prometheus/promql/engine_test.go

4875 lines
131 KiB
Go

// Copyright 2016 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package promql
import (
"context"
"errors"
"fmt"
"math"
"os"
"sort"
"testing"
"time"
"github.com/go-kit/log"
"github.com/stretchr/testify/require"
"go.uber.org/goleak"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/model/timestamp"
"github.com/prometheus/prometheus/promql/parser"
"github.com/prometheus/prometheus/promql/parser/posrange"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/tsdb/tsdbutil"
"github.com/prometheus/prometheus/util/annotations"
"github.com/prometheus/prometheus/util/stats"
"github.com/prometheus/prometheus/util/teststorage"
"github.com/prometheus/prometheus/util/testutil"
)
func TestMain(m *testing.M) {
goleak.VerifyTestMain(m)
}
func TestQueryConcurrency(t *testing.T) {
maxConcurrency := 10
dir, err := os.MkdirTemp("", "test_concurrency")
require.NoError(t, err)
defer os.RemoveAll(dir)
queryTracker := NewActiveQueryTracker(dir, maxConcurrency, nil)
t.Cleanup(queryTracker.Close)
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 100 * time.Second,
ActiveQueryTracker: queryTracker,
}
engine := NewEngine(opts)
ctx, cancelCtx := context.WithCancel(context.Background())
defer cancelCtx()
block := make(chan struct{})
processing := make(chan struct{})
done := make(chan int)
defer close(done)
f := func(context.Context) error {
select {
case processing <- struct{}{}:
case <-done:
}
select {
case <-block:
case <-done:
}
return nil
}
for i := 0; i < maxConcurrency; i++ {
q := engine.newTestQuery(f)
go q.Exec(ctx)
select {
case <-processing:
// Expected.
case <-time.After(20 * time.Millisecond):
require.Fail(t, "Query within concurrency threshold not being executed")
}
}
q := engine.newTestQuery(f)
go q.Exec(ctx)
select {
case <-processing:
require.Fail(t, "Query above concurrency threshold being executed")
case <-time.After(20 * time.Millisecond):
// Expected.
}
// Terminate a running query.
block <- struct{}{}
select {
case <-processing:
// Expected.
case <-time.After(20 * time.Millisecond):
require.Fail(t, "Query within concurrency threshold not being executed")
}
// Terminate remaining queries.
for i := 0; i < maxConcurrency; i++ {
block <- struct{}{}
}
}
func TestQueryTimeout(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 5 * time.Millisecond,
}
engine := NewEngine(opts)
ctx, cancelCtx := context.WithCancel(context.Background())
defer cancelCtx()
query := engine.newTestQuery(func(ctx context.Context) error {
time.Sleep(100 * time.Millisecond)
return contextDone(ctx, "test statement execution")
})
res := query.Exec(ctx)
require.Error(t, res.Err, "expected timeout error but got none")
var e ErrQueryTimeout
require.ErrorAs(t, res.Err, &e, "expected timeout error but got: %s", res.Err)
}
const errQueryCanceled = ErrQueryCanceled("test statement execution")
func TestQueryCancel(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
}
engine := NewEngine(opts)
ctx, cancelCtx := context.WithCancel(context.Background())
defer cancelCtx()
// Cancel a running query before it completes.
block := make(chan struct{})
processing := make(chan struct{})
query1 := engine.newTestQuery(func(ctx context.Context) error {
processing <- struct{}{}
<-block
return contextDone(ctx, "test statement execution")
})
var res *Result
go func() {
res = query1.Exec(ctx)
processing <- struct{}{}
}()
<-processing
query1.Cancel()
block <- struct{}{}
<-processing
require.Error(t, res.Err, "expected cancellation error for query1 but got none")
require.Equal(t, errQueryCanceled, res.Err)
// Canceling a query before starting it must have no effect.
query2 := engine.newTestQuery(func(ctx context.Context) error {
return contextDone(ctx, "test statement execution")
})
query2.Cancel()
res = query2.Exec(ctx)
require.NoError(t, res.Err)
}
// errQuerier implements storage.Querier which always returns error.
type errQuerier struct {
err error
}
func (q *errQuerier) Select(context.Context, bool, *storage.SelectHints, ...*labels.Matcher) storage.SeriesSet {
return errSeriesSet{err: q.err}
}
func (*errQuerier) LabelValues(context.Context, string, ...*labels.Matcher) ([]string, annotations.Annotations, error) {
return nil, nil, nil
}
func (*errQuerier) LabelNames(context.Context, ...*labels.Matcher) ([]string, annotations.Annotations, error) {
return nil, nil, nil
}
func (*errQuerier) Close() error { return nil }
// errSeriesSet implements storage.SeriesSet which always returns error.
type errSeriesSet struct {
err error
}
func (errSeriesSet) Next() bool { return false }
func (errSeriesSet) At() storage.Series { return nil }
func (e errSeriesSet) Err() error { return e.err }
func (e errSeriesSet) Warnings() annotations.Annotations { return nil }
func TestQueryError(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
}
engine := NewEngine(opts)
errStorage := ErrStorage{errors.New("storage error")}
queryable := storage.QueryableFunc(func(mint, maxt int64) (storage.Querier, error) {
return &errQuerier{err: errStorage}, nil
})
ctx, cancelCtx := context.WithCancel(context.Background())
defer cancelCtx()
vectorQuery, err := engine.NewInstantQuery(ctx, queryable, nil, "foo", time.Unix(1, 0))
require.NoError(t, err)
res := vectorQuery.Exec(ctx)
require.Error(t, res.Err, "expected error on failed select but got none")
require.ErrorIs(t, res.Err, errStorage, "expected error doesn't match")
matrixQuery, err := engine.NewInstantQuery(ctx, queryable, nil, "foo[1m]", time.Unix(1, 0))
require.NoError(t, err)
res = matrixQuery.Exec(ctx)
require.Error(t, res.Err, "expected error on failed select but got none")
require.ErrorIs(t, res.Err, errStorage, "expected error doesn't match")
}
type noopHintRecordingQueryable struct {
hints []*storage.SelectHints
}
func (h *noopHintRecordingQueryable) Querier(int64, int64) (storage.Querier, error) {
return &hintRecordingQuerier{Querier: &errQuerier{}, h: h}, nil
}
type hintRecordingQuerier struct {
storage.Querier
h *noopHintRecordingQueryable
}
func (h *hintRecordingQuerier) Select(ctx context.Context, sortSeries bool, hints *storage.SelectHints, matchers ...*labels.Matcher) storage.SeriesSet {
h.h.hints = append(h.h.hints, hints)
return h.Querier.Select(ctx, sortSeries, hints, matchers...)
}
func TestSelectHintsSetCorrectly(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
LookbackDelta: 5 * time.Second,
EnableAtModifier: true,
}
for _, tc := range []struct {
query string
// All times are in milliseconds.
start int64
end int64
// TODO(bwplotka): Add support for better hints when subquerying.
expected []*storage.SelectHints
}{
{
query: "foo", start: 10000,
expected: []*storage.SelectHints{
{Start: 5000, End: 10000},
},
}, {
query: "foo @ 15", start: 10000,
expected: []*storage.SelectHints{
{Start: 10000, End: 15000},
},
}, {
query: "foo @ 1", start: 10000,
expected: []*storage.SelectHints{
{Start: -4000, End: 1000},
},
}, {
query: "foo[2m]", start: 200000,
expected: []*storage.SelectHints{
{Start: 80000, End: 200000, Range: 120000},
},
}, {
query: "foo[2m] @ 180", start: 200000,
expected: []*storage.SelectHints{
{Start: 60000, End: 180000, Range: 120000},
},
}, {
query: "foo[2m] @ 300", start: 200000,
expected: []*storage.SelectHints{
{Start: 180000, End: 300000, Range: 120000},
},
}, {
query: "foo[2m] @ 60", start: 200000,
expected: []*storage.SelectHints{
{Start: -60000, End: 60000, Range: 120000},
},
}, {
query: "foo[2m] offset 2m", start: 300000,
expected: []*storage.SelectHints{
{Start: 60000, End: 180000, Range: 120000},
},
}, {
query: "foo[2m] @ 200 offset 2m", start: 300000,
expected: []*storage.SelectHints{
{Start: -40000, End: 80000, Range: 120000},
},
}, {
query: "foo[2m:1s]", start: 300000,
expected: []*storage.SelectHints{
{Start: 175000, End: 300000, Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s])", start: 300000,
expected: []*storage.SelectHints{
{Start: 175000, End: 300000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] @ 300)", start: 200000,
expected: []*storage.SelectHints{
{Start: 175000, End: 300000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] @ 200)", start: 200000,
expected: []*storage.SelectHints{
{Start: 75000, End: 200000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] @ 100)", start: 200000,
expected: []*storage.SelectHints{
{Start: -25000, End: 100000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] offset 10s)", start: 300000,
expected: []*storage.SelectHints{
{Start: 165000, End: 290000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time((foo offset 10s)[2m:1s] offset 10s)", start: 300000,
expected: []*storage.SelectHints{
{Start: 155000, End: 280000, Func: "count_over_time", Step: 1000},
},
}, {
// When the @ is on the vector selector, the enclosing subquery parameters
// don't affect the hint ranges.
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] offset 10s)", start: 300000,
expected: []*storage.SelectHints{
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
},
}, {
// When the @ is on the vector selector, the enclosing subquery parameters
// don't affect the hint ranges.
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000,
expected: []*storage.SelectHints{
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time((foo offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000,
expected: []*storage.SelectHints{
{Start: -45000, End: 80000, Func: "count_over_time", Step: 1000},
},
}, {
query: "foo", start: 10000, end: 20000,
expected: []*storage.SelectHints{
{Start: 5000, End: 20000, Step: 1000},
},
}, {
query: "foo @ 15", start: 10000, end: 20000,
expected: []*storage.SelectHints{
{Start: 10000, End: 15000, Step: 1000},
},
}, {
query: "foo @ 1", start: 10000, end: 20000,
expected: []*storage.SelectHints{
{Start: -4000, End: 1000, Step: 1000},
},
}, {
query: "rate(foo[2m] @ 180)", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: 60000, End: 180000, Range: 120000, Func: "rate", Step: 1000},
},
}, {
query: "rate(foo[2m] @ 300)", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: 180000, End: 300000, Range: 120000, Func: "rate", Step: 1000},
},
}, {
query: "rate(foo[2m] @ 60)", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: -60000, End: 60000, Range: 120000, Func: "rate", Step: 1000},
},
}, {
query: "rate(foo[2m])", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: 80000, End: 500000, Range: 120000, Func: "rate", Step: 1000},
},
}, {
query: "rate(foo[2m] offset 2m)", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 60000, End: 380000, Range: 120000, Func: "rate", Step: 1000},
},
}, {
query: "rate(foo[2m:1s])", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 175000, End: 500000, Func: "rate", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s])", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 175000, End: 500000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] offset 10s)", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 165000, End: 490000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] @ 300)", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: 175000, End: 300000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] @ 200)", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: 75000, End: 200000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time(foo[2m:1s] @ 100)", start: 200000, end: 500000,
expected: []*storage.SelectHints{
{Start: -25000, End: 100000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time((foo offset 10s)[2m:1s] offset 10s)", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 155000, End: 480000, Func: "count_over_time", Step: 1000},
},
}, {
// When the @ is on the vector selector, the enclosing subquery parameters
// don't affect the hint ranges.
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] offset 10s)", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
},
}, {
// When the @ is on the vector selector, the enclosing subquery parameters
// don't affect the hint ranges.
query: "count_over_time((foo @ 200 offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: 185000, End: 190000, Func: "count_over_time", Step: 1000},
},
}, {
query: "count_over_time((foo offset 10s)[2m:1s] @ 100 offset 10s)", start: 300000, end: 500000,
expected: []*storage.SelectHints{
{Start: -45000, End: 80000, Func: "count_over_time", Step: 1000},
},
}, {
query: "sum by (dim1) (foo)", start: 10000,
expected: []*storage.SelectHints{
{Start: 5000, End: 10000, Func: "sum", By: true, Grouping: []string{"dim1"}},
},
}, {
query: "sum without (dim1) (foo)", start: 10000,
expected: []*storage.SelectHints{
{Start: 5000, End: 10000, Func: "sum", Grouping: []string{"dim1"}},
},
}, {
query: "sum by (dim1) (avg_over_time(foo[1s]))", start: 10000,
expected: []*storage.SelectHints{
{Start: 9000, End: 10000, Func: "avg_over_time", Range: 1000},
},
}, {
query: "sum by (dim1) (max by (dim2) (foo))", start: 10000,
expected: []*storage.SelectHints{
{Start: 5000, End: 10000, Func: "max", By: true, Grouping: []string{"dim2"}},
},
}, {
query: "(max by (dim1) (foo))[5s:1s]", start: 10000,
expected: []*storage.SelectHints{
{Start: 0, End: 10000, Func: "max", By: true, Grouping: []string{"dim1"}, Step: 1000},
},
}, {
query: "(sum(http_requests{group=~\"p.*\"})+max(http_requests{group=~\"c.*\"}))[20s:5s]", start: 120000,
expected: []*storage.SelectHints{
{Start: 95000, End: 120000, Func: "sum", By: true, Step: 5000},
{Start: 95000, End: 120000, Func: "max", By: true, Step: 5000},
},
}, {
query: "foo @ 50 + bar @ 250 + baz @ 900", start: 100000, end: 500000,
expected: []*storage.SelectHints{
{Start: 45000, End: 50000, Step: 1000},
{Start: 245000, End: 250000, Step: 1000},
{Start: 895000, End: 900000, Step: 1000},
},
}, {
query: "foo @ 50 + bar + baz @ 900", start: 100000, end: 500000,
expected: []*storage.SelectHints{
{Start: 45000, End: 50000, Step: 1000},
{Start: 95000, End: 500000, Step: 1000},
{Start: 895000, End: 900000, Step: 1000},
},
}, {
query: "rate(foo[2s] @ 50) + bar @ 250 + baz @ 900", start: 100000, end: 500000,
expected: []*storage.SelectHints{
{Start: 48000, End: 50000, Step: 1000, Func: "rate", Range: 2000},
{Start: 245000, End: 250000, Step: 1000},
{Start: 895000, End: 900000, Step: 1000},
},
}, {
query: "rate(foo[2s:1s] @ 50) + bar + baz", start: 100000, end: 500000,
expected: []*storage.SelectHints{
{Start: 43000, End: 50000, Step: 1000, Func: "rate"},
{Start: 95000, End: 500000, Step: 1000},
{Start: 95000, End: 500000, Step: 1000},
},
}, {
query: "rate(foo[2s:1s] @ 50) + bar + rate(baz[2m:1s] @ 900 offset 2m) ", start: 100000, end: 500000,
expected: []*storage.SelectHints{
{Start: 43000, End: 50000, Step: 1000, Func: "rate"},
{Start: 95000, End: 500000, Step: 1000},
{Start: 655000, End: 780000, Step: 1000, Func: "rate"},
},
}, { // Hints are based on the inner most subquery timestamp.
