/usr/share/gocode/src/github.com/influxdb/influxdb/tsdb/functions.go is in golang-github-influxdb-influxdb-dev 0.10.0+dfsg1-1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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// All aggregate and query functions are defined in this file along with any intermediate data objects they need to process.
// Query functions are represented as two discreet functions: Map and Reduce. These roughly follow the MapReduce
// paradigm popularized by Google and Hadoop.
//
// When adding an aggregate function, define a mapper, a reducer, and add them in the switch statement in the MapreduceFuncs function
import (
"container/heap"
"encoding/json"
"fmt"
"math"
"math/rand"
"reflect"
"sort"
// "github.com/davecgh/go-spew/spew"
"github.com/influxdb/influxdb/influxql"
)
// MapInput represents a collection of values to be processed by the mapper.
type MapInput struct {
TMin int64
Items []MapItem
}
// MapItem represents a single item in a collection that's processed by the mapper.
type MapItem struct {
Timestamp int64
Value interface{}
// TODO(benbjohnson):
// Move fields and tags up to MapInput. Currently the engine combines
// multiple series together during processing. This needs to be fixed so
// that each map function only operates on a single series at a time instead.
Fields map[string]interface{}
Tags map[string]string
}
type MapItems []MapItem
func (a MapItems) Len() int { return len(a) }
func (a MapItems) Less(i, j int) bool { return a[i].Timestamp < a[j].Timestamp }
func (a MapItems) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
// mapFunc represents a function used for mapping over a sequential series of data.
// The iterator represents a single group by interval
type mapFunc func(*MapInput) interface{}
// reduceFunc represents a function used for reducing mapper output.
type reduceFunc func([]interface{}) interface{}
// UnmarshalFunc represents a function that can take bytes from a mapper from remote
// server and marshal it into an interface the reducer can use
type UnmarshalFunc func([]byte) (interface{}, error)
// initializemapFunc takes an aggregate call from the query and returns the mapFunc
func initializeMapFunc(c *influxql.Call) (mapFunc, error) {
// see if it's a query for raw data
if c == nil {
return MapRawQuery, nil
}
// Retrieve map function by name.
switch c.Name {
case "count":
if _, ok := c.Args[0].(*influxql.Distinct); ok {
return MapCountDistinct, nil
}
if c, ok := c.Args[0].(*influxql.Call); ok {
if c.Name == "distinct" {
return MapCountDistinct, nil
}
}
return MapCount, nil
case "distinct":
return MapDistinct, nil
case "sum":
return MapSum, nil
case "mean":
return MapMean, nil
case "median":
return MapStddev, nil
case "min":
return func(input *MapInput) interface{} {
return MapMin(input, c.Fields()[0])
}, nil
case "max":
return func(input *MapInput) interface{} {
return MapMax(input, c.Fields()[0])
}, nil
case "spread":
return MapSpread, nil
case "stddev":
return MapStddev, nil
case "first":
return func(input *MapInput) interface{} {
return MapFirst(input, c.Fields()[0])
}, nil
case "last":
return func(input *MapInput) interface{} {
return MapLast(input, c.Fields()[0])
}, nil
case "top", "bottom":
// Capture information from the call that the Map function will require
lit, _ := c.Args[len(c.Args)-1].(*influxql.NumberLiteral)
limit := int(lit.Val)
fields := topCallArgs(c)
return func(input *MapInput) interface{} {
return MapTopBottom(input, limit, fields, len(c.Args), c.Name)
}, nil
case "percentile":
return MapEcho, nil
case "derivative", "non_negative_derivative":
// If the arg is another aggregate e.g. derivative(mean(value)), then
// use the map func for that nested aggregate
if fn, ok := c.Args[0].(*influxql.Call); ok {
return initializeMapFunc(fn)
}
return MapRawQuery, nil
default:
return nil, fmt.Errorf("function not found: %q", c.Name)
}
}
// InitializereduceFunc takes an aggregate call from the query and returns the reduceFunc
func initializeReduceFunc(c *influxql.Call) (reduceFunc, error) {
// Retrieve reduce function by name.
