelsAPI returns deadline for the given request to /api/v1/labels, /api/v1/label/.../values or /api/v1/series
+func GetDeadlineForLabelsAPI(r *http.Request, startTime time.Time) Deadline {
+	dMax := maxLabelsAPIDuration.Milliseconds()
+	return getDeadlineWithMaxDuration(r, startTime, dMax, "-search.maxLabelsAPIDuration")
+}
+
 func getDeadlineWithMaxDuration(r *http.Request, startTime time.Time, dMax int64, flagHint string) Deadline {
 	d, err := httputils.GetDuration(r, "timeout", 0)
 	if err != nil {

app/vmselect/vmui/asset-manifest.json

@@ -1,13 +1,13 @@
 {
   "files": {
-    "main.css": "./static/css/main.be4fee7a.css",
-    "main.js": "./static/js/main.fd9d9e16.js",
-    "static/js/522.da77e7b3.chunk.js": "./static/js/522.da77e7b3.chunk.js",
-    "static/media/MetricsQL.md": "./static/media/MetricsQL.8a01ddf56e4e6bc1ccf1.md",
+    "main.css": "./static/css/main.dee51b1d.css",
+    "main.js": "./static/js/main.81b9e607.js",
+    "static/js/685.bebe1265.chunk.js": "./static/js/685.bebe1265.chunk.js",
+    "static/media/MetricsQL.md": "./static/media/MetricsQL.61a686c0661a23e4f2eb.md",
     "index.html": "./index.html"
   },
   "entrypoints": [
-    "static/css/main.be4fee7a.css",
-    "static/js/main.fd9d9e16.js"
+    "static/css/main.dee51b1d.css",
+    "static/js/main.81b9e607.js"
   ]
 }

app/vmselect/vmui/index.html

@@ -1 +1 @@
-<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.fd9d9e16.js"></script><link href="./static/css/main.be4fee7a.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
+<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="./favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1,maximum-scale=5"/><meta name="theme-color" content="#000000"/><meta name="description" content="UI for VictoriaMetrics"/><link rel="apple-touch-icon" href="./apple-touch-icon.png"/><link rel="icon" type="image/png" sizes="32x32" href="./favicon-32x32.png"><link rel="manifest" href="./manifest.json"/><title>VM UI</title><script src="./dashboards/index.js" type="module"></script><meta name="twitter:card" content="summary_large_image"><meta name="twitter:image" content="./preview.jpg"><meta name="twitter:title" content="UI for VictoriaMetrics"><meta name="twitter:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta name="twitter:site" content="@VictoriaMetrics"><meta property="og:title" content="Metric explorer for VictoriaMetrics"><meta property="og:description" content="Explore and troubleshoot your VictoriaMetrics data"><meta property="og:image" content="./preview.jpg"><meta property="og:type" content="website"><script defer="defer" src="./static/js/main.81b9e607.js"></script><link href="./static/css/main.dee51b1d.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>

app/vmselect/vmui/static/js/main.81b9e607.js.LICENSE.txt

@@ -4,10 +4,8 @@
 	http://jedwatson.github.io/classnames
 */
 
-/*! regenerator-runtime -- Copyright (c) 2014-present, Facebook, Inc. -- license (MIT): https://github.com/facebook/regenerator/blob/main/LICENSE */
-
 /**
- * @remix-run/router v1.10.0
+ * @remix-run/router v1.15.1
  *
  * Copyright (c) Remix Software Inc.
  *
@@ -18,7 +16,7 @@
  */
 
 /**
- * React Router DOM v6.17.0
+ * React Router DOM v6.22.1
  *
  * Copyright (c) Remix Software Inc.
  *
@@ -29,7 +27,7 @@
  */
 
 /**
- * React Router v6.17.0
+ * React Router v6.22.1
  *
  * Copyright (c) Remix Software Inc.
  *

app/vmselect/vmui/static/media/MetricsQL.61a686c0661a23e4f2eb.md

@@ -26,12 +26,18 @@ and introduction into [basic querying via MetricsQL](https://docs.victoriametric
 
 The following functionality is implemented differently in MetricsQL compared to PromQL. This improves user experience:
 
-* MetricsQL takes into account the previous point before the window in square brackets for range functions such as [rate](#rate) and [increase](#increase).
-  This allows returning the exact results users expect for `increase(metric[$__interval])` queries instead of incomplete results Prometheus returns for such queries.
-* MetricsQL doesn't extrapolate range function results. This addresses [this issue from Prometheus](https://github.com/prometheus/prometheus/issues/3746).
+* MetricsQL takes into account the last [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) before the lookbehind window
+  in square brackets for [increase](#increase) and [rate](#rate) functions. This allows returning the exact results users expect for `increase(metric[$__interval])` queries
+  instead of incomplete results Prometheus returns for such queries. Prometheus misses the increase between the last sample before the lookbehind window
+  and the first sample inside the lookbehind window.
+* MetricsQL doesn't extrapolate [rate](#rate) and [increase](#increase) function results, so it always returns the expected results. For example, it returns
+  integer results from `increase()` over slow-changing integer counter. Prometheus in this case returns unexpected fractional results,
+  which may significantly differ from the expected results. This addresses [this issue from Prometheus](https://github.com/prometheus/prometheus/issues/3746).
   See technical details about VictoriaMetrics and Prometheus calculations for [rate](#rate)
   and [increase](#increase) [in this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1215#issuecomment-850305711).
-* MetricsQL returns the expected non-empty responses for [rate](#rate) with `step` values smaller than scrape interval.
+* MetricsQL returns the expected non-empty responses for [rate](#rate) function when Grafana or [vmui](https://docs.victoriametrics.com/#vmui)
+  passes `step` values smaller than the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+  to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
   This addresses [this issue from Grafana](https://github.com/grafana/grafana/issues/11451).
   See also [this blog post](https://www.percona.com/blog/2020/02/28/better-prometheus-rate-function-with-victoriametrics/).
 * MetricsQL treats `scalar` type the same as `instant vector` without labels, since subtle differences between these types usually confuse users.
@@ -61,16 +67,17 @@ The list of MetricsQL features on top of PromQL:
 
 * Graphite-compatible filters can be passed via `{__graphite__="foo.*.bar"}` syntax.
   See [these docs](https://docs.victoriametrics.com/#selecting-graphite-metrics).
-  VictoriaMetrics also can be used as Graphite datasource in Grafana.
-  See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
+  VictoriaMetrics can be used as Graphite datasource in Grafana. See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
   See also [label_graphite_group](#label_graphite_group) function, which can be used for extracting the given groups from Graphite metric name.
-* Lookbehind window in square brackets may be omitted. VictoriaMetrics automatically selects the lookbehind window
-  depending on the current step used for building the graph (e.g. `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)).
+* Lookbehind window in square brackets for [rollup functions](#rollup-functions) may be omitted. VictoriaMetrics automatically selects the lookbehind window
+  depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
+  and the real interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) (aka `scrape_interval`).
   For instance, the following query is valid in VictoriaMetrics: `rate(node_network_receive_bytes_total)`.
-  It is equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
+  It is roughly equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
+  The difference is documented in [rate() docs](#rate).
 * Numeric values can contain `_` delimiters for better readability. For example, `1_234_567_890` can be used in queries instead of `1234567890`.
 * [Series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
-  selects series with either `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
+  selects series with `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
   See [these docs](https://docs.victoriametrics.com/keyConcepts.html#filtering-by-multiple-or-filters) for details.
 * Support for `group_left(*)` and `group_right(*)` for copying all the labels from time series on the `one` side
   of [many-to-one operations](https://prometheus.io/docs/prometheus/latest/querying/operators/#many-to-one-and-one-to-many-vector-matches).
@@ -117,7 +124,8 @@ The list of MetricsQL features on top of PromQL:
   Go to [WITH templates playground](https://play.victoriametrics.com/select/accounting/1/6a716b0f-38bc-4856-90ce-448fd713e3fe/expand-with-exprs) and try it.
 * String literals may be concatenated. This is useful with `WITH` templates:
   `WITH (commonPrefix="long_metric_prefix_") {__name__=commonPrefix+"suffix1"} / {__name__=commonPrefix+"suffix2"}`.
-* `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions), [transform functions](#transform-functions) and [binary operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#binary-operators).
+* `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions), [transform functions](#transform-functions)
+  and [binary operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#binary-operators).
   This modifier prevents from dropping metric names in function results. See [these docs](#keep_metric_names).
 
 ## keep_metric_names
@@ -155,14 +163,15 @@ Additional details:
   The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
 * If the given [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) returns multiple time series,
   then rollups are calculated individually per each returned series.
-* If lookbehind window in square brackets is missing, then MetricsQL automatically sets the lookbehind window
-  to the interval between points on the graph (aka `step` query arg at [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query),
-  `$__interval` value from Grafana or `1i` duration in MetricsQL).
-  For example, `rate(http_requests_total)` is equivalent to `rate(http_requests_total[$__interval])` in Grafana.
-  It is also equivalent to `rate(http_requests_total[1i])`.
+* If lookbehind window in square brackets is missing, then it is automatically set to the following value:
+  - To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
+    for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
+    For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
+  - To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+    for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
 * Every [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) in MetricsQL must be wrapped into a rollup function.
   Otherwise, it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}`
-  is automatically converted to `default_rollup(foo{bar="baz"}[1i])` before performing the calculations.
+  is automatically converted to `default_rollup(foo{bar="baz"})` before performing the calculations.
 * If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) is passed to rollup function,
   then the inner arg is automatically converted to a [subquery](#subqueries).
 * All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results.
@@ -177,7 +186,9 @@ The list of supported rollup functions:
 `absent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns 1
 if the given lookbehind window `d` doesn't contain raw samples. Otherwise, it returns an empty result.
 
-This function is supported by PromQL. See also [present_over_time](#present_over_time).
+This function is supported by PromQL.
+
+See also [present_over_time](#present_over_time).
 
 #### aggr_over_time
 
@@ -207,7 +218,9 @@ See also [descent_over_time](#descent_over_time).
 over raw samples on the given lookbehind window `d` per each time series returned
 from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [median_over_time](#median_over_time).
+This function is supported by PromQL.
+
+See also [median_over_time](#median_over_time).
 
 #### changes
 
@@ -220,7 +233,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [changes_prometheus](#changes_prometheus).
+This function is supported by PromQL.
+
+See also [changes_prometheus](#changes_prometheus).
 
 #### changes_prometheus
 
@@ -233,7 +248,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [changes](#changes).
+This function is supported by PromQL.
+
+See also [changes](#changes).
 
 #### count_eq_over_time
 
@@ -243,7 +260,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [count_over_time](#count_over_time).
+See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_over_time) and [count_values_over_time](#count_values_over_time).
 
 #### count_gt_over_time
 
@@ -253,7 +270,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [count_over_time](#count_over_time).
+See also [count_over_time](#count_over_time) and [share_gt_over_time](#share_gt_over_time).
 
 #### count_le_over_time
 
@@ -263,7 +280,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [count_over_time](#count_over_time).
+See also [count_over_time](#count_over_time) and [share_le_over_time](#share_le_over_time).
 
 #### count_ne_over_time
 
@@ -282,8 +299,19 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time),
-[count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
+This function is supported by PromQL.
+
+See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time), [count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
+
+#### count_values_over_time
+
+`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples
+with the same value over the given lookbehind window and stores the counts in a time series with an additional `label`, which contains each initial value.
+The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
+
+Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
+
+See also [count_eq_over_time](#count_eq_over_time), [count_values](#count_values) and [distinct_over_time](#distinct_over_time) and [label_match](#label_match).
 
 #### decreases_over_time
 
@@ -299,6 +327,11 @@ See also [increases_over_time](#increases_over_time).
 `default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
 per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
+If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
+passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
+while `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the selected time series.
+This allows avoiding unexpected gaps on the graph when `step` is smaller than the `scrape_interval`.
+
 #### delta
 
 `delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
@@ -310,7 +343,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
+This function is supported by PromQL.
+
+See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
 
 #### delta_prometheus
 
@@ -333,7 +368,9 @@ The derivative is calculated using linear regression.
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
+This function is supported by PromQL.
+
+See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
 
 #### deriv_fast
 
@@ -364,6 +401,8 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
+See also [count_values_over_time](#count_values_over_time).
+
 #### duration_over_time
 
 `duration_over_time(series_selector[d], max_interval)` is a [rollup function](#rollup-functions), which returns the duration in seconds
@@ -423,7 +462,9 @@ over the given lookbehind window `d` using the given smoothing factor `sf` and t
 Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
 returns time series of [gauge type](https://docs.victoriametrics.com/keyConcepts.html#gauge).
 
-This function is supported by PromQL. See also [range_linear_regression](#range_linear_regression).
+This function is supported by PromQL.
+
+See also [range_linear_regression](#range_linear_regression).
 
 #### idelta
 
@@ -432,7 +473,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [delta](#delta).
+This function is supported by PromQL.
+
+See also [delta](#delta).
 
 #### ideriv
 
@@ -455,7 +498,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
+This function is supported by PromQL.
+
+See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
 
 #### increase_prometheus
 
@@ -499,7 +544,9 @@ It is expected that the `series_selector` returns time series of [counter type](
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [rate](#rate) and [rollup_rate](#rollup_rate).
+This function is supported by PromQL.
+
+See also [rate](#rate) and [rollup_rate](#rollup_rate).
 
 #### lag
 
@@ -516,7 +563,9 @@ See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
 `last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
 per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_time).
+This function is supported by PromQL.
+
+See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_time).
 
 #### lifetime
 
@@ -539,7 +588,9 @@ See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outli
 `max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over raw samples
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [tmax_over_time](#tmax_over_time).
+This function is supported by PromQL.
+
+See also [tmax_over_time](#tmax_over_time).
 
 #### median_over_time
 
@@ -554,7 +605,9 @@ See also [avg_over_time](#avg_over_time).
 `min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over raw samples
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [tmin_over_time](#tmin_over_time).
+This function is supported by PromQL.
+
+See also [tmin_over_time](#tmin_over_time).
 
 #### mode_over_time
 
@@ -580,7 +633,9 @@ See also [outliers_iqr](#outliers_iqr).
 linear interpolation over raw samples on the given lookbehind window `d`. The predicted value is calculated individually per each time series
 returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [range_linear_regression](#range_linear_regression).
+This function is supported by PromQL.
+
+See also [range_linear_regression](#range_linear_regression).
 
