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3802 lines
121 KiB
3802 lines
121 KiB
// Copyright 2013 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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"bytes"
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"container/heap"
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"context"
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"errors"
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"fmt"
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"io"
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"log/slog"
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"math"
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"reflect"
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"runtime"
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"slices"
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"sort"
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"strconv"
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"strings"
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"sync"
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"time"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/common/model"
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"github.com/prometheus/common/promslog"
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"go.opentelemetry.io/otel"
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"go.opentelemetry.io/otel/attribute"
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"go.opentelemetry.io/otel/trace"
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"github.com/prometheus/prometheus/model/histogram"
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"github.com/prometheus/prometheus/model/labels"
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"github.com/prometheus/prometheus/model/timestamp"
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"github.com/prometheus/prometheus/model/value"
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"github.com/prometheus/prometheus/promql/parser"
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"github.com/prometheus/prometheus/promql/parser/posrange"
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"github.com/prometheus/prometheus/storage"
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"github.com/prometheus/prometheus/tsdb/chunkenc"
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"github.com/prometheus/prometheus/util/annotations"
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"github.com/prometheus/prometheus/util/stats"
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"github.com/prometheus/prometheus/util/zeropool"
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)
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const (
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namespace = "prometheus"
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subsystem = "engine"
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queryTag = "query"
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env = "query execution"
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defaultLookbackDelta = 5 * time.Minute
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// The largest SampleValue that can be converted to an int64 without overflow.
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maxInt64 = 9223372036854774784
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// The smallest SampleValue that can be converted to an int64 without underflow.
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minInt64 = -9223372036854775808
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// Max initial size for the pooled points slices.
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// The getHPointSlice and getFPointSlice functions are called with an estimated size which often can be
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// over-estimated.
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maxPointsSliceSize = 5000
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// The default buffer size for points used by the matrix selector.
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matrixSelectorSliceSize = 16
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)
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type engineMetrics struct {
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currentQueries prometheus.Gauge
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maxConcurrentQueries prometheus.Gauge
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queryLogEnabled prometheus.Gauge
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queryLogFailures prometheus.Counter
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queryQueueTime prometheus.Observer
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queryPrepareTime prometheus.Observer
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queryInnerEval prometheus.Observer
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queryResultSort prometheus.Observer
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querySamples prometheus.Counter
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}
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// convertibleToInt64 returns true if v does not over-/underflow an int64.
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func convertibleToInt64(v float64) bool {
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return v <= maxInt64 && v >= minInt64
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}
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type (
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// ErrQueryTimeout is returned if a query timed out during processing.
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ErrQueryTimeout string
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// ErrQueryCanceled is returned if a query was canceled during processing.
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ErrQueryCanceled string
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// ErrTooManySamples is returned if a query would load more than the maximum allowed samples into memory.
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ErrTooManySamples string
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// ErrStorage is returned if an error was encountered in the storage layer
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// during query handling.
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ErrStorage struct{ Err error }
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)
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func (e ErrQueryTimeout) Error() string {
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return fmt.Sprintf("query timed out in %s", string(e))
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}
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func (e ErrQueryCanceled) Error() string {
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return fmt.Sprintf("query was canceled in %s", string(e))
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}
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func (e ErrTooManySamples) Error() string {
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return fmt.Sprintf("query processing would load too many samples into memory in %s", string(e))
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}
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func (e ErrStorage) Error() string {
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return e.Err.Error()
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}
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// QueryEngine defines the interface for the *promql.Engine, so it can be replaced, wrapped or mocked.
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type QueryEngine interface {
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NewInstantQuery(ctx context.Context, q storage.Queryable, opts QueryOpts, qs string, ts time.Time) (Query, error)
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NewRangeQuery(ctx context.Context, q storage.Queryable, opts QueryOpts, qs string, start, end time.Time, interval time.Duration) (Query, error)
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}
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// QueryLogger is an interface that can be used to log all the queries logged
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// by the engine.
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type QueryLogger interface {
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Error(msg string, args ...any)
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Info(msg string, args ...any)
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Debug(msg string, args ...any)
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Warn(msg string, args ...any)
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With(args ...any)
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Close() error
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}
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// A Query is derived from an a raw query string and can be run against an engine
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// it is associated with.
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type Query interface {
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// Exec processes the query. Can only be called once.
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Exec(ctx context.Context) *Result
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// Close recovers memory used by the query result.
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Close()
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// Statement returns the parsed statement of the query.
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Statement() parser.Statement
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// Stats returns statistics about the lifetime of the query.
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Stats() *stats.Statistics
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// Cancel signals that a running query execution should be aborted.
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Cancel()
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// String returns the original query string.
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String() string
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}
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type PrometheusQueryOpts struct {
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// Enables recording per-step statistics if the engine has it enabled as well. Disabled by default.
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enablePerStepStats bool
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// Lookback delta duration for this query.
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lookbackDelta time.Duration
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}
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var _ QueryOpts = &PrometheusQueryOpts{}
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func NewPrometheusQueryOpts(enablePerStepStats bool, lookbackDelta time.Duration) QueryOpts {
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return &PrometheusQueryOpts{
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enablePerStepStats: enablePerStepStats,
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lookbackDelta: lookbackDelta,
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}
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}
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func (p *PrometheusQueryOpts) EnablePerStepStats() bool {
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return p.enablePerStepStats
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}
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func (p *PrometheusQueryOpts) LookbackDelta() time.Duration {
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return p.lookbackDelta
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}
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type QueryOpts interface {
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// Enables recording per-step statistics if the engine has it enabled as well. Disabled by default.
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EnablePerStepStats() bool
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// Lookback delta duration for this query.
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LookbackDelta() time.Duration
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}
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// query implements the Query interface.
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type query struct {
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// Underlying data provider.
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queryable storage.Queryable
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// The original query string.
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q string
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// Statement of the parsed query.
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stmt parser.Statement
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// Timer stats for the query execution.
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stats *stats.QueryTimers
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// Sample stats for the query execution.
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sampleStats *stats.QuerySamples
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// Result matrix for reuse.
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matrix Matrix
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// Cancellation function for the query.
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cancel func()
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// The engine against which the query is executed.
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ng *Engine
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}
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type QueryOrigin struct{}
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// Statement implements the Query interface.
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// Calling this after Exec may result in panic,
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// see https://github.com/prometheus/prometheus/issues/8949.
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func (q *query) Statement() parser.Statement {
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return q.stmt
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}
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// String implements the Query interface.
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func (q *query) String() string {
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return q.q
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}
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// Stats implements the Query interface.
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func (q *query) Stats() *stats.Statistics {
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return &stats.Statistics{
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Timers: q.stats,
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Samples: q.sampleStats,
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}
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}
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// Cancel implements the Query interface.
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func (q *query) Cancel() {
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if q.cancel != nil {
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q.cancel()
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}
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}
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// Close implements the Query interface.
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func (q *query) Close() {
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for _, s := range q.matrix {
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putFPointSlice(s.Floats)
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putHPointSlice(s.Histograms)
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}
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}
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// Exec implements the Query interface.
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func (q *query) Exec(ctx context.Context) *Result {
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if span := trace.SpanFromContext(ctx); span != nil {
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span.SetAttributes(attribute.String(queryTag, q.stmt.String()))
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}
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// Exec query.
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res, warnings, err := q.ng.exec(ctx, q)
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return &Result{Err: err, Value: res, Warnings: warnings}
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}
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// contextDone returns an error if the context was canceled or timed out.
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func contextDone(ctx context.Context, env string) error {
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if err := ctx.Err(); err != nil {
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return contextErr(err, env)
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}
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return nil
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}
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func contextErr(err error, env string) error {
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switch {
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case errors.Is(err, context.Canceled):
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return ErrQueryCanceled(env)
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case errors.Is(err, context.DeadlineExceeded):
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return ErrQueryTimeout(env)
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default:
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return err
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}
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}
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// QueryTracker provides access to two features:
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//
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// 1) Tracking of active query. If PromQL engine crashes while executing any query, such query should be present
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// in the tracker on restart, hence logged. After the logging on restart, the tracker gets emptied.
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//
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// 2) Enforcement of the maximum number of concurrent queries.
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type QueryTracker interface {
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io.Closer
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// GetMaxConcurrent returns maximum number of concurrent queries that are allowed by this tracker.
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GetMaxConcurrent() int
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// Insert inserts query into query tracker. This call must block if maximum number of queries is already running.
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// If Insert doesn't return error then returned integer value should be used in subsequent Delete call.
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// Insert should return error if context is finished before query can proceed, and integer value returned in this case should be ignored by caller.
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Insert(ctx context.Context, query string) (int, error)
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// Delete removes query from activity tracker. InsertIndex is value returned by Insert call.
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Delete(insertIndex int)
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}
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// EngineOpts contains configuration options used when creating a new Engine.
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type EngineOpts struct {
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Logger *slog.Logger
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Reg prometheus.Registerer
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MaxSamples int
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Timeout time.Duration
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ActiveQueryTracker QueryTracker
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// LookbackDelta determines the time since the last sample after which a time
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// series is considered stale.
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LookbackDelta time.Duration
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// NoStepSubqueryIntervalFn is the default evaluation interval of
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// a subquery in milliseconds if no step in range vector was specified `[30m:<step>]`.
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NoStepSubqueryIntervalFn func(rangeMillis int64) int64
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// EnableAtModifier if true enables @ modifier. Disabled otherwise. This
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// is supposed to be enabled for regular PromQL (as of Prometheus v2.33)
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// but the option to disable it is still provided here for those using
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// the Engine outside of Prometheus.
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EnableAtModifier bool
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// EnableNegativeOffset if true enables negative (-) offset
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// values. Disabled otherwise. This is supposed to be enabled for
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// regular PromQL (as of Prometheus v2.33) but the option to disable it
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// is still provided here for those using the Engine outside of
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// Prometheus.
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EnableNegativeOffset bool
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// EnablePerStepStats if true allows for per-step stats to be computed on request. Disabled otherwise.
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EnablePerStepStats bool
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// EnableDelayedNameRemoval delays the removal of the __name__ label to the last step of the query evaluation.
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// This is useful in certain scenarios where the __name__ label must be preserved or where applying a
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// regex-matcher to the __name__ label may otherwise lead to duplicate labelset errors.
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EnableDelayedNameRemoval bool
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}
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// Engine handles the lifetime of queries from beginning to end.
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// It is connected to a querier.
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type Engine struct {
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logger *slog.Logger
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metrics *engineMetrics
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timeout time.Duration
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maxSamplesPerQuery int
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activeQueryTracker QueryTracker
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queryLogger QueryLogger
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queryLoggerLock sync.RWMutex
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lookbackDelta time.Duration
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noStepSubqueryIntervalFn func(rangeMillis int64) int64
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enableAtModifier bool
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enableNegativeOffset bool
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enablePerStepStats bool
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enableDelayedNameRemoval bool
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}
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// NewEngine returns a new engine.
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func NewEngine(opts EngineOpts) *Engine {
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if opts.Logger == nil {
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opts.Logger = promslog.NewNopLogger()
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}
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queryResultSummary := prometheus.NewSummaryVec(prometheus.SummaryOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "query_duration_seconds",
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Help: "Query timings",
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Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
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},
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[]string{"slice"},
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)
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metrics := &engineMetrics{
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currentQueries: prometheus.NewGauge(prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "queries",
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Help: "The current number of queries being executed or waiting.",
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}),
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queryLogEnabled: prometheus.NewGauge(prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "query_log_enabled",
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Help: "State of the query log.",
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}),
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queryLogFailures: prometheus.NewCounter(prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "query_log_failures_total",
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Help: "The number of query log failures.",
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}),
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maxConcurrentQueries: prometheus.NewGauge(prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "queries_concurrent_max",
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Help: "The max number of concurrent queries.",
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}),
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querySamples: prometheus.NewCounter(prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "query_samples_total",
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Help: "The total number of samples loaded by all queries.",
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}),
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queryQueueTime: queryResultSummary.WithLabelValues("queue_time"),
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queryPrepareTime: queryResultSummary.WithLabelValues("prepare_time"),
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queryInnerEval: queryResultSummary.WithLabelValues("inner_eval"),
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queryResultSort: queryResultSummary.WithLabelValues("result_sort"),
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}
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if t := opts.ActiveQueryTracker; t != nil {
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metrics.maxConcurrentQueries.Set(float64(t.GetMaxConcurrent()))
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} else {
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metrics.maxConcurrentQueries.Set(-1)
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}
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if opts.LookbackDelta == 0 {
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opts.LookbackDelta = defaultLookbackDelta
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if l := opts.Logger; l != nil {
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l.Debug("Lookback delta is zero, setting to default value", "value", defaultLookbackDelta)
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}
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}
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if opts.Reg != nil {
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opts.Reg.MustRegister(
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metrics.currentQueries,
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metrics.maxConcurrentQueries,
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metrics.queryLogEnabled,
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metrics.queryLogFailures,
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metrics.querySamples,
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queryResultSummary,
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)
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}
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return &Engine{
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timeout: opts.Timeout,
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logger: opts.Logger,
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metrics: metrics,
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maxSamplesPerQuery: opts.MaxSamples,
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activeQueryTracker: opts.ActiveQueryTracker,
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lookbackDelta: opts.LookbackDelta,
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noStepSubqueryIntervalFn: opts.NoStepSubqueryIntervalFn,
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enableAtModifier: opts.EnableAtModifier,
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enableNegativeOffset: opts.EnableNegativeOffset,
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enablePerStepStats: opts.EnablePerStepStats,
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enableDelayedNameRemoval: opts.EnableDelayedNameRemoval,
|
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}
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}
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// Close closes ng.
|
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func (ng *Engine) Close() error {
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if ng == nil {
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return nil
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}
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|
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if ng.activeQueryTracker != nil {
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return ng.activeQueryTracker.Close()
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}
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return nil
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}
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|
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// SetQueryLogger sets the query logger.
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func (ng *Engine) SetQueryLogger(l QueryLogger) {
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ng.queryLoggerLock.Lock()
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defer ng.queryLoggerLock.Unlock()
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|
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if ng.queryLogger != nil {
|
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// An error closing the old file descriptor should
|
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// not make reload fail; only log a warning.
|
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err := ng.queryLogger.Close()
|
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if err != nil {
|
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ng.logger.Warn("Error while closing the previous query log file", "err", err)
|
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}
|
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}
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|
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ng.queryLogger = l
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|
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if l != nil {
|
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ng.metrics.queryLogEnabled.Set(1)
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} else {
|
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ng.metrics.queryLogEnabled.Set(0)
|
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}
|
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}
|
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|
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// NewInstantQuery returns an evaluation query for the given expression at the given time.
|
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func (ng *Engine) NewInstantQuery(ctx context.Context, q storage.Queryable, opts QueryOpts, qs string, ts time.Time) (Query, error) {
|
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pExpr, qry := ng.newQuery(q, qs, opts, ts, ts, 0)
|
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finishQueue, err := ng.queueActive(ctx, qry)
|
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if err != nil {
|
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return nil, err
|
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}
|
|
defer finishQueue()
|
|
expr, err := parser.ParseExpr(qs)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
if err := ng.validateOpts(expr); err != nil {
|
|
return nil, err
|
|
}
|
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*pExpr = PreprocessExpr(expr, ts, ts)
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|
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return qry, nil
|
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}
|
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|
|
// NewRangeQuery returns an evaluation query for the given time range and with
|
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// the resolution set by the interval.
|
|
func (ng *Engine) NewRangeQuery(ctx context.Context, q storage.Queryable, opts QueryOpts, qs string, start, end time.Time, interval time.Duration) (Query, error) {
|
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pExpr, qry := ng.newQuery(q, qs, opts, start, end, interval)
|
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finishQueue, err := ng.queueActive(ctx, qry)
|
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if err != nil {
|
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return nil, err
|
|
}
|
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defer finishQueue()
|
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expr, err := parser.ParseExpr(qs)
|
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if err != nil {
|
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return nil, err
|
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}
|
|
if err := ng.validateOpts(expr); err != nil {
|
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return nil, err
|
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}
|
|
if expr.Type() != parser.ValueTypeVector && expr.Type() != parser.ValueTypeScalar {
|
|
return nil, fmt.Errorf("invalid expression type %q for range query, must be Scalar or instant Vector", parser.DocumentedType(expr.Type()))
|
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}
|
|
*pExpr = PreprocessExpr(expr, start, end)
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|
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return qry, nil
|
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}
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|
|
func (ng *Engine) newQuery(q storage.Queryable, qs string, opts QueryOpts, start, end time.Time, interval time.Duration) (*parser.Expr, *query) {
|
|
if opts == nil {
|
|
opts = NewPrometheusQueryOpts(false, 0)
|
|
}
|
|
|
|
lookbackDelta := opts.LookbackDelta()
|
|
if lookbackDelta <= 0 {
|
|
lookbackDelta = ng.lookbackDelta
|
|
}
|
|
|
|
es := &parser.EvalStmt{
|
|
Start: start,
|
|
End: end,
|
|
Interval: interval,
|
|
LookbackDelta: lookbackDelta,
|
|
}
|
|
qry := &query{
|
|
q: qs,
|
|
stmt: es,
|
|
ng: ng,
|
|
stats: stats.NewQueryTimers(),
|
|
sampleStats: stats.NewQuerySamples(ng.enablePerStepStats && opts.EnablePerStepStats()),
|
|
queryable: q,
|
|
}
|
|
return &es.Expr, qry
|
|
}
|
|
|
|
var (
|
|
ErrValidationAtModifierDisabled = errors.New("@ modifier is disabled")
|
|
ErrValidationNegativeOffsetDisabled = errors.New("negative offset is disabled")
|
|
)
|
|
|
|
func (ng *Engine) validateOpts(expr parser.Expr) error {
|
|
if ng.enableAtModifier && ng.enableNegativeOffset {
|
|
return nil
|
|
}
|
|
|
|
var atModifierUsed, negativeOffsetUsed bool
|
|
|
|
var validationErr error
|
|
parser.Inspect(expr, func(node parser.Node, path []parser.Node) error {
|
|
switch n := node.(type) {
|
|
case *parser.VectorSelector:
|
|
if n.Timestamp != nil || n.StartOrEnd == parser.START || n.StartOrEnd == parser.END {
|
|
atModifierUsed = true
|
|
}
|
|
if n.OriginalOffset < 0 {
|
|
negativeOffsetUsed = true
|
|
}
|
|
|
|
case *parser.MatrixSelector:
|
|
vs := n.VectorSelector.(*parser.VectorSelector)
|
|
if vs.Timestamp != nil || vs.StartOrEnd == parser.START || vs.StartOrEnd == parser.END {
|
|
atModifierUsed = true
|
|
}
|
|
if vs.OriginalOffset < 0 {
|
|
negativeOffsetUsed = true
|
|
}
|
|
|
|
case *parser.SubqueryExpr:
|
|
if n.Timestamp != nil || n.StartOrEnd == parser.START || n.StartOrEnd == parser.END {
|
|
atModifierUsed = true
|
|
}
|
|
if n.OriginalOffset < 0 {
|
|
negativeOffsetUsed = true
|
|
}
|
|
}
|
|
|
|
if atModifierUsed && !ng.enableAtModifier {
|
|
validationErr = ErrValidationAtModifierDisabled
|
|
return validationErr
|
|
}
|
|
if negativeOffsetUsed && !ng.enableNegativeOffset {
|
|
validationErr = ErrValidationNegativeOffsetDisabled
|
|
return validationErr
|
|
}
|
|
|
|
return nil
|
|
})
|
|
|
|
return validationErr
|
|
}
|
|
|
|
// NewTestQuery injects special behaviour into Query for testing.
