ALS

Companion object ALS

class ALS extends Estimator[ALSModel] with ALSParams with DefaultParamsWritable

Alternating Least Squares (ALS) matrix factorization.

ALS attempts to estimate the ratings matrix R as the product of two lower-rank matrices, X and Y, i.e. X * Yt = R. Typically these approximations are called 'factor' matrices. The general approach is iterative. During each iteration, one of the factor matrices is held constant, while the other is solved for using least squares. The newly-solved factor matrix is then held constant while solving for the other factor matrix.

This is a blocked implementation of the ALS factorization algorithm that groups the two sets of factors (referred to as "users" and "products") into blocks and reduces communication by only sending one copy of each user vector to each product block on each iteration, and only for the product blocks that need that user's feature vector. This is achieved by pre-computing some information about the ratings matrix to determine the "out-links" of each user (which blocks of products it will contribute to) and "in-link" information for each product (which of the feature vectors it receives from each user block it will depend on). This allows us to send only an array of feature vectors between each user block and product block, and have the product block find the users' ratings and update the products based on these messages.

For implicit preference data, the algorithm used is based on "Collaborative Filtering for Implicit Feedback Datasets", available at https://doi.org/10.1109/ICDM.2008.22, adapted for the blocked approach used here.

Essentially instead of finding the low-rank approximations to the rating matrix R, this finds the approximations for a preference matrix P where the elements of P are 1 if r is greater than 0 and 0 if r is less than or equal to 0. The ratings then act as 'confidence' values related to strength of indicated user preferences rather than explicit ratings given to items.

Note: the input rating dataset to the ALS implementation should be deterministic. Nondeterministic data can cause failure during fitting ALS model. For example, an order-sensitive operation like sampling after a repartition makes dataset output nondeterministic, like dataset.repartition(2).sample(false, 0.5, 1618). Checkpointing sampled dataset or adding a sort before sampling can help make the dataset deterministic.

Annotations: @Since("1.3.0")
Source: ALS.scala

Linear Supertypes

DefaultParamsWritable, MLWritable, ALSParams, HasSeed, HasCheckpointInterval, HasRegParam, HasMaxIter, ALSModelParams, HasBlockSize, HasPredictionCol, Estimator[ALSModel], PipelineStage, Logging, Params, Serializable, Identifiable, AnyRef, Any

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Inherited

ALS
DefaultParamsWritable
MLWritable
ALSParams
HasSeed
HasCheckpointInterval
HasRegParam
HasMaxIter
ALSModelParams
HasBlockSize
HasPredictionCol
Estimator
PipelineStage
Logging
Params
Serializable
Identifiable
AnyRef
Any

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Visibility

Public
Protected

Instance Constructors

new ALS()
Annotations
@Since("1.4.0")
new ALS(uid: String)