switch c.Name {
case "count":
if _, ok := c.Args[0].(*influxql.Distinct); ok {
return ReduceCountDistinct, nil
}
if c, ok := c.Args[0].(*influxql.Call); ok {
if c.Name == "distinct" {
return ReduceCountDistinct, nil
}
}
return ReduceSum, nil
case "distinct":
return ReduceDistinct, nil
case "sum":
return ReduceSum, nil
case "mean":
return ReduceMean, nil
case "median":
return ReduceMedian, nil
case "min":
return ReduceMin, nil
case "max":
return ReduceMax, nil
case "spread":
return ReduceSpread, nil
case "stddev":
return ReduceStddev, nil
case "first":
return ReduceFirst, nil
case "last":
return ReduceLast, nil
case "top", "bottom":
return func(values []interface{}) interface{} {
lit, _ := c.Args[len(c.Args)-1].(*influxql.NumberLiteral)
limit := int(lit.Val)
fields := topCallArgs(c)
return ReduceTopBottom(values, limit, fields, c.Name)
}, nil
case "percentile":
return func(values []interface{}) interface{} {
// Checks that this arg exists and is a valid type are done in the parsing validation
// and have test coverage there
lit, _ := c.Args[1].(*influxql.NumberLiteral)
percentile := lit.Val
return ReducePercentile(values, percentile)
}, nil
case "derivative", "non_negative_derivative":
// If the arg is another aggregate e.g. derivative(mean(value)), then
// use the map func for that nested aggregate
if fn, ok := c.Args[0].(*influxql.Call); ok {
return initializeReduceFunc(fn)
}
return nil, fmt.Errorf("expected function argument to %s", c.Name)
default:
return nil, fmt.Errorf("function not found: %q", c.Name)
}
}
func InitializeUnmarshaller(c *influxql.Call) (UnmarshalFunc, error) {
// if c is nil it's a raw data query
if c == nil {
return func(b []byte) (interface{}, error) {
a := make([]*rawQueryMapOutput, 0)
err := json.Unmarshal(b, &a)
return a, err
}, nil
}
// Retrieve marshal function by name
switch c.Name {
case "mean":
return func(b []byte) (interface{}, error) {
var o meanMapOutput
err := json.Unmarshal(b, &o)
return &o, err
}, nil
case "min", "max":
return func(b []byte) (interface{}, error) {
if string(b) == "null" {
return nil, nil
}
var o minMaxMapOut
err := json.Unmarshal(b, &o)
return &o, err
}, nil
case "top", "bottom":
return func(b []byte) (interface{}, error) {
var o PositionPoints
err := json.Unmarshal(b, &o)
return o, err
}, nil
case "spread":
return func(b []byte) (interface{}, error) {
var o spreadMapOutput
err := json.Unmarshal(b, &o)
return &o, err
}, nil
case "distinct":
return func(b []byte) (interface{}, error) {
var val InterfaceValues
err := json.Unmarshal(b, &val)
return val, err
}, nil
case "first":
return func(b []byte) (interface{}, error) {
var o firstLastMapOutput
err := json.Unmarshal(b, &o)
return &o, err
}, nil
case "last":
return func(b []byte) (interface{}, error) {
var o firstLastMapOutput
err := json.Unmarshal(b, &o)
return &o, err
}, nil
case "stddev":
return func(b []byte) (interface{}, error) {
val := make([]float64, 0)
err := json.Unmarshal(b, &val)
return val, err
}, nil
case "median":
return func(b []byte) (interface{}, error) {
a := make([]float64, 0)
err := json.Unmarshal(b, &a)
return a, err
}, nil
default:
return func(b []byte) (interface{}, error) {
var val interface{}
err := json.Unmarshal(b, &val)
return val, err
}, nil
}
}
// MapCount computes the number of values in an iterator.
func MapCount(input *MapInput) interface{} {
n := float64(0)
for range input.Items {
n++
}
return n
}
type InterfaceValues []interface{}
func (d InterfaceValues) Len() int { return len(d) }
func (d InterfaceValues) Swap(i, j int) { d[i], d[j] = d[j], d[i] }
func (d InterfaceValues) Less(i, j int) bool {
cmpt, a, b := typeCompare(d[i], d[j])
cmpv := valueCompare(a, b)
if cmpv == 0 {
return cmpt < 0
}
return cmpv < 0
}
// MapDistinct computes the unique values in an iterator.
func MapDistinct(input *MapInput) interface{} {
m := make(map[interface{}]struct{})
for _, item := range input.Items {
m[item.Value] = struct{}{}
}
if len(m) == 0 {
return nil
}
results := make(InterfaceValues, len(m))
var i int
for value, _ := range m {
results[i] = value
i++
}
return results
}
// ReduceDistinct finds the unique values for each key.
func ReduceDistinct(values []interface{}) interface{} {
var index = make(map[interface{}]struct{})
// index distinct values from each mapper
for _, v := range values {
if v == nil {
continue
}
d, ok := v.(InterfaceValues)
if !ok {
msg := fmt.Sprintf("expected distinctValues, got: %T", v)
panic(msg)
}
for _, distinctValue := range d {
index[distinctValue] = struct{}{}
}
}
// convert map keys to an array
results := make(InterfaceValues, len(index))
var i int
for k, _ := range index {
results[i] = k
i++
}
if len(results) > 0 {
sort.Sort(results)
return results
}
return nil
}
// MapCountDistinct computes the unique count of values in an iterator.
func MapCountDistinct(input *MapInput) interface{} {
var index = make(map[interface{}]struct{})
for _, item := range input.Items {
index[item.Value] = struct{}{}
}
if len(index) == 0 {
return nil
}
return index
}
// ReduceCountDistinct finds the unique counts of values.
func ReduceCountDistinct(values []interface{}) interface{} {
var index = make(map[interface{}]struct{})
// index distinct values from each mapper
for _, v := range values {
if v == nil {
continue
}
d, ok := v.(map[interface{}]struct{})
if !ok {
msg := fmt.Sprintf("expected map[interface{}]struct{}, got: %T", v)
panic(msg)
}
for distinctCountValue, _ := range d {
index[distinctCountValue] = struct{}{}
}
}
return len(index)
}
type NumberType int8
const (
Float64Type NumberType = iota
Int64Type
)
// MapSum computes the summation of values in an iterator.