|
|
func (ng *Engine) NewTestQuery(f func(context.Context) error) Query {
|
|
qry := &query{
|
|
q: "test statement",
|
|
stmt: parser.TestStmt(f),
|
|
ng: ng,
|
|
stats: stats.NewQueryTimers(),
|
|
sampleStats: stats.NewQuerySamples(ng.enablePerStepStats),
|
|
}
|
|
return qry
|
|
}
|
|
|
|
// exec executes the query.
|
|
//
|
|
// At this point per query only one EvalStmt is evaluated. Alert and record
|
|
// statements are not handled by the Engine.
|
|
func (ng *Engine) exec(ctx context.Context, q *query) (v parser.Value, ws annotations.Annotations, err error) {
|
|
ng.metrics.currentQueries.Inc()
|
|
defer func() {
|
|
ng.metrics.currentQueries.Dec()
|
|
ng.metrics.querySamples.Add(float64(q.sampleStats.TotalSamples))
|
|
}()
|
|
|
|
ctx, cancel := context.WithTimeout(ctx, ng.timeout)
|
|
q.cancel = cancel
|
|
|
|
defer func() {
|
|
ng.queryLoggerLock.RLock()
|
|
if l := ng.queryLogger; l != nil {
|
|
params := make(map[string]interface{}, 4)
|
|
params["query"] = q.q
|
|
if eq, ok := q.Statement().(*parser.EvalStmt); ok {
|
|
params["start"] = formatDate(eq.Start)
|
|
params["end"] = formatDate(eq.End)
|
|
// The step provided by the user is in seconds.
|
|
params["step"] = int64(eq.Interval / (time.Second / time.Nanosecond))
|
|
}
|
|
l.With("params", params)
|
|
if err != nil {
|
|
l.With("error", err)
|
|
}
|
|
l.With("stats", stats.NewQueryStats(q.Stats()))
|
|
if span := trace.SpanFromContext(ctx); span != nil {
|
|
l.With("spanID", span.SpanContext().SpanID())
|
|
}
|
|
if origin := ctx.Value(QueryOrigin{}); origin != nil {
|
|
for k, v := range origin.(map[string]interface{}) {
|
|
l.With(k, v)
|
|
}
|
|
}
|
|
l.Info("promql query logged")
|
|
// TODO: @tjhop -- do we still need this metric/error log if logger doesn't return errors?
|
|
// ng.metrics.queryLogFailures.Inc()
|
|
// ng.logger.Error("can't log query", "err", err)
|
|
}
|
|
ng.queryLoggerLock.RUnlock()
|
|
}()
|
|
|
|
execSpanTimer, ctx := q.stats.GetSpanTimer(ctx, stats.ExecTotalTime)
|
|
defer execSpanTimer.Finish()
|
|
|
|
finishQueue, err := ng.queueActive(ctx, q)
|
|
if err != nil {
|
|
return nil, nil, err
|
|
}
|
|
defer finishQueue()
|
|
|
|
// Cancel when execution is done or an error was raised.
|
|
defer q.cancel()
|
|
|
|
evalSpanTimer, ctx := q.stats.GetSpanTimer(ctx, stats.EvalTotalTime)
|
|
defer evalSpanTimer.Finish()
|
|
|
|
// The base context might already be canceled on the first iteration (e.g. during shutdown).
|
|
if err := contextDone(ctx, env); err != nil {
|
|
return nil, nil, err
|
|
}
|
|
|
|
switch s := q.Statement().(type) {
|
|
case *parser.EvalStmt:
|
|
return ng.execEvalStmt(ctx, q, s)
|
|
case parser.TestStmt:
|
|
return nil, nil, s(ctx)
|
|
}
|
|
|
|
panic(fmt.Errorf("promql.Engine.exec: unhandled statement of type %T", q.Statement()))
|
|
}
|
|
|
|
// Log query in active log. The active log guarantees that we don't run over
|
|
// MaxConcurrent queries.
|
|
func (ng *Engine) queueActive(ctx context.Context, q *query) (func(), error) {
|
|
if ng.activeQueryTracker == nil {
|
|
return func() {}, nil
|
|
}
|
|
queueSpanTimer, _ := q.stats.GetSpanTimer(ctx, stats.ExecQueueTime, ng.metrics.queryQueueTime)
|
|
queryIndex, err := ng.activeQueryTracker.Insert(ctx, q.q)
|
|
queueSpanTimer.Finish()
|
|
return func() { ng.activeQueryTracker.Delete(queryIndex) }, err
|
|
}
|
|
|
|
func timeMilliseconds(t time.Time) int64 {
|
|
return t.UnixNano() / int64(time.Millisecond/time.Nanosecond)
|
|
}
|
|
|
|
func durationMilliseconds(d time.Duration) int64 {
|
|
return int64(d / (time.Millisecond / time.Nanosecond))
|
|
}
|
|
|
|
// execEvalStmt evaluates the expression of an evaluation statement for the given time range.
|
|
func (ng *Engine) execEvalStmt(ctx context.Context, query *query, s *parser.EvalStmt) (parser.Value, annotations.Annotations, error) {
|
|
prepareSpanTimer, ctxPrepare := query.stats.GetSpanTimer(ctx, stats.QueryPreparationTime, ng.metrics.queryPrepareTime)
|
|
mint, maxt := FindMinMaxTime(s)
|
|
querier, err := query.queryable.Querier(mint, maxt)
|
|
if err != nil {
|
|
prepareSpanTimer.Finish()
|
|
return nil, nil, err
|
|
}
|
|
defer querier.Close()
|
|
|
|
ng.populateSeries(ctxPrepare, querier, s)
|
|
prepareSpanTimer.Finish()
|
|
|
|
// Modify the offset of vector and matrix selectors for the @ modifier
|
|
// w.r.t. the start time since only 1 evaluation will be done on them.
|
|
setOffsetForAtModifier(timeMilliseconds(s.Start), s.Expr)
|
|
evalSpanTimer, ctxInnerEval := query.stats.GetSpanTimer(ctx, stats.InnerEvalTime, ng.metrics.queryInnerEval)
|
|
// Instant evaluation. This is executed as a range evaluation with one step.
|
|
if s.Start == s.End && s.Interval == 0 {
|
|
start := timeMilliseconds(s.Start)
|
|
evaluator := &evaluator{
|
|
startTimestamp: start,
|
|
endTimestamp: start,
|
|
interval: 1,
|
|
maxSamples: ng.maxSamplesPerQuery,
|
|
logger: ng.logger,
|
|
lookbackDelta: s.LookbackDelta,
|
|
samplesStats: query.sampleStats,
|
|
noStepSubqueryIntervalFn: ng.noStepSubqueryIntervalFn,
|
|
enableDelayedNameRemoval: ng.enableDelayedNameRemoval,
|
|
querier: querier,
|
|
}
|
|
query.sampleStats.InitStepTracking(start, start, 1)
|
|
|
|
val, warnings, err := evaluator.Eval(ctxInnerEval, s.Expr)
|
|
|
|
evalSpanTimer.Finish()
|
|
|
|
if err != nil {
|
|
return nil, warnings, err
|
|
}
|
|
|
|
var mat Matrix
|
|
|
|
switch result := val.(type) {
|
|
case Matrix:
|
|
mat = result
|
|
case String:
|
|
return result, warnings, nil
|
|
default:
|
|
panic(fmt.Errorf("promql.Engine.exec: invalid expression type %q", val.Type()))
|
|
}
|
|
|
|
query.matrix = mat
|
|
switch s.Expr.Type() {
|
|
case parser.ValueTypeVector:
|
|
// Convert matrix with one value per series into vector.
|
|
vector := make(Vector, len(mat))
|
|
for i, s := range mat {
|
|
// Point might have a different timestamp, force it to the evaluation
|
|
// timestamp as that is when we ran the evaluation.
|
|
if len(s.Histograms) > 0 {
|
|
vector[i] = Sample{Metric: s.Metric, H: s.Histograms[0].H, T: start, DropName: s.DropName}
|
|
} else {
|
|
vector[i] = Sample{Metric: s.Metric, F: s.Floats[0].F, T: start, DropName: s.DropName}
|
|
}
|
|
}
|
|
return vector, warnings, nil
|
|
case parser.ValueTypeScalar:
|
|
return Scalar{V: mat[0].Floats[0].F, T: start}, warnings, nil
|
|
case parser.ValueTypeMatrix:
|
|
ng.sortMatrixResult(ctx, query, mat)
|
|
return mat, warnings, nil
|
|
default:
|
|
panic(fmt.Errorf("promql.Engine.exec: unexpected expression type %q", s.Expr.Type()))
|
|
}
|
|
}
|
|
|
|
// Range evaluation.
|
|
evaluator := &evaluator{
|
|
startTimestamp: timeMilliseconds(s.Start),
|
|
endTimestamp: timeMilliseconds(s.End),
|
|
interval: durationMilliseconds(s.Interval),
|
|
maxSamples: ng.maxSamplesPerQuery,
|
|
logger: ng.logger,
|
|
lookbackDelta: s.LookbackDelta,
|
|
samplesStats: query.sampleStats,
|
|
noStepSubqueryIntervalFn: ng.noStepSubqueryIntervalFn,
|
|
enableDelayedNameRemoval: ng.enableDelayedNameRemoval,
|
|
querier: querier,
|
|
}
|
|
query.sampleStats.InitStepTracking(evaluator.startTimestamp, evaluator.endTimestamp, evaluator.interval)
|
|
val, warnings, err := evaluator.Eval(ctxInnerEval, s.Expr)
|
|
|
|
evalSpanTimer.Finish()
|
|
|
|
if err != nil {
|
|
return nil, warnings, err
|
|
}
|
|
|
|
mat, ok := val.(Matrix)
|
|
if !ok {
|
|
panic(fmt.Errorf("promql.Engine.exec: invalid expression type %q", val.Type()))
|
|
}
|
|
query.matrix = mat
|
|
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
return nil, warnings, err
|
|
}
|
|
|
|
// TODO(fabxc): where to ensure metric labels are a copy from the storage internals.
|
|
ng.sortMatrixResult(ctx, query, mat)
|
|
|
|
return mat, warnings, nil
|
|
}
|
|
|
|
func (ng *Engine) sortMatrixResult(ctx context.Context, query *query, mat Matrix) {
|
|
sortSpanTimer, _ := query.stats.GetSpanTimer(ctx, stats.ResultSortTime, ng.metrics.queryResultSort)
|
|
sort.Sort(mat)
|
|
sortSpanTimer.Finish()
|
|
}
|
|
|
|
// subqueryTimes returns the sum of offsets and ranges of all subqueries in the path.
|
|
// If the @ modifier is used, then the offset and range is w.r.t. that timestamp
|
|
// (i.e. the sum is reset when we have @ modifier).
|
|
// The returned *int64 is the closest timestamp that was seen. nil for no @ modifier.
|
|
func subqueryTimes(path []parser.Node) (time.Duration, time.Duration, *int64) {
|
|
var (
|
|
subqOffset, subqRange time.Duration
|
|
ts int64 = math.MaxInt64
|
|
)
|
|
for _, node := range path {
|
|
if n, ok := node.(*parser.SubqueryExpr); ok {
|
|
subqOffset += n.OriginalOffset
|
|
subqRange += n.Range
|
|
if n.Timestamp != nil {
|
|
// The @ modifier on subquery invalidates all the offset and
|
|
// range till now. Hence resetting it here.
|
|
subqOffset = n.OriginalOffset
|
|
subqRange = n.Range
|
|
ts = *n.Timestamp
|
|
}
|
|
}
|
|
}
|
|
var tsp *int64
|
|
if ts != math.MaxInt64 {
|
|
tsp = &ts
|
|
}
|
|
return subqOffset, subqRange, tsp
|
|
}
|
|
|
|
// FindMinMaxTime returns the time in milliseconds of the earliest and latest point in time the statement will try to process.
|
|
// This takes into account offsets, @ modifiers, and range selectors.
|
|
// If the statement does not select series, then FindMinMaxTime returns (0, 0).
|
|
func FindMinMaxTime(s *parser.EvalStmt) (int64, int64) {
|
|
var minTimestamp, maxTimestamp int64 = math.MaxInt64, math.MinInt64
|
|
// Whenever a MatrixSelector is evaluated, evalRange is set to the corresponding range.
|
|
// The evaluation of the VectorSelector inside then evaluates the given range and unsets
|
|
// the variable.
|
|
var evalRange time.Duration
|
|
parser.Inspect(s.Expr, func(node parser.Node, path []parser.Node) error {
|
|
switch n := node.(type) {
|
|
case *parser.VectorSelector:
|
|
start, end := getTimeRangesForSelector(s, n, path, evalRange)
|
|
if start < minTimestamp {
|
|
minTimestamp = start
|
|
}
|
|
if end > maxTimestamp {
|
|
maxTimestamp = end
|
|
}
|
|
evalRange = 0
|
|
case *parser.MatrixSelector:
|
|
evalRange = n.Range
|
|
}
|
|
return nil
|
|
})
|
|
|
|
if maxTimestamp == math.MinInt64 {
|
|
// This happens when there was no selector. Hence no time range to select.
|
|
minTimestamp = 0
|
|
maxTimestamp = 0
|
|
}
|
|
|
|
return minTimestamp, maxTimestamp
|
|
}
|
|
|
|
func getTimeRangesForSelector(s *parser.EvalStmt, n *parser.VectorSelector, path []parser.Node, evalRange time.Duration) (int64, int64) {
|
|
start, end := timestamp.FromTime(s.Start), timestamp.FromTime(s.End)
|
|
subqOffset, subqRange, subqTs := subqueryTimes(path)
|
|
|
|
if subqTs != nil {
|
|
// The timestamp on the subquery overrides the eval statement time ranges.
|
|
start = *subqTs
|
|
end = *subqTs
|
|
}
|
|
|
|
if n.Timestamp != nil {
|
|
// The timestamp on the selector overrides everything.
|
|
start = *n.Timestamp
|
|
end = *n.Timestamp
|
|
} else {
|
|
offsetMilliseconds := durationMilliseconds(subqOffset)
|
|
start = start - offsetMilliseconds - durationMilliseconds(subqRange)
|
|
end -= offsetMilliseconds
|
|
}
|
|
|
|
if evalRange == 0 {
|
|
// Reduce the start by one fewer ms than the lookback delta
|
|
// because wo want to exclude samples that are precisely the
|
|
// lookback delta before the eval time.
|
|
start -= durationMilliseconds(s.LookbackDelta) - 1
|
|
} else {
|
|
// For all matrix queries we want to ensure that we have
|
|
// (end-start) + range selected this way we have `range` data
|
|
// before the start time. We subtract one from the range to
|
|
// exclude samples positioned directly at the lower boundary of
|
|
// the range.
|
|
start -= durationMilliseconds(evalRange) - 1
|
|
}
|
|
|
|
offsetMilliseconds := durationMilliseconds(n.OriginalOffset)
|
|
start -= offsetMilliseconds
|
|
end -= offsetMilliseconds
|
|
|
|
return start, end
|
|
}
|
|
|
|
func (ng *Engine) getLastSubqueryInterval(path []parser.Node) time.Duration {
|
|
var interval time.Duration
|
|
for _, node := range path {
|
|
if n, ok := node.(*parser.SubqueryExpr); ok {
|
|
interval = n.Step
|
|
if n.Step == 0 {
|
|
interval = time.Duration(ng.noStepSubqueryIntervalFn(durationMilliseconds(n.Range))) * time.Millisecond
|
|
}
|
|
}
|
|
}
|
|
return interval
|
|
}
|
|
|
|
func (ng *Engine) populateSeries(ctx context.Context, querier storage.Querier, s *parser.EvalStmt) {
|
|
// Whenever a MatrixSelector is evaluated, evalRange is set to the corresponding range.
|
|
// The evaluation of the VectorSelector inside then evaluates the given range and unsets
|
|
// the variable.
|
|
var evalRange time.Duration
|
|
|
|
parser.Inspect(s.Expr, func(node parser.Node, path []parser.Node) error {
|
|
switch n := node.(type) {
|
|
case *parser.VectorSelector:
|
|
start, end := getTimeRangesForSelector(s, n, path, evalRange)
|
|
interval := ng.getLastSubqueryInterval(path)
|
|
if interval == 0 {
|
|
interval = s.Interval
|
|
}
|
|
hints := &storage.SelectHints{
|
|
Start: start,
|
|
End: end,
|
|
Step: durationMilliseconds(interval),
|
|
Range: durationMilliseconds(evalRange),
|
|
Func: extractFuncFromPath(path),
|
|
}
|
|
evalRange = 0
|
|
hints.By, hints.Grouping = extractGroupsFromPath(path)
|
|
n.UnexpandedSeriesSet = querier.Select(ctx, false, hints, n.LabelMatchers...)
|
|
|
|
case *parser.MatrixSelector:
|
|
evalRange = n.Range
|
|
}
|
|
return nil
|
|
})
|
|
}
|
|
|
|
// extractFuncFromPath walks up the path and searches for the first instance of
|
|
// a function or aggregation.
|
|
func extractFuncFromPath(p []parser.Node) string {
|
|
if len(p) == 0 {
|
|
return ""
|
|
}
|
|
switch n := p[len(p)-1].(type) {
|
|
case *parser.AggregateExpr:
|
|
return n.Op.String()
|
|
case *parser.Call:
|
|
return n.Func.Name
|
|
case *parser.BinaryExpr:
|
|
// If we hit a binary expression we terminate since we only care about functions
|
|
// or aggregations over a single metric.
|
|
return ""
|
|
}
|
|
return extractFuncFromPath(p[:len(p)-1])
|
|
}
|
|
|
|
// extractGroupsFromPath parses vector outer function and extracts grouping information if by or without was used.
|
|
func extractGroupsFromPath(p []parser.Node) (bool, []string) {
|
|
if len(p) == 0 {
|
|
return false, nil
|
|
}
|
|
if n, ok := p[len(p)-1].(*parser.AggregateExpr); ok {
|
|
return !n.Without, n.Grouping
|
|
}
|
|
return false, nil
|
|
}
|
|
|
|
// checkAndExpandSeriesSet expands expr's UnexpandedSeriesSet into expr's Series.
|
|
// If the Series field is already non-nil, it's a no-op.
|
|
func checkAndExpandSeriesSet(ctx context.Context, expr parser.Expr) (annotations.Annotations, error) {
|
|
switch e := expr.(type) {
|
|
case *parser.MatrixSelector:
|
|
return checkAndExpandSeriesSet(ctx, e.VectorSelector)
|
|
case *parser.VectorSelector:
|
|
if e.Series != nil {
|
|
return nil, nil
|
|
}
|
|
span := trace.SpanFromContext(ctx)
|
|
span.AddEvent("expand start", trace.WithAttributes(attribute.String("selector", e.String())))
|
|
series, ws, err := expandSeriesSet(ctx, e.UnexpandedSeriesSet)
|
|
if e.SkipHistogramBuckets {
|
|
for i := range series {
|
|
series[i] = newHistogramStatsSeries(series[i])
|
|
}
|
|
}
|
|
e.Series = series
|
|
span.AddEvent("expand end", trace.WithAttributes(attribute.Int("num_series", len(series))))
|
|
return ws, err
|
|
}
|
|
return nil, nil
|
|
}
|
|
|
|
func expandSeriesSet(ctx context.Context, it storage.SeriesSet) (res []storage.Series, ws annotations.Annotations, err error) {
|
|
for it.Next() {
|
|
select {
|
|
case <-ctx.Done():
|
|
return nil, nil, ctx.Err()
|
|
default:
|
|
}
|
|
res = append(res, it.At())
|
|
}
|
|
return res, it.Warnings(), it.Err()
|
|
}
|
|
|
|
type errWithWarnings struct {
|
|
err error
|
|
warnings annotations.Annotations
|
|
}
|
|
|
|
func (e errWithWarnings) Error() string { return e.err.Error() }
|
|
|
|
// An evaluator evaluates the given expressions over the given fixed
|
|
// timestamps. It is attached to an engine through which it connects to a
|
|
// querier and reports errors. On timeout or cancellation of its context it
|
|
// terminates.
