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allow metrictank to run as graphite 1.0 cluster node #611
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,39 @@ | ||
| package response | ||
|
|
||
| import ( | ||
| "bytes" | ||
| pickle "github.com/kisielk/og-rek" | ||
| ) | ||
|
|
||
| type Pickle struct { | ||
| code int | ||
| body interface{} | ||
| buf []byte | ||
| } | ||
|
|
||
| func NewPickle(code int, body interface{}) *Pickle { | ||
| return &Pickle{ | ||
| code: code, | ||
| body: body, | ||
| buf: BufferPool.Get(), | ||
| } | ||
| } | ||
|
|
||
| func (r *Pickle) Code() int { | ||
| return r.code | ||
| } | ||
|
|
||
| func (r *Pickle) Close() { | ||
| BufferPool.Put(r.buf) | ||
| } | ||
|
|
||
| func (r *Pickle) Body() ([]byte, error) { | ||
| buffer := bytes.NewBuffer(r.buf) | ||
| encoder := pickle.NewEncoder(buffer) | ||
| err := encoder.Encode(r.body) | ||
| return buffer.Bytes(), err | ||
| } | ||
|
|
||
| func (r *Pickle) Headers() (headers map[string]string) { | ||
| return map[string]string{"content-type": "application/pickle"} | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,138 @@ | ||
| package response | ||
|
|
||
| import ( | ||
| "math" | ||
| "testing" | ||
|
|
||
| "github.com/raintank/metrictank/api/models" | ||
| "gopkg.in/raintank/schema.v1" | ||
| ) | ||
|
|
||
| func BenchmarkHttpRespPickleEmptySeries(b *testing.B) { | ||
| data := []models.Series{ | ||
| { | ||
| Target: "an.empty.series", | ||
| Datapoints: make([]schema.Point, 0), | ||
| Interval: 10, | ||
| }, | ||
| } | ||
| var resp *Pickle | ||
| for n := 0; n < b.N; n++ { | ||
| resp = NewPickle(200, models.SeriesPickleFormat(data)) | ||
| resp.Body() | ||
| resp.Close() | ||
| } | ||
| } | ||
|
|
||
| func BenchmarkHttpRespPickleEmptySeriesNeedsEscaping(b *testing.B) { | ||
| data := []models.Series{ | ||
| { | ||
| Target: `an.empty\series`, | ||
| Datapoints: make([]schema.Point, 0), | ||
| Interval: 10, | ||
| }, | ||
| } | ||
| var resp *Pickle | ||
| for n := 0; n < b.N; n++ { | ||
| resp = NewPickle(200, models.SeriesPickleFormat(data)) | ||
| resp.Body() | ||
| resp.Close() | ||
| } | ||
| } | ||
|
|
||
| func BenchmarkHttpRespPickleIntegers(b *testing.B) { | ||
| points := make([]schema.Point, 1000, 1000) | ||
| baseTs := 1500000000 | ||
| for i := 0; i < 1000; i++ { | ||
| points[i] = schema.Point{Val: float64(10000 * i), Ts: uint32(baseTs + 10*i)} | ||
| } | ||
| data := []models.Series{ | ||
| { | ||
| Target: "some.metric.with.a-whole-bunch-of.integers", | ||
| Datapoints: points, | ||
| Interval: 10, | ||
| }, | ||
| } | ||
| b.SetBytes(int64(len(points) * 12)) | ||
|
|
||
| b.ResetTimer() | ||
| var resp *Pickle | ||
| for n := 0; n < b.N; n++ { | ||
| resp = NewPickle(200, models.SeriesPickleFormat(data)) | ||
| resp.Body() | ||
| resp.Close() | ||
| } | ||
| } | ||
|
|
||
| func BenchmarkHttpRespPickleFloats(b *testing.B) { | ||
| points := make([]schema.Point, 1000, 1000) | ||
| baseTs := 1500000000 | ||
| for i := 0; i < 1000; i++ { | ||
| points[i] = schema.Point{Val: 12.34 * float64(i), Ts: uint32(baseTs + 10*i)} | ||
| } | ||
| data := []models.Series{ | ||
| { | ||
| Target: "some.metric.with.a-whole-bunch-of.floats", | ||
| Datapoints: points, | ||
| Interval: 10, | ||
| }, | ||
| } | ||
| b.SetBytes(int64(len(points) * 12)) | ||
|
|
||
| b.ResetTimer() | ||
| var resp *Pickle | ||
| for n := 0; n < b.N; n++ { | ||
| resp = NewPickle(200, models.SeriesPickleFormat(data)) | ||
| resp.Body() | ||
| resp.Close() | ||
| } | ||
| } | ||
|
|
||
| func BenchmarkHttpRespPickleNulls(b *testing.B) { | ||
| points := make([]schema.Point, 1000, 1000) | ||
| baseTs := 1500000000 | ||
| for i := 0; i < 1000; i++ { | ||
| points[i] = schema.Point{Val: math.NaN(), Ts: uint32(baseTs + 10*i)} | ||
| } | ||
| data := []models.Series{ | ||
| { | ||
| Target: "some.metric.with.a-whole-bunch-of.nulls", | ||
| Datapoints: points, | ||
| Interval: 10, | ||
| }, | ||
| } | ||
| b.SetBytes(int64(len(points) * 12)) | ||
|
|
||
| b.ResetTimer() | ||
| var resp *Pickle | ||
| for n := 0; n < b.N; n++ { | ||
| resp = NewPickle(200, models.SeriesPickleFormat(data)) | ||
| resp.Body() | ||
| resp.Close() | ||
| } | ||
| } | ||
|
|
||
| var foo []models.SeriesForPickle | ||
|
|
||
| func BenchmarkConvertSeriesToPickleFormat10k(b *testing.B) { | ||
| points := make([]schema.Point, 10000) | ||
| baseTs := 1500000000 | ||
| for i := 0; i < 10000; i++ { | ||
| points[i] = schema.Point{Val: 1.2345 * float64(i), Ts: uint32(baseTs + 10*i)} | ||
| } | ||
| data := []models.Series{ | ||
| { | ||
| Target: "foo", | ||
| Datapoints: points, | ||
| Interval: 10, | ||
| }, | ||
| } | ||
| b.SetBytes(int64(len(points) * 12)) | ||
|
|
||
| b.ResetTimer() | ||
| var bar []models.SeriesForPickle | ||
| for n := 0; n < b.N; n++ { | ||
| bar = models.SeriesPickleFormat(data) | ||
| } | ||
| foo = bar | ||
| } | ||
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i'm curious what the cost of
models.SeriesPickleFormatitself is, that would be very interesting to also have as a separate benchmark.There was a problem hiding this comment.
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i added the benchmark.