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From mengxr <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-3974][MLlib] Distributed Block Matrix A...
Date Tue, 27 Jan 2015 02:02:08 GMT
Github user mengxr commented on a diff in the pull request:

    https://github.com/apache/spark/pull/3200#discussion_r23582384
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/BlockMatrix.scala
---
    @@ -0,0 +1,242 @@
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *    http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.mllib.linalg.distributed
    +
    +import breeze.linalg.{DenseMatrix => BDM}
    +
    +import org.apache.spark.{Logging, Partitioner}
    +import org.apache.spark.mllib.linalg._
    +import org.apache.spark.mllib.rdd.RDDFunctions._
    +import org.apache.spark.rdd.RDD
    +import org.apache.spark.storage.StorageLevel
    +
    +/**
    + * A grid partitioner, which stores every block in a separate partition.
    + *
    + * @param numRowBlocks Number of blocks that form the rows of the matrix.
    + * @param numColBlocks Number of blocks that form the columns of the matrix.
    + */
    +private[mllib] class GridPartitioner(
    +    val numRowBlocks: Int,
    +    val numColBlocks: Int,
    +    val numParts: Int) extends Partitioner {
    +  // Having the number of partitions greater than the number of sub matrices does not
help
    +  override val numPartitions = math.min(numParts, numRowBlocks * numColBlocks)
    +
    +  /**
    +   * Returns the index of the partition the SubMatrix belongs to. Tries to achieve block
wise
    +   * partitioning.
    +   *
    +   * @param key The key for the SubMatrix. Can be its position in the grid (its column
major index)
    +   *            or a tuple of three integers that are the final row index after the multiplication,
    +   *            the index of the block to multiply with, and the final column index after
the
    +   *            multiplication.
    +   * @return The index of the partition, which the SubMatrix belongs to.
    +   */
    +  override def getPartition(key: Any): Int = {
    +    key match {
    +      case (blockRowIndex: Int, blockColIndex: Int) =>
    +        getBlockId(blockRowIndex, blockColIndex)
    +      case (blockRowIndex: Int, innerIndex: Int, blockColIndex: Int) =>
    +        getBlockId(blockRowIndex, blockColIndex)
    +      case _ =>
    +        throw new IllegalArgumentException(s"Unrecognized key. key: $key")
    +    }
    +  }
    +
    +  /** Partitions sub-matrices as blocks with neighboring sub-matrices. */
    +  private def getBlockId(blockRowIndex: Int, blockColIndex: Int): Int = {
    +    val totalBlocks = numRowBlocks * numColBlocks
    +    // Gives the number of blocks that need to be in each partition
    +    val partitionRatio = math.ceil(totalBlocks * 1.0 / numPartitions).toInt
    +    // Number of neighboring blocks to take in each row
    +    val subBlocksPerRow = math.ceil(numRowBlocks * 1.0 / partitionRatio).toInt
    +    // Number of neighboring blocks to take in each column
    +    val subBlocksPerCol = math.ceil(numColBlocks * 1.0 / partitionRatio).toInt
    +    // Coordinates of the block
    +    val i = blockRowIndex / subBlocksPerRow
    +    val j = blockColIndex / subBlocksPerCol
    +    val blocksPerRow = math.ceil(numRowBlocks * 1.0 / subBlocksPerRow).toInt
    +    j * blocksPerRow + i
    +  }
    +
    +  /** Checks whether the partitioners have the same characteristics */
    +  override def equals(obj: Any): Boolean = {
    +    obj match {
    +      case r: GridPartitioner =>
    +        (this.numRowBlocks == r.numRowBlocks) && (this.numColBlocks == r.numColBlocks)
&&
    +          (this.numPartitions == r.numPartitions)
    +      case _ =>
    +        false
    +    }
    +  }
    +}
    +
    +/**
    + * Represents a distributed matrix in blocks of local matrices.
    + *
    + * @param rdd The RDD of SubMatrices (local matrices) that form this matrix
    + * @param nRows Number of rows of this matrix
    + * @param nCols Number of columns of this matrix
    + * @param numRowBlocks Number of blocks that form the rows of this matrix