 #### present_over_time
 
@@ -597,7 +652,9 @@ This function is supported by PromQL.
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 The `phi` value must be in the range `[0...1]`.
 
-This function is supported by PromQL. See also [quantiles_over_time](#quantiles_over_time).
+This function is supported by PromQL.
+
+See also [quantiles_over_time](#quantiles_over_time).
 
 #### quantiles_over_time
 
@@ -622,9 +679,16 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
 over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
 
+If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
+passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
+while `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the selected time series.
+This allows avoiding unexpected gaps on the graph when `step` is smaller than the `scrape_interval`.
+
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [irate](#irate) and [rollup_rate](#rollup_rate).
+This function is supported by PromQL.
+
+See also [irate](#irate) and [rollup_rate](#rollup_rate).
 
 #### rate_over_sum
 
@@ -652,6 +716,7 @@ on the given lookbehind window `d` and returns them in time series with `rollup=
 These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 #### rollup_candlestick
 
@@ -660,7 +725,8 @@ over raw samples on the given lookbehind window `d` and returns them in time ser
 The calculations are performed individually per each time series returned
 from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). This function is useful for financial applications.
 
-Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+Optional 2nd argument `"open"`, `"high"` or `"low"` or `"close"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 #### rollup_delta
 
@@ -670,6 +736,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
@@ -683,6 +750,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
@@ -694,6 +762,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. See also [rollup_delta](#rollup_delta).
 
@@ -707,10 +776,10 @@ See [this article](https://valyala.medium.com/why-irate-from-prometheus-doesnt-c
 when to use `rollup_rate()`.
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
 #### rollup_scrape_interval
@@ -721,6 +790,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. See also [scrape_interval](#scrape_interval).
 
@@ -743,7 +813,7 @@ This function is useful for calculating SLI and SLO. Example: `share_gt_over_tim
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [share_le_over_time](#share_le_over_time).
+See also [share_le_over_time](#share_le_over_time) and [count_gt_over_time](#count_gt_over_time).
 
 #### share_le_over_time
 
@@ -756,7 +826,7 @@ the share of time series values for the last 24 hours when memory usage was belo
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [share_gt_over_time](#share_gt_over_time).
+See also [share_gt_over_time](#share_gt_over_time) and [count_le_over_time](#count_le_over_time).
 
 #### share_eq_over_time
 
@@ -766,6 +836,8 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
+See also [count_eq_over_time](#count_eq_over_time).
+
 #### stale_samples_over_time
 
 `stale_samples_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the number
@@ -781,7 +853,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [stdvar_over_time](#stdvar_over_time).
+This function is supported by PromQL.
+
+See also [stdvar_over_time](#stdvar_over_time).
 
 #### stdvar_over_time
 
@@ -790,7 +864,36 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [stddev_over_time](#stddev_over_time).
+This function is supported by PromQL.
+
+See also [stddev_over_time](#stddev_over_time).
+
+#### sum_eq_over_time
+
+`sum_eq_over_time(series_selector[d], eq)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values equal to `eq`
+on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
+
+Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
+
+See also [sum_over_time](#sum_over_time) and [count_eq_over_time](#count_eq_over_time).
+
+#### sum_gt_over_time
+
+`sum_gt_over_time(series_selector[d], gt)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values bigger than `gt`
+on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
+
+Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
+
+See also [sum_over_time](#sum_over_time) and [count_gt_over_time](#count_gt_over_time).
+
+#### sum_le_over_time
+
+`sum_le_over_time(series_selector[d], le)` is a [rollup function](#rollup-function), which calculates the sum of raw sample values smaller or equal to `le`
+on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
+
+Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
+
+See also [sum_over_time](#sum_over_time) and [count_le_over_time](#count_le_over_time).
 
 #### sum_over_time
 
@@ -815,7 +918,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [timestamp_with_name](#timestamp_with_name).
+This function is supported by PromQL.
+
+See also [time](#time) and [now](#now).
 
 #### timestamp_with_name
 
@@ -824,7 +929,7 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are preserved in the resulting rollups.
 
-See also [timestamp](#timestamp).
+See also [timestamp](#timestamp) and [keep_metric_names](#keep_metric_names) modifier.
 
 #### tfirst_over_time
 
@@ -891,7 +996,7 @@ Additional details:
 
 * If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations.
-  For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature[1i]))`.
+  For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature))`.
 * All the transform functions accept optional `keep_metric_names` modifier. If it is set,
   then the function doesn't drop metric names from the resulting time series. See [these docs](#keep_metric_names).
 
@@ -909,7 +1014,9 @@ This function is supported by PromQL.
 
 `absent(q)` is a [transform function](#transform-functions), which returns 1 if `q` has no points. Otherwise, returns an empty result.
 
-This function is supported by PromQL. See also [absent_over_time](#absent_over_time).
+This function is supported by PromQL.
+
+See also [absent_over_time](#absent_over_time).
 
 #### acos
 
@@ -918,7 +1025,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
+This function is supported by PromQL.
+
+See also [asin](#asin) and [cos](#cos).
 
 #### acosh
 
@@ -927,7 +1036,9 @@ This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sinh](#cosh).
+This function is supported by PromQL.
+
+See also [sinh](#cosh).
 
 #### asin
 
@@ -936,7 +1047,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
+This function is supported by PromQL.
+
+See also [acos](#acos) and [sin](#sin).
 
 #### asinh
 
@@ -945,7 +1058,9 @@ This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sinh](#sinh).
+This function is supported by PromQL.
+
+See also [sinh](#sinh).
 
 #### atan
 
@@ -954,7 +1069,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [tan](#tan).
+This function is supported by PromQL.
+
+See also [tan](#tan).
 
 #### atanh
 
@@ -963,7 +1080,9 @@ This function is supported by PromQL. See also [tan](#tan).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [tanh](#tanh).
+This function is supported by PromQL.
+
+See also [tanh](#tanh).
 
 #### bitmap_and
 
@@ -994,25 +1113,33 @@ See also [prometheus_buckets](#prometheus_buckets) and [histogram_quantile](#his
 
 `ceil(q)` is a [transform function](#transform-functions), which rounds every point for every time series returned by `q` to the upper nearest integer.
 
-This function is supported by PromQL. See also [floor](#floor) and [round](#round).
+This function is supported by PromQL.
+
+See also [floor](#floor) and [round](#round).
 
 #### clamp
 
 `clamp(q, min, max)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `min` and `max` values.
 
-This function is supported by PromQL. See also [clamp_min](#clamp_min) and [clamp_max](#clamp_max).
+This function is supported by PromQL.
+
+See also [clamp_min](#clamp_min) and [clamp_max](#clamp_max).
 
 #### clamp_max
 
 `clamp_max(q, max)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `max` value.
 
-This function is supported by PromQL. See also [clamp](#clamp) and [clamp_min](#clamp_min).
+This function is supported by PromQL.
+
+See also [clamp](#clamp) and [clamp_min](#clamp_min).
 
 #### clamp_min
 
 `clamp_min(q, min)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `min` value.
 
-This function is supported by PromQL. See also [clamp](#clamp) and [clamp_max](#clamp_max).
+This function is supported by PromQL.
+
+See also [clamp](#clamp) and [clamp_max](#clamp_max).
 
 #### cos
 
@@ -1020,7 +1147,9 @@ This function is supported by PromQL. See also [clamp](#clamp) and [clamp_max](#
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sin](#sin).
+This function is supported by PromQL.
+
+See also [sin](#sin).
 
 #### cosh
 
@@ -1029,7 +1158,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [acosh](#acosh).
+This function is supported by PromQL.
+
+See also [acosh](#acosh).
 
 #### day_of_month
 
@@ -1040,6 +1171,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_week](#day_of_week) and [day_of_year](#day_of_year).
+
 #### day_of_week
 
 `day_of_week(q)` is a [transform function](#transform-functions), which returns the day of week for every point of every time series returned by `q`.
@@ -1049,6 +1182,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_month](#day_of_month) and [day_of_year](#day_of_year).
+
 #### day_of_year
 
 `day_of_year(q)` is a [transform function](#transform-functions), which returns the day of year for every point of every time series returned by `q`.
@@ -1058,6 +1193,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_week](#day_of_week) and [day_of_month](#day_of_month).
+
 #### days_in_month
 
 `days_in_month(q)` is a [transform function](#transform-functions), which returns the number of days in the month identified
@@ -1075,7 +1212,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [rad](#rad).
+This function is supported by PromQL.
+
+See also [rad](#rad).
 
 #### drop_empty_series
 
@@ -1101,13 +1240,17 @@ See also [start](#start), [time](#time) and [now](#now).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [ln](#ln).
+This function is supported by PromQL.
+
+See also [ln](#ln).
 
 #### floor
 
 `floor(q)` is a [transform function](#transform-functions), which rounds every point for every time series returned by `q` to the lower nearest integer.
 
-This function is supported by PromQL. See also [ceil](#ceil) and [round](#round).
+This function is supported by PromQL.
+
+See also [ceil](#ceil) and [round](#round).
 
 #### histogram_avg
 
@@ -1130,8 +1273,9 @@ When the [percentile](https://en.wikipedia.org/wiki/Percentile) is calculated ov
 then all the input histograms **must** have buckets with identical boundaries, e.g. they must have the same set of `le` or `vmrange` labels.
 Otherwise, the returned result may be invalid. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3231) for details.
 
-This function is supported by PromQL (except of the `boundLabel` arg). See also [histogram_quantiles](#histogram_quantiles), [histogram_share](#histogram_share)
-and [quantile](#quantile).
+This function is supported by PromQL (except of the `boundLabel` arg).
+
+See also [histogram_quantiles](#histogram_quantiles), [histogram_share](#histogram_share) and [quantile](#quantile).
 
 #### histogram_quantiles
 
@@ -1203,7 +1347,9 @@ This allows implementing simple paging for `q` time series. See also [limitk](#l
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
+This function is supported by PromQL.
+
+See also [exp](#exp) and [log2](#log2).
 
 #### log2
 
@@ -1211,7 +1357,9 @@ This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
+This function is supported by PromQL.
+
+See also [log10](#log10) and [ln](#ln).
 
 #### log10
 
@@ -1219,7 +1367,9 @@ This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [log2](#log2) and [ln](#ln).
+This function is supported by PromQL.
+
+See also [log2](#log2) and [ln](#ln).
 
 #### minute
 
@@ -1258,7 +1408,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [deg](#deg).
+This function is supported by PromQL.
+
+See also [deg](#deg).
 
 #### prometheus_buckets
 
@@ -1386,7 +1538,9 @@ for points returned by `q`, e.g. it is equivalent to the following query: `(q -
 `round(q, nearest)` is a [transform function](#transform-functions), which rounds every point of every time series returned by `q` to the `nearest` multiple.
 If `nearest` is missing then the rounding is performed to the nearest integer.
 
-This function is supported by PromQL. See also [floor](#floor) and [ceil](#ceil).
+This function is supported by PromQL.
+
+See also [floor](#floor) and [ceil](#ceil).
 
 #### ru
 
@@ -1430,7 +1584,9 @@ This function is supported by PromQL.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [cos](#cos).
+This function is supported by MetricsQL.
+
+See also [cos](#cos).
 
 #### sinh
 
@@ -1439,7 +1595,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [cosh](#cosh).
+This function is supported by MetricsQL.
+
+See also [cosh](#cosh).
 
 #### tan
 
@@ -1447,7 +1605,9 @@ This function is supported by MetricsQL. See also [cosh](#cosh).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [atan](#atan).
+This function is supported by MetricsQL.
+
+See also [atan](#atan).
 
 #### tanh
 
@@ -1456,7 +1616,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [atanh](#atanh).
+This function is supported by MetricsQL.
+
+See also [atanh](#atanh).
 
 #### smooth_exponential
 
@@ -1467,13 +1629,17 @@ by `q` using [exponential moving average](https://en.wikipedia.org/wiki/Moving_a
 
 `sort(q)` is a [transform function](#transform-functions), which sorts series in ascending order by the last point in every time series returned by `q`.
 
-This function is supported by PromQL. See also [sort_desc](#sort_desc) and [sort_by_label](#sort_by_label).
+This function is supported by PromQL.
+
+See also [sort_desc](#sort_desc) and [sort_by_label](#sort_by_label).
 
 #### sort_desc
 
 `sort_desc(q)` is a [transform function](#transform-functions), which sorts series in descending order by the last point in every time series returned by `q`.
 
-This function is supported by PromQL. See also [sort](#sort) and [sort_by_label](#sort_by_label_desc).
+This function is supported by PromQL.
+
+See also [sort](#sort) and [sort_by_label](#sort_by_label_desc).
 
 #### sqrt
 
@@ -1502,7 +1668,9 @@ See also [start](#start) and [end](#end).
 
 `time()` is a [transform function](#transform-functions), which returns unix timestamp for every returned point.
 
-This function is supported by PromQL. See also [now](#now), [start](#start) and [end](#end).
+This function is supported by PromQL.
+
+See also [timestamp](#timestamp), [now](#now), [start](#start) and [end](#end).
 
 #### timezone_offset
 
@@ -1551,7 +1719,7 @@ Additional details:
 
 * If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before performing the label transformation.
-  For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature[1i]), "foo")`.
+  For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature), "foo")`.
 
 See also [implicit query conversions](#implicit-query-conversions).
 
@@ -1728,7 +1896,7 @@ Additional details:
   Multiple labels can be put in `by` and `without` modifiers.
 * If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before calculating the aggregate.
-  For example, `count(up)` is implicitly transformed to `count(default_rollup(up[1i]))`.
+  For example, `count(up)` is implicitly transformed to `count(default_rollup(up))`.
 * Aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point
   across time series returned by `q1`, `q2` and `q3`.
 * Aggregate functions support optional `limit N` suffix, which can be used for limiting the number of output groups.
@@ -1756,7 +1924,9 @@ This function is supported by PromQL.
 `bottomk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` points with the smallest values across all the time series returned by `q`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [topk](#topk).
+This function is supported by PromQL.
+
+See also [topk](#topk), [bottomk_min](#bottomk_min) and [#bottomk_last](#bottomk_last).
 
