// Copyright 2020 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 storage import ( "fmt" "math" "sort" "github.com/prometheus/prometheus/model/histogram" "github.com/prometheus/prometheus/model/labels" "github.com/prometheus/prometheus/tsdb/chunkenc" "github.com/prometheus/prometheus/tsdb/chunks" ) type SeriesEntry struct { Lset labels.Labels SampleIteratorFn func(chunkenc.Iterator) chunkenc.Iterator } func (s *SeriesEntry) Labels() labels.Labels { return s.Lset } func (s *SeriesEntry) Iterator(it chunkenc.Iterator) chunkenc.Iterator { return s.SampleIteratorFn(it) } type ChunkSeriesEntry struct { Lset labels.Labels ChunkIteratorFn func(chunks.Iterator) chunks.Iterator } func (s *ChunkSeriesEntry) Labels() labels.Labels { return s.Lset } func (s *ChunkSeriesEntry) Iterator(it chunks.Iterator) chunks.Iterator { return s.ChunkIteratorFn(it) } // NewListSeries returns series entry with iterator that allows to iterate over provided samples. func NewListSeries(lset labels.Labels, s []chunks.Sample) *SeriesEntry { samplesS := Samples(samples(s)) return &SeriesEntry{ Lset: lset, SampleIteratorFn: func(it chunkenc.Iterator) chunkenc.Iterator { if lsi, ok := it.(*listSeriesIterator); ok { lsi.Reset(samplesS) return lsi } return NewListSeriesIterator(samplesS) }, } } // NewListChunkSeriesFromSamples returns chunk series entry that allows to iterate over provided samples. // NOTE: It uses inefficient chunks encoding implementation, not caring about chunk size. // Use only for testing. func NewListChunkSeriesFromSamples(lset labels.Labels, samples ...[]chunks.Sample) *ChunkSeriesEntry { chksFromSamples := make([]chunks.Meta, 0, len(samples)) for _, s := range samples { cfs, err := chunks.ChunkFromSamples(s) if err != nil { return &ChunkSeriesEntry{ Lset: lset, ChunkIteratorFn: func(it chunks.Iterator) chunks.Iterator { return errChunksIterator{err: err} }, } } chksFromSamples = append(chksFromSamples, cfs) } return &ChunkSeriesEntry{ Lset: lset, ChunkIteratorFn: func(it chunks.Iterator) chunks.Iterator { lcsi, existing := it.(*listChunkSeriesIterator) var chks []chunks.Meta if existing { chks = lcsi.chks[:0] } else { chks = make([]chunks.Meta, 0, len(samples)) } chks = append(chks, chksFromSamples...) if existing { lcsi.Reset(chks...) return lcsi } return NewListChunkSeriesIterator(chks...) }, } } type listSeriesIterator struct { samples Samples idx int } type samples []chunks.Sample func (s samples) Get(i int) chunks.Sample { return s[i] } func (s samples) Len() int { return len(s) } // Samples interface allows to work on arrays of types that are compatible with chunks.Sample. type Samples interface { Get(i int) chunks.Sample Len() int } // NewListSeriesIterator returns listSeriesIterator that allows to iterate over provided samples. func NewListSeriesIterator(samples Samples) chunkenc.Iterator { return &listSeriesIterator{samples: samples, idx: -1} } func (it *listSeriesIterator) Reset(samples Samples) { it.samples = samples it.idx = -1 } func (it *listSeriesIterator) At() (int64, float64) { s := it.samples.Get(it.idx) return s.T(), s.F() } func (it *listSeriesIterator) AtHistogram() (int64, *histogram.Histogram) { s := it.samples.Get(it.idx) return s.T(), s.H() } func (it *listSeriesIterator) AtFloatHistogram() (int64, *histogram.FloatHistogram) { s := it.samples.Get(it.idx) return s.T(), s.FH() } func (it *listSeriesIterator) AtT() int64 { s := it.samples.Get(it.idx) return s.T() } func (it *listSeriesIterator) Next() chunkenc.ValueType { it.idx++ if it.idx >= it.samples.Len() { return chunkenc.ValNone } return it.samples.Get(it.idx).Type() } func (it *listSeriesIterator) Seek(t int64) chunkenc.ValueType { if it.idx == -1 { it.idx = 