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af91fb8e31
This is done by bucketing chunks by fingerprint. If the persisting to disk falls behind, more and more chunks are in the queue. As soon as there are "double hits", we will now persist both chunks in one go, doubling the disk throughput (assuming it is limited by disk seeks). Should even more pile up so that we end wit "triple hits", we will persist those first, and so on. Even if we have millions of time series, this will still help, assuming not all of them are growing with the same speed. Series that get many samples and/or are not very compressable will accumulate chunks faster, and they will soon get double- or triple-writes. To improve the chance of double writes, -storage.local.persistence-queue-capacity could be set to a higher value. However, that will slow down shutdown a lot (as the queue has to be worked through). So we leave it to the user to set it to a really high value. A more fundamental solution would be to checkpoint not only head chunks, but also chunks still in the persist queue. That would be quite complicated for a rather limited use-case (running many time series with high ingestion rate on slow spinning disks).
624 lines
16 KiB
Go
624 lines
16 KiB
Go
// Copyright 2014 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package local
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import (
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"reflect"
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"testing"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/storage/local/codable"
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"github.com/prometheus/prometheus/storage/local/index"
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"github.com/prometheus/prometheus/storage/metric"
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"github.com/prometheus/prometheus/utility/test"
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)
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var (
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m1 = clientmodel.Metric{"label": "value1"}
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m2 = clientmodel.Metric{"label": "value2"}
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m3 = clientmodel.Metric{"label": "value3"}
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)
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func newTestPersistence(t *testing.T) (*persistence, test.Closer) {
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dir := test.NewTemporaryDirectory("test_persistence", t)
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p, err := newPersistence(dir.Path(), 1024, false)
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if err != nil {
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dir.Close()
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t.Fatal(err)
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}
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return p, test.NewCallbackCloser(func() {
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p.close()
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dir.Close()
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})
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}
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func buildTestChunks() map[clientmodel.Fingerprint][]chunk {
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fps := clientmodel.Fingerprints{
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m1.Fingerprint(),
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m2.Fingerprint(),
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m3.Fingerprint(),
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}
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fpToChunks := map[clientmodel.Fingerprint][]chunk{}
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for _, fp := range fps {
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fpToChunks[fp] = make([]chunk, 0, 10)
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for i := 0; i < 10; i++ {
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fpToChunks[fp] = append(fpToChunks[fp], newDeltaEncodedChunk(d1, d1, true).add(&metric.SamplePair{
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Timestamp: clientmodel.Timestamp(i),
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Value: clientmodel.SampleValue(fp),
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})[0])
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}
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}
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return fpToChunks
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}
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func chunksEqual(c1, c2 chunk) bool {
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values2 := c2.values()
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for v1 := range c1.values() {
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v2 := <-values2
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if !v1.Equal(v2) {
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return false
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}
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}
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return true
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}
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func TestPersistLoadDropChunks(t *testing.T) {
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p, closer := newTestPersistence(t)
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defer closer.Close()
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fpToChunks := buildTestChunks()
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for fp, chunks := range fpToChunks {
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for i, c := range chunks {
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index, err := p.persistChunks(fp, []chunk{c})
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if err != nil {
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t.Fatal(err)
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}
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if i != index {
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t.Errorf("Want chunk index %d, got %d.", i, index)
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}
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}
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}
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for fp, expectedChunks := range fpToChunks {
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indexes := make([]int, 0, len(expectedChunks))
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for i := range expectedChunks {
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indexes = append(indexes, i)
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}
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actualChunks, err := p.loadChunks(fp, indexes, 0)
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if err != nil {
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t.Fatal(err)
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}
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for _, i := range indexes {
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if !chunksEqual(expectedChunks[i], actualChunks[i]) {
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t.Errorf("%d. Chunks not equal.", i)
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}
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}
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// Load all chunk descs.
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actualChunkDescs, err := p.loadChunkDescs(fp, 10)
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if len(actualChunkDescs) != 10 {
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t.Errorf("Got %d chunkDescs, want %d.", len(actualChunkDescs), 10)
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}
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for i, cd := range actualChunkDescs {
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if cd.firstTime() != clientmodel.Timestamp(i) || cd.lastTime() != clientmodel.Timestamp(i) {
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t.Errorf(
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"Want ts=%v, got firstTime=%v, lastTime=%v.",
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i, cd.firstTime(), cd.lastTime(),
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)
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}
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}
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// Load chunk descs partially.