|
|
type evaluator struct {
|
|
startTimestamp int64 // Start time in milliseconds.
|
|
endTimestamp int64 // End time in milliseconds.
|
|
interval int64 // Interval in milliseconds.
|
|
|
|
maxSamples int
|
|
currentSamples int
|
|
logger *slog.Logger
|
|
lookbackDelta time.Duration
|
|
samplesStats *stats.QuerySamples
|
|
noStepSubqueryIntervalFn func(rangeMillis int64) int64
|
|
enableDelayedNameRemoval bool
|
|
querier storage.Querier
|
|
}
|
|
|
|
// errorf causes a panic with the input formatted into an error.
|
|
func (ev *evaluator) errorf(format string, args ...interface{}) {
|
|
ev.error(fmt.Errorf(format, args...))
|
|
}
|
|
|
|
// error causes a panic with the given error.
|
|
func (ev *evaluator) error(err error) {
|
|
panic(err)
|
|
}
|
|
|
|
// recover is the handler that turns panics into returns from the top level of evaluation.
|
|
func (ev *evaluator) recover(expr parser.Expr, ws *annotations.Annotations, errp *error) {
|
|
e := recover()
|
|
if e == nil {
|
|
return
|
|
}
|
|
|
|
switch err := e.(type) {
|
|
case runtime.Error:
|
|
// Print the stack trace but do not inhibit the running application.
|
|
buf := make([]byte, 64<<10)
|
|
buf = buf[:runtime.Stack(buf, false)]
|
|
|
|
ev.logger.Error("runtime panic during query evaluation", "expr", expr.String(), "err", e, "stacktrace", string(buf))
|
|
*errp = fmt.Errorf("unexpected error: %w", err)
|
|
case errWithWarnings:
|
|
*errp = err.err
|
|
ws.Merge(err.warnings)
|
|
case error:
|
|
*errp = err
|
|
default:
|
|
*errp = fmt.Errorf("%v", err)
|
|
}
|
|
}
|
|
|
|
func (ev *evaluator) Eval(ctx context.Context, expr parser.Expr) (v parser.Value, ws annotations.Annotations, err error) {
|
|
defer ev.recover(expr, &ws, &err)
|
|
|
|
v, ws = ev.eval(ctx, expr)
|
|
if ev.enableDelayedNameRemoval {
|
|
ev.cleanupMetricLabels(v)
|
|
}
|
|
return v, ws, nil
|
|
}
|
|
|
|
// EvalSeriesHelper stores extra information about a series.
|
|
type EvalSeriesHelper struct {
|
|
// Used to map left-hand to right-hand in binary operations.
|
|
signature string
|
|
}
|
|
|
|
// EvalNodeHelper stores extra information and caches for evaluating a single node across steps.
|
|
type EvalNodeHelper struct {
|
|
// Evaluation timestamp.
|
|
Ts int64
|
|
// Vector that can be used for output.
|
|
Out Vector
|
|
|
|
// Caches.
|
|
// funcHistogramQuantile for classic histograms.
|
|
signatureToMetricWithBuckets map[string]*metricWithBuckets
|
|
|
|
lb *labels.Builder
|
|
lblBuf []byte
|
|
lblResultBuf []byte
|
|
|
|
// For binary vector matching.
|
|
rightSigs map[string]Sample
|
|
matchedSigs map[string]map[uint64]struct{}
|
|
resultMetric map[string]labels.Labels
|
|
|
|
// Additional options for the evaluation.
|
|
enableDelayedNameRemoval bool
|
|
}
|
|
|
|
func (enh *EvalNodeHelper) resetBuilder(lbls labels.Labels) {
|
|
if enh.lb == nil {
|
|
enh.lb = labels.NewBuilder(lbls)
|
|
} else {
|
|
enh.lb.Reset(lbls)
|
|
}
|
|
}
|
|
|
|
// rangeEval evaluates the given expressions, and then for each step calls
|
|
// the given funcCall with the values computed for each expression at that
|
|
// step. The return value is the combination into time series of all the
|
|
// function call results.
|
|
// The prepSeries function (if provided) can be used to prepare the helper
|
|
// for each series, then passed to each call funcCall.
|
|
func (ev *evaluator) rangeEval(ctx context.Context, prepSeries func(labels.Labels, *EvalSeriesHelper), funcCall func([]parser.Value, [][]EvalSeriesHelper, *EvalNodeHelper) (Vector, annotations.Annotations), exprs ...parser.Expr) (Matrix, annotations.Annotations) {
|
|
numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
|
|
matrixes := make([]Matrix, len(exprs))
|
|
origMatrixes := make([]Matrix, len(exprs))
|
|
originalNumSamples := ev.currentSamples
|
|
|
|
var warnings annotations.Annotations
|
|
for i, e := range exprs {
|
|
// Functions will take string arguments from the expressions, not the values.
|
|
if e != nil && e.Type() != parser.ValueTypeString {
|
|
// ev.currentSamples will be updated to the correct value within the ev.eval call.
|
|
val, ws := ev.eval(ctx, e)
|
|
warnings.Merge(ws)
|
|
matrixes[i] = val.(Matrix)
|
|
|
|
// Keep a copy of the original point slices so that they
|
|
// can be returned to the pool.
|
|
origMatrixes[i] = make(Matrix, len(matrixes[i]))
|
|
copy(origMatrixes[i], matrixes[i])
|
|
}
|
|
}
|
|
|
|
vectors := make([]Vector, len(exprs)) // Input vectors for the function.
|
|
args := make([]parser.Value, len(exprs)) // Argument to function.
|
|
// Create an output vector that is as big as the input matrix with
|
|
// the most time series.
|
|
biggestLen := 1
|
|
for i := range exprs {
|
|
vectors[i] = make(Vector, 0, len(matrixes[i]))
|
|
if len(matrixes[i]) > biggestLen {
|
|
biggestLen = len(matrixes[i])
|
|
}
|
|
}
|
|
enh := &EvalNodeHelper{Out: make(Vector, 0, biggestLen), enableDelayedNameRemoval: ev.enableDelayedNameRemoval}
|
|
type seriesAndTimestamp struct {
|
|
Series
|
|
ts int64
|
|
}
|
|
seriess := make(map[uint64]seriesAndTimestamp, biggestLen) // Output series by series hash.
|
|
tempNumSamples := ev.currentSamples
|
|
|
|
var (
|
|
seriesHelpers [][]EvalSeriesHelper
|
|
bufHelpers [][]EvalSeriesHelper // Buffer updated on each step
|
|
)
|
|
|
|
// If the series preparation function is provided, we should run it for
|
|
// every single series in the matrix.
|
|
if prepSeries != nil {
|
|
seriesHelpers = make([][]EvalSeriesHelper, len(exprs))
|
|
bufHelpers = make([][]EvalSeriesHelper, len(exprs))
|
|
|
|
for i := range exprs {
|
|
seriesHelpers[i] = make([]EvalSeriesHelper, len(matrixes[i]))
|
|
bufHelpers[i] = make([]EvalSeriesHelper, len(matrixes[i]))
|
|
|
|
for si, series := range matrixes[i] {
|
|
prepSeries(series.Metric, &seriesHelpers[i][si])
|
|
}
|
|
}
|
|
}
|
|
|
|
for ts := ev.startTimestamp; ts <= ev.endTimestamp; ts += ev.interval {
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
ev.error(err)
|
|
}
|
|
// Reset number of samples in memory after each timestamp.
|
|
ev.currentSamples = tempNumSamples
|
|
// Gather input vectors for this timestamp.
|
|
for i := range exprs {
|
|
var bh []EvalSeriesHelper
|
|
var sh []EvalSeriesHelper
|
|
if prepSeries != nil {
|
|
bh = bufHelpers[i][:0]
|
|
sh = seriesHelpers[i]
|
|
}
|
|
vectors[i], bh = ev.gatherVector(ts, matrixes[i], vectors[i], bh, sh)
|
|
args[i] = vectors[i]
|
|
if prepSeries != nil {
|
|
bufHelpers[i] = bh
|
|
}
|
|
}
|
|
|
|
// Make the function call.
|
|
enh.Ts = ts
|
|
result, ws := funcCall(args, bufHelpers, enh)
|
|
enh.Out = result[:0] // Reuse result vector.
|
|
warnings.Merge(ws)
|
|
|
|
vecNumSamples := result.TotalSamples()
|
|
ev.currentSamples += vecNumSamples
|
|
// When we reset currentSamples to tempNumSamples during the next iteration of the loop it also
|
|
// needs to include the samples from the result here, as they're still in memory.
|
|
tempNumSamples += vecNumSamples
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
|
|
// If this could be an instant query, shortcut so as not to change sort order.
|
|
if ev.endTimestamp == ev.startTimestamp {
|
|
if !ev.enableDelayedNameRemoval && result.ContainsSameLabelset() {
|
|
ev.errorf("vector cannot contain metrics with the same labelset")
|
|
}
|
|
mat := make(Matrix, len(result))
|
|
for i, s := range result {
|
|
if s.H == nil {
|
|
mat[i] = Series{Metric: s.Metric, Floats: []FPoint{{T: ts, F: s.F}}, DropName: s.DropName}
|
|
} else {
|
|
mat[i] = Series{Metric: s.Metric, Histograms: []HPoint{{T: ts, H: s.H}}, DropName: s.DropName}
|
|
}
|
|
}
|
|
ev.currentSamples = originalNumSamples + mat.TotalSamples()
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
return mat, warnings
|
|
}
|
|
|
|
// Add samples in output vector to output series.
|
|
for _, sample := range result {
|
|
h := sample.Metric.Hash()
|
|
ss, ok := seriess[h]
|
|
if ok {
|
|
if ss.ts == ts { // If we've seen this output series before at this timestamp, it's a duplicate.
|
|
ev.errorf("vector cannot contain metrics with the same labelset")
|
|
}
|
|
ss.ts = ts
|
|
} else {
|
|
ss = seriesAndTimestamp{Series{Metric: sample.Metric, DropName: sample.DropName}, ts}
|
|
}
|
|
addToSeries(&ss.Series, enh.Ts, sample.F, sample.H, numSteps)
|
|
seriess[h] = ss
|
|
}
|
|
}
|
|
|
|
// Reuse the original point slices.
|
|
for _, m := range origMatrixes {
|
|
for _, s := range m {
|
|
putFPointSlice(s.Floats)
|
|
putHPointSlice(s.Histograms)
|
|
}
|
|
}
|
|
// Assemble the output matrix. By the time we get here we know we don't have too many samples.
|
|
mat := make(Matrix, 0, len(seriess))
|
|
for _, ss := range seriess {
|
|
mat = append(mat, ss.Series)
|
|
}
|
|
ev.currentSamples = originalNumSamples + mat.TotalSamples()
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
return mat, warnings
|
|
}
|
|
|
|
func (ev *evaluator) rangeEvalAgg(ctx context.Context, aggExpr *parser.AggregateExpr, sortedGrouping []string, inputMatrix Matrix, param float64) (Matrix, annotations.Annotations) {
|
|
// Keep a copy of the original point slice so that it can be returned to the pool.
|
|
origMatrix := slices.Clone(inputMatrix)
|
|
defer func() {
|
|
for _, s := range origMatrix {
|
|
putFPointSlice(s.Floats)
|
|
putHPointSlice(s.Histograms)
|
|
}
|
|
}()
|
|
|
|
var warnings annotations.Annotations
|
|
|
|
enh := &EvalNodeHelper{enableDelayedNameRemoval: ev.enableDelayedNameRemoval}
|
|
tempNumSamples := ev.currentSamples
|
|
|
|
// Create a mapping from input series to output groups.
|
|
buf := make([]byte, 0, 1024)
|
|
groupToResultIndex := make(map[uint64]int)
|
|
seriesToResult := make([]int, len(inputMatrix))
|
|
var result Matrix
|
|
|
|
groupCount := 0
|
|
for si, series := range inputMatrix {
|
|
var groupingKey uint64
|
|
groupingKey, buf = generateGroupingKey(series.Metric, sortedGrouping, aggExpr.Without, buf)
|
|
index, ok := groupToResultIndex[groupingKey]
|
|
// Add a new group if it doesn't exist.
|
|
if !ok {
|
|
if aggExpr.Op != parser.TOPK && aggExpr.Op != parser.BOTTOMK && aggExpr.Op != parser.LIMITK && aggExpr.Op != parser.LIMIT_RATIO {
|
|
m := generateGroupingLabels(enh, series.Metric, aggExpr.Without, sortedGrouping)
|
|
result = append(result, Series{Metric: m})
|
|
}
|
|
index = groupCount
|
|
groupToResultIndex[groupingKey] = index
|
|
groupCount++
|
|
}
|
|
seriesToResult[si] = index
|
|
}
|
|
groups := make([]groupedAggregation, groupCount)
|
|
|
|
var k int
|
|
var ratio float64
|
|
var seriess map[uint64]Series
|
|
switch aggExpr.Op {
|
|
case parser.TOPK, parser.BOTTOMK, parser.LIMITK:
|
|
if !convertibleToInt64(param) {
|
|
ev.errorf("Scalar value %v overflows int64", param)
|
|
}
|
|
k = int(param)
|
|
if k > len(inputMatrix) {
|
|
k = len(inputMatrix)
|
|
}
|
|
if k < 1 {
|
|
return nil, warnings
|
|
}
|
|
seriess = make(map[uint64]Series, len(inputMatrix)) // Output series by series hash.
|
|
case parser.LIMIT_RATIO:
|
|
if math.IsNaN(param) {
|
|
ev.errorf("Ratio value %v is NaN", param)
|
|
}
|
|
switch {
|
|
case param == 0:
|
|
return nil, warnings
|
|
case param < -1.0:
|
|
ratio = -1.0
|
|
warnings.Add(annotations.NewInvalidRatioWarning(param, ratio, aggExpr.Param.PositionRange()))
|
|
case param > 1.0:
|
|
ratio = 1.0
|
|
warnings.Add(annotations.NewInvalidRatioWarning(param, ratio, aggExpr.Param.PositionRange()))
|
|
default:
|
|
ratio = param
|
|
}
|
|
seriess = make(map[uint64]Series, len(inputMatrix)) // Output series by series hash.
|
|
case parser.QUANTILE:
|
|
if math.IsNaN(param) || param < 0 || param > 1 {
|
|
warnings.Add(annotations.NewInvalidQuantileWarning(param, aggExpr.Param.PositionRange()))
|
|
}
|
|
}
|
|
|
|
for ts := ev.startTimestamp; ts <= ev.endTimestamp; ts += ev.interval {
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
ev.error(err)
|
|
}
|
|
// Reset number of samples in memory after each timestamp.
|
|
ev.currentSamples = tempNumSamples
|
|
|
|
// Make the function call.
|
|
enh.Ts = ts
|
|
var ws annotations.Annotations
|
|
switch aggExpr.Op {
|
|
case parser.TOPK, parser.BOTTOMK, parser.LIMITK, parser.LIMIT_RATIO:
|
|
result, ws = ev.aggregationK(aggExpr, k, ratio, inputMatrix, seriesToResult, groups, enh, seriess)
|
|
// If this could be an instant query, shortcut so as not to change sort order.
|
|
if ev.endTimestamp == ev.startTimestamp {
|
|
warnings.Merge(ws)
|
|
return result, warnings
|
|
}
|
|
default:
|
|
ws = ev.aggregation(aggExpr, param, inputMatrix, result, seriesToResult, groups, enh)
|
|
}
|
|
|
|
warnings.Merge(ws)
|
|
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
}
|
|
|
|
// Assemble the output matrix. By the time we get here we know we don't have too many samples.
|
|
switch aggExpr.Op {
|
|
case parser.TOPK, parser.BOTTOMK, parser.LIMITK, parser.LIMIT_RATIO:
|
|
result = make(Matrix, 0, len(seriess))
|
|
for _, ss := range seriess {
|
|
result = append(result, ss)
|
|
}
|
|
default:
|
|
// Remove empty result rows.
|
|
dst := 0
|
|
for _, series := range result {
|
|
if len(series.Floats) > 0 || len(series.Histograms) > 0 {
|
|
result[dst] = series
|
|
dst++
|
|
}
|
|
}
|
|
result = result[:dst]
|
|
}
|
|
return result, warnings
|
|
}
|
|
|
|
// evalSeries generates a Matrix between ev.startTimestamp and ev.endTimestamp (inclusive), each point spaced ev.interval apart, from series given offset.
|
|
// For every storage.Series iterator in series, the method iterates in ev.interval sized steps from ev.startTimestamp until and including ev.endTimestamp,
|
|
// collecting every corresponding sample (obtained via ev.vectorSelectorSingle) into a Series.
|
|
// All of the generated Series are collected into a Matrix, that gets returned.
|
|
func (ev *evaluator) evalSeries(ctx context.Context, series []storage.Series, offset time.Duration, recordOrigT bool) Matrix {
|
|
numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
|
|
|
|
mat := make(Matrix, 0, len(series))
|
|
var prevSS *Series
|
|
it := storage.NewMemoizedEmptyIterator(durationMilliseconds(ev.lookbackDelta))
|
|
var chkIter chunkenc.Iterator
|
|
for _, s := range series {
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
ev.error(err)
|
|
}
|
|
|
|
chkIter = s.Iterator(chkIter)
|
|
it.Reset(chkIter)
|
|
ss := Series{
|
|
Metric: s.Labels(),
|
|
}
|
|
|
|
for ts, step := ev.startTimestamp, -1; ts <= ev.endTimestamp; ts += ev.interval {
|
|
step++
|
|
origT, f, h, ok := ev.vectorSelectorSingle(it, offset, ts)
|
|
if !ok {
|
|
continue
|
|
}
|
|
|
|
if h == nil {
|
|
ev.currentSamples++
|
|
ev.samplesStats.IncrementSamplesAtStep(step, 1)
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
if ss.Floats == nil {
|
|
ss.Floats = reuseOrGetFPointSlices(prevSS, numSteps)
|
|
}
|
|
if recordOrigT {
|
|
// This is an info metric, where we want to track the original sample timestamp.
|
|
// Info metric values should be 1 by convention, therefore we can re-use this
|
|
// space in the sample.
|
|
f = float64(origT)
|
|
}
|
|
ss.Floats = append(ss.Floats, FPoint{F: f, T: ts})
|
|
} else {
|
|
if recordOrigT {
|
|
ev.error(fmt.Errorf("this should be an info metric, with float samples: %s", ss.Metric))
|
|
}
|
|
|
|
point := HPoint{H: h, T: ts}
|
|
histSize := point.size()
|
|
ev.currentSamples += histSize
|
|
ev.samplesStats.IncrementSamplesAtStep(step, int64(histSize))
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
if ss.Histograms == nil {
|
|
ss.Histograms = reuseOrGetHPointSlices(prevSS, numSteps)
|
|
}
|
|
ss.Histograms = append(ss.Histograms, point)
|
|
}
|
|
}
|
|
|
|
if len(ss.Floats)+len(ss.Histograms) > 0 {
|
|
mat = append(mat, ss)
|
|
prevSS = &mat[len(mat)-1]
|
|
}
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
return mat
|
|
}
|
|
|
|
// evalSubquery evaluates given SubqueryExpr and returns an equivalent
|
|
// evaluated MatrixSelector in its place. Note that the Name and LabelMatchers are not set.
|
|
func (ev *evaluator) evalSubquery(ctx context.Context, subq *parser.SubqueryExpr) (*parser.MatrixSelector, int, annotations.Annotations) {
|
|
samplesStats := ev.samplesStats
|
|
// Avoid double counting samples when running a subquery, those samples will be counted in later stage.
|
|
ev.samplesStats = ev.samplesStats.NewChild()
|
|
val, ws := ev.eval(ctx, subq)
|
|
// But do incorporate the peak from the subquery
|
|
samplesStats.UpdatePeakFromSubquery(ev.samplesStats)
|
|
ev.samplesStats = samplesStats
|
|
mat := val.(Matrix)
|
|
vs := &parser.VectorSelector{
|
|
OriginalOffset: subq.OriginalOffset,
|
|
Offset: subq.Offset,
|
|
Series: make([]storage.Series, 0, len(mat)),
|
|
Timestamp: subq.Timestamp,
|
|
}
|
|
if subq.Timestamp != nil {
|
|
// The offset of subquery is not modified in case of @ modifier.
|
|
// Hence we take care of that here for the result.
|
|
vs.Offset = subq.OriginalOffset + time.Duration(ev.startTimestamp-*subq.Timestamp)*time.Millisecond
|
|
}
|
|
ms := &parser.MatrixSelector{
|
|
Range: subq.Range,
|
|
VectorSelector: vs,
|
|
}
|
|
for _, s := range mat {
|
|
vs.Series = append(vs.Series, NewStorageSeries(s))
|
|
}
|
|
return ms, mat.TotalSamples(), ws
|
|
}
|
|
|
|
// eval evaluates the given expression as the given AST expression node requires.
|
|
func (ev *evaluator) eval(ctx context.Context, expr parser.Expr) (parser.Value, annotations.Annotations) {
|
|
// This is the top-level evaluation method.
|
|
// Thus, we check for timeout/cancellation here.
