mirror of
https://github.com/prometheus/prometheus.git
synced 2025-08-07 22:57:13 +02:00
3d47f94149
After many transformations, it doesn't make sense to keep the metric names, since the result of the transformation is no longer that metric. This drops the metric name after such transformations and makes the web UI deal well with missing metric names. This depends on the current branch on the following things: - prometheus/client_golang needs to be ate237cf15c6in branch "julius/int-fingerprints" (to be merged with new storage) - prometheus/promdash needs to be atdd7691c9c2Change-Id: Ib3c8cad8d647d9854e8c653c424b8c235ccc231d
571 lines
16 KiB
Go
571 lines
16 KiB
Go
// Copyright 2013 Prometheus Team
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package ast
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import (
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"container/heap"
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"fmt"
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"math"
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"sort"
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"time"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/storage/metric"
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)
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// Function represents a function of the expression language and is
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// used by function nodes.
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type Function struct {
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name string
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argTypes []ExprType
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returnType ExprType
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callFn func(timestamp clientmodel.Timestamp, args []Node) interface{}
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}
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// CheckArgTypes returns a non-nil error if the number or types of
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// passed in arg nodes do not match the function's expectations.
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func (function *Function) CheckArgTypes(args []Node) error {
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if len(function.argTypes) != len(args) {
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return fmt.Errorf(
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"wrong number of arguments to function %v(): %v expected, %v given",
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function.name, len(function.argTypes), len(args),
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)
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}
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for idx, argType := range function.argTypes {
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invalidType := false
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var expectedType string
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if _, ok := args[idx].(ScalarNode); argType == SCALAR && !ok {
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invalidType = true
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expectedType = "scalar"
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}
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if _, ok := args[idx].(VectorNode); argType == VECTOR && !ok {
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invalidType = true
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expectedType = "vector"
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}
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if _, ok := args[idx].(MatrixNode); argType == MATRIX && !ok {
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invalidType = true
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expectedType = "matrix"
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}
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if _, ok := args[idx].(StringNode); argType == STRING && !ok {
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invalidType = true
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expectedType = "string"
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}
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if invalidType {
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return fmt.Errorf(
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"wrong type for argument %v in function %v(), expected %v",
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idx, function.name, expectedType,
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)
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}
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}
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return nil
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}
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// === time() clientmodel.SampleValue ===
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func timeImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return clientmodel.SampleValue(timestamp.Unix())
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}
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// === delta(matrix MatrixNode, isCounter ScalarNode) Vector ===
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func deltaImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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matrixNode := args[0].(MatrixNode)
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isCounter := args[1].(ScalarNode).Eval(timestamp) > 0
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resultVector := Vector{}
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// If we treat these metrics as counters, we need to fetch all values
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// in the interval to find breaks in the timeseries' monotonicity.
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// I.e. if a counter resets, we want to ignore that reset.
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var matrixValue Matrix
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if isCounter {
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matrixValue = matrixNode.Eval(timestamp)
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} else {
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matrixValue = matrixNode.EvalBoundaries(timestamp)
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}
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for _, samples := range matrixValue {
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// No sense in trying to compute a delta without at least two points. Drop
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// this vector element.
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if len(samples.Values) < 2 {
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continue
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}
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counterCorrection := clientmodel.SampleValue(0)
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lastValue := clientmodel.SampleValue(0)
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for _, sample := range samples.Values {
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currentValue := sample.Value
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if isCounter && currentValue < lastValue {
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counterCorrection += lastValue - currentValue
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}
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lastValue = currentValue
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}
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resultValue := lastValue - samples.Values[0].Value + counterCorrection
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targetInterval := args[0].(*MatrixSelector).interval
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sampledInterval := samples.Values[len(samples.Values)-1].Timestamp.Sub(samples.Values[0].Timestamp)
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if sampledInterval == 0 {
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// Only found one sample. Cannot compute a rate from this.
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continue
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}
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// Correct for differences in target vs. actual delta interval.
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//
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// Above, we didn't actually calculate the delta for the specified target
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// interval, but for an interval between the first and last found samples
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// under the target interval, which will usually have less time between
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// them. Depending on how many samples are found under a target interval,
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// the delta results are distorted and temporal aliasing occurs (ugly
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// bumps). This effect is corrected for below.
