// Copyright 2013 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package promql
import (
"bytes"
"container/heap"
"context"
"errors"
"fmt"
"math"
"reflect"
"runtime"
"sort"
"strconv"
"sync"
"time"
"github.com/go-kit/log"
"github.com/go-kit/log/level"
"github.com/grafana/regexp"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/common/model"
"go.opentelemetry.io/otel"
"go.opentelemetry.io/otel/attribute"
"go.opentelemetry.io/otel/trace"
"golang.org/x/exp/slices"
"github.com/prometheus/prometheus/model/histogram"
"github.com/prometheus/prometheus/model/labels"
"github.com/prometheus/prometheus/model/timestamp"
"github.com/prometheus/prometheus/model/value"
"github.com/prometheus/prometheus/promql/parser"
"github.com/prometheus/prometheus/storage"
"github.com/prometheus/prometheus/tsdb/chunkenc"
"github.com/prometheus/prometheus/util/annotations"
"github.com/prometheus/prometheus/util/stats"
"github.com/prometheus/prometheus/util/zeropool"
)
const (
namespace = "prometheus"
subsystem = "engine"
queryTag = "query"
env = "query execution"
defaultLookbackDelta = 5 * time.Minute
// The largest SampleValue that can be converted to an int64 without overflow.
maxInt64 = 9223372036854774784
// The smallest SampleValue that can be converted to an int64 without underflow.
minInt64 = -9223372036854775808
// Max initial size for the pooled points slices.
// The getHPointSlice and getFPointSlice functions are called with an estimated size which often can be
// over-estimated.
maxPointsSliceSize = 5000
)
type engineMetrics struct {
currentQueries prometheus.Gauge
maxConcurrentQueries prometheus.Gauge
queryLogEnabled prometheus.Gauge
queryLogFailures prometheus.Counter
queryQueueTime prometheus.Observer
queryPrepareTime prometheus.Observer
queryInnerEval prometheus.Observer
queryResultSort prometheus.Observer
querySamples prometheus.Counter
}
// convertibleToInt64 returns true if v does not over-/underflow an int64.
func convertibleToInt64(v float64) bool {
return v <= maxInt64 && v >= minInt64
}
type (
// ErrQueryTimeout is returned if a query timed out during processing.
ErrQueryTimeout string
// ErrQueryCanceled is returned if a query was canceled during processing.
ErrQueryCanceled string
// ErrTooManySamples is returned if a query would load more than the maximum allowed samples into memory.
ErrTooManySamples string
// ErrStorage is returned if an error was encountered in the storage layer
// during query handling.
ErrStorage struct{ Err error }
)
func (e ErrQueryTimeout) Error() string {
return fmt.Sprintf("query timed out in %s", string(e))
}
func (e ErrQueryCanceled) Error() string {
return fmt.Sprintf("query was canceled in %s", string(e))
}
func (e ErrTooManySamples) Error() string {
return fmt.Sprintf("query processing would load too many samples into memory in %s", string(e))
}
func (e ErrStorage) Error() string {
return e.Err.Error()
}
// QueryLogger is an interface that can be used to log all the queries logged
// by the engine.
type QueryLogger interface {
Log(...interface{}) error
Close() error
}
// A Query is derived from an a raw query string and can be run against an engine
// it is associated with.
type Query interface {
// Exec processes the query. Can only be called once.
Exec(ctx context.Context) *Result
// Close recovers memory used by the query result.
Close()
// Statement returns the parsed statement of the query.
Statement() parser.Statement
// Stats returns statistics about the lifetime of the query.
Stats() *stats.Statistics
// Cancel signals that a running query execution should be aborted.
Cancel()
// String returns the original query string.
String() string
}
type PrometheusQueryOpts struct {
// Enables recording per-step statistics if the engine has it enabled as well. Disabled by default.
enablePerStepStats bool
// Lookback delta duration for this query.
lookbackDelta time.Duration
}
var _ QueryOpts = &PrometheusQueryOpts{}
func NewPrometheusQueryOpts(enablePerStepStats bool, lookbackDelta time.Duration) QueryOpts {
return &PrometheusQueryOpts{
enablePerStepStats: enablePerStepStats,
lookbackDelta: lookbackDelta,
}
}
func (p *PrometheusQueryOpts) EnablePerStepStats() bool {
return p.enablePerStepStats
}
func (p *PrometheusQueryOpts) LookbackDelta() time.Duration {
return p.lookbackDelta
}
type QueryOpts interface {
// Enables recording per-step statistics if the engine has it enabled as well. Disabled by default.
EnablePerStepStats() bool
// Lookback delta duration for this query.
LookbackDelta() time.Duration
}
// query implements the Query interface.
type query struct {
// Underlying data provider.
queryable storage.Queryable
// The original query string.
q string
// Statement of the parsed query.
stmt parser.Statement
// Timer stats for the query execution.
stats *stats.QueryTimers
// Sample stats for the query execution.
sampleStats *stats.QuerySamples
// Result matrix for reuse.
matrix Matrix
// Cancellation function for the query.
cancel func()
// The engine against which the query is executed.
ng *Engine
}
type QueryOrigin struct{}
// Statement implements the Query interface.