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
ev.error(err)
|
|
}
|
|
numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
|
|
|
|
// Create a new span to help investigate inner evaluation performances.
|
|
ctx, span := otel.Tracer("").Start(ctx, stats.InnerEvalTime.SpanOperation()+" eval "+reflect.TypeOf(expr).String())
|
|
defer span.End()
|
|
if ss, ok := expr.(interface{ ShortString() string }); ok {
|
|
span.SetAttributes(attribute.String("operation", ss.ShortString()))
|
|
}
|
|
|
|
switch e := expr.(type) {
|
|
case *parser.AggregateExpr:
|
|
// Grouping labels must be sorted (expected both by generateGroupingKey() and aggregation()).
|
|
sortedGrouping := e.Grouping
|
|
slices.Sort(sortedGrouping)
|
|
|
|
unwrapParenExpr(&e.Param)
|
|
param := unwrapStepInvariantExpr(e.Param)
|
|
unwrapParenExpr(¶m)
|
|
|
|
if e.Op == parser.COUNT_VALUES {
|
|
valueLabel := param.(*parser.StringLiteral)
|
|
if !model.LabelName(valueLabel.Val).IsValid() {
|
|
ev.errorf("invalid label name %q", valueLabel)
|
|
}
|
|
if !e.Without {
|
|
sortedGrouping = append(sortedGrouping, valueLabel.Val)
|
|
slices.Sort(sortedGrouping)
|
|
}
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
return ev.aggregationCountValues(e, sortedGrouping, valueLabel.Val, v[0].(Vector), enh)
|
|
}, e.Expr)
|
|
}
|
|
|
|
var warnings annotations.Annotations
|
|
originalNumSamples := ev.currentSamples
|
|
// param is the number k for topk/bottomk, or q for quantile.
|
|
var fParam float64
|
|
if param != nil {
|
|
val, ws := ev.eval(ctx, param)
|
|
warnings.Merge(ws)
|
|
fParam = val.(Matrix)[0].Floats[0].F
|
|
}
|
|
// Now fetch the data to be aggregated.
|
|
val, ws := ev.eval(ctx, e.Expr)
|
|
warnings.Merge(ws)
|
|
inputMatrix := val.(Matrix)
|
|
|
|
result, ws := ev.rangeEvalAgg(ctx, e, sortedGrouping, inputMatrix, fParam)
|
|
warnings.Merge(ws)
|
|
ev.currentSamples = originalNumSamples + result.TotalSamples()
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
|
|
return result, warnings
|
|
|
|
case *parser.Call:
|
|
call := FunctionCalls[e.Func.Name]
|
|
if e.Func.Name == "timestamp" {
|
|
// Matrix evaluation always returns the evaluation time,
|
|
// so this function needs special handling when given
|
|
// a vector selector.
|
|
unwrapParenExpr(&e.Args[0])
|
|
arg := unwrapStepInvariantExpr(e.Args[0])
|
|
unwrapParenExpr(&arg)
|
|
vs, ok := arg.(*parser.VectorSelector)
|
|
if ok {
|
|
return ev.rangeEvalTimestampFunctionOverVectorSelector(ctx, vs, call, e)
|
|
}
|
|
}
|
|
|
|
// Check if the function has a matrix argument.
|
|
var (
|
|
matrixArgIndex int
|
|
matrixArg bool
|
|
warnings annotations.Annotations
|
|
)
|
|
for i := range e.Args {
|
|
unwrapParenExpr(&e.Args[i])
|
|
a := unwrapStepInvariantExpr(e.Args[i])
|
|
unwrapParenExpr(&a)
|
|
if _, ok := a.(*parser.MatrixSelector); ok {
|
|
matrixArgIndex = i
|
|
matrixArg = true
|
|
break
|
|
}
|
|
// parser.SubqueryExpr can be used in place of parser.MatrixSelector.
|
|
if subq, ok := a.(*parser.SubqueryExpr); ok {
|
|
matrixArgIndex = i
|
|
matrixArg = true
|
|
// Replacing parser.SubqueryExpr with parser.MatrixSelector.
|
|
val, totalSamples, ws := ev.evalSubquery(ctx, subq)
|
|
e.Args[i] = val
|
|
warnings.Merge(ws)
|
|
defer func() {
|
|
// subquery result takes space in the memory. Get rid of that at the end.
|
|
val.VectorSelector.(*parser.VectorSelector).Series = nil
|
|
ev.currentSamples -= totalSamples
|
|
}()
|
|
break
|
|
}
|
|
}
|
|
|
|
// Special handling for functions that work on series not samples.
|
|
switch e.Func.Name {
|
|
case "label_replace":
|
|
return ev.evalLabelReplace(ctx, e.Args)
|
|
case "label_join":
|
|
return ev.evalLabelJoin(ctx, e.Args)
|
|
case "info":
|
|
return ev.evalInfo(ctx, e.Args)
|
|
}
|
|
|
|
if !matrixArg {
|
|
// Does not have a matrix argument.
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
vec, annos := call(v, e.Args, enh)
|
|
return vec, warnings.Merge(annos)
|
|
}, e.Args...)
|
|
}
|
|
|
|
inArgs := make([]parser.Value, len(e.Args))
|
|
// Evaluate any non-matrix arguments.
|
|
otherArgs := make([]Matrix, len(e.Args))
|
|
otherInArgs := make([]Vector, len(e.Args))
|
|
for i, e := range e.Args {
|
|
if i != matrixArgIndex {
|
|
val, ws := ev.eval(ctx, e)
|
|
otherArgs[i] = val.(Matrix)
|
|
otherInArgs[i] = Vector{Sample{}}
|
|
inArgs[i] = otherInArgs[i]
|
|
warnings.Merge(ws)
|
|
}
|
|
}
|
|
|
|
unwrapParenExpr(&e.Args[matrixArgIndex])
|
|
arg := unwrapStepInvariantExpr(e.Args[matrixArgIndex])
|
|
unwrapParenExpr(&arg)
|
|
sel := arg.(*parser.MatrixSelector)
|
|
selVS := sel.VectorSelector.(*parser.VectorSelector)
|
|
|
|
ws, err := checkAndExpandSeriesSet(ctx, sel)
|
|
warnings.Merge(ws)
|
|
if err != nil {
|
|
ev.error(errWithWarnings{fmt.Errorf("expanding series: %w", err), warnings})
|
|
}
|
|
mat := make(Matrix, 0, len(selVS.Series)) // Output matrix.
|
|
offset := durationMilliseconds(selVS.Offset)
|
|
selRange := durationMilliseconds(sel.Range)
|
|
stepRange := selRange
|
|
if stepRange > ev.interval {
|
|
stepRange = ev.interval
|
|
}
|
|
// Reuse objects across steps to save memory allocations.
|
|
var floats []FPoint
|
|
var histograms []HPoint
|
|
var prevSS *Series
|
|
inMatrix := make(Matrix, 1)
|
|
inArgs[matrixArgIndex] = inMatrix
|
|
enh := &EvalNodeHelper{Out: make(Vector, 0, 1), enableDelayedNameRemoval: ev.enableDelayedNameRemoval}
|
|
// Process all the calls for one time series at a time.
|
|
it := storage.NewBuffer(selRange)
|
|
var chkIter chunkenc.Iterator
|
|
|
|
// The last_over_time function acts like offset; thus, it
|
|
// should keep the metric name. For all the other range
|
|
// vector functions, the only change needed is to drop the
|
|
// metric name in the output.
|
|
dropName := e.Func.Name != "last_over_time"
|
|
|
|
for i, s := range selVS.Series {
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
ev.error(err)
|
|
}
|
|
ev.currentSamples -= len(floats) + totalHPointSize(histograms)
|
|
if floats != nil {
|
|
floats = floats[:0]
|
|
}
|
|
if histograms != nil {
|
|
histograms = histograms[:0]
|
|
}
|
|
chkIter = s.Iterator(chkIter)
|
|
it.Reset(chkIter)
|
|
metric := selVS.Series[i].Labels()
|
|
if !ev.enableDelayedNameRemoval && dropName {
|
|
metric = metric.DropMetricName()
|
|
}
|
|
ss := Series{
|
|
Metric: metric,
|
|
DropName: dropName,
|
|
}
|
|
inMatrix[0].Metric = selVS.Series[i].Labels()
|
|
for ts, step := ev.startTimestamp, -1; ts <= ev.endTimestamp; ts += ev.interval {
|
|
step++
|
|
// Set the non-matrix arguments.
|
|
// They are scalar, so it is safe to use the step number
|
|
// when looking up the argument, as there will be no gaps.
|
|
for j := range e.Args {
|
|
if j != matrixArgIndex {
|
|
otherInArgs[j][0].F = otherArgs[j][0].Floats[step].F
|
|
}
|
|
}
|
|
// Evaluate the matrix selector for this series
|
|
// for this step, but only if this is the 1st
|
|
// iteration or no @ modifier has been used.
|
|
if ts == ev.startTimestamp || selVS.Timestamp == nil {
|
|
maxt := ts - offset
|
|
mint := maxt - selRange
|
|
floats, histograms = ev.matrixIterSlice(it, mint, maxt, floats, histograms)
|
|
}
|
|
if len(floats)+len(histograms) == 0 {
|
|
continue
|
|
}
|
|
inMatrix[0].Floats = floats
|
|
inMatrix[0].Histograms = histograms
|
|
enh.Ts = ts
|
|
// Make the function call.
|
|
outVec, annos := call(inArgs, e.Args, enh)
|
|
warnings.Merge(annos)
|
|
ev.samplesStats.IncrementSamplesAtStep(step, int64(len(floats)+totalHPointSize(histograms)))
|
|
|
|
enh.Out = outVec[:0]
|
|
if len(outVec) > 0 {
|
|
if outVec[0].H == nil {
|
|
if ss.Floats == nil {
|
|
ss.Floats = reuseOrGetFPointSlices(prevSS, numSteps)
|
|
}
|
|
|
|
ss.Floats = append(ss.Floats, FPoint{F: outVec[0].F, T: ts})
|
|
} else {
|
|
if ss.Histograms == nil {
|
|
ss.Histograms = reuseOrGetHPointSlices(prevSS, numSteps)
|
|
}
|
|
ss.Histograms = append(ss.Histograms, HPoint{H: outVec[0].H, T: ts})
|
|
}
|
|
}
|
|
// Only buffer stepRange milliseconds from the second step on.
|
|
it.ReduceDelta(stepRange)
|
|
}
|
|
histSamples := totalHPointSize(ss.Histograms)
|
|
|
|
if len(ss.Floats)+histSamples > 0 {
|
|
if ev.currentSamples+len(ss.Floats)+histSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
mat = append(mat, ss)
|
|
prevSS = &mat[len(mat)-1]
|
|
ev.currentSamples += len(ss.Floats) + histSamples
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
|
|
if e.Func.Name == "rate" || e.Func.Name == "increase" {
|
|
metricName := inMatrix[0].Metric.Get(labels.MetricName)
|
|
if metricName != "" && len(ss.Floats) > 0 &&
|
|
!strings.HasSuffix(metricName, "_total") &&
|
|
!strings.HasSuffix(metricName, "_sum") &&
|
|
!strings.HasSuffix(metricName, "_count") &&
|
|
!strings.HasSuffix(metricName, "_bucket") {
|
|
warnings.Add(annotations.NewPossibleNonCounterInfo(metricName, e.Args[0].PositionRange()))
|
|
}
|
|
}
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
|
|
ev.currentSamples -= len(floats) + totalHPointSize(histograms)
|
|
putFPointSlice(floats)
|
|
putMatrixSelectorHPointSlice(histograms)
|
|
|
|
// The absent_over_time function returns 0 or 1 series. So far, the matrix
|
|
// contains multiple series. The following code will create a new series
|
|
// with values of 1 for the timestamps where no series has value.
|
|
if e.Func.Name == "absent_over_time" {
|
|
steps := int(1 + (ev.endTimestamp-ev.startTimestamp)/ev.interval)
|
|
// Iterate once to look for a complete series.
|
|
for _, s := range mat {
|
|
if len(s.Floats)+len(s.Histograms) == steps {
|
|
return Matrix{}, warnings
|
|
}
|
|
}
|
|
|
|
found := map[int64]struct{}{}
|
|
|
|
for i, s := range mat {
|
|
for _, p := range s.Floats {
|
|
found[p.T] = struct{}{}
|
|
}
|
|
for _, p := range s.Histograms {
|
|
found[p.T] = struct{}{}
|
|
}
|
|
if i > 0 && len(found) == steps {
|
|
return Matrix{}, warnings
|
|
}
|
|
}
|
|
|
|
newp := make([]FPoint, 0, steps-len(found))
|
|
for ts := ev.startTimestamp; ts <= ev.endTimestamp; ts += ev.interval {
|
|
if _, ok := found[ts]; !ok {
|
|
newp = append(newp, FPoint{T: ts, F: 1})
|
|
}
|
|
}
|
|
|
|
return Matrix{
|
|
Series{
|
|
Metric: createLabelsForAbsentFunction(e.Args[0]),
|
|
Floats: newp,
|
|
DropName: dropName,
|
|
},
|
|
}, warnings
|
|
}
|
|
|
|
if !ev.enableDelayedNameRemoval && mat.ContainsSameLabelset() {
|
|
ev.errorf("vector cannot contain metrics with the same labelset")
|
|
}
|
|
return mat, warnings
|
|
|
|
case *parser.ParenExpr:
|
|
return ev.eval(ctx, e.Expr)
|
|
|
|
case *parser.UnaryExpr:
|
|
val, ws := ev.eval(ctx, e.Expr)
|
|
mat := val.(Matrix)
|
|
if e.Op == parser.SUB {
|
|
for i := range mat {
|
|
if !ev.enableDelayedNameRemoval {
|
|
mat[i].Metric = mat[i].Metric.DropMetricName()
|
|
}
|
|
mat[i].DropName = true
|
|
for j := range mat[i].Floats {
|
|
mat[i].Floats[j].F = -mat[i].Floats[j].F
|
|
}
|
|
for j := range mat[i].Histograms {
|
|
mat[i].Histograms[j].H = mat[i].Histograms[j].H.Copy().Mul(-1)
|
|
}
|
|
}
|
|
if !ev.enableDelayedNameRemoval && mat.ContainsSameLabelset() {
|
|
ev.errorf("vector cannot contain metrics with the same labelset")
|
|
}
|
|
}
|
|
return mat, ws
|
|
|
|
case *parser.BinaryExpr:
|
|
switch lt, rt := e.LHS.Type(), e.RHS.Type(); {
|
|
case lt == parser.ValueTypeScalar && rt == parser.ValueTypeScalar:
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
val := scalarBinop(e.Op, v[0].(Vector)[0].F, v[1].(Vector)[0].F)
|
|
return append(enh.Out, Sample{F: val}), nil
|
|
}, e.LHS, e.RHS)
|
|
case lt == parser.ValueTypeVector && rt == parser.ValueTypeVector:
|
|
// Function to compute the join signature for each series.
|
|
buf := make([]byte, 0, 1024)
|
|
sigf := signatureFunc(e.VectorMatching.On, buf, e.VectorMatching.MatchingLabels...)
|
|
initSignatures := func(series labels.Labels, h *EvalSeriesHelper) {
|
|
h.signature = sigf(series)
|
|
}
|
|
switch e.Op {
|
|
case parser.LAND:
|
|
return ev.rangeEval(ctx, initSignatures, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
return ev.VectorAnd(v[0].(Vector), v[1].(Vector), e.VectorMatching, sh[0], sh[1], enh), nil
|
|
}, e.LHS, e.RHS)
|
|
case parser.LOR:
|
|
return ev.rangeEval(ctx, initSignatures, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
return ev.VectorOr(v[0].(Vector), v[1].(Vector), e.VectorMatching, sh[0], sh[1], enh), nil
|
|
}, e.LHS, e.RHS)
|
|
case parser.LUNLESS:
|
|
return ev.rangeEval(ctx, initSignatures, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
return ev.VectorUnless(v[0].(Vector), v[1].(Vector), e.VectorMatching, sh[0], sh[1], enh), nil
|
|
}, e.LHS, e.RHS)
|
|
default:
|
|
return ev.rangeEval(ctx, initSignatures, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
vec, err := ev.VectorBinop(e.Op, v[0].(Vector), v[1].(Vector), e.VectorMatching, e.ReturnBool, sh[0], sh[1], enh, e.PositionRange())
|
|
return vec, handleVectorBinopError(err, e)
|
|
}, e.LHS, e.RHS)
|
|
}
|
|
|
|
case lt == parser.ValueTypeVector && rt == parser.ValueTypeScalar:
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
vec, err := ev.VectorscalarBinop(e.Op, v[0].(Vector), Scalar{V: v[1].(Vector)[0].F}, false, e.ReturnBool, enh, e.PositionRange())
|
|
return vec, handleVectorBinopError(err, e)
|
|
}, e.LHS, e.RHS)
|
|
|
|
case lt == parser.ValueTypeScalar && rt == parser.ValueTypeVector:
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
vec, err := ev.VectorscalarBinop(e.Op, v[1].(Vector), Scalar{V: v[0].(Vector)[0].F}, true, e.ReturnBool, enh, e.PositionRange())
|
|
return vec, handleVectorBinopError(err, e)
|
|
}, e.LHS, e.RHS)
|
|
}
|
|
|
|
case *parser.NumberLiteral:
|
|
span.SetAttributes(attribute.Float64("value", e.Val))
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
return append(enh.Out, Sample{F: e.Val, Metric: labels.EmptyLabels()}), nil
|
|
})
|
|
|
|
case *parser.StringLiteral:
|
|
span.SetAttributes(attribute.String("value", e.Val))
|
|
return String{V: e.Val, T: ev.startTimestamp}, nil
|
|
|
|
case *parser.VectorSelector:
|
|
ws, err := checkAndExpandSeriesSet(ctx, e)
|
|
if err != nil {
|
|
ev.error(errWithWarnings{fmt.Errorf("expanding series: %w", err), ws})
|
|
}
|
|
mat := ev.evalSeries(ctx, e.Series, e.Offset, false)
|
|
return mat, ws
|
|
|
|
case *parser.MatrixSelector:
|
|
if ev.startTimestamp != ev.endTimestamp {
|
|
panic(errors.New("cannot do range evaluation of matrix selector"))
|
|
}
|
|
return ev.matrixSelector(ctx, e)
|
|
|
|
case *parser.SubqueryExpr:
|
|
offsetMillis := durationMilliseconds(e.Offset)
|
|
rangeMillis := durationMilliseconds(e.Range)
|
|
newEv := &evaluator{
|
|
endTimestamp: ev.endTimestamp - offsetMillis,
|
|
currentSamples: ev.currentSamples,
|
|
maxSamples: ev.maxSamples,
|
|
logger: ev.logger,
|
|
lookbackDelta: ev.lookbackDelta,
|
|
samplesStats: ev.samplesStats.NewChild(),
|
|
noStepSubqueryIntervalFn: ev.noStepSubqueryIntervalFn,
|
|
enableDelayedNameRemoval: ev.enableDelayedNameRemoval,
|
|
querier: ev.querier,
|
|
}
|
|
|
|
if e.Step != 0 {
|
|
newEv.interval = durationMilliseconds(e.Step)
|
|
} else {
|
|
newEv.interval = ev.noStepSubqueryIntervalFn(rangeMillis)
|
|
}
|
|
|
|
// Start with the first timestamp after (ev.startTimestamp - offset - range)
|
|
// that is aligned with the step (multiple of 'newEv.interval').
