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, 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) }