// Calling this after Exec may result in panic,
// see https://github.com/prometheus/prometheus/issues/8949.
func (q *query) Statement() parser.Statement {
return q.stmt
}
// String implements the Query interface.
func (q *query) String() string {
return q.q
}
// Stats implements the Query interface.
func (q *query) Stats() *stats.Statistics {
return &stats.Statistics{
Timers: q.stats,
Samples: q.sampleStats,
}
}
// Cancel implements the Query interface.
func (q *query) Cancel() {
if q.cancel != nil {
q.cancel()
}
}
// Close implements the Query interface.
func (q *query) Close() {
for _, s := range q.matrix {
putFPointSlice(s.Floats)
putHPointSlice(s.Histograms)
}
}
// Exec implements the Query interface.
func (q *query) Exec(ctx context.Context) *Result {
if span := trace.SpanFromContext(ctx); span != nil {
span.SetAttributes(attribute.String(queryTag, q.stmt.String()))
}
// Exec query.
res, warnings, err := q.ng.exec(ctx, q)
return &Result{Err: err, Value: res, Warnings: warnings}
}
// contextDone returns an error if the context was canceled or timed out.
func contextDone(ctx context.Context, env string) error {
if err := ctx.Err(); err != nil {
return contextErr(err, env)
}
return nil
}
func contextErr(err error, env string) error {
switch {
case errors.Is(err, context.Canceled):
return ErrQueryCanceled(env)
case errors.Is(err, context.DeadlineExceeded):
return ErrQueryTimeout(env)
default:
return err
}
}
// QueryTracker provides access to two features:
//
// 1) Tracking of active query. If PromQL engine crashes while executing any query, such query should be present
// in the tracker on restart, hence logged. After the logging on restart, the tracker gets emptied.
//
// 2) Enforcement of the maximum number of concurrent queries.
type QueryTracker interface {
// GetMaxConcurrent returns maximum number of concurrent queries that are allowed by this tracker.
GetMaxConcurrent() int
// Insert inserts query into query tracker. This call must block if maximum number of queries is already running.
// If Insert doesn't return error then returned integer value should be used in subsequent Delete call.
// Insert should return error if context is finished before query can proceed, and integer value returned in this case should be ignored by caller.
Insert(ctx context.Context, query string) (int, error)
// Delete removes query from activity tracker. InsertIndex is value returned by Insert call.
Delete(insertIndex int)
}
// EngineOpts contains configuration options used when creating a new Engine.
type EngineOpts struct {
Logger log.Logger
Reg prometheus.Registerer
MaxSamples int
Timeout time.Duration
ActiveQueryTracker QueryTracker
// LookbackDelta determines the time since the last sample after which a time
// series is considered stale.
LookbackDelta time.Duration
// NoStepSubqueryIntervalFn is the default evaluation interval of
// a subquery in milliseconds if no step in range vector was specified `[30m:<step>]`.
NoStepSubqueryIntervalFn func(rangeMillis int64) int64
// EnableAtModifier if true enables @ modifier. Disabled otherwise. This
// is supposed to be enabled for regular PromQL (as of Prometheus v2.33)
// but the option to disable it is still provided here for those using
// the Engine outside of Prometheus.
EnableAtModifier bool
// EnableNegativeOffset if true enables negative (-) offset
// values. Disabled otherwise. This is supposed to be enabled for
// regular PromQL (as of Prometheus v2.33) but the option to disable it
// is still provided here for those using the Engine outside of
// Prometheus.
EnableNegativeOffset bool
// EnablePerStepStats if true allows for per-step stats to be computed on request. Disabled otherwise.
EnablePerStepStats bool
}
// Engine handles the lifetime of queries from beginning to end.
// It is connected to a querier.
type Engine struct {
logger log.Logger
metrics *engineMetrics
timeout time.Duration
maxSamplesPerQuery int
activeQueryTracker QueryTracker
queryLogger QueryLogger
queryLoggerLock sync.RWMutex
lookbackDelta time.Duration
noStepSubqueryIntervalFn func(rangeMillis int64) int64
enableAtModifier bool
enableNegativeOffset bool
enablePerStepStats bool
}
// NewEngine returns a new engine.
func NewEngine(opts EngineOpts) *Engine {
if opts.Logger == nil {
opts.Logger = log.NewNopLogger()
}
queryResultSummary := prometheus.NewSummaryVec(prometheus.SummaryOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_duration_seconds",
Help: "Query timings",
Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
},
[]string{"slice"},
)
metrics := &engineMetrics{
currentQueries: prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queries",
Help: "The current number of queries being executed or waiting.",
}),
queryLogEnabled: prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_log_enabled",
Help: "State of the query log.",
}),
queryLogFailures: prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_log_failures_total",
Help: "The number of query log failures.",
}),
maxConcurrentQueries: prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queries_concurrent_max",
Help: "The max number of concurrent queries.",
}),
querySamples: prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_samples_total",
Help: "The total number of samples loaded by all queries.",
}),
queryQueueTime: queryResultSummary.WithLabelValues("queue_time"),
queryPrepareTime: queryResultSummary.WithLabelValues("prepare_time"),
queryInnerEval: queryResultSummary.WithLabelValues("inner_eval"),
queryResultSort: queryResultSummary.WithLabelValues("result_sort"),
}
if t := opts.ActiveQueryTracker; t != nil {
metrics.maxConcurrentQueries.Set(float64(t.GetMaxConcurrent()))
} else {
metrics.maxConcurrentQueries.Set(-1)
}
if opts.LookbackDelta == 0 {
opts.LookbackDelta = defaultLookbackDelta
if l := opts.Logger; l != nil {
level.Debug(l).Log("msg", "Lookback delta is zero, setting to default value", "value", defaultLookbackDelta)
}
}
if opts.Reg != nil {
opts.Reg.MustRegister(
metrics.currentQueries,
metrics.maxConcurrentQueries,
metrics.queryLogEnabled,
metrics.queryLogFailures,
metrics.querySamples,
queryResultSummary,
)
}
return &Engine{
timeout: opts.Timeout,
logger: opts.Logger,
metrics: metrics,
maxSamplesPerQuery: opts.MaxSamples,
activeQueryTracker: opts.ActiveQueryTracker,
lookbackDelta: opts.LookbackDelta,
noStepSubqueryIntervalFn: opts.NoStepSubqueryIntervalFn,
enableAtModifier: opts.EnableAtModifier,
enableNegativeOffset: opts.EnableNegativeOffset,
enablePerStepStats: opts.EnablePerStepStats,
}
}
// SetQueryLogger sets the query logger.