 #### bottomk_avg
 
@@ -1818,10 +1988,14 @@ The aggregate is calculated individually per each group of points with the same
 
 This function is supported by PromQL.
 
+See also [count_values_over_time](#count_values_over_time) and [label_match](#label_match).
+
 #### distinct
 
 `distinct(q)` is [aggregate function](#aggregate-functions), which calculates the number of unique values per each group of points with the same timestamp.
 
+See also [distinct_over_time](#distinct_over_time).
+
 #### geomean
 
 `geomean(q)` is [aggregate function](#aggregate-functions), which calculates geometric mean per each group of points with the same timestamp.
@@ -1913,7 +2087,9 @@ See also [outliers_iqr](#outliers_iqr) and [outliers_mad](#outliers_mad).
 for all the time series returned by `q`. `phi` must be in the range `[0...1]`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [quantiles](#quantiles) and [histogram_quantile](#histogram_quantile).
+This function is supported by PromQL.
+
+See also [quantiles](#quantiles) and [histogram_quantile](#histogram_quantile).
 
 #### quantiles
 
@@ -1972,7 +2148,9 @@ for all the time series returned by `q`. The aggregate is calculated individuall
 `topk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` points with the biggest values across all the time series returned by `q`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [bottomk](#bottomk).
+This function is supported by PromQL.
+
+See also [bottomk](#bottomk), [topk_max](#topk_max) and [topk_last](#topk_last).
 
 #### topk_avg
 
@@ -2032,7 +2210,7 @@ See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_
 MetricsQL supports and extends PromQL subqueries. See [this article](https://valyala.medium.com/prometheus-subqueries-in-victoriametrics-9b1492b720b3) for details.
 Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) form a subquery.
 Nested rollup functions can be implicit thanks to the [implicit query conversions](#implicit-query-conversions).
-For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m[1i]))[1i:1i])`, so it becomes a subquery,
+For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m))[1i:1i])`, so it becomes a subquery,
 since it contains [default_rollup](#default_rollup) nested into [delta](#delta).
 
 VictoriaMetrics performs subqueries in the following way:
@@ -2047,21 +2225,23 @@ VictoriaMetrics performs subqueries in the following way:
 
 VictoriaMetrics performs the following implicit conversions for incoming queries before starting the calculations:
 
-* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions),
-  then `[1i]` is automatically added there. The `[1i]` means one `step` value, which is passed
-  to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
-  It is also known as `$__interval` in Grafana. For example, `rate(http_requests_count)` is automatically transformed to `rate(http_requests_count[1i])`.
+* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions), then it is automatically set to the following value:
+  - To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
+    for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
+    For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
+  - To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+    for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
 * All the [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   which aren't wrapped into [rollup functions](#rollup-functions), are automatically wrapped into [default_rollup](#default_rollup) function.
   Examples:
-  * `foo` is transformed to `default_rollup(foo[1i])`
-  * `foo + bar` is transformed to `default_rollup(foo[1i]) + default_rollup(bar[1i])`
-  * `count(up)` is transformed to `count(default_rollup(up[1i]))`, because [count](#count) isn't a [rollup function](#rollup-functions) -
+  * `foo` is transformed to `default_rollup(foo)`
+  * `foo + bar` is transformed to `default_rollup(foo) + default_rollup(bar)`
+  * `count(up)` is transformed to `count(default_rollup(up))`, because [count](#count) isn't a [rollup function](#rollup-functions) -
     it is [aggregate function](#aggregate-functions)
-  * `abs(temperature)` is transformed to `abs(default_rollup(temperature[1i]))`, because [abs](#abs) isn't a [rollup function](#rollup-functions) -
+  * `abs(temperature)` is transformed to `abs(default_rollup(temperature))`, because [abs](#abs) isn't a [rollup function](#rollup-functions) -
     it is [transform function](#transform-functions)
 * If `step` in square brackets is missing inside [subquery](#subqueries), then `1i` step is automatically added there.
   For example, `avg_over_time(rate(http_requests_total[5m])[1h])` is automatically converted to `avg_over_time(rate(http_requests_total[5m])[1h:1i])`.
 * If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
   is passed to [rollup function](#rollup-functions), then a [subquery](#subqueries) with `1i` lookbehind window and `1i` step is automatically formed.
-  For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up[1i])))[1i:1i])`.
+  For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`.

app/vmstorage/main.go

@@ -26,12 +26,12 @@ import (
 )
 
 var (
-	retentionPeriod       = flagutil.NewDuration("retentionPeriod", "1", "Data with timestamps outside the retentionPeriod is automatically deleted. The minimum retentionPeriod is 24h or 1d. See also -retentionFilter")
-	snapshotAuthKey       = flagutil.NewPassword("snapshotAuthKey", "authKey, which must be passed in query string to /snapshot* pages")
-	forceMergeAuthKey     = flagutil.NewPassword("forceMergeAuthKey", "authKey, which must be passed in query string to /internal/force_merge pages")
-	forceFlushAuthKey     = flagutil.NewPassword("forceFlushAuthKey", "authKey, which must be passed in query string to /internal/force_flush pages")
-	snapshotsMaxAge       = flagutil.NewDuration("snapshotsMaxAge", "0", "Automatically delete snapshots older than -snapshotsMaxAge if it is set to non-zero duration. Make sure that backup process has enough time to finish the backup before the corresponding snapshot is automatically deleted")
-	snapshotCreateTimeout = flag.Duration("snapshotCreateTimeout", 0, "The timeout for creating new snapshot. If set, make sure that timeout is lower than backup period")
+	retentionPeriod   = flagutil.NewDuration("retentionPeriod", "1", "Data with timestamps outside the retentionPeriod is automatically deleted. The minimum retentionPeriod is 24h or 1d. See also -retentionFilter")
+	snapshotAuthKey   = flagutil.NewPassword("snapshotAuthKey", "authKey, which must be passed in query string to /snapshot* pages")
+	forceMergeAuthKey = flagutil.NewPassword("forceMergeAuthKey", "authKey, which must be passed in query string to /internal/force_merge pages")
+	forceFlushAuthKey = flagutil.NewPassword("forceFlushAuthKey", "authKey, which must be passed in query string to /internal/force_flush pages")
+	snapshotsMaxAge   = flagutil.NewDuration("snapshotsMaxAge", "0", "Automatically delete snapshots older than -snapshotsMaxAge if it is set to non-zero duration. Make sure that backup process has enough time to finish the backup before the corresponding snapshot is automatically deleted")
+	_                 = flag.Duration("snapshotCreateTimeout", 0, "Deprecated: this flag does nothing")
 
 	precisionBits = flag.Int("precisionBits", 64, "The number of precision bits to store per each value. Lower precision bits improves data compression at the cost of precision loss")
 
@@ -299,11 +299,7 @@ func RequestHandler(w http.ResponseWriter, r *http.Request) bool {
 	case "/create":
 		snapshotsCreateTotal.Inc()
 		w.Header().Set("Content-Type", "application/json")
-		deadline := uint64(0)
-		if *snapshotCreateTimeout > 0 {
-			deadline = fasttime.UnixTimestamp() + uint64(snapshotCreateTimeout.Seconds())
-		}
-		snapshotPath, err := Storage.CreateSnapshot(deadline)
+		snapshotPath, err := Storage.CreateSnapshot()
 		if err != nil {
 			err = fmt.Errorf("cannot create snapshot: %w", err)
 			jsonResponseError(w, err)
@@ -524,6 +520,7 @@ func writeStorageMetrics(w io.Writer, strg *storage.Storage) {
 
 	metrics.WriteCounterUint64(w, `vm_rows_added_to_storage_total`, m.RowsAddedTotal)
 	metrics.WriteCounterUint64(w, `vm_deduplicated_samples_total{type="merge"}`, m.DedupsDuringMerge)
+	metrics.WriteGaugeUint64(w, `vm_snapshots`, m.SnapshotsCount)
 
 	metrics.WriteCounterUint64(w, `vm_rows_ignored_total{reason="big_timestamp"}`, m.TooBigTimestampRows)
 	metrics.WriteCounterUint64(w, `vm_rows_ignored_total{reason="small_timestamp"}`, m.TooSmallTimestampRows)

app/vmui/Dockerfile-web

@@ -1,4 +1,4 @@
-FROM golang:1.22.0 as build-web-stage
+FROM golang:1.21.7 as build-web-stage
 COPY build /build
 
 WORKDIR /build

app/vmui/packages/vmui/package-lock.json

@@ -30,7 +30,7 @@
         "sass": "^1.56.0",
         "source-map-explorer": "^2.5.3",
         "typescript": "~4.6.2",
-        "uplot": "^1.6.19",
+        "uplot": "^1.6.30",
         "web-vitals": "^3.3.2"
       },
       "devDependencies": {

app/vmui/packages/vmui/package.json

@@ -26,7 +26,7 @@
     "sass": "^1.56.0",
     "source-map-explorer": "^2.5.3",
     "typescript": "~4.6.2",
-    "uplot": "^1.6.19",
+    "uplot": "^1.6.30",
     "web-vitals": "^3.3.2"
   },
   "scripts": {

app/vmui/packages/vmui/src/assets/MetricsQL.md

@@ -26,12 +26,18 @@ and introduction into [basic querying via MetricsQL](https://docs.victoriametric
 
 The following functionality is implemented differently in MetricsQL compared to PromQL. This improves user experience:
 
-* MetricsQL takes into account the previous point before the window in square brackets for range functions such as [rate](#rate) and [increase](#increase).
-  This allows returning the exact results users expect for `increase(metric[$__interval])` queries instead of incomplete results Prometheus returns for such queries.
-* MetricsQL doesn't extrapolate range function results. This addresses [this issue from Prometheus](https://github.com/prometheus/prometheus/issues/3746).
+* MetricsQL takes into account the last [raw sample](https://docs.victoriametrics.com/keyconcepts/#raw-samples) before the lookbehind window
+  in square brackets for [increase](#increase) and [rate](#rate) functions. This allows returning the exact results users expect for `increase(metric[$__interval])` queries
+  instead of incomplete results Prometheus returns for such queries. Prometheus misses the increase between the last sample before the lookbehind window
+  and the first sample inside the lookbehind window.
+* MetricsQL doesn't extrapolate [rate](#rate) and [increase](#increase) function results, so it always returns the expected results. For example, it returns
+  integer results from `increase()` over slow-changing integer counter. Prometheus in this case returns unexpected fractional results,
+  which may significantly differ from the expected results. This addresses [this issue from Prometheus](https://github.com/prometheus/prometheus/issues/3746).
   See technical details about VictoriaMetrics and Prometheus calculations for [rate](#rate)
   and [increase](#increase) [in this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1215#issuecomment-850305711).
-* MetricsQL returns the expected non-empty responses for [rate](#rate) with `step` values smaller than scrape interval.
+* MetricsQL returns the expected non-empty responses for [rate](#rate) function when Grafana or [vmui](https://docs.victoriametrics.com/#vmui)
+  passes `step` values smaller than the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+  to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query).
   This addresses [this issue from Grafana](https://github.com/grafana/grafana/issues/11451).
   See also [this blog post](https://www.percona.com/blog/2020/02/28/better-prometheus-rate-function-with-victoriametrics/).
 * MetricsQL treats `scalar` type the same as `instant vector` without labels, since subtle differences between these types usually confuse users.
@@ -61,13 +67,14 @@ The list of MetricsQL features on top of PromQL:
 
 * Graphite-compatible filters can be passed via `{__graphite__="foo.*.bar"}` syntax.
   See [these docs](https://docs.victoriametrics.com/#selecting-graphite-metrics).
-  VictoriaMetrics also can be used as Graphite datasource in Grafana.
-  See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
+  VictoriaMetrics can be used as Graphite datasource in Grafana. See [these docs](https://docs.victoriametrics.com/#graphite-api-usage) for details.
   See also [label_graphite_group](#label_graphite_group) function, which can be used for extracting the given groups from Graphite metric name.
-* Lookbehind window in square brackets may be omitted. VictoriaMetrics automatically selects the lookbehind window
-  depending on the current step used for building the graph (e.g. `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)).
+* Lookbehind window in square brackets for [rollup functions](#rollup-functions) may be omitted. VictoriaMetrics automatically selects the lookbehind window
+  depending on the `step` query arg passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query)
+  and the real interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) (aka `scrape_interval`).
   For instance, the following query is valid in VictoriaMetrics: `rate(node_network_receive_bytes_total)`.
-  It is equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
+  It is roughly equivalent to `rate(node_network_receive_bytes_total[$__interval])` when used in Grafana.
+  The difference is documented in [rate() docs](#rate).
 * Numeric values can contain `_` delimiters for better readability. For example, `1_234_567_890` can be used in queries instead of `1234567890`.
 * [Series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering) accept multiple `or` filters. For example, `{env="prod",job="a" or env="dev",job="b"}`
   selects series with `{env="prod",job="a"}` or `{env="dev",job="b"}` labels.
@@ -117,7 +124,8 @@ The list of MetricsQL features on top of PromQL:
   Go to [WITH templates playground](https://play.victoriametrics.com/select/accounting/1/6a716b0f-38bc-4856-90ce-448fd713e3fe/expand-with-exprs) and try it.
 * String literals may be concatenated. This is useful with `WITH` templates:
   `WITH (commonPrefix="long_metric_prefix_") {__name__=commonPrefix+"suffix1"} / {__name__=commonPrefix+"suffix2"}`.
-* `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions), [transform functions](#transform-functions) and [binary operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#binary-operators).
+* `keep_metric_names` modifier can be applied to all the [rollup functions](#rollup-functions), [transform functions](#transform-functions)
+  and [binary operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#binary-operators).
   This modifier prevents from dropping metric names in function results. See [these docs](#keep_metric_names).
 