query: `sum_over_time(sum_over_time(metric{job="1"}[100s])[100s:25s] @ 50)[3s:1s] @ 3000`, start: 100000,
expected: []*storage.SelectHints{
{Start: -150000, End: 50000, Range: 100000, Func: "sum_over_time", Step: 25000},
},
}, { // Hints are based on the inner most subquery timestamp.
query: `sum_over_time(sum_over_time(metric{job="1"}[100s])[100s:25s] @ 3000)[3s:1s] @ 50`,
expected: []*storage.SelectHints{
{Start: 2800000, End: 3000000, Range: 100000, Func: "sum_over_time", Step: 25000},
},
},
} {
t.Run(tc.query, func(t *testing.T) {
engine := NewEngine(opts)
hintsRecorder := &noopHintRecordingQueryable{}
var (
query Query
err error
)
ctx := context.Background()
if tc.end == 0 {
query, err = engine.NewInstantQuery(ctx, hintsRecorder, nil, tc.query, timestamp.Time(tc.start))
} else {
query, err = engine.NewRangeQuery(ctx, hintsRecorder, nil, tc.query, timestamp.Time(tc.start), timestamp.Time(tc.end), time.Second)
}
require.NoError(t, err)
res := query.Exec(context.Background())
require.NoError(t, res.Err)
require.Equal(t, tc.expected, hintsRecorder.hints)
})
}
}
func TestEngineShutdown(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
}
engine := NewEngine(opts)
ctx, cancelCtx := context.WithCancel(context.Background())
block := make(chan struct{})
processing := make(chan struct{})
// Shutdown engine on first handler execution. Should handler execution ever become
// concurrent this test has to be adjusted accordingly.
f := func(ctx context.Context) error {
processing <- struct{}{}
<-block
return contextDone(ctx, "test statement execution")
}
query1 := engine.newTestQuery(f)
// Stopping the engine must cancel the base context. While executing queries is
// still possible, their context is canceled from the beginning and execution should
// terminate immediately.
var res *Result
go func() {
res = query1.Exec(ctx)
processing <- struct{}{}
}()
<-processing
cancelCtx()
block <- struct{}{}
<-processing
require.Error(t, res.Err, "expected error on shutdown during query but got none")
require.Equal(t, errQueryCanceled, res.Err)
query2 := engine.newTestQuery(func(context.Context) error {
require.FailNow(t, "reached query execution unexpectedly")
return nil
})
// The second query is started after the engine shut down. It must
// be canceled immediately.
res2 := query2.Exec(ctx)
require.Error(t, res2.Err, "expected error on querying with canceled context but got none")
var e ErrQueryCanceled
require.ErrorAs(t, res2.Err, &e, "expected cancellation error but got: %s", res2.Err)
}
func TestEngineEvalStmtTimestamps(t *testing.T) {
storage := LoadedStorage(t, `
load 10s
metric 1 2
`)
t.Cleanup(func() { storage.Close() })
cases := []struct {
Query string
Result parser.Value
Start time.Time
End time.Time
Interval time.Duration
ShouldError bool
}{
// Instant queries.
{
Query: "1",
Result: Scalar{V: 1, T: 1000},
Start: time.Unix(1, 0),
},
{
Query: "metric",
Result: Vector{
Sample{
F: 1,
T: 1000,
Metric: labels.FromStrings("__name__", "metric"),
},
},
Start: time.Unix(1, 0),
},
{
Query: "metric[20s]",
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 2, T: 10000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
Start: time.Unix(10, 0),
},
// Range queries.
{
Query: "1",
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 1, T: 1000}, {F: 1, T: 2000}},
Metric: labels.EmptyLabels(),
},
},
Start: time.Unix(0, 0),
End: time.Unix(2, 0),
Interval: time.Second,
},
{
Query: "metric",
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 1, T: 1000}, {F: 1, T: 2000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
Start: time.Unix(0, 0),
End: time.Unix(2, 0),
Interval: time.Second,
},
{
Query: "metric",
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
Start: time.Unix(0, 0),
End: time.Unix(10, 0),
Interval: 5 * time.Second,
},
{
Query: `count_values("wrong label!", metric)`,
ShouldError: true,
},
}
for i, c := range cases {
t.Run(fmt.Sprintf("%d query=%s", i, c.Query), func(t *testing.T) {
var err error
var qry Query
engine := newTestEngine()
if c.Interval == 0 {
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, c.Query, c.Start)
} else {
qry, err = engine.NewRangeQuery(context.Background(), storage, nil, c.Query, c.Start, c.End, c.Interval)
}
require.NoError(t, err)
res := qry.Exec(context.Background())
if c.ShouldError {
require.Error(t, res.Err, "expected error for the query %q", c.Query)
return
}
require.NoError(t, res.Err)
require.Equal(t, c.Result, res.Value, "query %q failed", c.Query)
})
}
}
func TestQueryStatistics(t *testing.T) {
storage := LoadedStorage(t, `
load 10s
metricWith1SampleEvery10Seconds 1+1x100
metricWith3SampleEvery10Seconds{a="1",b="1"} 1+1x100
metricWith3SampleEvery10Seconds{a="2",b="2"} 1+1x100
metricWith3SampleEvery10Seconds{a="3",b="2"} 1+1x100
`)
t.Cleanup(func() { storage.Close() })
cases := []struct {
Query string
SkipMaxCheck bool
TotalSamples int64
TotalSamplesPerStep stats.TotalSamplesPerStep
PeakSamples int
Start time.Time
End time.Time
Interval time.Duration
}{
{
Query: `"literal string"`,
SkipMaxCheck: true, // This can't fail from a max samples limit.
Start: time.Unix(21, 0),
TotalSamples: 0,
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 0,
},
},
{
Query: "1",
Start: time.Unix(21, 0),
TotalSamples: 0,
PeakSamples: 1,
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 0,
},
},
{
Query: "metricWith1SampleEvery10Seconds",
Start: time.Unix(21, 0),
PeakSamples: 1,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 1,
},
},
{
// timestamp function has a special handling.
Query: "timestamp(metricWith1SampleEvery10Seconds)",
Start: time.Unix(21, 0),
PeakSamples: 2,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 1,
},
},
{
Query: "metricWith1SampleEvery10Seconds",
Start: time.Unix(22, 0),
PeakSamples: 1,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
22000: 1, // Aligned to the step time, not the sample time.
},
},
{
Query: "metricWith1SampleEvery10Seconds offset 10s",
Start: time.Unix(21, 0),
PeakSamples: 1,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 1,
},
},
{
Query: "metricWith1SampleEvery10Seconds @ 15",
Start: time.Unix(21, 0),
PeakSamples: 1,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 1,
},
},
{
Query: `metricWith3SampleEvery10Seconds{a="1"}`,
Start: time.Unix(21, 0),
PeakSamples: 1,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 1,
},
},
{
Query: `metricWith3SampleEvery10Seconds{a="1"} @ 19`,
Start: time.Unix(21, 0),
PeakSamples: 1,
TotalSamples: 1, // 1 sample / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 1,
},
},
{
Query: `metricWith3SampleEvery10Seconds{a="1"}[20s] @ 19`,
Start: time.Unix(21, 0),
PeakSamples: 2,
TotalSamples: 2, // (1 sample / 10 seconds) * 20s
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 2,
},
},
{
Query: "metricWith3SampleEvery10Seconds",
Start: time.Unix(21, 0),
PeakSamples: 3,
TotalSamples: 3, // 3 samples / 10 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
21000: 3,
},
},
{
Query: "metricWith1SampleEvery10Seconds[60s]",
Start: time.Unix(201, 0),
PeakSamples: 6,
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 6,
},
},
{
Query: "max_over_time(metricWith1SampleEvery10Seconds[59s])[20s:5s]",
Start: time.Unix(201, 0),
PeakSamples: 10,
TotalSamples: 24, // (1 sample / 10 seconds * 60 seconds) * 60/5 (using 59s so we always return 6 samples
// as if we run a query on 00 looking back 60 seconds we will return 7 samples;
// see next test).
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 24,
},
},
{
Query: "max_over_time(metricWith1SampleEvery10Seconds[60s])[20s:5s]",
Start: time.Unix(201, 0),
PeakSamples: 11,
TotalSamples: 26, // (1 sample / 10 seconds * 60 seconds) + 2 as
// max_over_time(metricWith1SampleEvery10Seconds[60s]) @ 190 and 200 will return 7 samples.
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 26,
},
},
{
Query: "metricWith1SampleEvery10Seconds[60s] @ 30",
Start: time.Unix(201, 0),
PeakSamples: 4,
TotalSamples: 4, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 1 series
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 4,
},
},
{
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30))",
Start: time.Unix(201, 0),
PeakSamples: 7,
TotalSamples: 12, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
},
},
{
Query: "sum by (b) (max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30))",
Start: time.Unix(201, 0),
PeakSamples: 8,
TotalSamples: 12, // @ modifier force the evaluation to at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
},
},
{
Query: "metricWith1SampleEvery10Seconds[60s] offset 10s",
Start: time.Unix(201, 0),
PeakSamples: 6,
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 6,
},
},
{
Query: "metricWith3SampleEvery10Seconds[60s]",
Start: time.Unix(201, 0),
PeakSamples: 18,
TotalSamples: 18, // 3 sample / 10 seconds * 60 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 18,
},
},
{
Query: "max_over_time(metricWith1SampleEvery10Seconds[60s])",
Start: time.Unix(201, 0),
PeakSamples: 7,
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 6,
},
},
{
Query: "absent_over_time(metricWith1SampleEvery10Seconds[60s])",
Start: time.Unix(201, 0),
PeakSamples: 7,
TotalSamples: 6, // 1 sample / 10 seconds * 60 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 6,
},
},
{
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s])",
Start: time.Unix(201, 0),
PeakSamples: 9,
TotalSamples: 18, // 3 sample / 10 seconds * 60 seconds
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 18,
},
},
{
Query: "metricWith1SampleEvery10Seconds[60s:5s]",
Start: time.Unix(201, 0),
PeakSamples: 12,
TotalSamples: 12, // 1 sample per query * 12 queries (60/5)
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
},
},
{
Query: "metricWith1SampleEvery10Seconds[60s:5s] offset 10s",
Start: time.Unix(201, 0),
PeakSamples: 12,
TotalSamples: 12, // 1 sample per query * 12 queries (60/5)
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
},
},
{
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s:5s])",
Start: time.Unix(201, 0),
PeakSamples: 51,
TotalSamples: 36, // 3 sample per query * 12 queries (60/5)
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 36,
},
},
{
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s]))",
Start: time.Unix(201, 0),
PeakSamples: 52,
TotalSamples: 72, // 2 * (3 sample per query * 12 queries (60/5))
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 72,
},
},
{
Query: `metricWith3SampleEvery10Seconds{a="1"}`,
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 4,
TotalSamples: 4, // 1 sample per query * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 1,
206000: 1,
211000: 1,
216000: 1,
},
},
{
Query: `metricWith3SampleEvery10Seconds{a="1"}`,
Start: time.Unix(204, 0),
End: time.Unix(223, 0),
Interval: 5 * time.Second,
PeakSamples: 4,
TotalSamples: 4, // 1 sample per query * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
204000: 1, // aligned to the step time, not the sample time
209000: 1,
214000: 1,
219000: 1,
},
},
{
// timestamp function as a special handling
Query: "timestamp(metricWith1SampleEvery10Seconds)",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 5,
TotalSamples: 4, // (1 sample / 10 seconds) * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 1,
206000: 1,
211000: 1,
216000: 1,
},
},
{
Query: `max_over_time(metricWith3SampleEvery10Seconds{a="1"}[10s])`,
Start: time.Unix(991, 0),
End: time.Unix(1021, 0),
Interval: 10 * time.Second,
PeakSamples: 2,
TotalSamples: 2, // 1 sample per query * 2 steps with data
TotalSamplesPerStep: stats.TotalSamplesPerStep{
991000: 1,
1001000: 1,
1011000: 0,
1021000: 0,
},
},
{
Query: `metricWith3SampleEvery10Seconds{a="1"} offset 10s`,
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 4,
TotalSamples: 4, // 1 sample per query * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 1,
206000: 1,
211000: 1,
216000: 1,
},
},
{
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s] @ 30)",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 12,
TotalSamples: 48, // @ modifier force the evaluation timestamp at 30 seconds - So it brings 4 datapoints (0, 10, 20, 30 seconds) * 3 series * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
206000: 12,
211000: 12,
216000: 12,
},
},
{
Query: `metricWith3SampleEvery10Seconds`,
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
PeakSamples: 12,
Interval: 5 * time.Second,
TotalSamples: 12, // 3 sample per query * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 3,
206000: 3,
211000: 3,
216000: 3,
},
},
{
Query: `max_over_time(metricWith3SampleEvery10Seconds[60s])`,
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 18,
TotalSamples: 72, // (3 sample / 10 seconds * 60 seconds) * 4 steps = 72
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 18,
206000: 18,
211000: 18,
216000: 18,
},
},
{
Query: "max_over_time(metricWith3SampleEvery10Seconds[60s:5s])",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 72,
TotalSamples: 144, // 3 sample per query * 12 queries (60/5) * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 36,
206000: 36,
211000: 36,
216000: 36,
},
},
{
Query: "max_over_time(metricWith1SampleEvery10Seconds[60s:5s])",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 32,
TotalSamples: 48, // 1 sample per query * 12 queries (60/5) * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
206000: 12,
211000: 12,
216000: 12,
},
},
{
Query: "sum by (b) (max_over_time(metricWith1SampleEvery10Seconds[60s:5s]))",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 32,
TotalSamples: 48, // 1 sample per query * 12 queries (60/5) * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 12,
206000: 12,
211000: 12,
216000: 12,
},
},
{
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s]))",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 76,
TotalSamples: 288, // 2 * (3 sample per query * 12 queries (60/5) * 4 steps)
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 72,
206000: 72,
211000: 72,
216000: 72,
},
},
{
Query: "sum(max_over_time(metricWith3SampleEvery10Seconds[60s:5s])) + sum(max_over_time(metricWith1SampleEvery10Seconds[60s:5s]))",
Start: time.Unix(201, 0),
End: time.Unix(220, 0),
Interval: 5 * time.Second,
PeakSamples: 72,
TotalSamples: 192, // (1 sample per query * 12 queries (60/5) + 3 sample per query * 12 queries (60/5)) * 4 steps
TotalSamplesPerStep: stats.TotalSamplesPerStep{
201000: 48,
206000: 48,
211000: 48,
216000: 48,
},
},
}
engine := newTestEngine()
engine.enablePerStepStats = true
origMaxSamples := engine.maxSamplesPerQuery
for _, c := range cases {
t.Run(c.Query, func(t *testing.T) {
opts := NewPrometheusQueryOpts(true, 0)
engine.maxSamplesPerQuery = origMaxSamples
runQuery := func(expErr error) *stats.Statistics {
var err error
var qry Query
if c.Interval == 0 {
qry, err = engine.NewInstantQuery(context.Background(), storage, opts, c.Query, c.Start)
} else {
qry, err = engine.NewRangeQuery(context.Background(), storage, opts, c.Query, c.Start, c.End, c.Interval)
}
require.NoError(t, err)
res := qry.Exec(context.Background())
require.Equal(t, expErr, res.Err)
return qry.Stats()
}
stats := runQuery(nil)
require.Equal(t, c.TotalSamples, stats.Samples.TotalSamples, "Total samples mismatch")
require.Equal(t, &c.TotalSamplesPerStep, stats.Samples.TotalSamplesPerStepMap(), "Total samples per time mismatch")
require.Equal(t, c.PeakSamples, stats.Samples.PeakSamples, "Peak samples mismatch")
// Check that the peak is correct by setting the max to one less.
