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package kamon.metric
import kamon.Kamon
import org.scalatest.{Matchers, WordSpec}
import MeasurementUnit._
class HistogramSpec extends WordSpec with Matchers {
import HistogramTestHelper.HistogramMetricSyntax
"a Histogram" should {
"record values and reset internal state when a snapshot is taken" in {
val histogram = Kamon.histogram("test", unit = time.nanoseconds)
histogram.record(100)
histogram.record(150, 998)
histogram.record(200)
val distribution = histogram.distribution()
distribution.min shouldBe(100)
distribution.max shouldBe(200)
distribution.count shouldBe(1000)
distribution.buckets.length shouldBe 3
distribution.buckets.map(b => (b.value, b.frequency)) should contain.allOf(
(100 -> 1),
(150 -> 998),
(200 -> 1)
)
val emptyDistribution = histogram.distribution()
emptyDistribution.min shouldBe(0)
emptyDistribution.max shouldBe(0)
emptyDistribution.count shouldBe(0)
emptyDistribution.buckets.length shouldBe 0
}
"accept a smallest discernible value configuration" in {
// The lowestDiscernibleValue gets rounded down to the closest power of 2, so, here it will be 64.
val histogram = Kamon.histogram("test-lowest-discernible-value", unit = time.nanoseconds, dynamicRange = DynamicRange.Fine.withLowestDiscernibleValue(100))
histogram.record(100)
histogram.record(200)
histogram.record(300)
histogram.record(1000)
histogram.record(2000)
histogram.record(3000)
val distribution = histogram.distribution()
distribution.min shouldBe(64)
distribution.max shouldBe(2944)
distribution.count shouldBe(6)
distribution.buckets.length shouldBe 6
distribution.buckets.map(b => (b.value, b.frequency)) should contain.allOf(
(64 -> 1),
(192 -> 1),
(256 -> 1),
(960 -> 1),
(1984 -> 1),
(2944 -> 1)
)
}
"[private api] record values and optionally keep the internal state when a snapshot is taken" in {
val histogram = Kamon.histogram("test", unit = time.nanoseconds)
histogram.record(100)
histogram.record(150, 998)
histogram.record(200)
val distribution = {
histogram.distribution(resetState = false) // first one gets discarded
histogram.distribution(resetState = false)
}
distribution.min shouldBe(100)
distribution.max shouldBe(200)
distribution.count shouldBe(1000)
distribution.buckets.length shouldBe 3
distribution.buckets.map(b => (b.value, b.frequency)) should contain.allOf(
(100 -> 1),
(150 -> 998),
(200 -> 1)
)
}
}
}
object HistogramTestHelper {
implicit class HistogramMetricSyntax(metric: HistogramMetric) {
def distribution(resetState: Boolean = true): Distribution =
metric.refine(Map.empty[String, String]) match {
case h: AtomicHdrHistogram => h.snapshot(resetState).distribution
case h: HdrHistogram => h.snapshot(resetState).distribution
}
}
}
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