ALS

Type Members

class BlockIDGenerator extends Serializable
class BlockIDPartitioner extends Partitioner[Int]
case class BlockRating(ratings: Array[(Array[Int], Array[Double])]) extends Product with Serializable
case class BlockedFactorization(userFactors: DataSet[(Int, Array[Array[Double]])], itemFactors: DataSet[(Int, Array[Array[Double]])]) extends Product with Serializable
case class Factorization(userFactors: DataSet[Factors], itemFactors: DataSet[Factors]) extends Product with Serializable
case class Factors(id: Long, factors: Array[Double]) extends Product with Serializable

Latent factor model vector
case class InBlockInformation(elementIDs: Array[Long], ratingsForBlock: Array[BlockRating]) extends Product with Serializable
case class OutBlockInformation(elementIDs: Array[Long], outLinks: OutLinks) extends Product with Serializable
class OutLinks extends Value
case class Rating(user: Long, item: Long, rating: Double) extends Product with Serializable

Representation of a user-item rating
Representation of a user-item rating
user
User ID of the rating user
item
Item iD of the rated item
rating
Rating value

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
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final def ##(): Int

Definition Classes
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final def ==(arg0: Any): Boolean

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object Blocks extends Parameter[Int] with Product with Serializable
val ITEM_FACTORS_FILE: String
object Iterations extends Parameter[Int] with Product with Serializable
object Lambda extends Parameter[Double] with Product with Serializable
object NumFactors extends Parameter[Int] with Product with Serializable
object Seed extends Parameter[Long] with Product with Serializable
object TemporaryPath extends Parameter[String] with Product with Serializable
val USER_FACTORS_FILE: String
def apply(): ALS
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
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Annotations
@throws( ... )
def createBlockInformation(userBlocks: Int, itemBlocks: Int, ratings: DataSet[(Int, Rating)], blockIDPartitioner: BlockIDPartitioner): (DataSet[(Int, InBlockInformation)], DataSet[(Int, OutBlockInformation)])

Creates the meta information needed to route the item and user vectors to the respective user and item blocks.
Creates the meta information needed to route the item and user vectors to the respective user and item blocks. * @param userBlocks
def createInBlockInformation(ratings: DataSet[(Int, Rating)], usersPerBlock: DataSet[(Int, Array[Long])], blockIDGenerator: BlockIDGenerator): DataSet[(Int, InBlockInformation)]

Creates the incoming block information
Creates the incoming block information
Creates for every user block the incoming block information. The incoming block information contains the userIDs of the users in the respective block and for every item block a BlockRating instance. The BlockRating instance describes for every incoming set of item vectors of an item block, which user rated these items and what the rating was. For that purpose it contains for every incoming item vector a tuple of an id array us and a rating array rs. The array us contains the indices of the users having rated the respective item vector with the ratings in rs.
def createOutBlockInformation(ratings: DataSet[(Int, Rating)], usersPerBlock: DataSet[(Int, Array[Long])], itemBlocks: Int, blockIDGenerator: BlockIDGenerator): DataSet[(Int, OutBlockInformation)]

Creates the outgoing block information
Creates the outgoing block information
Creates for every user block the outgoing block information. The out block information contains for every item block a scala.collection.mutable.BitSet which indicates which user vector has to be sent to this block. If a vector v has to be sent to a block b, then bitsets(b)'s bit v is set to 1, otherwise 0. Additionally the user IDataSet are replaced by the user vector's index value.
def createUsersPerBlock(ratings: DataSet[(Int, Rating)]): DataSet[(Int, Array[Long])]

Calculates the userIDs in ascending order of each user block
final def eq(arg0: AnyRef): Boolean

Definition Classes
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def equals(arg0: Any): Boolean

Definition Classes
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def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
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Annotations
@throws( classOf[java.lang.Throwable] )
implicit val fitALS: FitOperation[ALS, (Long, Long, Double)]

Calculates the matrix factorization for the given ratings.
Calculates the matrix factorization for the given ratings. A rating is defined as a tuple of user ID, item ID and the corresponding rating.
returns
Factorization containing the user and item matrix
implicit val fitALSInt: FitOperation[ALS, (Int, Int, Double)]
def generateFullMatrix(triangularMatrix: Array[Double], fullMatrix: Array[Double], factors: Int): Unit
def generateRandomMatrix(users: DataSet[Int], factors: Int, seed: Long): DataSet[Factors]
final def getClass(): Class[_]

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def hashCode(): Int

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final def isInstanceOf[T0]: Boolean

Definition Classes
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final def ne(arg0: AnyRef): Boolean

Definition Classes
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final def notify(): Unit

Definition Classes
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final def notifyAll(): Unit

Definition Classes
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def outerProduct(vector: Array[Double], matrix: Array[Double], factors: Int): Unit
implicit val predictRating: PredictDataSetOperation[ALS, (Long, Long), (Long, Long, Double)]

Predict operation which calculates the matrix entry for the given indices
implicit val predictRatingInt: PredictDataSetOperation[ALS, (Int, Int), (Int, Int, Double)]
def randomFactors(factors: Int, random: Random): Array[Double]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
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def toString(): String