func MapSum(input *MapInput) interface{} {
if len(input.Items) == 0 {
return nil
}
n := float64(0)
var resultType NumberType
for _, item := range input.Items {
switch v := item.Value.(type) {
case float64:
n += v
case int64:
n += float64(v)
resultType = Int64Type
}
}
switch resultType {
case Float64Type:
return n
case Int64Type:
return int64(n)
default:
return nil
}
}
// ReduceSum computes the sum of values for each key.
func ReduceSum(values []interface{}) interface{} {
var n float64
count := 0
var resultType NumberType
for _, v := range values {
if v == nil {
continue
}
count++
switch n1 := v.(type) {
case float64:
n += n1
case int64:
n += float64(n1)
resultType = Int64Type
}
}
if count > 0 {
switch resultType {
case Float64Type:
return n
case Int64Type:
return int64(n)
}
}
return nil
}
// MapMean computes the count and sum of values in an iterator to be combined by the reducer.
func MapMean(input *MapInput) interface{} {
if len(input.Items) == 0 {
return nil
}
out := &meanMapOutput{}
for _, item := range input.Items {
out.Count++
switch v := item.Value.(type) {
case float64:
out.Total += v
case int64:
out.Total += float64(v)
out.ResultType = Int64Type
}
}
return out
}
type meanMapOutput struct {
Count int
Total float64
ResultType NumberType
}
// ReduceMean computes the mean of values for each key.
func ReduceMean(values []interface{}) interface{} {
var total float64
var count int
for _, v := range values {
if v, _ := v.(*meanMapOutput); v != nil {
count += v.Count
total += v.Total
}
}
if count == 0 {
return nil
}
return total / float64(count)
}
// ReduceMedian computes the median of values
func ReduceMedian(values []interface{}) interface{} {
var data []float64
// Collect all the data points
for _, value := range values {
if value == nil {
continue
}
data = append(data, value.([]float64)...)
}
length := len(data)
if length < 2 {
if length == 0 {
return nil
}
return data[0]
}
middle := length / 2
var sortedRange []float64
if length%2 == 0 {
sortedRange = getSortedRange(data, middle-1, 2)
var low, high = sortedRange[0], sortedRange[1]
return low + (high-low)/2
}
sortedRange = getSortedRange(data, middle, 1)
return sortedRange[0]
}
// getSortedRange returns a sorted subset of data. By using discardLowerRange and discardUpperRange to get the target
// subset (unsorted) and then just sorting that subset, the work can be reduced from O(N lg N), where N is len(data), to
// O(N + count lg count) for the average case
// - O(N) to discard the unwanted items
// - O(count lg count) to sort the count number of extracted items
// This can be useful for:
// - finding the median: getSortedRange(data, middle, 1)
// - finding the top N: getSortedRange(data, len(data) - N, N)
// - finding the bottom N: getSortedRange(data, 0, N)
func getSortedRange(data []float64, start int, count int) []float64 {
out := discardLowerRange(data, start)
k := len(out) - count
if k > 0 {
out = discardUpperRange(out, k)
}
sort.Float64s(out)
return out
}
// discardLowerRange discards the lower k elements of the sorted data set without sorting all the data. Sorting all of
// the data would take O(NlgN), where N is len(data), but partitioning to find the kth largest number is O(N) in the
// average case. The remaining N-k unsorted elements are returned - no kind of ordering is guaranteed on these elements.
func discardLowerRange(data []float64, k int) []float64 {
out := make([]float64, len(data)-k)
i := 0
// discard values lower than the desired range
for k > 0 {
lows, pivotValue, highs := partition(data)
lowLength := len(lows)
if lowLength > k {
// keep all the highs and the pivot
out[i] = pivotValue
i++
copy(out[i:], highs)
i += len(highs)
// iterate over the lows again
data = lows
} else {
// discard all the lows
data = highs
k -= lowLength
if k == 0 {
// if discarded enough lows, keep the pivot
out[i] = pivotValue
i++
} else {
// able to discard the pivot too
k--
}
}
}
copy(out[i:], data)
return out
}
// discardUpperRange discards the upper k elements of the sorted data set without sorting all the data. Sorting all of
// the data would take O(NlgN), where N is len(data), but partitioning to find the kth largest number is O(N) in the
// average case. The remaining N-k unsorted elements are returned - no kind of ordering is guaranteed on these elements.
func discardUpperRange(data []float64, k int) []float64 {
out := make([]float64, len(data)-k)
i := 0
// discard values higher than the desired range
for k > 0 {
lows, pivotValue, highs := partition(data)
highLength := len(highs)
if highLength > k {
// keep all the lows and the pivot
out[i] = pivotValue
i++
copy(out[i:], lows)
i += len(lows)
// iterate over the highs again
data = highs
} else {
// discard all the highs
data = lows
k -= highLength
if k == 0 {
// if discarded enough highs, keep the pivot
out[i] = pivotValue
i++
} else {
// able to discard the pivot too
k--
}
}
}
copy(out[i:], data)
return out
}
// partition takes a list of data, chooses a random pivot index and returns a list of elements lower than the
// pivotValue, the pivotValue, and a list of elements higher than the pivotValue. partition mutates data.
func partition(data []float64) (lows []float64, pivotValue float64, highs []float64) {
length := len(data)
// there are better (more complex) ways to calculate pivotIndex (e.g. median of 3, median of 3 medians) if this
// proves to be inadequate.