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intervalCorrection := clientmodel.SampleValue(targetInterval) / clientmodel.SampleValue(sampledInterval)
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resultValue *= intervalCorrection
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resultSample := &clientmodel.Sample{
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Metric: samples.Metric,
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Value: resultValue,
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Timestamp: timestamp,
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}
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delete(resultSample.Metric, clientmodel.MetricNameLabel)
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resultVector = append(resultVector, resultSample)
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}
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return resultVector
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}
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// === rate(node MatrixNode) Vector ===
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func rateImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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args = append(args, &ScalarLiteral{value: 1})
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vector := deltaImpl(timestamp, args).(Vector)
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// TODO: could be other type of MatrixNode in the future (right now, only
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// MatrixSelector exists). Find a better way of getting the duration of a
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// matrix, such as looking at the samples themselves.
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interval := args[0].(*MatrixSelector).interval
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for i := range vector {
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vector[i].Value /= clientmodel.SampleValue(interval / time.Second)
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}
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return vector
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}
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type vectorByValueHeap Vector
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func (s vectorByValueHeap) Len() int {
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return len(s)
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}
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func (s vectorByValueHeap) Less(i, j int) bool {
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return s[i].Value < s[j].Value
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}
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func (s vectorByValueHeap) Swap(i, j int) {
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s[i], s[j] = s[j], s[i]
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}
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func (s *vectorByValueHeap) Push(x interface{}) {
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*s = append(*s, x.(*clientmodel.Sample))
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}
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func (s *vectorByValueHeap) Pop() interface{} {
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old := *s
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n := len(old)
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el := old[n-1]
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*s = old[0 : n-1]
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return el
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}
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type reverseHeap struct {
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heap.Interface
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}
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func (s reverseHeap) Less(i, j int) bool {
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return s.Interface.Less(j, i)
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}
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// === sort(node VectorNode) Vector ===
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func sortImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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byValueSorter := vectorByValueHeap(args[0].(VectorNode).Eval(timestamp))
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sort.Sort(byValueSorter)
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return Vector(byValueSorter)
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}
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// === sortDesc(node VectorNode) Vector ===
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func sortDescImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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byValueSorter := vectorByValueHeap(args[0].(VectorNode).Eval(timestamp))
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sort.Sort(sort.Reverse(byValueSorter))
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return Vector(byValueSorter)
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}
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// === topk(k ScalarNode, node VectorNode) Vector ===
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func topkImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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k := int(args[0].(ScalarNode).Eval(timestamp))
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if k < 1 {
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return Vector{}
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}
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topk := make(vectorByValueHeap, 0, k)
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vector := args[1].(VectorNode).Eval(timestamp)
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for _, el := range vector {
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if len(topk) < k || topk[0].Value < el.Value {
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if len(topk) == k {
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heap.Pop(&topk)
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}
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heap.Push(&topk, el)
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}
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}
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sort.Sort(sort.Reverse(topk))
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return Vector(topk)
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}
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// === bottomk(k ScalarNode, node VectorNode) Vector ===
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func bottomkImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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k := int(args[0].(ScalarNode).Eval(timestamp))
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if k < 1 {
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return Vector{}
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}
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bottomk := make(vectorByValueHeap, 0, k)
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bkHeap := reverseHeap{Interface: &bottomk}
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vector := args[1].(VectorNode).Eval(timestamp)
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for _, el := range vector {
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if len(bottomk) < k || bottomk[0].Value > el.Value {
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if len(bottomk) == k {
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heap.Pop(&bkHeap)
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}
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heap.Push(&bkHeap, el)
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}
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}
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sort.Sort(bottomk)
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return Vector(bottomk)
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}
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// === drop_common_labels(node VectorNode) Vector ===
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func dropCommonLabelsImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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vector := args[0].(VectorNode).Eval(timestamp)
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if len(vector) < 1 {
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return Vector{}
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}
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common := clientmodel.LabelSet{}
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for k, v := range vector[0].Metric {
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// TODO(julius): Revisit this when https://github.com/prometheus/prometheus/issues/380
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// is implemented.