 ## keep_metric_names
@@ -155,14 +163,15 @@ Additional details:
   The interval between points is set as `step` query arg passed by Grafana to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
 * If the given [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) returns multiple time series,
   then rollups are calculated individually per each returned series.
-* If lookbehind window in square brackets is missing, then MetricsQL automatically sets the lookbehind window
-  to the interval between points on the graph (aka `step` query arg at [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query),
-  `$__interval` value from Grafana or `1i` duration in MetricsQL).
-  For example, `rate(http_requests_total)` is equivalent to `rate(http_requests_total[$__interval])` in Grafana.
-  It is also equivalent to `rate(http_requests_total[1i])`.
+* If lookbehind window in square brackets is missing, then it is automatically set to the following value:
+  - To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
+    for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
+    For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
+  - To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+    for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
 * Every [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) in MetricsQL must be wrapped into a rollup function.
   Otherwise, it is automatically wrapped into [default_rollup](#default_rollup). For example, `foo{bar="baz"}`
-  is automatically converted to `default_rollup(foo{bar="baz"}[1i])` before performing the calculations.
+  is automatically converted to `default_rollup(foo{bar="baz"})` before performing the calculations.
 * If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) is passed to rollup function,
   then the inner arg is automatically converted to a [subquery](#subqueries).
 * All the rollup functions accept optional `keep_metric_names` modifier. If it is set, then the function keeps metric names in results.
@@ -177,7 +186,9 @@ The list of supported rollup functions:
 `absent_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns 1
 if the given lookbehind window `d` doesn't contain raw samples. Otherwise, it returns an empty result.
 
-This function is supported by PromQL. See also [present_over_time](#present_over_time).
+This function is supported by PromQL.
+
+See also [present_over_time](#present_over_time).
 
 #### aggr_over_time
 
@@ -207,7 +218,9 @@ See also [descent_over_time](#descent_over_time).
 over raw samples on the given lookbehind window `d` per each time series returned
 from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [median_over_time](#median_over_time).
+This function is supported by PromQL.
+
+See also [median_over_time](#median_over_time).
 
 #### changes
 
@@ -220,7 +233,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [changes_prometheus](#changes_prometheus).
+This function is supported by PromQL.
+
+See also [changes_prometheus](#changes_prometheus).
 
 #### changes_prometheus
 
@@ -233,7 +248,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [changes](#changes).
+This function is supported by PromQL.
+
+See also [changes](#changes).
 
 #### count_eq_over_time
 
@@ -243,7 +260,7 @@ from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.ht
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-See also [count_over_time](#count_over_time) and [share_eq_over_time](#share_eq_over_time).
+See also [count_over_time](#count_over_time), [share_eq_over_time](#share_eq_over_time) and [count_values_over_time](#count_values_over_time).
 
 #### count_gt_over_time
 
@@ -282,8 +299,19 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time),
-[count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
+This function is supported by PromQL.
+
+See also [count_le_over_time](#count_le_over_time), [count_gt_over_time](#count_gt_over_time), [count_eq_over_time](#count_eq_over_time) and [count_ne_over_time](#count_ne_over_time).
+
+#### count_values_over_time
+
+`count_values_over_time("label", series_selector[d])` is a [rollup function](#rollup-functions), which counts the number of raw samples
+with the same value over the given lookbehind window and stores the counts in a time series with an additional `label`, which contains each initial value.
+The results are calculated independently per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
+
+Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
+
+See also [count_eq_over_time](#count_eq_over_time), [count_values](#count_values) and [distinct_over_time](#distinct_over_time) and [label_match](#label_match).
 
 #### decreases_over_time
 
@@ -299,6 +327,11 @@ See also [increases_over_time](#increases_over_time).
 `default_rollup(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
 per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
+If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
+passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
+while `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the selected time series.
+This allows avoiding unexpected gaps on the graph when `step` is smaller than the `scrape_interval`.
+
 #### delta
 
 `delta(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the difference between
@@ -310,7 +343,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
+This function is supported by PromQL.
+
+See also [increase](#increase) and [delta_prometheus](#delta_prometheus).
 
 #### delta_prometheus
 
@@ -333,7 +368,9 @@ The derivative is calculated using linear regression.
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
+This function is supported by PromQL.
+
+See also [deriv_fast](#deriv_fast) and [ideriv](#ideriv).
 
 #### deriv_fast
 
@@ -364,6 +401,8 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
+See also [count_values_over_time](#count_values_over_time).
+
 #### duration_over_time
 
 `duration_over_time(series_selector[d], max_interval)` is a [rollup function](#rollup-functions), which returns the duration in seconds
@@ -423,7 +462,9 @@ over the given lookbehind window `d` using the given smoothing factor `sf` and t
 Both `sf` and `tf` must be in the range `[0...1]`. It is expected that the [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
 returns time series of [gauge type](https://docs.victoriametrics.com/keyConcepts.html#gauge).
 
-This function is supported by PromQL. See also [range_linear_regression](#range_linear_regression).
+This function is supported by PromQL.
+
+See also [range_linear_regression](#range_linear_regression).
 
 #### idelta
 
@@ -432,7 +473,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [delta](#delta).
+This function is supported by PromQL.
+
+See also [delta](#delta).
 
 #### ideriv
 
@@ -455,7 +498,9 @@ See [this article](https://medium.com/@romanhavronenko/victoriametrics-promql-co
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
+This function is supported by PromQL.
+
+See also [increase_pure](#increase_pure), [increase_prometheus](#increase_prometheus) and [delta](#delta).
 
 #### increase_prometheus
 
@@ -499,7 +544,9 @@ It is expected that the `series_selector` returns time series of [counter type](
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [rate](#rate) and [rollup_rate](#rollup_rate).
+This function is supported by PromQL.
+
+See also [rate](#rate) and [rollup_rate](#rollup_rate).
 
 #### lag
 
@@ -516,7 +563,9 @@ See also [lifetime](#lifetime) and [duration_over_time](#duration_over_time).
 `last_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which returns the last raw sample value on the given lookbehind window `d`
 per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_time).
+This function is supported by PromQL.
+
+See also [first_over_time](#first_over_time) and [tlast_over_time](#tlast_over_time).
 
 #### lifetime
 
@@ -539,7 +588,9 @@ See also [mad](#mad), [range_mad](#range_mad) and [outlier_iqr_over_time](#outli
 `max_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the maximum value over raw samples
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [tmax_over_time](#tmax_over_time).
+This function is supported by PromQL.
+
+See also [tmax_over_time](#tmax_over_time).
 
 #### median_over_time
 
@@ -554,7 +605,9 @@ See also [avg_over_time](#avg_over_time).
 `min_over_time(series_selector[d])` is a [rollup function](#rollup-functions), which calculates the minimum value over raw samples
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [tmin_over_time](#tmin_over_time).
+This function is supported by PromQL.
+
+See also [tmin_over_time](#tmin_over_time).
 
 #### mode_over_time
 
@@ -580,7 +633,9 @@ See also [outliers_iqr](#outliers_iqr).
 linear interpolation over raw samples on the given lookbehind window `d`. The predicted value is calculated individually per each time series
 returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-This function is supported by PromQL. See also [range_linear_regression](#range_linear_regression).
+This function is supported by PromQL.
+
+See also [range_linear_regression](#range_linear_regression).
 
 #### present_over_time
 
@@ -597,7 +652,9 @@ This function is supported by PromQL.
 on the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 The `phi` value must be in the range `[0...1]`.
 
-This function is supported by PromQL. See also [quantiles_over_time](#quantiles_over_time).
+This function is supported by PromQL.
+
+See also [quantiles_over_time](#quantiles_over_time).
 
 #### quantiles_over_time
 
@@ -622,9 +679,16 @@ Metric names are stripped from the resulting rollups. Add [keep_metric_names](#k
 over the given lookbehind window `d` per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 It is expected that the `series_selector` returns time series of [counter type](https://docs.victoriametrics.com/keyConcepts.html#counter).
 
+If the lookbehind window is skipped in square brackets, then it is automatically calculated as `max(step, scrape_interval)`, where `step` is the query arg value
+passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyconcepts/#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query),
+while `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples) for the selected time series.
+This allows avoiding unexpected gaps on the graph when `step` is smaller than the `scrape_interval`.
+
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [irate](#irate) and [rollup_rate](#rollup_rate).
+This function is supported by PromQL.
+
+See also [irate](#irate) and [rollup_rate](#rollup_rate).
 
 #### rate_over_sum
 
@@ -652,6 +716,7 @@ on the given lookbehind window `d` and returns them in time series with `rollup=
 These values are calculated individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 #### rollup_candlestick
 
@@ -660,7 +725,8 @@ over raw samples on the given lookbehind window `d` and returns them in time ser
 The calculations are performed individually per each time series returned
 from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering). This function is useful for financial applications.
 
-Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+Optional 2nd argument `"open"`, `"high"` or `"low"` or `"close"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 #### rollup_delta
 
@@ -670,6 +736,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
@@ -683,6 +750,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
@@ -694,6 +762,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. See also [rollup_delta](#rollup_delta).
 
@@ -707,10 +776,10 @@ See [this article](https://valyala.medium.com/why-irate-from-prometheus-doesnt-c
 when to use `rollup_rate()`.
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
-
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
 #### rollup_scrape_interval
@@ -721,6 +790,7 @@ and returns them in time series with `rollup="min"`, `rollup="max"` and `rollup=
 The calculations are performed individually per each time series returned from the given [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering).
 
 Optional 2nd argument `"min"`, `"max"` or `"avg"` can be passed to keep only one calculation result and without adding a label.
+See also [label_match](#label_match).
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names. See also [scrape_interval](#scrape_interval).
 
@@ -783,7 +853,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [stdvar_over_time](#stdvar_over_time).
+This function is supported by PromQL.
+
+See also [stdvar_over_time](#stdvar_over_time).
 
 #### stdvar_over_time
 
@@ -792,7 +864,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [stddev_over_time](#stddev_over_time).
+This function is supported by PromQL.
+
+See also [stddev_over_time](#stddev_over_time).
 
 #### sum_eq_over_time
 
@@ -844,7 +918,9 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are stripped from the resulting rollups. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [timestamp_with_name](#timestamp_with_name).
+This function is supported by PromQL.
+
+See also [time](#time) and [now](#now).
 
 #### timestamp_with_name
 
@@ -853,7 +929,7 @@ on the given lookbehind window `d` per each time series returned from the given
 
 Metric names are preserved in the resulting rollups.
 
-See also [timestamp](#timestamp).
+See also [timestamp](#timestamp) and [keep_metric_names](#keep_metric_names) modifier.
 
 #### tfirst_over_time
 
@@ -920,7 +996,7 @@ Additional details:
 
 * If transform function is applied directly to a [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before calculating the transformations.
-  For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature[1i]))`.
+  For example, `abs(temperature)` is implicitly transformed to `abs(default_rollup(temperature))`.
 * All the transform functions accept optional `keep_metric_names` modifier. If it is set,
   then the function doesn't drop metric names from the resulting time series. See [these docs](#keep_metric_names).
 
@@ -938,7 +1014,9 @@ This function is supported by PromQL.
 
 `absent(q)` is a [transform function](#transform-functions), which returns 1 if `q` has no points. Otherwise, returns an empty result.
 
-This function is supported by PromQL. See also [absent_over_time](#absent_over_time).
+This function is supported by PromQL.
+
+See also [absent_over_time](#absent_over_time).
 
 #### acos
 
@@ -947,7 +1025,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
+This function is supported by PromQL.
+
+See also [asin](#asin) and [cos](#cos).
 
 #### acosh
 
@@ -956,7 +1036,9 @@ This function is supported by PromQL. See also [asin](#asin) and [cos](#cos).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sinh](#cosh).
+This function is supported by PromQL.
+
+See also [sinh](#cosh).
 
 #### asin
 
@@ -965,7 +1047,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
+This function is supported by PromQL.
+
+See also [acos](#acos) and [sin](#sin).
 
 #### asinh
 
@@ -974,7 +1058,9 @@ This function is supported by PromQL. See also [acos](#acos) and [sin](#sin).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sinh](#sinh).
+This function is supported by PromQL.
+
+See also [sinh](#sinh).
 
 #### atan
 
@@ -983,7 +1069,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [tan](#tan).
+This function is supported by PromQL.
+
+See also [tan](#tan).
 
 #### atanh
 
@@ -992,7 +1080,9 @@ This function is supported by PromQL. See also [tan](#tan).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [tanh](#tanh).
+This function is supported by PromQL.
+
+See also [tanh](#tanh).
 
 #### bitmap_and
 
@@ -1023,25 +1113,33 @@ See also [prometheus_buckets](#prometheus_buckets) and [histogram_quantile](#his
 
 `ceil(q)` is a [transform function](#transform-functions), which rounds every point for every time series returned by `q` to the upper nearest integer.
 
-This function is supported by PromQL. See also [floor](#floor) and [round](#round).
+This function is supported by PromQL.
+
+See also [floor](#floor) and [round](#round).
 
 #### clamp
 
 `clamp(q, min, max)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `min` and `max` values.
 
-This function is supported by PromQL. See also [clamp_min](#clamp_min) and [clamp_max](#clamp_max).
+This function is supported by PromQL.
+
+See also [clamp_min](#clamp_min) and [clamp_max](#clamp_max).
 
 #### clamp_max
 
 `clamp_max(q, max)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `max` value.
 
-This function is supported by PromQL. See also [clamp](#clamp) and [clamp_min](#clamp_min).
+This function is supported by PromQL.
+
+See also [clamp](#clamp) and [clamp_min](#clamp_min).
 
 #### clamp_min
 
 `clamp_min(q, min)` is a [transform function](#transform-functions), which clamps every point for every time series returned by `q` with the given `min` value.
 
-This function is supported by PromQL. See also [clamp](#clamp) and [clamp_max](#clamp_max).
+This function is supported by PromQL.
+
+See also [clamp](#clamp) and [clamp_max](#clamp_max).
 
 #### cos
 
@@ -1049,7 +1147,9 @@ This function is supported by PromQL. See also [clamp](#clamp) and [clamp_max](#
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [sin](#sin).
+This function is supported by PromQL.
+
+See also [sin](#sin).
 
 #### cosh
 
@@ -1058,7 +1158,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [acosh](#acosh).
+This function is supported by PromQL.
+
+See also [acosh](#acosh).
 
 #### day_of_month
 
@@ -1069,6 +1171,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_week](#day_of_week) and [day_of_year](#day_of_year).
+
 #### day_of_week
 
 `day_of_week(q)` is a [transform function](#transform-functions), which returns the day of week for every point of every time series returned by `q`.
@@ -1078,6 +1182,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_month](#day_of_month) and [day_of_year](#day_of_year).
+
 #### day_of_year
 
 `day_of_year(q)` is a [transform function](#transform-functions), which returns the day of year for every point of every time series returned by `q`.
@@ -1087,6 +1193,8 @@ Metric names are stripped from the resulting series. Add [keep_metric_names](#ke
 
 This function is supported by PromQL.
 
