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batch.go
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package storage
import (
"context"
"sort"
"time"
"github.com/go-kit/log/level"
"github.com/pkg/errors"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/client_golang/prometheus/promauto"
"github.com/prometheus/common/model"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/promql"
"github.com/grafana/loki/v3/pkg/chunkenc"
"github.com/grafana/loki/v3/pkg/iter"
"github.com/grafana/loki/v3/pkg/logproto"
"github.com/grafana/loki/v3/pkg/logql/log"
"github.com/grafana/loki/v3/pkg/logql/syntax"
"github.com/grafana/loki/v3/pkg/logqlmodel/stats"
"github.com/grafana/loki/v3/pkg/querier/astmapper"
"github.com/grafana/loki/v3/pkg/storage/chunk"
"github.com/grafana/loki/v3/pkg/storage/chunk/fetcher"
"github.com/grafana/loki/v3/pkg/storage/config"
"github.com/grafana/loki/v3/pkg/util/constants"
util_log "github.com/grafana/loki/v3/pkg/util/log"
)
type ChunkMetrics struct {
refs *prometheus.CounterVec
refsBypassed prometheus.Counter
series *prometheus.CounterVec
chunks *prometheus.CounterVec
batches *prometheus.HistogramVec
}
const (
statusDiscarded = "discarded"
statusMatched = "matched"
)
func NewChunkMetrics(r prometheus.Registerer, maxBatchSize int) *ChunkMetrics {
buckets := 5
if maxBatchSize < buckets {
maxBatchSize = buckets
}
return &ChunkMetrics{
refs: promauto.With(r).NewCounterVec(prometheus.CounterOpts{
Namespace: constants.Loki,
Subsystem: "index",
Name: "chunk_refs_total",
Help: "Number of chunks refs downloaded, partitioned by whether they intersect the query bounds.",
}, []string{"status"}),
refsBypassed: promauto.With(r).NewCounter(prometheus.CounterOpts{
Namespace: constants.Loki,
Subsystem: "store",
Name: "chunk_ref_lookups_bypassed_total",
Help: "Number of chunk refs that were bypassed due to store overrides: computed during planning to avoid lookups",
}),
series: promauto.With(r).NewCounterVec(prometheus.CounterOpts{
Namespace: constants.Loki,
Subsystem: "store",
Name: "series_total",
Help: "Number of series referenced by a query, partitioned by whether they satisfy matchers.",
}, []string{"status"}),
chunks: promauto.With(r).NewCounterVec(prometheus.CounterOpts{
Namespace: constants.Loki,
Subsystem: "store",
Name: "chunks_downloaded_total",
Help: "Number of chunks referenced or downloaded, partitioned by if they satisfy matchers.",
}, []string{"status"}),
batches: promauto.With(r).NewHistogramVec(prometheus.HistogramOpts{
Namespace: constants.Loki,
Subsystem: "store",
Name: "chunks_per_batch",
Help: "The chunk batch size, partitioned by if they satisfy matchers.",
// split buckets evenly across 0->maxBatchSize
Buckets: prometheus.LinearBuckets(0, float64(maxBatchSize/buckets), buckets+1), // increment buckets by one to ensure upper bound bucket exists.
}, []string{"status"}),
}
}
// batchChunkIterator iterates through chunks by batch of `batchSize`.
// Since chunks can overlap across batches for each iteration the iterator will keep all overlapping
// chunks with the next chunk from the next batch and added it to the next iteration. In this case the boundaries of the batch
// is reduced to non-overlapping chunks boundaries.
type batchChunkIterator struct {
schemas config.SchemaConfig
chunks lazyChunks
batchSize int
lastOverlapping []*LazyChunk
metrics *ChunkMetrics
matchers []*labels.Matcher
chunkFilterer chunk.Filterer
begun bool
ctx context.Context
start, end time.Time
direction logproto.Direction
next chan *chunkBatch
}
// newBatchChunkIterator creates a new batch iterator with the given batchSize.
func newBatchChunkIterator(
ctx context.Context,
s config.SchemaConfig,
chunks []*LazyChunk,
batchSize int,
direction logproto.Direction,
start, end time.Time,
metrics *ChunkMetrics,
matchers []*labels.Matcher,
chunkFilterer chunk.Filterer,
) *batchChunkIterator {
// __name__ is not something we filter by because it's a constant in loki
// and only used for upstream compatibility; therefore remove it.
