private void WriteHistogram(HistogramBase histogram)
{
var targetBuffer = ByteBuffer.Allocate(histogram.GetNeededByteBufferCapacity());
var compressedLength = histogram.EncodeIntoCompressedByteBuffer(targetBuffer);
byte[] compressedArray = new byte[compressedLength];
targetBuffer.BlockGet(compressedArray, 0, 0, compressedLength);
var startTimeStampSec = histogram.StartTimeStamp / 1000.0;
var endTimeStampSec = histogram.EndTimeStamp / 1000.0;
var intervalLength = endTimeStampSec - startTimeStampSec;
var maxValueUnitRatio = 1000000.0;
var intervalMax = histogram.GetMaxValue() / maxValueUnitRatio;
var binary = Convert.ToBase64String(compressedArray);
var payload = $"{startTimeStampSec:F3},{intervalLength:F3},{intervalMax:F3},{binary}";
_log.WriteLine(payload);
_log.Flush();
}
private void WriteHistogram(HistogramBase histogram)
{
var targetBuffer = ByteBuffer.Allocate(histogram.GetNeededByteBufferCapacity());
var compressedLength = histogram.EncodeIntoCompressedByteBuffer(targetBuffer);
byte[] compressedArray = new byte[compressedLength];
targetBuffer.BlockGet(compressedArray, 0, 0, compressedLength);
var startTimeStampSec = histogram.StartTimeStamp / 1000.0;
var endTimeStampSec = histogram.EndTimeStamp / 1000.0;
var intervalLength = endTimeStampSec - startTimeStampSec;
var maxValueUnitRatio = 1000000.0;
var intervalMax = histogram.GetMaxValue() / maxValueUnitRatio;
var binary = Convert.ToBase64String(compressedArray);
var payload = $"{startTimeStampSec:F3},{intervalLength:F3},{intervalMax:F3},{binary}";
_log.WriteLine(payload);
_log.Flush();
}
/// <summary>
/// Produce textual representation of the value distribution of histogram data by percentile.
/// The distribution is output with exponentially increasing resolution, with each exponentially decreasing
/// half-distance containing <paramref name="percentileTicksPerHalfDistance"/> percentile reporting tick points.
/// </summary>
/// <param name="histogram">The histogram to operate on</param>
/// <param name="printStream">Stream into which the distribution will be output</param>
/// <param name="percentileTicksPerHalfDistance">
/// The number of reporting points per exponentially decreasing half-distance
/// </param>
/// <param name="outputValueUnitScalingRatio">
/// The scaling factor by which to divide histogram recorded values units in output.
/// Use the <see cref="OutputScalingFactor"/> constant values to help choose an appropriate output measurement.
/// </param>
/// <param name="useCsvFormat">Output in CSV (Comma Separated Values) format if <c>true</c>, else use plain text form.</param>
public static void OutputPercentileDistribution(this HistogramBase histogram,
TextWriter printStream,
int percentileTicksPerHalfDistance = 5,
double outputValueUnitScalingRatio = OutputScalingFactor.TicksToMilliseconds,
bool useCsvFormat = false)
{
if (useCsvFormat)
{
printStream.Write("\"Value\",\"Percentile\",\"TotalCount\",\"1/(1-Percentile)\"\n");
}
else
{
printStream.Write("{0,12} {1,14} {2,10} {3,14}\n\n", "Value", "Percentile", "TotalCount", "1/(1-Percentile)");
}
string percentileFormatString;
string lastLinePercentileFormatString;
if (useCsvFormat)
{
percentileFormatString = "{0:F" + histogram.NumberOfSignificantValueDigits + "},{1:F12},{2},{3:F2}\n";
lastLinePercentileFormatString = "{0:F" + histogram.NumberOfSignificantValueDigits + "},{1:F12},{2},Infinity\n";
}
else
{
percentileFormatString = "{0,12:F" + histogram.NumberOfSignificantValueDigits + "}" + " {1,2:F12} {2,10} {3,14:F2}\n";
lastLinePercentileFormatString = "{0,12:F" + histogram.NumberOfSignificantValueDigits + "} {1,2:F12} {2,10}\n";
}
try
{
foreach (var iterationValue in histogram.Percentiles(percentileTicksPerHalfDistance))
{
if (iterationValue.PercentileLevelIteratedTo != 100.0D)
{
printStream.Write(percentileFormatString,
iterationValue.ValueIteratedTo / outputValueUnitScalingRatio,
iterationValue.PercentileLevelIteratedTo / 100.0D,
iterationValue.TotalCountToThisValue,
1 / (1.0D - (iterationValue.PercentileLevelIteratedTo / 100.0D)));
}
else
{
printStream.Write(lastLinePercentileFormatString,
iterationValue.ValueIteratedTo / outputValueUnitScalingRatio,
iterationValue.PercentileLevelIteratedTo / 100.0D,
iterationValue.TotalCountToThisValue);
}
}
if (!useCsvFormat)
{
// Calculate and output mean and std. deviation.
// Note: mean/std. deviation numbers are very often completely irrelevant when
// data is extremely non-normal in distribution (e.g. in cases of strong multi-modal
// response time distribution associated with GC pauses). However, reporting these numbers
// can be very useful for contrasting with the detailed percentile distribution
// reported by outputPercentileDistribution(). It is not at all surprising to find
// percentile distributions where results fall many tens or even hundreds of standard
// deviations away from the mean - such results simply indicate that the data sampled
// exhibits a very non-normal distribution, highlighting situations for which the std.
// deviation metric is a useless indicator.
var mean = histogram.GetMean() / outputValueUnitScalingRatio;
var stdDeviation = histogram.GetStdDeviation() / outputValueUnitScalingRatio;
printStream.Write("#[Mean = {0,12:F" + histogram.NumberOfSignificantValueDigits + "}, " +
"StdDeviation = {1,12:F" + histogram.NumberOfSignificantValueDigits + "}]\n", mean, stdDeviation);
printStream.Write("#[Max = {0,12:F" + histogram.NumberOfSignificantValueDigits + "}, Total count = {1,12}]\n",
histogram.GetMaxValue() / outputValueUnitScalingRatio, histogram.TotalCount);
printStream.Write("#[Buckets = {0,12}, SubBuckets = {1,12}]\n",
histogram.BucketCount, histogram.SubBucketCount);
}
}
catch (ArgumentOutOfRangeException)
{
// Overflow conditions on histograms can lead to ArgumentOutOfRangeException on iterations:
if (histogram.HasOverflowed())
{
printStream.Write("# Histogram counts indicate OVERFLOW values");
}
else
{
// Re-throw if reason is not a known overflow:
throw;
}
}
}