Uses of Enum Class
org.apache.datasketches.quantilescommon.QuantileSearchCriteria
Packages that use QuantileSearchCriteria
Package
Description
This package is for the implementations of the sketch algorithm developed by Zohar Karnin, Kevin Lang,
and Edo Liberty that is commonly referred to as the "KLL" sketch after the authors' last names.
This package is for classes that simplify the task of partitioning large data into many approximately equal-sized
partitions.
The quantiles package contains stochastic streaming algorithms that enable single-pass
analysis of the distribution of a stream of quantiles.
This package contains common tools and methods for the quantiles, kll and
req packages.
This package is for the implementation of the Relative Error Quantiles sketch algorithm.
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Uses of QuantileSearchCriteria in org.apache.datasketches.kll
Methods in org.apache.datasketches.kll with parameters of type QuantileSearchCriteriaModifier and TypeMethodDescriptiondouble[]KllDoublesSketch.getCDF(double[] splitPoints, QuantileSearchCriteria searchCrit) double[]KllFloatsSketch.getCDF(float[] splitPoints, QuantileSearchCriteria searchCrit) double[]KllItemsSketch.getCDF(T[] splitPoints, QuantileSearchCriteria searchCrit) double[]KllLongsSketch.getCDF(long[] splitPoints, QuantileSearchCriteria searchCrit) KllItemsSketch.getPartitionBoundariesFromNumParts(int numEquallySizedParts, QuantileSearchCriteria searchCrit) KllItemsSketch.getPartitionBoundariesFromPartSize(long nominalPartSizeItems, QuantileSearchCriteria searchCrit) double[]KllDoublesSketch.getPMF(double[] splitPoints, QuantileSearchCriteria searchCrit) double[]KllFloatsSketch.getPMF(float[] splitPoints, QuantileSearchCriteria searchCrit) double[]KllItemsSketch.getPMF(T[] splitPoints, QuantileSearchCriteria searchCrit) double[]KllLongsSketch.getPMF(long[] splitPoints, QuantileSearchCriteria searchCrit) doubleKllDoublesSketch.getQuantile(double rank, QuantileSearchCriteria searchCrit) floatKllFloatsSketch.getQuantile(double rank, QuantileSearchCriteria searchCrit) KllItemsSketch.getQuantile(double rank, QuantileSearchCriteria searchCrit) longKllLongsSketch.getQuantile(double rank, QuantileSearchCriteria searchCrit) double[]KllDoublesSketch.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) float[]KllFloatsSketch.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) T[]KllItemsSketch.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) long[]KllLongsSketch.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) doubleKllDoublesSketch.getRank(double quantile, QuantileSearchCriteria searchCrit) doubleKllFloatsSketch.getRank(float quantile, QuantileSearchCriteria searchCrit) doubleKllItemsSketch.getRank(T quantile, QuantileSearchCriteria searchCrit) doubleKllLongsSketch.getRank(long quantile, QuantileSearchCriteria searchCrit) double[]KllDoublesSketch.getRanks(double[] quantiles, QuantileSearchCriteria searchCrit) double[]KllFloatsSketch.getRanks(float[] quantiles, QuantileSearchCriteria searchCrit) double[]KllItemsSketch.getRanks(T[] quantiles, QuantileSearchCriteria searchCrit) double[]KllLongsSketch.getRanks(long[] quantiles, QuantileSearchCriteria searchCrit) -
Uses of QuantileSearchCriteria in org.apache.datasketches.partitions
Constructors in org.apache.datasketches.partitions with parameters of type QuantileSearchCriteriaModifierConstructorDescriptionPartitioner(long tgtPartitionSize, int maxPartsPerSk, SketchFillRequest<T, S> fillReq, QuantileSearchCriteria criteria) This constructor includes the QuantileSearchCriteria criteria as a parameter. -
Uses of QuantileSearchCriteria in org.apache.datasketches.quantiles
Methods in org.apache.datasketches.quantiles with parameters of type QuantileSearchCriteriaModifier and TypeMethodDescriptiondouble[]QuantilesDoublesSketch.getCDF(double[] splitPoints, QuantileSearchCriteria searchCrit) double[]QuantilesItemsSketch.getCDF(T[] splitPoints, QuantileSearchCriteria searchCrit) QuantilesItemsSketch.getPartitionBoundariesFromNumParts(int numEquallySizedParts, QuantileSearchCriteria searchCrit) QuantilesItemsSketch.getPartitionBoundariesFromPartSize(long nominalPartSizeItems, QuantileSearchCriteria searchCrit) double[]QuantilesDoublesSketch.getPMF(double[] splitPoints, QuantileSearchCriteria searchCrit) double[]QuantilesItemsSketch.getPMF(T[] splitPoints, QuantileSearchCriteria searchCrit) doubleQuantilesDoublesSketch.getQuantile(double rank, QuantileSearchCriteria searchCrit) QuantilesItemsSketch.getQuantile(double rank, QuantileSearchCriteria searchCrit) double[]QuantilesDoublesSketch.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) T[]QuantilesItemsSketch.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) doubleQuantilesDoublesSketch.getRank(double quantile, QuantileSearchCriteria searchCrit) doubleQuantilesItemsSketch.getRank(T quantile, QuantileSearchCriteria searchCrit) double[]QuantilesDoublesSketch.getRanks(double[] quantiles, QuantileSearchCriteria searchCrit) double[]QuantilesItemsSketch.getRanks(T[] quantiles, QuantileSearchCriteria searchCrit) -