    + * @param numColBlocks Number of blocks that form the columns of this matrix
    + * @param rowsPerBlock Number of rows that make up each block. The blocks forming the
final
    + *                     rows are not required to have the given number of rows
    + * @param colsPerBlock Number of columns that make up each block. The blocks forming
the final
    + *                     columns are not required to have the given number of columns
    + */
    +class BlockMatrix(
    +    val rdd: RDD[((Int, Int), Matrix)],
    +    private var nRows: Long,
    +    private var nCols: Long,
    +    val numRowBlocks: Int,
    +    val numColBlocks: Int,
    +    val rowsPerBlock: Int,
    +    val colsPerBlock: Int) extends DistributedMatrix with Logging {
    +
    +  private type SubMatrix = ((Int, Int), Matrix) // ((blockRowIndex, blockColIndex), matrix)
    +
    +  /**
    +   * Alternate constructor for BlockMatrix without the input of the number of rows and
columns.
    +   *
    +   * @param rdd The RDD of SubMatrices (local matrices) that form this matrix
    +   * @param numRowBlocks Number of blocks that form the rows of this matrix
    +   * @param numColBlocks Number of blocks that form the columns of this matrix
    +   * @param rowsPerBlock Number of rows that make up each block. The blocks forming the
final
    +   *                     rows are not required to have the given number of rows
    +   * @param colsPerBlock Number of columns that make up each block. The blocks forming
the final
    +   *                     columns are not required to have the given number of columns
    +   */
    +  def this(
    +      rdd: RDD[((Int, Int), Matrix)],
    +      numRowBlocks: Int,
    +      numColBlocks: Int,
    +      rowsPerBlock: Int,
    +      colsPerBlock: Int) = {
    +    this(rdd, 0L, 0L, numRowBlocks, numColBlocks, rowsPerBlock, colsPerBlock)
    +  }
    +
    +  private[mllib] var partitioner: GridPartitioner =
    +    new GridPartitioner(numRowBlocks, numColBlocks, rdd.partitions.length)
    +
    +  private lazy val dims: (Long, Long) = getDim
    +
    +  override def numRows(): Long = {
    +    if (nRows <= 0L) nRows = dims._1
    +    nRows
    +  }
    +
    +  override def numCols(): Long = {
    +    if (nCols <= 0L) nCols = dims._2
    +    nCols
    +  }
    +
    +  /** Returns the dimensions of the matrix. */
    +  private def getDim: (Long, Long) = {
    +    case class MatrixMetaData(var rowIndex: Int, var colIndex: Int,
    +        var numRows: Int, var numCols: Int)
    +    // picks the sizes of the matrix with the maximum indices
    +    def pickSizeByGreaterIndex(example: MatrixMetaData, base: MatrixMetaData): MatrixMetaData
= {
    +      if (example.rowIndex > base.rowIndex) {
    +        base.rowIndex = example.rowIndex
    +        base.numRows = example.numRows
    +      }
    +      if (example.colIndex > base.colIndex) {
    +        base.colIndex = example.colIndex
    +        base.numCols = example.numCols
    +      }
    +      base
    +    }
    +
    +    // Aggregate will return an error if the rdd is empty
    +    val lastRowCol = rdd.treeAggregate(new MatrixMetaData(0, 0, 0, 0))(
    +      seqOp = (c, v) => (c, v) match { case (base, ((blockXInd, blockYInd), mat))
=>
    +        pickSizeByGreaterIndex(
    +          new MatrixMetaData(blockXInd, blockYInd, mat.numRows, mat.numCols), base)
    +      },
    +      combOp = (c1, c2) => (c1, c2) match {
    +        case (res1, res2) =>
    +          pickSizeByGreaterIndex(res1, res2)
    +      })
    +    // We add the size of the edge matrices, because they can be less than the specified
    +    // rowsPerBlock or colsPerBlock.
    +    (lastRowCol.rowIndex.toLong * rowsPerBlock + lastRowCol.numRows,
    +      lastRowCol.colIndex.toLong * colsPerBlock + lastRowCol.numCols)
    +  }
    +
    +  /** Returns the Frobenius Norm of the matrix */
    +  def normFro(): Double = {
    --- End diff --
    
    Remove this function. We can add it back later.


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