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if k == clientmodel.MetricNameLabel {
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continue
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}
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common[k] = v
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}
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for _, el := range vector[1:] {
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for k, v := range common {
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if el.Metric[k] != v {
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// Deletion of map entries while iterating over them is safe.
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// From http://golang.org/ref/spec#For_statements:
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// "If map entries that have not yet been reached are deleted during
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// iteration, the corresponding iteration values will not be produced."
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delete(common, k)
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}
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}
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}
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for _, el := range vector {
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for k := range el.Metric {
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if _, ok := common[k]; ok {
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delete(el.Metric, k)
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}
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}
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}
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return vector
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}
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// === sampleVectorImpl() Vector ===
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func sampleVectorImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return Vector{
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "0",
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},
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Value: 10,
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Timestamp: timestamp,
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},
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "1",
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},
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Value: 20,
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Timestamp: timestamp,
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},
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "2",
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},
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Value: 30,
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Timestamp: timestamp,
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},
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "3",
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"group": "canary",
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},
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Value: 40,
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Timestamp: timestamp,
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},
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "2",
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"group": "canary",
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},
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Value: 40,
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Timestamp: timestamp,
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},
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "3",
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"group": "mytest",
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},
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Value: 40,
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Timestamp: timestamp,
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},
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&clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: "http_requests",
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clientmodel.JobLabel: "api-server",
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"instance": "3",
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"group": "mytest",
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},
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Value: 40,
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Timestamp: timestamp,
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},
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}
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}
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// === scalar(node VectorNode) Scalar ===
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func scalarImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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v := args[0].(VectorNode).Eval(timestamp)
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if len(v) != 1 {
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return clientmodel.SampleValue(math.NaN())
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}
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return clientmodel.SampleValue(v[0].Value)
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}
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// === count_scalar(vector VectorNode) model.SampleValue ===
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func countScalarImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return clientmodel.SampleValue(len(args[0].(VectorNode).Eval(timestamp)))
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}
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func aggrOverTime(timestamp clientmodel.Timestamp, args []Node, aggrFn func(metric.Values) clientmodel.SampleValue) interface{} {
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n := args[0].(MatrixNode)
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matrixVal := n.Eval(timestamp)
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resultVector := Vector{}
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for _, el := range matrixVal {
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if len(el.Values) == 0 {
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continue
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}
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delete(el.Metric, clientmodel.MetricNameLabel)
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resultVector = append(resultVector, &clientmodel.Sample{
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Metric: el.Metric,
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Value: aggrFn(el.Values),
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Timestamp: timestamp,
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})
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}
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return resultVector
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}
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// === avg_over_time(matrix MatrixNode) Vector ===
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func avgOverTimeImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return aggrOverTime(timestamp, args, func(values metric.Values) clientmodel.SampleValue {
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var sum clientmodel.SampleValue
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for _, v := range values {
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sum += v.Value
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}
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return sum / clientmodel.SampleValue(len(values))
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})
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}
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// === count_over_time(matrix MatrixNode) Vector ===
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func countOverTimeImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return aggrOverTime(timestamp, args, func(values metric.Values) clientmodel.SampleValue {
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return clientmodel.SampleValue(len(values))
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})
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}
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// === max_over_time(matrix MatrixNode) Vector ===
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func maxOverTimeImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return aggrOverTime(timestamp, args, func(values metric.Values) clientmodel.SampleValue {
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max := math.Inf(-1)
