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5602328c7c
This copies the evaluation logic from the current rules/ package. The new engine handles the execution process from query string to final result. It provides query timeout and cancellation and general flexibility for future changes. functions.go: Add evaluation implementation. Slight changes to in/out data but not to the processing logic. quantile.go: No changes. analyzer.go: No changes. engine.go: Actually new part. Mainly consists of evaluation methods which were not changed. setup_test.go: Copy of rules/helpers_test.go to setup test storage. promql_test.go: Copy of rules/rules_test.go.
107 lines
3.3 KiB
Go
107 lines
3.3 KiB
Go
// Copyright 2015 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 promql
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import (
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"math"
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"sort"
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clientmodel "github.com/prometheus/client_golang/model"
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)
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// Helpers to calculate quantiles.
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// excludedLabels are the labels to exclude from signature calculation for
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// quantiles.
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var excludedLabels = map[clientmodel.LabelName]struct{}{
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clientmodel.MetricNameLabel: struct{}{},
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clientmodel.BucketLabel: struct{}{},
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}
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type bucket struct {
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upperBound float64
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count clientmodel.SampleValue
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}
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// buckets implements sort.Interface.
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type buckets []bucket
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func (b buckets) Len() int { return len(b) }
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func (b buckets) Swap(i, j int) { b[i], b[j] = b[j], b[i] }
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func (b buckets) Less(i, j int) bool { return b[i].upperBound < b[j].upperBound }
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type metricWithBuckets struct {
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metric clientmodel.COWMetric
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buckets buckets
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}
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// quantile calculates the quantile 'q' based on the given buckets. The buckets
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// will be sorted by upperBound by this function (i.e. no sorting needed before
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// calling this function). The quantile value is interpolated assuming a linear
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// distribution within a bucket. However, if the quantile falls into the highest
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// bucket, the upper bound of the 2nd highest bucket is returned. A natural
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// lower bound of 0 is assumed if the upper bound of the lowest bucket is
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// greater 0. In that case, interpolation in the lowest bucket happens linearly
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// between 0 and the upper bound of the lowest bucket. However, if the lowest
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// bucket has an upper bound less or equal 0, this upper bound is returned if
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// the quantile falls into the lowest bucket.
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//
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// There are a number of special cases (once we have a way to report errors
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// happening during evaluations of AST functions, we should report those
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// explicitly):
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//
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// If 'buckets' has fewer than 2 elements, NaN is returned.
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//
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// If the highest bucket is not +Inf, NaN is returned.
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//
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// If q<0, -Inf is returned.
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//
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// If q>1, +Inf is returned.
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func quantile(q clientmodel.SampleValue, buckets buckets) float64 {
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if q < 0 {
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return math.Inf(-1)
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}
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if q > 1 {
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return math.Inf(+1)
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}
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if len(buckets) < 2 {
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return math.NaN()
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}
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sort.Sort(buckets)
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if !math.IsInf(buckets[len(buckets)-1].upperBound, +1) {
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return math.NaN()
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}
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rank := q * buckets[len(buckets)-1].count
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b := sort.Search(len(buckets)-1, func(i int) bool { return buckets[i].count >= rank })
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if b == len(buckets)-1 {
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return buckets[len(buckets)-2].upperBound
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}
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if b == 0 && buckets[0].upperBound <= 0 {
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return buckets[0].upperBound
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}
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var (
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bucketStart float64
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bucketEnd = buckets[b].upperBound
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count = buckets[b].count
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)
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if b > 0 {
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bucketStart = buckets[b-1].upperBound
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count -= buckets[b-1].count
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rank -= buckets[b-1].count
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}
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return bucketStart + (bucketEnd-bucketStart)*float64(rank/count)
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}
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