sampleclean.clean.deduplication.join

PassJoin

class PassJoin extends SimilarityJoin

A PassJoin is an implementation of a Similarity Join optimized for String comparisons. Currently, this algorithm is only supported by the EditBlocking Similarity Featurizer. In a distributed environment, this optimization involves broadcasting a series of maps to each node.

Note: because the algorithm may collect large RDDs into maps by using driver memory, java heap problems could arise. In this case, it is recommended to increase allocated driver memory through Spark configuration spark.driver.memory

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SimilarityJoin, Serializable, Serializable, AnyRef, Any
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Instance Constructors

  1. new PassJoin(sc: SparkContext, featurizer: AnnotatedSimilarityFeaturizer)

    sc

    Spark Context

    featurizer

    Similarity Featurizer optimized for PassJoin

Value Members

  1. final def !=(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  2. final def !=(arg0: Any): Boolean

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  12. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  13. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  14. def join(rddA: RDD[Row], rddB: RDD[Row], sampleA: Boolean = false): RDD[(Row, Row)]

    Join two RDDs.

    Join two RDDs. The resulting RDD will contain pairs of rows that are considered similar by the AnnotatedSimilarityFeaturizer. If rddA is the same as rddB, then the algorithm will trigger a self-join.

    The default implementation is naive but subclasses should override and optimize.

    rddA

    First RDD of rows

    rddB

    Second RDD of rows

    sampleA

    True if rddA is a sample of rddB

    returns

    an RDD with pairs of similar rows.

    Definition Classes
    PassJoinSimilarityJoin
    Annotations
    @Override()
  15. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  16. final def notify(): Unit

    Definition Classes
    AnyRef
  17. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  18. def setSimilarityFeaturizer(newSimilarity: String): Unit

    Definition Classes
    SimilarityJoin
  19. var simfeature: AnnotatedSimilarityFeaturizer

    Definition Classes
    SimilarityJoin
  20. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  21. def toString(): String

    Definition Classes
    AnyRef → Any
  22. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
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    @throws( ... )
  24. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
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    @throws( ... )

Inherited from SimilarityJoin

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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