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Declarative Machine Learning
/*
* 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.sysml.runtime.matrix;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.controlprogram.ParForProgramBlock.PDataPartitionFormat;
import org.apache.sysml.runtime.controlprogram.caching.MatrixObject;
import org.apache.sysml.runtime.controlprogram.parfor.DataPartitioner;
import org.apache.sysml.runtime.controlprogram.parfor.DataPartitionerRemoteMR;
import org.apache.sysml.runtime.instructions.Instruction;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.instructions.MRJobInstruction;
import org.apache.sysml.runtime.matrix.mapred.DistributedCacheInput;
public class DataPartitionMR
{
private DataPartitionMR() {
//prevent instantiation via private constructor
}
public static JobReturn runJob(MRJobInstruction jobinst, MatrixObject[] inputMatrices, String shuffleInst, byte[] resultIndices, MatrixObject[] outputMatrices, int numReducers, int replication) throws DMLRuntimeException {
MatrixCharacteristics[] sts = new MatrixCharacteristics[outputMatrices.length];
processPartitionInstructions(shuffleInst, inputMatrices, resultIndices, outputMatrices, numReducers, replication, sts);
JobReturn ret = new JobReturn(sts, true);
return ret;
}
private static void processPartitionInstructions(String shuffleInst, MatrixObject[] inputMatrices, byte[] resultIndices, MatrixObject[] outputMatrices, int numReducers, int replication, MatrixCharacteristics[] sts) throws DMLRuntimeException {
int i=0;
for(String inst : shuffleInst.split(Instruction.INSTRUCTION_DELIM)) {
if( InstructionUtils.getOpCode(inst).equalsIgnoreCase("partition") ) {
//long begin = System.currentTimeMillis();
String[] parts = InstructionUtils.getInstructionParts(inst);
int input_index = Integer.parseInt(parts[1]);
int output_index = Integer.parseInt(parts[2]);
MatrixObject in = inputMatrices[input_index];
MatrixObject out = outputMatrices[findResultIndex(resultIndices, output_index)];
PDataPartitionFormat pformat = PDataPartitionFormat.valueOf(parts[3]);
long rlen = in.getNumRows();
long clen = in.getNumColumns();
long brlen = in.getNumRowsPerBlock();
long bclen = in.getNumColumnsPerBlock();
long N = -1;
switch( pformat )
{
case ROW_BLOCK_WISE_N:
{
long numRowBlocks = (long)Math.ceil(((double)DistributedCacheInput.PARTITION_SIZE)/clen/brlen);
N = numRowBlocks * brlen;
break;
}
case COLUMN_BLOCK_WISE_N:
{
long numColBlocks = (long)Math.ceil(((double)DistributedCacheInput.PARTITION_SIZE)/rlen/bclen);
N = numColBlocks * bclen;
break;
}
default:
throw new DMLRuntimeException("Unsupported partition format for distributed cache input: "+pformat);
}
DataPartitioner dpart = new DataPartitionerRemoteMR(pformat, (int)N, -1, numReducers, replication, 4, false, true);
out = dpart.createPartitionedMatrixObject(in, out, true);
sts[i] = out.getMatrixCharacteristics();
i++;
}
}
}
private static int findResultIndex(byte[] resultIndices, int output_index) {
for(int i=0; i < resultIndices.length; i++) {
if(resultIndices[i] == output_index)
return i;
}
return -1;
}
}