org.apache.flink.runtime.operators.util

类 BloomFilter

java.lang.Object

org.apache.flink.runtime.operators.util.BloomFilter

public class BloomFilter
extends Object

BloomFilter is a probabilistic data structure for set membership check. BloomFilters are highly space efficient when compared to using a HashSet. Because of the probabilistic nature of bloom filter false positive (element not present in bloom filter but test() says true) are possible but false negatives are not possible (if element is present then test() will never say false). The false positive probability is configurable depending on which storage requirement may increase or decrease. Lower the false positive probability greater is the space requirement. Bloom filters are sensitive to number of elements that will be inserted in the bloom filter. During the creation of bloom filter expected number of entries must be specified. If the number of insertions exceed the specified initial number of entries then false positive probability will increase accordingly.

Internally, this implementation of bloom filter uses MemorySegment to store BitSet, BloomFilter and BitSet are designed to be able to switch between different MemorySegments, so that Flink can share the same BloomFilter/BitSet object instance for different bloom filters.

Part of this class refers to the implementation from Apache Hive project https://github.com/apache/hive/blob/master/common/src/java/org/apache/hive/common/util/BloomFilter.java

字段概要

字段

限定符和类型	字段和说明
protected BitSet	bitSet
protected int	expectedEntries
protected int	numHashFunctions

构造器概要

构造器

构造器和说明
BloomFilter(int expectedEntries, int byteSize)

方法概要

限定符和类型	方法和说明
void	addHash(int hash32)
static double	estimateFalsePositiveProbability(long inputEntries, int bitSize) Compute the false positive probability based on given input entries and bits size.
static int	optimalNumOfBits(long inputEntries, double fpp) Compute optimal bits number with given input entries and expected false positive probability.
void	reset()
void	setBitsLocation(org.apache.flink.core.memory.MemorySegment memorySegment, int offset)
boolean	testHash(int hash32)
String	toString()

从类继承的方法 java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

字段详细资料

bitSet

protected BitSet bitSet

expectedEntries

protected int expectedEntries

numHashFunctions

protected int numHashFunctions

构造器详细资料

BloomFilter

public BloomFilter(int expectedEntries,
                   int byteSize)

方法详细资料

setBitsLocation

public void setBitsLocation(org.apache.flink.core.memory.MemorySegment memorySegment,
                            int offset)

optimalNumOfBits

public static int optimalNumOfBits(long inputEntries,
                                   double fpp)

Compute optimal bits number with given input entries and expected false positive probability.

参数:

inputEntries -

fpp -

返回:

optimal bits number

estimateFalsePositiveProbability

public static double estimateFalsePositiveProbability(long inputEntries,
                                                      int bitSize)

Compute the false positive probability based on given input entries and bits size. Note: this is just the math expected value, you should not expect the fpp in real case would under the return value for certain.

参数:

inputEntries -

bitSize -

返回:

addHash

public void addHash(int hash32)

testHash

public boolean testHash(int hash32)

reset

public void reset()

toString

public String toString()

覆盖:

toString 在类中 Object