Type Members

implicit class LogStringContext extends AnyRef
Definition Classes
Logging

Value Members

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T
An alias for getOrDefault().
An alias for getOrDefault().
Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
val alpha: DoubleParam
Param for the alpha parameter in the implicit preference formulation (nonnegative).
Param for the alpha parameter in the implicit preference formulation (nonnegative). Default: 1.0
Definition Classes
ALSParams
final def asInstanceOf[T0]: T0
Definition Classes
Any
final val blockSize: IntParam
Param for block size for stacking input data in matrices.
Param for block size for stacking input data in matrices. Data is stacked within partitions. If block size is more than remaining data in a partition then it is adjusted to the size of this data..
Definition Classes
HasBlockSize
def checkIntegers(dataset: Dataset[_], colName: String): Column
Attempts to safely cast a user/item id to an Int.
Attempts to safely cast a user/item id to an Int. Throws an exception if the value is out of integer range or contains a fractional part.
Attributes
protected[recommendation]
Definition Classes
ALSModelParams
final val checkpointInterval: IntParam
Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
Param for set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the cache will get checkpointed every 10 iterations. Note: this setting will be ignored if the checkpoint directory is not set in the SparkContext.
Definition Classes
HasCheckpointInterval
final def clear(param: Param[_]): ALS.this.type
Clears the user-supplied value for the input param.
Clears the user-supplied value for the input param.
Definition Classes
Params
def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
val coldStartStrategy: Param[String]
Param for strategy for dealing with unknown or new users/items at prediction time.
Param for strategy for dealing with unknown or new users/items at prediction time. This may be useful in cross-validation or production scenarios, for handling user/item ids the model has not seen in the training data. Supported values: - "nan": predicted value for unknown ids will be NaN. - "drop": rows in the input DataFrame containing unknown ids will be dropped from the output DataFrame containing predictions. Default: "nan".
Definition Classes
ALSModelParams
def copy(extra: ParamMap): ALS
Creates a copy of this instance with the same UID and some extra 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().
Definition Classes
ALS → Estimator → PipelineStage → Params
Annotations
@Since("1.5.0")
def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
Copies param values from this instance to another instance for params shared by them.
Copies param values from this instance to another instance for params shared by them.
This handles default Params and explicitly set Params separately. Default Params are copied from and to defaultParamMap, and explicitly set Params are copied from and to paramMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.
to
the target instance, which should work with the same set of default Params as this source instance
extra
extra params to be copied to the target's paramMap
returns
the target instance with param values copied
Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T
Default implementation of copy with extra params.
Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.
Attributes
protected
Definition Classes
Params
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String
Explains a param.
Explains a param.
param
input param, must belong to this instance.
returns
a string that contains the input param name, doc, and optionally its default value and the user-supplied value
Definition Classes
Params
def explainParams(): String
Explains all params of this instance.
Explains all params of this instance. See explainParam().
Definition Classes
Params
final def extractParamMap(): ParamMap
extractParamMap with no extra values.
extractParamMap with no extra values.
Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Definition Classes
Params
val finalStorageLevel: Param[String]
Param for StorageLevel for ALS model factors.
Param for StorageLevel for ALS model factors. Pass in a string representation of StorageLevel. Default: "MEMORY_AND_DISK".
Definition Classes
ALSParams
def fit(dataset: Dataset[_]): ALSModel
Fits a model to the input data.
Fits a model to the input data.
Definition Classes
ALS → Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[ALSModel]
Fits multiple models to the input data with multiple sets of parameters.
Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.
dataset
input dataset
paramMaps
An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted models, matching the input parameter maps
Definition Classes
Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], paramMap: ParamMap): ALSModel
Fits a single model to the input data with provided parameter map.
Fits a single model to the input data with provided parameter map.
dataset
input dataset
paramMap
Parameter map. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted model
Definition Classes
Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ALSModel
Fits a single model to the input data with optional parameters.
Fits a single model to the input data with optional parameters.
dataset
input dataset
firstParamPair
the first param pair, overrides embedded params
otherParamPairs
other param pairs. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted model
Definition Classes
Estimator
Annotations
@Since("2.0.0") @varargs()
final def get[T](param: Param[T]): Option[T]
Optionally returns the user-supplied value of a param.
Optionally returns the user-supplied value of a param.
Definition Classes
Params
def getAlpha: Double
Definition Classes
ALSParams
final def getBlockSize: Int
Definition Classes
HasBlockSize
final def getCheckpointInterval: Int
Definition Classes
HasCheckpointInterval
final def getClass(): Class[_ <: AnyRef]
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
def getColdStartStrategy: String
Definition Classes
ALSModelParams
final def getDefault[T](param: Param[T]): Option[T]
Gets the default value of a parameter.
Gets the default value of a parameter.
Definition Classes
Params
def getFinalStorageLevel: String
Definition Classes
ALSParams
def getImplicitPrefs: Boolean
Definition Classes
ALSParams
def getIntermediateStorageLevel: String
Definition Classes
ALSParams
def getItemCol: String
Definition Classes
ALSModelParams
final def getMaxIter: Int
Definition Classes
HasMaxIter
def getNonnegative: Boolean
Definition Classes
ALSParams
def getNumItemBlocks: Int
Definition Classes
ALSParams
def getNumUserBlocks: Int
Definition Classes
ALSParams
final def getOrDefault[T](param: Param[T]): T
Gets the value of a param in the embedded param map or its default value.
Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.
Definition Classes
Params
def getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
Definition Classes
Params
final def getPredictionCol: String
Definition Classes
HasPredictionCol
def getRank: Int
Definition Classes
ALSParams
def getRatingCol: String
Definition Classes
ALSParams
final def getRegParam: Double
Definition Classes
HasRegParam
final def getSeed: Long
Definition Classes
HasSeed
def getUserCol: String
Definition Classes
ALSModelParams
final def hasDefault[T](param: Param[T]): Boolean
Tests whether the input param has a default value set.
Tests whether the input param has a default value set.
Definition Classes
Params
def hasParam(paramName: String): Boolean
Tests whether this instance contains a param with a given name.
