// 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"
	"github.com/prometheus/prometheus/tsdb/index"
	"io"
	"io/ioutil"
	"math"
	"os"
	"path/filepath"
	"runtime"
	"runtime/pprof"
	"sort"
	"strconv"
	"strings"
	"sync"
	"text/tabwriter"
	"time"

	"github.com/alecthomas/units"
	"github.com/go-kit/log"
	"github.com/pkg/errors"

	"github.com/prometheus/prometheus/pkg/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 := ioutil.TempDir("", "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, 0777); 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    *uint64
	}

	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 uint64
			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: %v", err)
	}
	if err := pprof.StartCPUProfile(b.cpuprof); err != nil {
		return fmt.Errorf("bench: could not start CPU profile: %v", 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: %v", 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: %v", 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: %v", 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: %v", 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: %v", 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: %v", 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.Labels, 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]})
		}
		// Order of the k/v labels matters, don't assume we'll always receive them already sorted.
		sort.Sort(m)
		h := m.Hash()
		if _, ok := hashes[h]; ok {
			continue
		}
		mets = append(mets, m)
		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) 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
	}
	lbls := labels.Labels{}
	chks := []chunks.Meta{}
	for p.Next() {
		if err = ir.Series(p.At(), &lbls, &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)
		for _, lbl := range lbls {
			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)

	return analyzeCompaction(block, ir)
}

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
	for postingsr.Next() {
		var lbsl = labels.Labels{}
		var chks []chunks.Meta
		if err := indexr.Series(postingsr.At(), &lbsl, &chks); err != nil {
			return err
		}

		for _, chk := range chks {
			// Load the actual data of the chunk.
			chk, err := chunkr.Chunk(chk.Ref)
			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) (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()

	ss := q.Select(false, nil, labels.MustNewMatcher(labels.MatchRegexp, "", ".*"))

	for ss.Next() {
		series := ss.At()
		lbs := series.Labels()
		it := series.Iterator()
		for it.Next() {
			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 string, 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, 0777); err != nil {
		return checkErr(errors.Wrap(err, "create output dir"))
	}

	return checkErr(backfill(5000, inputFile.Bytes(), outputDir, humanReadable, quiet, maxBlockDuration))
}