+See also [day_of_week](#day_of_week) and [day_of_month](#day_of_month).
+
 #### days_in_month
 
 `days_in_month(q)` is a [transform function](#transform-functions), which returns the number of days in the month identified
@@ -1104,7 +1212,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [rad](#rad).
+This function is supported by PromQL.
+
+See also [rad](#rad).
 
 #### drop_empty_series
 
@@ -1130,13 +1240,17 @@ See also [start](#start), [time](#time) and [now](#now).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [ln](#ln).
+This function is supported by PromQL.
+
+See also [ln](#ln).
 
 #### floor
 
 `floor(q)` is a [transform function](#transform-functions), which rounds every point for every time series returned by `q` to the lower nearest integer.
 
-This function is supported by PromQL. See also [ceil](#ceil) and [round](#round).
+This function is supported by PromQL.
+
+See also [ceil](#ceil) and [round](#round).
 
 #### histogram_avg
 
@@ -1159,8 +1273,9 @@ When the [percentile](https://en.wikipedia.org/wiki/Percentile) is calculated ov
 then all the input histograms **must** have buckets with identical boundaries, e.g. they must have the same set of `le` or `vmrange` labels.
 Otherwise, the returned result may be invalid. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3231) for details.
 
-This function is supported by PromQL (except of the `boundLabel` arg). See also [histogram_quantiles](#histogram_quantiles), [histogram_share](#histogram_share)
-and [quantile](#quantile).
+This function is supported by PromQL (except of the `boundLabel` arg).
+
+See also [histogram_quantiles](#histogram_quantiles), [histogram_share](#histogram_share) and [quantile](#quantile).
 
 #### histogram_quantiles
 
@@ -1232,7 +1347,9 @@ This allows implementing simple paging for `q` time series. See also [limitk](#l
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
+This function is supported by PromQL.
+
+See also [exp](#exp) and [log2](#log2).
 
 #### log2
 
@@ -1240,7 +1357,9 @@ This function is supported by PromQL. See also [exp](#exp) and [log2](#log2).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
+This function is supported by PromQL.
+
+See also [log10](#log10) and [ln](#ln).
 
 #### log10
 
@@ -1248,7 +1367,9 @@ This function is supported by PromQL. See also [log10](#log10) and [ln](#ln).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [log2](#log2) and [ln](#ln).
+This function is supported by PromQL.
+
+See also [log2](#log2) and [ln](#ln).
 
 #### minute
 
@@ -1287,7 +1408,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by PromQL. See also [deg](#deg).
+This function is supported by PromQL.
+
+See also [deg](#deg).
 
 #### prometheus_buckets
 
@@ -1415,7 +1538,9 @@ for points returned by `q`, e.g. it is equivalent to the following query: `(q -
 `round(q, nearest)` is a [transform function](#transform-functions), which rounds every point of every time series returned by `q` to the `nearest` multiple.
 If `nearest` is missing then the rounding is performed to the nearest integer.
 
-This function is supported by PromQL. See also [floor](#floor) and [ceil](#ceil).
+This function is supported by PromQL.
+
+See also [floor](#floor) and [ceil](#ceil).
 
 #### ru
 
@@ -1459,7 +1584,9 @@ This function is supported by PromQL.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [cos](#cos).
+This function is supported by MetricsQL.
+
+See also [cos](#cos).
 
 #### sinh
 
@@ -1468,7 +1595,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [cosh](#cosh).
+This function is supported by MetricsQL.
+
+See also [cosh](#cosh).
 
 #### tan
 
@@ -1476,7 +1605,9 @@ This function is supported by MetricsQL. See also [cosh](#cosh).
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [atan](#atan).
+This function is supported by MetricsQL.
+
+See also [atan](#atan).
 
 #### tanh
 
@@ -1485,7 +1616,9 @@ for every point of every time series returned by `q`.
 
 Metric names are stripped from the resulting series. Add [keep_metric_names](#keep_metric_names) modifier in order to keep metric names.
 
-This function is supported by MetricsQL. See also [atanh](#atanh).
+This function is supported by MetricsQL.
+
+See also [atanh](#atanh).
 
 #### smooth_exponential
 
@@ -1496,13 +1629,17 @@ by `q` using [exponential moving average](https://en.wikipedia.org/wiki/Moving_a
 
 `sort(q)` is a [transform function](#transform-functions), which sorts series in ascending order by the last point in every time series returned by `q`.
 
-This function is supported by PromQL. See also [sort_desc](#sort_desc) and [sort_by_label](#sort_by_label).
+This function is supported by PromQL.
+
+See also [sort_desc](#sort_desc) and [sort_by_label](#sort_by_label).
 
 #### sort_desc
 
 `sort_desc(q)` is a [transform function](#transform-functions), which sorts series in descending order by the last point in every time series returned by `q`.
 
-This function is supported by PromQL. See also [sort](#sort) and [sort_by_label](#sort_by_label_desc).
+This function is supported by PromQL.
+
+See also [sort](#sort) and [sort_by_label](#sort_by_label_desc).
 
 #### sqrt
 
@@ -1531,7 +1668,9 @@ See also [start](#start) and [end](#end).
 
 `time()` is a [transform function](#transform-functions), which returns unix timestamp for every returned point.
 
-This function is supported by PromQL. See also [now](#now), [start](#start) and [end](#end).
+This function is supported by PromQL.
+
+See also [timestamp](#timestamp), [now](#now), [start](#start) and [end](#end).
 
 #### timezone_offset
 
@@ -1580,7 +1719,7 @@ Additional details:
 
 * If label manipulation function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before performing the label transformation.
-  For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature[1i]), "foo")`.
+  For example, `alias(temperature, "foo")` is implicitly transformed to `alias(default_rollup(temperature), "foo")`.
 
 See also [implicit query conversions](#implicit-query-conversions).
 
@@ -1757,7 +1896,7 @@ Additional details:
   Multiple labels can be put in `by` and `without` modifiers.
 * If the aggregate function is applied directly to a [series_selector](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   then the [default_rollup()](#default_rollup) function is automatically applied before calculating the aggregate.
-  For example, `count(up)` is implicitly transformed to `count(default_rollup(up[1i]))`.
+  For example, `count(up)` is implicitly transformed to `count(default_rollup(up))`.
 * Aggregate functions accept arbitrary number of args. For example, `avg(q1, q2, q3)` would return the average values for every point
   across time series returned by `q1`, `q2` and `q3`.
 * Aggregate functions support optional `limit N` suffix, which can be used for limiting the number of output groups.
@@ -1785,7 +1924,9 @@ This function is supported by PromQL.
 `bottomk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` points with the smallest values across all the time series returned by `q`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [topk](#topk).
+This function is supported by PromQL.
+
+See also [topk](#topk), [bottomk_min](#bottomk_min) and [#bottomk_last](#bottomk_last).
 
 #### bottomk_avg
 
@@ -1847,10 +1988,14 @@ The aggregate is calculated individually per each group of points with the same
 
 This function is supported by PromQL.
 
+See also [count_values_over_time](#count_values_over_time) and [label_match](#label_match).
+
 #### distinct
 
 `distinct(q)` is [aggregate function](#aggregate-functions), which calculates the number of unique values per each group of points with the same timestamp.
 
+See also [distinct_over_time](#distinct_over_time).
+
 #### geomean
 
 `geomean(q)` is [aggregate function](#aggregate-functions), which calculates geometric mean per each group of points with the same timestamp.
@@ -1942,7 +2087,9 @@ See also [outliers_iqr](#outliers_iqr) and [outliers_mad](#outliers_mad).
 for all the time series returned by `q`. `phi` must be in the range `[0...1]`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [quantiles](#quantiles) and [histogram_quantile](#histogram_quantile).
+This function is supported by PromQL.
+
+See also [quantiles](#quantiles) and [histogram_quantile](#histogram_quantile).
 
 #### quantiles
 
@@ -2001,7 +2148,9 @@ for all the time series returned by `q`. The aggregate is calculated individuall
 `topk(k, q)` is [aggregate function](#aggregate-functions), which returns up to `k` points with the biggest values across all the time series returned by `q`.
 The aggregate is calculated individually per each group of points with the same timestamp.
 
-This function is supported by PromQL. See also [bottomk](#bottomk).
+This function is supported by PromQL.
+
+See also [bottomk](#bottomk), [topk_max](#topk_max) and [topk_last](#topk_last).
 
 #### topk_avg
 
@@ -2061,7 +2210,7 @@ See also [zscore_over_time](#zscore_over_time), [range_trim_zscore](#range_trim_
 MetricsQL supports and extends PromQL subqueries. See [this article](https://valyala.medium.com/prometheus-subqueries-in-victoriametrics-9b1492b720b3) for details.
 Any [rollup function](#rollup-functions) for something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering) form a subquery.
 Nested rollup functions can be implicit thanks to the [implicit query conversions](#implicit-query-conversions).
-For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m[1i]))[1i:1i])`, so it becomes a subquery,
+For example, `delta(sum(m))` is implicitly converted to `delta(sum(default_rollup(m))[1i:1i])`, so it becomes a subquery,
 since it contains [default_rollup](#default_rollup) nested into [delta](#delta).
 
 VictoriaMetrics performs subqueries in the following way:
@@ -2076,21 +2225,23 @@ VictoriaMetrics performs subqueries in the following way:
 
 VictoriaMetrics performs the following implicit conversions for incoming queries before starting the calculations:
 
-* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions),
-  then `[1i]` is automatically added there. The `[1i]` means one `step` value, which is passed
-  to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query).
-  It is also known as `$__interval` in Grafana. For example, `rate(http_requests_count)` is automatically transformed to `rate(http_requests_count[1i])`.
+* If lookbehind window in square brackets is missing inside [rollup function](#rollup-functions), then it is automatically set to the following value:
+  - To `step` value passed to [/api/v1/query_range](https://docs.victoriametrics.com/keyConcepts.html#range-query) or [/api/v1/query](https://docs.victoriametrics.com/keyconcepts/#instant-query)
+    for all the [rollup functions](#rollup-functions) except of [default_rollup](#default_rollup) and [rate](#rate). This value is known as `$__interval` in Grafana or `1i` in MetricsQL.
+    For example, `avg_over_time(temperature)` is automatically transformed to `avg_over_time(temperature[1i])`.
+  - To the `max(step, scrape_interval)`, where `scrape_interval` is the interval between [raw samples](https://docs.victoriametrics.com/keyconcepts/#raw-samples)
+    for [default_rollup](#default_rollup) and [rate](#rate) functions. This allows avoiding unexpected gaps on the graph when `step` is smaller than `scrape_interval`.
 * All the [series selectors](https://docs.victoriametrics.com/keyConcepts.html#filtering),
   which aren't wrapped into [rollup functions](#rollup-functions), are automatically wrapped into [default_rollup](#default_rollup) function.
   Examples:
-  * `foo` is transformed to `default_rollup(foo[1i])`
-  * `foo + bar` is transformed to `default_rollup(foo[1i]) + default_rollup(bar[1i])`
-  * `count(up)` is transformed to `count(default_rollup(up[1i]))`, because [count](#count) isn't a [rollup function](#rollup-functions) -
+  * `foo` is transformed to `default_rollup(foo)`
+  * `foo + bar` is transformed to `default_rollup(foo) + default_rollup(bar)`
+  * `count(up)` is transformed to `count(default_rollup(up))`, because [count](#count) isn't a [rollup function](#rollup-functions) -
     it is [aggregate function](#aggregate-functions)
-  * `abs(temperature)` is transformed to `abs(default_rollup(temperature[1i]))`, because [abs](#abs) isn't a [rollup function](#rollup-functions) -
+  * `abs(temperature)` is transformed to `abs(default_rollup(temperature))`, because [abs](#abs) isn't a [rollup function](#rollup-functions) -
     it is [transform function](#transform-functions)
 * If `step` in square brackets is missing inside [subquery](#subqueries), then `1i` step is automatically added there.
   For example, `avg_over_time(rate(http_requests_total[5m])[1h])` is automatically converted to `avg_over_time(rate(http_requests_total[5m])[1h:1i])`.
 * If something other than [series selector](https://docs.victoriametrics.com/keyConcepts.html#filtering)
   is passed to [rollup function](#rollup-functions), then a [subquery](#subqueries) with `1i` lookbehind window and `1i` step is automatically formed.
-  For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up[1i])))[1i:1i])`.
+  For example, `rate(sum(up))` is automatically converted to `rate((sum(default_rollup(up)))[1i:1i])`.

app/vmui/packages/vmui/src/components/Chart/Line/LineChart/LineChart.tsx

@@ -41,6 +41,7 @@ export interface LineChartProps {
   layoutSize: ElementSize;
   height?: number;
   anomalyView?: boolean;
+  spanGaps?: boolean;
 }
 
 const LineChart: FC<LineChartProps> = ({
@@ -53,7 +54,8 @@ const LineChart: FC<LineChartProps> = ({
   setPeriod,
   layoutSize,
   height,
-  anomalyView
+  anomalyView,
+  spanGaps = false
 }) => {
   const { isDarkTheme } = useAppState();
 
@@ -106,10 +108,10 @@ const LineChart: FC<LineChartProps> = ({
   useEffect(() => {
     if (!uPlotInst) return;
     delSeries(uPlotInst);
-    addSeries(uPlotInst, series);
+    addSeries(uPlotInst, series, spanGaps);
     setBand(uPlotInst, series);
     uPlotInst.redraw();
-  }, [series]);
+  }, [series, spanGaps]);
 
   useEffect(() => {
     if (!uPlotInst) return;

app/vmui/packages/vmui/src/components/Configurators/GraphSettings/GraphSettings.tsx

@@ -7,16 +7,21 @@ import Popper from "../../Main/Popper/Popper";
 import "./style.scss";
 import Tooltip from "../../Main/Tooltip/Tooltip";
 import useBoolean from "../../../hooks/useBoolean";
+import LinesConfigurator from "./LinesConfigurator/LinesConfigurator";
 