Tests whether this instance contains a param with a given name.
Definition Classes
Params
def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
val implicitPrefs: BooleanParam
Param to decide whether to use implicit preference.
Param to decide whether to use implicit preference. Default: false
Definition Classes
ALSParams
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit
Attributes
protected
Definition Classes
Logging
val intermediateStorageLevel: Param[String]
Param for StorageLevel for intermediate datasets.
Param for StorageLevel for intermediate datasets. Pass in a string representation of StorageLevel. Cannot be "NONE". Default: "MEMORY_AND_DISK".
Definition Classes
ALSParams
final def isDefined(param: Param[_]): Boolean
Checks whether a param is explicitly set or has a default value.
Checks whether a param is explicitly set or has a default value.
Definition Classes
Params
final def isInstanceOf[T0]: Boolean
Definition Classes
Any
final def isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
Definition Classes
Params
def isTraceEnabled(): Boolean
Attributes
protected
Definition Classes
Logging
val itemCol: Param[String]
Param for the column name for item ids.
Param for the column name for item ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "item"
Definition Classes
ALSModelParams
def log: Logger
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logName: String
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
final val maxIter: IntParam
Param for maximum number of iterations (>= 0).
Param for maximum number of iterations (>= 0).
Definition Classes
HasMaxIter
final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
val nonnegative: BooleanParam
Param for whether to apply nonnegativity constraints.
Param for whether to apply nonnegativity constraints. Default: false
Definition Classes
ALSParams
final def notify(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
val numItemBlocks: IntParam
Param for number of item blocks (positive).
Param for number of item blocks (positive). Default: 10
Definition Classes
ALSParams
val numUserBlocks: IntParam
Param for number of user blocks (positive).
Param for number of user blocks (positive). Default: 10
Definition Classes
ALSParams
lazy val params: Array[Param[_]]
Returns all params sorted by their names.
Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.
Definition Classes
Params
Note
Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.
final val predictionCol: Param[String]
Param for prediction column name.
Param for prediction column name.
Definition Classes
HasPredictionCol
val rank: IntParam
Param for rank of the matrix factorization (positive).
Param for rank of the matrix factorization (positive). Default: 10
Definition Classes
ALSParams
val ratingCol: Param[String]
Param for the column name for ratings.
Param for the column name for ratings. Default: "rating"
Definition Classes
ALSParams
final val regParam: DoubleParam
Param for regularization parameter (>= 0).
Param for regularization parameter (>= 0).
Definition Classes
HasRegParam
def save(path: String): Unit
Saves this ML instance to the input path, a shortcut of write.save(path).
Saves this ML instance to the input path, a shortcut of write.save(path).
Definition Classes
MLWritable
Annotations
@Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")
final val seed: LongParam
Param for random seed.
Param for random seed.
Definition Classes
HasSeed
final def set(paramPair: ParamPair[_]): ALS.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): ALS.this.type
Sets a parameter (by name) in the embedded param map.
Sets a parameter (by name) in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): ALS.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Definition Classes
Params
def setAlpha(value: Double): ALS.this.type
Annotations
@Since("1.3.0")
def setBlockSize(value: Int): ALS.this.type
Set block size for stacking input data in matrices.
Set block size for stacking input data in matrices. Default is 4096.
Annotations
@Since("3.0.0")
def setCheckpointInterval(value: Int): ALS.this.type
Annotations
@Since("1.4.0")
def setColdStartStrategy(value: String): ALS.this.type
Annotations
@Since("2.2.0")
final def setDefault(paramPairs: ParamPair[_]*): ALS.this.type
Sets default values for a list of params.
Sets default values for a list of params.
Note: Java developers should use the single-parameter setDefault. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.
paramPairs
a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.
Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): ALS.this.type
Sets a default value for a param.
Sets a default value for a param.
param
param to set the default value. Make sure that this param is initialized before this method gets called.
value
the default value
Attributes
protected[ml]
Definition Classes
Params
def setFinalStorageLevel(value: String): ALS.this.type
Annotations
@Since("2.0.0")
def setImplicitPrefs(value: Boolean): ALS.this.type
Annotations
@Since("1.3.0")
def setIntermediateStorageLevel(value: String): ALS.this.type
Annotations
@Since("2.0.0")
def setItemCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
def setMaxIter(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setNonnegative(value: Boolean): ALS.this.type
Annotations
@Since("1.3.0")
def setNumBlocks(value: Int): ALS.this.type
Sets both numUserBlocks and numItemBlocks to the specific value.
Sets both numUserBlocks and numItemBlocks to the specific value.
Annotations
@Since("1.3.0")
def setNumItemBlocks(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setNumUserBlocks(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setPredictionCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
def setRank(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setRatingCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
def setRegParam(value: Double): ALS.this.type
Annotations
@Since("1.3.0")
def setSeed(value: Long): ALS.this.type
Annotations
@Since("1.3.0")
def setUserCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
final def synchronized[T0](arg0: => T0): T0
Definition Classes
AnyRef
def toString(): String
Definition Classes
Identifiable → AnyRef → Any
def transformSchema(schema: StructType): StructType
Check transform validity and derive the output schema from the input schema.
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.
Definition Classes
ALS → PipelineStage
Annotations
@Since("1.3.0")
def transformSchema(schema: StructType, logging: Boolean): StructType
Derives the output schema from the input schema and parameters, optionally with logging.
This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.
Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String
An immutable unique ID for the object and its derivatives.
An immutable unique ID for the object and its derivatives.
Definition Classes
ALS → Identifiable
Annotations
@Since("1.4.0")
val userCol: Param[String]
Param for the column name for user ids.
Param for the column name for user ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "user"
Definition Classes
ALSModelParams
def validateAndTransformSchema(schema: StructType): StructType
Validates and transforms the input schema.
Validates and transforms the input schema.
schema
input schema
returns
output schema
Attributes
protected
Definition Classes
ALSParams
final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
def withLogContext(context: HashMap[String, String])(body: => Unit): Unit
Attributes
protected
Definition Classes
Logging
def write: MLWriter
Returns an MLWriter instance for this ML instance.
Returns an MLWriter instance for this ML instance.
Definition Classes
DefaultParamsWritable → MLWritable