pivotIndex := rand.Int() % length
pivotValue = data[pivotIndex]
low, high := 1, length-1
// put the pivot in the first position
data[pivotIndex], data[0] = data[0], data[pivotIndex]
// partition the data around the pivot
for low <= high {
for low <= high && data[low] <= pivotValue {
low++
}
for high >= low && data[high] >= pivotValue {
high--
}
if low < high {
data[low], data[high] = data[high], data[low]
}
}
return data[1:low], pivotValue, data[high+1:]
}
type minMaxMapOut struct {
Time int64
Val float64
Type NumberType
Fields map[string]interface{}
Tags map[string]string
}
// MapMin collects the values to pass to the reducer
func MapMin(input *MapInput, fieldName string) interface{} {
min := &minMaxMapOut{}
pointsYielded := false
var val float64
for _, item := range input.Items {
switch v := item.Value.(type) {
case float64:
val = v
case int64:
val = float64(v)
min.Type = Int64Type
case map[string]interface{}:
if d, t, ok := decodeValueAndNumberType(v[fieldName]); ok {
val, min.Type = d, t
} else {
continue
}
}
// Initialize min
if !pointsYielded {
min.Time = item.Timestamp
min.Val = val
min.Fields = item.Fields
min.Tags = item.Tags
pointsYielded = true
}
current := min.Val
min.Val = math.Min(min.Val, val)
// Check to see if the value changed, if so, update the fields/tags
if current != min.Val {
min.Time = item.Timestamp
min.Fields = item.Fields
min.Tags = item.Tags
}
}
if pointsYielded {
return min
}
return nil
}
// ReduceMin computes the min of value.
func ReduceMin(values []interface{}) interface{} {
var curr *minMaxMapOut
for _, value := range values {
v, _ := value.(*minMaxMapOut)
if v == nil {
continue
}
// Replace current if lower value.
if curr == nil || v.Val < curr.Val || (v.Val == curr.Val && v.Time < curr.Time) {
curr = v
}
}
if curr == nil {
return nil
}
switch curr.Type {
case Float64Type:
return PositionPoint{
Time: curr.Time,
Value: curr.Val,
Fields: curr.Fields,
Tags: curr.Tags,
}
case Int64Type:
return PositionPoint{
Time: curr.Time,
Value: int64(curr.Val),
Fields: curr.Fields,
Tags: curr.Tags,
}
default:
return nil
}
}
func decodeValueAndNumberType(v interface{}) (float64, NumberType, bool) {
switch n := v.(type) {
case float64:
return n, Float64Type, true
case int64:
return float64(n), Int64Type, true
default:
return 0, Float64Type, false
}
}
// MapMax collects the values to pass to the reducer
func MapMax(input *MapInput, fieldName string) interface{} {
max := &minMaxMapOut{}
pointsYielded := false
var val float64
for _, item := range input.Items {
switch v := item.Value.(type) {
case float64:
val = v
case int64:
val = float64(v)
max.Type = Int64Type
case map[string]interface{}:
if d, t, ok := decodeValueAndNumberType(v[fieldName]); ok {
val, max.Type = d, t
} else {
continue
}
}
// Initialize max
if !pointsYielded {
max.Time = item.Timestamp
max.Val = val
max.Fields = item.Fields
max.Tags = item.Tags
pointsYielded = true
}
current := max.Val
max.Val = math.Max(max.Val, val)
// Check to see if the value changed, if so, update the fields/tags
if current != max.Val {
max.Time = item.Timestamp
max.Fields = item.Fields
max.Tags = item.Tags
}
}
if pointsYielded {
return max
}
return nil
}
// ReduceMax computes the max of value.
func ReduceMax(values []interface{}) interface{} {
var curr *minMaxMapOut
for _, value := range values {
v, _ := value.(*minMaxMapOut)
if v == nil {
continue
}
// Replace current if higher value.
if curr == nil || v.Val > curr.Val || (v.Val == curr.Val && v.Time < curr.Time) {
curr = v
}
}
if curr == nil {
return nil
}
switch curr.Type {
case Float64Type:
return PositionPoint{
Time: curr.Time,
Value: curr.Val,
Fields: curr.Fields,
Tags: curr.Tags,
}
case Int64Type:
return PositionPoint{
Time: curr.Time,
Value: int64(curr.Val),
Fields: curr.Fields,
Tags: curr.Tags,
}
default:
return nil
}
}
type spreadMapOutput struct {
Min, Max float64
Type NumberType
}
// MapSpread collects the values to pass to the reducer
func MapSpread(input *MapInput) interface{} {
out := &spreadMapOutput{}
pointsYielded := false
var val float64
for _, item := range input.Items {
switch v := item.Value.(type) {
case float64:
val = v
case int64:
val = float64(v)
out.Type = Int64Type
}
// Initialize
if !pointsYielded {
out.Max = val
out.Min = val
pointsYielded = true
}
out.Max = math.Max(out.Max, val)
out.Min = math.Min(out.Min, val)
}
if pointsYielded {
return out
}
return nil
}
// ReduceSpread computes the spread of values.