if c.SkipMaxCheck {
return
}
engine.maxSamplesPerQuery = stats.Samples.PeakSamples - 1
runQuery(ErrTooManySamples(env))
})
}
}
func TestMaxQuerySamples(t *testing.T) {
storage := LoadedStorage(t, `
load 10s
metric 1+1x100
bigmetric{a="1"} 1+1x100
bigmetric{a="2"} 1+1x100
`)
t.Cleanup(func() { storage.Close() })
// These test cases should be touching the limit exactly (hence no exceeding).
// Exceeding the limit will be tested by doing -1 to the MaxSamples.
cases := []struct {
Query string
MaxSamples int
Start time.Time
End time.Time
Interval time.Duration
}{
// Instant queries.
{
Query: "1",
MaxSamples: 1,
Start: time.Unix(1, 0),
},
{
Query: "metric",
MaxSamples: 1,
Start: time.Unix(1, 0),
},
{
Query: "metric[20s]",
MaxSamples: 2,
Start: time.Unix(10, 0),
},
{
Query: "rate(metric[20s])",
MaxSamples: 3,
Start: time.Unix(10, 0),
},
{
Query: "metric[20s:5s]",
MaxSamples: 3,
Start: time.Unix(10, 0),
},
{
Query: "metric[20s] @ 10",
MaxSamples: 2,
Start: time.Unix(0, 0),
},
// Range queries.
{
Query: "1",
MaxSamples: 3,
Start: time.Unix(0, 0),
End: time.Unix(2, 0),
Interval: time.Second,
},
{
Query: "1",
MaxSamples: 3,
Start: time.Unix(0, 0),
End: time.Unix(2, 0),
Interval: time.Second,
},
{
Query: "metric",
MaxSamples: 3,
Start: time.Unix(0, 0),
End: time.Unix(2, 0),
Interval: time.Second,
},
{
Query: "metric",
MaxSamples: 3,
Start: time.Unix(0, 0),
End: time.Unix(10, 0),
Interval: 5 * time.Second,
},
{
Query: "rate(bigmetric[1s])",
MaxSamples: 1,
Start: time.Unix(0, 0),
End: time.Unix(10, 0),
Interval: 5 * time.Second,
},
{
// Result is duplicated, so @ also produces 3 samples.
Query: "metric @ 10",
MaxSamples: 3,
Start: time.Unix(0, 0),
End: time.Unix(10, 0),
Interval: 5 * time.Second,
},
{
// The peak samples in memory is during the first evaluation:
// - Subquery takes 22 samples, 11 for each bigmetric,
// - Result is calculated per series where the series samples is buffered, hence 11 more here.
// - The result of two series is added before the last series buffer is discarded, so 2 more here.
// Hence at peak it is 22 (subquery) + 11 (buffer of a series) + 2 (result from 2 series).
// The subquery samples and the buffer is discarded before duplicating.
Query: `rate(bigmetric[10s:1s] @ 10)`,
MaxSamples: 35,
Start: time.Unix(0, 0),
End: time.Unix(10, 0),
Interval: 5 * time.Second,
},
{
// Here the reasoning is same as above. But LHS and RHS are done one after another.
// So while one of them takes 35 samples at peak, we need to hold the 2 sample
// result of the other till then.
Query: `rate(bigmetric[10s:1s] @ 10) + rate(bigmetric[10s:1s] @ 30)`,
MaxSamples: 37,
Start: time.Unix(0, 0),
End: time.Unix(10, 0),
Interval: 5 * time.Second,
},
{
// Sample as above but with only 1 part as step invariant.
// Here the peak is caused by the non-step invariant part as it touches more time range.
// Hence at peak it is 2*21 (subquery from 0s to 20s)
// + 11 (buffer of a series per evaluation)
// + 6 (result from 2 series at 3 eval times).
Query: `rate(bigmetric[10s:1s]) + rate(bigmetric[10s:1s] @ 30)`,
MaxSamples: 59,
Start: time.Unix(10, 0),
End: time.Unix(20, 0),
Interval: 5 * time.Second,
},
{
// Nested subquery.
// We saw that innermost rate takes 35 samples which is still the peak
// since the other two subqueries just duplicate the result.
Query: `rate(rate(bigmetric[10s:1s] @ 10)[100s:25s] @ 1000)[100s:20s] @ 2000`,
MaxSamples: 35,
Start: time.Unix(10, 0),
},
{
// Nested subquery.
// Now the outmost subquery produces more samples than inner most rate.
Query: `rate(rate(bigmetric[10s:1s] @ 10)[100s:25s] @ 1000)[17s:1s] @ 2000`,
MaxSamples: 36,
Start: time.Unix(10, 0),
},
}
for _, c := range cases {
t.Run(c.Query, func(t *testing.T) {
engine := newTestEngine()
testFunc := func(expError error) {
var err error
var qry Query
if c.Interval == 0 {
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, c.Query, c.Start)
} else {
qry, err = engine.NewRangeQuery(context.Background(), storage, nil, c.Query, c.Start, c.End, c.Interval)
}
require.NoError(t, err)
res := qry.Exec(context.Background())
stats := qry.Stats()
require.Equal(t, expError, res.Err)
require.NotNil(t, stats)
if expError == nil {
require.Equal(t, c.MaxSamples, stats.Samples.PeakSamples, "peak samples mismatch for query %q", c.Query)
}
}
// Within limit.
engine.maxSamplesPerQuery = c.MaxSamples
testFunc(nil)
// Exceeding limit.
engine.maxSamplesPerQuery = c.MaxSamples - 1
testFunc(ErrTooManySamples(env))
})
}
}
func TestAtModifier(t *testing.T) {
engine := newTestEngine()
storage := LoadedStorage(t, `
load 10s
metric{job="1"} 0+1x1000
metric{job="2"} 0+2x1000
metric_topk{instance="1"} 0+1x1000
metric_topk{instance="2"} 0+2x1000
metric_topk{instance="3"} 1000-1x1000
load 1ms
metric_ms 0+1x10000
`)
t.Cleanup(func() { storage.Close() })
lbls1 := labels.FromStrings("__name__", "metric", "job", "1")
lbls2 := labels.FromStrings("__name__", "metric", "job", "2")
lblstopk2 := labels.FromStrings("__name__", "metric_topk", "instance", "2")
lblstopk3 := labels.FromStrings("__name__", "metric_topk", "instance", "3")
lblsms := labels.FromStrings("__name__", "metric_ms")
lblsneg := labels.FromStrings("__name__", "metric_neg")
// Add some samples with negative timestamp.
db := storage.DB
app := db.Appender(context.Background())
ref, err := app.Append(0, lblsneg, -1000000, 1000)
require.NoError(t, err)
for ts := int64(-1000000 + 1000); ts <= 0; ts += 1000 {
_, err := app.Append(ref, labels.EmptyLabels(), ts, -float64(ts/1000)+1)
require.NoError(t, err)
}
// To test the fix for https://github.com/prometheus/prometheus/issues/8433.
_, err = app.Append(0, labels.FromStrings("__name__", "metric_timestamp"), 3600*1000, 1000)
require.NoError(t, err)
require.NoError(t, app.Commit())
cases := []struct {
query string
start, end, interval int64 // Time in seconds.
result parser.Value
}{
{ // Time of the result is the evaluation time.
query: `metric_neg @ 0`,
start: 100,
result: Vector{
Sample{F: 1, T: 100000, Metric: lblsneg},
},
}, {
query: `metric_neg @ -200`,
start: 100,
result: Vector{
Sample{F: 201, T: 100000, Metric: lblsneg},
},
}, {
query: `metric{job="2"} @ 50`,
start: -2, end: 2, interval: 1,
result: Matrix{
Series{
Floats: []FPoint{{F: 10, T: -2000}, {F: 10, T: -1000}, {F: 10, T: 0}, {F: 10, T: 1000}, {F: 10, T: 2000}},
Metric: lbls2,
},
},
}, { // Timestamps for matrix selector does not depend on the evaluation time.
query: "metric[20s] @ 300",
start: 10,
result: Matrix{
Series{
Floats: []FPoint{{F: 28, T: 280000}, {F: 29, T: 290000}, {F: 30, T: 300000}},
Metric: lbls1,
},
Series{
Floats: []FPoint{{F: 56, T: 280000}, {F: 58, T: 290000}, {F: 60, T: 300000}},
Metric: lbls2,
},
},
}, {
query: `metric_neg[2s] @ 0`,
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 3, T: -2000}, {F: 2, T: -1000}, {F: 1, T: 0}},
Metric: lblsneg,
},
},
}, {
query: `metric_neg[3s] @ -500`,
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 504, T: -503000}, {F: 503, T: -502000}, {F: 502, T: -501000}, {F: 501, T: -500000}},
Metric: lblsneg,
},
},
}, {
query: `metric_ms[3ms] @ 2.345`,
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 2342, T: 2342}, {F: 2343, T: 2343}, {F: 2344, T: 2344}, {F: 2345, T: 2345}},
Metric: lblsms,
},
},
}, {
query: "metric[100s:25s] @ 300",
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 20, T: 200000}, {F: 22, T: 225000}, {F: 25, T: 250000}, {F: 27, T: 275000}, {F: 30, T: 300000}},
Metric: lbls1,
},
Series{
Floats: []FPoint{{F: 40, T: 200000}, {F: 44, T: 225000}, {F: 50, T: 250000}, {F: 54, T: 275000}, {F: 60, T: 300000}},
Metric: lbls2,
},
},
}, {
query: "metric_neg[50s:25s] @ 0",
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 51, T: -50000}, {F: 26, T: -25000}, {F: 1, T: 0}},
Metric: lblsneg,
},
},
}, {
query: "metric_neg[50s:25s] @ -100",
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 151, T: -150000}, {F: 126, T: -125000}, {F: 101, T: -100000}},
Metric: lblsneg,
},
},
}, {
query: `metric_ms[100ms:25ms] @ 2.345`,
start: 100,
result: Matrix{
Series{
Floats: []FPoint{{F: 2250, T: 2250}, {F: 2275, T: 2275}, {F: 2300, T: 2300}, {F: 2325, T: 2325}},
Metric: lblsms,
},
},
}, {
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ 100))`,
start: 50, end: 80, interval: 10,
result: Matrix{
Series{
Floats: []FPoint{{F: 995, T: 50000}, {F: 994, T: 60000}, {F: 993, T: 70000}, {F: 992, T: 80000}},
Metric: lblstopk3,
},
},
}, {
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ 5000))`,
start: 50, end: 80, interval: 10,
result: Matrix{
Series{
Floats: []FPoint{{F: 10, T: 50000}, {F: 12, T: 60000}, {F: 14, T: 70000}, {F: 16, T: 80000}},
Metric: lblstopk2,
},
},
}, {
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ end()))`,
start: 70, end: 100, interval: 10,
result: Matrix{
Series{
Floats: []FPoint{{F: 993, T: 70000}, {F: 992, T: 80000}, {F: 991, T: 90000}, {F: 990, T: 100000}},
Metric: lblstopk3,
},
},
}, {
query: `metric_topk and topk(1, sum_over_time(metric_topk[50s] @ start()))`,
start: 100, end: 130, interval: 10,
result: Matrix{
Series{
Floats: []FPoint{{F: 990, T: 100000}, {F: 989, T: 110000}, {F: 988, T: 120000}, {F: 987, T: 130000}},
Metric: lblstopk3,
},
},
}, {
// Tests for https://github.com/prometheus/prometheus/issues/8433.
