mudhorn/prometheus
1
0
Fork 0
mirror of https://github.com/prometheus/prometheus.git synced 2024-12-25 05:34:05 -08:00
Code Issues Actions 3 Packages Projects Releases Wiki Activity
prometheus/promql/engine_test.go
zenador 69edd8709b
Add warnings (and annotations) to PromQL query results (#12152) 
Return annotations (warnings and infos) from PromQL queries

This generalizes the warnings we have already used before (but only for problems with remote read) as "annotations".

Annotations can be warnings or infos (the latter could be false positives). We do not treat them different in the API for now and return them all as "warnings". It would be easy to distinguish them and return infos separately, should that appear useful in the future.

The new annotations are then used to create a lot of warnings or infos during PromQL evaluations. Partially these are things we have wanted for a long time (e.g. inform the user that they have applied `rate` to a metric that doesn't look like a counter), but the new native histograms have created even more needs for those annotations (e.g. if a query tries to aggregate float numbers with histograms).

The annotations added here are not yet complete. A prominent example would be a warning about a range too short for a rate calculation. But such a warnings is more tricky to create with good fidelity and we will tackle it later.

Another TODO is to take annotations into account when evaluating recording rules.

---------

Signed-off-by: Jeanette Tan <jeanette.tan@grafana.com>
2023-09-14 18:57:31 +02:00

4828 lines
129 KiB
Go
Raw Blame History

// 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"
)
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.True(t, errors.As(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.True(t, errors.Is(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.True(t, errors.Is(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.True(t, errors.As(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))
}
require.Equal(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
//nolint:govet
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)
require.Equal(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)
require.Equal(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.Equal(t, 2*l, len(f1.logs))
// 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.Nil(t, err1)
require.Nil(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)
require.Equal(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[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 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())
} 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().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().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: 8,
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())
} 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())
} 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))
})
}
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())
} 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())
} 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())
} 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)
require.Equal(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())
} 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)
}
}
}
require.Equal(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())
} 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)
require.Equal(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)
}
})
}
}
Reference in a new issue View git blame Copy permalink