public class KolmogorovSmirnovTest
extends Object
Implementation note: We seek to implement the KS test with a minimal number of distributed passes. We sort the RDD, and then perform the following operations on a perpartition basis: calculate an empirical cumulative distribution value for each observation, and a theoretical cumulative distribution value. We know the latter to be correct, while the former will be off by a constant (how large the constant is depends on how many values precede it in other partitions). However, given that this constant simply shifts the empirical CDF upwards, but doesn't change its shape, and furthermore, that constant is the same within a given partition, we can pick 2 values in each partition that can potentially resolve to the largest global distance. Namely, we pick the minimum distance and the maximum distance. Additionally, we keep track of how many elements are in each partition. Once these three values have been returned for every partition, we can collect and operate locally. Locally, we can now adjust each distance by the appropriate constant (the cumulative sum of number of elements in the prior partitions divided by the data set size). Finally, we take the maximum absolute value, and this is the statistic.
Modifier and Type  Class and Description 

static class 
KolmogorovSmirnovTest.NullHypothesis$ 
Constructor and Description 

KolmogorovSmirnovTest() 
Modifier and Type  Method and Description 

static KolmogorovSmirnovTestResult 
testOneSample(RDD<Object> data,
scala.Function1<Object,Object> cdf) 
static KolmogorovSmirnovTestResult 
testOneSample(RDD<Object> data,
org.apache.commons.math3.distribution.RealDistribution distObj) 
static KolmogorovSmirnovTestResult 
testOneSample(RDD<Object> data,
String distName,
double... params)
A convenience function that allows running the KS test for 1 set of sample data against
a named distribution

static KolmogorovSmirnovTestResult 
testOneSample(RDD<Object> data,
String distName,
scala.collection.Seq<Object> params) 
public static KolmogorovSmirnovTestResult testOneSample(RDD<Object> data, String distName, double... params)
data
 the sample data that we wish to evaluatedistName
 the name of the theoretical distributionparams
 Variable length parameter for distribution's parametersKolmogorovSmirnovTestResult
summarizing the
test results (pvalue, statistic, and null hypothesis)public static KolmogorovSmirnovTestResult testOneSample(RDD<Object> data, scala.Function1<Object,Object> cdf)
public static KolmogorovSmirnovTestResult testOneSample(RDD<Object> data, org.apache.commons.math3.distribution.RealDistribution distObj)
public static KolmogorovSmirnovTestResult testOneSample(RDD<Object> data, String distName, scala.collection.Seq<Object> params)