org.apache.mahout.flinkbindings.blas.FlinkOpAtB.scala Maven / Gradle / Ivy

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/**
 * 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.mahout.flinkbindings.blas

import java.lang.Iterable

import com.google.common.collect.Lists
import org.apache.flink.api.common.functions.{FlatMapFunction, GroupReduceFunction}
import org.apache.flink.api.scala._
import org.apache.flink.util.Collector
import org.apache.mahout.flinkbindings._
import org.apache.mahout.flinkbindings.drm.{BlockifiedFlinkDrm, FlinkDrm}
import org.apache.mahout.math.{Matrix, Vector}
import org.apache.mahout.math.drm._
import org.apache.mahout.math.drm.logical.OpAtB
import org.apache.mahout.math.scalabindings.RLikeOps._

import scala.collection.JavaConverters.asScalaBufferConverter

/**
 * Implementation of Flink A' * B
 */
object FlinkOpAtB {

  def notZippable[A](op: OpAtB[A], At: FlinkDrm[A], B: FlinkDrm[A]): FlinkDrm[Int] = {
    val rowsAt = At.asRowWise.ds.asInstanceOf[DrmDataSet[A]]
    val rowsB = B.asRowWise.ds.asInstanceOf[DrmDataSet[A]]
    val joined = rowsAt.join(rowsB).where(0).equalTo(0)

    val ncol = op.ncol
    val nrow = op.nrow.toInt
    val blockHeight = 10
    val blockCount = safeToNonNegInt((nrow - 1) / blockHeight + 1)

    val preProduct: DataSet[(Int, Matrix)] =
             joined.flatMap(new FlatMapFunction[((A, Vector), (A, Vector)), (Int, Matrix)] {
      def flatMap(in: ((A, Vector), (A, Vector)), out: Collector[(Int, Matrix)]): Unit = {
        val avec = in._1._2
        val bvec = in._2._2

        0.until(blockCount) map { blockKey =>
          val blockStart = blockKey * blockHeight
          val blockEnd = Math.min(nrow, blockStart + blockHeight)

          val outer = avec(blockStart until blockEnd) cross bvec
          out.collect(blockKey -> outer)
          out
        }
      }
    })

    val res: BlockifiedDrmDataSet[Int] = 
      preProduct.groupBy(0).reduceGroup(
        new GroupReduceFunction[(Int, Matrix), BlockifiedDrmTuple[Int]] {
          def reduce(values: Iterable[(Int, Matrix)], out: Collector[BlockifiedDrmTuple[Int]]): Unit = {
            val it = Lists.newArrayList(values).asScala
            val (idx, _) = it.head

            val block = it.map { t => t._2 }.reduce { (m1, m2) => m1 + m2 }

            val blockStart = idx * blockHeight
            val keys = Array.tabulate(block.nrow)(blockStart + _)

            out.collect(keys -> block)
          }
        }
      )

    new BlockifiedFlinkDrm[Int](res, ncol)
  }

}