Serializable
Histogram
, IntCountsHistogram
, ShortCountsHistogram
public abstract class AbstractHistogram extends EncodableHistogram implements Serializable
AbstractHistogram 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 it's maximum tracked value (1 hour), it would still maintain a resolution of 3.6 seconds (or better).
See package description for org.HdrHistogram
for details.
Modifier and Type  Class  Description 

class 
AbstractHistogram.AllValues 

class 
AbstractHistogram.LinearBucketValues 

class 
AbstractHistogram.LogarithmicBucketValues 

class 
AbstractHistogram.Percentiles 

class 
AbstractHistogram.RecordedValues 
Modifier  Constructor  Description 

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

protected 
AbstractHistogram(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.

protected 
AbstractHistogram(AbstractHistogram source) 
Construct a histogram with the same range settings as a given source histogram,
duplicating the source's start/end timestamps (but NOT it's contents)

Modifier and Type  Method  Description 

void 
add(AbstractHistogram otherHistogram) 
Add the contents of another histogram to this one.

void 
addWhileCorrectingForCoordinatedOmission(AbstractHistogram otherHistogram,
long expectedIntervalBetweenValueSamples) 
Add the contents of another histogram to this one, while correcting the incoming data for coordinated omission.

AbstractHistogram.AllValues 
allValues() 
Provide a means of iterating through all histogram values using the finest granularity steps supported by
the underlying representation.

abstract AbstractHistogram 
copy() 
Create a copy of this histogram, complete with data and everything.

abstract AbstractHistogram 
copyCorrectedForCoordinatedOmission(long expectedIntervalBetweenValueSamples) 
Get a copy of this histogram, corrected for coordinated omission.

void 
copyInto(AbstractHistogram targetHistogram) 
Copy this histogram into the target histogram, overwriting it's contents.

void 
copyIntoCorrectedForCoordinatedOmission(AbstractHistogram targetHistogram,
long expectedIntervalBetweenValueSamples) 
Copy this histogram, corrected for coordinated omission, into the target histogram, overwriting it's contents.

int 
encodeIntoByteBuffer(ByteBuffer buffer) 
Encode this histogram into a ByteBuffer

int 
encodeIntoCompressedByteBuffer(ByteBuffer targetBuffer) 
Encode this histogram in compressed form into a byte array

int 
encodeIntoCompressedByteBuffer(ByteBuffer targetBuffer,
int compressionLevel) 
Encode this histogram in compressed form into a byte array

boolean 
equals(Object other) 
Determine if this histogram is equivalent to another.

long 
getCountAtValue(long value) 
Get the count of recorded values at a specific value (to within the histogram resolution at the value level).

long 
getCountBetweenValues(long lowValue,
long highValue) 
Get the count of recorded values within a range of value levels (inclusive to within the histogram's resolution).

long 
getEndTimeStamp() 
get the end time stamp [optionally] stored with this histogram

int 
getEstimatedFootprintInBytes() 
Provide a (conservatively high) estimate of the Histogram's total footprint in bytes

long 
getHighestTrackableValue() 
get the configured highestTrackableValue

long 
getLowestDiscernibleValue() 
get the configured lowestDiscernibleValue

long 
getMaxValue() 
Get the highest recorded value level in the histogram.

double 
getMaxValueAsDouble() 
Get the highest recorded value level in the histogram as a double

double 
getMean() 
Get the computed mean value of all recorded values in the histogram

long 
getMinNonZeroValue() 
Get the lowest recorded nonzero value level in the histogram.

long 
getMinValue() 
Get the lowest recorded value level in the histogram.

int 
getNeededByteBufferCapacity() 
Get the capacity needed to encode this histogram into a ByteBuffer

int 
getNumberOfSignificantValueDigits() 
get the configured numberOfSignificantValueDigits

double 
getPercentileAtOrBelowValue(long value) 
Get the percentile at a given value.

long 
getStartTimeStamp() 
get the start time stamp [optionally] stored with this histogram

double 
getStdDeviation() 
Get the computed standard deviation of all recorded values in the histogram

String 
getTag() 
get the tag string [optionally] associated with this histogram

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

long 
getValueAtPercentile(double percentile) 
Get the value at a given percentile.

int 
hashCode() 

long 
highestEquivalentValue(long value) 
Get the highest value that is equivalent to the given value within the histogram's resolution.

boolean 
isAutoResize() 
Indicate whether or not the histogram is set to autoresize and autoadjust it's
highestTrackableValue

AbstractHistogram.LinearBucketValues 
linearBucketValues(long valueUnitsPerBucket) 
Provide a means of iterating through histogram values using linear steps.