func ReduceSpread(values []interface{}) interface{} {
result := &spreadMapOutput{}
pointsYielded := false
for _, v := range values {
if v == nil {
continue
}
val := v.(*spreadMapOutput)
// Initialize
if !pointsYielded {
result.Max = val.Max
result.Min = val.Min
result.Type = val.Type
pointsYielded = true
}
result.Max = math.Max(result.Max, val.Max)
result.Min = math.Min(result.Min, val.Min)
}
if pointsYielded {
switch result.Type {
case Float64Type:
return result.Max - result.Min
case Int64Type:
return int64(result.Max - result.Min)
}
}
return nil
}
// MapStddev collects the values to pass to the reducer
func MapStddev(input *MapInput) interface{} {
var a []float64
for _, item := range input.Items {
switch v := item.Value.(type) {
case float64:
a = append(a, v)
case int64:
a = append(a, float64(v))
}
}
return a
}
// ReduceStddev computes the stddev of values.
func ReduceStddev(values []interface{}) interface{} {
var data []float64
// Collect all the data points
for _, value := range values {
if value == nil {
continue
}
data = append(data, value.([]float64)...)
}
// If no data or we only have one point, it's nil or undefined
if len(data) < 2 {
return nil
}
// Get the mean
var mean float64
var count int
for _, v := range data {
count++
mean += (v - mean) / float64(count)
}
// Get the variance
var variance float64
for _, v := range data {
dif := v - mean
sq := math.Pow(dif, 2)
variance += sq
}
variance = variance / float64(count-1)
stddev := math.Sqrt(variance)
return stddev
}
type firstLastMapOutput struct {
Time int64
Value interface{}
Fields map[string]interface{}
Tags map[string]string
}
// MapFirst collects the values to pass to the reducer
// This function assumes time ordered input
func MapFirst(input *MapInput, fieldName string) interface{} {
if len(input.Items) == 0 {
return nil
}
k, v := input.Items[0].Timestamp, input.Items[0].Value
tags := input.Items[0].Tags
fields := input.Items[0].Fields
if n, ok := v.(map[string]interface{}); ok {
v = n[fieldName]
}
// Find greatest value at same timestamp.
for _, item := range input.Items[1:] {
nextk, nextv := item.Timestamp, item.Value
if nextk != k {
break
}
if n, ok := nextv.(map[string]interface{}); ok {
nextv = n[fieldName]
}
if greaterThan(nextv, v) {
fields = item.Fields
tags = item.Tags
v = nextv
}
}
return &firstLastMapOutput{Time: k, Value: v, Fields: fields, Tags: tags}
}
// ReduceFirst computes the first of value.
func ReduceFirst(values []interface{}) interface{} {
out := &firstLastMapOutput{}
pointsYielded := false
for _, v := range values {
if v == nil {
continue
}
val := v.(*firstLastMapOutput)
// Initialize first
if !pointsYielded {
out.Time = val.Time
out.Value = val.Value
out.Fields = val.Fields
out.Tags = val.Tags
pointsYielded = true
}
if val.Time < out.Time {
out.Time = val.Time
out.Value = val.Value
out.Fields = val.Fields
out.Tags = val.Tags
} else if val.Time == out.Time && greaterThan(val.Value, out.Value) {
out.Value = val.Value
out.Fields = val.Fields
out.Tags = val.Tags
}
}
if pointsYielded {
return PositionPoint{
Time: out.Time,
Value: out.Value,
Fields: out.Fields,
Tags: out.Tags,
}
}
return nil
}
// MapLast collects the values to pass to the reducer
func MapLast(input *MapInput, fieldName string) interface{} {
out := &firstLastMapOutput{}
pointsYielded := false
for _, item := range input.Items {
k, v := item.Timestamp, item.Value
if m, ok := v.(map[string]interface{}); ok {
v = m[fieldName]
}
// Initialize last
if !pointsYielded {
out.Time = k
out.Value = v
out.Fields = item.Fields
out.Tags = item.Tags
pointsYielded = true
}
if k > out.Time {
out.Time = k
out.Value = v
out.Fields = item.Fields
out.Tags = item.Tags
} else if k == out.Time && greaterThan(v, out.Value) {
out.Value = v
out.Fields = item.Fields
out.Tags = item.Tags
}
}
if pointsYielded {
return out
}
return nil
}
// ReduceLast computes the last of value.
func ReduceLast(values []interface{}) interface{} {
out := &firstLastMapOutput{}
pointsYielded := false
for _, v := range values {
if v == nil {
continue
}
val := v.(*firstLastMapOutput)
// Initialize last
if !pointsYielded {
out.Time = val.Time
out.Value = val.Value
out.Fields = val.Fields
out.Tags = val.Tags
pointsYielded = true
}
if val.Time > out.Time {
out.Time = val.Time
out.Value = val.Value
out.Fields = val.Fields
out.Tags = val.Tags
} else if val.Time == out.Time && greaterThan(val.Value, out.Value) {
out.Value = val.Value
out.Fields = val.Fields
out.Tags = val.Tags
}
}
if pointsYielded {
return PositionPoint{
Time: out.Time,
Value: out.Value,
Fields: out.Fields,
Tags: out.Tags,
}
}
return nil
}
type positionOut struct {
points PositionPoints
callArgs []string // ordered args in the call
}
func (p *positionOut) lessKey(a, b *PositionPoint) bool {
t1, t2 := a.Tags, b.Tags
for _, k := range p.callArgs {
if t1[k] != t2[k] {
return t1[k] < t2[k]
}
}
return false
}
// typeCompare compares the types of a and b and returns an arbitrary ordering.
