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
Modifier and Type | Field and Description |
---|---|
(package private) long[] |
counts |
(package private) int |
normalizingIndexOffset |
(package private) long |
totalCount |
leadingZeroCountBase, maxValue, minNonZeroValue, subBucketHalfCount, subBucketHalfCountMagnitude, subBucketMask, unitMagnitude, unitMagnitudeMask
autoResize, bucketCount, constructionIdentityCount, countsArrayLength, doubleToIntegerValueConversionRatio, endTimeStampMsec, highestTrackableValue, identity, integerToDoubleValueConversionRatio, intermediateUncompressedByteArray, intermediateUncompressedByteBuffer, lowestDiscernibleValue, numberOfSignificantValueDigits, percentileIterator, recordedValuesIterator, startTimeStampMsec, subBucketCount, tag, wordSizeInBytes
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(AbstractHistogram source,
boolean allocateCountsArray) |
Histogram(int numberOfSignificantValueDigits)
Construct an auto-resizing histogram with a lowest discernible value of 1 and an auto-adjusting
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.
|
Histogram(long lowestDiscernibleValue,
long highestTrackableValue,
int numberOfSignificantValueDigits,
boolean allocateCountsArray) |
Modifier and Type | Method and Description |
---|---|
(package private) int |
_getEstimatedFootprintInBytes() |
(package private) void |
addToCountAtIndex(int index,
long value) |
(package private) void |
addToTotalCount(long value) |
(package private) void |
clearCounts() |
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(java.nio.ByteBuffer buffer,
long minBarForHighestTrackableValue)
Construct a new histogram by decoding it from a ByteBuffer.
|
static Histogram |
decodeFromCompressedByteBuffer(java.nio.ByteBuffer buffer,
long minBarForHighestTrackableValue)
Construct a new histogram by decoding it from a compressed form in a ByteBuffer.
|
(package private) void |
fillCountsArrayFromBuffer(java.nio.ByteBuffer buffer,
int length) |
(package private) long |
getCountAtIndex(int index) |
(package private) long |
getCountAtNormalizedIndex(int index) |
(package private) int |
getNormalizingIndexOffset() |
long |
getTotalCount()
Get the total count of all recorded values in the histogram
|
(package private) void |
incrementCountAtIndex(int index) |
(package private) void |
incrementTotalCount() |
private void |
readObject(java.io.ObjectInputStream o) |
(package private) void |
resize(long newHighestTrackableValue) |
(package private) void |
setCountAtIndex(int index,
long value) |
(package private) void |
setCountAtNormalizedIndex(int index,
long value) |
(package private) void |
setIntegerToDoubleValueConversionRatio(double integerToDoubleValueConversionRatio) |
(package private) void |
setNormalizingIndexOffset(int normalizingIndexOffset) |
(package private) void |
setTotalCount(long totalCount) |
(package private) void |
shiftNormalizingIndexByOffset(int offsetToAdd,
boolean lowestHalfBucketPopulated,
double newIntegerToDoubleValueConversionRatio) |
add, addWhileCorrectingForCoordinatedOmission, allValues, copyInto, copyIntoCorrectedForCoordinatedOmission, countsArrayIndex, decodeFromByteBuffer, decodeFromCompressedByteBuffer, determineArrayLengthNeeded, encodeIntoByteBuffer, encodeIntoCompressedByteBuffer, encodeIntoCompressedByteBuffer, equals, establishInternalTackingValues, establishInternalTackingValues, establishSize, fillBufferFromCountsArray, getBucketIndex, getBucketsNeededToCoverValue, getCountAtValue, getCountBetweenValues, getEndTimeStamp, getEstimatedFootprintInBytes, getHighestTrackableValue, getLengthForNumberOfBuckets, getLowestDiscernibleValue, getMaxValue, getMaxValueAsDouble, getMean, getMinNonZeroValue, getMinValue, getNeededByteBufferCapacity, getNeededByteBufferCapacity, getNeededPayloadByteBufferCapacity, getNeededV0PayloadByteBufferCapacity, getNumberOfSignificantValueDigits, getPercentileAtOrBelowValue, getStartTimeStamp, getStdDeviation, getSubBucketIndex, getTag, getValueAtPercentile, hashCode, highestEquivalentValue, isAutoResize, linearBucketValues, logarithmicBucketValues, lowestEquivalentValue, medianEquivalentValue, nextNonEquivalentValue, nonConcurrentNormalizingIndexShift, normalizeIndex, numberOfSubbuckets, outputPercentileDistribution, outputPercentileDistribution, outputPercentileDistribution, percentiles, recordConvertedDoubleValue, recordConvertedDoubleValueWithCount, recordedValues, recordValue, recordValue, recordValueWithCount, recordValueWithExpectedInterval, reset, setAutoResize, setEndTimeStamp, setStartTimeStamp, setTag, shiftValuesLeft, shiftValuesLeft, shiftValuesRight, shiftValuesRight, sizeOfEquivalentValueRange, subtract, supportsAutoResize, updateMinAndMax, valueFromIndex, valuesAreEquivalent
getDoubleToIntegerValueConversionRatio, getIntegerToDoubleValueConversionRatio, nonConcurrentSetIntegerToDoubleValueConversionRatio
long totalCount
long[] counts
int normalizingIndexOffset
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 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 duplicateHistogram(AbstractHistogram source, boolean allocateCountsArray)
Histogram(long lowestDiscernibleValue, long highestTrackableValue, int numberOfSignificantValueDigits, boolean allocateCountsArray)
long getCountAtIndex(int index)
getCountAtIndex
in class AbstractHistogram
long getCountAtNormalizedIndex(int index)
getCountAtNormalizedIndex
in class AbstractHistogram
void incrementCountAtIndex(int index)
incrementCountAtIndex
in class AbstractHistogram
void addToCountAtIndex(int index, long value)
addToCountAtIndex
in class AbstractHistogram
void setCountAtIndex(int index, long value)
setCountAtIndex
in class AbstractHistogram
void setCountAtNormalizedIndex(int index, long value)
setCountAtNormalizedIndex
in class AbstractHistogram
int getNormalizingIndexOffset()
getNormalizingIndexOffset
in class AbstractHistogram
void setNormalizingIndexOffset(int normalizingIndexOffset)
setNormalizingIndexOffset
in class AbstractHistogram
void setIntegerToDoubleValueConversionRatio(double integerToDoubleValueConversionRatio)
setIntegerToDoubleValueConversionRatio
in class AbstractHistogramBase
void shiftNormalizingIndexByOffset(int offsetToAdd, boolean lowestHalfBucketPopulated, double newIntegerToDoubleValueConversionRatio)
shiftNormalizingIndexByOffset
in class AbstractHistogram
void clearCounts()
clearCounts
in class AbstractHistogram
public 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 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 AbstractHistogram
expectedIntervalBetweenValueSamples
- If expectedIntervalBetweenValueSamples is larger than 0, add
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamplespublic long getTotalCount()
AbstractHistogram
getTotalCount
in class AbstractHistogram
void setTotalCount(long totalCount)
setTotalCount
in class AbstractHistogram
void incrementTotalCount()
incrementTotalCount
in class AbstractHistogram
void addToTotalCount(long value)
addToTotalCount
in class AbstractHistogram
int _getEstimatedFootprintInBytes()
_getEstimatedFootprintInBytes
in class AbstractHistogram
void resize(long newHighestTrackableValue)
resize
in class AbstractHistogram
public static Histogram decodeFromByteBuffer(java.nio.ByteBuffer buffer, long minBarForHighestTrackableValue)
buffer
- The buffer to decode fromminBarForHighestTrackableValue
- Force highestTrackableValue to be set at least this highpublic static Histogram decodeFromCompressedByteBuffer(java.nio.ByteBuffer buffer, long minBarForHighestTrackableValue) throws java.util.zip.DataFormatException
buffer
- The buffer to decode fromminBarForHighestTrackableValue
- Force highestTrackableValue to be set at least this highjava.util.zip.DataFormatException
- on error parsing/decompressing the bufferprivate void readObject(java.io.ObjectInputStream o) throws java.io.IOException, java.lang.ClassNotFoundException
java.io.IOException
java.lang.ClassNotFoundException
void fillCountsArrayFromBuffer(java.nio.ByteBuffer buffer, int length)
fillCountsArrayFromBuffer
in class AbstractHistogram