AbstractHistogram.LogarithmicBucketValues 
logarithmicBucketValues(long valueUnitsInFirstBucket,
double logBase) 
Provide a means of iterating through histogram values at logarithmically increasing levels.

long 
lowestEquivalentValue(long value) 
Get the lowest value that is equivalent to the given value within the histogram's resolution.

long 
medianEquivalentValue(long value) 
Get a value that lies in the middle (rounded up) of the range of values equivalent the given value.

long 
nextNonEquivalentValue(long value) 
Get the next value that is not equivalent to the given value within the histogram's resolution.

void 
outputPercentileDistribution(PrintStream printStream,
int percentileTicksPerHalfDistance,
Double outputValueUnitScalingRatio) 
Produce textual representation of the value distribution of histogram data by percentile.

void 
outputPercentileDistribution(PrintStream printStream,
int percentileTicksPerHalfDistance,
Double outputValueUnitScalingRatio,
boolean useCsvFormat) 
Produce textual representation of the value distribution of histogram data by percentile.

void 
outputPercentileDistribution(PrintStream printStream,
Double outputValueUnitScalingRatio) 
Produce textual representation of the value distribution of histogram data by percentile.

AbstractHistogram.Percentiles 
percentiles(int percentileTicksPerHalfDistance) 
Provide a means of iterating through histogram values according to percentile levels.

void 
recordConvertedDoubleValueWithCount(double value,
long count) 

AbstractHistogram.RecordedValues 
recordedValues() 
Provide a means of iterating through all recorded histogram values using the finest granularity steps
supported by the underlying representation.

void 
recordValue(long value) 
Record a value in the histogram

void 
recordValue(long value,
long expectedIntervalBetweenValueSamples) 
Deprecated.
Record a value in the histogram. This deprecated method has identical behavior to
recordValueWithExpectedInterval() . It was renamed to avoid ambiguity. 
void 
recordValueWithCount(long value,
long count) 
Record a value in the histogram (adding to the value's current count)

void 
recordValueWithExpectedInterval(long value,
long expectedIntervalBetweenValueSamples) 
Record a value in the histogram.

void 
reset() 
Reset the contents and stats of this histogram

void 
setAutoResize(boolean autoResize) 
Control whether or not the histogram can autoresize and autoadjust it's
highestTrackableValue

void 
setEndTimeStamp(long timeStampMsec) 
Set the end time stamp value associated with this histogram to a given value.

void 
setStartTimeStamp(long timeStampMsec) 
Set the start time stamp value associated with this histogram to a given value.

void 
setTag(String tag) 
Set the tag string associated with this histogram

void 
shiftValuesLeft(int numberOfBinaryOrdersOfMagnitude) 
Shift recorded values to the left (the equivalent of a << shift operation on all recorded values).

void 
shiftValuesRight(int numberOfBinaryOrdersOfMagnitude) 
Shift recorded values to the right (the equivalent of a >> shift operation on all recorded values).

long 
sizeOfEquivalentValueRange(long value) 
Get the size (in value units) of the range of values that are equivalent to the given value within the
histogram's resolution.

void 
subtract(AbstractHistogram otherHistogram) 
Subtract the contents of another histogram from this one.

boolean 
supportsAutoResize() 
Indicate whether or not the histogram is capable of supporting autoresize functionality.

boolean 
valuesAreEquivalent(long value1,
long value2) 
Determine if two values are equivalent with the histogram's resolution.

