prometheus/rules/ast/functions.go
Bjoern Rabenstein fd63500ed3 Make rules/ast golint clean.
Mostly, that means adding compliant doc strings to exported items.

Also, remove 'go vet' warnings where possible. (Some are unfortunately
not to avoid, arguably bugs in 'go vet'.)

Change-Id: I2827b6dd317492864c1383c3de1ea9eac5a219bb
2014-02-14 15:01:39 +01:00

338 lines
9.9 KiB
Go

// Copyright 2013 Prometheus Team
// 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 ast
import (
"fmt"
"math"
"sort"
"time"
clientmodel "github.com/prometheus/client_golang/model"
"github.com/prometheus/prometheus/utility"
)
// Function represents a function of the expression language and is
// used by function nodes.
type Function struct {
name string
argTypes []ExprType
returnType ExprType
callFn func(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{}
}
// CheckArgTypes returns a non-nil error if the number or types of
// passed in arg nodes do not match the function's expectations.
func (function *Function) CheckArgTypes(args []Node) error {
if len(function.argTypes) != len(args) {
return fmt.Errorf(
"wrong number of arguments to function %v(): %v expected, %v given",
function.name, len(function.argTypes), len(args),
)
}
for idx, argType := range function.argTypes {
invalidType := false
var expectedType string
if _, ok := args[idx].(ScalarNode); argType == SCALAR && !ok {
invalidType = true
expectedType = "scalar"
}
if _, ok := args[idx].(VectorNode); argType == VECTOR && !ok {
invalidType = true
expectedType = "vector"
}
if _, ok := args[idx].(MatrixNode); argType == MATRIX && !ok {
invalidType = true
expectedType = "matrix"
}
if _, ok := args[idx].(StringNode); argType == STRING && !ok {
invalidType = true
expectedType = "string"
}
if invalidType {
return fmt.Errorf(
"wrong type for argument %v in function %v(), expected %v",
idx, function.name, expectedType,
)
}
}
return nil
}
// === time() clientmodel.SampleValue ===
func timeImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
return clientmodel.SampleValue(time.Now().Unix())
}
// === delta(matrix MatrixNode, isCounter ScalarNode) Vector ===
func deltaImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
matrixNode := args[0].(MatrixNode)
isCounter := args[1].(ScalarNode).Eval(timestamp, view) > 0
resultVector := Vector{}
// If we treat these metrics as counters, we need to fetch all values
// in the interval to find breaks in the timeseries' monotonicity.
// I.e. if a counter resets, we want to ignore that reset.
var matrixValue Matrix
if isCounter {
matrixValue = matrixNode.Eval(timestamp, view)
} else {
matrixValue = matrixNode.EvalBoundaries(timestamp, view)
}
for _, samples := range matrixValue {
// No sense in trying to compute a delta without at least two points. Drop
// this vector element.
if len(samples.Values) < 2 {
continue
}
counterCorrection := clientmodel.SampleValue(0)
lastValue := clientmodel.SampleValue(0)
for _, sample := range samples.Values {
currentValue := sample.Value
if isCounter && currentValue < lastValue {
counterCorrection += lastValue - currentValue
}
lastValue = currentValue
}
resultValue := lastValue - samples.Values[0].Value + counterCorrection
targetInterval := args[0].(*MatrixLiteral).interval
sampledInterval := samples.Values[len(samples.Values)-1].Timestamp.Sub(samples.Values[0].Timestamp)
if sampledInterval == 0 {
// Only found one sample. Cannot compute a rate from this.
continue
}
// Correct for differences in target vs. actual delta interval.
//
// Above, we didn't actually calculate the delta for the specified target
// interval, but for an interval between the first and last found samples
// under the target interval, which will usually have less time between
// them. Depending on how many samples are found under a target interval,
// the delta results are distorted and temporal aliasing occurs (ugly
// bumps). This effect is corrected for below.
intervalCorrection := clientmodel.SampleValue(targetInterval) / clientmodel.SampleValue(sampledInterval)
resultValue *= intervalCorrection
resultSample := &clientmodel.Sample{
