prometheus/cmd/promtool/tsdb.go
Amin Borjian 90d6873c7f promtool: add support of selecting timeseries for TSDB dump
Dumping without any limit on the data being dumped will generate
a large amount of data. Also, sometimes it is necessary to dump
only a part of the data in order to change or transfer it.

This change allows to specify a part of the data to dump and
by default works same as before. (no public API change)

Signed-off-by: Amin Borjian <borjianamin98@outlook.com>
2023-01-20 15:46:23 +03:30

692 lines
16 KiB
Go

// Copyright 2017 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 main
import (
"bufio"
"context"
"fmt"
"io"
"math"
"os"
"path/filepath"
"runtime"
"runtime/pprof"
"sort"
"strconv"
"strings"
"sync"
"text/tabwriter"
"time"
"github.com/prometheus/prometheus/promql/parser"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/tsdb/chunkenc"
"github.com/prometheus/prometheus/tsdb/index"
"github.com/alecthomas/units"
"github.com/go-kit/log"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/tsdb"
"github.com/prometheus/prometheus/tsdb/chunks"
tsdb_errors "github.com/prometheus/prometheus/tsdb/errors"
"github.com/prometheus/prometheus/tsdb/fileutil"
)
const timeDelta = 30000
type writeBenchmark struct {
outPath string
samplesFile string
cleanup bool
numMetrics int
storage *tsdb.DB
cpuprof *os.File
memprof *os.File
blockprof *os.File
mtxprof *os.File
logger log.Logger
}
func benchmarkWrite(outPath, samplesFile string, numMetrics, numScrapes int) error {
b := &writeBenchmark{
outPath: outPath,
samplesFile: samplesFile,
numMetrics: numMetrics,
logger: log.NewLogfmtLogger(log.NewSyncWriter(os.Stderr)),
}
if b.outPath == "" {
dir, err := os.MkdirTemp("", "tsdb_bench")
if err != nil {
return err
}
b.outPath = dir
b.cleanup = true
}
if err := os.RemoveAll(b.outPath); err != nil {
return err
}
if err := os.MkdirAll(b.outPath, 0o777); err != nil {
return err
}
dir := filepath.Join(b.outPath, "storage")
l := log.With(b.logger, "ts", log.DefaultTimestampUTC, "caller", log.DefaultCaller)
st, err := tsdb.Open(dir, l, nil, &tsdb.Options{
RetentionDuration: int64(15 * 24 * time.Hour / time.Millisecond),
MinBlockDuration: int64(2 * time.Hour / time.Millisecond),
}, tsdb.NewDBStats())
if err != nil {
return err
}
st.DisableCompactions()
b.storage = st
var lbs []labels.Labels
if _, err = measureTime("readData", func() error {
f, err := os.Open(b.samplesFile)
if err != nil {
return err
}
defer f.Close()
lbs, err = readPrometheusLabels(f, b.numMetrics)
if err != nil {
return err
}
return nil
}); err != nil {
return err
}
var total uint64
dur, err := measureTime("ingestScrapes", func() error {
if err := b.startProfiling(); err != nil {
return err
}
total, err = b.ingestScrapes(lbs, numScrapes)
if err != nil {
return err
}
return nil
})
if err != nil {
return err
}
fmt.Println(" > total samples:", total)
fmt.Println(" > samples/sec:", float64(total)/dur.Seconds())
if _, err = measureTime("stopStorage", func() error {
if err := b.storage.Close(); err != nil {
return err
}
return b.stopProfiling()
}); err != nil {
return err
}
return nil
}
func (b *writeBenchmark) ingestScrapes(lbls []labels.Labels, scrapeCount int) (uint64, error) {
var mu sync.Mutex
var total uint64
for i := 0; i < scrapeCount; i += 100 {
var wg sync.WaitGroup
lbls := lbls
for len(lbls) > 0 {
l := 1000
if len(lbls) < 1000 {
l = len(lbls)
}
batch := lbls[:l]
lbls = lbls[l:]
wg.Add(1)
go func() {
n, err := b.ingestScrapesShard(batch, 100, int64(timeDelta*i))
if err != nil {
// exitWithError(err)
fmt.Println(" err", err)
}
mu.Lock()
total += n
mu.Unlock()
wg.Done()
}()
}
wg.Wait()
}
fmt.Println("ingestion completed")
return total, nil
}
func (b *writeBenchmark) ingestScrapesShard(lbls []labels.Labels, scrapeCount int, baset int64) (uint64, error) {
ts := baset
type sample struct {
labels labels.Labels
value int64
ref *storage.SeriesRef
}
scrape := make([]*sample, 0, len(lbls))
for _, m := range lbls {
scrape = append(scrape, &sample{
labels: m,
value: 123456789,
})
}
total := uint64(0)
for i := 0; i < scrapeCount; i++ {
app := b.storage.Appender(context.TODO())
ts += timeDelta
for _, s := range scrape {
s.value += 1000
var ref storage.SeriesRef
if s.ref != nil {
ref = *s.ref
}
ref, err := app.Append(ref, s.labels, ts, float64(s.value))
if err != nil {
panic(err)
}
if s.ref == nil {
s.ref = &ref
}
total++
}
if err := app.Commit(); err != nil {
return total, err
}
}
return total, nil
}
func (b *writeBenchmark) startProfiling() error {
var err error
// Start CPU profiling.