|
|
newEv.startTimestamp = newEv.interval * ((ev.startTimestamp - offsetMillis - rangeMillis) / newEv.interval)
|
|
if newEv.startTimestamp < (ev.startTimestamp - offsetMillis - rangeMillis) {
|
|
newEv.startTimestamp += newEv.interval
|
|
}
|
|
|
|
if newEv.startTimestamp != ev.startTimestamp {
|
|
// Adjust the offset of selectors based on the new
|
|
// start time of the evaluator since the calculation
|
|
// of the offset with @ happens w.r.t. the start time.
|
|
setOffsetForAtModifier(newEv.startTimestamp, e.Expr)
|
|
}
|
|
|
|
res, ws := newEv.eval(ctx, e.Expr)
|
|
ev.currentSamples = newEv.currentSamples
|
|
ev.samplesStats.UpdatePeakFromSubquery(newEv.samplesStats)
|
|
ev.samplesStats.IncrementSamplesAtTimestamp(ev.endTimestamp, newEv.samplesStats.TotalSamples)
|
|
return res, ws
|
|
case *parser.StepInvariantExpr:
|
|
switch ce := e.Expr.(type) {
|
|
case *parser.StringLiteral, *parser.NumberLiteral:
|
|
return ev.eval(ctx, ce)
|
|
}
|
|
|
|
newEv := &evaluator{
|
|
startTimestamp: ev.startTimestamp,
|
|
endTimestamp: ev.startTimestamp, // Always a single evaluation.
|
|
interval: ev.interval,
|
|
currentSamples: ev.currentSamples,
|
|
maxSamples: ev.maxSamples,
|
|
logger: ev.logger,
|
|
lookbackDelta: ev.lookbackDelta,
|
|
samplesStats: ev.samplesStats.NewChild(),
|
|
noStepSubqueryIntervalFn: ev.noStepSubqueryIntervalFn,
|
|
enableDelayedNameRemoval: ev.enableDelayedNameRemoval,
|
|
querier: ev.querier,
|
|
}
|
|
res, ws := newEv.eval(ctx, e.Expr)
|
|
ev.currentSamples = newEv.currentSamples
|
|
ev.samplesStats.UpdatePeakFromSubquery(newEv.samplesStats)
|
|
for ts, step := ev.startTimestamp, -1; ts <= ev.endTimestamp; ts += ev.interval {
|
|
step++
|
|
ev.samplesStats.IncrementSamplesAtStep(step, newEv.samplesStats.TotalSamples)
|
|
}
|
|
switch e.Expr.(type) {
|
|
case *parser.MatrixSelector, *parser.SubqueryExpr:
|
|
// We do not duplicate results for range selectors since result is a matrix
|
|
// with their unique timestamps which does not depend on the step.
|
|
return res, ws
|
|
}
|
|
|
|
// For every evaluation while the value remains same, the timestamp for that
|
|
// value would change for different eval times. Hence we duplicate the result
|
|
// with changed timestamps.
|
|
mat, ok := res.(Matrix)
|
|
if !ok {
|
|
panic(fmt.Errorf("unexpected result in StepInvariantExpr evaluation: %T", expr))
|
|
}
|
|
for i := range mat {
|
|
if len(mat[i].Floats)+len(mat[i].Histograms) != 1 {
|
|
panic(errors.New("unexpected number of samples"))
|
|
}
|
|
for ts := ev.startTimestamp + ev.interval; ts <= ev.endTimestamp; ts += ev.interval {
|
|
if len(mat[i].Floats) > 0 {
|
|
mat[i].Floats = append(mat[i].Floats, FPoint{
|
|
T: ts,
|
|
F: mat[i].Floats[0].F,
|
|
})
|
|
ev.currentSamples++
|
|
} else {
|
|
point := HPoint{
|
|
T: ts,
|
|
H: mat[i].Histograms[0].H,
|
|
}
|
|
mat[i].Histograms = append(mat[i].Histograms, point)
|
|
ev.currentSamples += point.size()
|
|
}
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
}
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
return res, ws
|
|
}
|
|
|
|
panic(fmt.Errorf("unhandled expression of type: %T", expr))
|
|
}
|
|
|
|
// reuseOrGetHPointSlices reuses the space from previous slice to create new slice if the former has lots of room.
|
|
// The previous slices capacity is adjusted so when it is re-used from the pool it doesn't overflow into the new one.
|
|
func reuseOrGetHPointSlices(prevSS *Series, numSteps int) (r []HPoint) {
|
|
if prevSS != nil && cap(prevSS.Histograms)-2*len(prevSS.Histograms) > 0 {
|
|
r = prevSS.Histograms[len(prevSS.Histograms):]
|
|
prevSS.Histograms = prevSS.Histograms[0:len(prevSS.Histograms):len(prevSS.Histograms)]
|
|
return
|
|
}
|
|
|
|
return getHPointSlice(numSteps)
|
|
}
|
|
|
|
// reuseOrGetFPointSlices reuses the space from previous slice to create new slice if the former has lots of room.
|
|
// The previous slices capacity is adjusted so when it is re-used from the pool it doesn't overflow into the new one.
|
|
func reuseOrGetFPointSlices(prevSS *Series, numSteps int) (r []FPoint) {
|
|
if prevSS != nil && cap(prevSS.Floats)-2*len(prevSS.Floats) > 0 {
|
|
r = prevSS.Floats[len(prevSS.Floats):]
|
|
prevSS.Floats = prevSS.Floats[0:len(prevSS.Floats):len(prevSS.Floats)]
|
|
return
|
|
}
|
|
|
|
return getFPointSlice(numSteps)
|
|
}
|
|
|
|
func (ev *evaluator) rangeEvalTimestampFunctionOverVectorSelector(ctx context.Context, vs *parser.VectorSelector, call FunctionCall, e *parser.Call) (parser.Value, annotations.Annotations) {
|
|
ws, err := checkAndExpandSeriesSet(ctx, vs)
|
|
if err != nil {
|
|
ev.error(errWithWarnings{fmt.Errorf("expanding series: %w", err), ws})
|
|
}
|
|
|
|
seriesIterators := make([]*storage.MemoizedSeriesIterator, len(vs.Series))
|
|
for i, s := range vs.Series {
|
|
it := s.Iterator(nil)
|
|
seriesIterators[i] = storage.NewMemoizedIterator(it, durationMilliseconds(ev.lookbackDelta)-1)
|
|
}
|
|
|
|
return ev.rangeEval(ctx, nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
if vs.Timestamp != nil {
|
|
// This is a special case for "timestamp()" when the @ modifier is used, to ensure that
|
|
// we return a point for each time step in this case.
|
|
// See https://github.com/prometheus/prometheus/issues/8433.
|
|
vs.Offset = time.Duration(enh.Ts-*vs.Timestamp) * time.Millisecond
|
|
}
|
|
|
|
vec := make(Vector, 0, len(vs.Series))
|
|
for i, s := range vs.Series {
|
|
it := seriesIterators[i]
|
|
t, _, _, ok := ev.vectorSelectorSingle(it, vs.Offset, enh.Ts)
|
|
if !ok {
|
|
continue
|
|
}
|
|
|
|
// Note that we ignore the sample values because call only cares about the timestamp.
|
|
vec = append(vec, Sample{
|
|
Metric: s.Labels(),
|
|
T: t,
|
|
})
|
|
|
|
ev.currentSamples++
|
|
ev.samplesStats.IncrementSamplesAtTimestamp(enh.Ts, 1)
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
vec, annos := call([]parser.Value{vec}, e.Args, enh)
|
|
return vec, ws.Merge(annos)
|
|
})
|
|
}
|
|
|
|
// vectorSelectorSingle evaluates an instant vector for the iterator of one time series.
|
|
func (ev *evaluator) vectorSelectorSingle(it *storage.MemoizedSeriesIterator, offset time.Duration, ts int64) (
|
|
int64, float64, *histogram.FloatHistogram, bool,
|
|
) {
|
|
refTime := ts - durationMilliseconds(offset)
|
|
var t int64
|
|
var v float64
|
|
var h *histogram.FloatHistogram
|
|
|
|
valueType := it.Seek(refTime)
|
|
switch valueType {
|
|
case chunkenc.ValNone:
|
|
if it.Err() != nil {
|
|
ev.error(it.Err())
|
|
}
|
|
case chunkenc.ValFloat:
|
|
t, v = it.At()
|
|
case chunkenc.ValFloatHistogram:
|
|
t, h = it.AtFloatHistogram()
|
|
default:
|
|
panic(fmt.Errorf("unknown value type %v", valueType))
|
|
}
|
|
if valueType == chunkenc.ValNone || t > refTime {
|
|
var ok bool
|
|
t, v, h, ok = it.PeekPrev()
|
|
if !ok || t <= refTime-durationMilliseconds(ev.lookbackDelta) {
|
|
return 0, 0, nil, false
|
|
}
|
|
}
|
|
if value.IsStaleNaN(v) || (h != nil && value.IsStaleNaN(h.Sum)) {
|
|
return 0, 0, nil, false
|
|
}
|
|
return t, v, h, true
|
|
}
|
|
|
|
var (
|
|
fPointPool zeropool.Pool[[]FPoint]
|
|
hPointPool zeropool.Pool[[]HPoint]
|
|
|
|
// matrixSelectorHPool holds reusable histogram slices used by the matrix
|
|
// selector. The key difference between this pool and the hPointPool is that
|
|
// slices returned by this pool should never hold multiple copies of the same
|
|
// histogram pointer since histogram objects are reused across query evaluation
|
|
// steps.
|
|
matrixSelectorHPool zeropool.Pool[[]HPoint]
|
|
)
|
|
|
|
func getFPointSlice(sz int) []FPoint {
|
|
if p := fPointPool.Get(); p != nil {
|
|
return p
|
|
}
|
|
|
|
if sz > maxPointsSliceSize {
|
|
sz = maxPointsSliceSize
|
|
}
|
|
|
|
return make([]FPoint, 0, sz)
|
|
}
|
|
|
|
// putFPointSlice will return a FPoint slice of size max(maxPointsSliceSize, sz).
|
|
// This function is called with an estimated size which often can be over-estimated.
|
|
func putFPointSlice(p []FPoint) {
|
|
if p != nil {
|
|
fPointPool.Put(p[:0])
|
|
}
|
|
}
|
|
|
|
// getHPointSlice will return a HPoint slice of size max(maxPointsSliceSize, sz).
|
|
// This function is called with an estimated size which often can be over-estimated.
|
|
func getHPointSlice(sz int) []HPoint {
|
|
if p := hPointPool.Get(); p != nil {
|
|
return p
|
|
}
|
|
|
|
if sz > maxPointsSliceSize {
|
|
sz = maxPointsSliceSize
|
|
}
|
|
|
|
return make([]HPoint, 0, sz)
|
|
}
|
|
|
|
func putHPointSlice(p []HPoint) {
|
|
if p != nil {
|
|
hPointPool.Put(p[:0])
|
|
}
|
|
}
|
|
|
|
func getMatrixSelectorHPoints() []HPoint {
|
|
if p := matrixSelectorHPool.Get(); p != nil {
|
|
return p
|
|
}
|
|
|
|
return make([]HPoint, 0, matrixSelectorSliceSize)
|
|
}
|
|
|
|
func putMatrixSelectorHPointSlice(p []HPoint) {
|
|
if p != nil {
|
|
matrixSelectorHPool.Put(p[:0])
|
|
}
|
|
}
|
|
|
|
// matrixSelector evaluates a *parser.MatrixSelector expression.
|
|
func (ev *evaluator) matrixSelector(ctx context.Context, node *parser.MatrixSelector) (Matrix, annotations.Annotations) {
|
|
var (
|
|
vs = node.VectorSelector.(*parser.VectorSelector)
|
|
|
|
offset = durationMilliseconds(vs.Offset)
|
|
maxt = ev.startTimestamp - offset
|
|
mint = maxt - durationMilliseconds(node.Range)
|
|
matrix = make(Matrix, 0, len(vs.Series))
|
|
|
|
it = storage.NewBuffer(durationMilliseconds(node.Range))
|
|
)
|
|
ws, err := checkAndExpandSeriesSet(ctx, node)
|
|
if err != nil {
|
|
ev.error(errWithWarnings{fmt.Errorf("expanding series: %w", err), ws})
|
|
}
|
|
|
|
var chkIter chunkenc.Iterator
|
|
series := vs.Series
|
|
for i, s := range series {
|
|
if err := contextDone(ctx, "expression evaluation"); err != nil {
|
|
ev.error(err)
|
|
}
|
|
chkIter = s.Iterator(chkIter)
|
|
it.Reset(chkIter)
|
|
ss := Series{
|
|
Metric: series[i].Labels(),
|
|
}
|
|
|
|
ss.Floats, ss.Histograms = ev.matrixIterSlice(it, mint, maxt, nil, nil)
|
|
totalSize := int64(len(ss.Floats)) + int64(totalHPointSize(ss.Histograms))
|
|
ev.samplesStats.IncrementSamplesAtTimestamp(ev.startTimestamp, totalSize)
|
|
|
|
if totalSize > 0 {
|
|
matrix = append(matrix, ss)
|
|
} else {
|
|
putFPointSlice(ss.Floats)
|
|
putHPointSlice(ss.Histograms)
|
|
}
|
|
}
|
|
return matrix, ws
|
|
}
|
|
|
|
// matrixIterSlice populates a matrix vector covering the requested range for a
|
|
// single time series, with points retrieved from an iterator.
|
|
//
|
|
// As an optimization, the matrix vector may already contain points of the same
|
|
// time series from the evaluation of an earlier step (with lower mint and maxt
|
|
// values). Any such points falling before mint are discarded; points that fall
|
|
// into the [mint, maxt] range are retained; only points with later timestamps
|
|
// are populated from the iterator.
|
|
func (ev *evaluator) matrixIterSlice(
|
|
it *storage.BufferedSeriesIterator, mint, maxt int64,
|
|
floats []FPoint, histograms []HPoint,
|
|
) ([]FPoint, []HPoint) {
|
|
mintFloats, mintHistograms := mint, mint
|
|
|
|
// First floats...
|
|
if len(floats) > 0 && floats[len(floats)-1].T > mint {
|
|
// There is an overlap between previous and current ranges, retain common
|
|
// points. In most such cases:
|
|
// (a) the overlap is significantly larger than the eval step; and/or
|
|
// (b) the number of samples is relatively small.
|
|
// so a linear search will be as fast as a binary search.
|
|
var drop int
|
|
for drop = 0; floats[drop].T <= mint; drop++ {
|
|
}
|
|
ev.currentSamples -= drop
|
|
copy(floats, floats[drop:])
|
|
floats = floats[:len(floats)-drop]
|
|
// Only append points with timestamps after the last timestamp we have.
|
|
mintFloats = floats[len(floats)-1].T
|
|
} else {
|
|
ev.currentSamples -= len(floats)
|
|
if floats != nil {
|
|
floats = floats[:0]
|
|
}
|
|
}
|
|
|
|
// ...then the same for histograms. TODO(beorn7): Use generics?
|
|
if len(histograms) > 0 && histograms[len(histograms)-1].T > mint {
|
|
// There is an overlap between previous and current ranges, retain common
|
|
// points. In most such cases:
|
|
// (a) the overlap is significantly larger than the eval step; and/or
|
|
// (b) the number of samples is relatively small.
|
|
// so a linear search will be as fast as a binary search.
|
|
var drop int
|
|
for drop = 0; histograms[drop].T <= mint; drop++ {
|
|
}
|
|
// Rotate the buffer around the drop index so that points before mint can be
|
|
// reused to store new histograms.
|
|
tail := make([]HPoint, drop)
|
|
copy(tail, histograms[:drop])
|
|
copy(histograms, histograms[drop:])
|
|
copy(histograms[len(histograms)-drop:], tail)
|
|
histograms = histograms[:len(histograms)-drop]
|
|
ev.currentSamples -= totalHPointSize(histograms)
|
|
// Only append points with timestamps after the last timestamp we have.
|
|
mintHistograms = histograms[len(histograms)-1].T
|
|
} else {
|
|
ev.currentSamples -= totalHPointSize(histograms)
|
|
if histograms != nil {
|
|
histograms = histograms[:0]
|
|
}
|
|
}
|
|
|
|
soughtValueType := it.Seek(maxt)
|
|
if soughtValueType == chunkenc.ValNone {
|
|
if it.Err() != nil {
|
|
ev.error(it.Err())
|
|
}
|
|
}
|
|
|
|
buf := it.Buffer()
|
|
loop:
|
|
for {
|
|
switch buf.Next() {
|
|
case chunkenc.ValNone:
|
|
break loop
|
|
case chunkenc.ValFloatHistogram, chunkenc.ValHistogram:
|
|
t := buf.AtT()
|
|
// Values in the buffer are guaranteed to be smaller than maxt.
|
|
if t > mintHistograms {
|
|
if histograms == nil {
|
|
histograms = getMatrixSelectorHPoints()
|
|
}
|
|
n := len(histograms)
|
|
if n < cap(histograms) {
|
|
histograms = histograms[:n+1]
|
|
} else {
|
|
histograms = append(histograms, HPoint{H: &histogram.FloatHistogram{}})
|
|
}
|
|
histograms[n].T, histograms[n].H = buf.AtFloatHistogram(histograms[n].H)
|
|
if value.IsStaleNaN(histograms[n].H.Sum) {
|
|
histograms = histograms[:n]
|
|
continue loop
|
|
}
|
|
ev.currentSamples += histograms[n].size()
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
}
|
|
case chunkenc.ValFloat:
|
|
t, f := buf.At()
|
|
if value.IsStaleNaN(f) {
|
|
continue loop
|
|
}
|
|
// Values in the buffer are guaranteed to be smaller than maxt.
