package netstorage import ( "container/heap" "errors" "flag" "fmt" "runtime" "sort" "sync" "sync/atomic" "time" "github.com/VictoriaMetrics/VictoriaMetrics/app/vmselect/searchutils" "github.com/VictoriaMetrics/VictoriaMetrics/app/vmstorage" "github.com/VictoriaMetrics/VictoriaMetrics/lib/bytesutil" "github.com/VictoriaMetrics/VictoriaMetrics/lib/cgroup" "github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime" "github.com/VictoriaMetrics/VictoriaMetrics/lib/querytracer" "github.com/VictoriaMetrics/VictoriaMetrics/lib/storage" "github.com/VictoriaMetrics/metrics" "github.com/VictoriaMetrics/metricsql" ) var ( maxTagKeysPerSearch = flag.Int("search.maxTagKeys", 100e3, "The maximum number of tag keys returned from /api/v1/labels") maxTagValuesPerSearch = flag.Int("search.maxTagValues", 100e3, "The maximum number of tag values returned from /api/v1/label//values") maxSamplesPerSeries = flag.Int("search.maxSamplesPerSeries", 30e6, "The maximum number of raw samples a single query can scan per each time series. This option allows limiting memory usage") maxSamplesPerQuery = flag.Int("search.maxSamplesPerQuery", 1e9, "The maximum number of raw samples a single query can process across all time series. This protects from heavy queries, which select unexpectedly high number of raw samples. See also -search.maxSamplesPerSeries") ) // Result is a single timeseries result. // // ProcessSearchQuery returns Result slice. type Result struct { // The name of the metric. MetricName storage.MetricName // Values are sorted by Timestamps. Values []float64 Timestamps []int64 } func (r *Result) reset() { r.MetricName.Reset() r.Values = r.Values[:0] r.Timestamps = r.Timestamps[:0] } // Results holds results returned from ProcessSearchQuery. type Results struct { tr storage.TimeRange deadline searchutils.Deadline packedTimeseries []packedTimeseries sr *storage.Search tbf *tmpBlocksFile } // Len returns the number of results in rss. func (rss *Results) Len() int { return len(rss.packedTimeseries) } // Cancel cancels rss work. func (rss *Results) Cancel() { rss.mustClose() } func (rss *Results) mustClose() { putStorageSearch(rss.sr) rss.sr = nil putTmpBlocksFile(rss.tbf) rss.tbf = nil } type timeseriesWork struct { mustStop *uint32 rss *Results pts *packedTimeseries f func(rs *Result, workerID uint) error err error rowsProcessed int } func (tsw *timeseriesWork) reset() { tsw.mustStop = nil tsw.rss = nil tsw.pts = nil tsw.f = nil tsw.err = nil tsw.rowsProcessed = 0 } func getTimeseriesWork() *timeseriesWork { v := tswPool.Get() if v == nil { v = ×eriesWork{} } return v.(*timeseriesWork) } func putTimeseriesWork(tsw *timeseriesWork) { tsw.reset() tswPool.Put(tsw) } var tswPool sync.Pool func (tsw *timeseriesWork) do(r *Result, workerID uint) error { if atomic.LoadUint32(tsw.mustStop) != 0 { return nil } rss := tsw.rss if rss.deadline.Exceeded() { atomic.StoreUint32(tsw.mustStop, 1) return fmt.Errorf("timeout exceeded during query execution: %s", rss.deadline.String()) } if err := tsw.pts.Unpack(r, rss.tbf, rss.tr); err != nil { atomic.StoreUint32(tsw.mustStop, 1) return fmt.Errorf("error during time series unpacking: %w", err) } tsw.rowsProcessed = len(r.Timestamps) if len(r.Timestamps) > 0 { if err := tsw.f(r, workerID); err != nil { atomic.StoreUint32(tsw.mustStop, 1) return err } } return nil } func timeseriesWorker(qt *querytracer.Tracer, workChs []chan *timeseriesWork, workerID uint) { tmpResult := getTmpResult() // Perform own work at first. rowsProcessed := 0 seriesProcessed := 0 ch := workChs[workerID] for tsw := range ch { tsw.err = tsw.do(&tmpResult.rs, workerID) rowsProcessed += tsw.rowsProcessed seriesProcessed++ } qt.Printf("own work processed: series=%d, samples=%d", seriesProcessed, rowsProcessed) // Then help others with the remaining work. rowsProcessed = 0 seriesProcessed = 0 idx := int(workerID) for { tsw, idxNext := stealTimeseriesWork(workChs, idx) if tsw == nil { // There is no more work break } tsw.err = tsw.do(&tmpResult.rs, workerID) rowsProcessed += tsw.rowsProcessed seriesProcessed++ idx = idxNext } qt.Printf("others work processed: series=%d, samples=%d", seriesProcessed, rowsProcessed) putTmpResult(tmpResult) } func stealTimeseriesWork(workChs []chan *timeseriesWork, startIdx int) (*timeseriesWork, int) { for i := startIdx; i < startIdx+len(workChs); i++ { // Give a chance other goroutines to perform their work runtime.Gosched() idx := i % len(workChs) ch := workChs[idx] // It is expected that every channel in the workChs is already closed, // so the next line should return immediately. tsw, ok := <-ch if ok { return tsw, idx } } return nil, startIdx } func getTmpResult() *result { v := resultPool.Get() if v == nil { v = &result{} } return v.