protected AbstractHistogram(int numberOfSignificantValueDigits)
numberOfSignificantValueDigits
 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.protected AbstractHistogram(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
 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.protected AbstractHistogram(AbstractHistogram source)
source
 The source histogram to duplicatepublic abstract long getTotalCount()
public boolean isAutoResize()
public boolean supportsAutoResize()
public void setAutoResize(boolean autoResize)
autoResize
 autoResize settingpublic void recordValue(long value) throws ArrayIndexOutOfBoundsException
value
 The value to be recordedArrayIndexOutOfBoundsException
 (may throw) if value is exceeds highestTrackableValuepublic void recordValueWithCount(long value, long count) throws ArrayIndexOutOfBoundsException
value
 The value to be recordedcount
 The number of occurrences of this value to recordArrayIndexOutOfBoundsException
 (may throw) if value is exceeds highestTrackableValuepublic void recordValueWithExpectedInterval(long value, long expectedIntervalBetweenValueSamples) throws ArrayIndexOutOfBoundsException
To compensate for the loss of sampled values when a recorded value is larger than the expected interval between value samples, Histogram will autogenerate an additional series of decreasinglysmaller (down to the expectedIntervalBetweenValueSamples) value records.
Note: This is a atrecording correction method, as opposed to the postrecording correction method provided
by copyCorrectedForCoordinatedOmission(long)
.
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.
See notes in the description of the Histogram calls for an illustration of why this corrective behavior is important.
value
 The value to recordexpectedIntervalBetweenValueSamples
 If expectedIntervalBetweenValueSamples is larger than 0, add
autogenerated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplesArrayIndexOutOfBoundsException
 (may throw) if value is exceeds highestTrackableValuepublic void recordConvertedDoubleValueWithCount(double value, long count) throws ArrayIndexOutOfBoundsException
ArrayIndexOutOfBoundsException
public void recordValue(long value, long expectedIntervalBetweenValueSamples) throws ArrayIndexOutOfBoundsException
recordValueWithExpectedInterval()
. It was renamed to avoid ambiguity.value
 The value to recordexpectedIntervalBetweenValueSamples
 If expectedIntervalBetweenValueSamples is larger than 0, add
autogenerated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplesArrayIndexOutOfBoundsException
 (may throw) if value is exceeds highestTrackableValuepublic void reset()
public abstract AbstractHistogram copy()
public abstract AbstractHistogram copyCorrectedForCoordinatedOmission(long expectedIntervalBetweenValueSamples)
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.
expectedIntervalBetweenValueSamples
 If expectedIntervalBetweenValueSamples is larger than 0, add
autogenerated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplespublic void copyInto(AbstractHistogram targetHistogram)
targetHistogram
 the histogram to copy intopublic void copyIntoCorrectedForCoordinatedOmission(AbstractHistogram targetHistogram, long expectedIntervalBetweenValueSamples)
copyCorrectedForCoordinatedOmission(long)
for more detailed explanation about how correction is applied)targetHistogram
 the histogram to copy intoexpectedIntervalBetweenValueSamples
 If expectedIntervalBetweenValueSamples is larger than 0, add
autogenerated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplespublic void add(AbstractHistogram otherHistogram) throws ArrayIndexOutOfBoundsException
As part of adding the contents, the start/end timestamp range of this histogram will be extended to include the start/end timestamp range of the other histogram.
otherHistogram
 The other histogram.ArrayIndexOutOfBoundsException
 (may throw) if values in fromHistogram's are
higher than highestTrackableValue.public void subtract(AbstractHistogram otherHistogram) throws ArrayIndexOutOfBoundsException, IllegalArgumentException
The start/end timestamps of this histogram will remain unchanged.
otherHistogram
 The other histogram.ArrayIndexOutOfBoundsException
 (may throw) if values in otherHistogram's are higher than highestTrackableValue.IllegalArgumentException
public void addWhileCorrectingForCoordinatedOmission(AbstractHistogram otherHistogram, long expectedIntervalBetweenValueSamples)
To compensate for the loss of sampled values when a recorded value is larger than the expected
interval between value samples, the values added 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 postrecording correction 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.
otherHistogram
 The other histogram. highestTrackableValue and largestValueWithSingleUnitResolution must match.expectedIntervalBetweenValueSamples
 If expectedIntervalBetweenValueSamples is larger than 0, add
autogenerated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplesArrayIndexOutOfBoundsException
 (may throw) if values exceed highestTrackableValuepublic void shiftValuesLeft(int numberOfBinaryOrdersOfMagnitude)
ArrayIndexOutOfBoundsException
will be thrown if any recorded values may be lost
as a result of the attempted operation, reflecting an "overflow" conditions. Expect such an overflow
exception if the operation would cause the current maxValue to be scaled to a value that is outside
of the covered value range.numberOfBinaryOrdersOfMagnitude
 The number of binary orders of magnitude to shift bypublic void shiftValuesRight(int numberOfBinaryOrdersOfMagnitude)
Shift right operations that do not underflow are reversible with a shift left operation with no loss of
information. An ArrayIndexOutOfBoundsException
reflecting an "underflow" conditions will be thrown
if any recorded values may lose representation accuracy as a result of the attempted shift operation.