// It returns -1 if type(a) < type(b) , 0 if type(a) == type(b), or 1 if type(a) > type(b), following the strcmp convention
// from C.
//
// If the types are not equal, then it will attempt to coerce them to floating point and return them in the last 2 arguments.
// If the type cannot be coerced to floating point, it is returned unaltered.
func typeCompare(a, b interface{}) (int, interface{}, interface{}) {
const (
stringWeight = iota
boolWeight
intWeight
floatWeight
)
va := reflect.ValueOf(a)
vb := reflect.ValueOf(b)
vakind := va.Type().Kind()
vbkind := vb.Type().Kind()
// same kind. Ordering is dependent on value
if vakind == vbkind {
return 0, a, b
}
wa, a := inferFloat(va)
wb, b := inferFloat(vb)
if wa < wb {
return -1, a, b
} else if wa == wb {
return 0, a, b
}
return 1, a, b
}
// returns a weighting and if applicable, the value coerced to a float
func inferFloat(v reflect.Value) (weight int, value interface{}) {
const (
stringWeight = iota
boolWeight
intWeight
floatWeight
)
kind := v.Kind()
switch kind {
case reflect.Uint64, reflect.Uint32, reflect.Uint16, reflect.Uint8:
return intWeight, float64(v.Uint())
case reflect.Int64, reflect.Int32, reflect.Int16, reflect.Int8:
return intWeight, float64(v.Int())
case reflect.Float64, reflect.Float32:
return floatWeight, v.Float()
case reflect.Bool:
return boolWeight, v.Interface()
case reflect.String:
return stringWeight, v.Interface()
}
panic(fmt.Sprintf("InterfaceValues.Less - unreachable code; type was %T", v.Interface()))
}
func cmpFloat(a, b float64) int {
if a == b {
return 0
} else if a < b {
return -1
}
return 1
}
func cmpInt(a, b int64) int {
if a == b {
return 0
} else if a < b {
return -1
}
return 1
}
func cmpUint(a, b uint64) int {
if a == b {
return 0
} else if a < b {
return -1
}
return 1
}
// valueCompare returns -1 if a < b , 0 if a == b, or 1 if a > b
// If the interfaces are 2 different types, then 0 is returned
func valueCompare(a, b interface{}) int {
if reflect.TypeOf(a).Kind() != reflect.TypeOf(b).Kind() {
return 0
}
// compare by float64/int64 first as that is the most likely match
{
d1, ok1 := a.(float64)
d2, ok2 := b.(float64)
if ok1 && ok2 {
return cmpFloat(d1, d2)
}
}
{
d1, ok1 := a.(int64)
d2, ok2 := b.(int64)
if ok1 && ok2 {
return cmpInt(d1, d2)
}
}
// compare by every numeric type left
{
d1, ok1 := a.(float32)
d2, ok2 := b.(float32)
if ok1 && ok2 {
return cmpFloat(float64(d1), float64(d2))
}
}
{
d1, ok1 := a.(uint64)
d2, ok2 := b.(uint64)
if ok1 && ok2 {
return cmpUint(d1, d2)
}
}
{
d1, ok1 := a.(uint32)
d2, ok2 := b.(uint32)
if ok1 && ok2 {
return cmpUint(uint64(d1), uint64(d2))
}
}
{
d1, ok1 := a.(uint16)
d2, ok2 := b.(uint16)
if ok1 && ok2 {
return cmpUint(uint64(d1), uint64(d2))
}
}
{
d1, ok1 := a.(uint8)
d2, ok2 := b.(uint8)
if ok1 && ok2 {
return cmpUint(uint64(d1), uint64(d2))
}
}
{
d1, ok1 := a.(int32)
d2, ok2 := b.(int32)
if ok1 && ok2 {
return cmpInt(int64(d1), int64(d2))
}
}
{
d1, ok1 := a.(int16)
d2, ok2 := b.(int16)
if ok1 && ok2 {
return cmpInt(int64(d1), int64(d2))
}
}
{
d1, ok1 := a.(int8)
d2, ok2 := b.(int8)
if ok1 && ok2 {
return cmpInt(int64(d1), int64(d2))
}
}
{
d1, ok1 := a.(bool)
d2, ok2 := b.(bool)
if ok1 && ok2 {
if d1 == d2 {
return 0
} else if d1 == true && d2 == false {
return 1
}
return -1
}
}
{
d1, ok1 := a.(string)
d2, ok2 := b.(string)
if ok1 && ok2 {
if d1 == d2 {
return 0
}
if d1 > d2 {
return 1
}
return -1
}
}
panic(fmt.Sprintf("unreachable code; types were %T, %T", a, b))
}
// PositionPoints is a slice of PositionPoints used to return richer data from a reduce func
type PositionPoints []PositionPoint
// PositionPoint will return all data points from a written point that were selected in the query
// to be used in the post processing phase of the query executor to fill in additional
// tag and field values
type PositionPoint struct {
Time int64
Value interface{}
Fields map[string]interface{}
Tags map[string]string
}
type topBottomMapOut struct {
*positionOut
bottom bool
}
func (t *topBottomMapOut) Len() int { return len(t.points) }
func (t *topBottomMapOut) Swap(i, j int) { t.points[i], t.points[j] = t.points[j], t.points[i] }
func (t *topBottomMapOut) Less(i, j int) bool {
return t.positionPointLess(&t.points[i], &t.points[j])
}
func (t *topBottomMapOut) positionPointLess(pa, pb *PositionPoint) bool {
// old C trick makes this code easier to read. Imagine
// that the OP in "cmp(i, j) OP 0" is the comparison you want
// between i and j
cmpt, a, b := typeCompare(pa.Value, pb.Value)
cmpv := valueCompare(a, b)
if cmpv != 0 {
if t.bottom {
return cmpv > 0
}
return cmpv < 0
}
if cmpt != 0 {
return cmpt < 0
}
k1, k2 := pa.Time, pb.Time
if k1 != k2 {
return k1 > k2
}
return !t.lessKey(pa, pb)
}
// We never use this function, so make it a no-op.