b.cpuprof, err = os.Create(filepath.Join(b.outPath, "cpu.prof"))
if err != nil {
return fmt.Errorf("bench: could not create cpu profile: %w", err)
}
if err := pprof.StartCPUProfile(b.cpuprof); err != nil {
return fmt.Errorf("bench: could not start CPU profile: %w", err)
}
// Start memory profiling.
b.memprof, err = os.Create(filepath.Join(b.outPath, "mem.prof"))
if err != nil {
return fmt.Errorf("bench: could not create memory profile: %w", err)
}
runtime.MemProfileRate = 64 * 1024
// Start fatal profiling.
b.blockprof, err = os.Create(filepath.Join(b.outPath, "block.prof"))
if err != nil {
return fmt.Errorf("bench: could not create block profile: %w", err)
}
runtime.SetBlockProfileRate(20)
b.mtxprof, err = os.Create(filepath.Join(b.outPath, "mutex.prof"))
if err != nil {
return fmt.Errorf("bench: could not create mutex profile: %w", err)
}
runtime.SetMutexProfileFraction(20)
return nil
}
func (b *writeBenchmark) stopProfiling() error {
if b.cpuprof != nil {
pprof.StopCPUProfile()
b.cpuprof.Close()
b.cpuprof = nil
}
if b.memprof != nil {
if err := pprof.Lookup("heap").WriteTo(b.memprof, 0); err != nil {
return fmt.Errorf("error writing mem profile: %w", err)
}
b.memprof.Close()
b.memprof = nil
}
if b.blockprof != nil {
if err := pprof.Lookup("block").WriteTo(b.blockprof, 0); err != nil {
return fmt.Errorf("error writing block profile: %w", err)
}
b.blockprof.Close()
b.blockprof = nil
runtime.SetBlockProfileRate(0)
}
if b.mtxprof != nil {
if err := pprof.Lookup("mutex").WriteTo(b.mtxprof, 0); err != nil {
return fmt.Errorf("error writing mutex profile: %w", err)
}
b.mtxprof.Close()
b.mtxprof = nil
runtime.SetMutexProfileFraction(0)
}
return nil
}
func measureTime(stage string, f func() error) (time.Duration, error) {
fmt.Printf(">> start stage=%s\n", stage)
start := time.Now()
if err := f(); err != nil {
return 0, err
}
fmt.Printf(">> completed stage=%s duration=%s\n", stage, time.Since(start))
return time.Since(start), nil
}
func readPrometheusLabels(r io.Reader, n int) ([]labels.Labels, error) {
scanner := bufio.NewScanner(r)
var mets []labels.Labels
hashes := map[uint64]struct{}{}
i := 0
for scanner.Scan() && i < n {
m := make([]labels.Label, 0, 10)
r := strings.NewReplacer("\"", "", "{", "", "}", "")
s := r.Replace(scanner.Text())
labelChunks := strings.Split(s, ",")
for _, labelChunk := range labelChunks {
split := strings.Split(labelChunk, ":")
m = append(m, labels.Label{Name: split[0], Value: split[1]})
}
ml := labels.New(m...) // This sorts by name - order of the k/v labels matters, don't assume we'll always receive them already sorted.
