- Use bytesutil.InternString() instead of strings.Clone() for inputKey and outputKey in aggregatorpushSamples().
This should reduce string allocation rate, since strings can be re-used between aggrState flushes.
- Reduce memory allocations at dedupAggrShard by storing dedupAggrSample by value in the active series map.
- Remove duplicate call to bytesutil.InternBytes() at Deduplicator, since it is already called inside dedupAggr.pushSamples().
- Add missing string interning at rateAggrState.pushSamples().
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6402
The main change is getting rid of interning of sample key. It was
discovered that for cases with many unique time series aggregated by
vmagent interned keys could grow up to hundreds of millions of objects.
This has negative impact on the following aspects:
1. It slows down garbage collection cycles, as GC has to scan all inuse
objects periodically. The higher is the number of inuse objects, the
longer it takes/the more CPU it takes.
2. It slows down the hot path of samples aggregation where each key
needs to be looked up in the map first.
The change makes code more fragile, but suppose to provide performance
optimization for heavy-loaded vmagents with stream aggregation enabled.
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
- Reduce memory usage by up to 5x when de-duplicating samples across big number of time series.
- Reduce memory usage by up to 5x when aggregating across big number of output time series.
- Add lib/promutils.LabelsCompressor, which is going to be used by other VictoriaMetrics components
for reducing memory usage for marshaled []prompbmarshal.Label.
- Add `dedup_interval` option at aggregation config, which allows setting individual
deduplication intervals per each aggregation.
- Add `keep_metric_names` option at aggregation config, which allows keeping the original
metric names in the output samples.
- Add `unique_samples` output, which counts the number of unique sample values.
- Add `increase_prometheus` and `total_prometheus` outputs, which ignore the first sample
per each newly encountered time series.
- Use 64-bit hashes instead of marshaled labels as map keys when calculating `count_series` output.
This makes obsolete https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5579
- Expose various metrics, which may help debugging stream aggregation:
- vm_streamaggr_dedup_state_size_bytes - the size of data structures responsible for deduplication
- vm_streamaggr_dedup_state_items_count - the number of items in the deduplication data structures
- vm_streamaggr_labels_compressor_size_bytes - the size of labels compressor data structures
- vm_streamaggr_labels_compressor_items_count - the number of entries in the labels compressor
- vm_streamaggr_flush_duration_seconds - a histogram, which shows the duration of stream aggregation flushes
- vm_streamaggr_dedup_flush_duration_seconds - a histogram, which shows the duration of deduplication flushes
- vm_streamaggr_flush_timeouts_total - counter for timed out stream aggregation flushes,
which took longer than the configured interval
- vm_streamaggr_dedup_flush_timeouts_total - counter for timed out deduplication flushes,
which took longer than the configured dedup_interval
- Actualize docs/stream-aggregation.md
The memory usage reduction increases CPU usage during stream aggregation by up to 30%.
This commit is based on https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5850
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5898
