public class StreamingTest
extends Object
implements org.apache.spark.internal.Logging, scala.Serializable
 To address novelty affects, the peacePeriod specifies a set number of initial
 RDD batches of the DStream to be dropped from significance testing.
 
 The windowSize sets the number of batches each significance test is to be performed over. The
 window is sliding with a stride length of 1 batch. Setting windowSize to 0 will perform
 cumulative processing, using all batches seen so far.
 
 Different tests may be used for assessing statistical significance depending on assumptions
 satisfied by data. For more details, see StreamingTestMethod. The testMethod specifies
 which test will be used.
 
Use a builder pattern to construct a streaming test in an application, for example:
   val model = new StreamingTest()
     .setPeacePeriod(10)
     .setWindowSize(0)
     .setTestMethod("welch")
     .registerStream(DStream)
 | Constructor and Description | 
|---|
| StreamingTest() | 
| Modifier and Type | Method and Description | 
|---|---|
| DStream<org.apache.spark.mllib.stat.test.StreamingTestResult> | registerStream(DStream<BinarySample> data)Register a  DStreamof values for significance testing. | 
| JavaDStream<org.apache.spark.mllib.stat.test.StreamingTestResult> | registerStream(JavaDStream<BinarySample> data)Register a  JavaDStreamof values for significance testing. | 
| StreamingTest | setPeacePeriod(int peacePeriod)Set the number of initial batches to ignore. | 
| StreamingTest | setTestMethod(String method)Set the statistical method used for significance testing. | 
| StreamingTest | setWindowSize(int windowSize)Set the number of batches to compute significance tests over. | 
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitializepublic DStream<org.apache.spark.mllib.stat.test.StreamingTestResult> registerStream(DStream<BinarySample> data)
DStream of values for significance testing.
 data - stream of BinarySample(key,value) pairs where the key denotes group membership
             (true = experiment, false = control) and the value is the numerical metric to
             test for significancepublic JavaDStream<org.apache.spark.mllib.stat.test.StreamingTestResult> registerStream(JavaDStream<BinarySample> data)
JavaDStream of values for significance testing.
 data - stream of BinarySample(isExperiment,value) pairs where the isExperiment denotes
             group (true = experiment, false = control) and the value is the numerical metric
             to test for significancepublic StreamingTest setPeacePeriod(int peacePeriod)
public StreamingTest setTestMethod(String method)
public StreamingTest setWindowSize(int windowSize)
windowSize - (undocumented)