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for _, v := range values {
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max = math.Max(max, float64(v.Value))
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}
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return clientmodel.SampleValue(max)
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})
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}
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// === min_over_time(matrix MatrixNode) Vector ===
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func minOverTimeImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return aggrOverTime(timestamp, args, func(values metric.Values) clientmodel.SampleValue {
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min := math.Inf(1)
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for _, v := range values {
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min = math.Min(min, float64(v.Value))
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}
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return clientmodel.SampleValue(min)
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})
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}
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// === sum_over_time(matrix MatrixNode) Vector ===
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func sumOverTimeImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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return aggrOverTime(timestamp, args, func(values metric.Values) clientmodel.SampleValue {
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var sum clientmodel.SampleValue
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for _, v := range values {
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sum += v.Value
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}
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return sum
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})
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}
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// === abs(vector VectorNode) Vector ===
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func absImpl(timestamp clientmodel.Timestamp, args []Node) interface{} {
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n := args[0].(VectorNode)
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vector := n.Eval(timestamp)
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for _, el := range vector {
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delete(el.Metric, clientmodel.MetricNameLabel)
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el.Value = clientmodel.SampleValue(math.Abs(float64(el.Value)))
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}
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return vector
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}
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var functions = map[string]*Function{
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"abs": {
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name: "abs",
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argTypes: []ExprType{VECTOR},
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returnType: VECTOR,
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callFn: absImpl,
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},
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"avg_over_time": {
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name: "avg_over_time",
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argTypes: []ExprType{MATRIX},
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returnType: VECTOR,
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callFn: avgOverTimeImpl,
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},
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"bottomk": {
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name: "bottomk",
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argTypes: []ExprType{SCALAR, VECTOR},
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returnType: VECTOR,
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callFn: bottomkImpl,
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},
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"count_over_time": {
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name: "count_over_time",
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argTypes: []ExprType{MATRIX},
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returnType: VECTOR,
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callFn: countOverTimeImpl,
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},
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"count_scalar": {
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name: "count_scalar",
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argTypes: []ExprType{VECTOR},
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returnType: SCALAR,
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callFn: countScalarImpl,
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},
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"delta": {
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name: "delta",
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argTypes: []ExprType{MATRIX, SCALAR},
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returnType: VECTOR,
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callFn: deltaImpl,
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},
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"drop_common_labels": {
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name: "drop_common_labels",
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argTypes: []ExprType{VECTOR},
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returnType: VECTOR,
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callFn: dropCommonLabelsImpl,
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},
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"max_over_time": {
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name: "max_over_time",
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argTypes: []ExprType{MATRIX},
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returnType: VECTOR,
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callFn: maxOverTimeImpl,
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},
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"min_over_time": {
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name: "min_over_time",
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argTypes: []ExprType{MATRIX},
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returnType: VECTOR,
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callFn: minOverTimeImpl,
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},
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"rate": {
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name: "rate",
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argTypes: []ExprType{MATRIX},
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returnType: VECTOR,
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callFn: rateImpl,
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},
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"sampleVector": {
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name: "sampleVector",
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argTypes: []ExprType{},
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returnType: VECTOR,
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callFn: sampleVectorImpl,
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},
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"scalar": {
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name: "scalar",
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argTypes: []ExprType{VECTOR},
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returnType: SCALAR,
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callFn: scalarImpl,
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|
},
|
|
"sort": {
|
|
name: "sort",
|
|
argTypes: []ExprType{VECTOR},
|
|
returnType: VECTOR,
|
|
callFn: sortImpl,
|
|
},
|
|
"sort_desc": {
|
|
name: "sort_desc",
|
|
argTypes: []ExprType{VECTOR},
|
|
returnType: VECTOR,
|
|
callFn: sortDescImpl,
|
|
},
|
|
"sum_over_time": {
|
|
name: "sum_over_time",
|
|
argTypes: []ExprType{MATRIX},
|
|
returnType: VECTOR,
|
|
callFn: sumOverTimeImpl,
|
|
},
|
|
"time": {
|
|
name: "time",
|
|
argTypes: []ExprType{},
|
|
returnType: SCALAR,
|
|
callFn: timeImpl,
|
|
},
|
|
"topk": {
|
|
name: "topk",
|
|
argTypes: []ExprType{SCALAR, VECTOR},
|
|
returnType: VECTOR,
|
|
callFn: topkImpl,
|
|
},
|
|
}
|
|
|
|
// GetFunction returns a predefined Function object for the given
|
|
// name.
|
|
func GetFunction(name string) (*Function, error) {
|
|
function, ok := functions[name]
|
|
if !ok {
|
|
return nil, fmt.Errorf("couldn't find function %v()", name)
|
|
}
|
|
return function, nil
|
|
}
|