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8ef7dfdeeb
Add a chunk size limit in bytes This creates a hard cap for XOR chunks of 1024 bytes. The limit for histogram chunk is also 1024 bytes, but it is a soft limit as a histogram has a dynamic size, and even a single one could be larger than 1024 bytes. This also avoids cutting new histogram chunks if the existing chunk has fewer than 10 histograms yet. In that way, we are accepting "jumbo chunks" in order to have at least 10 histograms in a chunk, allowing compression to kick in. Signed-off-by: Justin Lei <justin.lei@grafana.com>
90 lines
2 KiB
Go
90 lines
2 KiB
Go
// Copyright 2023 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package chunks
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import (
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"github.com/prometheus/prometheus/model/histogram"
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"github.com/prometheus/prometheus/tsdb/chunkenc"
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)
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type Samples interface {
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Get(i int) Sample
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Len() int
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}
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type Sample interface {
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T() int64
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F() float64
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H() *histogram.Histogram
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FH() *histogram.FloatHistogram
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Type() chunkenc.ValueType
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}
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type SampleSlice []Sample
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func (s SampleSlice) Get(i int) Sample { return s[i] }
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func (s SampleSlice) Len() int { return len(s) }
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type sample struct {
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t int64
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f float64
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h *histogram.Histogram
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fh *histogram.FloatHistogram
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}
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func (s sample) T() int64 {
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return s.t
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}
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func (s sample) F() float64 {
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return s.f
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}
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func (s sample) H() *histogram.Histogram {
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return s.h
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}
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func (s sample) FH() *histogram.FloatHistogram {
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return s.fh
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}
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func (s sample) Type() chunkenc.ValueType {
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switch {
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case s.h != nil:
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return chunkenc.ValHistogram
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case s.fh != nil:
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return chunkenc.ValFloatHistogram
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default:
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return chunkenc.ValFloat
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}
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}
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// GenerateSamples starting at start and counting up numSamples.
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func GenerateSamples(start, numSamples int) []Sample {
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return generateSamples(start, numSamples, func(i int) Sample {
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return sample{
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t: int64(i),
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f: float64(i),
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}
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})
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}
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func generateSamples(start, numSamples int, gen func(int) Sample) []Sample {
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samples := make([]Sample, 0, numSamples)
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for i := start; i < start+numSamples; i++ {
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samples = append(samples, gen(i))
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}
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return samples
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}
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