Package org.apache.spark.ml.feature

Class MinHashLSH

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<T>

org.apache.spark.ml.feature.LSH<MinHashLSHModel>

org.apache.spark.ml.feature.MinHashLSH

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, org.apache.spark.ml.feature.LSHParams, Params, HasInputCol, HasOutputCol, HasSeed, DefaultParamsWritable, Identifiable, MLWritable

public class MinHashLSH
extends org.apache.spark.ml.feature.LSH<MinHashLSHModel>
implements HasSeed

LSH class for Jaccard distance.

The input can be dense or sparse vectors, but it is more efficient if it is sparse. For example, Vectors.sparse(10, Array((2, 1.0), (3, 1.0), (5, 1.0))) means there are 10 elements in the space. This set contains elements 2, 3, and 5. Also, any input vector must have at least 1 non-zero index, and all non-zero values are treated as binary "1" values.

References: Wikipedia on MinHash

See Also:

• Serialized Form

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

Constructor Summary

Constructors

Constructor	Description
MinHashLSH()
MinHashLSH(String uid)

Method Summary

Modifier and Type	Method	Description
MinHashLSH	copy(ParamMap extra)	Creates a copy of this instance with the same UID and some extra params.
static MinHashLSH	load(String path)
static MLReader<T>	read()
final LongParam	seed()	Param for random seed.
MinHashLSH	setInputCol(String value)
MinHashLSH	setNumHashTables(int value)
MinHashLSH	setOutputCol(String value)
MinHashLSH	setSeed(long value)
StructType	transformSchema(StructType schema)	Check transform validity and derive the output schema from the input schema.
String	uid()	An immutable unique ID for the object and its derivatives.

Methods inherited from class org.apache.spark.ml.feature.LSH

fit, getInputCol, getNumHashTables, getOutputCol, inputCol, numHashTables, org$apache$spark$ml$feature$LSHParams$_setter_$numHashTables_$eq, org$apache$spark$ml$param$shared$HasInputCol$_setter_$inputCol_$eq, org$apache$spark$ml$param$shared$HasOutputCol$_setter_$outputCol_$eq, outputCol, save, validateAndTransformSchema, write

Methods inherited from class org.apache.spark.ml.Estimator

fit, fit, fit, fit

Methods inherited from class org.apache.spark.ml.PipelineStage

params

Methods inherited from class java.lang.Object

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

Methods inherited from interface org.apache.spark.ml.param.shared.HasSeed

getSeed

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString

Methods inherited from interface org.apache.spark.internal.Logging

initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logBasedOnLevel, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, MDC, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Constructor Details

MinHashLSH

public MinHashLSH(String uid)

MinHashLSH

public MinHashLSH()

Method Details

load

public static MinHashLSH load(String path)

read

public static MLReader<T> read()

seed

public final LongParam seed()

Description copied from interface: HasSeed

Param for random seed.

Specified by:

seed in interface HasSeed

Returns:

(undocumented)

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

setInputCol

public MinHashLSH setInputCol(String value)

Overrides:

setInputCol in class org.apache.spark.ml.feature.LSH<MinHashLSHModel>

setOutputCol

public MinHashLSH setOutputCol(String value)

Overrides:

setOutputCol in class org.apache.spark.ml.feature.LSH<MinHashLSHModel>

setNumHashTables

public MinHashLSH setNumHashTables(int value)

Overrides:

setNumHashTables in class org.apache.spark.ml.feature.LSH<MinHashLSHModel>

setSeed

public MinHashLSH setSeed(long value)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

Check transform validity and derive the output schema from the input schema.

We check validity for interactions between parameters during transformSchema and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by Param.validate().

Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public MinHashLSH copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Estimator<MinHashLSHModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)