(*result) } func putTmpResult(r *result) { currentTime := fasttime.UnixTimestamp() if cap(r.rs.Values) > 1024*1024 && 4*len(r.rs.Values) < cap(r.rs.Values) && currentTime-r.lastResetTime > 10 { // Reset r.rs in order to preserve memory usage after processing big time series with millions of rows. r.rs = Result{} r.lastResetTime = currentTime } resultPool.Put(r) } type result struct { rs Result lastResetTime uint64 } var resultPool sync.Pool // RunParallel runs f in parallel for all the results from rss. // // f shouldn't hold references to rs after returning. // workerID is the id of the worker goroutine that calls f. // Data processing is immediately stopped if f returns non-nil error. // // rss becomes unusable after the call to RunParallel. func (rss *Results) RunParallel(qt *querytracer.Tracer, f func(rs *Result, workerID uint) error) error { qt = qt.NewChild("parallel process of fetched data") defer rss.mustClose() rowsProcessedTotal, err := rss.runParallel(qt, f) seriesProcessedTotal := len(rss.packedTimeseries) rss.packedTimeseries = rss.packedTimeseries[:0] rowsReadPerQuery.Update(float64(rowsProcessedTotal)) seriesReadPerQuery.Update(float64(seriesProcessedTotal)) qt.Donef("series=%d, samples=%d", seriesProcessedTotal, rowsProcessedTotal) return err } func (rss *Results) runParallel(qt *querytracer.Tracer, f func(rs *Result, workerID uint) error) (int, error) { tswsLen := len(rss.packedTimeseries) if tswsLen == 0 { // Nothing to process return 0, nil } var mustStop uint32 initTimeseriesWork := func(tsw *timeseriesWork, pts *packedTimeseries) { tsw.rss = rss tsw.pts = pts tsw.f = f tsw.mustStop = &mustStop } if gomaxprocs == 1 || tswsLen == 1 { // It is faster to process time series in the current goroutine. tsw := getTimeseriesWork() tmpResult := getTmpResult() rowsProcessedTotal := 0 var err error for i := range rss.packedTimeseries { initTimeseriesWork(tsw, &rss.packedTimeseries[i]) err = tsw.do(&tmpResult.rs, 0) rowsReadPerSeries.Update(float64(tsw.rowsProcessed)) rowsProcessedTotal += tsw.rowsProcessed if err != nil { break } tsw.reset() } putTmpResult(tmpResult) putTimeseriesWork(tsw) return rowsProcessedTotal, err } // Slow path - spin up multiple local workers for parallel data processing. // Do not use global workers pool, since it increases inter-CPU memory ping-poing, // which reduces the scalability on systems with many CPU cores. // Prepare the work for workers. tsws := make([]*timeseriesWork, len(rss.packedTimeseries)) for i := range rss.packedTimeseries { tsw := getTimeseriesWork() initTimeseriesWork(tsw, &rss.packedTimeseries[i]) tsws[i] = tsw } // Prepare worker channels. workers := len(tsws) if workers > gomaxprocs { workers = gomaxprocs } itemsPerWorker := (len(tsws) + workers - 1) / workers workChs := make([]chan *timeseriesWork, workers) for i := range workChs { workChs[i] = make(chan *timeseriesWork, itemsPerWorker) } // Spread work among workers. for i, tsw := range tsws { idx := i % len(workChs) workChs[idx] <- tsw } // Mark worker channels as closed. for _, workCh := range workChs { close(workCh) } // Start workers and wait until they finish the work. var wg sync.WaitGroup for i := range workChs { wg.Add(1) qtChild := qt.NewChild("worker #%d", i) go func(workerID uint) { timeseriesWorker(qtChild, workChs, workerID) qtChild.Done() wg.Done() }(uint(i)) } wg.Wait() // Collect results. var firstErr error rowsProcessedTotal := 0 for _, tsw := range tsws { if tsw.err != nil && firstErr == nil { // Return just the first error, since other errors are likely duplicate the first error. firstErr = tsw.err } rowsReadPerSeries.Update(float64(tsw.rowsProcessed)) rowsProcessedTotal += tsw.rowsProcessed putTimeseriesWork(tsw) } return rowsProcessedTotal, firstErr } var ( rowsReadPerSeries = metrics.NewHistogram(`vm_rows_read_per_series`) rowsReadPerQuery = metrics.NewHistogram(`vm_rows_read_per_query`) seriesReadPerQuery = metrics.NewHistogram(`vm_series_read_per_query`) ) var gomaxprocs = cgroup.AvailableCPUs() type packedTimeseries struct { metricName string brs []blockRef } type unpackWork struct { tbf *tmpBlocksFile br blockRef tr storage.TimeRange sb *sortBlock err error } func (upw *unpackWork) reset() { upw.tbf = nil upw.br = blockRef{} upw.tr = storage.TimeRange{} upw.sb = nil upw.err = nil } func (upw *unpackWork) unpack(tmpBlock *storage.Block) { sb := getSortBlock() if err := sb.unpackFrom(tmpBlock, upw.tbf, upw.br, upw.tr); err != nil { putSortBlock(sb) upw.err = fmt.Errorf("cannot unpack block: %w", err) return } upw.sb = sb } func getUnpackWork() *unpackWork { v := unpackWorkPool.Get() if v != nil { return v.(*unpackWork) } return &unpackWork{} } func putUnpackWork(upw *unpackWork) { upw.reset() unpackWorkPool.Put(upw) } var unpackWorkPool sync.Pool func unpackWorker(workChs []chan *unpackWork, workerID uint) { tmpBlock := getTmpStorageBlock() // Deal with own work at first. ch := workChs[workerID] for upw := range ch { upw.unpack(tmpBlock) } // Then help others with their work. idx := int(workerID) for { upw, idxNext := stealUnpackWork(workChs, idx) if upw == nil { // There is no more work break } upw.unpack(tmpBlock) idx = idxNext } putTmpStorageBlock(tmpBlock) } func stealUnpackWork(workChs []chan *unpackWork, startIdx int) (*unpackWork, int) { for i := startIdx; i < startIdx+len(workChs); i++ { // Give a chance other goroutines to perform their work runtime.Gosched() idx := i % len(workChs) ch := workChs[idx] // It is expected that every channel in the workChs is already closed, // so the next line should return immediately. upw, ok := <-ch if ok { return upw, idx } } return nil, startIdx } func getTmpStorageBlock() *storage.Block { v := tmpStorageBlockPool.Get() if v == nil { v = &storage.Block{} } return v.(*storage.Block) } func putTmpStorageBlock(sb *storage.Block) { tmpStorageBlockPool.Put(sb) } var tmpStorageBlockPool sync.Pool // Unpack unpacks pts to dst. func (pts *packedTimeseries) Unpack(dst *Result, tbf *tmpBlocksFile, tr storage.TimeRange) error { dst.reset() if err := dst.MetricName.Unmarshal(bytesutil.ToUnsafeBytes(pts.metricName)); err != nil { return fmt.Errorf("cannot unmarshal metricName %q: %w", pts.metricName, err) } sbh := getSortBlocksHeap() var err error sbh.sbs, err = pts.unpackTo(sbh.sbs[:0], tbf, tr) pts.brs = pts.brs[:0] if err != nil { putSortBlocksHeap(sbh) return err } dedupInterval := storage.GetDedupInterval() mergeSortBlocks(dst, sbh, dedupInterval) putSortBlocksHeap(sbh) return nil } func (pts *packedTimeseries) unpackTo(dst []*sortBlock, tbf *tmpBlocksFile, tr storage.TimeRange) ([]*sortBlock, error) { upwsLen := len(pts.brs) if upwsLen == 0 { // Nothing to do return nil, nil } initUnpackWork := func(upw *unpackWork, br blockRef) { upw.tbf = tbf upw.br = br upw.tr = tr } if gomaxprocs == 1 || upwsLen <= 1000 { // It is faster to unpack all the data in the current goroutine. upw := getUnpackWork() samples := 0 tmpBlock := getTmpStorageBlock() var err error for _, br := range pts.brs { initUnpackWork(upw, br) upw.unpack(tmpBlock) if upw.err != nil { return dst, upw.err } samples += len(upw.sb.Timestamps) if *maxSamplesPerSeries > 0 && samples > *maxSamplesPerSeries { putSortBlock(upw.sb) err = fmt.Errorf("cannot process more than %d samples per series; either increase -search.maxSamplesPerSeries "+ "or reduce time range for the query", *maxSamplesPerSeries) break } dst = append(dst, upw.sb) upw.reset() } putTmpStorageBlock(tmpBlock) putUnpackWork(upw) return dst, err } // Slow path - spin up multiple local workers for parallel data unpacking. // Do not use global workers pool, since it increases inter-CPU memory ping-poing, // which reduces the scalability on systems with many CPU cores. // Prepare the work for workers. upws := make([]*unpackWork, upwsLen) for i, br := range pts.brs { upw := getUnpackWork() initUnpackWork(upw, br) upws[i] = upw } // Prepare worker channels. workers := len(upws) if workers > gomaxprocs { workers = gomaxprocs } if workers < 1 { workers = 1 } itemsPerWorker := (len(upws) + workers - 1) / workers workChs := make([]chan *unpackWork, workers) for i := range workChs { workChs[i] = make(chan *unpackWork, itemsPerWorker) } // Spread work among worker channels. for i, upw := range upws { idx := i % len(workChs) workChs[idx] <- upw } // Mark worker channels as closed. for _, workCh := range workChs { close(workCh) } // Start workers and wait until they finish the work. var wg sync.WaitGroup for i := 0; i < workers; i++ { wg.Add(1) go func(workerID uint) { unpackWorker(workChs, workerID) wg.Done() }(uint(i)) } wg.Wait() // Collect results. samples := 0 var firstErr error for _, upw := range upws { if upw.err != nil && firstErr == nil { // Return the first error only, since other errors are likely the same. firstErr = upw.err } if firstErr == nil { sb := upw.sb samples += len(sb.Timestamps) if *maxSamplesPerSeries > 0 && samples > *maxSamplesPerSeries { putSortBlock(sb) firstErr = fmt.Errorf("cannot process more than %d samples per series; either increase -search.maxSamplesPerSeries "+ "or reduce time range for the query", *maxSamplesPerSeries) } else { dst = append(dst, sb) } } else { putSortBlock(upw.sb) } putUnpackWork(upw) } return dst, firstErr } func getSortBlock() *sortBlock { v := sbPool.Get() if v == nil { return &sortBlock{} } return v.(*sortBlock) } func putSortBlock(sb *sortBlock) { sb.reset() sbPool.Put(sb) } var sbPool sync.Pool var metricRowsSkipped = metrics.NewCounter(`vm_metric_rows_skipped_total{name="vmselect"}`) func mergeSortBlocks(dst *Result, sbh *sortBlocksHeap, dedupInterval int64) { // Skip empty sort blocks, since they cannot be passed to heap.Init. sbs := sbh.sbs[:0] for _, sb := range sbh.sbs { if len(sb.Timestamps) == 0 { putSortBlock(sb) continue } sbs = append(sbs, sb) } sbh.sbs = sbs if sbh.Len() == 0 { return } heap.Init(sbh) for { sbs := sbh.sbs top := sbs[0] if len(sbs) == 1 { dst.Timestamps = append(dst.Timestamps, top.Timestamps[top.NextIdx:]...) dst.Values = append(dst.Values, top.Values[top.NextIdx:]...) putSortBlock(top) break } sbNext := sbh.getNextBlock() tsNext := sbNext.Timestamps[sbNext.NextIdx] topNextIdx := top.NextIdx if n := equalSamplesPrefix(top, sbNext); n > 0 && dedupInterval > 0 { // Skip n replicated samples at top if deduplication is enabled. top.NextIdx = topNextIdx + n } else { // Copy samples from top to dst with timestamps not exceeding tsNext. top.NextIdx = topNextIdx + binarySearchTimestamps(top.Timestamps[topNextIdx:], tsNext) dst.Timestamps = append(dst.Timestamps, top.Timestamps[topNextIdx:top.NextIdx]...) dst.Values = append(dst.Values, top.Values[topNextIdx:top.NextIdx]...) } if top.NextIdx < len(top.Timestamps) { heap.Fix(sbh, 0) } else { heap.Pop(sbh) putSortBlock(top) } } timestamps, values := storage.DeduplicateSamples(dst.Timestamps, dst.Values, dedupInterval) dedups := len(dst.Timestamps) - len(timestamps) dedupsDuringSelect.Add(dedups) dst.Timestamps = timestamps dst.Values = values } var dedupsDuringSelect = metrics.NewCounter(`vm_deduplicated_samples_total{type="select"}`) func equalSamplesPrefix(a, b *sortBlock) int { n := equalTimestampsPrefix(a.Timestamps[a.NextIdx:], b.Timestamps[b.NextIdx:]) if n == 0 { return 0 } return equalValuesPrefix(a.Values[a.NextIdx:a.NextIdx+n], b.Values[b.NextIdx:b.NextIdx+n]) } func equalTimestampsPrefix(a, b []int64) int { for i, v := range a { if i >= len(b) || v != b[i] { return i } } return len(a) } func equalValuesPrefix(a, b []float64) int { for i, v := range a { if i >= len(b) || v != b[i] { return i } } return len(a) } func binarySearchTimestamps(timestamps []int64, ts int64) int { // The code has been adapted from sort.Search. n := len(timestamps) if n > 0 && timestamps[n-1] <= ts { // Fast path for timestamps scanned in ascending order. return n } i, j := 0, n for i < j { h := int(uint(i+j) >> 1) if h >= 0 && h < len(timestamps) && timestamps[h] <= ts { i = h + 1 } else { j = h } } return i } type sortBlock struct { Timestamps []int64 Values []float64 NextIdx int } func (sb *sortBlock) reset() { sb.Timestamps = sb.Timestamps[:0] sb.Values = sb.Values[:0] sb.NextIdx = 0 } func (sb *sortBlock) unpackFrom(tmpBlock *storage.Block, tbf *tmpBlocksFile, br blockRef, tr storage.TimeRange) error { tmpBlock.Reset() brReal := tbf.MustReadBlockRefAt(br.partRef, br.addr) brReal.MustReadBlock(tmpBlock) if err := tmpBlock.UnmarshalData(); err != nil { return fmt.Errorf("cannot unmarshal block: %w", err) } sb.Timestamps, sb.Values = tmpBlock.AppendRowsWithTimeRangeFilter(sb.Timestamps[:0], sb.Values[:0], tr) skippedRows := tmpBlock.RowsCount() - len(sb.Timestamps) metricRowsSkipped.Add(skippedRows) return nil } type sortBlocksHeap struct { sbs []*sortBlock } func (sbh *sortBlocksHeap) getNextBlock() *sortBlock { sbs := sbh.sbs if len(sbs) < 2 { return nil } if len(sbs) < 3 { return sbs[1] } a := sbs[1] b := sbs[2] if a.Timestamps[a.NextIdx] <= b.Timestamps[b.NextIdx] { return a } return b } func (sbh *sortBlocksHeap) Len() int { return len(sbh.sbs) } func (sbh *sortBlocksHeap) Less(i, j int) bool { sbs := sbh.sbs a := sbs[i] b := sbs[j] return a.Timestamps[a.NextIdx] < b.Timestamps[b.NextIdx] } func (sbh *sortBlocksHeap) Swap(i, j int) { sbs := sbh.sbs sbs[i], sbs[j] = sbs[j], sbs[i] } func (sbh *sortBlocksHeap) Push(x interface{}) { sbh.sbs = append(sbh.sbs, x.(*sortBlock)) } func (sbh *sortBlocksHeap) Pop() interface{} { sbs := sbh.sbs v := sbs[len(sbs)-1] sbs[len(sbs)-1] = nil sbh.sbs = sbs[:len(sbs)-1] return v } func getSortBlocksHeap() *sortBlocksHeap { v := sbhPool.Get() if v == nil { return &sortBlocksHeap{} } return v.(*sortBlocksHeap) } func putSortBlocksHeap(sbh *sortBlocksHeap) { sbs := sbh.sbs for i := range sbs { sbs[i] = nil } sbh.sbs = sbs[:0] sbhPool.Put(sbh) } var sbhPool sync.Pool // DeleteSeries deletes time series matching the given tagFilterss. func DeleteSeries(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline searchutils.Deadline) (int, error) { qt = qt.NewChild("delete series: %s", sq) defer qt.Done() tr := sq.GetTimeRange() tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return 0, err } return vmstorage.DeleteSeries(qt, tfss) } // LabelNames returns label names matching the given sq until the given deadline. func LabelNames(qt *querytracer.Tracer, sq *storage.SearchQuery, maxLabelNames int, deadline searchutils.Deadline) ([]string, error) { qt = qt.NewChild("get labels: %s", sq) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } if maxLabelNames > *maxTagKeysPerSearch || maxLabelNames <= 0 { maxLabelNames = *maxTagKeysPerSearch } tr := sq.GetTimeRange() tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return nil, err } labels, err := vmstorage.SearchLabelNamesWithFiltersOnTimeRange(qt, tfss, tr, maxLabelNames, sq.MaxMetrics, deadline.Deadline()) if err != nil { return nil, fmt.Errorf("error during labels search on time range: %w", err) } // Sort labels like Prometheus does sort.Strings(labels) qt.Printf("sort %d labels", len(labels)) return labels, nil } // GraphiteTags returns Graphite tags until the given deadline. func GraphiteTags(qt *querytracer.Tracer, filter string, limit int, deadline searchutils.Deadline) ([]string, error) { qt = qt.NewChild("get graphite tags: filter=%s, limit=%d", filter, limit) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } sq := storage.NewSearchQuery(0, 0, nil, 0) labels, err := LabelNames(qt, sq, 0, deadline) if err != nil { return nil, err } // Substitute "__name__" with "name" for Graphite compatibility for i := range labels { if labels[i] != "__name__" { continue } // Prevent from duplicate `name` tag. // See https://github.com/VictoriaMetrics/VictoriaMetrics/issues/942 if hasString(labels, "name") { labels = append(labels[:i], labels[i+1:]...) } else { labels[i] = "name" sort.Strings(labels) } break } if len(filter) > 0 { labels, err = applyGraphiteRegexpFilter(filter, labels) if err != nil { return nil, err } } if limit > 0 && limit < len(labels) { labels = labels[:limit] } return labels, nil } func hasString(a []string, s string) bool { for _, x := range a { if x == s { return true } } return false } // LabelValues returns label values matching the given labelName and sq until the given deadline. func LabelValues(qt *querytracer.Tracer, labelName string, sq *storage.SearchQuery, maxLabelValues int, deadline searchutils.Deadline) ([]string, error) { qt = qt.NewChild("get values for label %s: %s", labelName, sq) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } if maxLabelValues > *maxTagValuesPerSearch || maxLabelValues <= 0 { maxLabelValues = *maxTagValuesPerSearch } tr := sq.GetTimeRange() tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return nil, err } labelValues, err := vmstorage.SearchLabelValuesWithFiltersOnTimeRange(qt, labelName, tfss, tr, maxLabelValues, sq.MaxMetrics, deadline.Deadline()) if err != nil { return nil, fmt.Errorf("error during label values search on time range for labelName=%q: %w", labelName, err) } // Sort labelValues like Prometheus does sort.Strings(labelValues) qt.Printf("sort %d label values", len(labelValues)) return labelValues, nil } // GraphiteTagValues returns tag values for the given tagName until the given deadline. func GraphiteTagValues(qt *querytracer.Tracer, tagName, filter string, limit int, deadline searchutils.Deadline) ([]string, error) { qt = qt.NewChild("get graphite tag values for tagName=%s, filter=%s, limit=%d", tagName, filter, limit) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } if tagName == "name" { tagName = "" } sq := storage.NewSearchQuery(0, 0, nil, 0) tagValues, err := LabelValues(qt, tagName, sq, 0, deadline) if err != nil { return nil, err } if len(filter) > 0 { tagValues, err = applyGraphiteRegexpFilter(filter, tagValues) if err != nil { return nil, err } } if limit > 0 && limit < len(tagValues) { tagValues = tagValues[:limit] } return tagValues, nil } // TagValueSuffixes returns tag value suffixes for the given tagKey and the given tagValuePrefix. // // It can be used for implementing https://graphite-api.readthedocs.io/en/latest/api.html#metrics-find func TagValueSuffixes(qt *querytracer.Tracer, tr storage.TimeRange, tagKey, tagValuePrefix string, delimiter byte, maxSuffixes int, deadline searchutils.Deadline) ([]string, error) { qt = qt.NewChild("get tag value suffixes for tagKey=%s, tagValuePrefix=%s, maxSuffixes=%d, timeRange=%s", tagKey, tagValuePrefix, maxSuffixes, &tr) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } suffixes, err := vmstorage.SearchTagValueSuffixes(qt, tr, tagKey, tagValuePrefix, delimiter, maxSuffixes, deadline.Deadline()) if err != nil { return nil, fmt.Errorf("error during search for suffixes for tagKey=%q, tagValuePrefix=%q, delimiter=%c on time range %s: %w", tagKey, tagValuePrefix, delimiter, tr.String(), err) } if len(suffixes) >= maxSuffixes { return nil, fmt.Errorf("more than -search.maxTagValueSuffixesPerSearch=%d tag value suffixes found for tagKey=%q, tagValuePrefix=%q, delimiter=%c on time range %s; "+ "either narrow down the query or increase -search.maxTagValueSuffixesPerSearch command-line flag value", maxSuffixes, tagKey, tagValuePrefix, delimiter, tr.String()) } return suffixes, nil } // TSDBStatus returns tsdb status according to https://prometheus.io/docs/prometheus/latest/querying/api/#tsdb-stats // // It accepts arbitrary filters on time series in sq. func TSDBStatus(qt *querytracer.Tracer, sq *storage.SearchQuery, focusLabel string, topN int, deadline searchutils.Deadline) (*storage.TSDBStatus, error) { qt = qt.NewChild("get tsdb stats: %s, focusLabel=%q, topN=%d", sq, focusLabel, topN) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } tr := sq.GetTimeRange() tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return nil, err } date := uint64(tr.MinTimestamp) / (3600 * 24 * 1000) status, err := vmstorage.GetTSDBStatus(qt, tfss, date, focusLabel, topN, sq.MaxMetrics, deadline.Deadline()) if err != nil { return nil, fmt.Errorf("error during tsdb status request: %w", err) } return status, nil } // SeriesCount returns the number of unique series. func SeriesCount(qt *querytracer.Tracer, deadline searchutils.Deadline) (uint64, error) { qt = qt.NewChild("get series count") defer qt.Done() if deadline.Exceeded() { return 0, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } n, err := vmstorage.GetSeriesCount(deadline.Deadline()) if err != nil { return 0, fmt.Errorf("error during series count request: %w", err) } return n, nil } func getStorageSearch() *storage.Search { v := ssPool.Get() if v == nil { return &storage.Search{} } return v.(*storage.Search) } func putStorageSearch(sr *storage.Search) { sr.MustClose() ssPool.Put(sr) } var ssPool sync.Pool // ExportBlocks searches for time series matching sq and calls f for each found block. // // f is called in parallel from multiple goroutines. // Data processing is immediately stopped if f returns non-nil error. // It is the responsibility of f to call b.UnmarshalData before reading timestamps and values from the block. // It is the responsibility of f to filter blocks according to the given tr. func ExportBlocks(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline searchutils.Deadline, f func(mn *storage.MetricName, b *storage.Block, tr storage.TimeRange, workerID uint) error) error { qt = qt.NewChild("export blocks: %s", sq) defer qt.Done() if deadline.Exceeded() { return fmt.Errorf("timeout exceeded before starting data export: %s", deadline.String()) } tr := sq.GetTimeRange() if err := vmstorage.CheckTimeRange(tr); err != nil { return err } tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return err } vmstorage.WG.Add(1) defer vmstorage.WG.Done() sr := getStorageSearch() defer putStorageSearch(sr) startTime := time.Now() sr.Init(qt, vmstorage.Storage, tfss, tr, sq.MaxMetrics, deadline.Deadline()) indexSearchDuration.UpdateDuration(startTime) // Start workers that call f in parallel on available CPU cores. gomaxprocs := cgroup.AvailableCPUs() workCh := make(chan *exportWork, gomaxprocs*8) var ( errGlobal error errGlobalLock sync.Mutex mustStop uint32 ) var wg sync.WaitGroup wg.Add(gomaxprocs) for i := 0; i < gomaxprocs; i++ { go func(workerID uint) { defer wg.Done() for xw := range workCh { if err := f(&xw.mn, &xw.b, tr, workerID); err != nil { errGlobalLock.Lock() if errGlobal != nil { errGlobal = err atomic.StoreUint32(&mustStop, 1) } errGlobalLock.Unlock() } xw.reset() exportWorkPool.Put(xw) } }(uint(i)) } // Feed workers with work blocksRead := 0 samples := 0 for sr.NextMetricBlock() { blocksRead++ if deadline.Exceeded() { return fmt.Errorf("timeout exceeded while fetching data block #%d from storage: %s", blocksRead, deadline.String()) } if atomic.LoadUint32(&mustStop) != 0 { break } xw := exportWorkPool.Get().(*exportWork) if err := xw.mn.Unmarshal(sr.MetricBlockRef.MetricName); err != nil { return fmt.Errorf("cannot unmarshal metricName for block #%d: %w", blocksRead, err) } br := sr.MetricBlockRef.BlockRef br.MustReadBlock(&xw.b) samples += br.RowsCount() workCh <- xw } close(workCh) // Wait for workers to finish. wg.Wait() qt.Printf("export blocks=%d, samples=%d", blocksRead, samples) // Check errors. err = sr.Error() if err == nil { err = errGlobal } if err != nil { if errors.Is(err, storage.ErrDeadlineExceeded) { return fmt.Errorf("timeout exceeded during the query: %s", deadline.String()) } return fmt.Errorf("search error after reading %d data blocks: %w", blocksRead, err) } return nil } type exportWork struct { mn storage.MetricName b storage.Block } func (xw *exportWork) reset() { xw.mn.Reset() xw.b.Reset() } var exportWorkPool = &sync.Pool{ New: func() interface{} { return &exportWork{} }, } // SearchMetricNames returns all the metric names matching sq until the given deadline. // // The returned metric names must be unmarshaled via storage.MetricName.UnmarshalString(). func SearchMetricNames(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline searchutils.Deadline) ([]string, error) { qt = qt.NewChild("fetch metric names: %s", sq) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting to search metric names: %s", deadline.String()) } // Setup search. tr := sq.GetTimeRange() if err := vmstorage.CheckTimeRange(tr); err != nil { return nil, err } tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return nil, err } metricNames, err := vmstorage.SearchMetricNames(qt, tfss, tr, sq.MaxMetrics, deadline.Deadline()) if err != nil { return nil, fmt.Errorf("cannot find metric names: %w", err) } sort.Strings(metricNames) qt.Printf("sort %d metric names", len(metricNames)) return metricNames, nil } // ProcessSearchQuery performs sq until the given deadline. // // Results.RunParallel or Results.Cancel must be called on the returned Results. func ProcessSearchQuery(qt *querytracer.Tracer, sq *storage.SearchQuery, deadline searchutils.Deadline) (*Results, error) { qt = qt.NewChild("fetch matching series: %s", sq) defer qt.Done() if deadline.Exceeded() { return nil, fmt.Errorf("timeout exceeded before starting the query processing: %s", deadline.String()) } // Setup search. tr := sq.GetTimeRange() if err := vmstorage.CheckTimeRange(tr); err != nil { return nil, err } tfss, err := setupTfss(qt, tr, sq.TagFilterss, sq.MaxMetrics, deadline) if err != nil { return nil, err } vmstorage.WG.Add(1) defer vmstorage.WG.Done() sr := getStorageSearch() startTime := time.Now() maxSeriesCount := sr.Init(qt, vmstorage.Storage, tfss, tr, sq.MaxMetrics, deadline.Deadline()) indexSearchDuration.UpdateDuration(startTime) type blockRefs struct { brsPrealloc [4]blockRef brs []blockRef } m := make(map[string]*blockRefs, maxSeriesCount) orderedMetricNames := make([]string, 0, maxSeriesCount) blocksRead := 0 samples := 0 tbf := getTmpBlocksFile() var buf []byte for sr.NextMetricBlock() { blocksRead++ if deadline.Exceeded() { putTmpBlocksFile(tbf) putStorageSearch(sr) return nil, fmt.Errorf("timeout exceeded while fetching data block #%d from storage: %s", blocksRead, deadline.String()) } br := sr.MetricBlockRef.BlockRef samples += br.RowsCount() if *maxSamplesPerQuery > 0 && samples > *maxSamplesPerQuery { putTmpBlocksFile(tbf) putStorageSearch(sr) return nil, fmt.Errorf("cannot select more than -search.maxSamplesPerQuery=%d samples; possible solutions: to increase the -search.maxSamplesPerQuery; to reduce time range for the query; to use more specific label filters in order to select lower number of series", *maxSamplesPerQuery) } buf = br.Marshal(buf[:0]) addr, err := tbf.WriteBlockRefData(buf) if err != nil { putTmpBlocksFile(tbf) putStorageSearch(sr) return nil, fmt.Errorf("cannot write %d bytes to temporary file: %w", len(buf), err) } metricName := bytesutil.InternBytes(sr.MetricBlockRef.MetricName) brs := m[metricName] if brs == nil { brs = &blockRefs{} brs.brs = brs.brsPrealloc[:0] } brs.brs = append(brs.brs, blockRef{ partRef: br.PartRef(), addr: addr, }) if len(brs.brs) == 1 { orderedMetricNames = append(orderedMetricNames, metricName) m[metricName] = brs } } if err := sr.Error(); err != nil { putTmpBlocksFile(tbf) putStorageSearch(sr) if errors.Is(err, storage.ErrDeadlineExceeded) { return nil, fmt.Errorf("timeout exceeded during the query: %s", deadline.String()) } return nil, fmt.Errorf("search error after reading %d data blocks: %w", blocksRead, err) } if err := tbf.Finalize(); err != nil { putTmpBlocksFile(tbf) putStorageSearch(sr) return nil, fmt.Errorf("cannot finalize temporary file: %w", err) } qt.Printf("fetch unique series=%d, blocks=%d, samples=%d, bytes=%d", len(m), blocksRead, samples, tbf.Len()) var rss Results rss.tr = tr rss.deadline = deadline pts := make([]packedTimeseries, len(orderedMetricNames)) for i, metricName := range orderedMetricNames { pts[i] = packedTimeseries{ metricName: metricName, brs: m[metricName].brs, } } rss.packedTimeseries = pts rss.sr = sr rss.tbf = tbf return &rss, nil } var indexSearchDuration = metrics.NewHistogram(`vm_index_search_duration_seconds`) type blockRef struct { partRef storage.PartRef addr tmpBlockAddr } func setupTfss(qt *querytracer.Tracer, tr storage.TimeRange, tagFilterss [][]storage.TagFilter, maxMetrics int, deadline searchutils.Deadline) ([]*storage.TagFilters, error) { tfss := make([]*storage.TagFilters, 0, len(tagFilterss)) for _, tagFilters := range tagFilterss { tfs := storage.NewTagFilters() for i := range tagFilters { tf := &tagFilters[i] if string(tf.Key) == "__graphite__" { query := tf.Value paths, err := vmstorage.SearchGraphitePaths(qt, tr, query, maxMetrics, deadline.Deadline()) if err != nil { return nil, fmt.Errorf("error when searching for Graphite paths for query %q: %w", query, err) } if len(paths) >= maxMetrics { return nil, fmt.Errorf("more than %d time series match Graphite query %q; "+ "either narrow down the query or increase the corresponding -search.max* command-line flag value", maxMetrics, query) } tfs.AddGraphiteQuery(query, paths, tf.IsNegative) continue } if err := tfs.Add(tf.Key, tf.Value, tf.IsNegative, tf.IsRegexp); err != nil { return nil, fmt.Errorf("cannot parse tag filter %s: %w", tf, err) } } tfss = append(tfss, tfs) } return tfss, nil } func applyGraphiteRegexpFilter(filter string, ss []string) ([]string, error) { // Anchor filter regexp to the beginning of the string as Graphite does. // See https://github.com/graphite-project/graphite-web/blob/3ad279df5cb90b211953e39161df416e54a84948/webapp/graphite/tags/localdatabase.py#L157 filter = "^(?:" + filter + ")" re, err := metricsql.CompileRegexp(filter) if err != nil { return nil, fmt.Errorf("cannot parse regexp filter=%q: %w", filter, err) } dst := ss[:0] for _, s := range ss { if re.MatchString(s) { dst = append(dst, s) } } return dst, nil }