520 lines
12 KiB
Go
520 lines
12 KiB
Go
package statsd
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import (
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"errors"
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"fmt"
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"log"
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"net"
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"sort"
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"strconv"
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"strings"
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"sync"
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"github.com/influxdata/influxdb/services/graphite"
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"github.com/influxdata/telegraf/plugins/inputs"
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)
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const UDP_PACKET_SIZE int = 1500
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var dropwarn = "ERROR: Message queue full. Discarding line [%s] " +
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"You may want to increase allowed_pending_messages in the config\n"
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type Statsd struct {
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// Address & Port to serve from
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ServiceAddress string
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// Number of messages allowed to queue up in between calls to Gather. If this
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// fills up, packets will get dropped until the next Gather interval is ran.
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AllowedPendingMessages int
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// Percentiles specifies the percentiles that will be calculated for timing
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// and histogram stats.
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Percentiles []int
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PercentileLimit int
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DeleteGauges bool
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DeleteCounters bool
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DeleteSets bool
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DeleteTimings bool
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ConvertNames bool
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// UDPPacketSize is the size of the read packets for the server listening
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// for statsd UDP packets. This will default to 1500 bytes.
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UDPPacketSize int `toml:"udp_packet_size"`
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sync.Mutex
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// Channel for all incoming statsd packets
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in chan []byte
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done chan struct{}
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// Cache gauges, counters & sets so they can be aggregated as they arrive
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gauges map[string]cachedgauge
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counters map[string]cachedcounter
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sets map[string]cachedset
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timings map[string]cachedtimings
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// bucket -> influx templates
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Templates []string
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}
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func NewStatsd() *Statsd {
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s := Statsd{}
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// Make data structures
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s.done = make(chan struct{})
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s.in = make(chan []byte, s.AllowedPendingMessages)
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s.gauges = make(map[string]cachedgauge)
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s.counters = make(map[string]cachedcounter)
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s.sets = make(map[string]cachedset)
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s.timings = make(map[string]cachedtimings)
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s.ConvertNames = true
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s.UDPPacketSize = UDP_PACKET_SIZE
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return &s
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}
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// One statsd metric, form is <bucket>:<value>|<mtype>|@<samplerate>
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type metric struct {
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name string
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bucket string
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hash string
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intvalue int64
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floatvalue float64
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mtype string
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additive bool
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samplerate float64
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tags map[string]string
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}
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type cachedset struct {
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name string
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set map[int64]bool
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tags map[string]string
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}
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type cachedgauge struct {
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name string
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value float64
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tags map[string]string
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}
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type cachedcounter struct {
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name string
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value int64
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tags map[string]string
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}
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type cachedtimings struct {
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name string
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stats RunningStats
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tags map[string]string
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}
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func (_ *Statsd) Description() string {
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return "Statsd Server"
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}
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const sampleConfig = `
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# Address and port to host UDP listener on
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service_address = ":8125"
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# Delete gauges every interval (default=false)
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delete_gauges = false
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# Delete counters every interval (default=false)
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delete_counters = false
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# Delete sets every interval (default=false)
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delete_sets = false
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# Delete timings & histograms every interval (default=true)
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delete_timings = true
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# Percentiles to calculate for timing & histogram stats
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percentiles = [90]
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# convert measurement names, "." to "_" and "-" to "__"
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convert_names = true
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# templates = [
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# "cpu.* measurement*"
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# ]
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# Number of UDP messages allowed to queue up, once filled,
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# the statsd server will start dropping packets
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allowed_pending_messages = 10000
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# Number of timing/histogram values to track per-measurement in the
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# calculation of percentiles. Raising this limit increases the accuracy
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# of percentiles but also increases the memory usage and cpu time.
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percentile_limit = 1000
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# UDP packet size for the server to listen for. This will depend on the size
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# of the packets that the client is sending, which is usually 1500 bytes.