Inherited from DefaultParamsWritable

Value Members

def write: MLWriter
Returns an MLWriter instance for this ML instance.
Returns an MLWriter instance for this ML instance.
Definition Classes
DefaultParamsWritable → MLWritable

Inherited from MLWritable

Value Members

def save(path: String): Unit
Saves this ML instance to the input path, a shortcut of write.save(path).
Saves this ML instance to the input path, a shortcut of write.save(path).
Definition Classes
MLWritable
Annotations
@Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")

Inherited from ALSParams

Value Members

val alpha: DoubleParam
Param for the alpha parameter in the implicit preference formulation (nonnegative).
Param for the alpha parameter in the implicit preference formulation (nonnegative). Default: 1.0
Definition Classes
ALSParams
val finalStorageLevel: Param[String]
Param for StorageLevel for ALS model factors.
Param for StorageLevel for ALS model factors. Pass in a string representation of StorageLevel. Default: "MEMORY_AND_DISK".
Definition Classes
ALSParams
def getAlpha: Double
Definition Classes
ALSParams
def getFinalStorageLevel: String
Definition Classes
ALSParams
def getImplicitPrefs: Boolean
Definition Classes
ALSParams
def getIntermediateStorageLevel: String
Definition Classes
ALSParams
def getNonnegative: Boolean
Definition Classes
ALSParams
def getNumItemBlocks: Int
Definition Classes
ALSParams
def getNumUserBlocks: Int
Definition Classes
ALSParams
def getRank: Int
Definition Classes
ALSParams
def getRatingCol: String
Definition Classes
ALSParams
val implicitPrefs: BooleanParam
Param to decide whether to use implicit preference.
Param to decide whether to use implicit preference. Default: false
Definition Classes
ALSParams
val intermediateStorageLevel: Param[String]
Param for StorageLevel for intermediate datasets.
Param for StorageLevel for intermediate datasets. Pass in a string representation of StorageLevel. Cannot be "NONE". Default: "MEMORY_AND_DISK".
Definition Classes
ALSParams
val nonnegative: BooleanParam
Param for whether to apply nonnegativity constraints.
Param for whether to apply nonnegativity constraints. Default: false
Definition Classes
ALSParams
val numItemBlocks: IntParam
Param for number of item blocks (positive).
Param for number of item blocks (positive). Default: 10
Definition Classes
ALSParams
val numUserBlocks: IntParam
Param for number of user blocks (positive).
Param for number of user blocks (positive). Default: 10
Definition Classes
ALSParams
val rank: IntParam
Param for rank of the matrix factorization (positive).
Param for rank of the matrix factorization (positive). Default: 10
Definition Classes
ALSParams
val ratingCol: Param[String]
Param for the column name for ratings.
Param for the column name for ratings. Default: "rating"
Definition Classes
ALSParams
def validateAndTransformSchema(schema: StructType): StructType
Validates and transforms the input schema.
Validates and transforms the input schema.
schema
input schema
returns
output schema
Attributes
protected
Definition Classes
ALSParams

Inherited from HasSeed

Value Members

final def getSeed: Long
Definition Classes
HasSeed
final val seed: LongParam
Param for random seed.
Param for random seed.
Definition Classes
HasSeed

Inherited from HasCheckpointInterval

Value Members

final val checkpointInterval: IntParam
Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
Param for set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the cache will get checkpointed every 10 iterations. Note: this setting will be ignored if the checkpoint directory is not set in the SparkContext.
Definition Classes
HasCheckpointInterval
final def getCheckpointInterval: Int
Definition Classes
HasCheckpointInterval

Inherited from HasRegParam

Value Members

final def getRegParam: Double
Definition Classes
HasRegParam
final val regParam: DoubleParam
Param for regularization parameter (>= 0).
Param for regularization parameter (>= 0).
Definition Classes
HasRegParam

Inherited from HasMaxIter

Value Members

final def getMaxIter: Int
Definition Classes
HasMaxIter
final val maxIter: IntParam
Param for maximum number of iterations (>= 0).
Param for maximum number of iterations (>= 0).
Definition Classes
HasMaxIter

Inherited from ALSModelParams

Value Members

def checkIntegers(dataset: Dataset[_], colName: String): Column
Attempts to safely cast a user/item id to an Int.
Attempts to safely cast a user/item id to an Int. Throws an exception if the value is out of integer range or contains a fractional part.
Attributes
protected[recommendation]
Definition Classes
ALSModelParams
val coldStartStrategy: Param[String]
Param for strategy for dealing with unknown or new users/items at prediction time.
Param for strategy for dealing with unknown or new users/items at prediction time. This may be useful in cross-validation or production scenarios, for handling user/item ids the model has not seen in the training data. Supported values: - "nan": predicted value for unknown ids will be NaN. - "drop": rows in the input DataFrame containing unknown ids will be dropped from the output DataFrame containing predictions. Default: "nan".
Definition Classes
ALSModelParams
def getColdStartStrategy: String
Definition Classes
ALSModelParams
def getItemCol: String
Definition Classes
ALSModelParams
def getUserCol: String
Definition Classes
ALSModelParams
val itemCol: Param[String]
Param for the column name for item ids.
Param for the column name for item ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "item"
Definition Classes
ALSModelParams
val userCol: Param[String]
Param for the column name for user ids.
Param for the column name for user ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "user"
Definition Classes
ALSModelParams

Inherited from HasBlockSize

Value Members

final val blockSize: IntParam
Param for block size for stacking input data in matrices.
Param for block size for stacking input data in matrices. Data is stacked within partitions. If block size is more than remaining data in a partition then it is adjusted to the size of this data..
Definition Classes
HasBlockSize
final def getBlockSize: Int
Definition Classes
HasBlockSize

Inherited from HasPredictionCol

Value Members

final def getPredictionCol: String
Definition Classes
HasPredictionCol
final val predictionCol: Param[String]
Param for prediction column name.
Param for prediction column name.
Definition Classes
HasPredictionCol

Inherited from Estimator[ALSModel]