func (t *topBottomMapOut) Push(i interface{}) {
panic("someone used the function")
}
// this function doesn't return anything meaningful, since we don't look at the
// return value and we don't want to allocate for generating an interface.
func (t *topBottomMapOut) Pop() interface{} {
t.points = t.points[:len(t.points)-1]
return nil
}
func (t *topBottomMapOut) insert(p PositionPoint) {
t.points[0] = p
heap.Fix(t, 0)
}
type topBottomReduceOut struct {
positionOut
bottom bool
}
func (t topBottomReduceOut) Len() int { return len(t.points) }
func (t topBottomReduceOut) Swap(i, j int) { t.points[i], t.points[j] = t.points[j], t.points[i] }
func (t topBottomReduceOut) Less(i, j int) bool {
// Now sort by time first, not value
k1, k2 := t.points[i].Time, t.points[j].Time
if k1 != k2 {
return k1 < k2
}
cmpt, a, b := typeCompare(t.points[i].Value, t.points[j].Value)
cmpv := valueCompare(a, b)
if cmpv != 0 {
if t.bottom {
return cmpv < 0
}
return cmpv > 0
}
if cmpt != 0 {
return cmpt < 0
}
return t.lessKey(&t.points[i], &t.points[j])
}
// callArgs will get any additional field/tag names that may be needed to sort with
// it is important to maintain the order of these that they were asked for in the call
// for sorting purposes
func topCallArgs(c *influxql.Call) []string {
var names []string
for _, v := range c.Args[1 : len(c.Args)-1] {
if f, ok := v.(*influxql.VarRef); ok {
names = append(names, f.Val)
}
}
return names
}
func tagkeytop(args []string, fields map[string]interface{}, keys map[string]string) string {
key := ""
for _, a := range args {
if v, ok := fields[a]; ok {
key += a + ":" + fmt.Sprintf("%v", v) + ","
continue
}
if v, ok := keys[a]; ok {
key += a + ":" + v + ","
continue
}
}
return key
}
// map iterator. We need this for the top
// query, but luckily that doesn't require ordered
// iteration, so we can fake it
type mapIter struct {
m map[string]PositionPoint
currTags map[string]string
currFields map[string]interface{}
tmin int64
}
func (m *mapIter) TMin() int64 {
return m.tmin
}
func (m *mapIter) Fields() map[string]interface{} {
return m.currFields
}
func (m *mapIter) Tags() map[string]string {
return m.currTags
}
func (m *mapIter) Next() (time int64, value interface{}) {
// this is a bit ugly, but can't think of any other way that doesn't involve dumping
// the entire map to an array
for key, p := range m.m {
m.currFields = p.Fields
m.currTags = p.Tags
time = p.Time
value = p.Value
delete(m.m, key)
return
}
return -1, nil
}
// MapTopBottom emits the top/bottom data points for each group by interval
func MapTopBottom(input *MapInput, limit int, fields []string, argCount int, callName string) interface{} {
out := positionOut{callArgs: fields}
out.points = make([]PositionPoint, 0, limit)
minheap := topBottomMapOut{
&out,
callName == "bottom",
}
tagmap := make(map[string]PositionPoint)
// throughout this function, we refer to max and top. This is by the ordering specified by
// minheap, not the ordering based on value. Since this function handles both top and bottom
// max can be the lowest valued entry.
// buffer so we don't allocate every time through
var pp PositionPoint
if argCount > 2 {
// this is a tag aggregating query.
