public class Histogram extends AbstractHistogram
Histogram supports the recording and analyzing sampled data value counts across a configurable integer value
range with configurable value precision within the range. Value precision is expressed as the number of significant
digits in the value recording, and provides control over value quantization behavior across the value range and the
subsequent value resolution at any given level.
For example, a Histogram could be configured to track the counts of observed integer values between 0 and 3,600,000,000 while maintaining a value precision of 3 significant digits across that range. Value quantization within the range will thus be no larger than 1/1,000th (or 0.1%) of any value. This example Histogram could be used to track and analyze the counts of observed response times ranging between 1 microsecond and 1 hour in magnitude, while maintaining a value resolution of 1 microsecond up to 1 millisecond, a resolution of 1 millisecond (or better) up to one second, and a resolution of 1 second (or better) up to 1,000 seconds. At its maximum tracked value (1 hour), it would still maintain a resolution of 3.6 seconds (or better).
Histogram tracks value counts in long fields. Smaller field types are available in the
IntCountsHistogram and ShortCountsHistogram implementations of
AbstractHistogram.
Auto-resizing: When constructed with no specified value range range (or when auto-resize is turned on with AbstractHistogram.setAutoResize(boolean)) a Histogram will auto-resize its dynamic range to include recorded values as
they are encountered. Note that recording calls that cause auto-resizing may take longer to execute, as resizing
incurs allocation and copying of internal data structures.
See package description for org.HdrHistogram for details.
AbstractHistogram.AllValues, AbstractHistogram.LinearBucketValues, AbstractHistogram.LogarithmicBucketValues, AbstractHistogram.Percentiles, AbstractHistogram.RecordedValues| Constructor and Description |
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Histogram(AbstractHistogram source)
Construct a histogram with the same range settings as a given source histogram,
duplicating the source's start/end timestamps (but NOT its contents)
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Histogram(int numberOfSignificantValueDigits)
Construct an auto-resizing histogram with a lowest discernible value of 1 and an auto-adjusting
highestTrackableValue.
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Histogram(long highestTrackableValue,
int numberOfSignificantValueDigits)
Construct a Histogram given the Highest value to be tracked and a number of significant decimal digits.
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Histogram(long lowestDiscernibleValue,
long highestTrackableValue,
int numberOfSignificantValueDigits)
Construct a Histogram given the Lowest and Highest values to be tracked and a number of significant
decimal digits.
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| Modifier and Type | Method and Description |
|---|---|
Histogram |
copy()
Create a copy of this histogram, complete with data and everything.
|
Histogram |
copyCorrectedForCoordinatedOmission(long expectedIntervalBetweenValueSamples)
Get a copy of this histogram, corrected for coordinated omission.
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static Histogram |
decodeFromByteBuffer(ByteBuffer buffer,
long minBarForHighestTrackableValue)
Construct a new histogram by decoding it from a ByteBuffer.
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static Histogram |
decodeFromCompressedByteBuffer(ByteBuffer buffer,
long minBarForHighestTrackableValue)
Construct a new histogram by decoding it from a compressed form in a ByteBuffer.
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long |
getTotalCount()
Get the total count of all recorded values in the histogram
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add, addWhileCorrectingForCoordinatedOmission, allValues, copyInto, copyIntoCorrectedForCoordinatedOmission, encodeIntoByteBuffer, encodeIntoCompressedByteBuffer, encodeIntoCompressedByteBuffer, equals, getCountAtValue, getCountBetweenValues, getEndTimeStamp, getEstimatedFootprintInBytes, getHighestTrackableValue, getLowestDiscernibleValue, getMaxValue, getMaxValueAsDouble, getMean, getMinNonZeroValue, getMinValue, getNeededByteBufferCapacity, getNumberOfSignificantValueDigits, getPercentileAtOrBelowValue, getStartTimeStamp, getStdDeviation, getTag, getValueAtPercentile, hashCode, highestEquivalentValue, isAutoResize, linearBucketValues, logarithmicBucketValues, lowestEquivalentValue, medianEquivalentValue, nextNonEquivalentValue, outputPercentileDistribution, outputPercentileDistribution, outputPercentileDistribution, percentiles, recordedValues, recordValue, recordValue, recordValueWithCount, recordValueWithExpectedInterval, reset, setAutoResize, setEndTimeStamp, setStartTimeStamp, setTag, shiftValuesLeft, shiftValuesRight, sizeOfEquivalentValueRange, subtract, valuesAreEquivalentpublic Histogram(int numberOfSignificantValueDigits)
numberOfSignificantValueDigits - Specifies the precision to use. This is the number of significant
decimal digits to which the histogram will maintain value resolution
and separation. Must be a non-negative integer between 0 and 5.public Histogram(long highestTrackableValue,
int numberOfSignificantValueDigits)
highestTrackableValue - The highest value to be tracked by the histogram. Must be a positive
integer that is >= 2.numberOfSignificantValueDigits - Specifies the precision to use. This is the number of significant
decimal digits to which the histogram will maintain value resolution
and separation. Must be a non-negative integer between 0 and 5.public Histogram(long lowestDiscernibleValue,
long highestTrackableValue,
int numberOfSignificantValueDigits)
lowestDiscernibleValue - The lowest value that can be discerned (distinguished from 0) by the
histogram. Must be a positive integer that is >= 1. May be
internally rounded down to nearest power of 2.highestTrackableValue - The highest value to be tracked by the histogram. Must be a positive
integer that is >= (2 * lowestDiscernibleValue).numberOfSignificantValueDigits - Specifies the precision to use. This is the number of significant
decimal digits to which the histogram will maintain value resolution
and separation. Must be a non-negative integer between 0 and 5.public Histogram(AbstractHistogram source)
source - The source histogram to duplicatepublic Histogram copy()
AbstractHistogramcopy in class AbstractHistogrampublic Histogram copyCorrectedForCoordinatedOmission(long expectedIntervalBetweenValueSamples)
AbstractHistogram
To compensate for the loss of sampled values when a recorded value is larger than the expected
interval between value samples, the new histogram will include an auto-generated additional series of
decreasingly-smaller (down to the expectedIntervalBetweenValueSamples) value records for each count found
in the current histogram that is larger than the expectedIntervalBetweenValueSamples.
Note: This is a post-correction method, as opposed to the at-recording correction method provided
by recordValueWithExpectedInterval. The two
methods are mutually exclusive, and only one of the two should be be used on a given data set to correct
for the same coordinated omission issue.
by
See notes in the description of the Histogram calls for an illustration of why this corrective behavior is important.
copyCorrectedForCoordinatedOmission in class AbstractHistogramexpectedIntervalBetweenValueSamples - If expectedIntervalBetweenValueSamples is larger than 0, add
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplespublic long getTotalCount()
AbstractHistogramgetTotalCount in class AbstractHistogrampublic static Histogram decodeFromByteBuffer(ByteBuffer buffer, long minBarForHighestTrackableValue)
buffer - The buffer to decode fromminBarForHighestTrackableValue - Force highestTrackableValue to be set at least this highpublic static Histogram decodeFromCompressedByteBuffer(ByteBuffer buffer, long minBarForHighestTrackableValue) throws DataFormatException
buffer - The buffer to decode fromminBarForHighestTrackableValue - Force highestTrackableValue to be set at least this highDataFormatException - on error parsing/decompressing the bufferCopyright © 2016. All rights reserved.