Value Members

def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[ALSModel]
Fits multiple models to the input data with multiple sets of parameters.
Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.
dataset
input dataset
paramMaps
An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted models, matching the input parameter maps
Definition Classes
Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], paramMap: ParamMap): ALSModel
Fits a single model to the input data with provided parameter map.
Fits a single model to the input data with provided parameter map.
dataset
input dataset
paramMap
Parameter map. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted model
Definition Classes
Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ALSModel
Fits a single model to the input data with optional parameters.
Fits a single model to the input data with optional parameters.
dataset
input dataset
firstParamPair
the first param pair, overrides embedded params
otherParamPairs
other param pairs. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted model
Definition Classes
Estimator
Annotations
@Since("2.0.0") @varargs()

Inherited from PipelineStage

Value Members

def transformSchema(schema: StructType, logging: Boolean): StructType
Derives the output schema from the input schema and parameters, optionally with logging.
This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.
Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()

Inherited from Logging

Value Members

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit
Attributes
protected
Definition Classes
Logging
def isTraceEnabled(): Boolean
Attributes
protected
Definition Classes
Logging
def log: Logger
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logName: String
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def withLogContext(context: HashMap[String, String])(body: => Unit): Unit
Attributes
protected
Definition Classes
Logging

Inherited from Params

Value Members

final def $[T](param: Param[T]): T
An alias for getOrDefault().
An alias for getOrDefault().
Attributes
protected
Definition Classes
Params
final def clear(param: Param[_]): ALS.this.type
Clears the user-supplied value for the input param.
Clears the user-supplied value for the input param.
Definition Classes
Params
def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
Copies param values from this instance to another instance for params shared by them.
Copies param values from this instance to another instance for params shared by them.
This handles default Params and explicitly set Params separately. Default Params are copied from and to defaultParamMap, and explicitly set Params are copied from and to paramMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.
to
the target instance, which should work with the same set of default Params as this source instance
extra
extra params to be copied to the target's paramMap
returns
the target instance with param values copied
Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T
Default implementation of copy with extra params.
Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.
Attributes
protected
Definition Classes
Params
def explainParam(param: Param[_]): String
Explains a param.
Explains a param.
param
input param, must belong to this instance.
returns
a string that contains the input param name, doc, and optionally its default value and the user-supplied value
Definition Classes
Params
def explainParams(): String
Explains all params of this instance.
Explains all params of this instance. See explainParam().
Definition Classes
Params
final def extractParamMap(): ParamMap
extractParamMap with no extra values.
extractParamMap with no extra values.
Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Definition Classes
Params
final def get[T](param: Param[T]): Option[T]
Optionally returns the user-supplied value of a param.
Optionally returns the user-supplied value of a param.
Definition Classes
Params
final def getDefault[T](param: Param[T]): Option[T]
Gets the default value of a parameter.
Gets the default value of a parameter.
Definition Classes
Params
final def getOrDefault[T](param: Param[T]): T
Gets the value of a param in the embedded param map or its default value.
Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.
Definition Classes
Params
def getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
Definition Classes
Params
final def hasDefault[T](param: Param[T]): Boolean
Tests whether the input param has a default value set.
Tests whether the input param has a default value set.
Definition Classes
Params
def hasParam(paramName: String): Boolean
Tests whether this instance contains a param with a given name.
Tests whether this instance contains a param with a given name.
Definition Classes
Params
final def isDefined(param: Param[_]): Boolean
Checks whether a param is explicitly set or has a default value.
Checks whether a param is explicitly set or has a default value.
Definition Classes
Params
final def isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
Definition Classes
Params
lazy val params: Array[Param[_]]
Returns all params sorted by their names.
Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.
Definition Classes
Params
Note
Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.
final def set(paramPair: ParamPair[_]): ALS.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): ALS.this.type
Sets a parameter (by name) in the embedded param map.
Sets a parameter (by name) in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): ALS.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Definition Classes
Params
final def setDefault(paramPairs: ParamPair[_]*): ALS.this.type
Sets default values for a list of params.
Sets default values for a list of params.
Note: Java developers should use the single-parameter setDefault. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.
paramPairs
a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.
Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): ALS.this.type
Sets a default value for a param.
Sets a default value for a param.
param
param to set the default value. Make sure that this param is initialized before this method gets called.
value
the default value
Attributes
protected[ml]
Definition Classes
Params

Inherited from Identifiable

Value Members

def toString(): String
Definition Classes
Identifiable → AnyRef → Any

Inherited from AnyRef

Value Members

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
final def getClass(): Class[_ <: AnyRef]
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
final def notify(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def synchronized[T0](arg0: => T0): T0
Definition Classes
AnyRef
final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
def finalize(): Unit
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.Throwable]) @Deprecated
Deprecated
(Since version 9)

Inherited from Any

Value Members

final def asInstanceOf[T0]: T0
Definition Classes
Any
final def isInstanceOf[T0]: Boolean
Definition Classes
Any

