org.apache.hadoop.hive.ql.udf.generic
Class GenericUDAFCovariance

java.lang.Object
  org.apache.hadoop.hive.ql.udf.generic.AbstractGenericUDAFResolver
      org.apache.hadoop.hive.ql.udf.generic.GenericUDAFCovariance

All Implemented Interfaces:

GenericUDAFResolver, GenericUDAFResolver2

Direct Known Subclasses:

GenericUDAFCovarianceSample

public class GenericUDAFCovariance
extends AbstractGenericUDAFResolver

Compute the covariance covar_pop(x, y), using the following one-pass method (ref. "Formulas for Robust, One-Pass Parallel Computation of Covariances and Arbitrary-Order Statistical Moments", Philippe Pebay, Sandia Labs): Incremental: n : mx_n = mx_(n-1) + [x_n - mx_(n-1)]/n : my_n = my_(n-1) + [y_n - my_(n-1)]/n : c_n = c_(n-1) + (x_n - mx_(n-1))*(y_n - my_n) : Merge: c_X = c_A + c_B + (mx_A - mx_B)*(my_A - my_B)*n_A*n_B/n_X

Nested Class Summary

static class

GenericUDAFCovariance.GenericUDAFCovarianceEvaluator Evaluate the variance using the algorithm described in http://en.wikipedia.org/wiki/Algorithms_for_calculating_variance, presumably by Pébay, Philippe (2008), in "Formulas for Robust, One-Pass Parallel Computation of Covariances and Arbitrary-Order Statistical Moments", Technical Report SAND2008-6212, Sandia National Laboratories, http://infoserve.sandia.gov/sand_doc/2008/086212.pdf Incremental: n : mx_n = mx_(n-1) + [x_n - mx_(n-1)]/n : my_n = my_(n-1) + [y_n - my_(n-1)]/n : c_n = c_(n-1) + (x_n - mx_(n-1))*(y_n - my_n) : Merge: c_X = c_A + c_B + (mx_A - mx_B)*(my_A - my_B)*n_A*n_B/n_X This one-pass algorithm is stable.

Constructor Summary

GenericUDAFCovariance()

Method Summary

GenericUDAFEvaluator

getEvaluator(TypeInfo[] parameters) Get the evaluator for the parameter types.

Methods inherited from class org.apache.hadoop.hive.ql.udf.generic.AbstractGenericUDAFResolver

getEvaluator

Methods inherited from class java.lang.Object

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

Constructor Detail

GenericUDAFCovariance

public GenericUDAFCovariance()

Method Detail

getEvaluator

public GenericUDAFEvaluator getEvaluator(TypeInfo[] parameters)
                                  throws SemanticException

Description copied from interface: GenericUDAFResolver

Get the evaluator for the parameter types. The reason that this function returns an object instead of a class is because it is possible that the object needs some configuration (that can be serialized). In that case the class of the object has to implement the Serializable interface. At execution time, we will deserialize the object from the plan and use it to evaluate the aggregations.

If the class of the object does not implement Serializable, then we will create a new instance of the class at execution time.

Specified by:

getEvaluator in interface GenericUDAFResolver

Overrides:

getEvaluator in class AbstractGenericUDAFResolver

Parameters:

parameters - The types of the parameters. We need the type information to know which evaluator class to use.

Throws:

SemanticException