public void CanReadv1Logs_Skip_PreStart(string logPath, int skip, int take,
int expectedHistogramCount, int expectedCombinedValueCount,
int expectedCombined999, long expectedCombinedMaxLength,
double expectedStartTime)
{
var readerStream = GetEmbeddedFileStream(logPath);
var reader = new HistogramLogReader(readerStream);
int histogramCount = 0;
long totalCount = 0;
HistogramBase accumulatedHistogram = Create(OneHourOfNanoseconds, DefaultSignificantDigits);
var histograms = reader.ReadHistograms()
.Where(h => h.StartTimeStamp >= reader.GetStartTime().MillisecondsSinceUnixEpoch())
.Skip(skip)
.Take(take);
foreach (var histogram in histograms)
{
histogramCount++;
totalCount += histogram.TotalCount;
accumulatedHistogram.Add(histogram);
}
Assert.Equal(expectedHistogramCount, histogramCount);
Assert.Equal(expectedCombinedValueCount, totalCount);
Assert.Equal(expectedCombined999, accumulatedHistogram.GetValueAtPercentile(99.9));
Assert.Equal(expectedCombinedMaxLength, accumulatedHistogram.GetMaxValue());
Assert.Equal(expectedStartTime, reader.GetStartTime().SecondsSinceUnixEpoch());
}
static void Main(string[] args)
{
List <Thread> threadList = new List <Thread>();
for (int i = 0; i < threadCount; i++)
{
Thread t = new Thread(WorkerJob);
t.Start();
threadList.Add(t);
}
foreach (Thread t in threadList)
{
t.Join();
}
Console.WriteLine("Total operations: " + throughput);
double[] percentiles = new double[] { 50, 90, 95, 99, 99.9, 99.99, 100 };
foreach (double percentile in percentiles)
{
Console.WriteLine($"{percentile} : {histogram.GetValueAtPercentile(percentile)}");
}
Console.WriteLine("Results:");
// Write the results to console
histogram.OutputPercentileDistribution(
Console.Out,
percentileTicksPerHalfDistance: 3,
outputValueUnitScalingRatio: OutputScalingFactor.TimeStampToMilliseconds);
// Save the results to a file
using (StreamWriter writer = new StreamWriter("HistogramResults.hgrm"))
{
histogram.OutputPercentileDistribution(
writer,
percentileTicksPerHalfDistance: 3,
outputValueUnitScalingRatio: OutputScalingFactor.TimeStampToMilliseconds);
}
Console.WriteLine();
Console.WriteLine("These results have been saved to HistogramResults.hgrm");
}
public void TestScalingEquivalence()
{
Assert.AreEqual(
LongHistogram.GetMean() * 512,
ScaledHistogram.GetMean(), ScaledHistogram.GetMean() * 0.000001,
"averages should be equivalent");
Assert.AreEqual(
LongHistogram.TotalCount,
ScaledHistogram.TotalCount,
"total count should be the same");
Assert.AreEqual(
LongHistogram.LowestEquivalentValue(LongHistogram.GetValueAtPercentile(99.0)) * 512,
ScaledHistogram.LowestEquivalentValue(ScaledHistogram.GetValueAtPercentile(99.0)),
"99%'iles should be equivalent");
Assert.AreEqual(
ScaledHistogram.HighestEquivalentValue(LongHistogram.GetMaxValue() * 512),
ScaledHistogram.GetMaxValue(),
"Max should be equivalent for scaled data");
// Same for post-corrected:
Assert.AreEqual(
LongHistogram.GetMean() * 512,
ScaledHistogram.GetMean(), ScaledHistogram.GetMean() * 0.000001,
"averages should be equivalent");
Assert.AreEqual(
PostCorrectedHistogram.TotalCount,
PostCorrectedScaledHistogram.TotalCount,
"total count should be the same");
Assert.AreEqual(
PostCorrectedHistogram.LowestEquivalentValue(PostCorrectedHistogram.GetValueAtPercentile(99.0)) * 512,
PostCorrectedScaledHistogram.LowestEquivalentValue(PostCorrectedScaledHistogram.GetValueAtPercentile(99.0)),
"99%'iles should be equivalent");
Assert.AreEqual(
PostCorrectedScaledHistogram.HighestEquivalentValue(PostCorrectedHistogram.GetMaxValue() * 512),
PostCorrectedScaledHistogram.GetMaxValue(),
"Max should be equivalent for post-corrected data");
}
/// <inheritdoc cref="IReservoirSnapshot" />
public double GetValue(double quantile)
{
return(_histogram.GetValueAtPercentile(quantile * 100));
}
public long GetValueAtPercentile(double percentile)
{
return(_hdrHistogram.GetValueAtPercentile(percentile));
}