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
.
Autoresizing: When constructed with no specified value range range (or when autoresize is turned on with AbstractHistogram.setAutoResize(boolean)
) a Histogram
will autoresize its dynamic range to include recorded values as
they are encountered. Note that recording calls that cause autoresizing 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 

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)

Histogram(int numberOfSignificantValueDigits)
Construct an autoresizing histogram with a lowest discernible value of 1 and an autoadjusting
highestTrackableValue.

Histogram(long highestTrackableValue,
int numberOfSignificantValueDigits)
Construct a Histogram given the Highest value to be tracked and a number of significant decimal digits.

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.

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.

static Histogram 
decodeFromByteBuffer(ByteBuffer buffer,
long minBarForHighestTrackableValue)
Construct a new histogram by decoding it from a ByteBuffer.

static Histogram 
decodeFromCompressedByteBuffer(ByteBuffer buffer,
long minBarForHighestTrackableValue)
Construct a new histogram by decoding it from a compressed form in a ByteBuffer.

long 
getTotalCount()
Get the total count of all recorded values in the histogram

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, valuesAreEquivalent
public 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 nonnegative 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 nonnegative 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 nonnegative integer between 0 and 5.public Histogram(AbstractHistogram source)
source
 The source histogram to duplicatepublic Histogram copy()
AbstractHistogram
copy
in class AbstractHistogram
public 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 autogenerated additional series of
decreasinglysmaller (down to the expectedIntervalBetweenValueSamples) value records for each count found
in the current histogram that is larger than the expectedIntervalBetweenValueSamples.
Note: This is a postcorrection method, as opposed to the atrecording 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 AbstractHistogram
expectedIntervalBetweenValueSamples
 If expectedIntervalBetweenValueSamples is larger than 0, add
autogenerated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplespublic long getTotalCount()
AbstractHistogram
getTotalCount
in class AbstractHistogram
public 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.