-const title = "Axes settings";
+const title = "Graph settings";
 
 interface GraphSettingsProps {
   yaxis: YaxisState,
   setYaxisLimits: (limits: AxisRange) => void,
-  toggleEnableLimits: () => void
+  toggleEnableLimits: () => void,
+  spanGaps: {
+    value: boolean,
+    onChange: (value: boolean) => void,
+  },
 }
 
-const GraphSettings: FC<GraphSettingsProps> = ({ yaxis, setYaxisLimits, toggleEnableLimits }) => {
+const GraphSettings: FC<GraphSettingsProps> = ({ yaxis, setYaxisLimits, toggleEnableLimits, spanGaps }) => {
   const popperRef = useRef<HTMLDivElement>(null);
   const buttonRef = useRef<HTMLDivElement>(null);
 
@@ -55,6 +60,10 @@ const GraphSettings: FC<GraphSettingsProps> = ({ yaxis, setYaxisLimits, toggleEn
               setYaxisLimits={setYaxisLimits}
               toggleEnableLimits={toggleEnableLimits}
             />
+            <LinesConfigurator
+              spanGaps={spanGaps.value}
+              onChange={spanGaps.onChange}
+            />
           </div>
         </div>
       </Popper>

app/vmui/packages/vmui/src/components/Configurators/GraphSettings/LinesConfigurator/LinesConfigurator.tsx

@@ -0,0 +1,23 @@
+import React, { FC } from "preact/compat";
+import Switch from "../../../Main/Switch/Switch";
+import useDeviceDetect from "../../../../hooks/useDeviceDetect";
+
+interface Props {
+  spanGaps: boolean,
+  onChange: (value: boolean) => void,
+}
+
+const LinesConfigurator: FC<Props> = ({ spanGaps, onChange }) => {
+  const { isMobile } = useDeviceDetect();
+
+  return <div>
+    <Switch
+      value={spanGaps}
+      onChange={onChange}
+      label="Connect null values"
+      fullWidth={isMobile}
+    />
+  </div>;
+};
+
+export default LinesConfigurator;

app/vmui/packages/vmui/src/components/Configurators/GraphSettings/style.scss

@@ -8,7 +8,7 @@
 
     &__body {
       display: grid;
-      gap: $padding-small;
+      gap: $padding-large;
       padding: 0 $padding-global;
     }
   }

app/vmui/packages/vmui/src/components/Main/Popper/Popper.tsx

@@ -7,7 +7,6 @@ import useDeviceDetect from "../../../hooks/useDeviceDetect";
 import Button from "../Button/Button";
 import { CloseIcon } from "../Icons";
 import { useLocation, useNavigate } from "react-router-dom";
-import useBoolean from "../../../hooks/useBoolean";
 import useEventListener from "../../../hooks/useEventListener";
 import { useCallback } from "preact/compat";
 
@@ -43,12 +42,7 @@ const Popper: FC<PopperProps> = ({
   const navigate = useNavigate();
   const location = useLocation();
   const [popperSize, setPopperSize] = useState({ width: 0, height: 0 });
-
-  const {
-    value: isOpen,
-    setValue: setIsOpen,
-    setFalse: handleClose,
-  } = useBoolean(false);
+  const [isOpen, setIsOpen] = useState(false);
 
   const popperRef = useRef<HTMLDivElement>(null);
 
@@ -113,6 +107,7 @@ const Popper: FC<PopperProps> = ({
 
     if (fullWidth) position.width = `${buttonPos.width}px`;
     if (position.top < 0) position.top = 20;
+    if (position.left < 0) position.left = 20;
 
     return position;
   },[buttonRef, placement, isOpen, children, fullWidth]);
@@ -122,7 +117,15 @@ const Popper: FC<PopperProps> = ({
     onClose();
   };
 
-  if (clickOutside) useClickOutside(popperRef, () => setIsOpen(false), buttonRef);
+  const handleClose = () => {
+    setIsOpen(false);
+    onClose();
+  };
+
+  const handleClickOutside = () => {
+    if (!clickOutside) return;
+    handleClose();
+  };
 
   useEffect(() => {
     if (!popperRef.current || !isOpen || (isMobile && !disabledFullScreen)) return;
@@ -142,6 +145,7 @@ const Popper: FC<PopperProps> = ({
 
   useEventListener("scroll", handleClose);
   useEventListener("popstate", handlePopstate);
+  useClickOutside(popperRef, handleClickOutside, buttonRef);
 
   return (
     <>

app/vmui/packages/vmui/src/components/Views/GraphView/GraphView.tsx

@@ -41,6 +41,7 @@ export interface GraphViewProps {
   height?: number;
   isHistogram?: boolean;
   anomalyView?: boolean;
+  spanGaps?: boolean;
 }
 
 const GraphView: FC<GraphViewProps> = ({
@@ -58,6 +59,7 @@ const GraphView: FC<GraphViewProps> = ({
   height,
   isHistogram,
   anomalyView,
+  spanGaps
 }) => {
   const { isMobile } = useDeviceDetect();
   const { timezone } = useTimeState();
@@ -196,6 +198,7 @@ const GraphView: FC<GraphViewProps> = ({
           layoutSize={containerSize}
           height={height}
           anomalyView={anomalyView}
+          spanGaps={spanGaps}
         />
       )}
       {isHistogram && (

app/vmui/packages/vmui/src/layouts/LogsLayout/ControlsLogsLayout.tsx

@@ -2,7 +2,7 @@ import React, { FC } from "preact/compat";
 import classNames from "classnames";
 import GlobalSettings from "../../components/Configurators/GlobalSettings/GlobalSettings";
 import { ControlsProps } from "../Header/HeaderControls/HeaderControls";
-
+import { TimeSelector } from "../../components/Configurators/TimeRangeSettings/TimeSelector/TimeSelector";
 
 const ControlsLogsLayout: FC<ControlsProps> = ({ isMobile }) => {
 
@@ -13,6 +13,7 @@ const ControlsLogsLayout: FC<ControlsProps> = ({ isMobile }) => {
         "vm-header-controls_mobile": isMobile,
       })}
     >
+      <TimeSelector/>
       <GlobalSettings/>
     </div>
   );

app/vmui/packages/vmui/src/pages/CustomPanel/CustomPanelTabs/GraphTab.tsx

@@ -20,7 +20,7 @@ type Props = {
 const GraphTab: FC<Props> = ({ isHistogram, graphData, controlsRef, anomalyView }) => {
   const { isMobile } = useDeviceDetect();
 
-  const { customStep, yaxis } = useGraphState();
+  const { customStep, yaxis, spanGaps } = useGraphState();
   const { period } = useTimeState();
   const { query } = useQueryState();
 
@@ -35,6 +35,10 @@ const GraphTab: FC<Props> = ({ isHistogram, graphData, controlsRef, anomalyView
     graphDispatch({ type: "TOGGLE_ENABLE_YAXIS_LIMITS" });
   };
 
+  const setSpanGaps = (value: boolean) => {
+    graphDispatch({ type: "SET_SPAN_GAPS", payload: value });
+  };
+
   const setPeriod = ({ from, to }: {from: Date, to: Date}) => {
     timeDispatch({ type: "SET_PERIOD", payload: { from, to } });
   };
@@ -46,6 +50,7 @@ const GraphTab: FC<Props> = ({ isHistogram, graphData, controlsRef, anomalyView
         yaxis={yaxis}
         setYaxisLimits={setYaxisLimits}
         toggleEnableLimits={toggleEnableLimits}
+        spanGaps={{ value: spanGaps, onChange: setSpanGaps }}
       />
     </div>
   );
@@ -64,6 +69,7 @@ const GraphTab: FC<Props> = ({ isHistogram, graphData, controlsRef, anomalyView
         height={isMobile ? window.innerHeight * 0.5 : 500}
         isHistogram={isHistogram}
         anomalyView={anomalyView}
+        spanGaps={spanGaps}
       />
     </>
   );

app/vmui/packages/vmui/src/pages/ExploreLogs/ExploreLogs.tsx

@@ -8,17 +8,22 @@ import Spinner from "../../components/Main/Spinner/Spinner";
 import Alert from "../../components/Main/Alert/Alert";
 import ExploreLogsHeader from "./ExploreLogsHeader/ExploreLogsHeader";
 import "./style.scss";
-import usePrevious from "../../hooks/usePrevious";
 import { ErrorTypes } from "../../types";
 import { useState } from "react";
+import { useTimeState } from "../../state/time/TimeStateContext";
+import { getFromStorage, saveToStorage } from "../../utils/storage";
+
+const storageLimit = Number(getFromStorage("LOGS_LIMIT"));
+const defaultLimit = isNaN(storageLimit) ? 1000 : storageLimit;
 
 const ExploreLogs: FC = () => {
   const { serverUrl } = useAppState();
+  const { duration, relativeTime, period } = useTimeState();
   const { setSearchParamsFromKeys } = useSearchParamsFromObject();
 
+  const [limit, setLimit] = useStateSearchParams(defaultLimit, "limit");
   const [query, setQuery] = useStateSearchParams("", "query");
-  const prevQuery = usePrevious(query);
-  const { logs, isLoading, error, fetchLogs } = useFetchLogs(serverUrl, query);
+  const { logs, isLoading, error, fetchLogs } = useFetchLogs(serverUrl, query, limit);
   const [queryError, setQueryError] = useState<ErrorTypes | string>("");
   const [loaded, isLoaded] = useState(false);
 
@@ -31,14 +36,24 @@ const ExploreLogs: FC = () => {
     fetchLogs().then(() => {
       isLoaded(true);
     });
-    const changedQuery = prevQuery && query !== prevQuery;
-    const params: Record<string, string | number> = changedQuery ? { query, page: 1 } : { query };
-    setSearchParamsFromKeys(params);
+
+    setSearchParamsFromKeys( {
+      query,
+      "g0.range_input": duration,
+      "g0.end_input": period.date,
+      "g0.relative_time": relativeTime || "none",
+    });
+  };
+
+  const handleChangeLimit = (limit: number) => {
+    setLimit(limit);
+    setSearchParamsFromKeys({ limit });
+    saveToStorage("LOGS_LIMIT", `${limit}`);
   };
 
   useEffect(() => {
     if (query) handleRunQuery();
-  }, []);
+  }, [period]);
 
   useEffect(() => {
     setQueryError("");
@@ -49,7 +64,9 @@ const ExploreLogs: FC = () => {
       <ExploreLogsHeader
         query={query}
         error={queryError}
+        limit={limit}
         onChange={setQuery}
+        onChangeLimit={handleChangeLimit}
         onRun={handleRunQuery}
       />
       {isLoading && <Spinner />}

app/vmui/packages/vmui/src/pages/ExploreLogs/ExploreLogsBody/ExploreLogsBody.tsx

@@ -8,10 +8,8 @@ import useDeviceDetect from "../../../hooks/useDeviceDetect";
 import { Logs } from "../../../api/types";
 import dayjs from "dayjs";
 import { useTimeState } from "../../../state/time/TimeStateContext";
-import SelectLimit from "../../../components/Main/Pagination/SelectLimit/SelectLimit";
 import useStateSearchParams from "../../../hooks/useStateSearchParams";
 import useSearchParamsFromObject from "../../../hooks/useSearchParamsFromObject";
-import { getFromStorage, saveToStorage } from "../../../utils/storage";
 import TableSettings from "../../../components/Table/TableSettings/TableSettings";
 import useBoolean from "../../../hooks/useBoolean";
 import TableLogs from "./TableLogs";
@@ -29,16 +27,15 @@ enum DisplayType {
 }
 
 const tabs = [
-  { label: "Group", value: DisplayType.group, icon: <ListIcon /> },
-  { label: "Table", value: DisplayType.table, icon: <TableIcon /> },
-  { label: "JSON", value: DisplayType.json, icon: <CodeIcon /> },
+  { label: "Group", value: DisplayType.group, icon: <ListIcon/> },
+  { label: "Table", value: DisplayType.table, icon: <TableIcon/> },
+  { label: "JSON", value: DisplayType.json, icon: <CodeIcon/> },
 ];
 
 const ExploreLogsBody: FC<ExploreLogBodyProps> = ({ data, loaded }) => {
   const { isMobile } = useDeviceDetect();
   const { timezone } = useTimeState();
   const { setSearchParamsFromKeys } = useSearchParamsFromObject();
-  const [limitRows, setLimitRows] = useStateSearchParams(getFromStorage("LOGS_LIMIT") || 50, "limit");
 
   const [activeTab, setActiveTab] = useStateSearchParams(DisplayType.group, "view");
   const [displayColumns, setDisplayColumns] = useState<string[]>([]);
@@ -67,17 +64,11 @@ const ExploreLogsBody: FC<ExploreLogBodyProps> = ({ data, loaded }) => {
     setSearchParamsFromKeys({ view });
   };
 
-  const handleChangeLimit = (limit: number) => {
-    setLimitRows(limit);
-    setSearchParamsFromKeys({ limit });
-    saveToStorage("LOGS_LIMIT", `${limit}`);
-  };
-
   return (
     <div
       className={classNames({
         "vm-explore-logs-body": true,
-        "vm-block":  true,
+        "vm-block": true,
         "vm-block_mobile": isMobile,
       })}
     >
@@ -97,10 +88,6 @@ const ExploreLogsBody: FC<ExploreLogBodyProps> = ({ data, loaded }) => {
         </div>
         {activeTab === DisplayType.table && (
           <div className="vm-explore-logs-body-header__settings">
-            <SelectLimit
-              limit={+limitRows}
-              onChange={handleChangeLimit}
-            />
             <TableSettings
               columns={columns}
               defaultColumns={displayColumns}
@@ -128,7 +115,6 @@ const ExploreLogsBody: FC<ExploreLogBodyProps> = ({ data, loaded }) => {
             {activeTab === DisplayType.table && (
               <TableLogs
                 logs={logs}
-                limitRows={+limitRows}
                 displayColumns={displayColumns}
                 tableCompact={tableCompact}
                 columns={columns}
@@ -141,7 +127,7 @@ const ExploreLogsBody: FC<ExploreLogBodyProps> = ({ data, loaded }) => {
               />
             )}
             {activeTab === DisplayType.json && (
-              <JsonView data={data} />
+              <JsonView data={data}/>
             )}
           </>
         )}

app/vmui/packages/vmui/src/pages/ExploreLogs/ExploreLogsBody/TableLogs.tsx

@@ -2,22 +2,15 @@ import React, { FC, useMemo } from "preact/compat";
 import "./style.scss";
 import Table from "../../../components/Table/Table";
 import { Logs } from "../../../api/types";
-import useStateSearchParams from "../../../hooks/useStateSearchParams";
-import useSearchParamsFromObject from "../../../hooks/useSearchParamsFromObject";
-import PaginationControl from "../../../components/Main/Pagination/PaginationControl/PaginationControl";
 
 interface TableLogsProps {
   logs: Logs[];
-  limitRows: number;
   displayColumns: string[];
   tableCompact: boolean;
   columns: string[];
 }
 
