case class BFSparse[A](hashes: BFHash[A], bits: EWAHCompressedBitmap, width: Int) extends BF[A] with Product with Serializable
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- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- def +(item: A): BF[A]
- def ++(other: BF[A]): BF[A]
- final def ==(arg0: Any): Boolean
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- final def asInstanceOf[T0]: T0
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- val bits: EWAHCompressedBitmap
- def checkAndAdd(other: A): (BF[A], ApproximateBoolean)
- def clone(): AnyRef
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- def contains(item: A): ApproximateBoolean
- Definition Classes
- BF
- def dense: BFInstance[A]
Convert to a dense representation
- def density: Double
Proportion of bits that are set to true.
Proportion of bits that are set to true.
- Definition Classes
- BF
- final def eq(arg0: AnyRef): Boolean
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- def hammingDistance(that: BF[A]): Int
Compute the Hamming distance between the two Bloom filters
aandb.Compute the Hamming distance between the two Bloom filters
aandb. The distance is defined as the number of bits that need to change to in order to transform one filter into the other.- Definition Classes
- BF
- val hashes: BFHash[A]
- final def isInstanceOf[T0]: Boolean
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- def maybeContains(item: A): Boolean
This may be faster if you don't care about evaluating the false positive probability
- final def ne(arg0: AnyRef): Boolean
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- final def notifyAll(): Unit
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- def numBits: Int
The number of bits set to true in the bloom filter
- def numHashes: Int
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- def size: Approximate[Long]
- final def synchronized[T0](arg0: => T0): T0
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- def toBitSet: BitSet
- final def wait(): Unit
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- final def wait(arg0: Long, arg1: Int): Unit
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- final def wait(arg0: Long): Unit
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- val width: Int