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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.lops;
import org.apache.sysml.lops.LopProperties.ExecLocation;
import org.apache.sysml.lops.LopProperties.ExecType;
import org.apache.sysml.lops.ParameterizedBuiltin.OperationTypes;
import org.apache.sysml.lops.compile.JobType;
import org.apache.sysml.parser.DataExpression;
import org.apache.sysml.parser.Expression.DataType;
import org.apache.sysml.parser.Expression.ValueType;
import org.apache.sysml.parser.ParameterizedBuiltinFunctionExpression;
/**
* Lop to convert CSV data into SystemML data format (TextCell, BinaryCell, or BinaryBlock)
*/
public class CSVReBlock extends Lop
{
public static final String OPCODE = "csvrblk";
Long rows_per_block;
Long cols_per_block;
public CSVReBlock(Lop input, Long rows_per_block, Long cols_per_block, DataType dt, ValueType vt, ExecType et) throws LopsException
{
super(Lop.Type.CSVReBlock, dt, vt);
this.addInput(input);
input.addOutput(this);
this.rows_per_block = rows_per_block;
this.cols_per_block = cols_per_block;
/*
* This lop can be executed only in CSVREBLOCK job.
*/
boolean breaksAlignment = false;
boolean aligner = false;
boolean definesMRJob = true;
// If the input to reblock is a tranform, then piggyback it along with transform
if ( input instanceof ParameterizedBuiltin
&& ((ParameterizedBuiltin)input).getOp() == OperationTypes.TRANSFORM )
{
definesMRJob = false;
lps.addCompatibility(JobType.TRANSFORM);
}
else
{
lps.addCompatibility(JobType.CSV_REBLOCK);
}
if(et == ExecType.MR) {
this.lps.setProperties( inputs, ExecType.MR, ExecLocation.MapAndReduce, breaksAlignment, aligner, definesMRJob );
}
else if(et == ExecType.SPARK) {
this.lps.setProperties( inputs, ExecType.SPARK, ExecLocation.ControlProgram, breaksAlignment, aligner, definesMRJob );
}
else {
throw new LopsException("Incorrect execution type for CSVReblock:" + et);
}
}
@Override
public String toString() {
return "CSVReblock - rows per block = " + rows_per_block + " cols per block " + cols_per_block ;
}
private String prepCSVProperties() throws LopsException {
StringBuilder sb = new StringBuilder();
boolean isSparkTransformInput = false;
Data dataInput = null;
if(getInputs().get(0).getType() == Type.Data)
dataInput = (Data)getInputs().get(0);
else if ( getInputs().get(0).getType() == Type.ParameterizedBuiltin && ((ParameterizedBuiltin)getInputs().get(0)).getOp() == OperationTypes.TRANSFORM) {
isSparkTransformInput = (getExecType() == ExecType.SPARK);
dataInput = (Data) ((ParameterizedBuiltin)getInputs().get(0)).getNamedInput(ParameterizedBuiltinFunctionExpression.TF_FN_PARAM_DATA);
}
Lop headerLop = dataInput.getNamedInputLop(DataExpression.DELIM_HAS_HEADER_ROW);
Lop delimLop = dataInput.getNamedInputLop(DataExpression.DELIM_DELIMITER);
Lop fillLop = dataInput.getNamedInputLop(DataExpression.DELIM_FILL);
Lop fillValueLop = dataInput.getNamedInputLop(DataExpression.DELIM_FILL_VALUE);
if (headerLop.isVariable())
throw new LopsException(this.printErrorLocation()
+ "Parameter " + DataExpression.DELIM_HAS_HEADER_ROW
+ " must be a literal.");
if (delimLop.isVariable())
throw new LopsException(this.printErrorLocation()
+ "Parameter " + DataExpression.DELIM_DELIMITER
+ " must be a literal.");
if (fillLop.isVariable())
throw new LopsException(this.printErrorLocation()
+ "Parameter " + DataExpression.DELIM_FILL
+ " must be a literal.");
if (fillValueLop.isVariable())
throw new LopsException(this.printErrorLocation()
+ "Parameter " + DataExpression.DELIM_FILL_VALUE
+ " must be a literal.");
// Output from transform() does not have a header
// On MR, reblock is piggybacked along with transform, and hence
// specific information about header needn't be passed through instruction
sb.append( ((Data)headerLop).getBooleanValue() && !isSparkTransformInput );
sb.append( OPERAND_DELIMITOR );
sb.append( ((Data)delimLop).getStringValue() );
sb.append( OPERAND_DELIMITOR );
sb.append( ((Data)fillLop).getBooleanValue() );
sb.append( OPERAND_DELIMITOR );
sb.append( ((Data)fillValueLop).getDoubleValue() );
return sb.toString();
}
@Override
public String getInstructions(int input_index, int output_index) throws LopsException
{
StringBuilder sb = new StringBuilder();
sb.append( getExecType() );
sb.append( Lop.OPERAND_DELIMITOR );
sb.append( OPCODE );
sb.append( OPERAND_DELIMITOR );
Lop input = getInputs().get(0);
sb.append( input.prepInputOperand(input_index) );
sb.append( OPERAND_DELIMITOR );
sb.append( this.prepOutputOperand(output_index) );
sb.append( OPERAND_DELIMITOR );
sb.append( rows_per_block );
sb.append( OPERAND_DELIMITOR );
sb.append( cols_per_block );
sb.append( OPERAND_DELIMITOR );
sb.append( prepCSVProperties() );
return sb.toString();
}
@Override
public String getInstructions(String input1, String output) throws LopsException {
if(getExecType() != ExecType.SPARK) {
throw new LopsException("The method getInstructions(String,String) for CSVReblock should be called only for Spark execution type");
}
if (this.getInputs().size() == 1) {
StringBuilder sb = new StringBuilder();
sb.append( getExecType() );
sb.append( Lop.OPERAND_DELIMITOR );
sb.append( OPCODE );
sb.append( OPERAND_DELIMITOR );
sb.append( getInputs().get(0).prepInputOperand(input1));
sb.append( OPERAND_DELIMITOR );
sb.append( this.prepOutputOperand(output));
sb.append( OPERAND_DELIMITOR );
sb.append( rows_per_block );
sb.append( OPERAND_DELIMITOR );
sb.append( cols_per_block );
sb.append( OPERAND_DELIMITOR );
sb.append( prepCSVProperties() );
return sb.toString();
} else {
throw new LopsException(this.printErrorLocation() + "Invalid number of operands ("
+ this.getInputs().size() + ") for CSVReblock operation");
}
}
}