Package org.apache.spark.mllib.stat.test
Class StreamingTest
Object
org.apache.spark.mllib.stat.test.StreamingTest
- All Implemented Interfaces:
Serializable
,org.apache.spark.internal.Logging
public class StreamingTest
extends Object
implements org.apache.spark.internal.Logging, Serializable
Performs online 2-sample significance testing for a stream of (Boolean, Double) pairs. The
Boolean identifies which sample each observation comes from, and the Double is the numeric value
of the observation.
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)
- See Also:
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Nested Class Summary
Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging
org.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionJavaDStream<org.apache.spark.mllib.stat.test.StreamingTestResult>
Register aJavaDStream
of values for significance testing.DStream<org.apache.spark.mllib.stat.test.StreamingTestResult>
registerStream
(DStream<BinarySample> data) Register aDStream
of values for significance testing.setPeacePeriod
(int peacePeriod) Set the number of initial batches to ignore.setTestMethod
(String method) Set the statistical method used for significance testing.setWindowSize
(int windowSize) Set the number of batches to compute significance tests over.Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.apache.spark.internal.Logging
initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
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Constructor Details
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StreamingTest
public StreamingTest()
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Method Details
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registerStream
public DStream<org.apache.spark.mllib.stat.test.StreamingTestResult> registerStream(DStream<BinarySample> data) Register aDStream
of values for significance testing.- Parameters:
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 significance- Returns:
- stream of significance testing results
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registerStream
public JavaDStream<org.apache.spark.mllib.stat.test.StreamingTestResult> registerStream(JavaDStream<BinarySample> data) Register aJavaDStream
of values for significance testing.- Parameters:
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 significance- Returns:
- stream of significance testing results
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setPeacePeriod
Set the number of initial batches to ignore. Default: 0. -
setTestMethod
Set the statistical method used for significance testing. Default: "welch" -
setWindowSize
Set the number of batches to compute significance tests over. Default: 0. A value of 0 will use all batches seen so far.- Parameters:
windowSize
- (undocumented)- Returns:
- (undocumented)
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