0 } if it.idx >= it.samples.Len() { return chunkenc.ValNone } // No-op check. if s := it.samples.Get(it.idx); s.T() >= t { return s.Type() } // Do binary search between current position and end. it.idx += sort.Search(it.samples.Len()-it.idx, func(i int) bool { s := it.samples.Get(i + it.idx) return s.T() >= t }) if it.idx >= it.samples.Len() { return chunkenc.ValNone } return it.samples.Get(it.idx).Type() } func (it *listSeriesIterator) Err() error { return nil } type listChunkSeriesIterator struct { chks []chunks.Meta idx int } // NewListChunkSeriesIterator returns listChunkSeriesIterator that allows to iterate over provided chunks. func NewListChunkSeriesIterator(chks ...chunks.Meta) chunks.Iterator { return &listChunkSeriesIterator{chks: chks, idx: -1} } func (it *listChunkSeriesIterator) Reset(chks ...chunks.Meta) { it.chks = chks it.idx = -1 } func (it *listChunkSeriesIterator) At() chunks.Meta { return it.chks[it.idx] } func (it *listChunkSeriesIterator) Next() bool { it.idx++ return it.idx < len(it.chks) } func (it *listChunkSeriesIterator) Err() error { return nil } type chunkSetToSeriesSet struct { ChunkSeriesSet iter chunks.Iterator chkIterErr error sameSeriesChunks []Series } // NewSeriesSetFromChunkSeriesSet converts ChunkSeriesSet to SeriesSet by decoding chunks one by one. func NewSeriesSetFromChunkSeriesSet(chk ChunkSeriesSet) SeriesSet { return &chunkSetToSeriesSet{ChunkSeriesSet: chk} } func (c *chunkSetToSeriesSet) Next() bool { if c.Err() != nil || !c.ChunkSeriesSet.Next() { return false } c.iter = c.ChunkSeriesSet.At().Iterator(c.iter) c.sameSeriesChunks = nil for c.iter.Next() { c.sameSeriesChunks = append( c.sameSeriesChunks, newChunkToSeriesDecoder(c.ChunkSeriesSet.At().Labels(), c.iter.At()), ) } if c.iter.Err() != nil { c.chkIterErr = c.iter.Err() return false } return true } func (c *chunkSetToSeriesSet) At() Series { // Series composed of same chunks for the same series. return ChainedSeriesMerge(c.sameSeriesChunks...) } func (c *chunkSetToSeriesSet) Err() error { if c.chkIterErr != nil { return c.chkIterErr } return c.ChunkSeriesSet.Err() } func newChunkToSeriesDecoder(labels labels.Labels, chk chunks.Meta) Series { return &SeriesEntry{ Lset: labels, SampleIteratorFn: func(it chunkenc.Iterator) chunkenc.Iterator { // TODO(bwplotka): Can we provide any chunkenc buffer? return chk.Chunk.Iterator(it) }, } } type seriesSetToChunkSet struct { SeriesSet } // NewSeriesSetToChunkSet converts SeriesSet to ChunkSeriesSet by encoding chunks from samples. func NewSeriesSetToChunkSet(chk SeriesSet) ChunkSeriesSet { return &seriesSetToChunkSet{SeriesSet: chk} } func (c *seriesSetToChunkSet) Next() bool { if c.Err() != nil || !c.SeriesSet.Next() { return false } return true } func (c *seriesSetToChunkSet) At() ChunkSeries { return NewSeriesToChunkEncoder(c.SeriesSet.At()) } func (c *seriesSetToChunkSet) Err() error { return c.SeriesSet.Err() } type seriesToChunkEncoder struct { Series } const seriesToChunkEncoderSplit = 120 // NewSeriesToChunkEncoder encodes samples to chunks with 120 samples limit. func NewSeriesToChunkEncoder(series Series) ChunkSeries { return &seriesToChunkEncoder{series} } func (s *seriesToChunkEncoder) Iterator(it chunks.Iterator) chunks.Iterator { var ( chk, newChk chunkenc.Chunk app chunkenc.Appender err error recoded bool ) mint := int64(math.MaxInt64) maxt := int64(math.MinInt64) var chks []chunks.Meta lcsi, existing := it.