// For each unique permutation of the tags given,
// select the max and then fall through to select top of those
// points
for _, item := range input.Items {
pp = PositionPoint{
Time: item.Timestamp,
Value: item.Value,
Fields: item.Fields,
Tags: item.Tags,
}
tags := item.Tags
// TODO in the future we need to send in fields as well
// this will allow a user to query on both fields and tags
// fields will take the priority over tags if there is a name collision
key := tagkeytop(fields, nil, tags)
p, ok := tagmap[key]
if !ok || minheap.positionPointLess(&p, &pp) {
tagmap[key] = pp
}
}
items := make([]MapItem, 0, len(tagmap))
for _, p := range tagmap {
items = append(items, MapItem{Timestamp: p.Time, Value: p.Value, Fields: p.Fields, Tags: p.Tags})
}
input = &MapInput{
TMin: input.TMin,
Items: items,
}
}
for _, item := range input.Items {
t := item.Timestamp
if input.TMin > -1 {
t = input.TMin
}
if len(out.points) < limit {
out.points = append(out.points, PositionPoint{t, item.Value, item.Fields, item.Tags})
if len(out.points) == limit {
heap.Init(&minheap)
}
} else {
// we're over the limit, so find out if we're bigger than the
// smallest point in the set and eject it if we are
minval := &out.points[0]
pp = PositionPoint{t, item.Value, item.Fields, item.Tags}
if minheap.positionPointLess(minval, &pp) {
minheap.insert(pp)
}
}
}
// should only happen on empty iterator.
if len(out.points) == 0 {
return nil
} else if len(out.points) < limit {
// it would be as fast to just sort regularly here,
// but falling down to the heapsort will mean we can get
// rid of another sort order.
heap.Init(&minheap)
}
// minheap should now contain the largest/smallest values that were encountered
// during iteration.
//
// we want these values in ascending sorted order. We can achieve this by iteratively
// removing the lowest element and putting it at the end of the array. This is analogous
// to a heap sort.
//
// computer science is fun!
result := out.points
for len(out.points) > 0 {
p := out.points[0]
heap.Pop(&minheap)
// reslice so that we can get to the element just after the heap
endslice := out.points[:len(out.points)+1]
endslice[len(endslice)-1] = p
}
// the ascending order is now in the result slice
return result
}
// ReduceTop computes the top values for each key.
// This function assumes that its inputs are in sorted ascending order.
func ReduceTopBottom(values []interface{}, limit int, fields []string, callName string) interface{} {
out := positionOut{callArgs: fields}
minheap := topBottomMapOut{&out, callName == "bottom"}
results := make([]PositionPoints, 0, len(values))
out.points = make([]PositionPoint, 0, limit)
for _, v := range values {
if v == nil {
continue
}
o, ok := v.(PositionPoints)
if !ok {
continue
}
results = append(results, o)
}
// These ranges are all in sorted ascending order
// so we can grab the top value out of all of them
// to figure out the top X ones.
keys := map[string]struct{}{}
for i := 0; i < limit; i++ {
var max *PositionPoint
whichselected := -1
for iter, v := range results {
// ignore if there are no values or if value is less.
if len(v) == 0 {
continue
} else if max != nil && !minheap.positionPointLess(max, &v[0]) {
continue
}
// ignore if we've already appended this key.
if len(fields) > 0 {
tagkey := tagkeytop(fields, nil, v[0].Tags)
if _, ok := keys[tagkey]; ok {
continue
}
}
max = &v[0]
whichselected = iter
}
if whichselected == -1 {
break
}
v := results[whichselected]
tagkey := tagkeytop(fields, nil, v[0].Tags)
keys[tagkey] = struct{}{}
out.points = append(out.points, v[0])
results[whichselected] = v[1:]
}
// now we need to resort the tops by time
sort.Sort(topBottomReduceOut{out, callName == "bottom"})
return out.points
}
// MapEcho emits the data points for each group by interval
func MapEcho(input *MapInput) interface{} {
var values []interface{}
for _, item := range input.Items {
values = append(values, item.Value)
}
return values
}
// ReducePercentile computes the percentile of values for each key.
func ReducePercentile(values []interface{}, percentile float64) interface{} {
var allValues []float64
for _, v := range values {
if v == nil {
continue
}
vals := v.([]interface{})
for _, v := range vals {
switch v.(type) {
case int64:
allValues = append(allValues, float64(v.(int64)))
case float64:
allValues = append(allValues, v.(float64))
}
}
}
sort.Float64s(allValues)
length := len(allValues)
index := int(math.Floor(float64(length)*percentile/100.0+0.5)) - 1
if index < 0 || index >= len(allValues) {
return nil
}
return allValues[index]
}
// IsNumeric returns whether a given aggregate can only be run on numeric fields.
func IsNumeric(c *influxql.Call) bool {
switch c.Name {
case "count", "first", "last", "distinct":
return false
default:
return true
}
}
// MapRawQuery is for queries without aggregates
func MapRawQuery(input *MapInput) interface{} {
var values []*rawQueryMapOutput
for _, item := range input.Items {
values = append(values, &rawQueryMapOutput{item.Timestamp, item.Value})
}
return values
}
type rawQueryMapOutput struct {
Time int64
Values interface{}
}
func (r *rawQueryMapOutput) String() string {
return fmt.Sprintf("{%#v %#v}", r.Time, r.Values)
}
type rawOutputs []*rawQueryMapOutput
func (a rawOutputs) Len() int { return len(a) }
func (a rawOutputs) Less(i, j int) bool { return a[i].Time < a[j].Time }
func (a rawOutputs) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func greaterThan(a, b interface{}) bool {
switch a := a.(type) {
case int64:
switch b := b.(type) {
case int64:
return a > b
case float64:
return float64(a) > b
}
case float64:
switch b := b.(type) {
case int64:
return a > float64(b)
case float64:
return a > b
}
case string:
switch b := b.(type) {
case string:
return a > b
}
case bool:
return a == true
}
return false
}
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