// The trick here is that the query range should be > lookback delta.
query: `timestamp(metric_timestamp @ 3600)`,
start: 0, end: 7 * 60, interval: 60,
result: Matrix{
Series{
Floats: []FPoint{
{F: 3600, T: 0},
{F: 3600, T: 60 * 1000},
{F: 3600, T: 2 * 60 * 1000},
{F: 3600, T: 3 * 60 * 1000},
{F: 3600, T: 4 * 60 * 1000},
{F: 3600, T: 5 * 60 * 1000},
{F: 3600, T: 6 * 60 * 1000},
{F: 3600, T: 7 * 60 * 1000},
},
Metric: labels.EmptyLabels(),
},
},
},
}
for _, c := range cases {
t.Run(c.query, func(t *testing.T) {
if c.interval == 0 {
c.interval = 1
}
start, end, interval := time.Unix(c.start, 0), time.Unix(c.end, 0), time.Duration(c.interval)*time.Second
var err error
var qry Query
if c.end == 0 {
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, c.query, start)
} else {
qry, err = engine.NewRangeQuery(context.Background(), storage, nil, c.query, start, end, interval)
}
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
if expMat, ok := c.result.(Matrix); ok {
sort.Sort(expMat)
sort.Sort(res.Value.(Matrix))
}
testutil.RequireEqual(t, c.result, res.Value, "query %q failed", c.query)
})
}
}
func TestRecoverEvaluatorRuntime(t *testing.T) {
var output []interface{}
logger := log.Logger(log.LoggerFunc(func(keyvals ...interface{}) error {
output = append(output, keyvals...)
return nil
}))
ev := &evaluator{logger: logger}
expr, _ := parser.ParseExpr("sum(up)")
var err error
defer func() {
require.EqualError(t, err, "unexpected error: runtime error: index out of range [123] with length 0")
require.Contains(t, output, "sum(up)")
}()
defer ev.recover(expr, nil, &err)
// Cause a runtime panic.
var a []int
a[123] = 1
}
func TestRecoverEvaluatorError(t *testing.T) {
ev := &evaluator{logger: log.NewNopLogger()}
var err error
e := errors.New("custom error")
defer func() {
require.EqualError(t, err, e.Error())
}()
defer ev.recover(nil, nil, &err)
panic(e)
}
func TestRecoverEvaluatorErrorWithWarnings(t *testing.T) {
ev := &evaluator{logger: log.NewNopLogger()}
var err error
var ws annotations.Annotations
warnings := annotations.New().Add(errors.New("custom warning"))
e := errWithWarnings{
err: errors.New("custom error"),
warnings: warnings,
}
defer func() {
require.EqualError(t, err, e.Error())
require.Equal(t, warnings, ws, "wrong warning message")
}()
defer ev.recover(nil, &ws, &err)
panic(e)
}
func TestSubquerySelector(t *testing.T) {
type caseType struct {
Query string
Result Result
Start time.Time
}
for _, tst := range []struct {
loadString string
cases []caseType
}{
{
loadString: `load 10s
metric 1 2`,
cases: []caseType{
{
Query: "metric[20s:10s]",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 2, T: 10000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(10, 0),
},
{
Query: "metric[20s:5s]",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(10, 0),
},
{
Query: "metric[20s:5s] offset 2s",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(12, 0),
},
{
Query: "metric[20s:5s] offset 6s",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 1, T: 5000}, {F: 2, T: 10000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(20, 0),
},
{
Query: "metric[20s:5s] offset 4s",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}, {F: 2, T: 30000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(35, 0),
},
{
Query: "metric[20s:5s] offset 5s",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 2, T: 10000}, {F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}, {F: 2, T: 30000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(35, 0),
},
{
Query: "metric[20s:5s] offset 6s",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 2, T: 10000}, {F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(35, 0),
},
{
Query: "metric[20s:5s] offset 7s",
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 2, T: 10000}, {F: 2, T: 15000}, {F: 2, T: 20000}, {F: 2, T: 25000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
nil,
},
Start: time.Unix(35, 0),
},
},
},
{
loadString: `load 10s
http_requests{job="api-server", instance="0", group="production"} 0+10x1000 100+30x1000
http_requests{job="api-server", instance="1", group="production"} 0+20x1000 200+30x1000
http_requests{job="api-server", instance="0", group="canary"} 0+30x1000 300+80x1000
http_requests{job="api-server", instance="1", group="canary"} 0+40x2000`,
cases: []caseType{
{ // Normal selector.
Query: `http_requests{group=~"pro.*",instance="0"}[30s:10s]`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 9990, T: 9990000}, {F: 10000, T: 10000000}, {F: 100, T: 10010000}, {F: 130, T: 10020000}},
Metric: labels.FromStrings("__name__", "http_requests", "job", "api-server", "instance", "0", "group", "production"),
},
},
nil,
},
Start: time.Unix(10020, 0),
},
{ // Default step.
Query: `http_requests{group=~"pro.*",instance="0"}[5m:]`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 9840, T: 9840000}, {F: 9900, T: 9900000}, {F: 9960, T: 9960000}, {F: 130, T: 10020000}, {F: 310, T: 10080000}},
Metric: labels.FromStrings("__name__", "http_requests", "job", "api-server", "instance", "0", "group", "production"),
},
},
nil,
},
Start: time.Unix(10100, 0),
},
{ // Checking if high offset (>LookbackDelta) is being taken care of.
Query: `http_requests{group=~"pro.*",instance="0"}[5m:] offset 20m`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 8640, T: 8640000}, {F: 8700, T: 8700000}, {F: 8760, T: 8760000}, {F: 8820, T: 8820000}, {F: 8880, T: 8880000}},
Metric: labels.FromStrings("__name__", "http_requests", "job", "api-server", "instance", "0", "group", "production"),
},
},
nil,
},
Start: time.Unix(10100, 0),
},
{
Query: `rate(http_requests[1m])[15s:5s]`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 3, T: 7985000}, {F: 3, T: 7990000}, {F: 3, T: 7995000}, {F: 3, T: 8000000}},
Metric: labels.FromStrings("job", "api-server", "instance", "0", "group", "canary"),
},
Series{
Floats: []FPoint{{F: 4, T: 7985000}, {F: 4, T: 7990000}, {F: 4, T: 7995000}, {F: 4, T: 8000000}},
Metric: labels.FromStrings("job", "api-server", "instance", "1", "group", "canary"),
},
Series{
Floats: []FPoint{{F: 1, T: 7985000}, {F: 1, T: 7990000}, {F: 1, T: 7995000}, {F: 1, T: 8000000}},
Metric: labels.FromStrings("job", "api-server", "instance", "0", "group", "production"),
},
Series{
Floats: []FPoint{{F: 2, T: 7985000}, {F: 2, T: 7990000}, {F: 2, T: 7995000}, {F: 2, T: 8000000}},
Metric: labels.FromStrings("job", "api-server", "instance", "1", "group", "production"),
},
},
nil,
},
Start: time.Unix(8000, 0),
},
{
Query: `sum(http_requests{group=~"pro.*"})[30s:10s]`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 270, T: 90000}, {F: 300, T: 100000}, {F: 330, T: 110000}, {F: 360, T: 120000}},
Metric: labels.EmptyLabels(),
},
},
nil,
},
Start: time.Unix(120, 0),
},
{
Query: `sum(http_requests)[40s:10s]`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 800, T: 80000}, {F: 900, T: 90000}, {F: 1000, T: 100000}, {F: 1100, T: 110000}, {F: 1200, T: 120000}},
Metric: labels.EmptyLabels(),
},
},
nil,
},
Start: time.Unix(120, 0),
},
{
Query: `(sum(http_requests{group=~"p.*"})+sum(http_requests{group=~"c.*"}))[20s:5s]`,
Result: Result{
nil,
Matrix{
Series{
Floats: []FPoint{{F: 1000, T: 100000}, {F: 1000, T: 105000}, {F: 1100, T: 110000}, {F: 1100, T: 115000}, {F: 1200, T: 120000}},
Metric: labels.EmptyLabels(),
},
},
nil,
},
Start: time.Unix(120, 0),
},
},
},
} {
t.Run("", func(t *testing.T) {
engine := newTestEngine()
storage := LoadedStorage(t, tst.loadString)
t.Cleanup(func() { storage.Close() })
for _, c := range tst.cases {
t.Run(c.Query, func(t *testing.T) {
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, c.Query, c.Start)
require.NoError(t, err)
res := qry.Exec(context.Background())
require.Equal(t, c.Result.Err, res.Err)
mat := res.Value.(Matrix)
sort.Sort(mat)
testutil.RequireEqual(t, c.Result.Value, mat)
})
}
})
}
}
func TestTimestampFunction_StepsMoreOftenThanSamples(t *testing.T) {
engine := newTestEngine()
storage := LoadedStorage(t, `
load 1m
metric 0+1x1000
`)
t.Cleanup(func() { storage.Close() })
query := "timestamp(metric)"
start := time.Unix(0, 0)
end := time.Unix(61, 0)
interval := time.Second
// We expect the value to be 0 for t=0s to t=59s (inclusive), then 60 for t=60s and t=61s.
expectedPoints := []FPoint{}
for t := 0; t <= 59; t++ {
expectedPoints = append(expectedPoints, FPoint{F: 0, T: int64(t * 1000)})
}
expectedPoints = append(
expectedPoints,
FPoint{F: 60, T: 60_000},
FPoint{F: 60, T: 61_000},
)
expectedResult := Matrix{
Series{
Floats: expectedPoints,
Metric: labels.EmptyLabels(),
},
}
qry, err := engine.NewRangeQuery(context.Background(), storage, nil, query, start, end, interval)
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
testutil.RequireEqual(t, expectedResult, res.Value)
}
type FakeQueryLogger struct {
closed bool
logs []interface{}
}
func NewFakeQueryLogger() *FakeQueryLogger {
return &FakeQueryLogger{
closed: false,
logs: make([]interface{}, 0),
}
}
func (f *FakeQueryLogger) Close() error {
f.closed = true
return nil
}
func (f *FakeQueryLogger) Log(l ...interface{}) error {
f.logs = append(f.logs, l...)
return nil
}
func TestQueryLogger_basic(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
}
engine := NewEngine(opts)
queryExec := func() {
ctx, cancelCtx := context.WithCancel(context.Background())
defer cancelCtx()
query := engine.newTestQuery(func(ctx context.Context) error {
return contextDone(ctx, "test statement execution")
})
res := query.Exec(ctx)
require.NoError(t, res.Err)
}
// Query works without query log initialized.
queryExec()
f1 := NewFakeQueryLogger()
engine.SetQueryLogger(f1)
queryExec()
for i, field := range []interface{}{"params", map[string]interface{}{"query": "test statement"}} {
require.Equal(t, field, f1.logs[i])
}
l := len(f1.logs)
queryExec()
require.Len(t, f1.logs, 2*l)
// Test that we close the query logger when unsetting it.
require.False(t, f1.closed, "expected f1 to be open, got closed")
engine.SetQueryLogger(nil)
require.True(t, f1.closed, "expected f1 to be closed, got open")
queryExec()
// Test that we close the query logger when swapping.
f2 := NewFakeQueryLogger()
f3 := NewFakeQueryLogger()
engine.SetQueryLogger(f2)
require.False(t, f2.closed, "expected f2 to be open, got closed")
queryExec()
engine.SetQueryLogger(f3)
require.True(t, f2.closed, "expected f2 to be closed, got open")
require.False(t, f3.closed, "expected f3 to be open, got closed")
queryExec()
}
func TestQueryLogger_fields(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
}
engine := NewEngine(opts)
f1 := NewFakeQueryLogger()
engine.SetQueryLogger(f1)
ctx, cancelCtx := context.WithCancel(context.Background())
ctx = NewOriginContext(ctx, map[string]interface{}{"foo": "bar"})
defer cancelCtx()
query := engine.newTestQuery(func(ctx context.Context) error {
return contextDone(ctx, "test statement execution")
})
res := query.Exec(ctx)
require.NoError(t, res.Err)
expected := []string{"foo", "bar"}
for i, field := range expected {
v := f1.logs[len(f1.logs)-len(expected)+i].(string)
require.Equal(t, field, v)
}
}
func TestQueryLogger_error(t *testing.T) {
opts := EngineOpts{
Logger: nil,
Reg: nil,
MaxSamples: 10,
Timeout: 10 * time.Second,
}
engine := NewEngine(opts)
f1 := NewFakeQueryLogger()
engine.SetQueryLogger(f1)
ctx, cancelCtx := context.WithCancel(context.Background())
ctx = NewOriginContext(ctx, map[string]interface{}{"foo": "bar"})
defer cancelCtx()
testErr := errors.New("failure")
query := engine.newTestQuery(func(ctx context.Context) error {
return testErr
})
res := query.Exec(ctx)
require.Error(t, res.Err, "query should have failed")
for i, field := range []interface{}{"params", map[string]interface{}{"query": "test statement"}, "error", testErr} {
require.Equal(t, f1.logs[i], field)
}
}
func TestPreprocessAndWrapWithStepInvariantExpr(t *testing.T) {
startTime := time.Unix(1000, 0)
endTime := time.Unix(9999, 0)
testCases := []struct {
input string // The input to be parsed.
expected parser.Expr // The expected expression AST.
