mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
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ab88890523
This may reduce response times for aggregation over big number of time series with small step between output data points.
187 lines
4.9 KiB
Go
187 lines
4.9 KiB
Go
package promql
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import (
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"fmt"
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"math"
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"reflect"
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"runtime"
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"sync"
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"testing"
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)
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func TestIncrementalAggr(t *testing.T) {
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defaultTimestamps := []int64{100e3, 200e3, 300e3, 400e3}
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values := [][]float64{
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{1, nan, 2, nan},
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{3, nan, nan, 4},
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{nan, nan, 5, 6},
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{7, nan, 8, 9},
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{4, nan, nan, nan},
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{2, nan, 3, 2},
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{0, nan, 1, 1},
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}
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tssSrc := make([]*timeseries, len(values))
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for i, vs := range values {
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ts := ×eries{
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Timestamps: defaultTimestamps,
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Values: vs,
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}
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tssSrc[i] = ts
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}
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copyTimeseries := func(tssSrc []*timeseries) []*timeseries {
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tssDst := make([]*timeseries, len(tssSrc))
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for i, tsSrc := range tssSrc {
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var tsDst timeseries
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tsDst.CopyFromShallowTimestamps(tsSrc)
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tssDst[i] = &tsDst
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}
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return tssDst
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}
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f := func(name string, valuesExpected []float64) {
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t.Helper()
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callbacks := getIncrementalAggrFuncCallbacks(name)
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ae := &aggrFuncExpr{
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Name: name,
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}
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tssExpected := []*timeseries{{
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Timestamps: defaultTimestamps,
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Values: valuesExpected,
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}}
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// run the test multiple times to make sure there are no side effects on concurrency
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for i := 0; i < 10; i++ {
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iafc := newIncrementalAggrFuncContext(ae, callbacks)
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tssSrcCopy := copyTimeseries(tssSrc)
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if err := testIncrementalParallelAggr(iafc, tssSrcCopy, tssExpected); err != nil {
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t.Fatalf("unexpected error on iteration %d: %s", i, err)
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}
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}
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}
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t.Run("sum", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{17, nan, 19, 22}
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f("sum", valuesExpected)
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})
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t.Run("min", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{0, nan, 1, 1}
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f("min", valuesExpected)
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})
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t.Run("max", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{7, nan, 8, 9}
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f("max", valuesExpected)
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})
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t.Run("avg", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{2.8333333333333335, nan, 3.8, 4.4}
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f("avg", valuesExpected)
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})
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t.Run("count", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{6, 0, 5, 5}
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f("count", valuesExpected)
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})
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t.Run("sum2", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{79, nan, 103, 138}
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f("sum2", valuesExpected)
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})
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t.Run("geomean", func(t *testing.T) {
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t.Parallel()
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valuesExpected := []float64{0, nan, 2.9925557394776896, 3.365865436338599}
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f("geomean", valuesExpected)
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})
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}
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func testIncrementalParallelAggr(iafc *incrementalAggrFuncContext, tssSrc, tssExpected []*timeseries) error {
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const workersCount = 3
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tsCh := make(chan *timeseries)
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var wg sync.WaitGroup
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wg.Add(workersCount)
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for i := 0; i < workersCount; i++ {
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go func(workerID uint) {
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defer wg.Done()
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for ts := range tsCh {
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runtime.Gosched() // allow other goroutines performing the work
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iafc.updateTimeseries(ts, workerID)
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}
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}(uint(i))
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}
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for _, ts := range tssSrc {
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tsCh <- ts
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}
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close(tsCh)
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wg.Wait()
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tssActual := iafc.finalizeTimeseries()
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if err := expectTimeseriesEqual(tssActual, tssExpected); err != nil {
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return fmt.Errorf("%s; tssActual=%v, tssExpected=%v", err, tssActual, tssExpected)
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}
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return nil
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}
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func expectTimeseriesEqual(actual, expected []*timeseries) error {
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if len(actual) != len(expected) {
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return fmt.Errorf("unexpected number of time series; got %d; want %d", len(actual), len(expected))
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}
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mActual := timeseriesToMap(actual)
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mExpected := timeseriesToMap(expected)
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if len(mActual) != len(mExpected) {
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return fmt.Errorf("unexpected number of time series after converting to map; got %d; want %d", len(mActual), len(mExpected))
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}
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for k, tsExpected := range mExpected {
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tsActual := mActual[k]
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if tsActual == nil {
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return fmt.Errorf("missing time series for key=%q", k)
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}
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if err := expectTsEqual(tsActual, tsExpected); err != nil {
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return err
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}
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}
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return nil
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}
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func timeseriesToMap(tss []*timeseries) map[string]*timeseries {
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m := make(map[string]*timeseries, len(tss))
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for _, ts := range tss {
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k := ts.MetricName.Marshal(nil)
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m[string(k)] = ts
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}
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return m
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}
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func expectTsEqual(actual, expected *timeseries) error {
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mnActual := actual.MetricName.Marshal(nil)
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mnExpected := expected.MetricName.Marshal(nil)
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if string(mnActual) != string(mnExpected) {
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return fmt.Errorf("unexpected metric name; got %q; want %q", mnActual, mnExpected)
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}
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if !reflect.DeepEqual(actual.Timestamps, expected.Timestamps) {
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return fmt.Errorf("unexpected timestamps; got %v; want %v", actual.Timestamps, expected.Timestamps)
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}
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if err := compareValues(actual.Values, expected.Values); err != nil {
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return fmt.Errorf("%s; actual %v; expected %v", err, actual.Values, expected.Values)
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}
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return nil
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}
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func compareValues(vs1, vs2 []float64) error {
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if len(vs1) != len(vs2) {
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return fmt.Errorf("unexpected number of values; got %d; want %d", len(vs1), len(vs2))
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}
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for i, v1 := range vs1 {
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v2 := vs2[i]
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if math.IsNaN(v1) {
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if !math.IsNaN(v2) {
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return fmt.Errorf("unexpected value; got %v; want %v", v1, v2)
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}
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continue
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}
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if v1 != v2 {
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return fmt.Errorf("unexpected value; got %v; want %v", v1, v2)
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}
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}
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return nil
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}
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