// The same applies to the sharding label which is injected by the cortex storage code.
matchers = removeMatchersByName(matchers, labels.MetricName, astmapper.ShardLabel)
res := &batchChunkIterator{
batchSize: batchSize,
schemas: s,
metrics: metrics,
matchers: matchers,
start: start,
end: end,
direction: direction,
ctx: ctx,
chunks: lazyChunks{direction: direction, chunks: chunks},
next: make(chan *chunkBatch),
chunkFilterer: chunkFilterer,
}
sort.Sort(res.chunks)
return res
}
// Start is idempotent and will begin the processing thread which seeds the iterator data.
func (it *batchChunkIterator) Start() {
if !it.begun {
it.begun = true
go it.loop()
}
}
func (it *batchChunkIterator) loop() {
for {
if it.chunks.Len() == 0 {
close(it.next)
return
}
select {
case <-it.ctx.Done():
close(it.next)
return
case it.next <- it.nextBatch():
}
}
}
func (it *batchChunkIterator) Next() *chunkBatch {
it.Start() // Ensure the iterator has started.
return <-it.next
}
func (it *batchChunkIterator) nextBatch() (res *chunkBatch) {
defer func() {
if p := recover(); p != nil {
level.Error(util_log.Logger).Log("msg", "panic while fetching chunks", "panic", p)
res = &chunkBatch{
err: errors.Errorf("panic while fecthing chunks %+v", p),
}
}
}()
// the first chunk of the batch
headChunk := it.chunks.Peek()
from, through := it.start, it.end
batch := make([]*LazyChunk, 0, it.batchSize+len(it.lastOverlapping))
var nextChunk *LazyChunk
var includesOverlap bool
for it.chunks.Len() > 0 {
// pop the next batch of chunks and append/prepend previous overlapping chunks
// so we can merge/de-dupe overlapping entries.
if !includesOverlap && it.direction == logproto.FORWARD {
batch = append(batch, it.lastOverlapping...)
}
batch = append(batch, it.chunks.pop(it.batchSize)...)
if !includesOverlap && it.direction == logproto.BACKWARD {
batch = append(batch, it.lastOverlapping...)
}
includesOverlap = true
if it.chunks.Len() > 0 {
nextChunk = it.chunks.Peek()
// we max out our iterator boundaries to the next chunks in the queue
// so that overlapping chunks are together
if it.direction == logproto.BACKWARD {
from = time.Unix(0, nextChunk.Chunk.Through.UnixNano())
// we have to reverse the inclusivity of the chunk iterator from
// [from, through) to (from, through] for backward queries, except when
// the batch's `from` is equal to the query's Start. This can be achieved
// by shifting `from` by one nanosecond.
if !from.Equal(it.start) {
from = from.Add(time.Nanosecond)
}
} else {
through = time.Unix(0, nextChunk.Chunk.From.UnixNano())
}
// we save all overlapping chunks as they are also needed in the next batch to properly order entries.
// If we have chunks like below:
// ┌──────────────┐
// │ # 47 │
// └──────────────┘
// ┌──────────────────────────┐
// │ # 48 |
// └──────────────────────────┘
// ┌──────────────┐
// │ # 49 │
// └──────────────┘
// ┌────────────────────┐
// │ # 50 │
// └────────────────────┘
//
// And nextChunk is # 49, we need to keep references to #47 and #48 as they won't be
// iterated over completely (we're clipping through to #49's from) and then add them to the next batch.
}
if it.direction == logproto.BACKWARD {
through = time.Unix(0, headChunk.Chunk.Through.UnixNano())
if through.After(it.end) {
through = it.end
}
// we have to reverse the inclusivity of the chunk iterator from
// [from, through) to (from, through] for backward queries, except when
// the batch's `through` is equal to the query's End. This can be achieved
// by shifting `through` by one nanosecond.
if !through.Equal(it.end) {
through = through.Add(time.Nanosecond)
}
} else {
from = time.Unix(0, headChunk.Chunk.From.UnixNano())
// if the start of the batch is equal to the end of the query, since the end is not inclusive we can discard that batch.
if from.Equal(it.end) {
if it.end != it.start {
return nil
}
// unless end and start are equal in which case start and end are both inclusive.
from = it.end
}
// when clipping the from it should never be before the start.