(*listChunkSeriesIterator) if existing { chks = lcsi.chks[:0] } i := 0 seriesIter := s.Series.Iterator(nil) lastType := chunkenc.ValNone for typ := seriesIter.Next(); typ != chunkenc.ValNone; typ = seriesIter.Next() { if typ != lastType || i >= seriesToChunkEncoderSplit { // Create a new chunk if the sample type changed or too many samples in the current one. chks = appendChunk(chks, mint, maxt, chk) chk, err = chunkenc.NewEmptyChunk(typ.ChunkEncoding()) if err != nil { return errChunksIterator{err: err} } app, err = chk.Appender() if err != nil { return errChunksIterator{err: err} } mint = int64(math.MaxInt64) // maxt is immediately overwritten below which is why setting it here won't make a difference. i = 0 } lastType = typ var ( t int64 v float64 h *histogram.Histogram fh *histogram.FloatHistogram ) switch typ { case chunkenc.ValFloat: t, v = seriesIter.At() app.Append(t, v) case chunkenc.ValHistogram: t, h = seriesIter.AtHistogram() newChk, recoded, app, err = app.AppendHistogram(nil, t, h, false) if err != nil { return errChunksIterator{err: err} } if newChk != nil { if !recoded { chks = appendChunk(chks, mint, maxt, chk) mint = int64(math.MaxInt64) // maxt is immediately overwritten below which is why setting it here won't make a difference. i = 0 } chk = newChk } case chunkenc.ValFloatHistogram: t, fh = seriesIter.AtFloatHistogram() newChk, recoded, app, err = app.AppendFloatHistogram(nil, t, fh, false) if err != nil { return errChunksIterator{err: err} } if newChk != nil { if !recoded { chks = appendChunk(chks, mint, maxt, chk) mint = int64(math.MaxInt64) // maxt is immediately overwritten below which is why setting it here won't make a difference. i = 0 } chk = newChk } default: return errChunksIterator{err: fmt.Errorf("unknown sample type %s", typ.String())} } maxt = t if mint == math.MaxInt64 { mint = t } i++ } if err := seriesIter.Err(); err != nil { return errChunksIterator{err: err} } chks = appendChunk(chks, mint, maxt, chk) if existing { lcsi.Reset(chks...) return lcsi } return NewListChunkSeriesIterator(chks...) } func appendChunk(chks []chunks.Meta, mint, maxt int64, chk chunkenc.Chunk) []chunks.Meta { if chk != nil { chks = append(chks, chunks.Meta{ MinTime: mint, MaxTime: maxt, Chunk: chk, }) } return chks } type errChunksIterator struct { err error } func (e errChunksIterator) At() chunks.Meta { return chunks.Meta{} } func (e errChunksIterator) Next() bool { return false } func (e errChunksIterator) Err() error { return e.err } // ExpandSamples iterates over all samples in the iterator, buffering all in slice. // Optionally it takes samples constructor, useful when you want to compare sample slices with different // sample implementations. if nil, sample type from this package will be used. func ExpandSamples(iter chunkenc.Iterator, newSampleFn func(t int64, f float64, h *histogram.Histogram, fh *histogram.FloatHistogram) chunks.Sample) ([]chunks.Sample, error) { if newSampleFn == nil { newSampleFn = func(t int64, f float64, h *histogram.Histogram, fh *histogram.FloatHistogram) chunks.Sample { switch { case h != nil: return hSample{t, h} case fh != nil: return fhSample{t, fh} default: return fSample{t, f} } } } var result []chunks.Sample for { switch iter.Next() { case chunkenc.ValNone: return result, iter.Err() case chunkenc.ValFloat: t, f := iter.At() // NaNs can't be compared normally, so substitute for another value. if math.IsNaN(f) { f = -42 } result = append(result, newSampleFn(t, f, nil, nil)) case chunkenc.ValHistogram: t, h := iter.AtHistogram() result = append(result, newSampleFn(t, 0, h, nil)) case chunkenc.ValFloatHistogram: t, fh := iter.AtFloatHistogram() result = append(result, newSampleFn(t, 0, nil, fh)) } } } // ExpandChunks iterates over all chunks in the iterator, buffering all in slice. func ExpandChunks(iter chunks.Iterator) ([]chunks.Meta, error) { var result []chunks.Meta for iter.Next() { result = append(result, iter.At()) } return result, iter.Err() }