|
|
if t > mintFloats {
|
|
ev.currentSamples++
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
if floats == nil {
|
|
floats = getFPointSlice(16)
|
|
}
|
|
floats = append(floats, FPoint{T: t, F: f})
|
|
}
|
|
}
|
|
}
|
|
// The sought sample might also be in the range.
|
|
switch soughtValueType {
|
|
case chunkenc.ValFloatHistogram, chunkenc.ValHistogram:
|
|
if it.AtT() != maxt {
|
|
break
|
|
}
|
|
if histograms == nil {
|
|
histograms = getMatrixSelectorHPoints()
|
|
}
|
|
n := len(histograms)
|
|
if n < cap(histograms) {
|
|
histograms = histograms[:n+1]
|
|
} else {
|
|
histograms = append(histograms, HPoint{H: &histogram.FloatHistogram{}})
|
|
}
|
|
if histograms[n].H == nil {
|
|
// Make sure to pass non-nil H to AtFloatHistogram so that it does a deep-copy.
|
|
// Not an issue in the loop above since that uses an intermediate buffer.
|
|
histograms[n].H = &histogram.FloatHistogram{}
|
|
}
|
|
histograms[n].T, histograms[n].H = it.AtFloatHistogram(histograms[n].H)
|
|
if value.IsStaleNaN(histograms[n].H.Sum) {
|
|
histograms = histograms[:n]
|
|
break
|
|
}
|
|
ev.currentSamples += histograms[n].size()
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
|
|
case chunkenc.ValFloat:
|
|
t, f := it.At()
|
|
if t == maxt && !value.IsStaleNaN(f) {
|
|
ev.currentSamples++
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
if floats == nil {
|
|
floats = getFPointSlice(16)
|
|
}
|
|
floats = append(floats, FPoint{T: t, F: f})
|
|
}
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
return floats, histograms
|
|
}
|
|
|
|
func (ev *evaluator) VectorAnd(lhs, rhs Vector, matching *parser.VectorMatching, lhsh, rhsh []EvalSeriesHelper, enh *EvalNodeHelper) Vector {
|
|
if matching.Card != parser.CardManyToMany {
|
|
panic("set operations must only use many-to-many matching")
|
|
}
|
|
if len(lhs) == 0 || len(rhs) == 0 {
|
|
return nil // Short-circuit: AND with nothing is nothing.
|
|
}
|
|
|
|
// The set of signatures for the right-hand side Vector.
|
|
rightSigs := map[string]struct{}{}
|
|
// Add all rhs samples to a map so we can easily find matches later.
|
|
for _, sh := range rhsh {
|
|
rightSigs[sh.signature] = struct{}{}
|
|
}
|
|
|
|
for i, ls := range lhs {
|
|
// If there's a matching entry in the right-hand side Vector, add the sample.
|
|
if _, ok := rightSigs[lhsh[i].signature]; ok {
|
|
enh.Out = append(enh.Out, ls)
|
|
}
|
|
}
|
|
return enh.Out
|
|
}
|
|
|
|
func (ev *evaluator) VectorOr(lhs, rhs Vector, matching *parser.VectorMatching, lhsh, rhsh []EvalSeriesHelper, enh *EvalNodeHelper) Vector {
|
|
switch {
|
|
case matching.Card != parser.CardManyToMany:
|
|
panic("set operations must only use many-to-many matching")
|
|
case len(lhs) == 0: // Short-circuit.
|
|
enh.Out = append(enh.Out, rhs...)
|
|
return enh.Out
|
|
case len(rhs) == 0:
|
|
enh.Out = append(enh.Out, lhs...)
|
|
return enh.Out
|
|
}
|
|
|
|
leftSigs := map[string]struct{}{}
|
|
// Add everything from the left-hand-side Vector.
|
|
for i, ls := range lhs {
|
|
leftSigs[lhsh[i].signature] = struct{}{}
|
|
enh.Out = append(enh.Out, ls)
|
|
}
|
|
// Add all right-hand side elements which have not been added from the left-hand side.
|
|
for j, rs := range rhs {
|
|
if _, ok := leftSigs[rhsh[j].signature]; !ok {
|
|
enh.Out = append(enh.Out, rs)
|
|
}
|
|
}
|
|
return enh.Out
|
|
}
|
|
|
|
func (ev *evaluator) VectorUnless(lhs, rhs Vector, matching *parser.VectorMatching, lhsh, rhsh []EvalSeriesHelper, enh *EvalNodeHelper) Vector {
|
|
if matching.Card != parser.CardManyToMany {
|
|
panic("set operations must only use many-to-many matching")
|
|
}
|
|
// Short-circuit: empty rhs means we will return everything in lhs;
|
|
// empty lhs means we will return empty - don't need to build a map.
|
|
if len(lhs) == 0 || len(rhs) == 0 {
|
|
enh.Out = append(enh.Out, lhs...)
|
|
return enh.Out
|
|
}
|
|
|
|
rightSigs := map[string]struct{}{}
|
|
for _, sh := range rhsh {
|
|
rightSigs[sh.signature] = struct{}{}
|
|
}
|
|
|
|
for i, ls := range lhs {
|
|
if _, ok := rightSigs[lhsh[i].signature]; !ok {
|
|
enh.Out = append(enh.Out, ls)
|
|
}
|
|
}
|
|
return enh.Out
|
|
}
|
|
|
|
// VectorBinop evaluates a binary operation between two Vectors, excluding set operators.
|
|
func (ev *evaluator) VectorBinop(op parser.ItemType, lhs, rhs Vector, matching *parser.VectorMatching, returnBool bool, lhsh, rhsh []EvalSeriesHelper, enh *EvalNodeHelper, pos posrange.PositionRange) (Vector, error) {
|
|
if matching.Card == parser.CardManyToMany {
|
|
panic("many-to-many only allowed for set operators")
|
|
}
|
|
if len(lhs) == 0 || len(rhs) == 0 {
|
|
return nil, nil // Short-circuit: nothing is going to match.
|
|
}
|
|
|
|
// The control flow below handles one-to-one or many-to-one matching.
|
|
// For one-to-many, swap sidedness and account for the swap when calculating
|
|
// values.
|
|
if matching.Card == parser.CardOneToMany {
|
|
lhs, rhs = rhs, lhs
|
|
lhsh, rhsh = rhsh, lhsh
|
|
}
|
|
|
|
// All samples from the rhs hashed by the matching label/values.
|
|
if enh.rightSigs == nil {
|
|
enh.rightSigs = make(map[string]Sample, len(enh.Out))
|
|
} else {
|
|
for k := range enh.rightSigs {
|
|
delete(enh.rightSigs, k)
|
|
}
|
|
}
|
|
rightSigs := enh.rightSigs
|
|
|
|
// Add all rhs samples to a map so we can easily find matches later.
|
|
for i, rs := range rhs {
|
|
sig := rhsh[i].signature
|
|
// The rhs is guaranteed to be the 'one' side. Having multiple samples
|
|
// with the same signature means that the matching is many-to-many.
|
|
if duplSample, found := rightSigs[sig]; found {
|
|
// oneSide represents which side of the vector represents the 'one' in the many-to-one relationship.
|
|
oneSide := "right"
|
|
if matching.Card == parser.CardOneToMany {
|
|
oneSide = "left"
|
|
}
|
|
matchedLabels := rs.Metric.MatchLabels(matching.On, matching.MatchingLabels...)
|
|
// Many-to-many matching not allowed.
|
|
ev.errorf("found duplicate series for the match group %s on the %s hand-side of the operation: [%s, %s]"+
|
|
";many-to-many matching not allowed: matching labels must be unique on one side", matchedLabels.String(), oneSide, rs.Metric.String(), duplSample.Metric.String())
|
|
}
|
|
rightSigs[sig] = rs
|
|
}
|
|
|
|
// Tracks the match-signature. For one-to-one operations the value is nil. For many-to-one
|
|
// the value is a set of signatures to detect duplicated result elements.
|
|
if enh.matchedSigs == nil {
|
|
enh.matchedSigs = make(map[string]map[uint64]struct{}, len(rightSigs))
|
|
} else {
|
|
for k := range enh.matchedSigs {
|
|
delete(enh.matchedSigs, k)
|
|
}
|
|
}
|
|
matchedSigs := enh.matchedSigs
|
|
|
|
// For all lhs samples find a respective rhs sample and perform
|
|
// the binary operation.
|
|
var lastErr error
|
|
for i, ls := range lhs {
|
|
sig := lhsh[i].signature
|
|
|
|
rs, found := rightSigs[sig] // Look for a match in the rhs Vector.
|
|
if !found {
|
|
continue
|
|
}
|
|
|
|
// Account for potentially swapped sidedness.
|
|
fl, fr := ls.F, rs.F
|
|
hl, hr := ls.H, rs.H
|
|
if matching.Card == parser.CardOneToMany {
|
|
fl, fr = fr, fl
|
|
hl, hr = hr, hl
|
|
}
|
|
floatValue, histogramValue, keep, err := vectorElemBinop(op, fl, fr, hl, hr, pos)
|
|
if err != nil {
|
|
lastErr = err
|
|
}
|
|
switch {
|
|
case returnBool:
|
|
if keep {
|
|
floatValue = 1.0
|
|
} else {
|
|
floatValue = 0.0
|
|
}
|
|
case !keep:
|
|
continue
|
|
}
|
|
metric := resultMetric(ls.Metric, rs.Metric, op, matching, enh)
|
|
if !ev.enableDelayedNameRemoval && returnBool {
|
|
metric = metric.DropMetricName()
|
|
}
|
|
insertedSigs, exists := matchedSigs[sig]
|
|
if matching.Card == parser.CardOneToOne {
|
|
if exists {
|
|
ev.errorf("multiple matches for labels: many-to-one matching must be explicit (group_left/group_right)")
|
|
}
|
|
matchedSigs[sig] = nil // Set existence to true.
|
|
} else {
|
|
// In many-to-one matching the grouping labels have to ensure a unique metric
|
|
// for the result Vector. Check whether those labels have already been added for
|
|
// the same matching labels.
|
|
insertSig := metric.Hash()
|
|
|
|
if !exists {
|
|
insertedSigs = map[uint64]struct{}{}
|
|
matchedSigs[sig] = insertedSigs
|
|
} else if _, duplicate := insertedSigs[insertSig]; duplicate {
|
|
ev.errorf("multiple matches for labels: grouping labels must ensure unique matches")
|
|
}
|
|
insertedSigs[insertSig] = struct{}{}
|
|
}
|
|
|
|
enh.Out = append(enh.Out, Sample{
|
|
Metric: metric,
|
|
F: floatValue,
|
|
H: histogramValue,
|
|
DropName: returnBool,
|
|
})
|
|
}
|
|
return enh.Out, lastErr
|
|
}
|
|
|
|
func signatureFunc(on bool, b []byte, names ...string) func(labels.Labels) string {
|
|
if on {
|
|
slices.Sort(names)
|
|
return func(lset labels.Labels) string {
|
|
return string(lset.BytesWithLabels(b, names...))
|
|
}
|
|
}
|
|
names = append([]string{labels.MetricName}, names...)
|
|
slices.Sort(names)
|
|
return func(lset labels.Labels) string {
|
|
return string(lset.BytesWithoutLabels(b, names...))
|
|
}
|
|
}
|
|
|
|
// resultMetric returns the metric for the given sample(s) based on the Vector
|
|
// binary operation and the matching options.
|
|
func resultMetric(lhs, rhs labels.Labels, op parser.ItemType, matching *parser.VectorMatching, enh *EvalNodeHelper) labels.Labels {
|
|
if enh.resultMetric == nil {
|
|
enh.resultMetric = make(map[string]labels.Labels, len(enh.Out))
|
|
}
|
|
|
|
enh.resetBuilder(lhs)
|
|
buf := bytes.NewBuffer(enh.lblResultBuf[:0])
|
|
enh.lblBuf = lhs.Bytes(enh.lblBuf)
|
|
buf.Write(enh.lblBuf)
|
|
enh.lblBuf = rhs.Bytes(enh.lblBuf)
|
|
buf.Write(enh.lblBuf)
|
|
enh.lblResultBuf = buf.Bytes()
|
|
|
|
if ret, ok := enh.resultMetric[string(enh.lblResultBuf)]; ok {
|
|
return ret
|
|
}
|
|
str := string(enh.lblResultBuf)
|
|
|
|
if shouldDropMetricName(op) {
|
|
enh.lb.Del(labels.MetricName)
|
|
}
|
|
|
|
if matching.Card == parser.CardOneToOne {
|
|
if matching.On {
|
|
enh.lb.Keep(matching.MatchingLabels...)
|
|
} else {
|
|
enh.lb.Del(matching.MatchingLabels...)
|
|
}
|
|
}
|
|
for _, ln := range matching.Include {
|
|
// Included labels from the `group_x` modifier are taken from the "one"-side.
|
|
if v := rhs.Get(ln); v != "" {
|
|
enh.lb.Set(ln, v)
|
|
} else {
|
|
enh.lb.Del(ln)
|
|
}
|
|
}
|
|
|
|
ret := enh.lb.Labels()
|
|
enh.resultMetric[str] = ret
|
|
return ret
|
|
}
|
|
|
|
// VectorscalarBinop evaluates a binary operation between a Vector and a Scalar.
|
|
func (ev *evaluator) VectorscalarBinop(op parser.ItemType, lhs Vector, rhs Scalar, swap, returnBool bool, enh *EvalNodeHelper, pos posrange.PositionRange) (Vector, error) {
|
|
var lastErr error
|
|
for _, lhsSample := range lhs {
|
|
lf, rf := lhsSample.F, rhs.V
|
|
var rh *histogram.FloatHistogram
|
|
lh := lhsSample.H
|
|
// lhs always contains the Vector. If the original position was different
|
|
// swap for calculating the value.
|
|
if swap {
|
|
lf, rf = rf, lf
|
|
lh, rh = rh, lh
|
|
}
|
|
float, histogram, keep, err := vectorElemBinop(op, lf, rf, lh, rh, pos)
|
|
if err != nil {
|
|
lastErr = err
|
|
}
|
|
// Catch cases where the scalar is the LHS in a scalar-vector comparison operation.
|
|
// We want to always keep the vector element value as the output value, even if it's on the RHS.
|
|
if op.IsComparisonOperator() && swap {
|
|
float = rf
|
|
histogram = rh
|
|
}
|
|
if returnBool {
|
|
if keep {
|
|
float = 1.0
|
|
} else {
|
|
float = 0.0
|
|
}
|
|
keep = true
|
|
}
|
|
if keep {
|
|
lhsSample.F = float
|
|
lhsSample.H = histogram
|
|
if shouldDropMetricName(op) || returnBool {
|
|
if !ev.enableDelayedNameRemoval {
|
|
lhsSample.Metric = lhsSample.Metric.DropMetricName()
|
|
}
|
|
lhsSample.DropName = true
|
|
}
|
|
enh.Out = append(enh.Out, lhsSample)
|
|
}
|
|
}
|
|
return enh.Out, lastErr
|
|
}
|
|
|
|
// scalarBinop evaluates a binary operation between two Scalars.
|
|
func scalarBinop(op parser.ItemType, lhs, rhs float64) float64 {
|
|
switch op {
|
|
case parser.ADD:
|
|
return lhs + rhs
|
|
case parser.SUB:
|
|
return lhs - rhs
|
|
case parser.MUL:
|
|
return lhs * rhs
|
|
case parser.DIV:
|
|
return lhs / rhs
|
|
case parser.POW:
|
|
return math.Pow(lhs, rhs)
|
|
case parser.MOD:
|
|
return math.Mod(lhs, rhs)
|
|
case parser.EQLC:
|
|
return btos(lhs == rhs)
|
|
case parser.NEQ:
|
|
return btos(lhs != rhs)
|
|
case parser.GTR:
|
|
return btos(lhs > rhs)
|
|
case parser.LSS:
|
|
return btos(lhs < rhs)
|
|
case parser.GTE:
|
|
return btos(lhs >= rhs)
|
|
case parser.LTE:
|
|
return btos(lhs <= rhs)
|
|
case parser.ATAN2:
|
|
return math.Atan2(lhs, rhs)
|
|
}
|
|
panic(fmt.Errorf("operator %q not allowed for Scalar operations", op))
|
|
}
|
|
|
|
// vectorElemBinop evaluates a binary operation between two Vector elements.
|
|
func vectorElemBinop(op parser.ItemType, lhs, rhs float64, hlhs, hrhs *histogram.FloatHistogram, pos posrange.PositionRange) (float64, *histogram.FloatHistogram, bool, error) {
|
|
opName := parser.ItemTypeStr[op]
|
|
switch {
|
|
case hlhs == nil && hrhs == nil:
|
|
{
|
|
switch op {
|
|
case parser.ADD:
|
|
return lhs + rhs, nil, true, nil
|
|
case parser.SUB:
|
|
return lhs - rhs, nil, true, nil
|
|
case parser.MUL:
|
|
return lhs * rhs, nil, true, nil
|
|
case parser.DIV:
|
|
return lhs / rhs, nil, true, nil
|
|
case parser.POW:
|
|
return math.Pow(lhs, rhs), nil, true, nil
|
|
case parser.MOD:
|
|
return math.Mod(lhs, rhs), nil, true, nil
|
|
case parser.EQLC:
|
|
return lhs, nil, lhs == rhs, nil
|
|
case parser.NEQ:
|
|
return lhs, nil, lhs != rhs, nil
|
|
case parser.GTR:
|
|
return lhs, nil, lhs > rhs, nil
|
|
case parser.LSS:
|
|
return lhs, nil, lhs < rhs, nil
|
|
case parser.GTE:
|
|
return lhs, nil, lhs >= rhs, nil
|
|
case parser.LTE:
|
|
return lhs, nil, lhs <= rhs, nil
|
|
case parser.ATAN2:
|
|
return math.Atan2(lhs, rhs), nil, true, nil
|
|
}
|
|
}
|
|
case hlhs == nil && hrhs != nil:
|
|
{
|
|
switch op {
|
|
case parser.MUL:
|
|
return 0, hrhs.Copy().Mul(lhs).Compact(0), true, nil
|
|
case parser.ADD, parser.SUB, parser.DIV, parser.POW, parser.MOD, parser.EQLC, parser.NEQ, parser.GTR, parser.LSS, parser.GTE, parser.LTE, parser.ATAN2:
|
|
return 0, nil, false, annotations.NewIncompatibleTypesInBinOpInfo("float", opName, "histogram", pos)
|
|
}
|
|
}
|
|
case hlhs != nil && hrhs == nil:
|
|
{
|
|
switch op {
|
|
case parser.MUL:
|
|
return 0, hlhs.Copy().Mul(rhs).Compact(0), true, nil
|
|
case parser.DIV:
|
|
return 0, hlhs.Copy().Div(rhs).Compact(0), true, nil
|
|
case parser.ADD, parser.SUB, parser.POW, parser.MOD, parser.EQLC, parser.NEQ, parser.GTR, parser.LSS, parser.GTE, parser.LTE, parser.ATAN2:
|
|
return 0, nil, false, annotations.NewIncompatibleTypesInBinOpInfo("histogram", opName, "float", pos)
|
|
}
|
|
}
|
|
case hlhs != nil && hrhs != nil:
|
|
{
|
|
switch op {
|
|
case parser.ADD:
|
|
res, err := hlhs.Copy().Add(hrhs)
|
|
if err != nil {
|
|
return 0, nil, false, err
|
|
}
|
|
return 0, res.Compact(0), true, nil
|
|
case parser.SUB:
|
|
res, err := hlhs.Copy().Sub(hrhs)
|
|
if err != nil {
|
|
return 0, nil, false, err
|
|
}
|
|
return 0, res.Compact(0), true, nil
|
|
case parser.EQLC:
|
|
// This operation expects that both histograms are compacted.