Parameters

A list of (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

val alpha: DoubleParam
Param for the alpha parameter in the implicit preference formulation (nonnegative).
Param for the alpha parameter in the implicit preference formulation (nonnegative). Default: 1.0
Definition Classes
ALSParams
final val checkpointInterval: IntParam
Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
Param for set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the cache will get checkpointed every 10 iterations. Note: this setting will be ignored if the checkpoint directory is not set in the SparkContext.
Definition Classes
HasCheckpointInterval
val implicitPrefs: BooleanParam
Param to decide whether to use implicit preference.
Param to decide whether to use implicit preference. Default: false
Definition Classes
ALSParams
val itemCol: Param[String]
Param for the column name for item ids.
Param for the column name for item ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "item"
Definition Classes
ALSModelParams
final val maxIter: IntParam
Param for maximum number of iterations (>= 0).
Param for maximum number of iterations (>= 0).
Definition Classes
HasMaxIter
val nonnegative: BooleanParam
Param for whether to apply nonnegativity constraints.
Param for whether to apply nonnegativity constraints. Default: false
Definition Classes
ALSParams
val numItemBlocks: IntParam
Param for number of item blocks (positive).
Param for number of item blocks (positive). Default: 10
Definition Classes
ALSParams
val numUserBlocks: IntParam
Param for number of user blocks (positive).
Param for number of user blocks (positive). Default: 10
Definition Classes
ALSParams
final val predictionCol: Param[String]
Param for prediction column name.
Param for prediction column name.
Definition Classes
HasPredictionCol
val rank: IntParam
Param for rank of the matrix factorization (positive).
Param for rank of the matrix factorization (positive). Default: 10
Definition Classes
ALSParams
val ratingCol: Param[String]
Param for the column name for ratings.
Param for the column name for ratings. Default: "rating"
Definition Classes
ALSParams
final val regParam: DoubleParam
Param for regularization parameter (>= 0).
Param for regularization parameter (>= 0).
Definition Classes
HasRegParam
final val seed: LongParam
Param for random seed.
Param for random seed.
Definition Classes
HasSeed
val userCol: Param[String]
Param for the column name for user ids.
Param for the column name for user ids. Ids must be integers. Other numeric types are supported for this column, but will be cast to integers as long as they fall within the integer value range. Default: "user"
Definition Classes
ALSModelParams

