Package org.apache.beam.sdk.transforms

Class ApproximateUnique

  • @Deprecated
public class ApproximateUnique
extends java.lang.Object
    Deprecated.

    Consider using ApproximateCountDistinct in the zetasketch extension module, which makes use of the HllCount implementation.

    If ApproximateCountDistinct does not meet your needs then you can directly use HllCount. Direct usage will also give you access to save intermediate aggregation result into a sketch for later processing.

    For example, to estimate the number of distinct elements in a PCollection<String>: 

    
 PCollection<String> input = ...;
 PCollection<Long> countDistinct =
     input.apply(HllCount.Init.forStrings().globally()).apply(HllCount.Extract.globally());
    For more details about using HllCount and the zetasketch extension module, see https://s.apache.org/hll-in-beam#bookmark=id.v6chsij1ixo7.
    PTransforms for estimating the number of distinct elements in a PCollection, or the number of distinct values associated with each key in a PCollection of KVs.

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description
      static class  ApproximateUnique.ApproximateUniqueCombineFn<T>
      Deprecated.
      CombineFn that computes an estimate of the number of distinct values that were combined.
      static class  ApproximateUnique.Globally<T>
      Deprecated.
      PTransform for estimating the number of distinct elements in a PCollection.
      static class  ApproximateUnique.PerKey<K,​V>
      Deprecated.
      PTransform for estimating the number of distinct values associated with each key in a PCollection of KVs.

    • Constructor Summary

      Constructors 
      Constructor Description
      ApproximateUnique()
      Deprecated.
       

    • Method Summary

      All Methods Static Methods Concrete Methods Deprecated Methods 
      Modifier and Type Method Description
      static <T> ApproximateUnique.Globally<T> globally​(double maximumEstimationError)
      Deprecated.
      Like globally(int), but specifies the desired maximum estimation error instead of the sample size.
      static <T> ApproximateUnique.Globally<T> globally​(int sampleSize)
      Deprecated.
      Returns a PTransform that takes a PCollection<T> and returns a PCollection<Long> containing a single value that is an estimate of the number of distinct elements in the input PCollection.
      static <K,​V>
      ApproximateUnique.PerKey<K,​V>      		 perKey​(double maximumEstimationError)
      Deprecated.
      Like perKey(int), but specifies the desired maximum estimation error instead of the sample size.
      static <K,​V>
      ApproximateUnique.PerKey<K,​V>      		 perKey​(int sampleSize)
      Deprecated.
      Returns a PTransform that takes a PCollection<KV<K, V>> and returns a PCollection<KV<K, Long>> that contains an output element mapping each distinct key in the input PCollection to an estimate of the number of distinct values associated with that key in the input PCollection.

      • Methods inherited from class java.lang.Object

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

    • Constructor Detail

      • ApproximateUnique

        public ApproximateUnique()
        Deprecated.

    • Method Detail

      • globally

        public static <T> ApproximateUnique.Globally<T> globally​(int sampleSize)
        Deprecated.
        Returns a PTransform that takes a PCollection<T> and returns a PCollection<Long> containing a single value that is an estimate of the number of distinct elements in the input PCollection.

        The sampleSize parameter controls the estimation error. The error is about 2 / sqrt(sampleSize), so for ApproximateUnique.globally(10000) the estimation error is about 2%. Similarly, for ApproximateUnique.of(16) the estimation error is about 50%. If there are fewer than sampleSize distinct elements then the returned result will be exact with extremely high probability (the chance of a hash collision is about sampleSize^2 / 2^65).

        This transform approximates the number of elements in a set by computing the top sampleSize hash values, and using that to extrapolate the size of the entire set of hash values by assuming the rest of the hash values are as densely distributed as the top sampleSize.

        See also globally(double).

        Example of use: 

        
 PCollection<String> pc = ...;
 PCollection<Long> approxNumDistinct =
     pc.apply(ApproximateUnique.<String>globally(1000));
        Type Parameters:
        T - the type of the elements in the input PCollection
        Parameters:
        sampleSize - the number of entries in the statistical sample; the higher this number, the more accurate the estimate will be; should be >= 16
        Throws:
        java.lang.IllegalArgumentException - if the sampleSize argument is too small

      • globally

        public static <T> ApproximateUnique.Globally<T> globally​(double maximumEstimationError)
        Deprecated.
        Like globally(int), but specifies the desired maximum estimation error instead of the sample size.
        Type Parameters:
        T - the type of the elements in the input PCollection
        Parameters:
        maximumEstimationError - the maximum estimation error, which should be in the range [0.01, 0.5]
        Throws:
        java.lang.IllegalArgumentException - if the maximumEstimationError argument is out of range

      • perKey

        public static <K,​V> ApproximateUnique.PerKey<K,​V> perKey​(int sampleSize)
        Deprecated.
        Returns a PTransform that takes a PCollection<KV<K, V>> and returns a PCollection<KV<K, Long>> that contains an output element mapping each distinct key in the input PCollection to an estimate of the number of distinct values associated with that key in the input PCollection.

        See globally(int) for an explanation of the sampleSize parameter. A separate sampling is computed for each distinct key of the input.

        See also perKey(double).

        Example of use: 

        
 PCollection<KV<Integer, String>> pc = ...;
 PCollection<KV<Integer, Long>> approxNumDistinctPerKey =
     pc.apply(ApproximateUnique.<Integer, String>perKey(1000));
        Type Parameters:
        K - the type of the keys in the input and output PCollections
        V - the type of the values in the input PCollection
        Parameters:
        sampleSize - the number of entries in the statistical sample; the higher this number, the more accurate the estimate will be; should be >= 16
        Throws:
        java.lang.IllegalArgumentException - if the sampleSize argument is too small

      • perKey

        public static <K,​V> ApproximateUnique.PerKey<K,​V> perKey​(double maximumEstimationError)
        Deprecated.
        Like perKey(int), but specifies the desired maximum estimation error instead of the sample size.
        Type Parameters:
        K - the type of the keys in the input and output PCollections
        V - the type of the values in the input PCollection
        Parameters:
        maximumEstimationError - the maximum estimation error, which should be in the range [0.01, 0.5]
        Throws:
        java.lang.IllegalArgumentException - if the maximumEstimationError argument is out of range