func (ng *Engine) SetQueryLogger(l QueryLogger) {
ng.queryLoggerLock.Lock()
defer ng.queryLoggerLock.Unlock()
if ng.queryLogger != nil {
// An error closing the old file descriptor should
// not make reload fail; only log a warning.
err := ng.queryLogger.Close()
if err != nil {
level.Warn(ng.logger).Log("msg", "Error while closing the previous query log file", "err", err)
}
}
ng.queryLogger = l
if l != nil {
ng.metrics.queryLogEnabled.Set(1)
} else {
ng.metrics.queryLogEnabled.Set(0)
}
}
// NewInstantQuery returns an evaluation query for the given expression at the given time.
func (ng *Engine) NewInstantQuery(ctx context.Context, q storage.Queryable, opts QueryOpts, qs string, ts time.Time) (Query, error) {
pExpr, qry := ng.newQuery(q, qs, opts, ts, ts, 0)
finishQueue, err := ng.queueActive(ctx, qry)
if err != nil {
return nil, err
}
defer finishQueue()
expr, err := parser.ParseExpr(qs)
if err != nil {
return nil, err
}
if err := ng.validateOpts(expr); err != nil {
return nil, err
}
*pExpr = PreprocessExpr(expr, ts, ts)
return qry, nil
}
// NewRangeQuery returns an evaluation query for the given time range and with
// 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) {
pExpr, qry := ng.newQuery(q, qs, opts, start, end, interval)
finishQueue, err := ng.queueActive(ctx, qry)
if err != nil {
return nil, err
}
defer finishQueue()
expr, err := parser.ParseExpr(qs)
if err != nil {
return nil, err
}
if err := ng.validateOpts(expr); err != nil {
return nil, err
}
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()))
}
*pExpr = PreprocessExpr(expr, start, end)
return qry, nil
}
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
}
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))
}
f := []interface{}{"params", params}
if err != nil {
f = append(f, "error", err)
}
f = append(f, "stats", stats.NewQueryStats(q.Stats()))
if span := trace.SpanFromContext(ctx); span != nil {
f = append(f, "spanID", span.SpanContext().SpanID())
}
if origin := ctx.Value(QueryOrigin{}); origin != nil {
for k, v := range origin.(map[string]interface{}) {
f = append(f, k, v)
}
}
if err := l.Log(f...); err != nil {
ng.metrics.queryLogFailures.Inc()
level.Error(ng.logger).Log("msg", "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,
ctx: ctxInnerEval,
maxSamples: ng.maxSamplesPerQuery,
logger: ng.logger,
lookbackDelta: s.LookbackDelta,
samplesStats: query.sampleStats,
noStepSubqueryIntervalFn: ng.noStepSubqueryIntervalFn,
}
query.sampleStats.InitStepTracking(start, start, 1)
val, warnings, err := evaluator.Eval(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}
} else {
vector[i] = Sample{Metric: s.Metric, F: s.Floats[0].F, T: start}
}
}
return vector, warnings, nil
case parser.ValueTypeScalar:
return Scalar{V: mat[0].Floats[0].F, T: start}, warnings, nil
case parser.ValueTypeMatrix:
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),
ctx: ctxInnerEval,
maxSamples: ng.maxSamplesPerQuery,
logger: ng.logger,
lookbackDelta: s.LookbackDelta,
samplesStats: query.sampleStats,
noStepSubqueryIntervalFn: ng.noStepSubqueryIntervalFn,
}
query.sampleStats.InitStepTracking(evaluator.startTimestamp, evaluator.endTimestamp, evaluator.interval)
val, warnings, err := evaluator.Eval(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.
sortSpanTimer, _ := query.stats.GetSpanTimer(ctx, stats.ResultSortTime, ng.metrics.queryResultSort)
sort.Sort(mat)
sortSpanTimer.Finish()
return mat, warnings, nil
}
// 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 {
start -= durationMilliseconds(s.LookbackDelta)
} 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
start -= durationMilliseconds(evalRange)
}
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
}
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
}
series, ws, err := expandSeriesSet(ctx, e.UnexpandedSeriesSet)
e.Series = 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 {
ctx context.Context
startTimestamp int64 // Start time in milliseconds.
endTimestamp int64 // End time in milliseconds.
interval int64 // Interval in milliseconds.
maxSamples int
currentSamples int
logger log.Logger
lookbackDelta time.Duration
samplesStats *stats.QuerySamples
noStepSubqueryIntervalFn func(rangeMillis int64) int64
}
// 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)]
level.Error(ev.logger).Log("msg", "runtime panic in parser", "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(expr parser.Expr) (v parser.Value, ws annotations.Annotations, err error) {
defer ev.recover(expr, &ws, &err)
v, ws = ev.eval(expr)
return v, ws, nil
}
// EvalSeriesHelper stores extra information about a series.
type EvalSeriesHelper struct {
// The grouping key used by aggregation.
groupingKey uint64
// 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.