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actualChunkDescs, err = p.loadChunkDescs(fp, 5)
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if len(actualChunkDescs) != 5 {
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t.Errorf("Got %d chunkDescs, want %d.", len(actualChunkDescs), 5)
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}
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for i, cd := range actualChunkDescs {
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if cd.firstTime() != clientmodel.Timestamp(i) || cd.lastTime() != clientmodel.Timestamp(i) {
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t.Errorf(
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"Want ts=%v, got firstTime=%v, lastTime=%v.",
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i, cd.firstTime(), cd.lastTime(),
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)
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}
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}
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}
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// Drop half of the chunks.
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for fp, expectedChunks := range fpToChunks {
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firstTime, numDropped, allDropped, err := p.dropChunks(fp, 5)
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if err != nil {
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t.Fatal(err)
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}
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if firstTime != 5 {
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t.Errorf("want first time 5, got %d", firstTime)
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}
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if numDropped != 5 {
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t.Errorf("want 5 dropped chunks, got %v", numDropped)
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}
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if allDropped {
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t.Error("all chunks dropped")
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}
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indexes := make([]int, 5)
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for i := range indexes {
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indexes[i] = i
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}
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actualChunks, err := p.loadChunks(fp, indexes, 0)
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if err != nil {
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t.Fatal(err)
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}
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for _, i := range indexes {
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if !chunksEqual(expectedChunks[i+5], actualChunks[i]) {
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t.Errorf("%d. Chunks not equal.", i)
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}
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}
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}
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// Drop all the chunks.
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for fp := range fpToChunks {
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firstTime, numDropped, allDropped, err := p.dropChunks(fp, 100)
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if firstTime != 0 {
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t.Errorf("want first time 0, got %d", firstTime)
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}
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if err != nil {
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t.Fatal(err)
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}
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if numDropped != 5 {
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t.Errorf("want 5 dropped chunks, got %v", numDropped)
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}
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if !allDropped {
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t.Error("not all chunks dropped")
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}
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}
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}
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func TestCheckpointAndLoadSeriesMapAndHeads(t *testing.T) {
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p, closer := newTestPersistence(t)
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defer closer.Close()
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fpLocker := newFingerprintLocker(10)
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sm := newSeriesMap()
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s1 := newMemorySeries(m1, true, 0)
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s2 := newMemorySeries(m2, false, 0)
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s3 := newMemorySeries(m3, false, 0)
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s1.add(m1.Fingerprint(), &metric.SamplePair{Timestamp: 1, Value: 3.14})
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s3.add(m1.Fingerprint(), &metric.SamplePair{Timestamp: 2, Value: 2.7})
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s3.headChunkPersisted = true
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sm.put(m1.Fingerprint(), s1)
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sm.put(m2.Fingerprint(), s2)
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sm.put(m3.Fingerprint(), s3)
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if err := p.checkpointSeriesMapAndHeads(sm, fpLocker); err != nil {
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t.Fatal(err)
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}
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loadedSM, err := p.loadSeriesMapAndHeads()
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if err != nil {
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t.Fatal(err)
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}
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if loadedSM.length() != 2 {
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t.Errorf("want 2 series in map, got %d", loadedSM.length())
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}
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if loadedS1, ok := loadedSM.get(m1.Fingerprint()); ok {
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if !reflect.DeepEqual(loadedS1.metric, m1) {
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t.Errorf("want metric %v, got %v", m1, loadedS1.metric)
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}
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if !reflect.DeepEqual(loadedS1.head().chunk, s1.head().chunk) {
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t.Error("head chunks differ")
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}
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if loadedS1.chunkDescsOffset != 0 {
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t.Errorf("want chunkDescsOffset 0, got %d", loadedS1.chunkDescsOffset)
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}
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if loadedS1.headChunkPersisted {
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t.Error("headChunkPersisted is true")
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}
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} else {
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t.Errorf("couldn't find %v in loaded map", m1)
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}
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if loadedS3, ok := loadedSM.get(m3.Fingerprint()); ok {
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if !reflect.DeepEqual(loadedS3.metric, m3) {
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t.Errorf("want metric %v, got %v", m3, loadedS3.metric)
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}
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if loadedS3.head().chunk != nil {
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t.Error("head chunk not evicted")
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}
