telegraf/internal/models/running_output.go

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package models
import (
"sync"
"sync/atomic"
"time"
"github.com/influxdata/telegraf"
"github.com/influxdata/telegraf/selfstat"
)
const (
// Default size of metrics batch size.
DEFAULT_METRIC_BATCH_SIZE = 1000
// Default number of metrics kept. It should be a multiple of batch size.
DEFAULT_METRIC_BUFFER_LIMIT = 10000
)
// OutputConfig containing name and filter
type OutputConfig struct {
Name string
Alias string
Filter Filter
FlushInterval time.Duration
FlushJitter *time.Duration
MetricBufferLimit int
MetricBatchSize int
}
// RunningOutput contains the output configuration
type RunningOutput struct {
// Must be 64-bit aligned
newMetricsCount int64
droppedMetrics int64
Output telegraf.Output
Config *OutputConfig
MetricBufferLimit int
MetricBatchSize int
MetricsFiltered selfstat.Stat
WriteTime selfstat.Stat
BatchReady chan time.Time
buffer *Buffer
log telegraf.Logger
aggMutex sync.Mutex
}
func NewRunningOutput(
name string,
output telegraf.Output,
config *OutputConfig,
batchSize int,
bufferLimit int,
) *RunningOutput {
tags := map[string]string{"output": config.Name}
if config.Alias != "" {
tags["alias"] = config.Alias
}
logger := &Logger{
Name: logName("outputs", config.Name, config.Alias),
Errs: selfstat.Register("write", "errors", tags),
}
setLogIfExist(output, logger)
if config.MetricBufferLimit > 0 {
bufferLimit = config.MetricBufferLimit
}
if bufferLimit == 0 {
bufferLimit = DEFAULT_METRIC_BUFFER_LIMIT
}
if config.MetricBatchSize > 0 {
batchSize = config.MetricBatchSize
}
if batchSize == 0 {
batchSize = DEFAULT_METRIC_BATCH_SIZE
}
ro := &RunningOutput{
buffer: NewBuffer(config.Name, config.Alias, bufferLimit),
BatchReady: make(chan time.Time, 1),
Output: output,
Config: config,
MetricBufferLimit: bufferLimit,
MetricBatchSize: batchSize,
MetricsFiltered: selfstat.Register(
"write",
"metrics_filtered",
tags,
),
WriteTime: selfstat.RegisterTiming(
"write",
"write_time_ns",
tags,
),
log: logger,
}
return ro
}
func (r *RunningOutput) LogName() string {
return logName("outputs", r.Config.Name, r.Config.Alias)
}
func (ro *RunningOutput) metricFiltered(metric telegraf.Metric) {
ro.MetricsFiltered.Incr(1)
metric.Drop()
}
func (r *RunningOutput) Init() error {
if p, ok := r.Output.(telegraf.Initializer); ok {
err := p.Init()
if err != nil {
return err
}
}
return nil
}
// AddMetric adds a metric to the output.
//
// Takes ownership of metric
func (ro *RunningOutput) AddMetric(metric telegraf.Metric) {
if ok := ro.Config.Filter.Select(metric); !ok {
ro.metricFiltered(metric)
return
}
ro.Config.Filter.Modify(metric)
if len(metric.FieldList()) == 0 {
ro.metricFiltered(metric)
return
}
if output, ok := ro.Output.(telegraf.AggregatingOutput); ok {
ro.aggMutex.Lock()
output.Add(metric)
ro.aggMutex.Unlock()
return
}
dropped := ro.buffer.Add(metric)
atomic.AddInt64(&ro.droppedMetrics, int64(dropped))
count := atomic.AddInt64(&ro.newMetricsCount, 1)
if count == int64(ro.MetricBatchSize) {
atomic.StoreInt64(&ro.newMetricsCount, 0)
select {
case ro.BatchReady <- time.Now():
default:
}
}
}
// Write writes all metrics to the output, stopping when all have been sent on
// or error.
func (ro *RunningOutput) Write() error {
if output, ok := ro.Output.(telegraf.AggregatingOutput); ok {
ro.aggMutex.Lock()
metrics := output.Push()
ro.buffer.Add(metrics...)
output.Reset()
ro.aggMutex.Unlock()
}
atomic.StoreInt64(&ro.newMetricsCount, 0)
// Only process the metrics in the buffer now. Metrics added while we are
// writing will be sent on the next call.
nBuffer := ro.buffer.Len()
nBatches := nBuffer/ro.MetricBatchSize + 1
for i := 0; i < nBatches; i++ {
batch := ro.buffer.Batch(ro.MetricBatchSize)
if len(batch) == 0 {
break
}
err := ro.write(batch)
if err != nil {
ro.buffer.Reject(batch)
return err
}
ro.buffer.Accept(batch)
}
return nil
}
// WriteBatch writes a single batch of metrics to the output.
func (ro *RunningOutput) WriteBatch() error {
batch := ro.buffer.Batch(ro.MetricBatchSize)
if len(batch) == 0 {
return nil
}
err := ro.write(batch)
if err != nil {
ro.buffer.Reject(batch)
return err
}
ro.buffer.Accept(batch)
return nil
}
func (r *RunningOutput) Close() {
err := r.Output.Close()
if err != nil {
r.log.Errorf("Error closing output: %v", err)
}
}
func (r *RunningOutput) write(metrics []telegraf.Metric) error {
dropped := atomic.LoadInt64(&r.droppedMetrics)
if dropped > 0 {
r.log.Warnf("Metric buffer overflow; %d metrics have been dropped", dropped)
atomic.StoreInt64(&r.droppedMetrics, 0)
}
start := time.Now()
err := r.Output.Write(metrics)
elapsed := time.Since(start)
r.WriteTime.Incr(elapsed.Nanoseconds())
if err == nil {
r.log.Debugf("Wrote batch of %d metrics in %s", len(metrics), elapsed)
}
return err
}
func (r *RunningOutput) LogBufferStatus() {
nBuffer := r.buffer.Len()
r.log.Debugf("Buffer fullness: %d / %d metrics", nBuffer, r.MetricBufferLimit)
}