// DropMetricName and label_*.
Dmn map[uint64]labels.Labels
// funcHistogramQuantile for classic histograms.
signatureToMetricWithBuckets map[string]*metricWithBuckets
// label_replace.
regex *regexp.Regexp
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
}
func (enh *EvalNodeHelper) resetBuilder(lbls labels.Labels) {
if enh.lb == nil {
enh.lb = labels.NewBuilder(lbls)
} else {
enh.lb.Reset(lbls)
}
}
// DropMetricName is a cached version of DropMetricName.
func (enh *EvalNodeHelper) DropMetricName(l labels.Labels) labels.Labels {
if enh.Dmn == nil {
enh.Dmn = make(map[uint64]labels.Labels, len(enh.Out))
}
h := l.Hash()
ret, ok := enh.Dmn[h]
if ok {
return ret
}
ret = dropMetricName(l)
enh.Dmn[h] = ret
return ret
}
// 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(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(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)}
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(ev.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 {
vectors[i] = vectors[i][:0]
if prepSeries != nil {
bufHelpers[i] = bufHelpers[i][:0]
}
for si, series := range matrixes[i] {
switch {
case len(series.Floats) > 0 && series.Floats[0].T == ts:
vectors[i] = append(vectors[i], Sample{Metric: series.Metric, F: series.Floats[0].F, T: ts})
// Move input vectors forward so we don't have to re-scan the same
// past points at the next step.
matrixes[i][si].Floats = series.Floats[1:]
case len(series.Histograms) > 0 && series.Histograms[0].T == ts:
vectors[i] = append(vectors[i], Sample{Metric: series.Metric, H: series.Histograms[0].H, T: ts})
matrixes[i][si].Histograms = series.Histograms[1:]
default:
continue
}
if prepSeries != nil {
bufHelpers[i] = append(bufHelpers[i], seriesHelpers[i][si])
}
ev.currentSamples++
if ev.currentSamples > ev.maxSamples {
ev.error(ErrTooManySamples(env))
}
}
args[i] = vectors[i]
ev.samplesStats.UpdatePeak(ev.currentSamples)
}
// 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))
}
ev.samplesStats.UpdatePeak(ev.currentSamples)
// If this could be an instant query, shortcut so as not to change sort order.
if ev.endTimestamp == ev.startTimestamp {
if 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}}}
} else {
mat[i] = Series{Metric: s.Metric, Histograms: []HPoint{{T: ts, H: s.H}}}
}
}
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}, ts}
}
if sample.H == nil {
if ss.Floats == nil {
ss.Floats = getFPointSlice(numSteps)
}
ss.Floats = append(ss.Floats, FPoint{T: ts, F: sample.F})
} else {
if ss.Histograms == nil {
ss.Histograms = getHPointSlice(numSteps)
}
ss.Histograms = append(ss.Histograms, HPoint{T: ts, H: sample.H})
}
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
}
// 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(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(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(expr parser.Expr) (parser.Value, annotations.Annotations) {
// This is the top-level evaluation method.
// Thus, we check for timeout/cancellation here.
if err := contextDone(ev.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.
ctxWithSpan, span := otel.Tracer("").Start(ev.ctx, stats.InnerEvalTime.SpanOperation()+" eval "+reflect.TypeOf(expr).String())
ev.ctx = ctxWithSpan
defer span.End()
switch e := expr.(type) {
case *parser.AggregateExpr:
// Grouping labels must be sorted (expected both by generateGroupingKey() and aggregation()).
sortedGrouping := e.Grouping
slices.Sort(sortedGrouping)
// Prepare a function to initialise series helpers with the grouping key.
buf := make([]byte, 0, 1024)
initSeries := func(series labels.Labels, h *EvalSeriesHelper) {
h.groupingKey, buf = generateGroupingKey(series, sortedGrouping, e.Without, buf)
}
unwrapParenExpr(&e.Param)
param := unwrapStepInvariantExpr(e.Param)
unwrapParenExpr(¶m)
if s, ok := param.(*parser.StringLiteral); ok {
return ev.rangeEval(initSeries, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return ev.aggregation(e, sortedGrouping, s.Val, v[0].(Vector), sh[0], enh)
}, e.Expr)
}
return ev.rangeEval(initSeries, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
var param float64
if e.Param != nil {
param = v[0].(Vector)[0].F
}
return ev.aggregation(e, sortedGrouping, param, v[1].(Vector), sh[1], enh)
}, e.Param, e.Expr)
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(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(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
}
}
if !matrixArg {
// Does not have a matrix argument.
return ev.rangeEval(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(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(ev.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
inMatrix := make(Matrix, 1)
inArgs[matrixArgIndex] = inMatrix
enh := &EvalNodeHelper{Out: make(Vector, 0, 1)}
// Process all the calls for one time series at a time.
it := storage.NewBuffer(selRange)
var chkIter chunkenc.Iterator
for i, s := range selVS.Series {
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()
// 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.
if e.Func.Name != "last_over_time" {
metric = dropMetricName(metric)
}
ss := Series{
Metric: metric,
}
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
}
}
maxt := ts - offset
mint := maxt - selRange
// Evaluate the matrix selector for this series for this step.
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 = getFPointSlice(numSteps)
}
ss.Floats = append(ss.Floats, FPoint{F: outVec[0].F, T: ts})
} else {
if ss.Histograms == nil {
ss.Histograms = getHPointSlice(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 {
mat = append(mat, ss)
ev.currentSamples += len(ss.Floats) + histSamples
} else {
ev.error(ErrTooManySamples(env))
}
}
ev.samplesStats.UpdatePeak(ev.currentSamples)
}
ev.samplesStats.UpdatePeak(ev.currentSamples)
ev.currentSamples -= len(floats) + totalHPointSize(histograms)
putFPointSlice(floats)
putHPointSlice(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,
},
}, warnings
}
if mat.ContainsSameLabelset() {
ev.errorf("vector cannot contain metrics with the same labelset")
}
return mat, warnings
case *parser.ParenExpr:
return ev.eval(e.Expr)
case *parser.UnaryExpr:
val, ws := ev.eval(e.Expr)
mat := val.(Matrix)
if e.Op == parser.SUB {
for i := range mat {
mat[i].Metric = dropMetricName(mat[i].Metric)
for j := range mat[i].Floats {
mat[i].Floats[j].F = -mat[i].Floats[j].F
}
}
if 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(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(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(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(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(initSignatures, func(v []parser.Value, sh [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return ev.VectorBinop(e.Op, v[0].(Vector), v[1].(Vector), e.VectorMatching, e.ReturnBool, sh[0], sh[1], enh), nil
}, e.LHS, e.RHS)
}
case lt == parser.ValueTypeVector && rt == parser.ValueTypeScalar:
return ev.rangeEval(nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return ev.VectorscalarBinop(e.Op, v[0].(Vector), Scalar{V: v[1].(Vector)[0].F}, false, e.ReturnBool, enh), nil
}, e.LHS, e.RHS)
case lt == parser.ValueTypeScalar && rt == parser.ValueTypeVector:
return ev.rangeEval(nil, func(v []parser.Value, _ [][]EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
return ev.VectorscalarBinop(e.Op, v[1].(Vector), Scalar{V: v[0].(Vector)[0].F}, true, e.ReturnBool, enh), nil
}, e.LHS, e.RHS)
}
case *parser.NumberLiteral:
return ev.rangeEval(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:
return String{V: e.Val, T: ev.startTimestamp}, nil
case *parser.VectorSelector:
ws, err := checkAndExpandSeriesSet(ev.ctx, e)
if err != nil {
ev.error(errWithWarnings{fmt.Errorf("expanding series: %w", err), ws})
}
mat := make(Matrix, 0, len(e.Series))
it := storage.NewMemoizedEmptyIterator(durationMilliseconds(ev.lookbackDelta))
var chkIter chunkenc.Iterator
for i, s := range e.Series {
chkIter = s.Iterator(chkIter)
it.Reset(chkIter)
ss := Series{
Metric: e.Series[i].Labels(),
}
for ts, step := ev.startTimestamp, -1; ts <= ev.endTimestamp; ts += ev.interval {
step++
_, f, h, ok := ev.vectorSelectorSingle(it, e, ts)
if ok {
if ev.currentSamples < ev.maxSamples {
if h == nil {
if ss.Floats == nil {
ss.Floats = getFPointSlice(numSteps)
}
ss.Floats = append(ss.Floats, FPoint{F: f, T: ts})
ev.currentSamples++
ev.samplesStats.IncrementSamplesAtStep(step, 1)
} else {
if ss.Histograms == nil {
ss.Histograms = getHPointSlice(numSteps)
}
point := HPoint{H: h, T: ts}
ss.Histograms = append(ss.Histograms, point)
histSize := point.size()
ev.currentSamples += histSize
ev.samplesStats.IncrementSamplesAtStep(step, int64(histSize))
}
} else {
ev.error(ErrTooManySamples(env))
}
}
}
if len(ss.Floats)+len(ss.Histograms) > 0 {
mat = append(mat, ss)
}
}
ev.samplesStats.UpdatePeak(ev.currentSamples)
return mat, ws
case *parser.MatrixSelector:
if ev.startTimestamp != ev.endTimestamp {
panic(errors.New("cannot do range evaluation of matrix selector"))
}
return ev.matrixSelector(e)
case *parser.SubqueryExpr:
offsetMillis := durationMilliseconds(e.Offset)
rangeMillis := durationMilliseconds(e.Range)
newEv := &evaluator{
endTimestamp: ev.endTimestamp - offsetMillis,
ctx: ev.ctx,
currentSamples: ev.currentSamples,
maxSamples: ev.maxSamples,
logger: ev.logger,
lookbackDelta: ev.lookbackDelta,
samplesStats: ev.samplesStats.NewChild(),
noStepSubqueryIntervalFn: ev.noStepSubqueryIntervalFn,
}
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(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(ce)
}
newEv := &evaluator{
startTimestamp: ev.startTimestamp,
endTimestamp: ev.startTimestamp, // Always a single evaluation.
interval: ev.interval,
ctx: ev.ctx,
currentSamples: ev.currentSamples,
maxSamples: ev.maxSamples,
logger: ev.logger,
lookbackDelta: ev.lookbackDelta,
samplesStats: ev.samplesStats.NewChild(),
noStepSubqueryIntervalFn: ev.noStepSubqueryIntervalFn,
}
res, ws := newEv.eval(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(fmt.Errorf("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))
}
func (ev *evaluator) rangeEvalTimestampFunctionOverVectorSelector(vs *parser.VectorSelector, call FunctionCall, e *parser.Call) (parser.Value, annotations.Annotations) {
ws, err := checkAndExpandSeriesSet(ev.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))
}
return ev.rangeEval(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, f, h, ok := ev.vectorSelectorSingle(it, vs, enh.Ts)
if ok {
vec = append(vec, Sample{
Metric: s.Labels(),
T: t,
F: f,
H: h,
})
histSize := 0
if h != nil {
histSize := h.Size() / 16 // 16 bytes per sample.
ev.currentSamples += histSize
}
ev.currentSamples++
ev.samplesStats.IncrementSamplesAtTimestamp(enh.Ts, int64(1+histSize))
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, node *parser.VectorSelector, ts int64) (
int64, float64, *histogram.FloatHistogram, bool,
) {
refTime := ts - durationMilliseconds(node.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]
)
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])
}
}
// matrixSelector evaluates a *parser.MatrixSelector expression.
func (ev *evaluator) matrixSelector(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(ev.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(ev.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 + 1
} 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++ {
}
copy(histograms, histograms[drop:])
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 + 1
} 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 = getHPointSlice(16)
}
n := len(histograms)
if n < cap(histograms) {
histograms = histograms[:n+1]
} else {
histograms = append(histograms, HPoint{})
}
histograms[n].T, histograms[n].H = buf.AtFloatHistogram(histograms[n].H)
if value.IsStaleNaN(histograms[n].H.Sum) {
histograms = histograms[:n]
continue loop
}
if ev.currentSamples >= ev.maxSamples {
ev.error(ErrTooManySamples(env))
}
ev.currentSamples += histograms[n].size()
}
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 {
if ev.currentSamples >= ev.maxSamples {
ev.error(ErrTooManySamples(env))
}
ev.currentSamples++
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:
t, h := it.AtFloatHistogram()
if t == maxt && !value.IsStaleNaN(h.Sum) {
if ev.currentSamples >= ev.maxSamples {
ev.error(ErrTooManySamples(env))
}
if histograms == nil {
histograms = getHPointSlice(16)
}
point := HPoint{T: t, H: h}
histograms = append(histograms, point)
ev.currentSamples += point.size()
}
case chunkenc.ValFloat:
t, f := it.At()
if t == maxt && !value.IsStaleNaN(f) {
if ev.currentSamples >= ev.maxSamples {
ev.error(ErrTooManySamples(env))
}
if floats == nil {
floats = getFPointSlice(16)
}
floats = append(floats, FPoint{T: t, F: f})
ev.currentSamples++
}
}
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) Vector {
if matching.Card == parser.CardManyToMany {
panic("many-to-many only allowed for set operators")
}
if len(lhs) == 0 || len(rhs) == 0 {
return 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.
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 := vectorElemBinop(op, fl, fr, hl, hr)
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 returnBool {
metric = enh.DropMetricName(metric)
}
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,
})
}
return enh.Out
}
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) Vector {
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 := vectorElemBinop(op, lf, rf, lh, rh)
// 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 {
lhsSample.Metric = enh.DropMetricName(lhsSample.Metric)
}
enh.Out = append(enh.Out, lhsSample)
}
}
return enh.Out
}
func dropMetricName(l labels.Labels) labels.Labels {
return labels.NewBuilder(l).Del(labels.MetricName).Labels()
}
// 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) (float64, *histogram.FloatHistogram, bool) {
switch op {
case parser.ADD:
if hlhs != nil && hrhs != nil {
// The histogram being added must have the larger schema
// code (i.e. the higher resolution).
if hrhs.Schema >= hlhs.Schema {
return 0, hlhs.Copy().Add(hrhs).Compact(0), true
}
return 0, hrhs.Copy().Add(hlhs).Compact(0), true
}
return lhs + rhs, nil, true
case parser.SUB:
if hlhs != nil && hrhs != nil {
// The histogram being subtracted must have the larger schema
// code (i.e. the higher resolution).
if hrhs.Schema >= hlhs.Schema {
return 0, hlhs.Copy().Sub(hrhs).Compact(0), true
}
return 0, hrhs.Copy().Mul(-1).Add(hlhs).Compact(0), true
}
return lhs - rhs, nil, true
case parser.MUL:
if hlhs != nil && hrhs == nil {
return 0, hlhs.Copy().Mul(rhs), true
}
if hlhs == nil && hrhs != nil {
return 0, hrhs.Copy().Mul(lhs), true
}
return lhs * rhs, nil, true
case parser.DIV:
if hlhs != nil && hrhs == nil {
return 0, hlhs.Copy().Div(rhs), true
}
return lhs / rhs, nil, true
case parser.POW:
return math.Pow(lhs, rhs), nil, true
case parser.MOD:
return math.Mod(lhs, rhs), nil, true
case parser.EQLC:
return lhs, nil, lhs == rhs
case parser.NEQ:
return lhs, nil, lhs != rhs
case parser.GTR:
return lhs, nil, lhs > rhs
case parser.LSS:
return lhs, nil, lhs < rhs
case parser.GTE:
return lhs, nil, lhs >= rhs
case parser.LTE:
return lhs, nil, lhs <= rhs
case parser.ATAN2:
return math.Atan2(lhs, rhs), nil, true
}
panic(fmt.Errorf("operator %q not allowed for operations between Vectors", op))
}
type groupedAggregation struct {
hasFloat bool // Has at least 1 float64 sample aggregated.
hasHistogram bool // Has at least 1 histogram sample aggregated.
labels labels.Labels
floatValue float64
histogramValue *histogram.FloatHistogram
floatMean float64
histogramMean *histogram.FloatHistogram
groupCount int
heap vectorByValueHeap
reverseHeap vectorByReverseValueHeap
}
// aggregation evaluates an aggregation operation on a Vector. The provided grouping labels
// must be sorted.
func (ev *evaluator) aggregation(e *parser.AggregateExpr, grouping []string, param interface{}, vec Vector, seriesHelper []EvalSeriesHelper, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
op := e.Op
without := e.Without
var annos annotations.Annotations
result := map[uint64]*groupedAggregation{}
orderedResult := []*groupedAggregation{}
var k int64
if op == parser.TOPK || op == parser.BOTTOMK {
f := param.(float64)
if !convertibleToInt64(f) {
ev.errorf("Scalar value %v overflows int64", f)
}
k = int64(f)
if k < 1 {
return Vector{}, annos
}
}
var q float64
if op == parser.QUANTILE {
q = param.(float64)
}
var valueLabel string
var recomputeGroupingKey bool
if op == parser.COUNT_VALUES {
valueLabel = param.(string)
if !model.LabelName(valueLabel).IsValid() {
ev.errorf("invalid label name %q", valueLabel)
}
if !without {
// We're changing the grouping labels so we have to ensure they're still sorted
// and we have to flag to recompute the grouping key. 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.
grouping = append(grouping, valueLabel)
slices.Sort(grouping)
recomputeGroupingKey = true
}
}
var buf []byte
for si, s := range vec {
metric := s.Metric
if op == parser.COUNT_VALUES {
enh.resetBuilder(metric)
enh.lb.Set(valueLabel, strconv.FormatFloat(s.F, 'f', -1, 64))
metric = enh.lb.Labels()
// We've changed the metric so we have to recompute the grouping key.
recomputeGroupingKey = true
}
// We can use the pre-computed grouping key unless grouping labels have changed.
var groupingKey uint64
if !recomputeGroupingKey {
groupingKey = seriesHelper[si].groupingKey
} else {
groupingKey, buf = generateGroupingKey(metric, grouping, without, buf)
}
group, ok := result[groupingKey]
// Add a new group if it doesn't exist.
if !ok {
var m labels.Labels
enh.resetBuilder(metric)
switch {
case without:
enh.lb.Del(grouping...)
enh.lb.Del(labels.MetricName)
m = enh.lb.Labels()
case len(grouping) > 0:
enh.lb.Keep(grouping...)
m = enh.lb.Labels()
default:
m = labels.EmptyLabels()
}
newAgg := &groupedAggregation{
labels: m,
floatValue: s.F,
floatMean: s.F,
groupCount: 1,
}
switch {
case s.H == nil:
newAgg.hasFloat = true
case op == parser.SUM:
newAgg.histogramValue = s.H.Copy()
newAgg.hasHistogram = true
case op == parser.AVG:
newAgg.histogramMean = s.H.Copy()
newAgg.hasHistogram = true
case op == parser.STDVAR || op == parser.STDDEV:
newAgg.groupCount = 0
}
result[groupingKey] = newAgg
orderedResult = append(orderedResult, newAgg)
inputVecLen := int64(len(vec))
resultSize := k
switch {
case k > inputVecLen:
resultSize = inputVecLen
case k == 0:
resultSize = 1
}
switch op {
case parser.STDVAR, parser.STDDEV:
result[groupingKey].floatValue = 0
case parser.TOPK, parser.QUANTILE:
result[groupingKey].heap = make(vectorByValueHeap, 1, resultSize)
result[groupingKey].heap[0] = Sample{
F: s.F,
Metric: s.Metric,
}
case parser.BOTTOMK:
result[groupingKey].reverseHeap = make(vectorByReverseValueHeap, 1, resultSize)
result[groupingKey].reverseHeap[0] = Sample{
F: s.F,
Metric: s.Metric,
}
case parser.GROUP:
result[groupingKey].floatValue = 1
}
continue
}
switch op {
case parser.SUM:
if s.H != nil {
group.hasHistogram = true
if group.histogramValue != nil {
// The histogram being added must have
// an equal or larger schema.
