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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.instructions.mr;
import java.util.ArrayList;
import org.apache.sysml.lops.PartialAggregate.CorrectionLocationType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.DMLUnsupportedOperationException;
import org.apache.sysml.runtime.functionobjects.KahanPlus;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.matrix.MatrixCharacteristics;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.MatrixIndexes;
import org.apache.sysml.runtime.matrix.data.MatrixValue;
import org.apache.sysml.runtime.matrix.data.OperationsOnMatrixValues;
import org.apache.sysml.runtime.matrix.mapred.CachedValueMap;
import org.apache.sysml.runtime.matrix.mapred.DistributedCacheInput;
import org.apache.sysml.runtime.matrix.mapred.IndexedMatrixValue;
import org.apache.sysml.runtime.matrix.mapred.MRBaseForCommonInstructions;
import org.apache.sysml.runtime.matrix.operators.AggregateOperator;
import org.apache.sysml.runtime.matrix.operators.Operator;
public class GroupedAggregateMInstruction extends BinaryMRInstructionBase implements IDistributedCacheConsumer
{
private int _ngroups = -1;
public GroupedAggregateMInstruction(Operator op, byte in1, byte in2, byte out, int ngroups, String istr)
{
super(op, in1, in2, out);
_ngroups = ngroups;
}
/**
*
* @param str
* @return
* @throws DMLRuntimeException
*/
public static GroupedAggregateMInstruction parseInstruction ( String str )
throws DMLRuntimeException
{
String[] parts = InstructionUtils.getInstructionParts ( str );
InstructionUtils.checkNumFields(parts, 5);
byte in1 = Byte.parseByte(parts[1]);
byte in2 = Byte.parseByte(parts[2]);
byte out = Byte.parseByte(parts[3]);
int ngroups = Integer.parseInt(parts[4]);
//partitioning ignored
Operator op = new AggregateOperator(0, KahanPlus.getKahanPlusFnObject(), true, CorrectionLocationType.LASTCOLUMN);
return new GroupedAggregateMInstruction(op, in1, in2, out, ngroups, str);
}
@Override
public void processInstruction(Class valueClass,
CachedValueMap cachedValues, IndexedMatrixValue tempValue, IndexedMatrixValue zeroInput,
int blockRowFactor, int blockColFactor)
throws DMLUnsupportedOperationException, DMLRuntimeException
{
ArrayList blkList = cachedValues.get(input1);
if( blkList == null )
return;
for(IndexedMatrixValue in1 : blkList)
{
if(in1 == null)
continue;
DistributedCacheInput dcInput = MRBaseForCommonInstructions.dcValues.get(input2);
//get all inputs
MatrixIndexes ix = in1.getIndexes();
MatrixBlock groups = (MatrixBlock)dcInput.getDataBlock((int)ix.getRowIndex(), 1).getValue();
//output blocked result
int brlen = dcInput.getNumRowsPerBlock();
int bclen = dcInput.getNumColsPerBlock();
//execute map grouped aggregate operations
ArrayList outlist = new ArrayList();
OperationsOnMatrixValues.performMapGroupedAggregate(getOperator(), in1, groups, _ngroups, brlen, bclen, outlist);
//output all result blocks
for( IndexedMatrixValue out : outlist ) {
cachedValues.add(output, out);
}
}
}
@Override //IDistributedCacheConsumer
public boolean isDistCacheOnlyIndex( String inst, byte index )
{
return (index==input2 && index!=input1);
}
@Override //IDistributedCacheConsumer
public void addDistCacheIndex( String inst, ArrayList indexes )
{
indexes.add(input2);
}
public void computeOutputCharacteristics(MatrixCharacteristics mcIn, MatrixCharacteristics mcOut) {
mcOut.set(_ngroups, mcIn.getCols(), mcIn.getRowsPerBlock(), mcIn.getColsPerBlock());
}
}