Metric: samples.Metric,
Value: resultValue,
Timestamp: timestamp,
}
resultVector = append(resultVector, resultSample)
}
return resultVector
}
// === rate(node *MatrixNode) Vector ===
func rateImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
args = append(args, &ScalarLiteral{value: 1})
vector := deltaImpl(timestamp, view, args).(Vector)
// TODO: could be other type of MatrixNode in the future (right now, only
// MatrixLiteral exists). Find a better way of getting the duration of a
// matrix, such as looking at the samples themselves.
interval := args[0].(*MatrixLiteral).interval
for i := range vector {
vector[i].Value /= clientmodel.SampleValue(interval / time.Second)
}
return vector
}
type vectorByValueSorter struct {
vector Vector
}
func (sorter vectorByValueSorter) Len() int {
return len(sorter.vector)
}
func (sorter vectorByValueSorter) Less(i, j int) bool {
return sorter.vector[i].Value < sorter.vector[j].Value
}
func (sorter vectorByValueSorter) Swap(i, j int) {
sorter.vector[i], sorter.vector[j] = sorter.vector[j], sorter.vector[i]
}
// === sort(node *VectorNode) Vector ===
func sortImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
byValueSorter := vectorByValueSorter{
vector: args[0].(VectorNode).Eval(timestamp, view),
}
sort.Sort(byValueSorter)
return byValueSorter.vector
}
// === sortDesc(node *VectorNode) Vector ===
func sortDescImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
descByValueSorter := utility.ReverseSorter{
Interface: vectorByValueSorter{
vector: args[0].(VectorNode).Eval(timestamp, view),
},
}
sort.Sort(descByValueSorter)
return descByValueSorter.Interface.(vectorByValueSorter).vector
}
// === sampleVectorImpl() Vector ===
func sampleVectorImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
return Vector{
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "0",
},
Value: 10,
Timestamp: timestamp,
},
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "1",
},
Value: 20,
Timestamp: timestamp,
},
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "2",
},
Value: 30,
Timestamp: timestamp,
},
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "3",
"group": "canary",
},
Value: 40,
Timestamp: timestamp,
},
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "2",
"group": "canary",
},
Value: 40,
Timestamp: timestamp,
},
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "3",
"group": "mytest",
},
Value: 40,
Timestamp: timestamp,
},
&clientmodel.Sample{
Metric: clientmodel.Metric{
clientmodel.MetricNameLabel: "http_requests",
clientmodel.JobLabel: "api-server",
"instance": "3",
"group": "mytest",
},
Value: 40,
Timestamp: timestamp,
},
}
}
// === scalar(node *VectorNode) Scalar ===
func scalarImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
v := args[0].(VectorNode).Eval(timestamp, view)
if len(v) != 1 {
return clientmodel.SampleValue(math.NaN())
}
return clientmodel.SampleValue(v[0].Value)
}
// === count_scalar(vector VectorNode) model.SampleValue ===
func countScalarImpl(timestamp clientmodel.Timestamp, view *viewAdapter, args []Node) interface{} {
return clientmodel.SampleValue(len(args[0].(VectorNode).Eval(timestamp, view)))
}
var functions = map[string]*Function{
"count_scalar": {
name: "count_scalar",
argTypes: []ExprType{VECTOR},
returnType: SCALAR,
callFn: countScalarImpl,
},
"delta": {
name: "delta",
argTypes: []ExprType{MATRIX, SCALAR},
returnType: VECTOR,
callFn: deltaImpl,
},
"rate": {
name: "rate",
argTypes: []ExprType{MATRIX},
returnType: VECTOR,
callFn: rateImpl,
},
"sampleVector": {
name: "sampleVector",
argTypes: []ExprType{},
returnType: VECTOR,
callFn: sampleVectorImpl,
},
"scalar": {
name: "scalar",
argTypes: []ExprType{VECTOR},
returnType: SCALAR,
callFn: scalarImpl,
},
"sort": {
name: "sort",
argTypes: []ExprType{VECTOR},
returnType: VECTOR,
callFn: sortImpl,
},
"sort_desc": {
name: "sort_desc",
argTypes: []ExprType{VECTOR},
returnType: VECTOR,
callFn: sortDescImpl,
},
"time": {
name: "time",
argTypes: []ExprType{},
returnType: SCALAR,
callFn: timeImpl,
},
}
// 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
}