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influxql.go
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influxql.go
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package kapacitor
import (
"fmt"
"log"
"sync"
"time"
"github.com/influxdata/kapacitor/expvar"
"github.com/influxdata/kapacitor/models"
"github.com/influxdata/kapacitor/pipeline"
"github.com/pkg/errors"
)
// tmpl -- go get github.com/benbjohnson/tmpl
//go:generate tmpl -data=@tmpldata influxql.gen.go.tmpl
type createReduceContextFunc func(c baseReduceContext) reduceContext
var ErrEmptyEmit = errors.New("error call to emit produced no results")
type InfluxQLNode struct {
node
n *pipeline.InfluxQLNode
createFn createReduceContextFunc
isStreamTransformation bool
}
func newInfluxQLNode(et *ExecutingTask, n *pipeline.InfluxQLNode, l *log.Logger) (*InfluxQLNode, error) {
m := &InfluxQLNode{
node: node{Node: n, et: et, logger: l},
n: n,
isStreamTransformation: n.ReduceCreater.IsStreamTransformation,
}
m.node.runF = m.runInfluxQLs
return m, nil
}
func (n *InfluxQLNode) runInfluxQLs([]byte) error {
switch n.n.Wants() {
case pipeline.StreamEdge:
return n.runStreamInfluxQL()
case pipeline.BatchEdge:
return n.runBatchInfluxQL()
default:
return fmt.Errorf("cannot map %v edge", n.n.Wants())
}
}
type reduceContext interface {
AggregatePoint(p *models.Point) error
AggregateBatch(b *models.Batch) error
EmitPoint() (models.Point, error)
EmitBatch() models.Batch
Time() time.Time
}
type baseReduceContext struct {
as string
field string
name string
group models.GroupID
dimensions models.Dimensions
tags models.Tags
time time.Time
pointTimes bool
topBottomInfo *pipeline.TopBottomCallInfo
}
func (c *baseReduceContext) Time() time.Time {
return c.time
}
func (n *InfluxQLNode) runStreamInfluxQL() error {
var mu sync.RWMutex
contexts := make(map[models.GroupID]reduceContext)
n.nodeCardinality = expvar.NewIntFuncGauge(func() int64 {
mu.RLock()
l := len(contexts)
mu.RUnlock()
return int64(l)
})
for p, ok := n.ins[0].NextPoint(); ok; {
n.timer.Start()
mu.RLock()
context := contexts[p.Group]
mu.RUnlock()
// Fisrt point in window
if context == nil {
// Create new context
c := baseReduceContext{
as: n.n.As,
field: n.n.Field,
name: p.Name,
group: p.Group,
dimensions: p.Dimensions,
tags: p.PointTags(),
time: p.Time,
pointTimes: n.n.PointTimes || n.isStreamTransformation,
}
createFn, err := n.getCreateFn(p.Fields[c.field])
if err != nil {
return err
}
context = createFn(c)
mu.Lock()
contexts[p.Group] = context
mu.Unlock()
}
if n.isStreamTransformation {
err := context.AggregatePoint(&p)
if err != nil {
n.incrementErrorCount()
n.logger.Println("E! failed to aggregate point:", err)
}
p, ok = n.ins[0].NextPoint()
err = n.emit(context)
if err != nil && err != ErrEmptyEmit {
n.incrementErrorCount()
n.logger.Println("E! failed to emit stream:", err)
}
} else {
if p.Time.Equal(context.Time()) {
err := context.AggregatePoint(&p)
if err != nil {
n.incrementErrorCount()
n.logger.Println("E! failed to aggregate point:", err)
}
// advance to next point
p, ok = n.ins[0].NextPoint()
} else {
err := n.emit(context)
if err != nil {
n.incrementErrorCount()
n.logger.Println("E! failed to emit stream:", err)
}
// Nil out reduced point
mu.Lock()
contexts[p.Group] = nil
mu.Unlock()
// do not advance,
// go through loop again to initialize new iterator.
}
}
n.timer.Stop()
}
return nil
}
func (n *InfluxQLNode) runBatchInfluxQL() error {
var exampleValue interface{}
for b, ok := n.ins[0].NextBatch(); ok; b, ok = n.ins[0].NextBatch() {
n.timer.Start()
// Create new base context
c := baseReduceContext{
as: n.n.As,
field: n.n.Field,
name: b.Name,
group: b.Group,
dimensions: b.PointDimensions(),
tags: b.Tags,
time: b.TMax,
pointTimes: n.n.PointTimes || n.isStreamTransformation,
}
if len(b.Points) == 0 {
if !n.n.ReduceCreater.IsEmptyOK {
// If the reduce does not handle empty batches continue
n.timer.Stop()
continue
}
if exampleValue == nil {
// If we have no points and have never seen a point assume float64
exampleValue = float64(0)
}
} else {
exampleValue = b.Points[0].Fields[c.field]
}
createFn, err := n.getCreateFn(exampleValue)
if err != nil {
return err
}
context := createFn(c)
if n.isStreamTransformation {
// We have a stream transformation, so treat the batch as if it were a stream
// Create a new batch for emitting
eb := b
eb.Points = make([]models.BatchPoint, 0, len(b.Points))
for _, bp := range b.Points {
p := models.Point{
Name: b.Name,
Time: bp.Time,
Fields: bp.Fields,
Tags: bp.Tags,
}
if err := context.AggregatePoint(&p); err != nil {
n.incrementErrorCount()
n.logger.Println("E! failed to aggregate batch point:", err)
}
if ep, err := context.EmitPoint(); err != nil && err != ErrEmptyEmit {
n.incrementErrorCount()
n.logger.Println("E! failed to emit batch point:", err)
} else if err != ErrEmptyEmit {
eb.Points = append(eb.Points, models.BatchPoint{
Time: ep.Time,
Fields: ep.Fields,
Tags: ep.Tags,
})
}
}
// Emit the complete batch
n.timer.Pause()
for _, out := range n.outs {
if err := out.CollectBatch(eb); err != nil {
n.incrementErrorCount()
n.logger.Println("E! failed to emit batch points:", err)
}
}
n.timer.Resume()
} else {
err := context.AggregateBatch(&b)
if err == nil {
if err := n.emit(context); err != nil {
n.incrementErrorCount()
n.logger.Println("E! failed to emit batch:", err)
}
} else {
n.incrementErrorCount()
n.logger.Println("E! failed to aggregate batch:", err)
}
}
n.timer.Stop()
}
return nil
}
func (n *InfluxQLNode) getCreateFn(value interface{}) (createReduceContextFunc, error) {
if n.createFn != nil {
return n.createFn, nil
}
createFn, err := determineReduceContextCreateFn(n.n.Method, value, n.n.ReduceCreater)
if err != nil {
return nil, errors.Wrapf(err, "invalid influxql func %s with field %s", n.n.Method, n.n.Field)
}
n.createFn = createFn
return n.createFn, nil
}
func (n *InfluxQLNode) emit(context reduceContext) error {
switch n.Provides() {
case pipeline.StreamEdge:
p, err := context.EmitPoint()
if err != nil {
return err
}
n.timer.Pause()
for _, out := range n.outs {
err := out.CollectPoint(p)
if err != nil {
return err
}
}
n.timer.Resume()
case pipeline.BatchEdge:
b := context.EmitBatch()
n.timer.Pause()
for _, out := range n.outs {
err := out.CollectBatch(b)
if err != nil {
return err
}
}
n.timer.Resume()
}
return nil
}