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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.mapred;
import java.io.IOException;
import java.util.HashMap;
import java.util.Iterator;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.sysml.runtime.functionobjects.CM;
import org.apache.sysml.runtime.functionobjects.KahanPlus;
import org.apache.sysml.runtime.instructions.cp.CM_COV_Object;
import org.apache.sysml.runtime.instructions.cp.KahanObject;
import org.apache.sysml.runtime.instructions.mr.GroupedAggregateInstruction;
import org.apache.sysml.runtime.matrix.data.TaggedMatrixIndexes;
import org.apache.sysml.runtime.matrix.data.WeightedCell;
import org.apache.sysml.runtime.matrix.operators.AggregateOperator;
import org.apache.sysml.runtime.matrix.operators.CMOperator;
import org.apache.sysml.runtime.matrix.operators.Operator;
public class GroupedAggMRCombiner extends ReduceBase
implements Reducer
{
//grouped aggregate instructions
private HashMap grpaggInstructions = new HashMap();
//reused intermediate objects
private CM_COV_Object cmObj = new CM_COV_Object();
private HashMap cmFn = new HashMap();
private WeightedCell outCell = new WeightedCell();
@Override
public void reduce(TaggedMatrixIndexes key, Iterator values,
OutputCollector out, Reporter reporter)
throws IOException
{
long start = System.currentTimeMillis();
//get aggregate operator
GroupedAggregateInstruction ins = grpaggInstructions.get(key.getTag());
Operator op = ins.getOperator();
boolean isPartialAgg = true;
//combine iterator to single value
try
{
if(op instanceof CMOperator) //everything except sum
{
if( ((CMOperator) op).isPartialAggregateOperator() )
{
cmObj.reset();
CM lcmFn = cmFn.get(key.getTag());
//partial aggregate cm operator
while( values.hasNext() )
{
WeightedCell value=values.next();
lcmFn.execute(cmObj, value.getValue(), value.getWeight());
}
outCell.setValue(cmObj.getRequiredPartialResult(op));
outCell.setWeight(cmObj.getWeight());
}
else //forward tuples to reducer
{
isPartialAgg = false;
while( values.hasNext() )
out.collect(key, values.next());
}
}
else if(op instanceof AggregateOperator) //sum
{
AggregateOperator aggop=(AggregateOperator) op;
if( aggop.correctionExists )
{
KahanObject buffer=new KahanObject(aggop.initialValue, 0);
KahanPlus.getKahanPlusFnObject();
//partial aggregate with correction
while( values.hasNext() )
{
WeightedCell value=values.next();
aggop.increOp.fn.execute(buffer, value.getValue()*value.getWeight());
}
outCell.setValue(buffer._sum);
outCell.setWeight(1);
}
else //no correction
{
double v = aggop.initialValue;
//partial aggregate without correction
while(values.hasNext())
{
WeightedCell value=values.next();
v=aggop.increOp.fn.execute(v, value.getValue()*value.getWeight());
}
outCell.setValue(v);
outCell.setWeight(1);
}
}
else
throw new IOException("Unsupported operator in instruction: " + ins);
}
catch(Exception ex)
{
throw new IOException(ex);
}
//collect the output (to reducer)
if( isPartialAgg )
out.collect(key, outCell);
reporter.incrCounter(Counters.COMBINE_OR_REDUCE_TIME, System.currentTimeMillis()-start);
}
@Override
public void configure(JobConf job)
{
try
{
GroupedAggregateInstruction[] grpaggIns = MRJobConfiguration.getGroupedAggregateInstructions(job);
if( grpaggIns != null )
for(GroupedAggregateInstruction ins : grpaggIns)
{
grpaggInstructions.put(ins.output, ins);
if( ins.getOperator() instanceof CMOperator )
cmFn.put(ins.output, CM.getCMFnObject(((CMOperator)ins.getOperator()).getAggOpType()));
}
}
catch (Exception e)
{
throw new RuntimeException(e);
}
}
@Override
public void close()
{
//do nothing, overrides unnecessary handling in superclass
}
}