For a shift of a single order of magnitude, expect such an underflow exception if any recorded nonzero values up to [numberOfSignificantValueDigits (rounded up to nearest power of 2) multiplied by (2 ^ numberOfBinaryOrdersOfMagnitude) currently exist in the histogram.
numberOfBinaryOrdersOfMagnitude
 The number of binary orders of magnitude to shift bypublic boolean equals(Object other)
public long getLowestDiscernibleValue()
public long getHighestTrackableValue()
public int getNumberOfSignificantValueDigits()
public long sizeOfEquivalentValueRange(long value)
value
 The given valuepublic long lowestEquivalentValue(long value)
value
 The given valuepublic long highestEquivalentValue(long value)
value
 The given valuepublic long medianEquivalentValue(long value)
value
 The given valuepublic long nextNonEquivalentValue(long value)
value
 The given valuepublic boolean valuesAreEquivalent(long value1, long value2)
value1
 first value to comparevalue2
 second value to comparepublic int getEstimatedFootprintInBytes()
public long getStartTimeStamp()
getStartTimeStamp
in class EncodableHistogram
public void setStartTimeStamp(long timeStampMsec)
setStartTimeStamp
in class EncodableHistogram
timeStampMsec
 the value to set the time stamp to, [by convention] in msec since the epoch.public long getEndTimeStamp()
getEndTimeStamp
in class EncodableHistogram
public void setEndTimeStamp(long timeStampMsec)
setEndTimeStamp
in class EncodableHistogram
timeStampMsec
 the value to set the time stamp to, [by convention] in msec since the epoch.public String getTag()
getTag
in class EncodableHistogram
public void setTag(String tag)
setTag
in class EncodableHistogram
tag
 the tag string to assciate with this histogrampublic long getMinValue()
public long getMaxValue()
public long getMinNonZeroValue()
public double getMaxValueAsDouble()
getMaxValueAsDouble
in class EncodableHistogram
public double getMean()
public double getStdDeviation()
public long getValueAtPercentile(double percentile)
Note that two values are "equivalent" in this statement if
valuesAreEquivalent(long, long)
would return true.
percentile
 The percentile for which to return the associated valuepublic double getPercentileAtOrBelowValue(long value)
Note that two values are "equivalent" in this statement if
valuesAreEquivalent(long, long)
would return true.
value
 The value for which to return the associated percentilepublic long getCountBetweenValues(long lowValue, long highValue) throws ArrayIndexOutOfBoundsException
lowValue
 The lower value bound on the range for which
to provide the recorded count. Will be rounded down with
lowestEquivalentValue
.highValue
 The higher value bound on the range for which to provide the recorded count.
Will be rounded up with highestEquivalentValue
.ArrayIndexOutOfBoundsException
public long getCountAtValue(long value) throws ArrayIndexOutOfBoundsException
value
 The value for which to provide the recorded countArrayIndexOutOfBoundsException
public AbstractHistogram.Percentiles percentiles(int percentileTicksPerHalfDistance)
percentileTicksPerHalfDistance
 The number of iteration steps per halfdistance to 100%.Iterable
<HistogramIterationValue
>
through the histogram using a
PercentileIterator
public AbstractHistogram.LinearBucketValues linearBucketValues(long valueUnitsPerBucket)
valueUnitsPerBucket
 The size (in value units) of the linear buckets to useIterable
<HistogramIterationValue
>
through the histogram using a
LinearIterator
public AbstractHistogram.LogarithmicBucketValues logarithmicBucketValues(long valueUnitsInFirstBucket, double logBase)
valueUnitsInFirstBucket
 The size (in value units) of the first bucket in the iterationlogBase
 The multiplier by which bucket sizes will grow in each iteration stepIterable
<HistogramIterationValue
>
through the histogram using
a LogarithmicIterator
public AbstractHistogram.RecordedValues recordedValues()
Iterable
<HistogramIterationValue
>
through the histogram using
a RecordedValuesIterator
public AbstractHistogram.AllValues allValues()
Iterable
<HistogramIterationValue
>
through the histogram using
a AllValuesIterator
public void outputPercentileDistribution(PrintStream printStream, Double outputValueUnitScalingRatio)
printStream
 Stream into which the distribution will be output
outputValueUnitScalingRatio
 The scaling factor by which to divide histogram recorded values units in
outputpublic void outputPercentileDistribution(PrintStream printStream, int percentileTicksPerHalfDistance, Double outputValueUnitScalingRatio)
printStream
 Stream into which the distribution will be output
percentileTicksPerHalfDistance
 The number of reporting points per exponentially decreasing halfdistance
outputValueUnitScalingRatio
 The scaling factor by which to divide histogram recorded values units in
outputpublic void outputPercentileDistribution(PrintStream printStream, int percentileTicksPerHalfDistance, Double outputValueUnitScalingRatio, boolean useCsvFormat)
printStream
 Stream into which the distribution will be output
percentileTicksPerHalfDistance
 The number of reporting points per exponentially decreasing halfdistance
outputValueUnitScalingRatio
 The scaling factor by which to divide histogram recorded values units in
outputuseCsvFormat
 Output in CSV format if true. Otherwise use plain text form.public int getNeededByteBufferCapacity()
getNeededByteBufferCapacity
in class EncodableHistogram
public int encodeIntoByteBuffer(ByteBuffer buffer)
buffer
 The buffer to encode intopublic int encodeIntoCompressedByteBuffer(ByteBuffer targetBuffer, int compressionLevel)
encodeIntoCompressedByteBuffer
in class EncodableHistogram
targetBuffer
 The buffer to encode intocompressionLevel
 Compression level (for java.util.zip.Deflater).public int encodeIntoCompressedByteBuffer(ByteBuffer targetBuffer)
targetBuffer
 The buffer to encode intoCopyright © 2017. All rights reserved.