// Doing so would include entries not requested.
if from.Before(it.start) {
from = it.start
}
}
// it's possible that the current batch and the next batch are fully overlapping in which case
// we should keep adding more items until the batch boundaries difference is positive.
if through.Sub(from) > 0 {
break
}
}
// If every chunk overlaps and we exhaust fetching chunks before ever finding a non overlapping chunk
// in this case it will be possible to have a through value which is older or equal to our from value
// If that happens we reset the bounds according to the iteration direction
if through.Sub(from) <= 0 {
if it.direction == logproto.BACKWARD {
from = it.start
} else {
through = it.end
}
}
if it.chunks.Len() > 0 {
it.lastOverlapping = it.lastOverlapping[:0]
for _, c := range batch {
if c.IsOverlapping(nextChunk, it.direction) {
it.lastOverlapping = append(it.lastOverlapping, c)
}
}
}
// download chunk for this batch.
chksBySeries, err := fetchChunkBySeries(it.ctx, it.schemas, it.metrics, batch, it.matchers, it.chunkFilterer)
if err != nil {
return &chunkBatch{err: err}
}
return &chunkBatch{
chunksBySeries: chksBySeries,
err: err,
from: from,
through: through,
nextChunk: nextChunk,
}
}
type chunkBatch struct {
chunksBySeries map[model.Fingerprint][][]*LazyChunk
err error
from, through time.Time
nextChunk *LazyChunk
}
type logBatchIterator struct {
*batchChunkIterator
curr iter.EntryIterator
err error
ctx context.Context
cancel context.CancelFunc
pipeline syntax.Pipeline
}
func newLogBatchIterator(
ctx context.Context,
schemas config.SchemaConfig,
metrics *ChunkMetrics,
chunks []*LazyChunk,
batchSize int,
matchers []*labels.Matcher,
pipeline syntax.Pipeline,
direction logproto.Direction,
start, end time.Time,
chunkFilterer chunk.Filterer,
) (iter.EntryIterator, error) {
ctx, cancel := context.WithCancel(ctx)
return &logBatchIterator{
pipeline: pipeline,
ctx: ctx,
cancel: cancel,
batchChunkIterator: newBatchChunkIterator(ctx, schemas, chunks, batchSize, direction, start, end, metrics, matchers, chunkFilterer),
}, nil
}
func (it *logBatchIterator) Labels() string {
return it.curr.Labels()
}
func (it *logBatchIterator) StreamHash() uint64 {
return it.curr.StreamHash()
}
func (it *logBatchIterator) Err() error {
if it.err != nil {
return it.err
}
if it.curr != nil && it.curr.Err() != nil {
return it.curr.Err()
}
if it.ctx.Err() != nil {
return it.ctx.Err()
}
return nil
}
func (it *logBatchIterator) Close() error {
it.cancel()
if it.curr != nil {
return it.curr.Close()
}
return nil
}
func (it *logBatchIterator) At() logproto.Entry {
return it.curr.At()
}
func (it *logBatchIterator) Next() bool {
// for loop to avoid recursion
for {
if it.curr != nil && it.curr.Next() {
return true
}
// close previous iterator
if it.curr != nil {
it.err = it.curr.Close()
}
next := it.batchChunkIterator.Next()
if next == nil {
return false
}
if next.err != nil {
it.err = next.err
return false
}
var err error
it.curr, err = it.newChunksIterator(next)
if err != nil {
it.err = err
return false
}
}
}
// newChunksIterator creates an iterator over a set of lazychunks.