if s.H.Schema >= group.histogramValue.Schema {
group.histogramValue.Add(s.H)
} else {
group.histogramValue = s.H.Copy().Add(group.histogramValue)
}
}
// 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 += s.F
}
case parser.AVG:
group.groupCount++
if s.H != nil {
group.hasHistogram = true
if group.histogramMean != nil {
left := s.H.Copy().Div(float64(group.groupCount))
right := group.histogramMean.Copy().Div(float64(group.groupCount))
// The histogram being added/subtracted must have
// an equal or larger schema.
if s.H.Schema >= group.histogramMean.Schema {
toAdd := right.Mul(-1).Add(left)
group.histogramMean.Add(toAdd)
} else {
toAdd := left.Sub(right)
group.histogramMean = toAdd.Add(group.histogramMean)
}
}
// 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 math.IsInf(group.floatMean, 0) {
if math.IsInf(s.F, 0) && (group.floatMean > 0) == (s.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(s.F, 0) && !math.IsNaN(s.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
}
}
// Divide each side of the `-` by `group.groupCount` to avoid float64 overflows.
group.floatMean += s.F/float64(group.groupCount) - group.floatMean/float64(group.groupCount)
}
case parser.GROUP:
// Do nothing. Required to avoid the panic in `default:` below.
case parser.MAX:
if group.floatValue < s.F || math.IsNaN(group.floatValue) {
group.floatValue = s.F
}
case parser.MIN:
if group.floatValue > s.F || math.IsNaN(group.floatValue) {
group.floatValue = s.F
}
case parser.COUNT, parser.COUNT_VALUES:
group.groupCount++
case parser.STDVAR, parser.STDDEV:
if s.H == nil { // Ignore native histograms.
group.groupCount++
delta := s.F - group.floatMean
group.floatMean += delta / float64(group.groupCount)
group.floatValue += delta * (s.F - group.floatMean)
}
case parser.TOPK:
// We build a heap of up to k elements, with the smallest element at heap[0].
switch {
case int64(len(group.heap)) < k:
heap.Push(&group.heap, &Sample{
F: s.F,
Metric: s.Metric,
})
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] = Sample{
F: s.F,
Metric: s.Metric,
}
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 int64(len(group.reverseHeap)) < k:
heap.Push(&group.reverseHeap, &Sample{
F: s.F,
Metric: s.Metric,
})
case group.reverseHeap[0].F > s.F || (math.IsNaN(group.reverseHeap[0].F) && !math.IsNaN(s.F)):
// This new element is smaller than the previous biggest element - overwrite that.
group.reverseHeap[0] = Sample{
F: s.F,
Metric: s.Metric,
}
if k > 1 {
heap.Fix(&group.reverseHeap, 0) // Maintain the heap invariant.
}
}
case parser.QUANTILE:
group.heap = append(group.heap, s)
default:
panic(fmt.Errorf("expected aggregation operator but got %q", op))
}
}
// Construct the result Vector from the aggregated groups.
for _, aggr := range orderedResult {
switch op {
case parser.AVG:
if aggr.hasFloat && aggr.hasHistogram {
// We cannot aggregate histogram sample with a float64 sample.
metricName := aggr.labels.Get(labels.MetricName)
annos.Add(annotations.NewMixedFloatsHistogramsWarning(metricName, e.Expr.PositionRange()))
continue
}
if aggr.hasHistogram {
aggr.histogramValue = aggr.histogramMean.Compact(0)
} else {
aggr.floatValue = aggr.floatMean
}
case parser.COUNT, parser.COUNT_VALUES:
aggr.floatValue = float64(aggr.groupCount)
case parser.STDVAR:
aggr.floatValue /= float64(aggr.groupCount)
case parser.STDDEV:
aggr.floatValue = math.Sqrt(aggr.floatValue / float64(aggr.groupCount))
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 {
enh.Out = append(enh.Out, Sample{
Metric: v.Metric,
F: v.F,
})
}
continue // Bypass default append.
case parser.BOTTOMK:
// The heap keeps the highest value on top, so reverse it.
if len(aggr.reverseHeap) > 1 {
sort.Sort(sort.Reverse(aggr.reverseHeap))
}
for _, v := range aggr.reverseHeap {
enh.Out = append(enh.Out, Sample{
Metric: v.Metric,
F: v.F,
})
}
continue // Bypass default append.
case parser.QUANTILE:
if math.IsNaN(q) || q < 0 || q > 1 {
annos.Add(annotations.NewInvalidQuantileWarning(q, e.Param.PositionRange()))
}
aggr.floatValue = quantile(q, aggr.heap)
case parser.SUM:
if aggr.hasFloat && aggr.hasHistogram {
// We cannot aggregate histogram sample with a float64 sample.
metricName := aggr.labels.Get(labels.MetricName)
annos.Add(annotations.NewMixedFloatsHistogramsWarning(metricName, e.Expr.PositionRange()))
continue
}
if aggr.hasHistogram {
aggr.histogramValue.Compact(0)
}
default:
// For other aggregations, we already have the right value.
}
enh.Out = append(enh.Out, Sample{
Metric: aggr.labels,
F: aggr.floatValue,
H: aggr.histogramValue,
})
}
return enh.Out, annos
}
// 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...)
}
// 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 {
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
})
}
func makeInt64Pointer(val int64) *int64 {
valp := new(int64)
*valp = val
return valp
}