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udp_packet_size = 1500
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`
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func (_ *Statsd) SampleConfig() string {
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return sampleConfig
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}
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func (s *Statsd) Gather(acc inputs.Accumulator) error {
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s.Lock()
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defer s.Unlock()
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for _, metric := range s.timings {
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acc.Add(metric.name+"_mean", metric.stats.Mean(), metric.tags)
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acc.Add(metric.name+"_stddev", metric.stats.Stddev(), metric.tags)
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acc.Add(metric.name+"_upper", metric.stats.Upper(), metric.tags)
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acc.Add(metric.name+"_lower", metric.stats.Lower(), metric.tags)
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acc.Add(metric.name+"_count", metric.stats.Count(), metric.tags)
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for _, percentile := range s.Percentiles {
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name := fmt.Sprintf("%s_percentile_%v", metric.name, percentile)
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acc.Add(name, metric.stats.Percentile(percentile), metric.tags)
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}
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}
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if s.DeleteTimings {
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s.timings = make(map[string]cachedtimings)
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}
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for _, metric := range s.gauges {
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acc.Add(metric.name, metric.value, metric.tags)
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}
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if s.DeleteGauges {
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s.gauges = make(map[string]cachedgauge)
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}
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for _, metric := range s.counters {
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acc.Add(metric.name, metric.value, metric.tags)
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}
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if s.DeleteCounters {
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s.counters = make(map[string]cachedcounter)
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}
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for _, metric := range s.sets {
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acc.Add(metric.name, int64(len(metric.set)), metric.tags)
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}
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if s.DeleteSets {
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s.sets = make(map[string]cachedset)
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}
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return nil
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}
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func (s *Statsd) Start() error {
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// Make data structures
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s.done = make(chan struct{})
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s.in = make(chan []byte, s.AllowedPendingMessages)
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s.gauges = make(map[string]cachedgauge)
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s.counters = make(map[string]cachedcounter)
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s.sets = make(map[string]cachedset)
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s.timings = make(map[string]cachedtimings)
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// Start the UDP listener
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go s.udpListen()
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// Start the line parser
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go s.parser()
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log.Printf("Started the statsd service on %s\n", s.ServiceAddress)
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return nil
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}
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// udpListen starts listening for udp packets on the configured port.
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func (s *Statsd) udpListen() error {
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address, _ := net.ResolveUDPAddr("udp", s.ServiceAddress)
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listener, err := net.ListenUDP("udp", address)
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if err != nil {
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log.Fatalf("ERROR: ListenUDP - %s", err)
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}
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defer listener.Close()
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log.Println("Statsd listener listening on: ", listener.LocalAddr().String())
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for {
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select {
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case <-s.done:
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return nil
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default:
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buf := make([]byte, s.UDPPacketSize)
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n, _, err := listener.ReadFromUDP(buf)
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if err != nil {
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log.Printf("ERROR: %s\n", err.Error())
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}
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select {
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case s.in <- buf[:n]:
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default:
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log.Printf(dropwarn, string(buf[:n]))
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}
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}
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}
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}
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// parser monitors the s.in channel, if there is a packet ready, it parses the
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// packet into statsd strings and then calls parseStatsdLine, which parses a
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// single statsd metric into a struct.
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func (s *Statsd) parser() error {
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for {
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select {
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case <-s.done:
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return nil
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case packet := <-s.in:
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lines := strings.Split(string(packet), "\n")
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for _, line := range lines {
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line = strings.TrimSpace(line)
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if line != "" {
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s.parseStatsdLine(line)
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}
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}
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}
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}
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}
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// parseStatsdLine will parse the given statsd line, validating it as it goes.
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// If the line is valid, it will be cached for the next call to Gather()
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func (s *Statsd) parseStatsdLine(line string) error {
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s.Lock()
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defer s.Unlock()
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// Validate splitting the line on ":"
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bits := strings.Split(line, ":")
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if len(bits) < 2 {
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log.Printf("Error: splitting ':', Unable to parse metric: %s\n", line)
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return errors.New("Error Parsing statsd line")
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}
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// Extract bucket name from individual metric bits
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bucketName, bits := bits[0], bits[1:]
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// Add a metric for each bit available
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for _, bit := range bits {
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m := metric{}
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m.bucket = bucketName
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// Validate splitting the bit on "|"
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pipesplit := strings.Split(bit, "|")
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if len(pipesplit) < 2 {
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log.Printf("Error: splitting '|', Unable to parse metric: %s\n", line)
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return errors.New("Error Parsing statsd line")
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} else if len(pipesplit) > 2 {
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sr := pipesplit[2]
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errmsg := "Error: parsing sample rate, %s, it must be in format like: " +
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"@0.1, @0.5, etc. Ignoring sample rate for line: %s\n"
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if strings.Contains(sr, "@") && len(sr) > 1 {
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samplerate, err := strconv.ParseFloat(sr[1:], 64)
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if err != nil {
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log.Printf(errmsg, err.Error(), line)
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} else {
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// sample rate successfully parsed
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m.samplerate = samplerate
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}
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} else {
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log.Printf(errmsg, "", line)
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}
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}
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// Validate metric type
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switch pipesplit[1] {
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case "g", "c", "s", "ms", "h":
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m.mtype = pipesplit[1]
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default:
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log.Printf("Error: Statsd Metric type %s unsupported", pipesplit[1])
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return errors.New("Error Parsing statsd line")
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}
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// Parse the value
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if strings.ContainsAny(pipesplit[0], "-+") {
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if m.mtype != "g" {
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log.Printf("Error: +- values are only supported for gauges: %s\n", line)
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return errors.New("Error Parsing statsd line")
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}
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m.additive = true
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}
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switch m.mtype {
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case "g", "ms", "h":
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v, err := strconv.ParseFloat(pipesplit[0], 64)
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if err != nil {
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log.Printf("Error: parsing value to float64: %s\n", line)
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return errors.New("Error Parsing statsd line")
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}
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m.floatvalue = v
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case "c", "s":
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v, err := strconv.ParseInt(pipesplit[0], 10, 64)
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if err != nil {
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log.Printf("Error: parsing value to int64: %s\n", line)
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return errors.New("Error Parsing statsd line")
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}
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// If a sample rate is given with a counter, divide value by the rate
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if m.samplerate != 0 && m.mtype == "c" {
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v = int64(float64(v) / m.samplerate)
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}
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m.intvalue = v
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}
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// Parse the name & tags from bucket
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m.name, m.tags = s.parseName(m.bucket)
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switch m.mtype {
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case "c":
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m.tags["metric_type"] = "counter"
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case "g":
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m.tags["metric_type"] = "gauge"
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case "s":
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m.tags["metric_type"] = "set"
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case "ms":
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m.tags["metric_type"] = "timing"
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case "h":
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m.tags["metric_type"] = "histogram"
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}
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// Make a unique key for the measurement name/tags
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var tg []string
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for k, v := range m.tags {
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tg = append(tg, fmt.Sprintf("%s=%s", k, v))
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}
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sort.Strings(tg)
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m.hash = fmt.Sprintf("%s%s", strings.Join(tg, ""), m.name)
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s.aggregate(m)
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}
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return nil
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}
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// parseName parses the given bucket name with the list of bucket maps in the
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// config file. If there is a match, it will parse the name of the metric and
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// map of tags.