Definition Classes
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def unblock(users: DataSet[(Int, Array[Array[Double]])], outInfo: DataSet[(Int, OutBlockInformation)], blockIDPartitioner: BlockIDPartitioner): DataSet[Factors]

Unblocks the blocked user and item matrix representation so that it is at DataSet of column vectors.
def updateFactors(numUserBlocks: Int, items: DataSet[(Int, Array[Array[Double]])], itemOut: DataSet[(Int, OutBlockInformation)], userIn: DataSet[(Int, InBlockInformation)], factors: Int, lambda: Double, blockIDPartitioner: Partitioner[Int]): DataSet[(Int, Array[Array[Double]])]

Calculates a single half step of the ALS optimization.
Calculates a single half step of the ALS optimization. The result is the new value for either the user or item matrix, depending with which matrix the method was called.
numUserBlocks
Number of blocks in the respective dimension
items
Fixed matrix value for the half step
itemOut
Out information to know where to send the vectors
userIn
In information for the cogroup step
factors
Number of latent factors
lambda
Regularization constant
blockIDPartitioner
Custom Flink partitioner
returns
New value for the optimized matrix (either user or item)
final def wait(): Unit

Definition Classes
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Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
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Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
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Annotations
@throws( ... )

Related Docs: class ALS | package recommendation

object ALS

Type Members

class BlockIDGenerator extends Serializable

class BlockIDPartitioner extends Partitioner[Int]

case class BlockRating(ratings: Array[(Array[Int], Array[Double])]) extends Product with Serializable

case class BlockedFactorization(userFactors: DataSet[(Int, Array[Array[Double]])], itemFactors: DataSet[(Int, Array[Array[Double]])]) extends Product with Serializable

case class Factorization(userFactors: DataSet[Factors], itemFactors: DataSet[Factors]) extends Product with Serializable

case class Factors(id: Long, factors: Array[Double]) extends Product with Serializable

case class InBlockInformation(elementIDs: Array[Long], ratingsForBlock: Array[BlockRating]) extends Product with Serializable

case class OutBlockInformation(elementIDs: Array[Long], outLinks: OutLinks) extends Product with Serializable

class OutLinks extends Value

case class Rating(user: Long, item: Long, rating: Double) extends Product with Serializable

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

object Blocks extends Parameter[Int] with Product with Serializable

val ITEM_FACTORS_FILE: String

object Iterations extends Parameter[Int] with Product with Serializable

object Lambda extends Parameter[Double] with Product with Serializable

object NumFactors extends Parameter[Int] with Product with Serializable

object Seed extends Parameter[Long] with Product with Serializable

object TemporaryPath extends Parameter[String] with Product with Serializable

val USER_FACTORS_FILE: String

def apply(): ALS

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def createBlockInformation(userBlocks: Int, itemBlocks: Int, ratings: DataSet[(Int, Rating)], blockIDPartitioner: BlockIDPartitioner): (DataSet[(Int, InBlockInformation)], DataSet[(Int, OutBlockInformation)])

def createInBlockInformation(ratings: DataSet[(Int, Rating)], usersPerBlock: DataSet[(Int, Array[Long])], blockIDGenerator: BlockIDGenerator): DataSet[(Int, InBlockInformation)]

def createOutBlockInformation(ratings: DataSet[(Int, Rating)], usersPerBlock: DataSet[(Int, Array[Long])], itemBlocks: Int, blockIDGenerator: BlockIDGenerator): DataSet[(Int, OutBlockInformation)]

def createUsersPerBlock(ratings: DataSet[(Int, Rating)]): DataSet[(Int, Array[Long])]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

implicit val fitALS: FitOperation[ALS, (Long, Long, Double)]

implicit val fitALSInt: FitOperation[ALS, (Int, Int, Double)]

def generateFullMatrix(triangularMatrix: Array[Double], fullMatrix: Array[Double], factors: Int): Unit

def generateRandomMatrix(users: DataSet[Int], factors: Int, seed: Long): DataSet[Factors]

final def getClass(): Class[_]

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def outerProduct(vector: Array[Double], matrix: Array[Double], factors: Int): Unit

implicit val predictRating: PredictDataSetOperation[ALS, (Long, Long), (Long, Long, Double)]

implicit val predictRatingInt: PredictDataSetOperation[ALS, (Int, Int), (Int, Int, Double)]

def randomFactors(factors: Int, random: Random): Array[Double]

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

def unblock(users: DataSet[(Int, Array[Array[Double]])], outInfo: DataSet[(Int, OutBlockInformation)], blockIDPartitioner: BlockIDPartitioner): DataSet[Factors]

def updateFactors(numUserBlocks: Int, items: DataSet[(Int, Array[Array[Double]])], itemOut: DataSet[(Int, OutBlockInformation)], userIn: DataSet[(Int, InBlockInformation)], factors: Int, lambda: Double, blockIDPartitioner: Partitioner[Int]): DataSet[(Int, Array[Array[Double]])]

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

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