diff options
Diffstat (limited to 'Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go')
-rw-r--r-- | Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go | 363 |
1 files changed, 0 insertions, 363 deletions
diff --git a/Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go b/Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go deleted file mode 100644 index d60e99c5b..000000000 --- a/Godeps/_workspace/src/github.com/rcrowley/go-metrics/sample_test.go +++ /dev/null @@ -1,363 +0,0 @@ -package metrics - -import ( - "math/rand" - "runtime" - "testing" - "time" -) - -// Benchmark{Compute,Copy}{1000,1000000} demonstrate that, even for relatively -// expensive computations like Variance, the cost of copying the Sample, as -// approximated by a make and copy, is much greater than the cost of the -// computation for small samples and only slightly less for large samples. -func BenchmarkCompute1000(b *testing.B) { - s := make([]int64, 1000) - for i := 0; i < len(s); i++ { - s[i] = int64(i) - } - b.ResetTimer() - for i := 0; i < b.N; i++ { - SampleVariance(s) - } -} -func BenchmarkCompute1000000(b *testing.B) { - s := make([]int64, 1000000) - for i := 0; i < len(s); i++ { - s[i] = int64(i) - } - b.ResetTimer() - for i := 0; i < b.N; i++ { - SampleVariance(s) - } -} -func BenchmarkCopy1000(b *testing.B) { - s := make([]int64, 1000) - for i := 0; i < len(s); i++ { - s[i] = int64(i) - } - b.ResetTimer() - for i := 0; i < b.N; i++ { - sCopy := make([]int64, len(s)) - copy(sCopy, s) - } -} -func BenchmarkCopy1000000(b *testing.B) { - s := make([]int64, 1000000) - for i := 0; i < len(s); i++ { - s[i] = int64(i) - } - b.ResetTimer() - for i := 0; i < b.N; i++ { - sCopy := make([]int64, len(s)) - copy(sCopy, s) - } -} - -func BenchmarkExpDecaySample257(b *testing.B) { - benchmarkSample(b, NewExpDecaySample(257, 0.015)) -} - -func BenchmarkExpDecaySample514(b *testing.B) { - benchmarkSample(b, NewExpDecaySample(514, 0.015)) -} - -func BenchmarkExpDecaySample1028(b *testing.B) { - benchmarkSample(b, NewExpDecaySample(1028, 0.015)) -} - -func BenchmarkUniformSample257(b *testing.B) { - benchmarkSample(b, NewUniformSample(257)) -} - -func BenchmarkUniformSample514(b *testing.B) { - benchmarkSample(b, NewUniformSample(514)) -} - -func BenchmarkUniformSample1028(b *testing.B) { - benchmarkSample(b, NewUniformSample(1028)) -} - -func TestExpDecaySample10(t *testing.T) { - rand.Seed(1) - s := NewExpDecaySample(100, 0.99) - for i := 0; i < 10; i++ { - s.Update(int64(i)) - } - if size := s.Count(); 10 != size { - t.Errorf("s.Count(): 10 != %v\n", size) - } - if size := s.Size(); 10 != size { - t.Errorf("s.Size(): 10 != %v\n", size) - } - if l := len(s.Values()); 10 != l { - t.Errorf("len(s.Values()): 10 != %v\n", l) - } - for _, v := range s.Values() { - if v > 10 || v < 0 { - t.Errorf("out of range [0, 10): %v\n", v) - } - } -} - -func TestExpDecaySample100(t *testing.T) { - rand.Seed(1) - s := NewExpDecaySample(1000, 0.01) - for i := 0; i < 100; i++ { - s.Update(int64(i)) - } - if size := s.Count(); 100 != size { - t.Errorf("s.Count(): 100 != %v\n", size) - } - if size := s.Size(); 100 != size { - t.Errorf("s.Size(): 