func (it *logBatchIterator) newChunksIterator(b *chunkBatch) (iter.EntryIterator, error) {
iters, err := it.buildIterators(b.chunksBySeries, b.from, b.through, b.nextChunk)
if err != nil {
return nil, err
}
if len(iters) == 1 {
return iters[0], nil
}
return iter.NewSortEntryIterator(iters, it.direction), nil
}
func (it *logBatchIterator) buildIterators(chks map[model.Fingerprint][][]*LazyChunk, from, through time.Time, nextChunk *LazyChunk) ([]iter.EntryIterator, error) {
result := make([]iter.EntryIterator, 0, len(chks))
for _, chunks := range chks {
if len(chunks) != 0 && len(chunks[0]) != 0 {
streamPipeline := it.pipeline.ForStream(labels.NewBuilder(chunks[0][0].Chunk.Metric).Del(labels.MetricName).Labels())
iterator, err := it.buildMergeIterator(chunks, from, through, streamPipeline, nextChunk)
if err != nil {
return nil, err
}
result = append(result, iterator)
}
}
return result, nil
}
func (it *logBatchIterator) buildMergeIterator(chks [][]*LazyChunk, from, through time.Time, streamPipeline log.StreamPipeline, nextChunk *LazyChunk) (iter.EntryIterator, error) {
result := make([]iter.EntryIterator, 0, len(chks))
for i := range chks {
iterators := make([]iter.EntryIterator, 0, len(chks[i]))
for j := range chks[i] {
if !chks[i][j].IsValid {
continue
}
iterator, err := chks[i][j].Iterator(it.ctx, from, through, it.direction, streamPipeline, nextChunk)
if err != nil {
return nil, err
}
iterators = append(iterators, iterator)
}
if it.direction == logproto.BACKWARD {
for i, j := 0, len(iterators)-1; i < j; i, j = i+1, j-1 {
iterators[i], iterators[j] = iterators[j], iterators[i]
}
}
result = append(result, iter.NewNonOverlappingIterator(iterators))
}
return iter.NewMergeEntryIterator(it.ctx, result, it.direction), nil
}
type sampleBatchIterator struct {
*batchChunkIterator
curr iter.SampleIterator
err error
ctx context.Context
cancel context.CancelFunc
extractor syntax.SampleExtractor
}
func newSampleBatchIterator(
ctx context.Context,
schemas config.SchemaConfig,
metrics *ChunkMetrics,
chunks []*LazyChunk,
batchSize int,
matchers []*labels.Matcher,
extractor syntax.SampleExtractor,
start, end time.Time,
chunkFilterer chunk.Filterer,
) (iter.SampleIterator, error) {
ctx, cancel := context.WithCancel(ctx)
return &sampleBatchIterator{
extractor: extractor,
ctx: ctx,
cancel: cancel,
batchChunkIterator: newBatchChunkIterator(ctx, schemas, chunks, batchSize, logproto.FORWARD, start, end, metrics, matchers, chunkFilterer),
}, nil
}
func (it *sampleBatchIterator) Labels() string {
return it.curr.Labels()
}
func (it *sampleBatchIterator) StreamHash() uint64 {
return it.curr.StreamHash()
}
func (it *sampleBatchIterator) Err() error {
if it.err != nil {
return it.err
}
if it.curr != nil && it.curr.Err() != nil {
return it.curr.Err()
}
if it.ctx.Err() != nil {
return it.ctx.Err()
}
return nil
}
func (it *sampleBatchIterator) Close() error {
it.cancel()
if it.curr != nil {
return it.curr.Close()
}
return nil
}
func (it *sampleBatchIterator) At() logproto.Sample {
return it.curr.At()
}
func (it *sampleBatchIterator) Next() bool {
// for loop to avoid recursion
for it.ctx.Err() == nil {
if it.curr != nil && it.curr.Next() {
return true
}
// close previous iterator
if it.curr != nil {
it.err = it.curr.Close()
}
next := it.batchChunkIterator.Next()
if next == nil {
return false
}
if next.err != nil {
it.err = next.err
return false
}
var err error
it.curr, err = it.newChunksIterator(next)
if err != nil {
it.err = err
return false
}
}
return false
}
// newChunksIterator creates an iterator over a set of lazychunks.