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if loadedS3.chunkDescsOffset != -1 {
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t.Errorf("want chunkDescsOffset -1, got %d", loadedS3.chunkDescsOffset)
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}
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if !loadedS3.headChunkPersisted {
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t.Error("headChunkPersisted is false")
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}
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} else {
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t.Errorf("couldn't find %v in loaded map", m1)
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}
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}
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func TestGetFingerprintsModifiedBefore(t *testing.T) {
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p, closer := newTestPersistence(t)
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defer closer.Close()
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m1 := clientmodel.Metric{"n1": "v1"}
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m2 := clientmodel.Metric{"n2": "v2"}
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m3 := clientmodel.Metric{"n1": "v2"}
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p.archiveMetric(1, m1, 2, 4)
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p.archiveMetric(2, m2, 1, 6)
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p.archiveMetric(3, m3, 5, 5)
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expectedFPs := map[clientmodel.Timestamp][]clientmodel.Fingerprint{
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0: {},
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1: {},
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2: {2},
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3: {1, 2},
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4: {1, 2},
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5: {1, 2},
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6: {1, 2, 3},
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}
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for ts, want := range expectedFPs {
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got, err := p.getFingerprintsModifiedBefore(ts)
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if err != nil {
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t.Fatal(err)
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}
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if !reflect.DeepEqual(want, got) {
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t.Errorf("timestamp: %v, want FPs %v, got %v", ts, want, got)
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}
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}
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unarchived, firstTime, err := p.unarchiveMetric(1)
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if err != nil {
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t.Fatal(err)
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}
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if !unarchived {
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t.Fatal("expected actual unarchival")
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}
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if firstTime != 2 {
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t.Errorf("expected first time 2, got %v", firstTime)
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}
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unarchived, firstTime, err = p.unarchiveMetric(1)
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if err != nil {
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t.Fatal(err)
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}
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if unarchived {
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t.Fatal("expected no unarchival")
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}
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expectedFPs = map[clientmodel.Timestamp][]clientmodel.Fingerprint{
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0: {},
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1: {},
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2: {2},
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3: {2},
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4: {2},
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5: {2},
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6: {2, 3},
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}
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for ts, want := range expectedFPs {
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got, err := p.getFingerprintsModifiedBefore(ts)
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if err != nil {
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t.Fatal(err)
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}
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if !reflect.DeepEqual(want, got) {
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t.Errorf("timestamp: %v, want FPs %v, got %v", ts, want, got)
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}
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}
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}
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func TestDropArchivedMetric(t *testing.T) {
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p, closer := newTestPersistence(t)
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defer closer.Close()
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m1 := clientmodel.Metric{"n1": "v1"}
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m2 := clientmodel.Metric{"n2": "v2"}
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p.archiveMetric(1, m1, 2, 4)
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p.archiveMetric(2, m2, 1, 6)
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p.indexMetric(1, m1)
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p.indexMetric(2, m2)
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p.waitForIndexing()
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outFPs, err := p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n1", Value: "v1"})
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if err != nil {
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t.Fatal(err)
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}
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want := clientmodel.Fingerprints{1}
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if !reflect.DeepEqual(outFPs, want) {
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t.Errorf("want %#v, got %#v", want, outFPs)
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}
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outFPs, err = p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n2", Value: "v2"})
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if err != nil {
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t.Fatal(err)
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}
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want = clientmodel.Fingerprints{2}
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if !reflect.DeepEqual(outFPs, want) {
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t.Errorf("want %#v, got %#v", want, outFPs)
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}
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if archived, _, _, err := p.hasArchivedMetric(1); err != nil || !archived {
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t.Error("want FP 1 archived")
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}
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if archived, _, _, err := p.hasArchivedMetric(2); err != nil || !archived {
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t.Error("want FP 2 archived")
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}
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if err != p.dropArchivedMetric(1) {
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t.Fatal(err)
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}
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if err != p.dropArchivedMetric(3) {
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// Dropping something that has not beet archived is not an error.
