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java.lang.Objectorg.HdrHistogram.EncodableHistogram
org.HdrHistogram.AbstractHistogram
public abstract class AbstractHistogram
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.
| Nested Class Summary | |
|---|---|
class |
AbstractHistogram.AllValues
An Iterable<HistogramIterationValue> through
the histogram using a AllValuesIterator |
class |
AbstractHistogram.LinearBucketValues
An Iterable<HistogramIterationValue> through
the histogram using a LinearIterator |
class |
AbstractHistogram.LogarithmicBucketValues
An Iterable<HistogramIterationValue> through
the histogram using a LogarithmicIterator |
class |
AbstractHistogram.Percentiles
An Iterable<HistogramIterationValue> through
the histogram using a PercentileIterator |
class |
AbstractHistogram.RecordedValues
An Iterable<HistogramIterationValue> through
the histogram using a RecordedValuesIterator |
| Constructor Summary | |
|---|---|
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) |
protected |
AbstractHistogram(int numberOfSignificantValueDigits)
Construct an auto-resizing histogram with a lowest discernible value of 1 and an auto-adjusting 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. |
| Method Summary | |
|---|---|
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 non-zero 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 |
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. |
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 auto-resize and auto-adjust 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,
Double outputValueUnitScalingRatio)
Produce textual representation of the value distribution of histogram data by percentile. |
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. |
AbstractHistogram.Percentiles |
percentiles(int percentileTicksPerHalfDistance)
Provide a means of iterating through histogram values according to percentile levels. |
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 auto-resize and auto-adjust 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 |
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 |
valuesAreEquivalent(long value1,
long value2)
Determine if two values are equivalent with the histogram's resolution. |
| Methods inherited from class java.lang.Object |
|---|
clone, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
protected AbstractHistogram(int numberOfSignificantValueDigits)
numberOfSignificantValueDigits - 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.
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 non-negative
integer between 0 and 5.protected AbstractHistogram(AbstractHistogram source)
source - The source histogram to duplicate| Method Detail |
|---|
public abstract long getTotalCount()
public boolean isAutoResize()
public void setAutoResize(boolean autoResize)
autoResize - autoResize setting
public void recordValue(long value)
throws ArrayIndexOutOfBoundsException
value - The value to be recorded
ArrayIndexOutOfBoundsException - (may throw) if value is exceeds highestTrackableValue
public void recordValueWithCount(long value,
long count)
throws ArrayIndexOutOfBoundsException
value - The value to be recordedcount - The number of occurrences of this value to record
ArrayIndexOutOfBoundsException - (may throw) if value is exceeds highestTrackableValue
public 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 auto-generate an additional series of decreasingly-smaller (down to the expectedIntervalBetweenValueSamples) value records.
Note: This is a at-recording correction method, as opposed to the post-recording 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
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamples
ArrayIndexOutOfBoundsException - (may throw) if value is exceeds highestTrackableValue
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
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamples
ArrayIndexOutOfBoundsException - (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 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.
expectedIntervalBetweenValueSamples - If expectedIntervalBetweenValueSamples is larger than 0, add
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamples
public void copyInto(AbstractHistogram targetHistogram)
targetHistogram - the histogram to copy into
public 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
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamples
public 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 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-recording 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.
otherHistogram - The other histogram. highestTrackableValue and largestValueWithSingleUnitResolution must match.expectedIntervalBetweenValueSamples - If expectedIntervalBetweenValueSamples is larger than 0, add
auto-generated value records as appropriate if value is larger
than expectedIntervalBetweenValueSamples
ArrayIndexOutOfBoundsException - (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 non-zero 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)
equals in class Objectother - the other histogram to compare to
public long getLowestDiscernibleValue()
public long getHighestTrackableValue()
public int getNumberOfSignificantValueDigits()
public long sizeOfEquivalentValueRange(long value)
value - The given value
public long lowestEquivalentValue(long value)
value - The given value
public long highestEquivalentValue(long value)
value - The given value
public long medianEquivalentValue(long value)
value - The given value
public long nextNonEquivalentValue(long value)
value - The given value
public boolean valuesAreEquivalent(long value1,
long value2)
value1 - first value to comparevalue2 - second value to compare
public int getEstimatedFootprintInBytes()
public long getStartTimeStamp()
getStartTimeStamp in class EncodableHistogrampublic void setStartTimeStamp(long timeStampMsec)
setStartTimeStamp in class EncodableHistogramtimeStampMsec - the value to set the time stamp to, [by convention] in msec since the epoch.public long getEndTimeStamp()
getEndTimeStamp in class EncodableHistogrampublic void setEndTimeStamp(long timeStampMsec)
setEndTimeStamp in class EncodableHistogramtimeStampMsec - the value to set the time stamp to, [by convention] in msec since the epoch.public long getMinValue()
public long getMaxValue()
public long getMinNonZeroValue()
public double getMaxValueAsDouble()
getMaxValueAsDouble in class EncodableHistogrampublic 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 value
public 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 percentile
public 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 count
ArrayIndexOutOfBoundsExceptionpublic AbstractHistogram.Percentiles percentiles(int percentileTicksPerHalfDistance)
percentileTicksPerHalfDistance - The number of iteration steps per half-distance to 100%.
Iterable<HistogramIterationValue>
through the histogram using a
PercentileIteratorpublic AbstractHistogram.LinearBucketValues linearBucketValues(long valueUnitsPerBucket)
valueUnitsPerBucket - The size (in value units) of the linear buckets to use
Iterable<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 step
Iterable<HistogramIterationValue>
through the histogram using
a LogarithmicIteratorpublic AbstractHistogram.RecordedValues recordedValues()
Iterable<HistogramIterationValue>
through the histogram using
a RecordedValuesIteratorpublic 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
output
public 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 half-distance
outputValueUnitScalingRatio - The scaling factor by which to divide histogram recorded values units in
output
public 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 half-distance
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 EncodableHistogrampublic int encodeIntoByteBuffer(ByteBuffer buffer)
buffer - The buffer to encode into
public int encodeIntoCompressedByteBuffer(ByteBuffer targetBuffer,
int compressionLevel)
encodeIntoCompressedByteBuffer in class EncodableHistogramtargetBuffer - The buffer to encode intocompressionLevel - Compression level (for java.util.zip.Deflater).
public int encodeIntoCompressedByteBuffer(ByteBuffer targetBuffer)
targetBuffer - The buffer to encode into
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