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docs/CHANGELOG.md: link to the related issue for range_normalize() function

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Aliaksandr Valialkin 2022-11-21 23:27:00 +02:00
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@ -17,7 +17,7 @@ The following tip changes can be tested by building VictoriaMetrics components f
* FEATURE: [VictoriaMetrics enterprise](https://docs.victoriametrics.com/enterprise.html): add `-storageNode.filter` command-line flag for filtering the [discovered vmstorage nodes](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html#automatic-vmstorage-discovery) with arbitrary regular expressions. See [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3353). * FEATURE: [VictoriaMetrics enterprise](https://docs.victoriametrics.com/enterprise.html): add `-storageNode.filter` command-line flag for filtering the [discovered vmstorage nodes](https://docs.victoriametrics.com/Cluster-VictoriaMetrics.html#automatic-vmstorage-discovery) with arbitrary regular expressions. See [this feature request](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3353).
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): allow using numeric values with `K`, `Ki`, `M`, `Mi`, `G`, `Gi`, `T` and `Ti` suffixes inside MetricsQL queries. For example `8Ki` equals to `8*1024`, while `8.2M` equals to `8.2*1000*1000`. * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): allow using numeric values with `K`, `Ki`, `M`, `Mi`, `G`, `Gi`, `T` and `Ti` suffixes inside MetricsQL queries. For example `8Ki` equals to `8*1024`, while `8.2M` equals to `8.2*1000*1000`.
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_normalize](https://docs.victoriametrics.com/MetricsQL.html#range_normalize) function for normalizing multiple time series into `[0...1]` value range. This function is useful for correlation analyzis of time series with distinct value ranges. * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_normalize](https://docs.victoriametrics.com/MetricsQL.html#range_normalize) function for normalizing multiple time series into `[0...1]` value range. This function is useful for correlation analyzis of time series with distinct value ranges. See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3167).
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_linear_regression](https://docs.victoriametrics.com/MetricsQL.html#range_linear_regression) function for calculating [simple linear regression](https://en.wikipedia.org/wiki/Simple_linear_regression) over the input time series on the selected time range. This function is useful for predictions and capacity planning. For example, `range_linear_regression(process_resident_memory_bytes)` can predict future memory usage based on the past memory usage. * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_linear_regression](https://docs.victoriametrics.com/MetricsQL.html#range_linear_regression) function for calculating [simple linear regression](https://en.wikipedia.org/wiki/Simple_linear_regression) over the input time series on the selected time range. This function is useful for predictions and capacity planning. For example, `range_linear_regression(process_resident_memory_bytes)` can predict future memory usage based on the past memory usage.
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_stddev](https://docs.victoriametrics.com/MetricsQL.html#range_stddev) and [range_stdvar](https://docs.victoriametrics.com/MetricsQL.html#range_stdvar) functions. * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): add [range_stddev](https://docs.victoriametrics.com/MetricsQL.html#range_stddev) and [range_stdvar](https://docs.victoriametrics.com/MetricsQL.html#range_stdvar) functions.
* FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): optimize `expr1 op expr2` query when `expr1` returns an empty result. In this case there is no sense in executing `expr2` for `op` not equal to `or`, since the end result will be empty according to [PromQL series matching rules](https://prometheus.io/docs/prometheus/latest/querying/operators/#vector-matching). See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3349). Thanks to @jianglinjian for pointing to this case. * FEATURE: [MetricsQL](https://docs.victoriametrics.com/MetricsQL.html): optimize `expr1 op expr2` query when `expr1` returns an empty result. In this case there is no sense in executing `expr2` for `op` not equal to `or`, since the end result will be empty according to [PromQL series matching rules](https://prometheus.io/docs/prometheus/latest/querying/operators/#vector-matching). See [this issue](https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3349). Thanks to @jianglinjian for pointing to this case.