func Example_mergeMultipleStreams() { // Scenario: // We have multiple database shards. On each shard, there is a process // collecting query response times from the database logs and inserting // them into a Stream (created via NewTargeted(0.90)), much like the // Simple example. These processes expose a network interface for us to // ask them to serialize and send us the results of their // Stream.Samples so we may Merge and Query them. // // NOTES: // * These sample sets are small, allowing us to get them // across the network much faster than sending the entire list of data // points. // // * For this to work correctly, we must supply the same quantiles // a priori the process collecting the samples supplied to NewTargeted, // even if we do not plan to query them all here. ch := make(chan quantile.Samples) getDBQuerySamples(ch) q := quantile.NewTargeted(map[float64]float64{0.90: 0.001}) for samples := range ch { q.Merge(samples) } fmt.Println("perc90:", q.Query(0.90)) }
func Example_window() { // Scenario: We want the 90th, 95th, and 99th percentiles for each // minute. ch := make(chan float64) go sendStreamValues(ch) tick := time.NewTicker(1 * time.Minute) q := quantile.NewTargeted(map[float64]float64{ 0.90: 0.001, 0.95: 0.0005, 0.99: 0.0001, }) for { select { case t := <-tick.C: flushToDB(t, q.Samples()) q.Reset() case v := <-ch: q.Insert(v) } } }
func Example_simple() { ch := make(chan float64) go sendFloats(ch) // Compute the 50th, 90th, and 99th percentile. q := quantile.NewTargeted(map[float64]float64{ 0.50: 0.005, 0.90: 0.001, 0.99: 0.0001, }) for v := range ch { q.Insert(v) } fmt.Println("perc50:", q.Query(0.50)) fmt.Println("perc90:", q.Query(0.90)) fmt.Println("perc99:", q.Query(0.99)) fmt.Println("count:", q.Count()) // Output: // perc50: 5 // perc90: 16 // perc99: 223 // count: 2388 }
func (s *summary) newStream() *quantile.Stream { return quantile.NewTargeted(s.objectives) }