outputTest bool
}{
{
input: "123.4567",
expected: &parser.StepInvariantExpr{
Expr: &parser.NumberLiteral{
Val: 123.4567,
PosRange: posrange.PositionRange{Start: 0, End: 8},
},
},
},
{
input: `"foo"`,
expected: &parser.StepInvariantExpr{
Expr: &parser.StringLiteral{
Val: "foo",
PosRange: posrange.PositionRange{Start: 0, End: 5},
},
},
},
{
input: "foo * bar",
expected: &parser.BinaryExpr{
Op: parser.MUL,
LHS: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 3,
},
},
RHS: &parser.VectorSelector{
Name: "bar",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
},
PosRange: posrange.PositionRange{
Start: 6,
End: 9,
},
},
VectorMatching: &parser.VectorMatching{Card: parser.CardOneToOne},
},
},
{
input: "foo * bar @ 10",
expected: &parser.BinaryExpr{
Op: parser.MUL,
LHS: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 3,
},
},
RHS: &parser.StepInvariantExpr{
Expr: &parser.VectorSelector{
Name: "bar",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
},
PosRange: posrange.PositionRange{
Start: 6,
End: 14,
},
Timestamp: makeInt64Pointer(10000),
},
},
VectorMatching: &parser.VectorMatching{Card: parser.CardOneToOne},
},
},
{
input: "foo @ 20 * bar @ 10",
expected: &parser.StepInvariantExpr{
Expr: &parser.BinaryExpr{
Op: parser.MUL,
LHS: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 8,
},
Timestamp: makeInt64Pointer(20000),
},
RHS: &parser.VectorSelector{
Name: "bar",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
},
PosRange: posrange.PositionRange{
Start: 11,
End: 19,
},
Timestamp: makeInt64Pointer(10000),
},
VectorMatching: &parser.VectorMatching{Card: parser.CardOneToOne},
},
},
},
{
input: "test[5s]",
expected: &parser.MatrixSelector{
VectorSelector: &parser.VectorSelector{
Name: "test",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 4,
},
},
Range: 5 * time.Second,
EndPos: 8,
},
},
{
input: `test{a="b"}[5y] @ 1603774699`,
expected: &parser.StepInvariantExpr{
Expr: &parser.MatrixSelector{
VectorSelector: &parser.VectorSelector{
Name: "test",
Timestamp: makeInt64Pointer(1603774699000),
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "a", "b"),
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 11,
},
},
Range: 5 * 365 * 24 * time.Hour,
EndPos: 28,
},
},
},
{
input: "sum by (foo)(some_metric)",
expected: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 13,
End: 24,
},
},
Grouping: []string{"foo"},
PosRange: posrange.PositionRange{
Start: 0,
End: 25,
},
},
},
{
input: "sum by (foo)(some_metric @ 10)",
expected: &parser.StepInvariantExpr{
Expr: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 13,
End: 29,
},
Timestamp: makeInt64Pointer(10000),
},
Grouping: []string{"foo"},
PosRange: posrange.PositionRange{
Start: 0,
End: 30,
},
},
},
},
{
input: "sum(some_metric1 @ 10) + sum(some_metric2 @ 20)",
expected: &parser.StepInvariantExpr{
Expr: &parser.BinaryExpr{
Op: parser.ADD,
VectorMatching: &parser.VectorMatching{},
LHS: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "some_metric1",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric1"),
},
PosRange: posrange.PositionRange{
Start: 4,
End: 21,
},
Timestamp: makeInt64Pointer(10000),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 22,
},
},
RHS: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "some_metric2",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric2"),
},
PosRange: posrange.PositionRange{
Start: 29,
End: 46,
},
Timestamp: makeInt64Pointer(20000),
},
PosRange: posrange.PositionRange{
Start: 25,
End: 47,
},
},
},
},
},
{
input: "some_metric and topk(5, rate(some_metric[1m] @ 20))",
expected: &parser.BinaryExpr{
Op: parser.LAND,
VectorMatching: &parser.VectorMatching{
Card: parser.CardManyToMany,
},
LHS: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 11,
},
},
RHS: &parser.StepInvariantExpr{
Expr: &parser.AggregateExpr{
Op: parser.TOPK,
Expr: &parser.Call{
Func: parser.MustGetFunction("rate"),
Args: parser.Expressions{
&parser.MatrixSelector{
VectorSelector: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 29,
End: 40,
},
Timestamp: makeInt64Pointer(20000),
},
Range: 1 * time.Minute,
EndPos: 49,
},
},
PosRange: posrange.PositionRange{
Start: 24,
End: 50,
},
},
Param: &parser.NumberLiteral{
Val: 5,
PosRange: posrange.PositionRange{
Start: 21,
End: 22,
},
},
PosRange: posrange.PositionRange{
Start: 16,
End: 51,
},
},
},
},
},
{
input: "time()",
expected: &parser.Call{
Func: parser.MustGetFunction("time"),
Args: parser.Expressions{},
PosRange: posrange.PositionRange{
Start: 0,
End: 6,
},
},
},
{
input: `foo{bar="baz"}[10m:6s]`,
expected: &parser.SubqueryExpr{
Expr: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 14,
},
},
Range: 10 * time.Minute,
Step: 6 * time.Second,
EndPos: 22,
},
},
{
input: `foo{bar="baz"}[10m:6s] @ 10`,
expected: &parser.StepInvariantExpr{
Expr: &parser.SubqueryExpr{
Expr: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 14,
},
},
Range: 10 * time.Minute,
Step: 6 * time.Second,
Timestamp: makeInt64Pointer(10000),
EndPos: 27,
},
},
},
{ // Even though the subquery is step invariant, the inside is also wrapped separately.
input: `sum(foo{bar="baz"} @ 20)[10m:6s] @ 10`,
expected: &parser.StepInvariantExpr{
Expr: &parser.SubqueryExpr{
Expr: &parser.StepInvariantExpr{
Expr: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 4,
End: 23,
},
Timestamp: makeInt64Pointer(20000),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 24,
},
},
},
Range: 10 * time.Minute,
Step: 6 * time.Second,
Timestamp: makeInt64Pointer(10000),
EndPos: 37,
},
},
},
{
input: `min_over_time(rate(foo{bar="baz"}[2s])[5m:] @ 1603775091)[4m:3s]`,
expected: &parser.SubqueryExpr{
Expr: &parser.StepInvariantExpr{
Expr: &parser.Call{
Func: parser.MustGetFunction("min_over_time"),
Args: parser.Expressions{
&parser.SubqueryExpr{
Expr: &parser.Call{
Func: parser.MustGetFunction("rate"),
Args: parser.Expressions{
&parser.MatrixSelector{
VectorSelector: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "bar", "baz"),
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 19,
End: 33,
},
},
Range: 2 * time.Second,
EndPos: 37,
},
},
PosRange: posrange.PositionRange{
Start: 14,
End: 38,
},
},
Range: 5 * time.Minute,
Timestamp: makeInt64Pointer(1603775091000),
EndPos: 56,
},
},
PosRange: posrange.PositionRange{
Start: 0,
End: 57,
},
},
},
Range: 4 * time.Minute,
Step: 3 * time.Second,
EndPos: 64,
},
},
{
input: `some_metric @ 123 offset 1m [10m:5s]`,
expected: &parser.SubqueryExpr{
Expr: &parser.StepInvariantExpr{
Expr: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 27,
},
Timestamp: makeInt64Pointer(123000),
OriginalOffset: 1 * time.Minute,
},
},
Range: 10 * time.Minute,
Step: 5 * time.Second,
EndPos: 36,
},
},
{
input: `some_metric[10m:5s] offset 1m @ 123`,
expected: &parser.StepInvariantExpr{
Expr: &parser.SubqueryExpr{
Expr: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 11,
},
},
Timestamp: makeInt64Pointer(123000),
OriginalOffset: 1 * time.Minute,
Range: 10 * time.Minute,
Step: 5 * time.Second,
EndPos: 35,
},
},
},
{
input: `(foo + bar{nm="val"} @ 1234)[5m:] @ 1603775019`,
expected: &parser.StepInvariantExpr{
Expr: &parser.SubqueryExpr{
Expr: &parser.ParenExpr{
Expr: &parser.BinaryExpr{
Op: parser.ADD,
VectorMatching: &parser.VectorMatching{
Card: parser.CardOneToOne,
},
LHS: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 1,
End: 4,
},
},
RHS: &parser.StepInvariantExpr{
Expr: &parser.VectorSelector{
Name: "bar",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "nm", "val"),
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "bar"),
},
Timestamp: makeInt64Pointer(1234000),
PosRange: posrange.PositionRange{
Start: 7,
End: 27,
},
},
},
},
PosRange: posrange.PositionRange{
Start: 0,
End: 28,
},
},
Range: 5 * time.Minute,
Timestamp: makeInt64Pointer(1603775019000),
EndPos: 46,
},
},
},
{
input: "abs(abs(metric @ 10))",
expected: &parser.StepInvariantExpr{
Expr: &parser.Call{
Func: &parser.Function{
Name: "abs",
ArgTypes: []parser.ValueType{parser.ValueTypeVector},
ReturnType: parser.ValueTypeVector,
},
Args: parser.Expressions{&parser.Call{
Func: &parser.Function{
Name: "abs",
ArgTypes: []parser.ValueType{parser.ValueTypeVector},
ReturnType: parser.ValueTypeVector,
},
Args: parser.Expressions{&parser.VectorSelector{
Name: "metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "metric"),
},
PosRange: posrange.PositionRange{
Start: 8,
End: 19,
},
Timestamp: makeInt64Pointer(10000),
}},
PosRange: posrange.PositionRange{
Start: 4,
End: 20,
},
}},
PosRange: posrange.PositionRange{
Start: 0,
End: 21,
},
},
},
},
{
input: "sum(sum(some_metric1 @ 10) + sum(some_metric2 @ 20))",
expected: &parser.StepInvariantExpr{
Expr: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.BinaryExpr{
Op: parser.ADD,
VectorMatching: &parser.VectorMatching{},
LHS: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "some_metric1",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric1"),
},
PosRange: posrange.PositionRange{
Start: 8,
End: 25,
},
Timestamp: makeInt64Pointer(10000),
},
PosRange: posrange.PositionRange{
Start: 4,
End: 26,
},
},
RHS: &parser.AggregateExpr{
Op: parser.SUM,
Expr: &parser.VectorSelector{
Name: "some_metric2",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric2"),
},
PosRange: posrange.PositionRange{
Start: 33,
End: 50,
},
Timestamp: makeInt64Pointer(20000),
},
PosRange: posrange.PositionRange{
Start: 29,
End: 52,
},
},
},
PosRange: posrange.PositionRange{
Start: 0,
End: 52,
},
},
},
},
{
input: `foo @ start()`,
expected: &parser.StepInvariantExpr{
Expr: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 13,
},
Timestamp: makeInt64Pointer(timestamp.FromTime(startTime)),
StartOrEnd: parser.START,
},
},
},
{
input: `foo @ end()`,
expected: &parser.StepInvariantExpr{
Expr: &parser.VectorSelector{
Name: "foo",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "foo"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 11,
},
Timestamp: makeInt64Pointer(timestamp.FromTime(endTime)),
StartOrEnd: parser.END,
},
},
},
{
input: `test[5y] @ start()`,
expected: &parser.StepInvariantExpr{
Expr: &parser.MatrixSelector{
VectorSelector: &parser.VectorSelector{
Name: "test",
Timestamp: makeInt64Pointer(timestamp.FromTime(startTime)),
StartOrEnd: parser.START,
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 4,
},
},
Range: 5 * 365 * 24 * time.Hour,
EndPos: 18,
},
},
},
{
input: `test[5y] @ end()`,
expected: &parser.StepInvariantExpr{
Expr: &parser.MatrixSelector{
VectorSelector: &parser.VectorSelector{
Name: "test",
Timestamp: makeInt64Pointer(timestamp.FromTime(endTime)),
StartOrEnd: parser.END,
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "test"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 4,
},
},
Range: 5 * 365 * 24 * time.Hour,
EndPos: 16,
},
},
},
{
input: `some_metric[10m:5s] @ start()`,
expected: &parser.StepInvariantExpr{
Expr: &parser.SubqueryExpr{
Expr: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 11,
},
},
Timestamp: makeInt64Pointer(timestamp.FromTime(startTime)),
StartOrEnd: parser.START,
Range: 10 * time.Minute,
Step: 5 * time.Second,
EndPos: 29,
},
},
},
{
input: `some_metric[10m:5s] @ end()`,
expected: &parser.StepInvariantExpr{
Expr: &parser.SubqueryExpr{
Expr: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 0,
End: 11,
},
},
Timestamp: makeInt64Pointer(timestamp.FromTime(endTime)),
StartOrEnd: parser.END,
Range: 10 * time.Minute,
Step: 5 * time.Second,
EndPos: 27,
},
},
},
{
input: `floor(some_metric / (3 * 1024))`,
outputTest: true,
expected: &parser.Call{
Func: &parser.Function{
Name: "floor",
ArgTypes: []parser.ValueType{parser.ValueTypeVector},
ReturnType: parser.ValueTypeVector,
},
Args: parser.Expressions{
&parser.BinaryExpr{
Op: parser.DIV,
LHS: &parser.VectorSelector{
Name: "some_metric",
LabelMatchers: []*labels.Matcher{
parser.MustLabelMatcher(labels.MatchEqual, "__name__", "some_metric"),
},
PosRange: posrange.PositionRange{
Start: 6,
End: 17,
},
},
RHS: &parser.StepInvariantExpr{
Expr: &parser.ParenExpr{
Expr: &parser.BinaryExpr{
Op: parser.MUL,
LHS: &parser.NumberLiteral{
Val: 3,
PosRange: posrange.PositionRange{
Start: 21,
End: 22,
},
},
RHS: &parser.NumberLiteral{
Val: 1024,
PosRange: posrange.PositionRange{
Start: 25,
End: 29,
},
},
},
PosRange: posrange.PositionRange{
Start: 20,
End: 30,
},
},
},
},
},
PosRange: posrange.PositionRange{
Start: 0,
End: 31,
},
},
},
}
for _, test := range testCases {
t.Run(test.input, func(t *testing.T) {
expr, err := parser.ParseExpr(test.input)
require.NoError(t, err)
expr = PreprocessExpr(expr, startTime, endTime)
if test.outputTest {
require.Equal(t, test.input, expr.String(), "error on input '%s'", test.input)
}
require.Equal(t, test.expected, expr, "error on input '%s'", test.input)
})
}
}
func TestEngineOptsValidation(t *testing.T) {
cases := []struct {
opts EngineOpts
query string
fail bool
expError error
}{
{
opts: EngineOpts{EnableAtModifier: false},
query: "metric @ 100", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "rate(metric[1m] @ 100)", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "rate(metric[1h:1m] @ 100)", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "metric @ start()", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "rate(metric[1m] @ start())", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "rate(metric[1h:1m] @ start())", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "metric @ end()", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "rate(metric[1m] @ end())", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: false},