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t.Fatal(err)
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}
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p.waitForIndexing()
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outFPs, err = p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n1", Value: "v1"})
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if err != nil {
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t.Fatal(err)
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}
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want = nil
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if !reflect.DeepEqual(outFPs, want) {
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t.Errorf("want %#v, got %#v", want, outFPs)
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}
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outFPs, err = p.getFingerprintsForLabelPair(metric.LabelPair{Name: "n2", Value: "v2"})
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if err != nil {
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t.Fatal(err)
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}
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want = clientmodel.Fingerprints{2}
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if !reflect.DeepEqual(outFPs, want) {
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t.Errorf("want %#v, got %#v", want, outFPs)
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}
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if archived, _, _, err := p.hasArchivedMetric(1); err != nil || archived {
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t.Error("want FP 1 not archived")
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}
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if archived, _, _, err := p.hasArchivedMetric(2); err != nil || !archived {
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t.Error("want FP 2 archived")
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}
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}
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type incrementalBatch struct {
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fpToMetric index.FingerprintMetricMapping
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expectedLnToLvs index.LabelNameLabelValuesMapping
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expectedLpToFps index.LabelPairFingerprintsMapping
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}
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func TestIndexing(t *testing.T) {
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batches := []incrementalBatch{
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{
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fpToMetric: index.FingerprintMetricMapping{
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0: {
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clientmodel.MetricNameLabel: "metric_0",
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"label_1": "value_1",
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},
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1: {
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clientmodel.MetricNameLabel: "metric_0",
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"label_2": "value_2",
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"label_3": "value_3",
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},
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2: {
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clientmodel.MetricNameLabel: "metric_1",
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"label_1": "value_2",
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},
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},
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expectedLnToLvs: index.LabelNameLabelValuesMapping{
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clientmodel.MetricNameLabel: codable.LabelValueSet{
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"metric_0": struct{}{},
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"metric_1": struct{}{},
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},
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"label_1": codable.LabelValueSet{
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"value_1": struct{}{},
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"value_2": struct{}{},
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},
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"label_2": codable.LabelValueSet{
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"value_2": struct{}{},
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},
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"label_3": codable.LabelValueSet{
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"value_3": struct{}{},
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},
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},
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expectedLpToFps: index.LabelPairFingerprintsMapping{
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metric.LabelPair{
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Name: clientmodel.MetricNameLabel,
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Value: "metric_0",
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}: codable.FingerprintSet{0: struct{}{}, 1: struct{}{}},
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metric.LabelPair{
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Name: clientmodel.MetricNameLabel,
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Value: "metric_1",
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}: codable.FingerprintSet{2: struct{}{}},
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metric.LabelPair{
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Name: "label_1",
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Value: "value_1",
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}: codable.FingerprintSet{0: struct{}{}},
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metric.LabelPair{
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Name: "label_1",
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Value: "value_2",
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}: codable.FingerprintSet{2: struct{}{}},
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metric.LabelPair{
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Name: "label_2",
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Value: "value_2",
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}: codable.FingerprintSet{1: struct{}{}},
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metric.LabelPair{
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Name: "label_3",