Uses of QuantileSearchCriteria in org.apache.datasketches.quantilescommon
Subclasses with type arguments of type QuantileSearchCriteria in org.apache.datasketches.quantilescommonModifier and TypeClassDescriptionenumThese search criteria are used by the KLL, REQ and Classic Quantiles sketches in the DataSketches library.Methods in org.apache.datasketches.quantilescommon that return QuantileSearchCriteriaModifier and TypeMethodDescriptionGenericPartitionBoundaries.getSearchCriteria()Gets the search criteria specified for the source sketchstatic QuantileSearchCriteriaReturns the enum constant of this class with the specified name.static QuantileSearchCriteria[]QuantileSearchCriteria.values()Returns an array containing the constants of this enum class, in the order they are declared.Methods in org.apache.datasketches.quantilescommon with parameters of type QuantileSearchCriteriaModifier and TypeMethodDescriptiondefault double[]DoublesSortedView.getCDF(double[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.default double[]FloatsSortedView.getCDF(float[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.default double[]GenericSortedView.getCDF(T[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.default double[]LongsSortedView.getCDF(long[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesDoublesAPI.getCDF(double[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesFloatsAPI.getCDF(float[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesGenericAPI.getCDF(T[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesLongsAPI.getCDF(long[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Cumulative Distribution Function (CDF) of the input stream as a monotonically increasing array of double ranks (or cumulative probabilities) on the interval [0.0, 1.0], given a set of splitPoints.static doubleQuantilesUtil.getNaturalRank(double normalizedRank, long totalN, QuantileSearchCriteria searchCrit) Computes the closest Natural Rank from a given Normalized RanklongSortedViewIterator.getNaturalRank(QuantileSearchCriteria searchCrit) Gets the natural rank at the current index (or previous index) based on the chosen search criterion.doubleSortedViewIterator.getNormalizedRank(QuantileSearchCriteria searchCrit) Gets the normalized rank at the current index (or previous index) based on the chosen search criterion.ItemsSketchSortedView.getPartitionBoundariesFromNumParts(int numEquallySizedParts, QuantileSearchCriteria searchCrit) PartitioningFeature.getPartitionBoundariesFromNumParts(int numEquallySizedParts, QuantileSearchCriteria searchCrit) This method returns an instance ofGenericPartitionBoundarieswhich provides sufficient information for the user to create the given number of equally sized partitions, where "equally sized" refers to an approximately equal number of items per partition.ItemsSketchSortedView.getPartitionBoundariesFromPartSize(long nominalPartitionSize, QuantileSearchCriteria searchCrit) PartitioningFeature.getPartitionBoundariesFromPartSize(long nominalPartSizeItems, QuantileSearchCriteria searchCrit) This method returns an instance ofGenericPartitionBoundarieswhich provides sufficient information for the user to create the given number of equally sized partitions, where "equally sized" refers to an approximately equal number of items per partition.default double[]DoublesSortedView.getPMF(double[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.default double[]FloatsSortedView.getPMF(float[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.default double[]GenericSortedView.getPMF(T[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.default double[]LongsSortedView.getPMF(long[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesDoublesAPI.getPMF(double[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesFloatsAPI.getPMF(float[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesGenericAPI.getPMF(T[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.double[]QuantilesLongsAPI.getPMF(long[] splitPoints, QuantileSearchCriteria searchCrit) Returns an approximation to the Probability Mass Function (PMF) of the input stream as an array of probability masses as doubles on the interval [0.0, 1.0], given a set of splitPoints.doubleDoublesSketchSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) doubleDoublesSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.floatFloatsSketchSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) floatFloatsSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.GenericSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.GenericSortedViewIterator.getQuantile(QuantileSearchCriteria searchCrit) Gets the quantile at the current index (or previous index) based on the chosen search criterion.ItemsSketchSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) longLongsSketchSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) longLongsSortedView.