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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.sysds.runtime.instructions.spark;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.sysds.common.Types.DataType;
import org.apache.sysds.common.Types.ValueType;
import org.apache.sysds.lops.SortKeys;
import org.apache.sysds.runtime.DMLRuntimeException;
import org.apache.sysds.runtime.controlprogram.context.ExecutionContext;
import org.apache.sysds.runtime.controlprogram.context.SparkExecutionContext;
import org.apache.sysds.runtime.instructions.InstructionUtils;
import org.apache.sysds.runtime.instructions.cp.CPOperand;
import org.apache.sysds.runtime.instructions.spark.utils.RDDSortUtils;
import org.apache.sysds.runtime.matrix.data.MatrixBlock;
import org.apache.sysds.runtime.matrix.data.MatrixIndexes;
import org.apache.sysds.runtime.meta.DataCharacteristics;
/**
* This class supports two variants of sort operation on a 1-dimensional input matrix.
* The two variants are <code> weighted </code> and <code> unweighted </code>.
* Example instructions:
* sort:mVar1:mVar2 (input=mVar1, output=mVar2)
* sort:mVar1:mVar2:mVar3 (input=mVar1, weights=mVar2, output=mVar3)
*
*/
public class QuantileSortSPInstruction extends UnarySPInstruction {
private QuantileSortSPInstruction(CPOperand in, CPOperand out, String opcode, String istr) {
this(in, null, out, opcode, istr);
}
private QuantileSortSPInstruction(CPOperand in1, CPOperand in2, CPOperand out, String opcode,
String istr) {
super(SPType.QSort, null, in1, in2, out, opcode, istr);
}
public static QuantileSortSPInstruction parseInstruction ( String str ) {
CPOperand in1 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
CPOperand in2 = null;
CPOperand out = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
String opcode = parts[0];
if ( opcode.equalsIgnoreCase(SortKeys.OPCODE) ) {
if ( parts.length == 3 ) {
// Example: sort:mVar1:mVar2 (input=mVar1, output=mVar2)
parseUnaryInstruction(str, in1, out);
return new QuantileSortSPInstruction(in1, out, opcode, str);
}
else if ( parts.length == 4 ) {
// Example: sort:mVar1:mVar2:mVar3 (input=mVar1, weights=mVar2, output=mVar3)
in2 = new CPOperand("", ValueType.UNKNOWN, DataType.UNKNOWN);
parseUnaryInstruction(str, in1, in2, out);
return new QuantileSortSPInstruction(in1, in2, out, opcode, str);
}
else {
throw new DMLRuntimeException("Invalid number of operands in instruction: " + str);
}
}
else {
throw new DMLRuntimeException("Unknown opcode while parsing a SortSPInstruction: " + str);
}
}
@Override
public void processInstruction(ExecutionContext ec) {
SparkExecutionContext sec = (SparkExecutionContext)ec;
boolean weighted = (input2 != null);
//get input rdds
JavaPairRDD<MatrixIndexes,MatrixBlock> in = sec.getBinaryMatrixBlockRDDHandleForVariable( input1.getName() );
JavaPairRDD<MatrixIndexes,MatrixBlock> inW = weighted ? sec.getBinaryMatrixBlockRDDHandleForVariable( input2.getName() ) : null;
DataCharacteristics mc = sec.getDataCharacteristics(input1.getName());
JavaPairRDD<MatrixIndexes,MatrixBlock> out = null;
long clen = -1;
if( !weighted ) { //W/O WEIGHTS (default)
out = RDDSortUtils.sortByVal(in, mc.getRows(), mc.getBlocksize());
clen = 1;
}
else { //W/ WEIGHTS
out = RDDSortUtils.sortByVal(in, inW, mc.getRows(), mc.getBlocksize());
clen = 2;
}
//put output RDD handle into symbol table
sec.setRDDHandleForVariable(output.getName(), out);
sec.addLineageRDD(output.getName(), input1.getName());
if( weighted )
sec.addLineageRDD(output.getName(), input2.getName());
//update output matrix characteristics
DataCharacteristics mcOut = sec.getDataCharacteristics(output.getName());
mcOut.set(mc.getRows(), clen, mc.getBlocksize(), mc.getBlocksize());
}
}