100 != %v\n", size) - } - if l := len(s.Values()); 100 != l { - t.Errorf("len(s.Values()): 100 != %v\n", l) - } - for _, v := range s.Values() { - if v > 100 || v < 0 { - t.Errorf("out of range [0, 100): %v\n", v) - } - } -} - -func TestExpDecaySample1000(t *testing.T) { - rand.Seed(1) - s := NewExpDecaySample(100, 0.99) - for i := 0; i < 1000; i++ { - s.Update(int64(i)) - } - if size := s.Count(); 1000 != size { - t.Errorf("s.Count(): 1000 != %v\n", size) - } - if size := s.Size(); 100 != size { - t.Errorf("s.Size(): 100 != %v\n", size) - } - if l := len(s.Values()); 100 != l { - t.Errorf("len(s.Values()): 100 != %v\n", l) - } - for _, v := range s.Values() { - if v > 1000 || v < 0 { - t.Errorf("out of range [0, 1000): %v\n", v) - } - } -} - -// This test makes sure that the sample's priority is not amplified by using -// nanosecond duration since start rather than second duration since start. -// The priority becomes +Inf quickly after starting if this is done, -// effectively freezing the set of samples until a rescale step happens. -func TestExpDecaySampleNanosecondRegression(t *testing.T) { - rand.Seed(1) - s := NewExpDecaySample(100, 0.99) - for i := 0; i < 100; i++ { - s.Update(10) - } - time.Sleep(1 * time.Millisecond) - for i := 0; i < 100; i++ { - s.Update(20) - } - v := s.Values() - avg := float64(0) - for i := 0; i < len(v); i++ { - avg += float64(v[i]) - } - avg /= float64(len(v)) - if avg > 16 || avg < 14 { - t.Errorf("out of range [14, 16]: %v\n", avg) - } -} - -func TestExpDecaySampleRescale(t *testing.T) { - s := NewExpDecaySample(2, 0.001).(*ExpDecaySample) - s.update(time.Now(), 1) - s.update(time.Now().Add(time.Hour+time.Microsecond), 1) - for _, v := range s.values.Values() { - if v.k == 0.0 { - t.Fatal("v.k == 0.0") - } - } -} - -func TestExpDecaySampleSnapshot(t *testing.T) { - now := time.Now() - rand.Seed(1) - s := NewExpDecaySample(100, 0.99) - for i := 1; i <= 10000; i++ { - s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i)) - } - snapshot := s.Snapshot() - s.Update(1) - testExpDecaySampleStatistics(t, snapshot) -} - -func TestExpDecaySampleStatistics(t *testing.T) { - now := time.Now() - rand.Seed(1) - s := NewExpDecaySample(100, 0.99) - for i := 1; i <= 10000; i++ { - s.(*ExpDecaySample).update(now.Add(time.Duration(i)), int64(i)) - } - testExpDecaySampleStatistics(t, s) -} - -func TestUniformSample(t *testing.T) { - rand.Seed(1) - s := NewUniformSample(100) - for i := 0; i < 1000; i++ { - s.Update(int64(i)) - } - if size := s.Count(); 1000 != size { - t.Errorf("s.Count(): 1000 != %v\n", size) - } - if size := s.Size(); 100 != size { - t.Errorf("s.Size(): 100 != %v\n", size) - } - if l := len(s.Values()); 100 != l { - t.Errorf("len(s.Values()): 100 != %v\n", l) - } - for _, v := range s.Values() { - if v > 1000 || v < 0 { - t.Errorf("out of range [0, 100): %v\n", v) - } - } -} - -func TestUniformSampleIncludesTail(t *testing.T) { - rand.Seed(1) - s := NewUniformSample(100) - max := 100 - for i := 0; i < max; i++ { - s.Update(int64(i)) - } - v := s.Values() - sum := 0 - exp := (max - 1) * max / 2 - for i := 0; i < len(v); i++ { - sum += int(v[i]) - } - if