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.doubleQuantilesDoublesAPI.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.floatQuantilesFloatsAPI.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.QuantilesGenericAPI.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.longQuantilesLongsAPI.getQuantile(double rank, QuantileSearchCriteria searchCrit) Gets the approximate quantile of the given normalized rank and the given search criterion.T[]ItemsSketchSortedView.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) Gets an array of quantiles corresponding to the given array of ranks.double[]QuantilesDoublesAPI.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) Gets an array of quantiles from the given array of normalized ranks.float[]QuantilesFloatsAPI.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) Gets an array of quantiles from the given array of normalized ranks.T[]QuantilesGenericAPI.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) Gets an array of quantiles from the given array of normalized ranks.long[]QuantilesLongsAPI.getQuantiles(double[] ranks, QuantileSearchCriteria searchCrit) Gets an array of quantiles from the given array of normalized ranks.doubleDoublesSketchSortedView.getRank(double quantile, QuantileSearchCriteria searchCrit) doubleDoublesSortedView.getRank(double quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleFloatsSketchSortedView.getRank(float quantile, QuantileSearchCriteria searchCrit) doubleFloatsSortedView.getRank(float quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleGenericSortedView.getRank(T quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleItemsSketchSortedView.getRank(T quantile, QuantileSearchCriteria searchCrit) doubleLongsSketchSortedView.getRank(long quantile, QuantileSearchCriteria searchCrit) doubleLongsSortedView.getRank(long quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleQuantilesDoublesAPI.getRank(double quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleQuantilesFloatsAPI.getRank(float quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleQuantilesGenericAPI.getRank(T quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.doubleQuantilesLongsAPI.getRank(long quantile, QuantileSearchCriteria searchCrit) Gets the normalized rank corresponding to the given a quantile.double[]QuantilesDoublesAPI.getRanks(double[] quantiles, QuantileSearchCriteria searchCrit) Gets an array of normalized ranks corresponding to the given array of quantiles and the given search criterion.double[]QuantilesFloatsAPI.getRanks(float[] quantiles, QuantileSearchCriteria searchCrit) Gets an array of normalized ranks corresponding to the given array of quantiles and the given search criterion.double[]QuantilesGenericAPI.getRanks(T[] quantiles, QuantileSearchCriteria searchCrit) Gets an array of normalized ranks corresponding to the given array of quantiles and the given search criterion.double[]QuantilesLongsAPI.getRanks(long[] quantiles, QuantileSearchCriteria searchCrit) Gets an array of normalized ranks corresponding to the given array of quantiles and the given search criterion.Constructors in org.apache.datasketches.quantilescommon with parameters of type QuantileSearchCriteriaModifierConstructorDescriptionGenericPartitionBoundaries(long totalN, T[] boundaries, long[] natRanks, double[] normRanks, T maxItem, T minItem, QuantileSearchCriteria searchCrit) Constructor. -
Uses of QuantileSearchCriteria in org.apache.datasketches.req
Methods in org.apache.datasketches.req with parameters of type QuantileSearchCriteriaModifier and TypeMethodDescriptiondouble[]ReqSketch.getCDF(float[] splitPoints, QuantileSearchCriteria searchCrit) double[]ReqSketch.getPMF(float[] splitPoints, QuantileSearchCriteria searchCrit) floatReqSketch.getQuantile(double normRank, QuantileSearchCriteria searchCrit) float[]ReqSketch.getQuantiles(double[] normRanks, QuantileSearchCriteria searchCrit) doubleReqSketch.getRank(float quantile, QuantileSearchCriteria searchCrit) double[]ReqSketch.getRanks(float[] quantiles, QuantileSearchCriteria searchCrit)