func (it *sampleBatchIterator) newChunksIterator(b *chunkBatch) (iter.SampleIterator, error) {
iters, err := it.buildIterators(b.chunksBySeries, b.from, b.through, b.nextChunk)
if err != nil {
return nil, err
}
return iter.NewSortSampleIterator(iters), nil
}
func (it *sampleBatchIterator) buildIterators(chks map[model.Fingerprint][][]*LazyChunk, from, through time.Time, nextChunk *LazyChunk) ([]iter.SampleIterator, error) {
result := make([]iter.SampleIterator, 0, len(chks))
for _, chunks := range chks {
if len(chunks) != 0 && len(chunks[0]) != 0 {
streamExtractor := it.extractor.ForStream(labels.NewBuilder(chunks[0][0].Chunk.Metric).Del(labels.MetricName).Labels())
iterator, err := it.buildHeapIterator(chunks, from, through, streamExtractor, nextChunk)
if err != nil {
return nil, err
}
result = append(result, iterator)
}
}
return result, nil
}
func (it *sampleBatchIterator) buildHeapIterator(chks [][]*LazyChunk, from, through time.Time, streamExtractor log.StreamSampleExtractor, nextChunk *LazyChunk) (iter.SampleIterator, error) {
result := make([]iter.SampleIterator, 0, len(chks))
for i := range chks {
iterators := make([]iter.SampleIterator, 0, len(chks[i]))
for j := range chks[i] {
if !chks[i][j].IsValid {
continue
}
iterator, err := chks[i][j].SampleIterator(it.ctx, from, through, streamExtractor, nextChunk)
if err != nil {
return nil, err
}
iterators = append(iterators, iterator)
}
result = append(result, iter.NewNonOverlappingSampleIterator(iterators))
}
return iter.NewMergeSampleIterator(it.ctx, result), nil
}
func removeMatchersByName(matchers []*labels.Matcher, names ...string) []*labels.Matcher {
for _, omit := range names {
for i := range matchers {
if matchers[i].Name == omit {
matchers = append(matchers[:i], matchers[i+1:]...)
break
}
}
}
return matchers
}
func fetchChunkBySeries(
ctx context.Context,
s config.SchemaConfig,
metrics *ChunkMetrics,
chunks []*LazyChunk,
matchers []*labels.Matcher,
chunkFilter chunk.Filterer,
) (map[model.Fingerprint][][]*LazyChunk, error) {
chksBySeries := partitionBySeriesChunks(chunks)
// Make sure the initial chunks are loaded. This is not one chunk
// per series, but rather a chunk per non-overlapping iterator.
if err := loadFirstChunks(ctx, s, chksBySeries); err != nil {
return nil, err
}
// Now that we have the first chunk for each series loaded,
// we can proceed to filter the series that don't match.
chksBySeries = filterSeriesByMatchers(chksBySeries, matchers, chunkFilter, metrics)
var allChunks []*LazyChunk
for _, series := range chksBySeries {
for _, chunks := range series {
allChunks = append(allChunks, chunks...)
}
}
// Finally we load all chunks not already loaded
if err := fetchLazyChunks(ctx, s, allChunks); err != nil {
return nil, err
}
metrics.chunks.WithLabelValues(statusMatched).Add(float64(len(allChunks)))
metrics.series.WithLabelValues(statusMatched).Add(float64(len(chksBySeries)))
metrics.batches.WithLabelValues(statusMatched).Observe(float64(len(allChunks)))
metrics.batches.WithLabelValues(statusDiscarded).Observe(float64(len(chunks) - len(allChunks)))
return chksBySeries, nil
}
func filterSeriesByMatchers(
chks map[model.Fingerprint][][]*LazyChunk,
matchers []*labels.Matcher,
chunkFilterer chunk.Filterer,
metrics *ChunkMetrics,
) map[model.Fingerprint][][]*LazyChunk {
var filteredSeries, filteredChks int
removeSeries := func(fp model.Fingerprint, chunks [][]*LazyChunk) {
delete(chks, fp)
filteredSeries++
for _, grp := range chunks {
filteredChks += len(grp)
}
}
outer:
for fp, chunks := range chks {
for _, matcher := range matchers {
if !matcher.Matches(chunks[0][0].Chunk.Metric.Get(matcher.Name)) {
removeSeries(fp, chunks)
continue outer
}
}