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// Return values are (<name>, <tags>)
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func (s *Statsd) parseName(bucket string) (string, map[string]string) {
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tags := make(map[string]string)
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bucketparts := strings.Split(bucket, ",")
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// Parse out any tags in the bucket
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if len(bucketparts) > 1 {
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for _, btag := range bucketparts[1:] {
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k, v := parseKeyValue(btag)
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if k != "" {
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tags[k] = v
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}
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}
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}
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o := graphite.Options{
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Separator: "_",
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Templates: s.Templates,
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DefaultTags: tags,
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}
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name := bucketparts[0]
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p, err := graphite.NewParserWithOptions(o)
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if err == nil {
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name, tags, _, _ = p.ApplyTemplate(name)
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}
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if s.ConvertNames {
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name = strings.Replace(name, ".", "_", -1)
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name = strings.Replace(name, "-", "__", -1)
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}
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return name, tags
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}
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// Parse the key,value out of a string that looks like "key=value"
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func parseKeyValue(keyvalue string) (string, string) {
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var key, val string
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split := strings.Split(keyvalue, "=")
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// Must be exactly 2 to get anything meaningful out of them
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if len(split) == 2 {
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key = split[0]
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val = split[1]
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} else if len(split) == 1 {
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val = split[0]
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}
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return key, val
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}
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// aggregate takes in a metric. It then
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// aggregates and caches the current value(s). It does not deal with the
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// Delete* options, because those are dealt with in the Gather function.
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func (s *Statsd) aggregate(m metric) {
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switch m.mtype {
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case "ms", "h":
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cached, ok := s.timings[m.hash]
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if !ok {
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cached = cachedtimings{
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name: m.name,
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tags: m.tags,
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stats: RunningStats{
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PercLimit: s.PercentileLimit,
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},
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}
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}
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if m.samplerate > 0 {
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for i := 0; i < int(1.0/m.samplerate); i++ {
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cached.stats.AddValue(m.floatvalue)
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}
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s.timings[m.hash] = cached
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} else {
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cached.stats.AddValue(m.floatvalue)
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s.timings[m.hash] = cached
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}
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case "c":
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cached, ok := s.counters[m.hash]
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if !ok {
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s.counters[m.hash] = cachedcounter{
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name: m.name,
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value: m.intvalue,
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tags: m.tags,
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}
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} else {
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cached.value += m.intvalue
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s.counters[m.hash] = cached
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}
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case "g":
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cached, ok := s.gauges[m.hash]
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if !ok {
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s.gauges[m.hash] = cachedgauge{
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name: m.name,
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value: m.floatvalue,
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tags: m.tags,
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}
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} else {
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if m.additive {
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cached.value = cached.value + m.floatvalue
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} else {
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cached.value = m.floatvalue
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}
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s.gauges[m.hash] = cached
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}
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case "s":
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cached, ok := s.sets[m.hash]
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if !ok {
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// Completely new metric (initialize with count of 1)
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s.sets[m.hash] = cachedset{
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name: m.name,
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tags: m.tags,
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set: map[int64]bool{m.intvalue: true},
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}
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} else {
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cached.set[m.intvalue] = true
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s.sets[m.hash] = cached
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}
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}
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}
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func (s *Statsd) Stop() {
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s.Lock()
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defer s.Unlock()
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log.Println("Stopping the statsd service")
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close(s.done)
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close(s.in)
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}
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func init() {
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inputs.Add("statsd", func() inputs.Input {
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return &Statsd{
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ConvertNames: true,
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UDPPacketSize: UDP_PACKET_SIZE,
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}
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})
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}
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