query: "rate(metric[1h:1m] @ end())", fail: true, expError: ErrValidationAtModifierDisabled,
}, {
opts: EngineOpts{EnableAtModifier: true},
query: "metric @ 100",
}, {
opts: EngineOpts{EnableAtModifier: true},
query: "rate(metric[1m] @ start())",
}, {
opts: EngineOpts{EnableAtModifier: true},
query: "rate(metric[1h:1m] @ end())",
}, {
opts: EngineOpts{EnableNegativeOffset: false},
query: "metric offset -1s", fail: true, expError: ErrValidationNegativeOffsetDisabled,
}, {
opts: EngineOpts{EnableNegativeOffset: true},
query: "metric offset -1s",
}, {
opts: EngineOpts{EnableAtModifier: true, EnableNegativeOffset: true},
query: "metric @ 100 offset -2m",
}, {
opts: EngineOpts{EnableAtModifier: true, EnableNegativeOffset: true},
query: "metric offset -2m @ 100",
},
}
for _, c := range cases {
eng := NewEngine(c.opts)
_, err1 := eng.NewInstantQuery(context.Background(), nil, nil, c.query, time.Unix(10, 0))
_, err2 := eng.NewRangeQuery(context.Background(), nil, nil, c.query, time.Unix(0, 0), time.Unix(10, 0), time.Second)
if c.fail {
require.Equal(t, c.expError, err1)
require.Equal(t, c.expError, err2)
} else {
require.NoError(t, err1)
require.NoError(t, err2)
}
}
}
func TestRangeQuery(t *testing.T) {
cases := []struct {
Name string
Load string
Query string
Result parser.Value
Start time.Time
End time.Time
Interval time.Duration
}{
{
Name: "sum_over_time with all values",
Load: `load 30s
bar 0 1 10 100 1000`,
Query: "sum_over_time(bar[30s])",
Result: Matrix{
Series{
Floats: []FPoint{{F: 0, T: 0}, {F: 11, T: 60000}, {F: 1100, T: 120000}},
Metric: labels.EmptyLabels(),
},
},
Start: time.Unix(0, 0),
End: time.Unix(120, 0),
Interval: 60 * time.Second,
},
{
Name: "sum_over_time with trailing values",
Load: `load 30s
bar 0 1 10 100 1000 0 0 0 0`,
Query: "sum_over_time(bar[30s])",
Result: Matrix{
Series{
Floats: []FPoint{{F: 0, T: 0}, {F: 11, T: 60000}, {F: 1100, T: 120000}},
Metric: labels.EmptyLabels(),
},
},
Start: time.Unix(0, 0),
End: time.Unix(120, 0),
Interval: 60 * time.Second,
},
{
Name: "sum_over_time with all values long",
Load: `load 30s
bar 0 1 10 100 1000 10000 100000 1000000 10000000`,
Query: "sum_over_time(bar[30s])",
Result: Matrix{
Series{
Floats: []FPoint{{F: 0, T: 0}, {F: 11, T: 60000}, {F: 1100, T: 120000}, {F: 110000, T: 180000}, {F: 11000000, T: 240000}},
Metric: labels.EmptyLabels(),
},
},
Start: time.Unix(0, 0),
End: time.Unix(240, 0),
Interval: 60 * time.Second,
},
{
Name: "sum_over_time with all values random",
Load: `load 30s
bar 5 17 42 2 7 905 51`,
Query: "sum_over_time(bar[30s])",
Result: Matrix{
Series{
Floats: []FPoint{{F: 5, T: 0}, {F: 59, T: 60000}, {F: 9, T: 120000}, {F: 956, T: 180000}},
Metric: labels.EmptyLabels(),
},
},
Start: time.Unix(0, 0),
End: time.Unix(180, 0),
Interval: 60 * time.Second,
},
{
Name: "metric query",
Load: `load 30s
metric 1+1x4`,
Query: "metric",
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 3, T: 60000}, {F: 5, T: 120000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
Start: time.Unix(0, 0),
End: time.Unix(120, 0),
Interval: 1 * time.Minute,
},
{
Name: "metric query with trailing values",
Load: `load 30s
metric 1+1x8`,
Query: "metric",
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 3, T: 60000}, {F: 5, T: 120000}},
Metric: labels.FromStrings("__name__", "metric"),
},
},
Start: time.Unix(0, 0),
End: time.Unix(120, 0),
Interval: 1 * time.Minute,
},
{
Name: "short-circuit",
Load: `load 30s
foo{job="1"} 1+1x4
bar{job="2"} 1+1x4`,
Query: `foo > 2 or bar`,
Result: Matrix{
Series{
Floats: []FPoint{{F: 1, T: 0}, {F: 3, T: 60000}, {F: 5, T: 120000}},
Metric: labels.FromStrings(
"__name__", "bar",
"job", "2",
),
},
Series{
Floats: []FPoint{{F: 3, T: 60000}, {F: 5, T: 120000}},
Metric: labels.FromStrings(
"__name__", "foo",
"job", "1",
),
},
},
Start: time.Unix(0, 0),
End: time.Unix(120, 0),
Interval: 1 * time.Minute,
},
}
for _, c := range cases {
t.Run(c.Name, func(t *testing.T) {
engine := newTestEngine()
storage := LoadedStorage(t, c.Load)
t.Cleanup(func() { storage.Close() })
qry, err := engine.NewRangeQuery(context.Background(), storage, nil, c.Query, c.Start, c.End, c.Interval)
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
testutil.RequireEqual(t, c.Result, res.Value)
})
}
}
func TestNativeHistogramRate(t *testing.T) {
// TODO(beorn7): Integrate histograms into the PromQL testing framework
// and write more tests there.
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
lbls := labels.FromStrings("__name__", seriesName)
app := storage.Appender(context.Background())
for i, h := range tsdbutil.GenerateTestHistograms(100) {
_, err := app.AppendHistogram(0, lbls, int64(i)*int64(15*time.Second/time.Millisecond), h, nil)
require.NoError(t, err)
}
require.NoError(t, app.Commit())
queryString := fmt.Sprintf("rate(%s[45s])", seriesName)
t.Run("instant_query", func(t *testing.T) {
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(int64(5*time.Minute/time.Millisecond)))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
actualHistogram := vector[0].H
expectedHistogram := &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Schema: 1,
ZeroThreshold: 0.001,
ZeroCount: 1. / 15.,
Count: 9. / 15.,
Sum: 1.2266666666666663,
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
PositiveBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
NegativeSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
NegativeBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
}
require.Equal(t, expectedHistogram, actualHistogram)
})
t.Run("range_query", func(t *testing.T) {
step := 30 * time.Second
start := timestamp.Time(int64(5 * time.Minute / time.Millisecond))
end := start.Add(step)
qry, err := engine.NewRangeQuery(context.Background(), storage, nil, queryString, start, end, step)
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
matrix, err := res.Matrix()
require.NoError(t, err)
require.Len(t, matrix, 1)
require.Len(t, matrix[0].Histograms, 2)
actualHistograms := matrix[0].Histograms
expectedHistograms := []HPoint{{
T: 300000,
H: &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Schema: 1,
ZeroThreshold: 0.001,
ZeroCount: 1. / 15.,
Count: 9. / 15.,
Sum: 1.2266666666666663,
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
PositiveBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
NegativeSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
NegativeBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
},
}, {
T: 330000,
H: &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Schema: 1,
ZeroThreshold: 0.001,
ZeroCount: 1. / 15.,
Count: 9. / 15.,
Sum: 1.2266666666666663,
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
PositiveBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
NegativeSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
NegativeBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
},
}}
require.Equal(t, expectedHistograms, actualHistograms)
})
}
func TestNativeFloatHistogramRate(t *testing.T) {
// TODO(beorn7): Integrate histograms into the PromQL testing framework
// and write more tests there.
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
lbls := labels.FromStrings("__name__", seriesName)
app := storage.Appender(context.Background())
for i, fh := range tsdbutil.GenerateTestFloatHistograms(100) {
_, err := app.AppendHistogram(0, lbls, int64(i)*int64(15*time.Second/time.Millisecond), nil, fh)
require.NoError(t, err)
}
require.NoError(t, app.Commit())
queryString := fmt.Sprintf("rate(%s[1m])", seriesName)
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(int64(5*time.Minute/time.Millisecond)))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
actualHistogram := vector[0].H
expectedHistogram := &histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Schema: 1,
ZeroThreshold: 0.001,
ZeroCount: 1. / 15.,
Count: 9. / 15.,
Sum: 1.226666666666667,
PositiveSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
PositiveBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
NegativeSpans: []histogram.Span{{Offset: 0, Length: 2}, {Offset: 1, Length: 2}},
NegativeBuckets: []float64{1. / 15., 1. / 15., 1. / 15., 1. / 15.},
}
require.Equal(t, expectedHistogram, actualHistogram)
}
func TestNativeHistogram_HistogramCountAndSum(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
h := &histogram.Histogram{
Count: 24,
ZeroCount: 4,
ZeroThreshold: 0.001,
Sum: 100,
Schema: 0,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, 1, -2, 3},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
NegativeBuckets: []int64{2, 1, -2, 3},
}
for _, floatHisto := range []bool{true, false} {
t.Run(fmt.Sprintf("floatHistogram=%t", floatHisto), func(t *testing.T) {
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
lbls := labels.FromStrings("__name__", seriesName)
ts := int64(10 * time.Minute / time.Millisecond)
app := storage.Appender(context.Background())
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, h.ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, h, nil)
}
require.NoError(t, err)
require.NoError(t, app.Commit())
queryString := fmt.Sprintf("histogram_count(%s)", seriesName)
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
require.Nil(t, vector[0].H)
if floatHisto {
require.Equal(t, h.ToFloat(nil).Count, vector[0].F)
} else {
require.Equal(t, float64(h.Count), vector[0].F)
}
queryString = fmt.Sprintf("histogram_sum(%s)", seriesName)
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res = qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err = res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
require.Nil(t, vector[0].H)
if floatHisto {
require.Equal(t, h.ToFloat(nil).Sum, vector[0].F)
} else {
require.Equal(t, h.Sum, vector[0].F)
}
})
}
}
func TestNativeHistogram_HistogramStdDevVar(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
testCases := []struct {
name string
h *histogram.Histogram
stdVar float64
}{
{
name: "1, 2, 3, 4 low-res",
h: &histogram.Histogram{
Count: 4,
Sum: 10,
Schema: 2,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 1},
{Offset: 3, Length: 1},
{Offset: 2, Length: 2},
},
PositiveBuckets: []int64{1, 0, 0, 0},
},
stdVar: 1.163807968526718, // actual variance: 1.25
},
{
name: "1, 2, 3, 4 hi-res",
h: &histogram.Histogram{
Count: 4,
Sum: 10,
Schema: 8,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 1},
{Offset: 255, Length: 1},
{Offset: 149, Length: 1},
{Offset: 105, Length: 1},
},
PositiveBuckets: []int64{1, 0, 0, 0},
},
stdVar: 1.2471347737158793, // actual variance: 1.25
},
{
name: "-50, -8, 0, 3, 8, 9, 100",
h: &histogram.Histogram{
Count: 7,
ZeroCount: 1,
Sum: 62,
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 13, Length: 1},
{Offset: 10, Length: 1},
{Offset: 1, Length: 1},
{Offset: 27, Length: 1},
},
PositiveBuckets: []int64{1, 0, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 24, Length: 1},
{Offset: 21, Length: 1},
},
NegativeBuckets: []int64{1, 0},
},
stdVar: 1544.8582535368798, // actual variance: 1738.4082
},
{
name: "-50, -8, 0, 3, 8, 9, 100, NaN",
h: &histogram.Histogram{
Count: 8,
ZeroCount: 1,
Sum: math.NaN(),
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 13, Length: 1},
{Offset: 10, Length: 1},
{Offset: 1, Length: 1},
{Offset: 27, Length: 1},
},
PositiveBuckets: []int64{1, 0, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 24, Length: 1},
{Offset: 21, Length: 1},
},
NegativeBuckets: []int64{1, 0},
},
stdVar: math.NaN(),
},
{
name: "-50, -8, 0, 3, 8, 9, 100, +Inf",
h: &histogram.Histogram{
Count: 7,
ZeroCount: 1,
Sum: math.Inf(1),
Schema: 3,
PositiveSpans: []histogram.Span{
{Offset: 13, Length: 1},
{Offset: 10, Length: 1},
{Offset: 1, Length: 1},
{Offset: 27, Length: 1},
},
PositiveBuckets: []int64{1, 0, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 24, Length: 1},
{Offset: 21, Length: 1},
},
NegativeBuckets: []int64{1, 0},
},
stdVar: math.NaN(),
},
}
for _, tc := range testCases {
for _, floatHisto := range []bool{true, false} {
t.Run(fmt.Sprintf("%s floatHistogram=%t", tc.name, floatHisto), func(t *testing.T) {
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
lbls := labels.FromStrings("__name__", seriesName)
ts := int64(10 * time.Minute / time.Millisecond)
app := storage.Appender(context.Background())
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, tc.h.ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, tc.h, nil)
}
require.NoError(t, err)
require.NoError(t, app.Commit())
queryString := fmt.Sprintf("histogram_stdvar(%s)", seriesName)
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
require.Nil(t, vector[0].H)
require.InEpsilon(t, tc.stdVar, vector[0].F, 1e-12)
queryString = fmt.Sprintf("histogram_stddev(%s)", seriesName)
qry, err = engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res = qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err = res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
require.Nil(t, vector[0].H)
require.InEpsilon(t, math.Sqrt(tc.stdVar), vector[0].F, 1e-12)
})
}
}
}
func TestNativeHistogram_HistogramQuantile(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
type subCase struct {
quantile string
value float64
}
cases := []struct {
text string
// Histogram to test.
h *histogram.Histogram
// Different quantiles to test for this histogram.
subCases []subCase
}{
{
text: "all positive buckets with zero bucket",
h: &histogram.Histogram{
Count: 12,
ZeroCount: 2,
ZeroThreshold: 0.001,
Sum: 100, // Does not matter.