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Value: "value_3",
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}: codable.FingerprintSet{1: struct{}{}},
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},
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}, {
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fpToMetric: index.FingerprintMetricMapping{
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3: {
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clientmodel.MetricNameLabel: "metric_0",
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"label_1": "value_3",
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},
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4: {
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clientmodel.MetricNameLabel: "metric_2",
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"label_2": "value_2",
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"label_3": "value_1",
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},
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5: {
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clientmodel.MetricNameLabel: "metric_1",
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"label_1": "value_3",
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},
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},
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expectedLnToLvs: index.LabelNameLabelValuesMapping{
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clientmodel.MetricNameLabel: codable.LabelValueSet{
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"metric_0": struct{}{},
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"metric_1": struct{}{},
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"metric_2": struct{}{},
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},
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"label_1": codable.LabelValueSet{
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"value_1": struct{}{},
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"value_2": struct{}{},
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"value_3": struct{}{},
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},
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"label_2": codable.LabelValueSet{
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"value_2": struct{}{},
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},
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"label_3": codable.LabelValueSet{
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"value_1": struct{}{},
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"value_3": struct{}{},
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},
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},
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expectedLpToFps: index.LabelPairFingerprintsMapping{
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metric.LabelPair{
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Name: clientmodel.MetricNameLabel,
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Value: "metric_0",
|
|
}: codable.FingerprintSet{0: struct{}{}, 1: struct{}{}, 3: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: clientmodel.MetricNameLabel,
|
|
Value: "metric_1",
|
|
}: codable.FingerprintSet{2: struct{}{}, 5: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: clientmodel.MetricNameLabel,
|
|
Value: "metric_2",
|
|
}: codable.FingerprintSet{4: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: "label_1",
|
|
Value: "value_1",
|
|
}: codable.FingerprintSet{0: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: "label_1",
|
|
Value: "value_2",
|
|
}: codable.FingerprintSet{2: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: "label_1",
|
|
Value: "value_3",
|
|
}: codable.FingerprintSet{3: struct{}{}, 5: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: "label_2",
|
|
Value: "value_2",
|
|
}: codable.FingerprintSet{1: struct{}{}, 4: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: "label_3",
|
|
Value: "value_1",
|
|
}: codable.FingerprintSet{4: struct{}{}},
|
|
metric.LabelPair{
|
|
Name: "label_3",
|
|
Value: "value_3",
|
|
}: codable.FingerprintSet{1: struct{}{}},
|
|
},
|
|
},
|
|
}
|
|
|
|
p, closer := newTestPersistence(t)
|
|
defer closer.Close()
|
|
|
|
indexedFpsToMetrics := index.FingerprintMetricMapping{}
|
|
for i, b := range batches {
|
|
for fp, m := range b.fpToMetric {
|
|
p.indexMetric(fp, m)
|
|
if err := p.archiveMetric(fp, m, 1, 2); err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
indexedFpsToMetrics[fp] = m
|
|
}
|
|
verifyIndexedState(i, t, b, indexedFpsToMetrics, p)
|
|
}
|
|
|
|
for i := len(batches) - 1; i >= 0; i-- {
|
|
b := batches[i]
|
|
verifyIndexedState(i, t, batches[i], indexedFpsToMetrics, p)
|
|
for fp, m := range b.fpToMetric {
|
|
p.unindexMetric(fp, m)
|
|
unarchived, firstTime, err := p.unarchiveMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !unarchived {
|
|
t.Errorf("%d. metric not unarchived", i)
|
|
}
|
|
if firstTime != 1 {
|
|
t.Errorf("%d. expected firstTime=1, got %v", i, firstTime)
|
|
}
|
|
delete(indexedFpsToMetrics, fp)
|
|
}
|
|
}
|
|
}
|
|
|
|
func verifyIndexedState(i int, t *testing.T, b incrementalBatch, indexedFpsToMetrics index.FingerprintMetricMapping, p *persistence) {
|
|
p.waitForIndexing()
|
|
for fp, m := range indexedFpsToMetrics {
|
|
// Compare archived metrics with input metrics.
|
|
mOut, err := p.getArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !mOut.Equal(m) {
|
|
t.Errorf("%d. %v: Got: %s; want %s", i, fp, mOut, m)
|
|
}
|
|
|
|
// Check that archived metrics are in membership index.
|
|
has, first, last, err := p.hasArchivedMetric(fp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
if !has {
|
|
t.Errorf("%d. fingerprint %v not found", i, fp)
|
|
}
|
|
if first != 1 || last != 2 {
|
|
t.Errorf(
|
|
"%d. %v: Got first: %d, last %d; want first: %d, last %d",
|
|
i, fp, first, last, 1, 2,
|
|
)
|
|
}
|
|
}
|
|
|
|
// Compare label name -> label values mappings.
|
|
for ln, lvs := range b.expectedLnToLvs {
|
|
outLvs, err := p.getLabelValuesForLabelName(ln)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
|
|
outSet := codable.LabelValueSet{}
|
|
for _, lv := range outLvs {
|
|
outSet[lv] = struct{}{}
|
|
}
|
|
|
|
if !reflect.DeepEqual(lvs, outSet) {
|
|
t.Errorf("%d. label values don't match. Got: %v; want %v", i, outSet, lvs)
|
|
}
|
|
}
|
|
|
|
// Compare label pair -> fingerprints mappings.
|
|
for lp, fps := range b.expectedLpToFps {
|
|
outFPs, err := p.getFingerprintsForLabelPair(lp)
|
|
if err != nil {
|
|
t.Fatal(err)
|
|
}
|
|
|
|
outSet := codable.FingerprintSet{}
|
|
for _, fp := range outFPs {
|
|
outSet[fp] = struct{}{}
|
|
}
|
|
|
|
if !reflect.DeepEqual(fps, outSet) {
|
|
t.Errorf("%d. %v: fingerprints don't match. Got: %v; want %v", i, lp, outSet, fps)
|
|
}
|
|
}
|
|
}
|