-const TableLogs: FC<TableLogsProps> = ({ logs, limitRows, displayColumns, tableCompact, columns }) => {
-  const { setSearchParamsFromKeys } = useSearchParamsFromObject();
-  const [page, setPage] = useStateSearchParams(1, "page");
-
+const TableLogs: FC<TableLogsProps> = ({ logs, displayColumns, tableCompact, columns }) => {
   const getColumnClass = (key: string) => {
     switch (key) {
       case "time":
@@ -29,16 +22,6 @@ const TableLogs: FC<TableLogsProps> = ({ logs, limitRows, displayColumns, tableC
     }
   };
 
-  // TODO: Remove when pagination is implemented on the backend.
-  const paginationOffset = useMemo(() => {
-    const startIndex = (page - 1) * Number(limitRows);
-    const endIndex = startIndex + Number(limitRows);
-    return {
-      startIndex,
-      endIndex
-    };
-  }, [page, limitRows]);
-
   const tableColumns = useMemo(() => {
     if (tableCompact) {
       return [{
@@ -60,11 +43,6 @@ const TableLogs: FC<TableLogsProps> = ({ logs, limitRows, displayColumns, tableC
     return tableColumns.filter(c => displayColumns.includes(c.key as string));
   }, [tableColumns, displayColumns, tableCompact]);
 
-  const handleChangePage = (page: number) => {
-    setPage(page);
-    setSearchParamsFromKeys({ page });
-  };
-
   return (
     <>
       <Table
@@ -72,14 +50,7 @@ const TableLogs: FC<TableLogsProps> = ({ logs, limitRows, displayColumns, tableC
         columns={filteredColumns}
         defaultOrderBy={"time"}
         copyToClipboard={"data"}
-        paginationOffset={paginationOffset}
-      />
-      <PaginationControl
-        page={page}
-        limit={+limitRows}
-        // TODO: Remove .slice() when pagination is implemented on the backend.
-        length={logs.slice(paginationOffset.startIndex, paginationOffset.endIndex).length}
-        onChange={handleChangePage}
+        paginationOffset={{ startIndex: 0, endIndex: Infinity }}
       />
     </>
   );

app/vmui/packages/vmui/src/pages/ExploreLogs/ExploreLogsHeader/ExploreLogsHeader.tsx

@@ -1,21 +1,42 @@
-import React, { FC } from "react";
+import React, { FC, useEffect, useState } from "preact/compat";
 import { InfoIcon, PlayIcon, WikiIcon } from "../../../components/Main/Icons";
 import "./style.scss";
 import classNames from "classnames";
 import useDeviceDetect from "../../../hooks/useDeviceDetect";
 import Button from "../../../components/Main/Button/Button";
 import QueryEditor from "../../../components/Configurators/QueryEditor/QueryEditor";
+import TextField from "../../../components/Main/TextField/TextField";
 
 export interface ExploreLogHeaderProps {
   query: string;
+  limit: number;
   error?: string;
   onChange: (val: string) => void;
+  onChangeLimit: (val: number) => void;
   onRun: () => void;
 }
 
-const ExploreLogsHeader: FC<ExploreLogHeaderProps> = ({ query, error, onChange, onRun }) => {
+const ExploreLogsHeader: FC<ExploreLogHeaderProps> = ({ query, limit, error, onChange, onChangeLimit, onRun }) => {
   const { isMobile } = useDeviceDetect();
 
+  const [errorLimit, setErrorLimit] = useState("");
+  const [limitInput, setLimitInput] = useState(limit);
+
+  const handleChangeLimit = (val: string) => {
+    const number = +val;
+    setLimitInput(number);
+    if (isNaN(number) || number < 0) {
+      setErrorLimit("Number must be bigger than zero");
+    } else {
+      setErrorLimit("");
+      onChangeLimit(number);
+    }
+  };
+
+  useEffect(() => {
+    setLimitInput(limit);
+  }, [limit]);
+
   return (
     <div
       className={classNames({
@@ -24,7 +45,7 @@ const ExploreLogsHeader: FC<ExploreLogHeaderProps> = ({ query, error, onChange,
         "vm-block_mobile": isMobile,
       })}
     >
-      <div className="vm-explore-logs-header__input">
+      <div className="vm-explore-logs-header-top">
         <QueryEditor
           value={query}
           autocomplete={false}
@@ -35,6 +56,14 @@ const ExploreLogsHeader: FC<ExploreLogHeaderProps> = ({ query, error, onChange,
           label={"Log query"}
           error={error}
         />
+        <TextField
+          label="Limit entries"
+          type="number"
+          value={limitInput}
+          error={errorLimit}
+          onChange={handleChangeLimit}
+          onEnter={onRun}
+        />
       </div>
       <div className="vm-explore-logs-header-bottom">
         <div className="vm-explore-logs-header-bottom-helpful">
@@ -63,7 +92,7 @@ const ExploreLogsHeader: FC<ExploreLogHeaderProps> = ({ query, error, onChange,
             onClick={onRun}
             fullWidth
           >
-           Execute Query
+            Execute Query
           </Button>
         </div>
       </div>

app/vmui/packages/vmui/src/pages/ExploreLogs/ExploreLogsHeader/style.scss

@@ -5,7 +5,13 @@
   align-items: center;
   gap: $padding-global;
 
-  &__input {}
+  &-top {
+    display: grid;
+    grid-template-columns: 8fr 2fr;
+    align-items: flex-start;
+    justify-content: center;
+    gap: $padding-global;
+  }
 
   &-bottom {
     display: flex;

app/vmui/packages/vmui/src/pages/ExploreLogs/hooks/useFetchLogs.ts

@@ -2,26 +2,49 @@ import { useCallback, useMemo, useState } from "preact/compat";
 import { getLogsUrl } from "../../../api/logs";
 import { ErrorTypes } from "../../../types";
 import { Logs } from "../../../api/types";
+import { useTimeState } from "../../../state/time/TimeStateContext";
+import dayjs from "dayjs";
 
-const MAX_LINES = 1000;
-
-export const useFetchLogs = (server: string, query: string) => {
+export const useFetchLogs = (server: string, query: string, limit: number) => {
+  const { period } = useTimeState();
   const [logs, setLogs] = useState<Logs[]>([]);
   const [isLoading, setIsLoading] = useState(false);
   const [error, setError] = useState<ErrorTypes | string>();
 
   const url = useMemo(() => getLogsUrl(server), [server]);
 
+  // include time range in query if not already present
+  const queryWithTime = useMemo(() => {
+    if (!/_time/.test(query)) {
+      const start = dayjs(period.start * 1000).tz().toISOString();
+      const end = dayjs(period.end * 1000).tz().toISOString();
+      const timerange = `_time:[${start}, ${end}]`;
+      return `${timerange} AND ${query}`;
+    }
+    return query;
+  }, [query, period]);
+
   const options = useMemo(() => ({
     method: "POST",
     headers: {
-      "Accept": "application/stream+json; charset=utf-8",
-      "Content-Type": "application/x-www-form-urlencoded",
+      "Accept": "application/stream+json",
     },
-    body: `query=${encodeURIComponent(query.trim())}`
-  }), [query]);
+    body: new URLSearchParams({
+      query: queryWithTime.trim(),
+      limit: `${limit}`
+    })
+  }), [queryWithTime, limit]);
+
+  const parseLineToJSON = (line: string): Logs | null => {
+    try {
+      return JSON.parse(line);
+    } catch (e) {
+      return null;
+    }
+  };
 
   const fetchLogs = useCallback(async () => {
+    const limit = Number(options.body.get("limit")) + 1;
     setIsLoading(true);
     setError(undefined);
     try {
@@ -50,29 +73,21 @@ export const useFetchLogs = (server: string, query: string) => {
         const lines = decoder.decode(value, { stream: true }).split("\n");
         result.push(...lines);
 
-        // Trim result to MAX_LINES
-        if (result.length > MAX_LINES) {
-          result.splice(0, result.length - MAX_LINES);
+        // Trim result to limit
+        // This will lose its meaning with these changes:
+        // https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5778
+        if (result.length > limit) {
+          result.splice(0, result.length - limit);
         }
 
-        if (result.length >= MAX_LINES) {
+        if (result.length >= limit) {
           // Reached the maximum line limit
           reader.cancel();
           break;
         }
       }
-      const data = result
-        .map((line) => {
-          try {
-            return JSON.parse(line);
-          } catch (e) {
-            return "";
-          }
-        })
-        .filter(line => line);
-
+      const data = result.map(parseLineToJSON).filter(line => line) as Logs[];
       setLogs(data);
-
     } catch (e) {
       console.error(e);
       setLogs([]);

app/vmui/packages/vmui/src/pages/PredefinedPanels/PredefinedPanel/PredefinedPanel.tsx

@@ -34,6 +34,7 @@ const PredefinedPanel: FC<PredefinedPanelsProps> = ({
 
   const containerRef = useRef<HTMLDivElement>(null);
   const [visible, setVisible] = useState(false);
+  const [spanGaps, setSpanGaps] = useState(false);
   const [yaxis, setYaxis] = useState<YaxisState>({
     limits: {
       enable: false,
@@ -121,6 +122,7 @@ const PredefinedPanel: FC<PredefinedPanelsProps> = ({
         yaxis={yaxis}
         setYaxisLimits={setYaxisLimits}
         toggleEnableLimits={toggleEnableLimits}
+        spanGaps={{ value: spanGaps, onChange: setSpanGaps }}
       />
     </div>
     <div className="vm-predefined-panel-body">
@@ -140,6 +142,7 @@ const PredefinedPanel: FC<PredefinedPanelsProps> = ({
         setPeriod={setPeriod}
         fullWidth={false}
         height={isMobile ? window.innerHeight * 0.5 : 500}
+        spanGaps={spanGaps}
       />
       }
     </div>

app/vmui/packages/vmui/src/pages/QueryAnalyzer/QueryAnalyzerView/QueryAnalyzerView.tsx

@@ -49,7 +49,7 @@ const QueryAnalyzerView: FC<Props> = ({ data, period }) => {
   }, [data]);
   const [displayType, setDisplayType] = useState(tabs[0].value);
 
-  const { yaxis } = useGraphState();
+  const { yaxis, spanGaps } = useGraphState();
   const graphDispatch = useGraphDispatch();
 
   const setYaxisLimits = (limits: AxisRange) => {
@@ -60,6 +60,10 @@ const QueryAnalyzerView: FC<Props> = ({ data, period }) => {
     graphDispatch({ type: "TOGGLE_ENABLE_YAXIS_LIMITS" });
   };
 
+  const setSpanGaps = (value: boolean) => {
+    graphDispatch({ type: "SET_SPAN_GAPS", payload: value });
+  };
+
   const handleChangeDisplayType = (newValue: string) => {
     setDisplayType(newValue as DisplayType);
   };
@@ -137,6 +141,7 @@ const QueryAnalyzerView: FC<Props> = ({ data, period }) => {
                 yaxis={yaxis}
                 setYaxisLimits={setYaxisLimits}
                 toggleEnableLimits={toggleEnableLimits}
+                spanGaps={{ value: spanGaps, onChange: setSpanGaps }}
               />
             )}
             {displayType === "table" && (
@@ -161,6 +166,7 @@ const QueryAnalyzerView: FC<Props> = ({ data, period }) => {
             setPeriod={() => null}
             height={isMobile ? window.innerHeight * 0.5 : 500}
             isHistogram={isHistogram}
+            spanGaps={spanGaps}
           />
         )}
         {liveData && (displayType === "code") && (

app/vmui/packages/vmui/src/state/graph/reducer.ts

@@ -15,6 +15,8 @@ export interface GraphState {
   customStep: string
   yaxis: YaxisState
   isHistogram: boolean
+  /** when true, null data values will not cause line breaks */
+  spanGaps: boolean
 }
 
 export type GraphAction =
@@ -22,13 +24,15 @@ export type GraphAction =
   | { type: "SET_YAXIS_LIMITS", payload: AxisRange }
   | { type: "SET_CUSTOM_STEP", payload: string}
   | { type: "SET_IS_HISTOGRAM", payload: boolean }
+  | { type: "SET_SPAN_GAPS", payload: boolean }
 
 export const initialGraphState: GraphState = {
   customStep: getQueryStringValue("g0.step_input", "") as string,
   yaxis: {
     limits: { enable: false, range: { "1": [0, 0] } }
   },
-  isHistogram: false
+  isHistogram: false,
+  spanGaps: false,
 };
 
 export function reducer(state: GraphState, action: GraphAction): GraphState {
@@ -65,6 +69,11 @@ export function reducer(state: GraphState, action: GraphAction): GraphState {
         ...state,
         isHistogram: action.payload
       };
+    case "SET_SPAN_GAPS":
+      return {
+        ...state,
+        spanGaps: action.payload
+      };
     default:
       throw new Error();
   }

app/vmui/packages/vmui/src/utils/uplot/series.ts

@@ -94,6 +94,7 @@ export const getSeriesItemContext = (data: MetricResult[], hideSeries: string[],
       width,
       stroke,
       points,
+      spanGaps: false,
       forecast: forecast.value,
       forecastGroup: forecast.group,
       freeFormFields: d.metric,
@@ -165,8 +166,9 @@ export const delSeries = (u: uPlot) => {
   }
 };
 
-export const addSeries = (u: uPlot, series: uPlotSeries[]) => {
+export const addSeries = (u: uPlot, series: uPlotSeries[], spanGaps = false) => {
   series.forEach((s) => {
+    if (s.label) s.spanGaps = spanGaps;
     u.addSeries(s);
   });
 };

deployment/docker/Makefile

@@ -5,7 +5,7 @@ DOCKER_NAMESPACE ?= victoriametrics
 ROOT_IMAGE ?= alpine:3.19.1
 CERTS_IMAGE := alpine:3.19.1
 
-GO_BUILDER_IMAGE := golang:1.22.0-alpine
+GO_BUILDER_IMAGE := golang:1.21.7-alpine
 BUILDER_IMAGE := local/builder:2.0.0-$(shell echo $(GO_BUILDER_IMAGE) | tr :/ __)-1
 BASE_IMAGE := local/base:1.1.4-$(shell echo $(ROOT_IMAGE) | tr :/ __)-$(shell echo $(CERTS_IMAGE) | tr :/ __)
 DOCKER ?= docker
@@ -204,3 +204,9 @@ docker-cluster-vm-datasource-up:
 
 docker-cluster-vm-datasource-down:
 	$(DOCKER_COMPOSE) -f deployment/docker/docker-compose-cluster.yml -f deployment/docker/vm-datasource/docker-compose-cluster.yml down -v
+
+docker-victorialogs-up:
+	$(DOCKER_COMPOSE) -f deployment/docker/docker-compose-victorialogs.yml up -d
+
+docker-victorialogs-down:
+	$(DOCKER_COMPOSE) -f deployment/docker/docker-compose-victorialogs.yml down -v

deployment/docker/README.md

@@ -38,6 +38,8 @@ The communication scheme between components is the following:
   and recording rules back to it;
 * [alertmanager](#alertmanager) is configured to receive notifications from `vmalert`.
 