h := ml.Hash()
if _, ok := hashes[h]; ok {
continue
}
mets = append(mets, ml)
hashes[h] = struct{}{}
i++
}
return mets, nil
}
func listBlocks(path string, humanReadable bool) error {
db, err := tsdb.OpenDBReadOnly(path, nil)
if err != nil {
return err
}
defer func() {
err = tsdb_errors.NewMulti(err, db.Close()).Err()
}()
blocks, err := db.Blocks()
if err != nil {
return err
}
printBlocks(blocks, true, humanReadable)
return nil
}
func printBlocks(blocks []tsdb.BlockReader, writeHeader, humanReadable bool) {
tw := tabwriter.NewWriter(os.Stdout, 13, 0, 2, ' ', 0)
defer tw.Flush()
if writeHeader {
fmt.Fprintln(tw, "BLOCK ULID\tMIN TIME\tMAX TIME\tDURATION\tNUM SAMPLES\tNUM CHUNKS\tNUM SERIES\tSIZE")
}
for _, b := range blocks {
meta := b.Meta()
fmt.Fprintf(tw,
"%v\t%v\t%v\t%v\t%v\t%v\t%v\t%v\n",
meta.ULID,
getFormatedTime(meta.MinTime, humanReadable),
getFormatedTime(meta.MaxTime, humanReadable),
time.Duration(meta.MaxTime-meta.MinTime)*time.Millisecond,
meta.Stats.NumSamples,
meta.Stats.NumChunks,
meta.Stats.NumSeries,
getFormatedBytes(b.Size(), humanReadable),
)
}
}
func getFormatedTime(timestamp int64, humanReadable bool) string {
if humanReadable {
return time.Unix(timestamp/1000, 0).UTC().String()
}
return strconv.FormatInt(timestamp, 10)
}
func getFormatedBytes(bytes int64, humanReadable bool) string {
if humanReadable {
return units.Base2Bytes(bytes).String()
}
return strconv.FormatInt(bytes, 10)
}
func openBlock(path, blockID string) (*tsdb.DBReadOnly, tsdb.BlockReader, error) {
db, err := tsdb.OpenDBReadOnly(path, nil)
if err != nil {
return nil, nil, err
}
blocks, err := db.Blocks()
if err != nil {
return nil, nil, err
}
var block tsdb.BlockReader
if blockID != "" {
for _, b := range blocks {
if b.Meta().ULID.String() == blockID {
block = b
break
}
}
} else if len(blocks) > 0 {
block = blocks[len(blocks)-1]
}
if block == nil {
return nil, nil, fmt.Errorf("block %s not found", blockID)
}
return db, block, nil
}
func analyzeBlock(path, blockID string, limit int, runExtended bool) error {
db, block, err := openBlock(path, blockID)
if err != nil {
return err
}
defer func() {
err = tsdb_errors.NewMulti(err, db.Close()).Err()
}()
meta := block.Meta()
fmt.Printf("Block ID: %s\n", meta.ULID)
// Presume 1ms resolution that Prometheus uses.
fmt.Printf("Duration: %s\n", (time.Duration(meta.MaxTime-meta.MinTime) * 1e6).String())
fmt.Printf("Series: %d\n", meta.Stats.NumSeries)
ir, err := block.Index()
if err != nil {
return err
}
defer ir.Close()
allLabelNames, err := ir.LabelNames()
if err != nil {
return err
}
fmt.Printf("Label names: %d\n", len(allLabelNames))
type postingInfo struct {
key string
metric uint64
}
postingInfos := []postingInfo{}
printInfo := func(postingInfos []postingInfo) {
sort.Slice(postingInfos, func(i, j int) bool { return postingInfos[i].metric > postingInfos[j].metric })
for i, pc := range postingInfos {
if i >= limit {
break
}
fmt.Printf("%d %s\n", pc.metric, pc.key)
}
}
labelsUncovered := map[string]uint64{}
labelpairsUncovered := map[string]uint64{}
labelpairsCount := map[string]uint64{}
entries := 0
p, err := ir.Postings("", "") // The special all key.
if err != nil {
return err
}
chks := []chunks.Meta{}
builder := labels.ScratchBuilder{}
for p.Next() {
if err = ir.Series(p.At(), &builder, &chks); err != nil {
return err
}
// Amount of the block time range not covered by this series.