Members

implicit class LogStringContext extends AnyRef
Definition Classes
Logging

final def !=(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def ##: Int
Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T
An alias for getOrDefault().
An alias for getOrDefault().
Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean
Definition Classes
AnyRef → Any
final def asInstanceOf[T0]: T0
Definition Classes
Any
def checkIntegers(dataset: Dataset[_], colName: String): Column
Attempts to safely cast a user/item id to an Int.
Attempts to safely cast a user/item id to an Int. Throws an exception if the value is out of integer range or contains a fractional part.
Attributes
protected[recommendation]
Definition Classes
ALSModelParams
final def clear(param: Param[_]): ALS.this.type
Clears the user-supplied value for the input param.
Clears the user-supplied value for the input param.
Definition Classes
Params
def clone(): AnyRef
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
def copy(extra: ParamMap): ALS
Creates a copy of this instance with the same UID and some extra 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().
Definition Classes
ALS → Estimator → PipelineStage → Params
Annotations
@Since("1.5.0")
def copyValues[T <: Params](to: T, extra: ParamMap = ParamMap.empty): T
Copies param values from this instance to another instance for params shared by them.
Copies param values from this instance to another instance for params shared by them.
This handles default Params and explicitly set Params separately. Default Params are copied from and to defaultParamMap, and explicitly set Params are copied from and to paramMap. Warning: This implicitly assumes that this Params instance and the target instance share the same set of default Params.
to
the target instance, which should work with the same set of default Params as this source instance
extra
extra params to be copied to the target's paramMap
returns
the target instance with param values copied
Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T
Default implementation of copy with extra params.
Default implementation of copy with extra params. It tries to create a new instance with the same UID. Then it copies the embedded and extra parameters over and returns the new instance.
Attributes
protected
Definition Classes
Params
final def eq(arg0: AnyRef): Boolean
Definition Classes
AnyRef
def equals(arg0: AnyRef): Boolean
Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String
Explains a param.
Explains a param.
param
input param, must belong to this instance.
returns
a string that contains the input param name, doc, and optionally its default value and the user-supplied value
Definition Classes
Params
def explainParams(): String
Explains all params of this instance.
Explains all params of this instance. See explainParam().
Definition Classes
Params
final def extractParamMap(): ParamMap
extractParamMap with no extra values.
extractParamMap with no extra values.
Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Extracts the embedded default param values and user-supplied values, and then merges them with extra values from input into a flat param map, where the latter value is used if there exist conflicts, i.e., with ordering: default param values less than user-supplied values less than extra.
Definition Classes
Params
def fit(dataset: Dataset[_]): ALSModel
Fits a model to the input data.
Fits a model to the input data.
Definition Classes
ALS → Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[ALSModel]
Fits multiple models to the input data with multiple sets of parameters.
Fits multiple models to the input data with multiple sets of parameters. The default implementation uses a for loop on each parameter map. Subclasses could override this to optimize multi-model training.
dataset
input dataset
paramMaps
An array of parameter maps. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted models, matching the input parameter maps
Definition Classes
Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], paramMap: ParamMap): ALSModel
Fits a single model to the input data with provided parameter map.
Fits a single model to the input data with provided parameter map.
dataset
input dataset
paramMap
Parameter map. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted model
Definition Classes
Estimator
Annotations
@Since("2.0.0")
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): ALSModel
Fits a single model to the input data with optional parameters.
Fits a single model to the input data with optional parameters.
dataset
input dataset
firstParamPair
the first param pair, overrides embedded params
otherParamPairs
other param pairs. These values override any specified in this Estimator's embedded ParamMap.
returns
fitted model
Definition Classes
Estimator
Annotations
@Since("2.0.0") @varargs()
final def get[T](param: Param[T]): Option[T]
Optionally returns the user-supplied value of a param.
Optionally returns the user-supplied value of a param.
Definition Classes
Params
final def getClass(): Class[_ <: AnyRef]
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
final def getDefault[T](param: Param[T]): Option[T]
Gets the default value of a parameter.
Gets the default value of a parameter.
Definition Classes
Params
final def getOrDefault[T](param: Param[T]): T
Gets the value of a param in the embedded param map or its default value.
Gets the value of a param in the embedded param map or its default value. Throws an exception if neither is set.
Definition Classes
Params
def getParam(paramName: String): Param[Any]
Gets a param by its name.
Gets a param by its name.
Definition Classes
Params
final def hasDefault[T](param: Param[T]): Boolean
Tests whether the input param has a default value set.
Tests whether the input param has a default value set.
Definition Classes
Params
def hasParam(paramName: String): Boolean
Tests whether this instance contains a param with a given name.
Tests whether this instance contains a param with a given name.
Definition Classes
Params
def hashCode(): Int
Definition Classes
AnyRef → Any
Annotations
@IntrinsicCandidate() @native()
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit
Attributes
protected
Definition Classes
Logging
final def isDefined(param: Param[_]): Boolean
Checks whether a param is explicitly set or has a default value.
Checks whether a param is explicitly set or has a default value.
Definition Classes
Params
final def isInstanceOf[T0]: Boolean
Definition Classes
Any
final def isSet(param: Param[_]): Boolean
Checks whether a param is explicitly set.
Checks whether a param is explicitly set.
Definition Classes
Params
def isTraceEnabled(): Boolean
Attributes
protected
Definition Classes
Logging
def log: Logger
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logDebug(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logError(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logError(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logInfo(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logName: String
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logTrace(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry, throwable: Throwable): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(entry: LogEntry): Unit
Attributes
protected
Definition Classes
Logging
def logWarning(msg: => String): Unit
Attributes
protected
Definition Classes
Logging
final def ne(arg0: AnyRef): Boolean
Definition Classes
AnyRef
final def notify(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
final def notifyAll(): Unit
Definition Classes
AnyRef
Annotations
@IntrinsicCandidate() @native()
lazy val params: Array[Param[_]]
Returns all params sorted by their names.
Returns all params sorted by their names. The default implementation uses Java reflection to list all public methods that have no arguments and return Param.
Definition Classes
Params
Note
Developer should not use this method in constructor because we cannot guarantee that this variable gets initialized before other params.
def save(path: String): Unit
Saves this ML instance to the input path, a shortcut of write.save(path).
Saves this ML instance to the input path, a shortcut of write.save(path).
Definition Classes
MLWritable
Annotations
@Since("1.6.0") @throws("If the input path already exists but overwrite is not enabled.")
final def set(paramPair: ParamPair[_]): ALS.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): ALS.this.type
Sets a parameter (by name) in the embedded param map.
Sets a parameter (by name) in the embedded param map.
Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): ALS.this.type
Sets a parameter in the embedded param map.
Sets a parameter in the embedded param map.
Definition Classes
Params
final def setDefault(paramPairs: ParamPair[_]*): ALS.this.type
Sets default values for a list of params.
Sets default values for a list of params.
Note: Java developers should use the single-parameter setDefault. Annotating this with varargs can cause compilation failures due to a Scala compiler bug. See SPARK-9268.
paramPairs
a list of param pairs that specify params and their default values to set respectively. Make sure that the params are initialized before this method gets called.
Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): ALS.this.type
Sets a default value for a param.
Sets a default value for a param.
param
param to set the default value. Make sure that this param is initialized before this method gets called.
value
the default value
Attributes
protected[ml]
Definition Classes
Params
final def synchronized[T0](arg0: => T0): T0
Definition Classes
AnyRef
def toString(): String
Definition Classes
Identifiable → AnyRef → Any
def transformSchema(schema: StructType): StructType
Check transform validity and derive the output schema from the input schema.
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.
Definition Classes
ALS → PipelineStage
Annotations
@Since("1.3.0")
def transformSchema(schema: StructType, logging: Boolean): StructType
Derives the output schema from the input schema and parameters, optionally with logging.
This should be optimistic. If it is unclear whether the schema will be valid, then it should be assumed valid until proven otherwise.
Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String
An immutable unique ID for the object and its derivatives.
An immutable unique ID for the object and its derivatives.
Definition Classes
ALS → Identifiable
Annotations
@Since("1.4.0")
def validateAndTransformSchema(schema: StructType): StructType
Validates and transforms the input schema.
Validates and transforms the input schema.
schema
input schema
returns
output schema
Attributes
protected
Definition Classes
ALSParams
final def wait(arg0: Long, arg1: Int): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
final def wait(arg0: Long): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException]) @native()
final def wait(): Unit
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.InterruptedException])
def withLogContext(context: HashMap[String, String])(body: => Unit): Unit
Attributes
protected
Definition Classes
Logging
def write: MLWriter
Returns an MLWriter instance for this ML instance.
Returns an MLWriter instance for this ML instance.
Definition Classes
DefaultParamsWritable → MLWritable
def finalize(): Unit
Attributes
protected[lang]
Definition Classes
AnyRef
Annotations
@throws(classOf[java.lang.Throwable]) @Deprecated
Deprecated
(Since version 9)