+<img alt="VictoriaMetrics single-server deployment" width="500" src="assets/vm-single-server.png">
+
 To access Grafana use link [http://localhost:3000](http://localhost:3000).
 
 To access [vmui](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#vmui)
@@ -72,6 +74,8 @@ The communication scheme between components is the following:
   and recording rules to `vminsert`;
 * [alertmanager](#alertmanager) is configured to receive notifications from `vmalert`.
 
+<img alt="VictoriaMetrics cluster deployment" width="500" src="assets/vm-cluster.png">
+
 To access Grafana use link [http://localhost:3000](http://localhost:3000).
 
 To access [vmui](https://docs.victoriametrics.com/Single-server-VictoriaMetrics.html#vmui)
@@ -165,13 +169,26 @@ VictoriaMetrics installations.
 
 ## VictoriaLogs server
 
-VictoriaLogs will be accessible on the following port: `--httpListenAddr=:9428`
+To spin-up environment with VictoriaLogs run the following command:
+```
+make docker-victorialogs-up
+```
 
-[Fluent Bit](https://docs.fluentbit.io/manual) is used to send logs to VictoriaLogs instance.
-Fluent Bit is configured to send logs from running containers to VictoriaLogs instance.
-Additionally, it is configured to listen for syslog logs on port `5140` and send them to VictoriaLogs instance.
+VictoriaLogs will be accessible on the `--httpListenAddr=:9428` port.
+In addition to VictoriaLogs server, the docker compose contains the following componetns:
+* [fluentbit](https://docs.fluentbit.io/manual) service for collecting docker logs and sending them to VictoriaLogs;
+* VictoriaMetrics single server to collect metrics from `VictoriaLogs` and `fluentbit`;
+* [grafana](#grafana) is configured with [VictoriaLogs datasource](https://github.com/VictoriaMetrics/victorialogs-datasource).
 
-To access VictoriaLogs UI use link [http://localhost:9428/select/vmui/](http://localhost:9428/select/vmui/).
+To access Grafana use link [http://localhost:3000](http://localhost:3000).
+
+To access [VictoriaLogs UI](https://docs.victoriametrics.com/victorialogs/querying/#web-ui)
+use link [http://localhost:9428/select/vmui](http://localhost:9428/select/vmui).
 
 Please, also see [how to monitor](https://docs.victoriametrics.com/VictoriaLogs/#monitoring) 
 VictoriaLogs installations.
+
+To shutdown environment execute the following command:
+```
+make docker-victorialogs-down
+```

deployment/docker/docker-compose-cluster.yml

@@ -153,7 +153,7 @@ services:
   # and distributes them according to --config.file.
   alertmanager:
     container_name: alertmanager
-    image: prom/alertmanager:v0.25.0
+    image: prom/alertmanager:v0.27.0
     volumes:
       - ./alertmanager.yml:/config/alertmanager.yml
     command:

deployment/docker/docker-compose-victorialogs.yml

@@ -0,0 +1,80 @@
+version: "3.5"
+services:
+  # Grafana instance configured with VictoriaLogs as datasource
+  grafana:
+    container_name: grafana
+    image: grafana/grafana:10.3.1
+    depends_on:
+      - "victoriametrics"
+      - "victorialogs"
+    ports:
+      - 3000:3000
+    entrypoint: [ "/bin/bash", "-c" ]
+    command: [ "chmod +x /download.sh && /download.sh && /run.sh" ]
+    volumes:
+      - grafanadata:/var/lib/grafana
+      - ./provisioning/datasources/victorialogs-datasource:/etc/grafana/provisioning/datasources
+      - ./provisioning/dashboards:/etc/grafana/provisioning/dashboards
+      - ./provisioning/plugins/:/var/lib/grafana/plugins
+      - ./../../dashboards/victoriametrics.json:/var/lib/grafana/dashboards/vm.json
+      - ./../../dashboards/victorialogs.json:/var/lib/grafana/dashboards/vl.json
+      - ./victorialogs/download.sh:/download.sh
+    environment:
+      - "GF_PLUGINS_ALLOW_LOADING_UNSIGNED_PLUGINS=victorialogs-datasource"
+    networks:
+      - vm_net
+    restart: always
+
+  # fluentbit is logs collector. It collects logs according to fluent-bit.conf
+  # and forwards them to VictoriaLogs
+  fluentbit:
+    container_name: fluentbit
+    image: cr.fluentbit.io/fluent/fluent-bit:2.1.4
+    volumes:
+      - /var/lib/docker/containers:/var/lib/docker/containers:ro
+      - ./fluent-bit.conf:/fluent-bit/etc/fluent-bit.conf
+    depends_on: [victorialogs]
+    ports:
+      - "5140:5140"
+    networks:
+      - vm_net
+
+#  VictoriaLogs instance, a single process responsible for
+#  storing logs and serving read queries.
+  victorialogs:
+    container_name: victorialogs
+    image: docker.io/victoriametrics/victoria-logs:v0.4.2-victorialogs
+    command:
+      - "--storageDataPath=/vlogs"
+      - "--httpListenAddr=:9428"
+    volumes:
+      - vldata:/vlogs
+    ports:
+      - "9428:9428"
+    networks:
+      - vm_net
+
+  # VictoriaMetrics instance, a single process responsible for
+  # scraping, storing metrics and serve read requests.
+  victoriametrics:
+    container_name: victoriametrics
+    image: victoriametrics/victoria-metrics:v1.98.0
+    ports:
+      - 8428:8428
+    volumes:
+      - vmdata:/storage
+      - ./prometheus-victorialogs.yml:/etc/prometheus/prometheus.yml
+    command:
+      - "--storageDataPath=/storage"
+      - "--httpListenAddr=:8428"
+      - "--promscrape.config=/etc/prometheus/prometheus.yml"
+    networks:
+      - vm_net
+    restart: always
+
+volumes:
+  vmdata: {}
+  vldata: {}
+  grafanadata: {}
+networks:
+  vm_net:

deployment/docker/docker-compose.yml

@@ -57,7 +57,6 @@ services:
       - ./provisioning/datasources/prometheus-datasource:/etc/grafana/provisioning/datasources
       - ./provisioning/dashboards:/etc/grafana/provisioning/dashboards
       - ./../../dashboards/victoriametrics.json:/var/lib/grafana/dashboards/vm.json
-      - ./../../dashboards/victorialogs.json:/var/lib/grafana/dashboards/vl.json
       - ./../../dashboards/vmagent.json:/var/lib/grafana/dashboards/vmagent.json
       - ./../../dashboards/vmalert.json:/var/lib/grafana/dashboards/vmalert.json
     networks:
@@ -96,7 +95,7 @@ services:
   # and distributes them according to --config.file.
   alertmanager:
     container_name: alertmanager
-    image: prom/alertmanager:v0.25.0
+    image: prom/alertmanager:v0.27.0
     volumes:
       - ./alertmanager.yml:/config/alertmanager.yml
     command:
@@ -107,38 +106,9 @@ services:
       - vm_net
     restart: always
 
-  # fluentbit is logs collector. It collects logs according to fluent-bit.conf
-  # and forwards them to VictoriaLogs
-  fluentbit:
-    container_name: fluentbit
-    image: cr.fluentbit.io/fluent/fluent-bit:2.1.4
-    volumes:
-      - /var/lib/docker/containers:/var/lib/docker/containers:ro
-      - ./fluent-bit.conf:/fluent-bit/etc/fluent-bit.conf
-    depends_on: [victorialogs]
-    ports:
-      - "5140:5140"
-    networks:
-      - vm_net
-
-#  VictoriaLogs instance, a single process responsible for
-#  storing logs and serving read queries.
-  victorialogs:
-    container_name: victorialogs
-    image: docker.io/victoriametrics/victoria-logs:v0.4.2-victorialogs
-    command:
-      - "--storageDataPath=/vlogs"
-      - "--httpListenAddr=:9428"
-    volumes:
-      - victorialogs-fluentbit:/vlogs
-    ports:
-      - "9428:9428"
-    networks:
-      - vm_net
 volumes:
   vmagentdata: {}
   vmdata: {}
   grafanadata: {}
-  victorialogs-fluentbit: {}
 networks:
   vm_net:

deployment/docker/fluent-bit.conf

@@ -16,6 +16,9 @@
 [SERVICE]
     Flush        1
     Parsers_File parsers.conf
+    HTTP_Server  On
+    HTTP_Listen  0.0.0.0
+    HTTP_PORT    2020
 
 [Output]
     Name http

deployment/docker/prometheus-victorialogs.yml

@@ -0,0 +1,13 @@
+global:
+  scrape_interval: 10s
+
+scrape_configs:
+  - job_name: 'victoriametrics'
+    static_configs:
+      - targets: ['victoriametrics:8428']
+  - job_name: 'victorialogs'
+    static_configs:
+      - targets: ['victorialogs:9428']
+  - job_name: 'fluentbit'
+    static_configs:
+      - targets: ['fluentbit:2020/api/v1/metrics/prometheus']

deployment/docker/prometheus.yml

@@ -11,6 +11,3 @@ scrape_configs:
   - job_name: 'victoriametrics'
     static_configs:
       - targets: ['victoriametrics:8428']
-  - job_name: 'victorialogs'
-    static_configs:
-      - targets: ['victorialogs:9428']

deployment/docker/provisioning/datasources/victorialogs-datasource/victorialogs-datasource.yml

@@ -0,0 +1,12 @@
+apiVersion: 1
+
+datasources:
+  - name: VictoriaLogs
+    type: victorialogs-datasource
+    access: proxy
+    url:  http://victorialogs:9428
+
+  - name: VictoriaMetrics
+    type: prometheus
+    access: proxy
+    url: http://victoriametrics:8428

deployment/docker/victorialogs/download.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+set -ex
+
+VM_DS_PATH='/var/lib/grafana/plugins/victorialogs-datasource'
+PLUGIN_PATH='/var/lib/grafana/plugins'
+
+if [[ -f ${VM_DS_PATH}/plugin.json ]]; then
+    ver=$(cat ${VM_DS_PATH}/plugin.json)
+    if [[ ! -z "$ver" ]]; then
+    exit
+    fi
+fi
+
+echo "VictoriaLogs datasource is not installed. Installing datasource..."
+rm -rf ${VM_DS_PATH}/* || true
+mkdir -p ${VM_DS_PATH}
+
+export LATEST_VERSION=$(curl https://api.github.com/repos/VictoriaMetrics/victorialogs-datasource/releases/latest | grep -oE 'v[0-9]+\.[0-9]+\.[0-9]+' | head -1); \
+curl -L https://github.com/VictoriaMetrics/victorialogs-datasource/releases/download/${LATEST_VERSION}/victorialogs-datasource-${LATEST_VERSION}.tar.gz -o ${PLUGIN_PATH}/plugin.tar.gz && \
+tar -xzf ${PLUGIN_PATH}/plugin.tar.gz -C ${PLUGIN_PATH}
+echo "VictoriaLogs datasource has been installed."
+rm ${PLUGIN_PATH}/plugin.tar.gz

deployment/docker/vm-datasource/download.sh

@@ -11,12 +11,12 @@ if [[ -f ${VM_DS_PATH}/plugin.json ]]; then
     fi
 fi
 
-echo "Victoriametrics datasource is not installed. Installing datasource..."
+echo "VictoriaMetrics datasource is not installed. Installing datasource..."
 rm -rf ${VM_DS_PATH}/* || true
 mkdir -p ${VM_DS_PATH}
 
 export LATEST_VERSION=$(curl https://api.github.com/repos/VictoriaMetrics/grafana-datasource/releases/latest | grep -oE 'v[0-9]+\.[0-9]+\.[0-9]+' | head -1); \
 curl -L https://github.com/VictoriaMetrics/grafana-datasource/releases/download/${LATEST_VERSION}/victoriametrics-datasource-${LATEST_VERSION}.tar.gz -o ${PLUGIN_PATH}/plugin.tar.gz && \
 tar -xzf ${PLUGIN_PATH}/plugin.tar.gz -C ${PLUGIN_PATH}
-echo "Victoriametrics datasource has been installed."
+echo "VictoriaMetrics datasource has been installed."
 rm ${PLUGIN_PATH}/plugin.tar.gz

deployment/docker/vmanomaly/vmanomaly-integration/docker-compose.yml

@@ -73,7 +73,7 @@ services:
     restart: always
   vmanomaly:
     container_name: vmanomaly
-    image: victoriametrics/vmanomaly:v1.10.0
+    image: victoriametrics/vmanomaly:v1.11.0
     depends_on:
       - "victoriametrics"
     ports:
@@ -90,7 +90,7 @@ services:
       - "--license-file=/license"
   alertmanager:
     container_name: alertmanager
-    image: prom/alertmanager:v0.25.0
+    image: prom/alertmanager:v0.27.0
     volumes:
       - ./alertmanager.yml:/config/alertmanager.yml
     command: