prometheus/promql/engine.go

1428 lines
39 KiB
Go

// 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 (
"container/heap"
"fmt"
"math"
"runtime"
"sort"
"time"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/common/log"
"github.com/prometheus/common/model"
"golang.org/x/net/context"
"github.com/prometheus/prometheus/storage/local"
"github.com/prometheus/prometheus/storage/metric"
"github.com/prometheus/prometheus/util/stats"
)
const (
namespace = "prometheus"
subsystem = "engine"
// The largest SampleValue that can be converted to an int64 without overflow.
maxInt64 model.SampleValue = 9223372036854774784
// The smallest SampleValue that can be converted to an int64 without underflow.
minInt64 model.SampleValue = -9223372036854775808
)
var (
currentQueries = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queries",
Help: "The current number of queries being executed or waiting.",
})
maxConcurrentQueries = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queries_concurrent_max",
Help: "The max number of concurrent queries.",
})
queryPrepareTime = prometheus.NewSummary(
prometheus.SummaryOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_duration_seconds",
Help: "Query timmings",
ConstLabels: prometheus.Labels{"slice": "prepare_time"},
},
)
queryInnerEval = prometheus.NewSummary(
prometheus.SummaryOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_duration_seconds",
Help: "Query timmings",
ConstLabels: prometheus.Labels{"slice": "inner_eval"},
},
)
queryResultAppend = prometheus.NewSummary(
prometheus.SummaryOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_duration_seconds",
Help: "Query timmings",
ConstLabels: prometheus.Labels{"slice": "result_append"},
},
)
queryResultSort = prometheus.NewSummary(
prometheus.SummaryOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "query_duration_seconds",
Help: "Query timmings",
ConstLabels: prometheus.Labels{"slice": "result_sort"},
},
)
)
func init() {
prometheus.MustRegister(currentQueries)
prometheus.MustRegister(maxConcurrentQueries)
prometheus.MustRegister(queryPrepareTime)
prometheus.MustRegister(queryInnerEval)
prometheus.MustRegister(queryResultAppend)
prometheus.MustRegister(queryResultSort)
}
// convertibleToInt64 returns true if v does not over-/underflow an int64.
func convertibleToInt64(v model.SampleValue) bool {
return v <= maxInt64 && v >= minInt64
}
// sampleStream is a stream of Values belonging to an attached COWMetric.
type sampleStream struct {
Metric metric.Metric
Values []model.SamplePair
}
// sample is a single sample belonging to a COWMetric.
type sample struct {
Metric metric.Metric
Value model.SampleValue
Timestamp model.Time
}
// vector is basically only an alias for model.Samples, but the
// contract is that in a Vector, all Samples have the same timestamp.
type vector []*sample
func (vector) Type() model.ValueType { return model.ValVector }
func (vec vector) String() string { return vec.value().String() }
func (vec vector) value() model.Vector {
val := make(model.Vector, len(vec))
for i, s := range vec {
val[i] = &model.Sample{
Metric: s.Metric.Copy().Metric,
Value: s.Value,
Timestamp: s.Timestamp,
}
}
return val
}
// matrix is a slice of SampleStreams that implements sort.Interface and
// has a String method.
type matrix []*sampleStream
func (matrix) Type() model.ValueType { return model.ValMatrix }
func (mat matrix) String() string { return mat.value().String() }
func (mat matrix) value() model.Matrix {
val := make(model.Matrix, len(mat))
for i, ss := range mat {
val[i] = &model.SampleStream{
Metric: ss.Metric.Copy().Metric,
Values: ss.Values,
}
}
return val
}
// Result holds the resulting value of an execution or an error
// if any occurred.
type Result struct {
Err error
Value model.Value
}
// Vector returns a vector if the result value is one. An error is returned if
// the result was an error or the result value is not a vector.
func (r *Result) Vector() (model.Vector, error) {
if r.Err != nil {
return nil, r.Err
}
v, ok := r.Value.(model.Vector)
if !ok {
return nil, fmt.Errorf("query result is not a vector")
}
return v, nil
}
// Matrix returns a matrix. An error is returned if
// the result was an error or the result value is not a matrix.
func (r *Result) Matrix() (model.Matrix, error) {
if r.Err != nil {
return nil, r.Err
}
v, ok := r.Value.(model.Matrix)
if !ok {
return nil, fmt.Errorf("query result is not a range vector")
}
return v, nil
}
// Scalar returns a scalar value. An error is returned if
// the result was an error or the result value is not a scalar.
func (r *Result) Scalar() (*model.Scalar, error) {
if r.Err != nil {
return nil, r.Err
}
v, ok := r.Value.(*model.Scalar)
if !ok {
return nil, fmt.Errorf("query result is not a scalar")
}
return v, nil
}
func (r *Result) String() string {
if r.Err != nil {
return r.Err.Error()
}
if r.Value == nil {
return ""
}
return r.Value.String()
}
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
)
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)) }
// 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 and
Exec(ctx context.Context) *Result
// Statement returns the parsed statement of the query.
Statement() Statement
// Stats returns statistics about the lifetime of the query.
Stats() *stats.TimerGroup
// Cancel signals that a running query execution should be aborted.
Cancel()
}
// query implements the Query interface.
type query struct {
// The original query string.
q string
// Statement of the parsed query.
stmt Statement
// Timer stats for the query execution.
stats *stats.TimerGroup
// Cancelation function for the query.
cancel func()
// The engine against which the query is executed.
ng *Engine
}
// Statement implements the Query interface.
func (q *query) Statement() Statement {
return q.stmt
}
// Stats implements the Query interface.
func (q *query) Stats() *stats.TimerGroup {
return q.stats
}
// Cancel implements the Query interface.
func (q *query) Cancel() {
if q.cancel != nil {
q.cancel()
}
}
// Exec implements the Query interface.
func (q *query) Exec(ctx context.Context) *Result {
res, err := q.ng.exec(ctx, q)
return &Result{Err: err, Value: res}
}
// contextDone returns an error if the context was canceled or timed out.
func contextDone(ctx context.Context, env string) error {
select {
case <-ctx.Done():
err := ctx.Err()
switch err {
case context.Canceled:
return ErrQueryCanceled(env)
case context.DeadlineExceeded:
return ErrQueryTimeout(env)
default:
return err
}
default:
return nil
}
}
// Engine handles the lifetime of queries from beginning to end.
// It is connected to a querier.
type Engine struct {
// A Querier constructor against an underlying storage.
queryable Queryable
// The gate limiting the maximum number of concurrent and waiting queries.
gate *queryGate
options *EngineOptions
}
// Queryable allows opening a storage querier.
type Queryable interface {
Querier() (local.Querier, error)
}
// NewEngine returns a new engine.
func NewEngine(queryable Queryable, o *EngineOptions) *Engine {
if o == nil {
o = DefaultEngineOptions
}
maxConcurrentQueries.Set(float64(o.MaxConcurrentQueries))
return &Engine{
queryable: queryable,
gate: newQueryGate(o.MaxConcurrentQueries),
options: o,
}
}
// EngineOptions contains configuration parameters for an Engine.
type EngineOptions struct {
MaxConcurrentQueries int
Timeout time.Duration
}
// DefaultEngineOptions are the default engine options.
var DefaultEngineOptions = &EngineOptions{
MaxConcurrentQueries: 20,
Timeout: 2 * time.Minute,
}
// NewInstantQuery returns an evaluation query for the given expression at the given time.
func (ng *Engine) NewInstantQuery(qs string, ts model.Time) (Query, error) {
expr, err := ParseExpr(qs)
if err != nil {
return nil, err
}
qry := ng.newQuery(expr, ts, ts, 0)
qry.q = qs
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(qs string, start, end model.Time, interval time.Duration) (Query, error) {
expr, err := ParseExpr(qs)
if err != nil {
return nil, err
}
if expr.Type() != model.ValVector && expr.Type() != model.ValScalar {
return nil, fmt.Errorf("invalid expression type %q for range query, must be scalar or instant vector", documentedType(expr.Type()))
}
qry := ng.newQuery(expr, start, end, interval)
qry.q = qs
return qry, nil
}
func (ng *Engine) newQuery(expr Expr, start, end model.Time, interval time.Duration) *query {
es := &EvalStmt{
Expr: expr,
Start: start,
End: end,
Interval: interval,
}
qry := &query{
stmt: es,
ng: ng,
stats: stats.NewTimerGroup(),
}
return qry
}
// testStmt is an internal helper statement that allows execution
// of an arbitrary function during handling. It is used to test the Engine.
type testStmt func(context.Context) error
func (testStmt) String() string { return "test statement" }
func (testStmt) stmt() {}
func (ng *Engine) newTestQuery(f func(context.Context) error) Query {
qry := &query{
q: "test statement",
stmt: testStmt(f),
ng: ng,
stats: stats.NewTimerGroup(),
}
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) (model.Value, error) {
currentQueries.Inc()
defer currentQueries.Dec()
ctx, cancel := context.WithTimeout(ctx, ng.options.Timeout)
q.cancel = cancel
queueTimer := q.stats.GetTimer(stats.ExecQueueTime).Start()
if err := ng.gate.Start(ctx); err != nil {
return nil, err
}
defer ng.gate.Done()
queueTimer.Stop()
// Cancel when execution is done or an error was raised.
defer q.cancel()
const env = "query execution"
evalTimer := q.stats.GetTimer(stats.TotalEvalTime).Start()
defer evalTimer.Stop()
// The base context might already be canceled on the first iteration (e.g. during shutdown).
if err := contextDone(ctx, env); err != nil {
return nil, err
}
switch s := q.Statement().(type) {
case *EvalStmt:
return ng.execEvalStmt(ctx, q, s)
case testStmt:
return nil, s(ctx)
}
panic(fmt.Errorf("promql.Engine.exec: unhandled statement of type %T", q.Statement()))
}
// execEvalStmt evaluates the expression of an evaluation statement for the given time range.
func (ng *Engine) execEvalStmt(ctx context.Context, query *query, s *EvalStmt) (model.Value, error) {
querier, err := ng.queryable.Querier()
if err != nil {
return nil, err
}
defer querier.Close()
prepareTimer := query.stats.GetTimer(stats.QueryPreparationTime).Start()
err = ng.populateIterators(ctx, querier, s)
prepareTimer.Stop()
queryPrepareTime.Observe(prepareTimer.ElapsedTime().Seconds())
if err != nil {
return nil, err
}
defer ng.closeIterators(s)
evalTimer := query.stats.GetTimer(stats.InnerEvalTime).Start()
// Instant evaluation.
if s.Start == s.End && s.Interval == 0 {
evaluator := &evaluator{
Timestamp: s.Start,
ctx: ctx,
}
val, err := evaluator.Eval(s.Expr)
if err != nil {
return nil, err
}
// Turn matrix and vector types with protected metrics into
// model.* types.
switch v := val.(type) {
case vector:
val = v.value()
case matrix:
val = v.value()
}
evalTimer.Stop()
queryInnerEval.Observe(evalTimer.ElapsedTime().Seconds())
return val, nil
}
numSteps := int(s.End.Sub(s.Start) / s.Interval)
// Range evaluation.
sampleStreams := map[model.Fingerprint]*sampleStream{}
for ts := s.Start; !ts.After(s.End); ts = ts.Add(s.Interval) {
if err := contextDone(ctx, "range evaluation"); err != nil {
return nil, err
}
evaluator := &evaluator{
Timestamp: ts,
ctx: ctx,
}
val, err := evaluator.Eval(s.Expr)
if err != nil {
return nil, err
}
switch v := val.(type) {
case *model.Scalar:
// As the expression type does not change we can safely default to 0
// as the fingerprint for scalar expressions.
ss := sampleStreams[0]
if ss == nil {
ss = &sampleStream{Values: make([]model.SamplePair, 0, numSteps)}
sampleStreams[0] = ss
}
ss.Values = append(ss.Values, model.SamplePair{
Value: v.Value,
Timestamp: v.Timestamp,
})
case vector:
for _, sample := range v {
fp := sample.Metric.Metric.Fingerprint()
ss := sampleStreams[fp]
if ss == nil {
ss = &sampleStream{
Metric: sample.Metric,
Values: make([]model.SamplePair, 0, numSteps),
}
sampleStreams[fp] = ss
}
ss.Values = append(ss.Values, model.SamplePair{
Value: sample.Value,
Timestamp: sample.Timestamp,
})
}
default:
panic(fmt.Errorf("promql.Engine.exec: invalid expression type %q", val.Type()))
}
}
evalTimer.Stop()
queryInnerEval.Observe(evalTimer.ElapsedTime().Seconds())
if err := contextDone(ctx, "expression evaluation"); err != nil {
return nil, err
}
appendTimer := query.stats.GetTimer(stats.ResultAppendTime).Start()
mat := matrix{}
for _, ss := range sampleStreams {
mat = append(mat, ss)
}
appendTimer.Stop()
queryResultAppend.Observe(appendTimer.ElapsedTime().Seconds())
if err := contextDone(ctx, "expression evaluation"); err != nil {
return nil, err
}
// Turn matrix type with protected metric into model.Matrix.
resMatrix := mat.value()
sortTimer := query.stats.GetTimer(stats.ResultSortTime).Start()
sort.Sort(resMatrix)
sortTimer.Stop()
queryResultSort.Observe(sortTimer.ElapsedTime().Seconds())
return resMatrix, nil
}
func (ng *Engine) populateIterators(ctx context.Context, querier local.Querier, s *EvalStmt) error {
var queryErr error
Inspect(s.Expr, func(node Node) bool {
switch n := node.(type) {
case *VectorSelector:
if s.Start.Equal(s.End) {
n.iterators, queryErr = querier.QueryInstant(
ctx,
s.Start.Add(-n.Offset),
StalenessDelta,
n.LabelMatchers...,
)
} else {
n.iterators, queryErr = querier.QueryRange(
ctx,
s.Start.Add(-n.Offset-StalenessDelta),
s.End.Add(-n.Offset),
n.LabelMatchers...,
)
}
if queryErr != nil {
return false
}
case *MatrixSelector:
n.iterators, queryErr = querier.QueryRange(
ctx,
s.Start.Add(-n.Offset-n.Range),
s.End.Add(-n.Offset),
n.LabelMatchers...,
)
if queryErr != nil {
return false
}
}
return true
})
return queryErr
}
func (ng *Engine) closeIterators(s *EvalStmt) {
Inspect(s.Expr, func(node Node) bool {
switch n := node.(type) {
case *VectorSelector:
for _, it := range n.iterators {
it.Close()
}
case *MatrixSelector:
for _, it := range n.iterators {
it.Close()
}
}
return true
})
}
// An evaluator evaluates given expressions at a fixed timestamp. 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
Timestamp model.Time
}
// fatalf causes a panic with the input formatted into an error.
func (ev *evaluator) errorf(format string, args ...interface{}) {
ev.error(fmt.Errorf(format, args...))
}
// fatal 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(errp *error) {
e := recover()
if e != nil {
if _, ok := e.(runtime.Error); ok {
// Print the stack trace but do not inhibit the running application.
buf := make([]byte, 64<<10)
buf = buf[:runtime.Stack(buf, false)]
log.Errorf("parser panic: %v\n%s", e, buf)
*errp = fmt.Errorf("unexpected error")
} else {
*errp = e.(error)
}
}
}
// evalScalar attempts to evaluate e to a scalar value and errors otherwise.
func (ev *evaluator) evalScalar(e Expr) *model.Scalar {
val := ev.eval(e)
sv, ok := val.(*model.Scalar)
if !ok {
ev.errorf("expected scalar but got %s", documentedType(val.Type()))
}
return sv
}
// evalVector attempts to evaluate e to a vector value and errors otherwise.
func (ev *evaluator) evalVector(e Expr) vector {
val := ev.eval(e)
vec, ok := val.(vector)
if !ok {
ev.errorf("expected instant vector but got %s", documentedType(val.Type()))
}
return vec
}
// evalInt attempts to evaluate e into an integer and errors otherwise.
func (ev *evaluator) evalInt(e Expr) int64 {
sc := ev.evalScalar(e)
if !convertibleToInt64(sc.Value) {
ev.errorf("scalar value %v overflows int64", sc.Value)
}
return int64(sc.Value)
}
// evalFloat attempts to evaluate e into a float and errors otherwise.
func (ev *evaluator) evalFloat(e Expr) float64 {
sc := ev.evalScalar(e)
return float64(sc.Value)
}
// evalMatrix attempts to evaluate e into a matrix and errors otherwise.
// The error message uses the term "range vector" to match the user facing
// documentation.
func (ev *evaluator) evalMatrix(e Expr) matrix {
val := ev.eval(e)
mat, ok := val.(matrix)
if !ok {
ev.errorf("expected range vector but got %s", documentedType(val.Type()))
}
return mat
}
// evalString attempts to evaluate e to a string value and errors otherwise.
func (ev *evaluator) evalString(e Expr) *model.String {
val := ev.eval(e)
sv, ok := val.(*model.String)
if !ok {
ev.errorf("expected string but got %s", documentedType(val.Type()))
}
return sv
}
// evalOneOf evaluates e and errors unless the result is of one of the given types.
func (ev *evaluator) evalOneOf(e Expr, t1, t2 model.ValueType) model.Value {
val := ev.eval(e)
if val.Type() != t1 && val.Type() != t2 {
ev.errorf("expected %s or %s but got %s", documentedType(t1), documentedType(t2), documentedType(val.Type()))
}
return val
}
func (ev *evaluator) Eval(expr Expr) (v model.Value, err error) {
defer ev.recover(&err)
return ev.eval(expr), nil
}
// eval evaluates the given expression as the given AST expression node requires.
func (ev *evaluator) eval(expr Expr) model.Value {
// This is the top-level evaluation method.
// Thus, we check for timeout/cancelation here.
if err := contextDone(ev.ctx, "expression evaluation"); err != nil {
ev.error(err)
}
switch e := expr.(type) {
case *AggregateExpr:
vector := ev.evalVector(e.Expr)
return ev.aggregation(e.Op, e.Grouping, e.Without, e.KeepCommonLabels, e.Param, vector)
case *BinaryExpr:
lhs := ev.evalOneOf(e.LHS, model.ValScalar, model.ValVector)
rhs := ev.evalOneOf(e.RHS, model.ValScalar, model.ValVector)
switch lt, rt := lhs.Type(), rhs.Type(); {
case lt == model.ValScalar && rt == model.ValScalar:
return &model.Scalar{
Value: scalarBinop(e.Op, lhs.(*model.Scalar).Value, rhs.(*model.Scalar).Value),
Timestamp: ev.Timestamp,
}
case lt == model.ValVector && rt == model.ValVector:
switch e.Op {
case itemLAND:
return ev.vectorAnd(lhs.(vector), rhs.(vector), e.VectorMatching)
case itemLOR:
return ev.vectorOr(lhs.(vector), rhs.(vector), e.VectorMatching)
case itemLUnless:
return ev.vectorUnless(lhs.(vector), rhs.(vector), e.VectorMatching)
default:
return ev.vectorBinop(e.Op, lhs.(vector), rhs.(vector), e.VectorMatching, e.ReturnBool)
}
case lt == model.ValVector && rt == model.ValScalar:
return ev.vectorScalarBinop(e.Op, lhs.(vector), rhs.(*model.Scalar), false, e.ReturnBool)
case lt == model.ValScalar && rt == model.ValVector:
return ev.vectorScalarBinop(e.Op, rhs.(vector), lhs.(*model.Scalar), true, e.ReturnBool)
}
case *Call:
return e.Func.Call(ev, e.Args)
case *MatrixSelector:
return ev.matrixSelector(e)
case *NumberLiteral:
return &model.Scalar{Value: e.Val, Timestamp: ev.Timestamp}
case *ParenExpr:
return ev.eval(e.Expr)
case *StringLiteral:
return &model.String{Value: e.Val, Timestamp: ev.Timestamp}
case *UnaryExpr:
se := ev.evalOneOf(e.Expr, model.ValScalar, model.ValVector)
// Only + and - are possible operators.
if e.Op == itemSUB {
switch v := se.(type) {
case *model.Scalar:
v.Value = -v.Value
case vector:
for i, sv := range v {
v[i].Value = -sv.Value
}
}
}
return se
case *VectorSelector:
return ev.vectorSelector(e)
}
panic(fmt.Errorf("unhandled expression of type: %T", expr))
}
// vectorSelector evaluates a *VectorSelector expression.
func (ev *evaluator) vectorSelector(node *VectorSelector) vector {
vec := vector{}
for _, it := range node.iterators {
refTime := ev.Timestamp.Add(-node.Offset)
samplePair := it.ValueAtOrBeforeTime(refTime)
if samplePair.Timestamp.Before(refTime.Add(-StalenessDelta)) {
continue // Sample outside of staleness policy window.
}
vec = append(vec, &sample{
Metric: it.Metric(),
Value: samplePair.Value,
Timestamp: ev.Timestamp,
})
}
return vec
}
// matrixSelector evaluates a *MatrixSelector expression.
func (ev *evaluator) matrixSelector(node *MatrixSelector) matrix {
interval := metric.Interval{
OldestInclusive: ev.Timestamp.Add(-node.Range - node.Offset),
NewestInclusive: ev.Timestamp.Add(-node.Offset),
}
sampleStreams := make([]*sampleStream, 0, len(node.iterators))
for _, it := range node.iterators {
samplePairs := it.RangeValues(interval)
if len(samplePairs) == 0 {
continue
}
if node.Offset != 0 {
for _, sp := range samplePairs {
sp.Timestamp = sp.Timestamp.Add(node.Offset)
}
}
sampleStream := &sampleStream{
Metric: it.Metric(),
Values: samplePairs,
}
sampleStreams = append(sampleStreams, sampleStream)
}
return matrix(sampleStreams)
}
func (ev *evaluator) vectorAnd(lhs, rhs vector, matching *VectorMatching) vector {
if matching.Card != CardManyToMany {
panic("set operations must only use many-to-many matching")
}
sigf := signatureFunc(matching.On, matching.MatchingLabels...)
var result vector
// The set of signatures for the right-hand side vector.
rightSigs := map[uint64]struct{}{}
// Add all rhs samples to a map so we can easily find matches later.
for _, rs := range rhs {
rightSigs[sigf(rs.Metric)] = struct{}{}
}
for _, ls := range lhs {
// If there's a matching entry in the right-hand side vector, add the sample.
if _, ok := rightSigs[sigf(ls.Metric)]; ok {
result = append(result, ls)
}
}
return result
}
func (ev *evaluator) vectorOr(lhs, rhs vector, matching *VectorMatching) vector {
if matching.Card != CardManyToMany {
panic("set operations must only use many-to-many matching")
}
sigf := signatureFunc(matching.On, matching.MatchingLabels...)
var result vector
leftSigs := map[uint64]struct{}{}
// Add everything from the left-hand-side vector.
for _, ls := range lhs {
leftSigs[sigf(ls.Metric)] = struct{}{}
result = append(result, ls)
}
// Add all right-hand side elements which have not been added from the left-hand side.
for _, rs := range rhs {
if _, ok := leftSigs[sigf(rs.Metric)]; !ok {
result = append(result, rs)
}
}
return result
}
func (ev *evaluator) vectorUnless(lhs, rhs vector, matching *VectorMatching) vector {
if matching.Card != CardManyToMany {
panic("set operations must only use many-to-many matching")
}
sigf := signatureFunc(matching.On, matching.MatchingLabels...)
rightSigs := map[uint64]struct{}{}
for _, rs := range rhs {
rightSigs[sigf(rs.Metric)] = struct{}{}
}
var result vector
for _, ls := range lhs {
if _, ok := rightSigs[sigf(ls.Metric)]; !ok {
result = append(result, ls)
}
}
return result
}
// vectorBinop evaluates a binary operation between two vectors, excluding set operators.
func (ev *evaluator) vectorBinop(op itemType, lhs, rhs vector, matching *VectorMatching, returnBool bool) vector {
if matching.Card == CardManyToMany {
panic("many-to-many only allowed for set operators")
}
var (
result = vector{}
sigf = signatureFunc(matching.On, matching.MatchingLabels...)
)
// 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 == CardOneToMany {
lhs, rhs = rhs, lhs
}
// All samples from the rhs hashed by the matching label/values.
rightSigs := map[uint64]*sample{}
// Add all rhs samples to a map so we can easily find matches later.
for _, rs := range rhs {
sig := sigf(rs.Metric)
// 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 _, found := rightSigs[sig]; found {
// Many-to-many matching not allowed.
ev.errorf("many-to-many matching not allowed: matching labels must be unique on one side")
}
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.
matchedSigs := map[uint64]map[uint64]struct{}{}
// For all lhs samples find a respective rhs sample and perform
// the binary operation.
for _, ls := range lhs {
sig := sigf(ls.Metric)
rs, found := rightSigs[sig] // Look for a match in the rhs vector.
if !found {
continue
}
// Account for potentially swapped sidedness.
vl, vr := ls.Value, rs.Value
if matching.Card == CardOneToMany {
vl, vr = vr, vl
}
value, keep := vectorElemBinop(op, vl, vr)
if returnBool {
if keep {
value = 1.0
} else {
value = 0.0
}
} else if !keep {
continue
}
metric := resultMetric(ls.Metric, rs.Metric, op, matching)
insertedSigs, exists := matchedSigs[sig]
if matching.Card == 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 := uint64(metric.Metric.Fingerprint())
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{}{}
}
result = append(result, &sample{
Metric: metric,
Value: value,
Timestamp: ev.Timestamp,
})
}
return result
}
// signatureFunc returns a function that calculates the signature for a metric
// ignoring the provided labels. If on, then the given labels are only used instead.
func signatureFunc(on bool, labels ...model.LabelName) func(m metric.Metric) uint64 {
if !on {
return func(m metric.Metric) uint64 {
tmp := m.Metric.Clone()
for _, l := range labels {
delete(tmp, l)
}
delete(tmp, model.MetricNameLabel)
return uint64(tmp.Fingerprint())
}
}
return func(m metric.Metric) uint64 {
return model.SignatureForLabels(m.Metric, labels...)
}
}
// resultMetric returns the metric for the given sample(s) based on the vector
// binary operation and the matching options.
func resultMetric(lhs, rhs metric.Metric, op itemType, matching *VectorMatching) metric.Metric {
if shouldDropMetricName(op) {
lhs.Del(model.MetricNameLabel)
}
if !matching.On {
if matching.Card == CardOneToOne {
for _, l := range matching.MatchingLabels {
lhs.Del(l)
}
}
for _, ln := range matching.Include {
// Included labels from the `group_x` modifier are taken from the "one"-side.
value := rhs.Metric[ln]
if value != "" {
lhs.Set(ln, rhs.Metric[ln])
} else {
lhs.Del(ln)
}
}
return lhs
}
// As we definitely write, creating a new metric is the easiest solution.
m := model.Metric{}
if matching.Card == CardOneToOne {
for _, ln := range matching.MatchingLabels {
if v, ok := lhs.Metric[ln]; ok {
m[ln] = v
}
}
} else {
for k, v := range lhs.Metric {
m[k] = v
}
}
for _, ln := range matching.Include {
// Included labels from the `group_x` modifier are taken from the "one"-side .
if v, ok := rhs.Metric[ln]; ok {
m[ln] = v
} else {
delete(m, ln)
}
}
return metric.Metric{Metric: m, Copied: false}
}
// vectorScalarBinop evaluates a binary operation between a vector and a scalar.
func (ev *evaluator) vectorScalarBinop(op itemType, lhs vector, rhs *model.Scalar, swap, returnBool bool) vector {
vec := make(vector, 0, len(lhs))
for _, lhsSample := range lhs {
lv, rv := lhsSample.Value, rhs.Value
// lhs always contains the vector. If the original position was different
// swap for calculating the value.
if swap {
lv, rv = rv, lv
}
value, keep := vectorElemBinop(op, lv, rv)
if returnBool {
if keep {
value = 1.0
} else {
value = 0.0
}
keep = true
}
if keep {
lhsSample.Value = value
if shouldDropMetricName(op) {
lhsSample.Metric.Del(model.MetricNameLabel)
}
vec = append(vec, lhsSample)
}
}
return vec
}
// scalarBinop evaluates a binary operation between two scalars.
func scalarBinop(op itemType, lhs, rhs model.SampleValue) model.SampleValue {
switch op {
case itemADD:
return lhs + rhs
case itemSUB:
return lhs - rhs
case itemMUL:
return lhs * rhs
case itemDIV:
return lhs / rhs
case itemPOW:
return model.SampleValue(math.Pow(float64(lhs), float64(rhs)))
case itemMOD:
return model.SampleValue(math.Mod(float64(lhs), float64(rhs)))
case itemEQL:
return btos(lhs == rhs)
case itemNEQ:
return btos(lhs != rhs)
case itemGTR:
return btos(lhs > rhs)
case itemLSS:
return btos(lhs < rhs)
case itemGTE:
return btos(lhs >= rhs)
case itemLTE:
return btos(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 itemType, lhs, rhs model.SampleValue) (model.SampleValue, bool) {
switch op {
case itemADD:
return lhs + rhs, true
case itemSUB:
return lhs - rhs, true
case itemMUL:
return lhs * rhs, true
case itemDIV:
return lhs / rhs, true
case itemPOW:
return model.SampleValue(math.Pow(float64(lhs), float64(rhs))), true
case itemMOD:
return model.SampleValue(math.Mod(float64(lhs), float64(rhs))), true
case itemEQL:
return lhs, lhs == rhs
case itemNEQ:
return lhs, lhs != rhs
case itemGTR:
return lhs, lhs > rhs
case itemLSS:
return lhs, lhs < rhs
case itemGTE:
return lhs, lhs >= rhs
case itemLTE:
return lhs, lhs <= rhs
}
panic(fmt.Errorf("operator %q not allowed for operations between vectors", op))
}
// labelIntersection returns the metric of common label/value pairs of two input metrics.
func labelIntersection(metric1, metric2 metric.Metric) metric.Metric {
for label, value := range metric1.Metric {
if metric2.Metric[label] != value {
metric1.Del(label)
}
}
return metric1
}
type groupedAggregation struct {
labels metric.Metric
value model.SampleValue
valuesSquaredSum model.SampleValue
groupCount int
heap vectorByValueHeap
reverseHeap vectorByReverseValueHeap
}
// aggregation evaluates an aggregation operation on a vector.
func (ev *evaluator) aggregation(op itemType, grouping model.LabelNames, without bool, keepCommon bool, param Expr, vec vector) vector {
result := map[uint64]*groupedAggregation{}
var k int64
if op == itemTopK || op == itemBottomK {
k = ev.evalInt(param)
if k < 1 {
return vector{}
}
}
var q float64
if op == itemQuantile {
q = ev.evalFloat(param)
}
var valueLabel model.LabelName
if op == itemCountValues {
valueLabel = model.LabelName(ev.evalString(param).Value)
if !without {
grouping = append(grouping, valueLabel)
}
}
for _, s := range vec {
withoutMetric := s.Metric
if without {
for _, l := range grouping {
withoutMetric.Del(l)
}
withoutMetric.Del(model.MetricNameLabel)
if op == itemCountValues {
withoutMetric.Set(valueLabel, model.LabelValue(s.Value.String()))
}
} else {
if op == itemCountValues {
s.Metric.Set(valueLabel, model.LabelValue(s.Value.String()))
}
}
var groupingKey uint64
if without {
groupingKey = uint64(withoutMetric.Metric.Fingerprint())
} else {
groupingKey = model.SignatureForLabels(s.Metric.Metric, grouping...)
}
groupedResult, ok := result[groupingKey]
// Add a new group if it doesn't exist.
if !ok {
var m metric.Metric
if keepCommon {
m = s.Metric
m.Del(model.MetricNameLabel)
} else if without {
m = withoutMetric
} else {
m = metric.Metric{
Metric: model.Metric{},
Copied: true,
}
for _, l := range grouping {
if v, ok := s.Metric.Metric[l]; ok {
m.Set(l, v)
}
}
}
result[groupingKey] = &groupedAggregation{
labels: m,
value: s.Value,
valuesSquaredSum: s.Value * s.Value,
groupCount: 1,
}
if op == itemTopK || op == itemQuantile {
result[groupingKey].heap = make(vectorByValueHeap, 0, k)
heap.Push(&result[groupingKey].heap, &sample{Value: s.Value, Metric: s.Metric})
} else if op == itemBottomK {
result[groupingKey].reverseHeap = make(vectorByReverseValueHeap, 0, k)
heap.Push(&result[groupingKey].reverseHeap, &sample{Value: s.Value, Metric: s.Metric})
}
continue
}
// Add the sample to the existing group.
if keepCommon {
groupedResult.labels = labelIntersection(groupedResult.labels, s.Metric)
}
switch op {
case itemSum:
groupedResult.value += s.Value
case itemAvg:
groupedResult.value += s.Value
groupedResult.groupCount++
case itemMax:
if groupedResult.value < s.Value || math.IsNaN(float64(groupedResult.value)) {
groupedResult.value = s.Value
}
case itemMin:
if groupedResult.value > s.Value || math.IsNaN(float64(groupedResult.value)) {
groupedResult.value = s.Value
}
case itemCount, itemCountValues:
groupedResult.groupCount++
case itemStdvar, itemStddev:
groupedResult.value += s.Value
groupedResult.valuesSquaredSum += s.Value * s.Value
groupedResult.groupCount++
case itemTopK:
if int64(len(groupedResult.heap)) < k || groupedResult.heap[0].Value < s.Value || math.IsNaN(float64(groupedResult.heap[0].Value)) {
if int64(len(groupedResult.heap)) == k {
heap.Pop(&groupedResult.heap)
}
heap.Push(&groupedResult.heap, &sample{Value: s.Value, Metric: s.Metric})
}
case itemBottomK:
if int64(len(groupedResult.reverseHeap)) < k || groupedResult.reverseHeap[0].Value > s.Value || math.IsNaN(float64(groupedResult.reverseHeap[0].Value)) {
if int64(len(groupedResult.reverseHeap)) == k {
heap.Pop(&groupedResult.reverseHeap)
}
heap.Push(&groupedResult.reverseHeap, &sample{Value: s.Value, Metric: s.Metric})
}
case itemQuantile:
groupedResult.heap = append(groupedResult.heap, s)
default:
panic(fmt.Errorf("expected aggregation operator but got %q", op))
}
}
// Construct the result vector from the aggregated groups.
resultVector := make(vector, 0, len(result))
for _, aggr := range result {
switch op {
case itemAvg:
aggr.value = aggr.value / model.SampleValue(aggr.groupCount)
case itemCount, itemCountValues:
aggr.value = model.SampleValue(aggr.groupCount)
case itemStdvar:
avg := float64(aggr.value) / float64(aggr.groupCount)
aggr.value = model.SampleValue(float64(aggr.valuesSquaredSum)/float64(aggr.groupCount) - avg*avg)
case itemStddev:
avg := float64(aggr.value) / float64(aggr.groupCount)
aggr.value = model.SampleValue(math.Sqrt(float64(aggr.valuesSquaredSum)/float64(aggr.groupCount) - avg*avg))
case itemTopK:
// The heap keeps the lowest value on top, so reverse it.
sort.Sort(sort.Reverse(aggr.heap))
for _, v := range aggr.heap {
resultVector = append(resultVector, &sample{
Metric: v.Metric,
Value: v.Value,
Timestamp: ev.Timestamp,
})
}
continue // Bypass default append.
case itemBottomK:
// The heap keeps the lowest value on top, so reverse it.
sort.Sort(sort.Reverse(aggr.reverseHeap))
for _, v := range aggr.reverseHeap {
resultVector = append(resultVector, &sample{
Metric: v.Metric,
Value: v.Value,
Timestamp: ev.Timestamp,
})
}
continue // Bypass default append.
case itemQuantile:
aggr.value = model.SampleValue(quantile(q, aggr.heap))
default:
// For other aggregations, we already have the right value.
}
sample := &sample{
Metric: aggr.labels,
Value: aggr.value,
Timestamp: ev.Timestamp,
}
resultVector = append(resultVector, sample)
}
return resultVector
}
// btos returns 1 if b is true, 0 otherwise.
func btos(b bool) model.SampleValue {
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 itemType) bool {
switch op {
case itemADD, itemSUB, itemDIV, itemMUL, itemMOD:
return true
default:
return false
}
}
// StalenessDelta determines the time since the last sample after which a time
// series is considered stale.
var StalenessDelta = 5 * time.Minute
// A queryGate controls the maximum number of concurrently running and waiting queries.
type queryGate struct {
ch chan struct{}
}
// newQueryGate returns a query gate that limits the number of queries
// being concurrently executed.
func newQueryGate(length int) *queryGate {
return &queryGate{
ch: make(chan struct{}, length),
}
}
// Start blocks until the gate has a free spot or the context is done.
func (g *queryGate) Start(ctx context.Context) error {
select {
case <-ctx.Done():
return contextDone(ctx, "query queue")
case g.ch <- struct{}{}:
return nil
}
}
// Done releases a single spot in the gate.
func (g *queryGate) Done() {
select {
case <-g.ch:
default:
panic("engine.queryGate.Done: more operations done than started")
}
}
// documentedType returns the internal type to the equivalent
// user facing terminology as defined in the documentation.
func documentedType(t model.ValueType) string {
switch t.String() {
case "vector":
return "instant vector"
case "matrix":
return "range vector"
default:
return t.String()
}
}