if chunkFilterer != nil && chunkFilterer.ShouldFilter(chunks[0][0].Chunk.Metric) {
removeSeries(fp, chunks)
continue outer
}
}
metrics.chunks.WithLabelValues(statusDiscarded).Add(float64(filteredChks))
metrics.series.WithLabelValues(statusDiscarded).Add(float64(filteredSeries))
return chks
}
func fetchLazyChunks(ctx context.Context, s config.SchemaConfig, chunks []*LazyChunk) error {
var (
totalChunks int64
start = time.Now()
stats = stats.FromContext(ctx)
logger = util_log.WithContext(ctx, util_log.Logger)
)
defer func() {
stats.AddChunksDownloadTime(time.Since(start))
stats.AddChunksDownloaded(totalChunks)
}()
chksByFetcher := map[*fetcher.Fetcher][]*LazyChunk{}
for _, c := range chunks {
if c.Chunk.Data == nil {
chksByFetcher[c.Fetcher] = append(chksByFetcher[c.Fetcher], c)
totalChunks++
}
}
if len(chksByFetcher) == 0 {
return nil
}
level.Debug(logger).Log("msg", "loading lazy chunks", "chunks", totalChunks)
errChan := make(chan error)
for f, chunks := range chksByFetcher {
go func(fetcher *fetcher.Fetcher, chunks []*LazyChunk) {
chks := make([]chunk.Chunk, 0, len(chunks))
index := make(map[string]*LazyChunk, len(chunks))
for _, chk := range chunks {
key := s.ExternalKey(chk.Chunk.ChunkRef)
chks = append(chks, chk.Chunk)
index[key] = chk
}
chks, err := fetcher.FetchChunks(ctx, chks)
if ctx.Err() != nil {
errChan <- nil
return
}
if err != nil {
level.Error(logger).Log("msg", "error fetching chunks", "err", err)
if isInvalidChunkError(err) {
level.Error(logger).Log("msg", "checksum of chunks does not match", "err", chunk.ErrInvalidChecksum)
errChan <- nil
return
}
errChan <- err
return
}
// assign fetched chunk by key as FetchChunks doesn't guarantee the order.
for _, chk := range chks {
index[s.ExternalKey(chk.ChunkRef)].Chunk = chk
}
errChan <- nil
}(f, chunks)
}
var lastErr error
for i := 0; i < len(chksByFetcher); i++ {
if err := <-errChan; err != nil {
lastErr = err
}
}
if lastErr != nil {
return lastErr
}
for _, c := range chunks {
if c.Chunk.Data != nil {
c.IsValid = true
}
}
return nil
}
func isInvalidChunkError(err error) bool {
err = errors.Cause(err)
if err, ok := err.(promql.ErrStorage); ok {
return err.Err == chunk.ErrInvalidChecksum || err.Err == chunkenc.ErrInvalidChecksum
}
return false
}
func loadFirstChunks(ctx context.Context, s config.SchemaConfig, chks map[model.Fingerprint][][]*LazyChunk) error {
var toLoad []*LazyChunk
for _, lchks := range chks {
for _, lchk := range lchks {
if len(lchk) == 0 {
continue
}
toLoad = append(toLoad, lchk[0])
}
}
return fetchLazyChunks(ctx, s, toLoad)
}
func partitionBySeriesChunks(chunks []*LazyChunk) map[model.Fingerprint][][]*LazyChunk {
chunksByFp := map[model.Fingerprint][]*LazyChunk{}
for _, c := range chunks {
fp := c.Chunk.FingerprintModel()
chunksByFp[fp] = append(chunksByFp[fp], c)
}
result := make(map[model.Fingerprint][][]*LazyChunk, len(chunksByFp))
for fp, chks := range chunksByFp {
result[fp] = partitionOverlappingChunks(chks)
}
return result
}
// partitionOverlappingChunks splits the list of chunks into different non-overlapping lists.
// todo this might reverse the order.
func partitionOverlappingChunks(chunks []*LazyChunk) [][]*LazyChunk {
sort.Slice(chunks, func(i, j int) bool {
return chunks[i].Chunk.From < chunks[j].Chunk.From
})
css := [][]*LazyChunk{}
outer:
for _, c := range chunks {
for i, cs := range css {
// If the chunk doesn't overlap with the current list, then add it to it.
if cs[len(cs)-1].Chunk.Through.Before(c.Chunk.From) {
css[i] = append(css[i], c)
continue outer
}
}
// If the chunk overlaps with every existing list, then create a new list.
cs := make([]*LazyChunk, 0, len(chunks)/(len(css)+1))
cs = append(cs, c)
css = append(css, cs)
}
return css
}