Schema: 0,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, 1, -2, 3},
},
subCases: []subCase{
{
quantile: "1.0001",
value: math.Inf(1),
},
{
quantile: "1",
value: 16,
},
{
quantile: "0.99",
value: 15.759999999999998,
},
{
quantile: "0.9",
value: 13.600000000000001,
},
{
quantile: "0.6",
value: 4.799999999999997,
},
{
quantile: "0.5",
value: 1.6666666666666665,
},
{ // Zero bucket.
quantile: "0.1",
value: 0.0006000000000000001,
},
{
quantile: "0",
value: 0,
},
{
quantile: "-1",
value: math.Inf(-1),
},
},
},
{
text: "all negative buckets with zero bucket",
h: &histogram.Histogram{
Count: 12,
ZeroCount: 2,
ZeroThreshold: 0.001,
Sum: 100, // Does not matter.
Schema: 0,
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
NegativeBuckets: []int64{2, 1, -2, 3},
},
subCases: []subCase{
{
quantile: "1.0001",
value: math.Inf(1),
},
{ // Zero bucket.
quantile: "1",
value: 0,
},
{ // Zero bucket.
quantile: "0.99",
value: -6.000000000000048e-05,
},
{ // Zero bucket.
quantile: "0.9",
value: -0.0005999999999999996,
},
{
quantile: "0.5",
value: -1.6666666666666667,
},
{
quantile: "0.1",
value: -13.6,
},
{
quantile: "0",
value: -16,
},
{
quantile: "-1",
value: math.Inf(-1),
},
},
},
{
text: "both positive and negative buckets with zero bucket",
h: &histogram.Histogram{
Count: 24,
ZeroCount: 4,
ZeroThreshold: 0.001,
Sum: 100, // Does not matter.
Schema: 0,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, 1, -2, 3},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
NegativeBuckets: []int64{2, 1, -2, 3},
},
subCases: []subCase{
{
quantile: "1.0001",
value: math.Inf(1),
},
{
quantile: "1",
value: 16,
},
{
quantile: "0.99",
value: 15.519999999999996,
},
{
quantile: "0.9",
value: 11.200000000000003,
},
{
quantile: "0.7",
value: 1.2666666666666657,
},
{ // Zero bucket.
quantile: "0.55",
value: 0.0006000000000000005,
},
{ // Zero bucket.
quantile: "0.5",
value: 0,
},
{ // Zero bucket.
quantile: "0.45",
value: -0.0005999999999999996,
},
{
quantile: "0.3",
value: -1.266666666666667,
},
{
quantile: "0.1",
value: -11.2,
},
{
quantile: "0.01",
value: -15.52,
},
{
quantile: "0",
value: -16,
},
{
quantile: "-1",
value: math.Inf(-1),
},
},
},
}
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
idx := int64(0)
for _, floatHisto := range []bool{true, false} {
for _, c := range cases {
t.Run(fmt.Sprintf("%s floatHistogram=%t", c.text, floatHisto), func(t *testing.T) {
seriesName := "sparse_histogram_series"
lbls := labels.FromStrings("__name__", seriesName)
ts := idx * int64(10*time.Minute/time.Millisecond)
app := storage.Appender(context.Background())
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, c.h.ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, c.h, nil)
}
require.NoError(t, err)
require.NoError(t, app.Commit())
for j, sc := range c.subCases {
t.Run(fmt.Sprintf("%d %s", j, sc.quantile), func(t *testing.T) {
queryString := fmt.Sprintf("histogram_quantile(%s, %s)", sc.quantile, seriesName)
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
require.Nil(t, vector[0].H)
require.True(t, almostEqual(sc.value, vector[0].F, defaultEpsilon))
})
}
idx++
})
}
}
}
func TestNativeHistogram_HistogramFraction(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
type subCase struct {
lower, upper string
value float64
}
invariantCases := []subCase{
{
lower: "42",
upper: "3.1415",
value: 0,
},
{
lower: "0",
upper: "0",
value: 0,
},
{
lower: "0.000001",
upper: "0.000001",
value: 0,
},
{
lower: "42",
upper: "42",
value: 0,
},
{
lower: "-3.1",
upper: "-3.1",
value: 0,
},
{
lower: "3.1415",
upper: "NaN",
value: math.NaN(),
},
{
lower: "NaN",
upper: "42",
value: math.NaN(),
},
{
lower: "NaN",
upper: "NaN",
value: math.NaN(),
},
{
lower: "-Inf",
upper: "+Inf",
value: 1,
},
}
cases := []struct {
text string
// Histogram to test.
h *histogram.Histogram
// Different ranges to test for this histogram.
subCases []subCase
}{
{
text: "empty histogram",
h: &histogram.Histogram{},
subCases: []subCase{
{
lower: "3.1415",
upper: "42",
value: math.NaN(),
},
},
},
{
text: "all positive buckets with zero bucket",
h: &histogram.Histogram{
Count: 12,
ZeroCount: 2,
ZeroThreshold: 0.001,
Sum: 100, // Does not matter.
Schema: 0,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, 1, -2, 3}, // Abs: 2, 3, 1, 4
},
subCases: append([]subCase{
{
lower: "0",
upper: "+Inf",
value: 1,
},
{
lower: "-Inf",
upper: "0",
value: 0,
},
{
lower: "-0.001",
upper: "0",
value: 0,
},
{
lower: "0",
upper: "0.001",
value: 2. / 12.,
},
{
lower: "0",
upper: "0.0005",
value: 1. / 12.,
},
{
lower: "0.001",
upper: "inf",
value: 10. / 12.,
},
{
lower: "-inf",
upper: "-0.001",
value: 0,
},
{
lower: "1",
upper: "2",
value: 3. / 12.,
},
{
lower: "1.5",
upper: "2",
value: 1.5 / 12.,
},
{
lower: "1",
upper: "8",
value: 4. / 12.,
},
{
lower: "1",
upper: "6",
value: 3.5 / 12.,
},
{
lower: "1.5",
upper: "6",
value: 2. / 12.,
},
{
lower: "-2",
upper: "-1",
value: 0,
},
{
lower: "-2",
upper: "-1.5",
value: 0,
},
{
lower: "-8",
upper: "-1",
value: 0,
},
{
lower: "-6",
upper: "-1",
value: 0,
},
{
lower: "-6",
upper: "-1.5",
value: 0,
},
}, invariantCases...),
},
{
text: "all negative buckets with zero bucket",
h: &histogram.Histogram{
Count: 12,
ZeroCount: 2,
ZeroThreshold: 0.001,
Sum: 100, // Does not matter.
Schema: 0,
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
NegativeBuckets: []int64{2, 1, -2, 3},
},
subCases: append([]subCase{
{
lower: "0",
upper: "+Inf",
value: 0,
},
{
lower: "-Inf",
upper: "0",
value: 1,
},
{
lower: "-0.001",
upper: "0",
value: 2. / 12.,
},
{
lower: "0",
upper: "0.001",
value: 0,
},
{
lower: "-0.0005",
upper: "0",
value: 1. / 12.,
},
{
lower: "0.001",
upper: "inf",
value: 0,
},
{
lower: "-inf",
upper: "-0.001",
value: 10. / 12.,
},
{
lower: "1",
upper: "2",
value: 0,
},
{
lower: "1.5",
upper: "2",
value: 0,
},
{
lower: "1",
upper: "8",
value: 0,
},
{
lower: "1",
upper: "6",
value: 0,
},
{
lower: "1.5",
upper: "6",
value: 0,
},
{
lower: "-2",
upper: "-1",
value: 3. / 12.,
},
{
lower: "-2",
upper: "-1.5",
value: 1.5 / 12.,
},
{
lower: "-8",
upper: "-1",
value: 4. / 12.,
},
{
lower: "-6",
upper: "-1",
value: 3.5 / 12.,
},
{
lower: "-6",
upper: "-1.5",
value: 2. / 12.,
},
}, invariantCases...),
},
{
text: "both positive and negative buckets with zero bucket",
h: &histogram.Histogram{
Count: 24,
ZeroCount: 4,
ZeroThreshold: 0.001,
Sum: 100, // Does not matter.
Schema: 0,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, 1, -2, 3},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
NegativeBuckets: []int64{2, 1, -2, 3},
},
subCases: append([]subCase{
{
lower: "0",
upper: "+Inf",
value: 0.5,
},
{
lower: "-Inf",
upper: "0",
value: 0.5,
},
{
lower: "-0.001",
upper: "0",
value: 2. / 24,
},
{
lower: "0",
upper: "0.001",
value: 2. / 24.,
},
{
lower: "-0.0005",
upper: "0.0005",
value: 2. / 24.,
},
{
lower: "0.001",
upper: "inf",
value: 10. / 24.,
},
{
lower: "-inf",
upper: "-0.001",
value: 10. / 24.,
},
{
lower: "1",
upper: "2",
value: 3. / 24.,
},
{
lower: "1.5",
upper: "2",
value: 1.5 / 24.,
},
{
lower: "1",
upper: "8",
value: 4. / 24.,
},
{
lower: "1",
upper: "6",
value: 3.5 / 24.,
},
{
lower: "1.5",
upper: "6",
value: 2. / 24.,
},
{
lower: "-2",
upper: "-1",
value: 3. / 24.,
},
{
lower: "-2",
upper: "-1.5",
value: 1.5 / 24.,
},
{
lower: "-8",
upper: "-1",
value: 4. / 24.,
},
{
lower: "-6",
upper: "-1",
value: 3.5 / 24.,
},
{
lower: "-6",
upper: "-1.5",
value: 2. / 24.,
},
}, invariantCases...),
},
}
idx := int64(0)
for _, floatHisto := range []bool{true, false} {
for _, c := range cases {
t.Run(fmt.Sprintf("%s floatHistogram=%t", c.text, floatHisto), func(t *testing.T) {
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
lbls := labels.FromStrings("__name__", seriesName)
ts := idx * int64(10*time.Minute/time.Millisecond)
app := storage.Appender(context.Background())
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, c.h.ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, c.h, nil)
}
require.NoError(t, err)
require.NoError(t, app.Commit())
for j, sc := range c.subCases {
t.Run(fmt.Sprintf("%d %s %s", j, sc.lower, sc.upper), func(t *testing.T) {
queryString := fmt.Sprintf("histogram_fraction(%s, %s, %s)", sc.lower, sc.upper, seriesName)
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
require.Len(t, vector, 1)
require.Nil(t, vector[0].H)
if math.IsNaN(sc.value) {
require.True(t, math.IsNaN(vector[0].F))
return
}
require.Equal(t, sc.value, vector[0].F)
})
}
idx++
})
}
}
}
func TestNativeHistogram_Sum_Count_Add_AvgOperator(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
cases := []struct {
histograms []histogram.Histogram
expected histogram.FloatHistogram
expectedAvg histogram.FloatHistogram
}{
{
histograms: []histogram.Histogram{
{
CounterResetHint: histogram.GaugeType,
Schema: 0,
Count: 25,
Sum: 1234.5,
ZeroThreshold: 0.001,
ZeroCount: 4,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{1, 1, -1, 0},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 2, Length: 2},
},
NegativeBuckets: []int64{2, 2, -3, 8},
},
{
CounterResetHint: histogram.GaugeType,
Schema: 0,
Count: 41,
Sum: 2345.6,
ZeroThreshold: 0.001,
ZeroCount: 5,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 4},
{Offset: 0, Length: 0},
{Offset: 0, Length: 3},
},
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 2, Length: 0},
{Offset: 2, Length: 3},
},
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
},
{
CounterResetHint: histogram.GaugeType,
Schema: 0,
Count: 41,
Sum: 1111.1,
ZeroThreshold: 0.001,
ZeroCount: 5,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 4},
{Offset: 0, Length: 0},
{Offset: 0, Length: 3},
},
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 2, Length: 0},
{Offset: 2, Length: 3},
},
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
},
{
CounterResetHint: histogram.GaugeType,
Schema: 1, // Everything is 0 just to make the count 4 so avg has nicer numbers.
},
},
expected: histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Schema: 0,
ZeroThreshold: 0.001,
ZeroCount: 14,
Count: 107,
Sum: 4691.2,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 7},
},
PositiveBuckets: []float64{3, 8, 2, 5, 3, 2, 2},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 6},
{Offset: 3, Length: 3},
},
NegativeBuckets: []float64{2, 6, 8, 4, 15, 9, 10, 10, 4},
},
expectedAvg: histogram.FloatHistogram{
CounterResetHint: histogram.GaugeType,
Schema: 0,
ZeroThreshold: 0.001,
ZeroCount: 3.5,
Count: 26.75,
Sum: 1172.8,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 7},
},
PositiveBuckets: []float64{0.75, 2, 0.5, 1.25, 0.75, 0.5, 0.5},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 6},
{Offset: 3, Length: 3},
},
NegativeBuckets: []float64{0.5, 1.5, 2, 1, 3.75, 2.25, 2.5, 2.5, 1},
},
},
}
idx0 := int64(0)
for _, c := range cases {
for _, floatHisto := range []bool{true, false} {
t.Run(fmt.Sprintf("floatHistogram=%t %d", floatHisto, idx0), func(t *testing.T) {
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
seriesNameOverTime := "sparse_histogram_series_over_time"
engine := newTestEngine()
ts := idx0 * int64(10*time.Minute/time.Millisecond)
app := storage.Appender(context.Background())
for idx1, h := range c.histograms {
lbls := labels.FromStrings("__name__", seriesName, "idx", fmt.Sprintf("%d", idx1))
// Since we mutate h later, we need to create a copy here.