|
|
return 0, hlhs, hlhs.Equals(hrhs), nil
|
|
case parser.NEQ:
|
|
// This operation expects that both histograms are compacted.
|
|
return 0, hlhs, !hlhs.Equals(hrhs), nil
|
|
case parser.MUL, parser.DIV, parser.POW, parser.MOD, parser.GTR, parser.LSS, parser.GTE, parser.LTE, parser.ATAN2:
|
|
return 0, nil, false, annotations.NewIncompatibleTypesInBinOpInfo("histogram", opName, "histogram", pos)
|
|
}
|
|
}
|
|
}
|
|
panic(fmt.Errorf("operator %q not allowed for operations between Vectors", op))
|
|
}
|
|
|
|
type groupedAggregation struct {
|
|
floatValue float64
|
|
histogramValue *histogram.FloatHistogram
|
|
floatMean float64
|
|
floatKahanC float64 // "Compensating value" for Kahan summation.
|
|
groupCount float64
|
|
heap vectorByValueHeap
|
|
|
|
// All bools together for better packing within the struct.
|
|
seen bool // Was this output groups seen in the input at this timestamp.
|
|
hasFloat bool // Has at least 1 float64 sample aggregated.
|
|
hasHistogram bool // Has at least 1 histogram sample aggregated.
|
|
incompatibleHistograms bool // If true, group has seen mixed exponential and custom buckets, or incompatible custom buckets.
|
|
groupAggrComplete bool // Used by LIMITK to short-cut series loop when we've reached K elem on every group.
|
|
incrementalMean bool // True after reverting to incremental calculation of the mean value.
|
|
}
|
|
|
|
// aggregation evaluates sum, avg, count, stdvar, stddev or quantile at one timestep on inputMatrix.
|
|
// These functions produce one output series for each group specified in the expression, with just the labels from `by(...)`.
|
|
// outputMatrix should be already populated with grouping labels; groups is one-to-one with outputMatrix.
|
|
// seriesToResult maps inputMatrix indexes to outputMatrix indexes.
|
|
func (ev *evaluator) aggregation(e *parser.AggregateExpr, q float64, inputMatrix, outputMatrix Matrix, seriesToResult []int, groups []groupedAggregation, enh *EvalNodeHelper) annotations.Annotations {
|
|
op := e.Op
|
|
var annos annotations.Annotations
|
|
for i := range groups {
|
|
groups[i].seen = false
|
|
}
|
|
|
|
for si := range inputMatrix {
|
|
f, h, ok := ev.nextValues(enh.Ts, &inputMatrix[si])
|
|
if !ok {
|
|
continue
|
|
}
|
|
|
|
group := &groups[seriesToResult[si]]
|
|
// Initialize this group if it's the first time we've seen it.
|
|
if !group.seen {
|
|
*group = groupedAggregation{
|
|
seen: true,
|
|
floatValue: f,
|
|
floatMean: f,
|
|
incompatibleHistograms: false,
|
|
groupCount: 1,
|
|
}
|
|
switch op {
|
|
case parser.AVG, parser.SUM:
|
|
if h == nil {
|
|
group.hasFloat = true
|
|
} else {
|
|
group.histogramValue = h.Copy()
|
|
group.hasHistogram = true
|
|
}
|
|
case parser.STDVAR, parser.STDDEV:
|
|
switch {
|
|
case h != nil:
|
|
// Ignore histograms for STDVAR and STDDEV.
|
|
group.seen = false
|
|
if op == parser.STDVAR {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("stdvar", e.Expr.PositionRange()))
|
|
} else {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("stddev", e.Expr.PositionRange()))
|
|
}
|
|
case math.IsNaN(f), math.IsInf(f, 0):
|
|
group.floatValue = math.NaN()
|
|
default:
|
|
group.floatValue = 0
|
|
}
|
|
case parser.QUANTILE:
|
|
if h != nil {
|
|
group.seen = false
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("quantile", e.Expr.PositionRange()))
|
|
}
|
|
group.heap = make(vectorByValueHeap, 1)
|
|
group.heap[0] = Sample{F: f}
|
|
case parser.GROUP:
|
|
group.floatValue = 1
|
|
case parser.MIN, parser.MAX:
|
|
if h != nil {
|
|
group.seen = false
|
|
if op == parser.MIN {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("min", e.Expr.PositionRange()))
|
|
} else {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("max", e.Expr.PositionRange()))
|
|
}
|
|
}
|
|
}
|
|
continue
|
|
}
|
|
|
|
if group.incompatibleHistograms {
|
|
continue
|
|
}
|
|
|
|
switch op {
|
|
case parser.SUM:
|
|
if h != nil {
|
|
group.hasHistogram = true
|
|
if group.histogramValue != nil {
|
|
_, err := group.histogramValue.Add(h)
|
|
if err != nil {
|
|
handleAggregationError(err, e, inputMatrix[si].Metric.Get(model.MetricNameLabel), &annos)
|
|
group.incompatibleHistograms = true
|
|
}
|
|
}
|
|
// Otherwise the aggregation contained floats
|
|
// previously and will be invalid anyway. No
|
|
// point in copying the histogram in that case.
|
|
} else {
|
|
group.hasFloat = true
|
|
group.floatValue, group.floatKahanC = kahanSumInc(f, group.floatValue, group.floatKahanC)
|
|
}
|
|
|
|
case parser.AVG:
|
|
group.groupCount++
|
|
if h != nil {
|
|
group.hasHistogram = true
|
|
if group.histogramValue != nil {
|
|
left := h.Copy().Div(group.groupCount)
|
|
right := group.histogramValue.Copy().Div(group.groupCount)
|
|
toAdd, err := left.Sub(right)
|
|
if err != nil {
|
|
handleAggregationError(err, e, inputMatrix[si].Metric.Get(model.MetricNameLabel), &annos)
|
|
group.incompatibleHistograms = true
|
|
continue
|
|
}
|
|
_, err = group.histogramValue.Add(toAdd)
|
|
if err != nil {
|
|
handleAggregationError(err, e, inputMatrix[si].Metric.Get(model.MetricNameLabel), &annos)
|
|
group.incompatibleHistograms = true
|
|
continue
|
|
}
|
|
}
|
|
// Otherwise the aggregation contained floats
|
|
// previously and will be invalid anyway. No
|
|
// point in copying the histogram in that case.
|
|
} else {
|
|
group.hasFloat = true
|
|
if !group.incrementalMean {
|
|
newV, newC := kahanSumInc(f, group.floatValue, group.floatKahanC)
|
|
if !math.IsInf(newV, 0) {
|
|
// The sum doesn't overflow, so we propagate it to the
|
|
// group struct and continue with the regular
|
|
// calculation of the mean value.
|
|
group.floatValue, group.floatKahanC = newV, newC
|
|
break
|
|
}
|
|
// If we are here, we know that the sum _would_ overflow. So
|
|
// instead of continue to sum up, we revert to incremental
|
|
// calculation of the mean value from here on.
|
|
group.incrementalMean = true
|
|
group.floatMean = group.floatValue / (group.groupCount - 1)
|
|
group.floatKahanC /= group.groupCount - 1
|
|
}
|
|
if math.IsInf(group.floatMean, 0) {
|
|
if math.IsInf(f, 0) && (group.floatMean > 0) == (f > 0) {
|
|
// The `floatMean` and `s.F` values are `Inf` of the same sign. They
|
|
// can't be subtracted, but the value of `floatMean` is correct
|
|
// already.
|
|
break
|
|
}
|
|
if !math.IsInf(f, 0) && !math.IsNaN(f) {
|
|
// At this stage, the mean is an infinite. If the added
|
|
// value is neither an Inf or a Nan, we can keep that mean
|
|
// value.
|
|
// This is required because our calculation below removes
|
|
// the mean value, which would look like Inf += x - Inf and
|
|
// end up as a NaN.
|
|
break
|
|
}
|
|
}
|
|
currentMean := group.floatMean + group.floatKahanC
|
|
group.floatMean, group.floatKahanC = kahanSumInc(
|
|
// Divide each side of the `-` by `group.groupCount` to avoid float64 overflows.
|
|
f/group.groupCount-currentMean/group.groupCount,
|
|
group.floatMean,
|
|
group.floatKahanC,
|
|
)
|
|
}
|
|
|
|
case parser.GROUP:
|
|
// Do nothing. Required to avoid the panic in `default:` below.
|
|
|
|
case parser.MAX:
|
|
if h != nil {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("min", e.Expr.PositionRange()))
|
|
continue
|
|
}
|
|
if group.floatValue < f || math.IsNaN(group.floatValue) {
|
|
group.floatValue = f
|
|
}
|
|
|
|
case parser.MIN:
|
|
if h != nil {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("max", e.Expr.PositionRange()))
|
|
continue
|
|
}
|
|
if group.floatValue > f || math.IsNaN(group.floatValue) {
|
|
group.floatValue = f
|
|
}
|
|
|
|
case parser.COUNT:
|
|
group.groupCount++
|
|
|
|
case parser.STDVAR, parser.STDDEV:
|
|
if h == nil { // Ignore native histograms.
|
|
group.groupCount++
|
|
delta := f - group.floatMean
|
|
group.floatMean += delta / group.groupCount
|
|
group.floatValue += delta * (f - group.floatMean)
|
|
if op == parser.STDVAR {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("stdvar", e.Expr.PositionRange()))
|
|
} else {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("stddev", e.Expr.PositionRange()))
|
|
}
|
|
}
|
|
|
|
case parser.QUANTILE:
|
|
if h != nil {
|
|
annos.Add(annotations.NewHistogramIgnoredInAggregationInfo("quantile", e.Expr.PositionRange()))
|
|
continue
|
|
}
|
|
group.heap = append(group.heap, Sample{F: f})
|
|
|
|
default:
|
|
panic(fmt.Errorf("expected aggregation operator but got %q", op))
|
|
}
|
|
}
|
|
|
|
// Construct the output matrix from the aggregated groups.
|
|
numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
|
|
|
|
for ri, aggr := range groups {
|
|
if !aggr.seen {
|
|
continue
|
|
}
|
|
switch op {
|
|
case parser.AVG:
|
|
if aggr.hasFloat && aggr.hasHistogram {
|
|
// We cannot aggregate histogram sample with a float64 sample.
|
|
annos.Add(annotations.NewMixedFloatsHistogramsAggWarning(e.Expr.PositionRange()))
|
|
continue
|
|
}
|
|
switch {
|
|
case aggr.incompatibleHistograms:
|
|
continue
|
|
case aggr.hasHistogram:
|
|
aggr.histogramValue = aggr.histogramValue.Compact(0)
|
|
case aggr.incrementalMean:
|
|
aggr.floatValue = aggr.floatMean + aggr.floatKahanC
|
|
default:
|
|
aggr.floatValue = (aggr.floatValue + aggr.floatKahanC) / aggr.groupCount
|
|
}
|
|
|
|
case parser.COUNT:
|
|
aggr.floatValue = aggr.groupCount
|
|
|
|
case parser.STDVAR:
|
|
aggr.floatValue /= aggr.groupCount
|
|
|
|
case parser.STDDEV:
|
|
aggr.floatValue = math.Sqrt(aggr.floatValue / aggr.groupCount)
|
|
|
|
case parser.QUANTILE:
|
|
aggr.floatValue = quantile(q, aggr.heap)
|
|
|
|
case parser.SUM:
|
|
if aggr.hasFloat && aggr.hasHistogram {
|
|
// We cannot aggregate histogram sample with a float64 sample.
|
|
annos.Add(annotations.NewMixedFloatsHistogramsAggWarning(e.Expr.PositionRange()))
|
|
continue
|
|
}
|
|
switch {
|
|
case aggr.incompatibleHistograms:
|
|
continue
|
|
case aggr.hasHistogram:
|
|
aggr.histogramValue.Compact(0)
|
|
default:
|
|
aggr.floatValue += aggr.floatKahanC
|
|
}
|
|
default:
|
|
// For other aggregations, we already have the right value.
|
|
}
|
|
|
|
ss := &outputMatrix[ri]
|
|
addToSeries(ss, enh.Ts, aggr.floatValue, aggr.histogramValue, numSteps)
|
|
ss.DropName = inputMatrix[ri].DropName
|
|
}
|
|
|
|
return annos
|
|
}
|
|
|
|
// aggregationK evaluates topk, bottomk, limitk, or limit_ratio at one timestep on inputMatrix.
|
|
// Output that has the same labels as the input, but just k of them per group.
|
|
// seriesToResult maps inputMatrix indexes to groups indexes.
|
|
// For an instant query, returns a Matrix in descending order for topk or ascending for bottomk, or without any order for limitk / limit_ratio.
|
|
// For a range query, aggregates output in the seriess map.
|
|
func (ev *evaluator) aggregationK(e *parser.AggregateExpr, k int, r float64, inputMatrix Matrix, seriesToResult []int, groups []groupedAggregation, enh *EvalNodeHelper, seriess map[uint64]Series) (Matrix, annotations.Annotations) {
|
|
op := e.Op
|
|
var s Sample
|
|
var annos annotations.Annotations
|
|
// Used to short-cut the loop for LIMITK if we already collected k elements for every group
|
|
groupsRemaining := len(groups)
|
|
for i := range groups {
|
|
groups[i].seen = false
|
|
}
|
|
|
|
seriesLoop:
|
|
for si := range inputMatrix {
|
|
f, _, ok := ev.nextValues(enh.Ts, &inputMatrix[si])
|
|
if !ok {
|
|
continue
|
|
}
|
|
s = Sample{Metric: inputMatrix[si].Metric, F: f, DropName: inputMatrix[si].DropName}
|
|
|
|
group := &groups[seriesToResult[si]]
|
|
// Initialize this group if it's the first time we've seen it.
|
|
if !group.seen {
|
|
// LIMIT_RATIO is a special case, as we may not add this very sample to the heap,
|
|
// while we also don't know the final size of it.
|
|
if op == parser.LIMIT_RATIO {
|
|
*group = groupedAggregation{
|
|
seen: true,
|
|
heap: make(vectorByValueHeap, 0),
|
|
}
|
|
if ratiosampler.AddRatioSample(r, &s) {
|
|
heap.Push(&group.heap, &s)
|
|
}
|
|
} else {
|
|
*group = groupedAggregation{
|
|
seen: true,
|
|
heap: make(vectorByValueHeap, 1, k),
|
|
}
|
|
group.heap[0] = s
|
|
}
|
|
continue
|
|
}
|
|
|
|
switch op {
|
|
case parser.TOPK:
|
|
// We build a heap of up to k elements, with the smallest element at heap[0].
|
|
switch {
|
|
case len(group.heap) < k:
|
|
heap.Push(&group.heap, &s)
|
|
case group.heap[0].F < s.F || (math.IsNaN(group.heap[0].F) && !math.IsNaN(s.F)):
|
|
// This new element is bigger than the previous smallest element - overwrite that.
|
|
group.heap[0] = s
|
|
if k > 1 {
|
|
heap.Fix(&group.heap, 0) // Maintain the heap invariant.
|
|
}
|
|
}
|
|
|
|
case parser.BOTTOMK:
|
|
// We build a heap of up to k elements, with the biggest element at heap[0].
|
|
switch {
|
|
case len(group.heap) < k:
|
|
heap.Push((*vectorByReverseValueHeap)(&group.heap), &s)
|
|
case group.heap[0].F > s.F || (math.IsNaN(group.heap[0].F) && !math.IsNaN(s.F)):
|
|
// This new element is smaller than the previous biggest element - overwrite that.
|
|
group.heap[0] = s
|
|
if k > 1 {
|
|
heap.Fix((*vectorByReverseValueHeap)(&group.heap), 0) // Maintain the heap invariant.
|
|
}
|
|
}
|
|
|
|
case parser.LIMITK:
|
|
if len(group.heap) < k {
|
|
heap.Push(&group.heap, &s)
|
|
}
|
|
// LIMITK optimization: early break if we've added K elem to _every_ group,
|
|
// especially useful for large timeseries where the user is exploring labels via e.g.
|
|
// limitk(10, my_metric)
|
|
if !group.groupAggrComplete && len(group.heap) == k {
|
|
group.groupAggrComplete = true
|
|
groupsRemaining--
|
|
if groupsRemaining == 0 {
|
|
break seriesLoop
|
|
}
|
|
}
|
|
|
|
case parser.LIMIT_RATIO:
|
|
if ratiosampler.AddRatioSample(r, &s) {
|
|
heap.Push(&group.heap, &s)
|
|
}
|
|
|
|
default:
|
|
panic(fmt.Errorf("expected aggregation operator but got %q", op))
|
|
}
|
|
}
|
|
|
|
// Construct the result from the aggregated groups.
|
|
numSteps := int((ev.endTimestamp-ev.startTimestamp)/ev.interval) + 1
|
|
var mat Matrix
|
|
if ev.endTimestamp == ev.startTimestamp {
|
|
mat = make(Matrix, 0, len(groups))
|
|
}
|
|
|
|
add := func(lbls labels.Labels, f float64, dropName bool) {
|
|
// If this could be an instant query, add directly to the matrix so the result is in consistent order.
|
|
if ev.endTimestamp == ev.startTimestamp {
|
|
mat = append(mat, Series{Metric: lbls, Floats: []FPoint{{T: enh.Ts, F: f}}, DropName: dropName})
|
|
} else {
|
|
// Otherwise the results are added into seriess elements.
|
|
hash := lbls.Hash()
|
|
ss, ok := seriess[hash]
|
|
if !ok {
|
|
ss = Series{Metric: lbls, DropName: dropName}
|
|
}
|
|
addToSeries(&ss, enh.Ts, f, nil, numSteps)
|
|
seriess[hash] = ss
|
|
}
|
|
}
|
|
for _, aggr := range groups {
|
|
if !aggr.seen {
|
|
continue
|
|
}
|
|
switch op {
|
|
case parser.TOPK:
|
|
// The heap keeps the lowest value on top, so reverse it.
|
|
if len(aggr.heap) > 1 {
|
|
sort.Sort(sort.Reverse(aggr.heap))
|
|
}
|
|
for _, v := range aggr.heap {
|
|
add(v.Metric, v.F, v.DropName)
|
|
}
|
|
|
|
case parser.BOTTOMK:
|
|
// The heap keeps the highest value on top, so reverse it.
|
|
if len(aggr.heap) > 1 {
|
|
sort.Sort(sort.Reverse((*vectorByReverseValueHeap)(&aggr.heap)))
|
|
}
|
|
for _, v := range aggr.heap {
|
|
add(v.Metric, v.F, v.DropName)
|
|
}
|
|
|
|
case parser.LIMITK, parser.LIMIT_RATIO:
|
|
for _, v := range aggr.heap {
|
|
add(v.Metric, v.F, v.DropName)
|
|
}
|
|
}
|
|
}
|
|
|
|
return mat, annos
|
|
}
|
|
|
|
// aggregationCountValues evaluates count_values on vec.
|
|
// Outputs as many series per group as there are values in the input.
|
|
func (ev *evaluator) aggregationCountValues(e *parser.AggregateExpr, grouping []string, valueLabel string, vec Vector, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
|
|
type groupCount struct {
|
|
labels labels.Labels
|
|
count int
|
|
}
|
|
result := map[uint64]*groupCount{}
|
|
|
|
var buf []byte
|
|
for _, s := range vec {
|
|
enh.resetBuilder(s.Metric)
|
|
enh.lb.Set(valueLabel, strconv.FormatFloat(s.F, 'f', -1, 64))
|
|
metric := enh.lb.Labels()
|
|
|
|
// Considering the count_values()
|
|
// operator is less frequently used than other aggregations, we're fine having to
|
|
// re-compute the grouping key on each step for this case.