uncovered := uint64(meta.MaxTime-meta.MinTime) - uint64(chks[len(chks)-1].MaxTime-chks[0].MinTime)
builder.Labels().Range(func(lbl labels.Label) {
key := lbl.Name + "=" + lbl.Value
labelsUncovered[lbl.Name] += uncovered
labelpairsUncovered[key] += uncovered
labelpairsCount[key]++
entries++
})
}
if p.Err() != nil {
return p.Err()
}
fmt.Printf("Postings (unique label pairs): %d\n", len(labelpairsUncovered))
fmt.Printf("Postings entries (total label pairs): %d\n", entries)
postingInfos = postingInfos[:0]
for k, m := range labelpairsUncovered {
postingInfos = append(postingInfos, postingInfo{k, uint64(float64(m) / float64(meta.MaxTime-meta.MinTime))})
}
fmt.Printf("\nLabel pairs most involved in churning:\n")
printInfo(postingInfos)
postingInfos = postingInfos[:0]
for k, m := range labelsUncovered {
postingInfos = append(postingInfos, postingInfo{k, uint64(float64(m) / float64(meta.MaxTime-meta.MinTime))})
}
fmt.Printf("\nLabel names most involved in churning:\n")
printInfo(postingInfos)
postingInfos = postingInfos[:0]
for k, m := range labelpairsCount {
postingInfos = append(postingInfos, postingInfo{k, m})
}
fmt.Printf("\nMost common label pairs:\n")
printInfo(postingInfos)
postingInfos = postingInfos[:0]
for _, n := range allLabelNames {
values, err := ir.SortedLabelValues(n)
if err != nil {
return err
}
var cumulativeLength uint64
for _, str := range values {
cumulativeLength += uint64(len(str))
}
postingInfos = append(postingInfos, postingInfo{n, cumulativeLength})
}
fmt.Printf("\nLabel names with highest cumulative label value length:\n")
printInfo(postingInfos)
postingInfos = postingInfos[:0]
for _, n := range allLabelNames {
lv, err := ir.SortedLabelValues(n)
if err != nil {
return err
}
postingInfos = append(postingInfos, postingInfo{n, uint64(len(lv))})
}
fmt.Printf("\nHighest cardinality labels:\n")
printInfo(postingInfos)
postingInfos = postingInfos[:0]
lv, err := ir.SortedLabelValues("__name__")
if err != nil {
return err
}
for _, n := range lv {
postings, err := ir.Postings("__name__", n)
if err != nil {
return err
}
count := 0
for postings.Next() {
count++
}
if postings.Err() != nil {
return postings.Err()
}
postingInfos = append(postingInfos, postingInfo{n, uint64(count)})
}
fmt.Printf("\nHighest cardinality metric names:\n")
printInfo(postingInfos)
if runExtended {
return analyzeCompaction(block, ir)
}
return nil
}
func analyzeCompaction(block tsdb.BlockReader, indexr tsdb.IndexReader) (err error) {
postingsr, err := indexr.Postings(index.AllPostingsKey())
if err != nil {
return err
}
chunkr, err := block.Chunks()
if err != nil {
return err
}
defer func() {
err = tsdb_errors.NewMulti(err, chunkr.Close()).Err()
}()
const maxSamplesPerChunk = 120
nBuckets := 10
histogram := make([]int, nBuckets)
totalChunks := 0
var builder labels.ScratchBuilder
for postingsr.Next() {
var chks []chunks.Meta
if err := indexr.Series(postingsr.At(), &builder, &chks); err != nil {
return err
}
for _, chk := range chks {
// Load the actual data of the chunk.
chk, err := chunkr.Chunk(chk)
if err != nil {
return err
}
chunkSize := math.Min(float64(chk.NumSamples()), maxSamplesPerChunk)
// Calculate the bucket for the chunk and increment it in the histogram.
bucket := int(math.Ceil(float64(nBuckets)*chunkSize/maxSamplesPerChunk)) - 1
histogram[bucket]++
totalChunks++
}
}
fmt.Printf("\nCompaction analysis:\n")
fmt.Println("Fullness: Amount of samples in chunks (100% is 120 samples)")
// Normalize absolute counts to percentages and print them out.
for bucket, count := range histogram {
percentage := 100.0 * count / totalChunks
fmt.Printf("%7d%%: ", (bucket+1)*10)
for j := 0; j < percentage; j++ {
fmt.Printf("#")
}
fmt.Println()
}
return nil
}
func dumpSamples(path string, mint, maxt int64, match string) (err error) {
db, err := tsdb.OpenDBReadOnly(path, nil)
if err != nil {
return err
}
defer func() {
err = tsdb_errors.NewMulti(err, db.Close()).Err()
}()
q, err := db.Querier(context.TODO(), mint, maxt)
if err != nil {
return err
}
defer q.Close()
matchers, err := parser.ParseMetricSelector(match)
if err != nil {
return err
}
ss := q.Select(false, nil, matchers...)
for ss.Next() {
series := ss.At()
lbs := series.Labels()
it := series.Iterator(nil)
for it.Next() == chunkenc.ValFloat {
ts, val := it.At()
fmt.Printf("%s %g %d\n", lbs, val, ts)
}
if it.Err() != nil {
return ss.Err()
}
}
if ws := ss.Warnings(); len(ws) > 0 {
return tsdb_errors.NewMulti(ws...).Err()
}
if ss.Err() != nil {
return ss.Err()
}
return nil
}
func checkErr(err error) int {
if err != nil {
fmt.Fprintln(os.Stderr, err)
return 1
}
return 0
}
func backfillOpenMetrics(path, outputDir string, humanReadable, quiet bool, maxBlockDuration time.Duration) int {
inputFile, err := fileutil.OpenMmapFile(path)
if err != nil {
return checkErr(err)
}
defer inputFile.Close()
if err := os.MkdirAll(outputDir, 0o777); err != nil {
return checkErr(fmt.Errorf("create output dir: %w", err))
}
return checkErr(backfill(5000, inputFile.Bytes(), outputDir, humanReadable, quiet, maxBlockDuration))
}