mirror of
https://github.com/VictoriaMetrics/VictoriaMetrics.git
synced 2024-12-01 14:47:38 +00:00
4acc4602b3
This should reduce the maximum memory usage at VictoriaMetrics when importing time series with big number of samples.
92 lines
2.2 KiB
Go
92 lines
2.2 KiB
Go
package vm
|
|
|
|
import (
|
|
"fmt"
|
|
"io"
|
|
)
|
|
|
|
// TimeSeries represents a time series.
|
|
type TimeSeries struct {
|
|
Name string
|
|
LabelPairs []LabelPair
|
|
Timestamps []int64
|
|
Values []float64
|
|
}
|
|
|
|
// LabelPair represents a label
|
|
type LabelPair struct {
|
|
Name string
|
|
Value string
|
|
}
|
|
|
|
// String returns user-readable ts.
|
|
func (ts TimeSeries) String() string {
|
|
s := ts.Name
|
|
if len(ts.LabelPairs) < 1 {
|
|
return s
|
|
}
|
|
var labels string
|
|
for i, lp := range ts.LabelPairs {
|
|
labels += fmt.Sprintf("%s=%q", lp.Name, lp.Value)
|
|
if i < len(ts.LabelPairs)-1 {
|
|
labels += ","
|
|
}
|
|
}
|
|
return fmt.Sprintf("%s{%s}", s, labels)
|
|
}
|
|
|
|
// cWriter used to avoid error checking
|
|
// while doing Write calls.
|
|
// cWriter caches the first error if any
|
|
// and discards all sequential write calls
|
|
type cWriter struct {
|
|
w io.Writer
|
|
n int
|
|
err error
|
|
}
|
|
|
|
func (cw *cWriter) printf(format string, args ...interface{}) {
|
|
if cw.err != nil {
|
|
return
|
|
}
|
|
n, err := fmt.Fprintf(cw.w, format, args...)
|
|
cw.n += n
|
|
cw.err = err
|
|
}
|
|
|
|
//"{"metric":{"__name__":"cpu_usage_guest","arch":"x64","hostname":"host_19",},"timestamps":[1567296000000,1567296010000],"values":[1567296000000,66]}
|
|
func (ts *TimeSeries) write(w io.Writer) (int, error) {
|
|
timestamps := ts.Timestamps
|
|
values := ts.Values
|
|
cw := &cWriter{w: w}
|
|
for len(timestamps) > 0 {
|
|
// Split long lines with more than 10K samples into multiple JSON lines.
|
|
// This should limit memory usage at VictoriaMetrics during data ingestion,
|
|
// since it allocates memory for the whole JSON line and processes it in one go.
|
|
batchSize := 10000
|
|
if batchSize > len(timestamps) {
|
|
batchSize = len(timestamps)
|
|
}
|
|
timestampsBatch := timestamps[:batchSize]
|
|
valuesBatch := values[:batchSize]
|
|
timestamps = timestamps[batchSize:]
|
|
values = values[batchSize:]
|
|
|
|
cw.printf(`{"metric":{"__name__":%q`, ts.Name)
|
|
for _, lp := range ts.LabelPairs {
|
|
cw.printf(",%q:%q", lp.Name, lp.Value)
|
|
}
|
|
|
|
pointsCount := len(timestampsBatch)
|
|
cw.printf(`},"timestamps":[`)
|
|
for i := 0; i < pointsCount-1; i++ {
|
|
cw.printf(`%d,`, timestampsBatch[i])
|
|
}
|
|
cw.printf(`%d],"values":[`, timestampsBatch[pointsCount-1])
|
|
for i := 0; i < pointsCount-1; i++ {
|
|
cw.printf(`%v,`, valuesBatch[i])
|
|
}
|
|
cw.printf("%v]}\n", valuesBatch[pointsCount-1])
|
|
}
|
|
return cw.n, cw.err
|
|
}
|