Parameter setters

def setAlpha(value: Double): ALS.this.type
Annotations
@Since("1.3.0")
def setCheckpointInterval(value: Int): ALS.this.type
Annotations
@Since("1.4.0")
def setImplicitPrefs(value: Boolean): ALS.this.type
Annotations
@Since("1.3.0")
def setItemCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
def setMaxIter(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setNonnegative(value: Boolean): ALS.this.type
Annotations
@Since("1.3.0")
def setNumBlocks(value: Int): ALS.this.type
Sets both numUserBlocks and numItemBlocks to the specific value.
Sets both numUserBlocks and numItemBlocks to the specific value.
Annotations
@Since("1.3.0")
def setNumItemBlocks(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setNumUserBlocks(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setPredictionCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
def setRank(value: Int): ALS.this.type
Annotations
@Since("1.3.0")
def setRatingCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")
def setRegParam(value: Double): ALS.this.type
Annotations
@Since("1.3.0")
def setSeed(value: Long): ALS.this.type
Annotations
@Since("1.3.0")
def setUserCol(value: String): ALS.this.type
Annotations
@Since("1.3.0")

Parameter getters

def getAlpha: Double
Definition Classes
ALSParams
final def getCheckpointInterval: Int
Definition Classes
HasCheckpointInterval
def getImplicitPrefs: Boolean
Definition Classes
ALSParams
def getItemCol: String
Definition Classes
ALSModelParams
final def getMaxIter: Int
Definition Classes
HasMaxIter
def getNonnegative: Boolean
Definition Classes
ALSParams
def getNumItemBlocks: Int
Definition Classes
ALSParams
def getNumUserBlocks: Int
Definition Classes
ALSParams
final def getPredictionCol: String
Definition Classes
HasPredictionCol
def getRank: Int
Definition Classes
ALSParams
def getRatingCol: String
Definition Classes
ALSParams
final def getRegParam: Double
Definition Classes
HasRegParam
final def getSeed: Long
Definition Classes
HasSeed
def getUserCol: String
Definition Classes
ALSModelParams

(expert-only) Parameters

A list of advanced, expert-only (hyper-)parameter keys this algorithm can take. Users can set and get the parameter values through setters and getters, respectively.

final val blockSize: IntParam
Param for block size for stacking input data in matrices.
Param for block size for stacking input data in matrices. Data is stacked within partitions. If block size is more than remaining data in a partition then it is adjusted to the size of this data..
Definition Classes
HasBlockSize
val coldStartStrategy: Param[String]
Param for strategy for dealing with unknown or new users/items at prediction time.
Param for strategy for dealing with unknown or new users/items at prediction time. This may be useful in cross-validation or production scenarios, for handling user/item ids the model has not seen in the training data. Supported values: - "nan": predicted value for unknown ids will be NaN. - "drop": rows in the input DataFrame containing unknown ids will be dropped from the output DataFrame containing predictions. Default: "nan".
Definition Classes
ALSModelParams
val finalStorageLevel: Param[String]
Param for StorageLevel for ALS model factors.
Param for StorageLevel for ALS model factors. Pass in a string representation of StorageLevel. Default: "MEMORY_AND_DISK".
Definition Classes
ALSParams
val intermediateStorageLevel: Param[String]
Param for StorageLevel for intermediate datasets.
Param for StorageLevel for intermediate datasets. Pass in a string representation of StorageLevel. Cannot be "NONE". Default: "MEMORY_AND_DISK".
Definition Classes
ALSParams

(expert-only) Parameter setters

def setBlockSize(value: Int): ALS.this.type
Set block size for stacking input data in matrices.
Set block size for stacking input data in matrices. Default is 4096.
Annotations
@Since("3.0.0")
def setColdStartStrategy(value: String): ALS.this.type
Annotations
@Since("2.2.0")
def setFinalStorageLevel(value: String): ALS.this.type
Annotations
@Since("2.0.0")
def setIntermediateStorageLevel(value: String): ALS.this.type
Annotations
@Since("2.0.0")

(expert-only) Parameter getters

final def getBlockSize: Int
Definition Classes
HasBlockSize
def getColdStartStrategy: String
Definition Classes
ALSModelParams
def getFinalStorageLevel: String
Definition Classes
ALSParams
def getIntermediateStorageLevel: String
Definition Classes
ALSParams

Packages

ALS

Companion object ALS

class ALS extends Estimator[ALSModel] with ALSParams with DefaultParamsWritable

Instance Constructors

Type Members

Value Members

Deprecated Value Members

Inherited from DefaultParamsWritable

Value Members

Inherited from MLWritable

Value Members

Inherited from ALSParams

Value Members

Inherited from HasSeed

Value Members

Inherited from HasCheckpointInterval

Value Members

Inherited from HasRegParam

Value Members

Inherited from HasMaxIter

Value Members

Inherited from ALSModelParams

Value Members

Inherited from HasBlockSize

Value Members

Inherited from HasPredictionCol

Value Members

Inherited from Estimator[ALSModel]

Value Members

Inherited from PipelineStage

Value Members

Inherited from Logging

Value Members

Inherited from Params

Value Members

Inherited from Identifiable

Value Members

Inherited from AnyRef

Value Members

Inherited from Any

Value Members

Parameters

Members

Parameter setters

Parameter getters

(expert-only) Parameters

(expert-only) Parameter setters

(expert-only) Parameter getters

ALS