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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.spark;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.Function2;
import scala.Tuple2;
import org.apache.sysml.parser.Expression.DataType;
import org.apache.sysml.parser.Expression.ValueType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.DMLUnsupportedOperationException;
import org.apache.sysml.runtime.controlprogram.context.ExecutionContext;
import org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext;
import org.apache.sysml.runtime.functionobjects.COV;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.instructions.cp.CM_COV_Object;
import org.apache.sysml.runtime.instructions.cp.CPOperand;
import org.apache.sysml.runtime.instructions.cp.DoubleObject;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.MatrixIndexes;
import org.apache.sysml.runtime.matrix.operators.COVOperator;
/**
*
*/
public class CovarianceSPInstruction extends BinarySPInstruction
{
public CovarianceSPInstruction(COVOperator op, CPOperand in, CPOperand in2, CPOperand out,
String opcode, String istr)
{
super(op, in, in2, out, opcode, istr);
}
public CovarianceSPInstruction(COVOperator op, CPOperand in, CPOperand in2, CPOperand in3, CPOperand out,
String opcode, String istr)
{
super(op, in, in2, out, opcode, istr);
}
/**
*
* @param str
* @return
* @throws DMLRuntimeException
*/
public static CovarianceSPInstruction parseInstruction(String str)
throws DMLRuntimeException
{
CPOperand in1 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
CPOperand in2 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
CPOperand in3 = null;
CPOperand out = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
String opcode = parts[0];
if( !opcode.equalsIgnoreCase("cov") ) {
throw new DMLRuntimeException("CovarianceCPInstruction.parseInstruction():: Unknown opcode " + opcode);
}
COVOperator cov = new COVOperator(COV.getCOMFnObject());
if ( parts.length == 4 ) {
// CP.cov.mVar0.mVar1.mVar2
parseBinaryInstruction(str, in1, in2, out);
return new CovarianceSPInstruction(cov, in1, in2, out, opcode, str);
} else if ( parts.length == 5 ) {
// CP.cov.mVar0.mVar1.mVar2.mVar3
in3 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
parseBinaryInstruction(str, in1, in2, in3, out);
return new CovarianceSPInstruction(cov, in1, in2, in3, out, opcode, str);
}
else {
throw new DMLRuntimeException("Invalid number of arguments in Instruction: " + str);
}
}
@Override
public void processInstruction( ExecutionContext ec )
throws DMLRuntimeException, DMLUnsupportedOperationException
{
SparkExecutionContext sec = (SparkExecutionContext)ec;
COVOperator cop = ((COVOperator)_optr);
//get input
JavaPairRDD in1 = sec.getBinaryBlockRDDHandleForVariable( input1.getName() );
JavaPairRDD in2 = sec.getBinaryBlockRDDHandleForVariable( input2.getName() );
//process central moment instruction
CM_COV_Object cmobj = null;
if( input3 == null ) //w/o weights
{
cmobj = in1.join( in2 )
.values().map(new RDDCOVFunction(cop))
.reduce(new RDDCOVReduceFunction(cop));
}
else //with weights
{
JavaPairRDD in3 = sec.getBinaryBlockRDDHandleForVariable( input3.getName() );
cmobj = in1.join( in2 )
.join( in3 )
.values().map(new RDDCOVWeightsFunction(cop))
.reduce(new RDDCOVReduceFunction(cop));
}
//create scalar output (no lineage information required)
double val = cmobj.getRequiredResult(_optr);
DoubleObject ret = new DoubleObject(output.getName(), val);
ec.setScalarOutput(output.getName(), ret);
}
/**
*
*/
private static class RDDCOVFunction implements Function, CM_COV_Object>
{
private static final long serialVersionUID = -9088449969750217519L;
private COVOperator _op = null;
public RDDCOVFunction( COVOperator op ) {
_op = op;
}
@Override
public CM_COV_Object call(Tuple2 arg0)
throws Exception
{
MatrixBlock input1 = arg0._1();
MatrixBlock input2 = arg0._2();
//execute cov operations
return input1.covOperations(_op, input2);
}
}
/**
*
*/
private static class RDDCOVWeightsFunction implements Function,MatrixBlock>, CM_COV_Object>
{
private static final long serialVersionUID = 1945166819152577077L;
private COVOperator _op = null;
public RDDCOVWeightsFunction( COVOperator op ) {
_op = op;
}
@Override
public CM_COV_Object call(Tuple2,MatrixBlock> arg0)
throws Exception
{
MatrixBlock input1 = arg0._1()._1();
MatrixBlock input2 = arg0._1()._2();
MatrixBlock weights = arg0._2();
//execute cov operations
return input1.covOperations(_op, input2, weights);
}
}
/**
*
*/
private static class RDDCOVReduceFunction implements Function2
{
private static final long serialVersionUID = 1118102911706607118L;
private COVOperator _op = null;
public RDDCOVReduceFunction( COVOperator op ) {
_op = op;
}
@Override
public CM_COV_Object call(CM_COV_Object arg0, CM_COV_Object arg1)
throws Exception
{
CM_COV_Object out = new CM_COV_Object();
//execute cov combine operations
_op.fn.execute(out, arg0);
_op.fn.execute(out, arg1);
return out;
}
}
}