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https://github.com/VictoriaMetrics/VictoriaMetrics.git
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0d5d46f9db
- 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
119 lines
2.4 KiB
Go
119 lines
2.4 KiB
Go
package promutils
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import (
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"fmt"
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"sync"
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"testing"
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"github.com/VictoriaMetrics/VictoriaMetrics/lib/prompbmarshal"
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)
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func TestLabelsCompressorSerial(t *testing.T) {
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var lc LabelsCompressor
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f := func(labels []prompbmarshal.Label) {
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t.Helper()
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sExpected := labelsToString(labels)
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data := lc.Compress(nil, labels)
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labelsResult := lc.Decompress(nil, data)
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sResult := labelsToString(labelsResult)
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if sExpected != sResult {
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t.Fatalf("unexpected result; got %s; want %s", sResult, sExpected)
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}
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if len(labels) > 0 {
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if n := lc.SizeBytes(); n == 0 {
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t.Fatalf("Unexpected zero SizeBytes()")
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}
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if n := lc.ItemsCount(); n == 0 {
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t.Fatalf("Unexpected zero ItemsCount()")
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}
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}
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}
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// empty labels
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f(nil)
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f([]prompbmarshal.Label{})
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// non-empty labels
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f([]prompbmarshal.Label{
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{
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Name: "instance",
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Value: "12345.4342.342.3",
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},
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{
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Name: "job",
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Value: "kube-pod-12323",
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},
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})
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f([]prompbmarshal.Label{
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{
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Name: "instance",
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Value: "12345.4342.342.3",
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},
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{
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Name: "job",
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Value: "kube-pod-12323",
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},
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{
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Name: "pod",
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Value: "foo-bar-baz",
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},
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})
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}
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func TestLabelsCompressorConcurrent(t *testing.T) {
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const concurrency = 5
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var lc LabelsCompressor
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var wg sync.WaitGroup
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for i := 0; i < concurrency; i++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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series := newTestSeries(100, 20)
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for i, labels := range series {
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sExpected := labelsToString(labels)
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data := lc.Compress(nil, labels)
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labelsResult := lc.Decompress(nil, data)
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sResult := labelsToString(labelsResult)
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if sExpected != sResult {
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panic(fmt.Errorf("unexpected result on iteration %d; got %s; want %s", i, sResult, sExpected))
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}
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}
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}()
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}
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wg.Wait()
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if n := lc.SizeBytes(); n == 0 {
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t.Fatalf("Unexpected zero SizeBytes()")
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}
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if n := lc.ItemsCount(); n == 0 {
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t.Fatalf("Unexpected zero ItemsCount()")
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}
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}
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func labelsToString(labels []prompbmarshal.Label) string {
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l := Labels{
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Labels: labels,
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}
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return l.String()
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}
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func newTestSeries(seriesCount, labelsPerSeries int) [][]prompbmarshal.Label {
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series := make([][]prompbmarshal.Label, seriesCount)
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for i := 0; i < seriesCount; i++ {
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labels := make([]prompbmarshal.Label, labelsPerSeries)
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for j := 0; j < labelsPerSeries; j++ {
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labels[j] = prompbmarshal.Label{
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Name: fmt.Sprintf("label_%d", j),
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Value: fmt.Sprintf("value_%d_%d", i, j),
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}
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}
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series[i] = labels
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}
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return series
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}
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