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docs: add case for histograms aggregation (#4702)

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docs: add case for histograms aggregation

Signed-off-by: hagen1778 <roman@victoriametrics.com>

---------

Signed-off-by: hagen1778 <roman@victoriametrics.com>
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Roman Khavronenko 2023-07-24 15:04:49 +02:00 committed by GitHub
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docs/stream-aggregation.md
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@ -64,6 +64,7 @@ Stream aggregation can be used as [statsd](https://github.com/statsd/statsd) alt
* [Summing input metrics](#summing-input-metrics)
* [Quantiles over input metrics](#quantiles-over-input-metrics)
* [Histograms over input metrics](#histograms-over-input-metrics)
* [Aggregating histograms](#aggregating-histograms)
Currently, streaming aggregation is available only for [supported data ingestion protocols](https://docs.victoriametrics.com/#how-to-import-time-series-data)
and not available for [Statsd metrics format](https://github.com/statsd/statsd/blob/master/docs/metric_types.md).
@ -140,7 +141,7 @@ some_metric:5m_max
```
See [the list of aggregate output](#aggregation-outputs), which can be specified at `output` field.
See also [aggregating by labels](#aggregating-by-labels).
See also [aggregating histograms](#aggregating-histograms) and [aggregating by labels](#aggregating-by-labels).
### Reducing the number of stored series
@ -165,7 +166,7 @@ http_requests_total:30s_without_path_user_total
```
See [the list of aggregate output](#aggregation-outputs), which can be specified at `output` field.
See also [aggregating histograms](#aggregating-histograms).
### Counting input samples
@ -308,6 +309,48 @@ The resulting histogram buckets can be queried with [MetricsQL](https://docs.vic
See [the list of aggregate output](#aggregation-outputs), which can be specified at `output` field.
See also [quantiles over input metrics](#quantiles-over-input-metrics) and [aggregating by labels](#aggregating-by-labels).
### Aggregating histograms
[Histogram](https://docs.victoriametrics.com/keyConcepts.html#histogram) is a set of [counter](https://docs.victoriametrics.com/keyConcepts.html#counter)
metrics with different `vmrange` or `le` labels. As they're counters, the applicable aggregation output is
[total](https://docs.victoriametrics.com/stream-aggregation.html#total):
```yaml
- match: 'http_request_duration_seconds_bucket'
interval: 1m
without: [instance]
outputs: [total]
output_relabel_configs:
- source_labels: [__name__]
target_label: __name__
```
This config generates the following output metrics according to [output metric naming](#output-metric-names):
```
http_request_duration_seconds_bucket:1m_without_instance_total{le="0.1"} value1
http_request_duration_seconds_bucket:1m_without_instance_total{le="0.2"} value2
http_request_duration_seconds_bucket:1m_without_instance_total{le="0.4"} value3
http_request_duration_seconds_bucket:1m_without_instance_total{le="1"} value4
http_request_duration_seconds_bucket:1m_without_instance_total{le="3"} value5
http_request_duration_seconds_bucket:1m_without_instance_total{le="8"} value6
http_request_duration_seconds_bucket:1m_without_instance_total{le="20"} value7
http_request_duration_seconds_bucket:1m_without_instance_total{le="60"} value8
http_request_duration_seconds_bucket:1m_without_instance_total{le="120"} value9
http_request_duration_seconds_bucket:1m_without_instance_total{le="+Inf" value10
```
The resulting metrics can be used in [histogram_quantile](https://docs.victoriametrics.com/MetricsQL.html#histogram_quantile)
function:
```metricsql
histogram_quantile(0.9, sum(rate(http_request_duration_seconds_bucket:1m_without_instance_total[5m])) by(le))
```
Please note, histograms can be aggregated if their `le` labels are configured identically.
[VictoriaMetrics histogram buckets](https://valyala.medium.com/improving-histogram-usability-for-prometheus-and-grafana-bc7e5df0e350)
have no such requirement.
See [the list of aggregate output](#aggregation-outputs), which can be specified at `output` field.
See also [histograms over input metrics](#histograms-over-input-metrics) and [quantiles over input metrics](#quantiles-over-input-metrics).
## Output metric names
@ -476,6 +519,7 @@ For example, see below time series produced by config with aggregation interval
`histogram_bucket` returns [VictoriaMetrics histogram buckets](https://valyala.medium.com/improving-histogram-usability-for-prometheus-and-grafana-bc7e5df0e350)
for the input [sample values](https://docs.victoriametrics.com/keyConcepts.html#raw-samples).
`histogram_bucket` makes sense only for aggregating [gauge](https://docs.victoriametrics.com/keyConcepts.html#gauge) metrics.
See how to aggregate regular histograms [here](#aggregating-histograms).
The results of `histogram_bucket` with aggregation interval of `1m` is equal to the `histogram_over_time(some_histogram_bucket[1m])` query.