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, h.Copy().ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, h.Copy(), nil)
}
require.NoError(t, err)
lbls = labels.FromStrings("__name__", seriesNameOverTime)
newTs := ts + int64(idx1)*int64(time.Minute/time.Millisecond)
// Since we mutate h later, we need to create a copy here.
if floatHisto {
_, err = app.AppendHistogram(0, lbls, newTs, nil, h.Copy().ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, newTs, h.Copy(), nil)
}
require.NoError(t, err)
}
require.NoError(t, app.Commit())
queryAndCheck := func(queryString string, ts int64, exp Vector) {
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
testutil.RequireEqual(t, exp, vector)
}
// sum().
queryString := fmt.Sprintf("sum(%s)", seriesName)
queryAndCheck(queryString, ts, []Sample{{T: ts, H: &c.expected, Metric: labels.EmptyLabels()}})
// + operator.
queryString = fmt.Sprintf(`%s{idx="0"}`, seriesName)
for idx := 1; idx < len(c.histograms); idx++ {
queryString += fmt.Sprintf(` + ignoring(idx) %s{idx="%d"}`, seriesName, idx)
}
queryAndCheck(queryString, ts, []Sample{{T: ts, H: &c.expected, Metric: labels.EmptyLabels()}})
// count().
queryString = fmt.Sprintf("count(%s)", seriesName)
queryAndCheck(queryString, ts, []Sample{{T: ts, F: 4, Metric: labels.EmptyLabels()}})
// avg().
queryString = fmt.Sprintf("avg(%s)", seriesName)
queryAndCheck(queryString, ts, []Sample{{T: ts, H: &c.expectedAvg, Metric: labels.EmptyLabels()}})
offset := int64(len(c.histograms) - 1)
newTs := ts + offset*int64(time.Minute/time.Millisecond)
// sum_over_time().
queryString = fmt.Sprintf("sum_over_time(%s[%dm:1m])", seriesNameOverTime, offset)
queryAndCheck(queryString, newTs, []Sample{{T: newTs, H: &c.expected, Metric: labels.EmptyLabels()}})
// avg_over_time().
queryString = fmt.Sprintf("avg_over_time(%s[%dm:1m])", seriesNameOverTime, offset)
queryAndCheck(queryString, newTs, []Sample{{T: newTs, H: &c.expectedAvg, Metric: labels.EmptyLabels()}})
})
idx0++
}
}
}
func TestNativeHistogram_SubOperator(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
cases := []struct {
histograms []histogram.Histogram
expected histogram.FloatHistogram
}{
{
histograms: []histogram.Histogram{
{
Schema: 0,
Count: 41,
Sum: 2345.6,
ZeroThreshold: 0.001,
ZeroCount: 5,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 4},
{Offset: 0, Length: 0},
{Offset: 0, Length: 3},
},
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 2, Length: 0},
{Offset: 2, Length: 3},
},
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
},
{
Schema: 0,
Count: 11,
Sum: 1234.5,
ZeroThreshold: 0.001,
ZeroCount: 3,
PositiveSpans: []histogram.Span{
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, -1},
NegativeSpans: []histogram.Span{
{Offset: 2, Length: 2},
},
NegativeBuckets: []int64{3, -1},
},
},
expected: histogram.FloatHistogram{
Schema: 0,
Count: 30,
Sum: 1111.1,
ZeroThreshold: 0.001,
ZeroCount: 2,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 2},
{Offset: 1, Length: 4},
},
PositiveBuckets: []float64{1, 1, 2, 1, 1, 1},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 2},
{Offset: 1, Length: 1},
{Offset: 4, Length: 3},
},
NegativeBuckets: []float64{1, 1, 7, 5, 5, 2},
},
},
{
histograms: []histogram.Histogram{
{
Schema: 0,
Count: 41,
Sum: 2345.6,
ZeroThreshold: 0.001,
ZeroCount: 5,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 4},
{Offset: 0, Length: 0},
{Offset: 0, Length: 3},
},
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 2, Length: 0},
{Offset: 2, Length: 3},
},
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
},
{
Schema: 1,
Count: 11,
Sum: 1234.5,
ZeroThreshold: 0.001,
ZeroCount: 3,
PositiveSpans: []histogram.Span{
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, -1},
NegativeSpans: []histogram.Span{
{Offset: 2, Length: 2},
},
NegativeBuckets: []int64{3, -1},
},
},
expected: histogram.FloatHistogram{
Schema: 0,
Count: 30,
Sum: 1111.1,
ZeroThreshold: 0.001,
ZeroCount: 2,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 1},
{Offset: 1, Length: 5},
},
PositiveBuckets: []float64{1, 1, 2, 1, 1, 1},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 4, Length: 3},
},
NegativeBuckets: []float64{-2, 2, 2, 7, 5, 5, 2},
},
},
{
histograms: []histogram.Histogram{
{
Schema: 1,
Count: 11,
Sum: 1234.5,
ZeroThreshold: 0.001,
ZeroCount: 3,
PositiveSpans: []histogram.Span{
{Offset: 1, Length: 2},
},
PositiveBuckets: []int64{2, -1},
NegativeSpans: []histogram.Span{
{Offset: 2, Length: 2},
},
NegativeBuckets: []int64{3, -1},
},
{
Schema: 0,
Count: 41,
Sum: 2345.6,
ZeroThreshold: 0.001,
ZeroCount: 5,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 4},
{Offset: 0, Length: 0},
{Offset: 0, Length: 3},
},
PositiveBuckets: []int64{1, 2, -2, 1, -1, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 2, Length: 0},
{Offset: 2, Length: 3},
},
NegativeBuckets: []int64{1, 3, -2, 5, -2, 0, -3},
},
},
expected: histogram.FloatHistogram{
Schema: 0,
Count: -30,
Sum: -1111.1,
ZeroThreshold: 0.001,
ZeroCount: -2,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 1},
{Offset: 1, Length: 5},
},
PositiveBuckets: []float64{-1, -1, -2, -1, -1, -1},
NegativeSpans: []histogram.Span{
{Offset: 1, Length: 4},
{Offset: 4, Length: 3},
},
NegativeBuckets: []float64{2, -2, -2, -7, -5, -5, -2},
},
},
}
idx0 := int64(0)
for _, c := range cases {
for _, floatHisto := range []bool{true, false} {
t.Run(fmt.Sprintf("floatHistogram=%t %d", floatHisto, idx0), func(t *testing.T) {
engine := newTestEngine()
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
ts := idx0 * int64(10*time.Minute/time.Millisecond)
app := storage.Appender(context.Background())
for idx1, h := range c.histograms {
lbls := labels.FromStrings("__name__", seriesName, "idx", fmt.Sprintf("%d", idx1))
// Since we mutate h later, we need to create a copy here.
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, h.Copy().ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, h.Copy(), nil)
}
require.NoError(t, err)
}
require.NoError(t, app.Commit())
queryAndCheck := func(queryString string, exp Vector) {
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
if len(vector) == len(exp) {
for i, e := range exp {
got := vector[i].H
if got != e.H {
// Error messages are better if we compare structs, not pointers.
require.Equal(t, *e.H, *got)
}
}
}
testutil.RequireEqual(t, exp, vector)
}
// - operator.
queryString := fmt.Sprintf(`%s{idx="0"}`, seriesName)
for idx := 1; idx < len(c.histograms); idx++ {
queryString += fmt.Sprintf(` - ignoring(idx) %s{idx="%d"}`, seriesName, idx)
}
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expected, Metric: labels.EmptyLabels()}})
})
}
idx0++
}
}
func TestNativeHistogram_MulDivOperator(t *testing.T) {
// TODO(codesome): Integrate histograms into the PromQL testing framework
// and write more tests there.
originalHistogram := histogram.Histogram{
Schema: 0,
Count: 21,
Sum: 33,
ZeroThreshold: 0.001,
ZeroCount: 3,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
PositiveBuckets: []int64{3, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
NegativeBuckets: []int64{3, 0, 0},
}
cases := []struct {
scalar float64
histogram histogram.Histogram
expectedMul histogram.FloatHistogram
expectedDiv histogram.FloatHistogram
}{
{
scalar: 3,
histogram: originalHistogram,
expectedMul: histogram.FloatHistogram{
Schema: 0,
Count: 63,
Sum: 99,
ZeroThreshold: 0.001,
ZeroCount: 9,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
PositiveBuckets: []float64{9, 9, 9},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
NegativeBuckets: []float64{9, 9, 9},
},
expectedDiv: histogram.FloatHistogram{
Schema: 0,
Count: 7,
Sum: 11,
ZeroThreshold: 0.001,
ZeroCount: 1,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
PositiveBuckets: []float64{1, 1, 1},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
NegativeBuckets: []float64{1, 1, 1},
},
},
{
scalar: 0,
histogram: originalHistogram,
expectedMul: histogram.FloatHistogram{
Schema: 0,
Count: 0,
Sum: 0,
ZeroThreshold: 0.001,
ZeroCount: 0,
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
PositiveBuckets: []float64{0, 0, 0},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
NegativeBuckets: []float64{0, 0, 0},
},
expectedDiv: histogram.FloatHistogram{
Schema: 0,
Count: math.Inf(1),
Sum: math.Inf(1),
ZeroThreshold: 0.001,
ZeroCount: math.Inf(1),
PositiveSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
PositiveBuckets: []float64{math.Inf(1), math.Inf(1), math.Inf(1)},
NegativeSpans: []histogram.Span{
{Offset: 0, Length: 3},
},
NegativeBuckets: []float64{math.Inf(1), math.Inf(1), math.Inf(1)},
},
},
}
idx0 := int64(0)
for _, c := range cases {
for _, floatHisto := range []bool{true, false} {
t.Run(fmt.Sprintf("floatHistogram=%t %d", floatHisto, idx0), func(t *testing.T) {
storage := teststorage.New(t)
t.Cleanup(func() { storage.Close() })
seriesName := "sparse_histogram_series"
floatSeriesName := "float_series"
engine := newTestEngine()
ts := idx0 * int64(10*time.Minute/time.Millisecond)
app := storage.Appender(context.Background())
h := c.histogram
lbls := labels.FromStrings("__name__", seriesName)
// Since we mutate h later, we need to create a copy here.
var err error
if floatHisto {
_, err = app.AppendHistogram(0, lbls, ts, nil, h.Copy().ToFloat(nil))
} else {
_, err = app.AppendHistogram(0, lbls, ts, h.Copy(), nil)
}
require.NoError(t, err)
_, err = app.Append(0, labels.FromStrings("__name__", floatSeriesName), ts, c.scalar)
require.NoError(t, err)
require.NoError(t, app.Commit())
queryAndCheck := func(queryString string, exp Vector) {
qry, err := engine.NewInstantQuery(context.Background(), storage, nil, queryString, timestamp.Time(ts))
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vector, err := res.Vector()
require.NoError(t, err)
testutil.RequireEqual(t, exp, vector)
}
// histogram * scalar.
queryString := fmt.Sprintf(`%s * %f`, seriesName, c.scalar)
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expectedMul, Metric: labels.EmptyLabels()}})
// scalar * histogram.
queryString = fmt.Sprintf(`%f * %s`, c.scalar, seriesName)
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expectedMul, Metric: labels.EmptyLabels()}})
// histogram * float.
queryString = fmt.Sprintf(`%s * %s`, seriesName, floatSeriesName)
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expectedMul, Metric: labels.EmptyLabels()}})
// float * histogram.
queryString = fmt.Sprintf(`%s * %s`, floatSeriesName, seriesName)
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expectedMul, Metric: labels.EmptyLabels()}})
// histogram / scalar.
queryString = fmt.Sprintf(`%s / %f`, seriesName, c.scalar)
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expectedDiv, Metric: labels.EmptyLabels()}})
// histogram / float.
queryString = fmt.Sprintf(`%s / %s`, seriesName, floatSeriesName)
queryAndCheck(queryString, []Sample{{T: ts, H: &c.expectedDiv, Metric: labels.EmptyLabels()}})
})
idx0++
}
}
}
func TestQueryLookbackDelta(t *testing.T) {
var (
load = `load 5m
metric 0 1 2
`
query = "metric"
lastDatapointTs = time.Unix(600, 0)
)
cases := []struct {
name string
ts time.Time
engineLookback, queryLookback time.Duration
expectSamples bool
}{
{
name: "default lookback delta",
ts: lastDatapointTs.Add(defaultLookbackDelta),
expectSamples: true,
},
{
name: "outside default lookback delta",
ts: lastDatapointTs.Add(defaultLookbackDelta + time.Millisecond),
expectSamples: false,
},
{
name: "custom engine lookback delta",
ts: lastDatapointTs.Add(10 * time.Minute),
engineLookback: 10 * time.Minute,
expectSamples: true,
},
{
name: "outside custom engine lookback delta",
ts: lastDatapointTs.Add(10*time.Minute + time.Millisecond),
engineLookback: 10 * time.Minute,
expectSamples: false,
},
{
name: "custom query lookback delta",
ts: lastDatapointTs.Add(20 * time.Minute),
engineLookback: 10 * time.Minute,
queryLookback: 20 * time.Minute,
expectSamples: true,
},
{
name: "outside custom query lookback delta",
ts: lastDatapointTs.Add(20*time.Minute + time.Millisecond),
engineLookback: 10 * time.Minute,
queryLookback: 20 * time.Minute,
expectSamples: false,
},
{
name: "negative custom query lookback delta",
ts: lastDatapointTs.Add(20 * time.Minute),
engineLookback: -10 * time.Minute,
queryLookback: 20 * time.Minute,
expectSamples: true,
},
}
for _, c := range cases {
c := c
t.Run(c.name, func(t *testing.T) {
engine := newTestEngine()
storage := LoadedStorage(t, load)
t.Cleanup(func() { storage.Close() })
if c.engineLookback != 0 {
engine.lookbackDelta = c.engineLookback
}
opts := NewPrometheusQueryOpts(false, c.queryLookback)
qry, err := engine.NewInstantQuery(context.Background(), storage, opts, query, c.ts)
require.NoError(t, err)
res := qry.Exec(context.Background())
require.NoError(t, res.Err)
vec, ok := res.Value.(Vector)
require.True(t, ok)
if c.expectSamples {
require.NotEmpty(t, vec)
} else {
require.Empty(t, vec)
}
})
}
}