exp != sum { - t.Errorf("sum: %v != %v\n", exp, sum) - } -} - -func TestUniformSampleSnapshot(t *testing.T) { - s := NewUniformSample(100) - for i := 1; i <= 10000; i++ { - s.Update(int64(i)) - } - snapshot := s.Snapshot() - s.Update(1) - testUniformSampleStatistics(t, snapshot) -} - -func TestUniformSampleStatistics(t *testing.T) { - rand.Seed(1) - s := NewUniformSample(100) - for i := 1; i <= 10000; i++ { - s.Update(int64(i)) - } - testUniformSampleStatistics(t, s) -} - -func benchmarkSample(b *testing.B, s Sample) { - var memStats runtime.MemStats - runtime.ReadMemStats(&memStats) - pauseTotalNs := memStats.PauseTotalNs - b.ResetTimer() - for i := 0; i < b.N; i++ { - s.Update(1) - } - b.StopTimer() - runtime.GC() - runtime.ReadMemStats(&memStats) - b.Logf("GC cost: %d ns/op", int(memStats.PauseTotalNs-pauseTotalNs)/b.N) -} - -func testExpDecaySampleStatistics(t *testing.T, s Sample) { - if count := s.Count(); 10000 != count { - t.Errorf("s.Count(): 10000 != %v\n", count) - } - if min := s.Min(); 107 != min { - t.Errorf("s.Min(): 107 != %v\n", min) - } - if max := s.Max(); 10000 != max { - t.Errorf("s.Max(): 10000 != %v\n", max) - } - if mean := s.Mean(); 4965.98 != mean { - t.Errorf("s.Mean(): 4965.98 != %v\n", mean) - } - if stdDev := s.StdDev(); 2959.825156930727 != stdDev { - t.Errorf("s.StdDev(): 2959.825156930727 != %v\n", stdDev) - } - ps := s.Percentiles([]float64{0.5, 0.75, 0.99}) - if 4615 != ps[0] { - t.Errorf("median: 4615 != %v\n", ps[0]) - } - if 7672 != ps[1] { - t.Errorf("75th percentile: 7672 != %v\n", ps[1]) - } - if 9998.99 != ps[2] { - t.Errorf("99th percentile: 9998.99 != %v\n", ps[2]) - } -} - -func testUniformSampleStatistics(t *testing.T, s Sample) { - if count := s.Count(); 10000 != count { - t.Errorf("s.Count(): 10000 != %v\n", count) - } - if min := s.Min(); 37 != min { - t.Errorf("s.Min(): 37 != %v\n", min) - } - if max := s.Max(); 9989 != max { - t.Errorf("s.Max(): 9989 != %v\n", max) - } - if mean := s.Mean(); 4748.14 != mean { - t.Errorf("s.Mean(): 4748.14 != %v\n", mean) - } - if stdDev := s.StdDev(); 2826.684117548333 != stdDev { - t.Errorf("s.StdDev(): 2826.684117548333 != %v\n", stdDev) - } - ps := s.Percentiles([]float64{0.5, 0.75, 0.99}) - if 4599 != ps[0] { - t.Errorf("median: 4599 != %v\n", ps[0]) - } - if 7380.5 != ps[1] { - t.Errorf("75th percentile: 7380.5 != %v\n", ps[1]) - } - if 9986.429999999998 != ps[2] { - t.Errorf("99th percentile: 9986.429999999998 != %v\n", ps[2]) - } -} - -// TestUniformSampleConcurrentUpdateCount would expose data race problems with -// concurrent Update and Count calls on Sample when test is called with -race -// argument -func TestUniformSampleConcurrentUpdateCount(t *testing.T) { - if testing.Short() { - t.Skip("skipping in short mode") - } - s := NewUniformSample(100) - for i := 0; i < 100; i++ { - s.Update(int64(i)) - } - quit := make(chan struct{}) - go func() { - t := time.NewTicker(10 * time.Millisecond) - for { - select { - case <-t.C: - s.Update(rand.Int63()) - case <-quit: - t.Stop() - return - } - } - }() - for i := 0; i < 1000; i++ { - s.Count() - time.Sleep(5 * time.Millisecond) - } - quit <- struct{}{} -} |