|
|
var groupingKey uint64
|
|
groupingKey, buf = generateGroupingKey(metric, grouping, e.Without, buf)
|
|
|
|
group, ok := result[groupingKey]
|
|
// Add a new group if it doesn't exist.
|
|
if !ok {
|
|
result[groupingKey] = &groupCount{
|
|
labels: generateGroupingLabels(enh, metric, e.Without, grouping),
|
|
count: 1,
|
|
}
|
|
continue
|
|
}
|
|
|
|
group.count++
|
|
}
|
|
|
|
// Construct the result Vector from the aggregated groups.
|
|
for _, aggr := range result {
|
|
enh.Out = append(enh.Out, Sample{
|
|
Metric: aggr.labels,
|
|
F: float64(aggr.count),
|
|
})
|
|
}
|
|
return enh.Out, nil
|
|
}
|
|
|
|
func (ev *evaluator) cleanupMetricLabels(v parser.Value) {
|
|
if v.Type() == parser.ValueTypeMatrix {
|
|
mat := v.(Matrix)
|
|
for i := range mat {
|
|
if mat[i].DropName {
|
|
mat[i].Metric = mat[i].Metric.DropMetricName()
|
|
}
|
|
}
|
|
if mat.ContainsSameLabelset() {
|
|
ev.errorf("vector cannot contain metrics with the same labelset")
|
|
}
|
|
} else if v.Type() == parser.ValueTypeVector {
|
|
vec := v.(Vector)
|
|
for i := range vec {
|
|
if vec[i].DropName {
|
|
vec[i].Metric = vec[i].Metric.DropMetricName()
|
|
}
|
|
}
|
|
if vec.ContainsSameLabelset() {
|
|
ev.errorf("vector cannot contain metrics with the same labelset")
|
|
}
|
|
}
|
|
}
|
|
|
|
func addToSeries(ss *Series, ts int64, f float64, h *histogram.FloatHistogram, numSteps int) {
|
|
if h == nil {
|
|
if ss.Floats == nil {
|
|
ss.Floats = getFPointSlice(numSteps)
|
|
}
|
|
ss.Floats = append(ss.Floats, FPoint{T: ts, F: f})
|
|
return
|
|
}
|
|
if ss.Histograms == nil {
|
|
ss.Histograms = getHPointSlice(numSteps)
|
|
}
|
|
ss.Histograms = append(ss.Histograms, HPoint{T: ts, H: h})
|
|
}
|
|
|
|
func (ev *evaluator) nextValues(ts int64, series *Series) (f float64, h *histogram.FloatHistogram, b bool) {
|
|
switch {
|
|
case len(series.Floats) > 0 && series.Floats[0].T == ts:
|
|
f = series.Floats[0].F
|
|
series.Floats = series.Floats[1:] // Move input vectors forward
|
|
case len(series.Histograms) > 0 && series.Histograms[0].T == ts:
|
|
h = series.Histograms[0].H
|
|
series.Histograms = series.Histograms[1:]
|
|
default:
|
|
return f, h, false
|
|
}
|
|
return f, h, true
|
|
}
|
|
|
|
// handleAggregationError adds the appropriate annotation based on the aggregation error.
|
|
func handleAggregationError(err error, e *parser.AggregateExpr, metricName string, annos *annotations.Annotations) {
|
|
pos := e.Expr.PositionRange()
|
|
if errors.Is(err, histogram.ErrHistogramsIncompatibleSchema) {
|
|
annos.Add(annotations.NewMixedExponentialCustomHistogramsWarning(metricName, pos))
|
|
} else if errors.Is(err, histogram.ErrHistogramsIncompatibleBounds) {
|
|
annos.Add(annotations.NewIncompatibleCustomBucketsHistogramsWarning(metricName, pos))
|
|
}
|
|
}
|
|
|
|
// handleVectorBinopError returns the appropriate annotation based on the vector binary operation error.
|
|
func handleVectorBinopError(err error, e *parser.BinaryExpr) annotations.Annotations {
|
|
if err == nil {
|
|
return nil
|
|
}
|
|
metricName := ""
|
|
pos := e.PositionRange()
|
|
if errors.Is(err, annotations.PromQLInfo) || errors.Is(err, annotations.PromQLWarning) {
|
|
return annotations.New().Add(err)
|
|
}
|
|
if errors.Is(err, histogram.ErrHistogramsIncompatibleSchema) {
|
|
return annotations.New().Add(annotations.NewMixedExponentialCustomHistogramsWarning(metricName, pos))
|
|
} else if errors.Is(err, histogram.ErrHistogramsIncompatibleBounds) {
|
|
return annotations.New().Add(annotations.NewIncompatibleCustomBucketsHistogramsWarning(metricName, pos))
|
|
}
|
|
return nil
|
|
}
|
|
|
|
// groupingKey builds and returns the grouping key for the given metric and
|
|
// grouping labels.
|
|
func generateGroupingKey(metric labels.Labels, grouping []string, without bool, buf []byte) (uint64, []byte) {
|
|
if without {
|
|
return metric.HashWithoutLabels(buf, grouping...)
|
|
}
|
|
|
|
if len(grouping) == 0 {
|
|
// No need to generate any hash if there are no grouping labels.
|
|
return 0, buf
|
|
}
|
|
|
|
return metric.HashForLabels(buf, grouping...)
|
|
}
|
|
|
|
func generateGroupingLabels(enh *EvalNodeHelper, metric labels.Labels, without bool, grouping []string) labels.Labels {
|
|
enh.resetBuilder(metric)
|
|
switch {
|
|
case without:
|
|
enh.lb.Del(grouping...)
|
|
enh.lb.Del(labels.MetricName)
|
|
return enh.lb.Labels()
|
|
case len(grouping) > 0:
|
|
enh.lb.Keep(grouping...)
|
|
return enh.lb.Labels()
|
|
default:
|
|
return labels.EmptyLabels()
|
|
}
|
|
}
|
|
|
|
// btos returns 1 if b is true, 0 otherwise.
|
|
func btos(b bool) float64 {
|
|
if b {
|
|
return 1
|
|
}
|
|
return 0
|
|
}
|
|
|
|
// shouldDropMetricName returns whether the metric name should be dropped in the
|
|
// result of the op operation.
|
|
func shouldDropMetricName(op parser.ItemType) bool {
|
|
switch op {
|
|
case parser.ADD, parser.SUB, parser.DIV, parser.MUL, parser.POW, parser.MOD, parser.ATAN2:
|
|
return true
|
|
default:
|
|
return false
|
|
}
|
|
}
|
|
|
|
// NewOriginContext returns a new context with data about the origin attached.
|
|
func NewOriginContext(ctx context.Context, data map[string]interface{}) context.Context {
|
|
return context.WithValue(ctx, QueryOrigin{}, data)
|
|
}
|
|
|
|
func formatDate(t time.Time) string {
|
|
return t.UTC().Format("2006-01-02T15:04:05.000Z07:00")
|
|
}
|
|
|
|
// unwrapParenExpr does the AST equivalent of removing parentheses around a expression.
|
|
func unwrapParenExpr(e *parser.Expr) {
|
|
for {
|
|
if p, ok := (*e).(*parser.ParenExpr); ok {
|
|
*e = p.Expr
|
|
} else {
|
|
break
|
|
}
|
|
}
|
|
}
|
|
|
|
func unwrapStepInvariantExpr(e parser.Expr) parser.Expr {
|
|
if p, ok := e.(*parser.StepInvariantExpr); ok {
|
|
return p.Expr
|
|
}
|
|
return e
|
|
}
|
|
|
|
// PreprocessExpr wraps all possible step invariant parts of the given expression with
|
|
// StepInvariantExpr. It also resolves the preprocessors.
|
|
func PreprocessExpr(expr parser.Expr, start, end time.Time) parser.Expr {
|
|
detectHistogramStatsDecoding(expr)
|
|
|
|
isStepInvariant := preprocessExprHelper(expr, start, end)
|
|
if isStepInvariant {
|
|
return newStepInvariantExpr(expr)
|
|
}
|
|
return expr
|
|
}
|
|
|
|
// preprocessExprHelper wraps the child nodes of the expression
|
|
// with a StepInvariantExpr wherever it's step invariant. The returned boolean is true if the
|
|
// passed expression qualifies to be wrapped by StepInvariantExpr.
|
|
// It also resolves the preprocessors.
|
|
func preprocessExprHelper(expr parser.Expr, start, end time.Time) bool {
|
|
switch n := expr.(type) {
|
|
case *parser.VectorSelector:
|
|
switch n.StartOrEnd {
|
|
case parser.START:
|
|
n.Timestamp = makeInt64Pointer(timestamp.FromTime(start))
|
|
case parser.END:
|
|
n.Timestamp = makeInt64Pointer(timestamp.FromTime(end))
|
|
}
|
|
return n.Timestamp != nil
|
|
|
|
case *parser.AggregateExpr:
|
|
return preprocessExprHelper(n.Expr, start, end)
|
|
|
|
case *parser.BinaryExpr:
|
|
isInvariant1, isInvariant2 := preprocessExprHelper(n.LHS, start, end), preprocessExprHelper(n.RHS, start, end)
|
|
if isInvariant1 && isInvariant2 {
|
|
return true
|
|
}
|
|
|
|
if isInvariant1 {
|
|
n.LHS = newStepInvariantExpr(n.LHS)
|
|
}
|
|
if isInvariant2 {
|
|
n.RHS = newStepInvariantExpr(n.RHS)
|
|
}
|
|
|
|
return false
|
|
|
|
case *parser.Call:
|
|
_, ok := AtModifierUnsafeFunctions[n.Func.Name]
|
|
isStepInvariant := !ok
|
|
isStepInvariantSlice := make([]bool, len(n.Args))
|
|
for i := range n.Args {
|
|
isStepInvariantSlice[i] = preprocessExprHelper(n.Args[i], start, end)
|
|
isStepInvariant = isStepInvariant && isStepInvariantSlice[i]
|
|
}
|
|
|
|
if isStepInvariant {
|
|
// The function and all arguments are step invariant.
|
|
return true
|
|
}
|
|
|
|
for i, isi := range isStepInvariantSlice {
|
|
if isi {
|
|
n.Args[i] = newStepInvariantExpr(n.Args[i])
|
|
}
|
|
}
|
|
return false
|
|
|
|
case *parser.MatrixSelector:
|
|
return preprocessExprHelper(n.VectorSelector, start, end)
|
|
|
|
case *parser.SubqueryExpr:
|
|
// Since we adjust offset for the @ modifier evaluation,
|
|
// it gets tricky to adjust it for every subquery step.
|
|
// Hence we wrap the inside of subquery irrespective of
|
|
// @ on subquery (given it is also step invariant) so that
|
|
// it is evaluated only once w.r.t. the start time of subquery.
|
|
isInvariant := preprocessExprHelper(n.Expr, start, end)
|
|
if isInvariant {
|
|
n.Expr = newStepInvariantExpr(n.Expr)
|
|
}
|
|
switch n.StartOrEnd {
|
|
case parser.START:
|
|
n.Timestamp = makeInt64Pointer(timestamp.FromTime(start))
|
|
case parser.END:
|
|
n.Timestamp = makeInt64Pointer(timestamp.FromTime(end))
|
|
}
|
|
return n.Timestamp != nil
|
|
|
|
case *parser.ParenExpr:
|
|
return preprocessExprHelper(n.Expr, start, end)
|
|
|
|
case *parser.UnaryExpr:
|
|
return preprocessExprHelper(n.Expr, start, end)
|
|
|
|
case *parser.StringLiteral, *parser.NumberLiteral:
|
|
return true
|
|
}
|
|
|
|
panic(fmt.Sprintf("found unexpected node %#v", expr))
|
|
}
|
|
|
|
func newStepInvariantExpr(expr parser.Expr) parser.Expr {
|
|
return &parser.StepInvariantExpr{Expr: expr}
|
|
}
|
|
|
|
// setOffsetForAtModifier modifies the offset of vector and matrix selector
|
|
// and subquery in the tree to accommodate the timestamp of @ modifier.
|
|
// The offset is adjusted w.r.t. the given evaluation time.
|
|
func setOffsetForAtModifier(evalTime int64, expr parser.Expr) {
|
|
getOffset := func(ts *int64, originalOffset time.Duration, path []parser.Node) time.Duration {
|
|
if ts == nil {
|
|
return originalOffset
|
|
}
|
|
|
|
subqOffset, _, subqTs := subqueryTimes(path)
|
|
if subqTs != nil {
|
|
subqOffset += time.Duration(evalTime-*subqTs) * time.Millisecond
|
|
}
|
|
|
|
offsetForTs := time.Duration(evalTime-*ts) * time.Millisecond
|
|
offsetDiff := offsetForTs - subqOffset
|
|
return originalOffset + offsetDiff
|
|
}
|
|
|
|
parser.Inspect(expr, func(node parser.Node, path []parser.Node) error {
|
|
switch n := node.(type) {
|
|
case *parser.VectorSelector:
|
|
n.Offset = getOffset(n.Timestamp, n.OriginalOffset, path)
|
|
|
|
case *parser.MatrixSelector:
|
|
vs := n.VectorSelector.(*parser.VectorSelector)
|
|
vs.Offset = getOffset(vs.Timestamp, vs.OriginalOffset, path)
|
|
|
|
case *parser.SubqueryExpr:
|
|
n.Offset = getOffset(n.Timestamp, n.OriginalOffset, path)
|
|
}
|
|
return nil
|
|
})
|
|
}
|
|
|
|
// detectHistogramStatsDecoding modifies the expression by setting the
|
|
// SkipHistogramBuckets field in those vector selectors for which it is safe to
|
|
// return only histogram statistics (sum and count), excluding histogram spans
|
|
// and buckets. The function can be treated as an optimization and is not
|
|
// required for correctness.
|
|
func detectHistogramStatsDecoding(expr parser.Expr) {
|
|
parser.Inspect(expr, func(node parser.Node, path []parser.Node) error {
|
|
if n, ok := node.(*parser.BinaryExpr); ok {
|
|
detectHistogramStatsDecoding(n.LHS)
|
|
detectHistogramStatsDecoding(n.RHS)
|
|
return errors.New("stop")
|
|
}
|
|
|
|
n, ok := (node).(*parser.VectorSelector)
|
|
if !ok {
|
|
return nil
|
|
}
|
|
|
|
for _, p := range path {
|
|
call, ok := p.(*parser.Call)
|
|
if !ok {
|
|
continue
|
|
}
|
|
if call.Func.Name == "histogram_count" || call.Func.Name == "histogram_sum" {
|
|
n.SkipHistogramBuckets = true
|
|
break
|
|
}
|
|
if call.Func.Name == "histogram_quantile" || call.Func.Name == "histogram_fraction" {
|
|
n.SkipHistogramBuckets = false
|
|
break
|
|
}
|
|
}
|
|
return errors.New("stop")
|
|
})
|
|
}
|
|
|
|
func makeInt64Pointer(val int64) *int64 {
|
|
valp := new(int64)
|
|
*valp = val
|
|
return valp
|
|
}
|
|
|
|
// RatioSampler allows unit-testing (previously: Randomizer).
|
|
type RatioSampler interface {
|
|
// Return this sample "offset" between [0.0, 1.0]
|
|
sampleOffset(ts int64, sample *Sample) float64
|
|
AddRatioSample(r float64, sample *Sample) bool
|
|
}
|
|
|
|
// HashRatioSampler uses Hash(labels.String()) / maxUint64 as a "deterministic"
|
|
// value in [0.0, 1.0].
|
|
type HashRatioSampler struct{}
|
|
|
|
var ratiosampler RatioSampler = NewHashRatioSampler()
|
|
|
|
func NewHashRatioSampler() *HashRatioSampler {
|
|
return &HashRatioSampler{}
|
|
}
|
|
|
|
func (s *HashRatioSampler) sampleOffset(ts int64, sample *Sample) float64 {
|
|
const (
|
|
float64MaxUint64 = float64(math.MaxUint64)
|
|
)
|
|
return float64(sample.Metric.Hash()) / float64MaxUint64
|
|
}
|
|
|
|
func (s *HashRatioSampler) AddRatioSample(ratioLimit float64, sample *Sample) bool {
|
|
// If ratioLimit >= 0: add sample if sampleOffset is lesser than ratioLimit
|
|
//
|
|
// 0.0 ratioLimit 1.0
|
|
// [---------|--------------------------]
|
|
// [#########...........................]
|
|
//
|
|
// e.g.:
|
|
// sampleOffset==0.3 && ratioLimit==0.4
|
|
// 0.3 < 0.4 ? --> add sample
|
|
//
|
|
// Else if ratioLimit < 0: add sample if rand() return the "complement" of ratioLimit>=0 case
|
|
// (loosely similar behavior to negative array index in other programming languages)
|
|
//
|
|
// 0.0 1+ratioLimit 1.0
|
|
// [---------|--------------------------]
|
|
// [.........###########################]
|
|
//
|
|
// e.g.:
|
|
// sampleOffset==0.3 && ratioLimit==-0.6
|
|
// 0.3 >= 0.4 ? --> don't add sample
|
|
sampleOffset := s.sampleOffset(sample.T, sample)
|
|
return (ratioLimit >= 0 && sampleOffset < ratioLimit) ||
|
|
(ratioLimit < 0 && sampleOffset >= (1.0+ratioLimit))
|
|
}
|
|
|
|
type histogramStatsSeries struct {
|
|
storage.Series
|
|
}
|
|
|
|
func newHistogramStatsSeries(series storage.Series) *histogramStatsSeries {
|
|
return &histogramStatsSeries{Series: series}
|
|
}
|
|
|
|
func (s histogramStatsSeries) Iterator(it chunkenc.Iterator) chunkenc.Iterator {
|
|
return NewHistogramStatsIterator(s.Series.Iterator(it))
|
|
}
|
|
|
|
// gatherVector gathers a Vector for ts from the series in input.
|
|
// output is used as a buffer.
|
|
// If bufHelpers and seriesHelpers are provided, seriesHelpers[i] is appended to bufHelpers for every input index i.
|
|
// The gathered Vector and bufHelper are returned.
|
|
func (ev *evaluator) gatherVector(ts int64, input Matrix, output Vector, bufHelpers, seriesHelpers []EvalSeriesHelper) (Vector, []EvalSeriesHelper) {
|
|
output = output[:0]
|
|
for i, series := range input {
|
|
switch {
|
|
case len(series.Floats) > 0 && series.Floats[0].T == ts:
|
|
s := series.Floats[0]
|
|
output = append(output, Sample{Metric: series.Metric, F: s.F, T: ts, DropName: series.DropName})
|
|
// Move input vectors forward so we don't have to re-scan the same
|
|
// past points at the next step.
|
|
input[i].Floats = series.Floats[1:]
|
|
case len(series.Histograms) > 0 && series.Histograms[0].T == ts:
|
|
s := series.Histograms[0]
|
|
output = append(output, Sample{Metric: series.Metric, H: s.H, T: ts, DropName: series.DropName})
|
|
input[i].Histograms = series.Histograms[1:]
|
|
default:
|
|
continue
|
|
}
|
|
if len(seriesHelpers) > 0 {
|
|
bufHelpers = append(bufHelpers, seriesHelpers[i])
|
|
}
|
|
|
|
// Don't add histogram size here because we only
|
|
// copy the pointer above, not the whole
|
|
// histogram.
|
|
ev.currentSamples++
|
|
if ev.currentSamples > ev.maxSamples {
|
|
ev.error(ErrTooManySamples(env))
|
|
}
|
|
}
|
|
ev.samplesStats.UpdatePeak(ev.currentSamples)
|
|
|
|
return output, bufHelpers
|
|
}
|