VictoriaMetrics/app/vmctl/opentsdb.go

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package main
import (
"fmt"
"log"
"sync"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmctl/opentsdb"
"github.com/VictoriaMetrics/VictoriaMetrics/app/vmctl/vm"
"github.com/cheggaaa/pb/v3"
)
type otsdbProcessor struct {
oc *opentsdb.Client
im *vm.Importer
otsdbcc int
isVerbose bool
}
type queryObj struct {
Series opentsdb.Meta
Rt opentsdb.RetentionMeta
Tr opentsdb.TimeRange
StartTime int64
}
func newOtsdbProcessor(oc *opentsdb.Client, im *vm.Importer, otsdbcc int, verbose bool) *otsdbProcessor {
if otsdbcc < 1 {
otsdbcc = 1
}
return &otsdbProcessor{
oc: oc,
im: im,
otsdbcc: otsdbcc,
isVerbose: verbose,
}
}
func (op *otsdbProcessor) run() error {
log.Println("Loading all metrics from OpenTSDB for filters: ", op.oc.Filters)
var metrics []string
for _, filter := range op.oc.Filters {
q := fmt.Sprintf("%s/api/suggest?type=metrics&q=%s&max=%d", op.oc.Addr, filter, op.oc.Limit)
m, err := op.oc.FindMetrics(q)
if err != nil {
return fmt.Errorf("metric discovery failed for %q: %s", q, err)
}
metrics = append(metrics, m...)
}
if len(metrics) < 1 {
return fmt.Errorf("found no timeseries to import with filters %q", op.oc.Filters)
}
question := fmt.Sprintf("Found %d metrics to import. Continue?", len(metrics))
if !prompt(question) {
return nil
}
op.im.ResetStats()
var startTime int64
if op.oc.HardTS != 0 {
startTime = op.oc.HardTS
} else {
startTime = time.Now().Unix()
}
queryRanges := 0
// pre-calculate the number of query ranges we'll be processing
for _, rt := range op.oc.Retentions {
queryRanges += len(rt.QueryRanges)
}
for _, metric := range metrics {
log.Printf("Starting work on %s", metric)
serieslist, err := op.oc.FindSeries(metric)
if err != nil {
return fmt.Errorf("couldn't retrieve series list for %s : %s", metric, err)
}
/*
Create channels for collecting/processing series and errors
We'll create them per metric to reduce pressure against OpenTSDB
Limit the size of seriesCh so we can't get too far ahead of actual processing
*/
seriesCh := make(chan queryObj, op.otsdbcc)
errCh := make(chan error)
// we're going to make serieslist * queryRanges queries, so we should represent that in the progress bar
bar := pb.StartNew(len(serieslist) * queryRanges)
defer func(bar *pb.ProgressBar) {
bar.Finish()
}(bar)
var wg sync.WaitGroup
wg.Add(op.otsdbcc)
for i := 0; i < op.otsdbcc; i++ {
go func() {
defer wg.Done()
for s := range seriesCh {
if err := op.do(s); err != nil {
errCh <- fmt.Errorf("couldn't retrieve series for %s : %s", metric, err)
return
}
bar.Increment()
}
}()
}
/*
Loop through all series for this metric, processing all retentions and time ranges
requested. This loop is our primary "collect data from OpenTSDB loop" and should
be async, sending data to VictoriaMetrics over time.
The idea with having the select at the inner-most loop is to ensure quick
short-circuiting on error.
*/
for _, series := range serieslist {
for _, rt := range op.oc.Retentions {
for _, tr := range rt.QueryRanges {
select {
case otsdbErr := <-errCh:
return fmt.Errorf("opentsdb error: %s", otsdbErr)
case vmErr := <-op.im.Errors():
return fmt.Errorf("import process failed: %s", wrapErr(vmErr, op.isVerbose))
case seriesCh <- queryObj{
Tr: tr, StartTime: startTime,
Series: series, Rt: opentsdb.RetentionMeta{
FirstOrder: rt.FirstOrder, SecondOrder: rt.SecondOrder, AggTime: rt.AggTime}}:
}
}
}
}
// Drain channels per metric
close(seriesCh)
wg.Wait()
close(errCh)
// check for any lingering errors on the query side
for otsdbErr := range errCh {
return fmt.Errorf("Import process failed: \n%s", otsdbErr)
}
bar.Finish()
log.Print(op.im.Stats())
}
op.im.Close()
for vmErr := range op.im.Errors() {
if vmErr.Err != nil {
return fmt.Errorf("import process failed: %s", wrapErr(vmErr, op.isVerbose))
}
}
log.Println("Import finished!")
log.Print(op.im.Stats())
return nil
}
func (op *otsdbProcessor) do(s queryObj) error {
start := s.StartTime - s.Tr.Start
end := s.StartTime - s.Tr.End
data, err := op.oc.GetData(s.Series, s.Rt, start, end, op.oc.MsecsTime)
if err != nil {
return fmt.Errorf("failed to collect data for %v in %v:%v :: %v", s.Series, s.Rt, s.Tr, err)
}
if len(data.Timestamps) < 1 || len(data.Values) < 1 {
return nil
}
labels := make([]vm.LabelPair, 0, len(data.Tags))
for k, v := range data.Tags {
labels = append(labels, vm.LabelPair{Name: k, Value: v})
}
ts := vm.TimeSeries{
Name: data.Metric,
LabelPairs: labels,
Timestamps: data.Timestamps,
Values: data.Values,
}
return op.im.Input(&ts)
}