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* 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
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*
* 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
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package org.apache.sysml.runtime.instructions.spark;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.storage.StorageLevel;
import org.apache.sysml.hops.OptimizerUtils;
import org.apache.sysml.lops.Checkpoint;
import org.apache.sysml.parser.Expression.DataType;
import org.apache.sysml.runtime.DMLRuntimeException;
import org.apache.sysml.runtime.controlprogram.caching.CacheableData;
import org.apache.sysml.runtime.controlprogram.context.ExecutionContext;
import org.apache.sysml.runtime.controlprogram.context.SparkExecutionContext;
import org.apache.sysml.runtime.instructions.InstructionUtils;
import org.apache.sysml.runtime.instructions.cp.BooleanObject;
import org.apache.sysml.runtime.instructions.cp.CPOperand;
import org.apache.sysml.runtime.instructions.spark.data.RDDObject;
import org.apache.sysml.runtime.instructions.spark.functions.CopyFrameBlockFunction;
import org.apache.sysml.runtime.instructions.spark.functions.CreateSparseBlockFunction;
import org.apache.sysml.runtime.instructions.spark.utils.SparkUtils;
import org.apache.sysml.runtime.matrix.MatrixCharacteristics;
import org.apache.sysml.runtime.matrix.data.InputInfo;
import org.apache.sysml.runtime.matrix.data.FrameBlock;
import org.apache.sysml.runtime.matrix.data.MatrixBlock;
import org.apache.sysml.runtime.matrix.data.MatrixIndexes;
import org.apache.sysml.runtime.matrix.data.SparseBlock;
import org.apache.sysml.runtime.matrix.operators.Operator;
public class CheckpointSPInstruction extends UnarySPInstruction
{
//default storage level
private StorageLevel _level = null;
public CheckpointSPInstruction(Operator op, CPOperand in, CPOperand out, StorageLevel level, String opcode, String istr) {
super(op, in, out, opcode, istr);
_sptype = SPINSTRUCTION_TYPE.Checkpoint;
_level = level;
}
public static CheckpointSPInstruction parseInstruction ( String str )
throws DMLRuntimeException
{
String[] parts = InstructionUtils.getInstructionPartsWithValueType(str);
InstructionUtils.checkNumFields(parts, 3);
String opcode = parts[0];
CPOperand in = new CPOperand(parts[1]);
CPOperand out = new CPOperand(parts[2]);
StorageLevel level = StorageLevel.fromString(parts[3]);
return new CheckpointSPInstruction(null, in, out, level, opcode, str);
}
@Override
@SuppressWarnings("unchecked")
public void processInstruction(ExecutionContext ec)
throws DMLRuntimeException
{
SparkExecutionContext sec = (SparkExecutionContext)ec;
// Step 1: early abort on non-existing inputs
// -------
// (checkpoints are generated for all read only variables in loops; due to unbounded scoping and
// conditional control flow they to not necessarily exist in the symbol table during runtime -
// this is valid if relevant branches are never entered)
if( sec.getVariable( input1.getName() ) == null || sec.getVariable( input1.getName() ) instanceof BooleanObject) {
//add a dummy entry to the input, which will be immediately overwritten by the null output.
sec.setVariable( input1.getName(), new BooleanObject(false));
sec.setVariable( output.getName(), new BooleanObject(false));
return;
}
//get input rdd handle (for matrix or frame)
JavaPairRDD<?,?> in = sec.getRDDHandleForVariable( input1.getName(), InputInfo.BinaryBlockInputInfo );
MatrixCharacteristics mcIn = sec.getMatrixCharacteristics( input1.getName() );
// Step 2: Checkpoint given rdd (only if currently in different storage level to prevent redundancy)
// -------
// Note that persist is an transformation which will be triggered on-demand with the next rdd operations
// This prevents unnecessary overhead if the dataset is only consumed by cp operations.
JavaPairRDD<?,?> out = null;
if( !in.getStorageLevel().equals( _level ) )
{
//(trigger coalesce if intended number of partitions exceeded by 20%
//and not hash partitioned to avoid losing the existing partitioner)
int numPartitions = SparkUtils.getNumPreferredPartitions(mcIn, in);
boolean coalesce = ( 1.2*numPartitions < in.getNumPartitions()
&& !SparkUtils.isHashPartitioned(in) );
//checkpoint pre-processing rdd operations
if( coalesce ) {
//merge partitions without shuffle if too many partitions
out = in.coalesce( numPartitions );
}
else {
//since persist is an in-place marker for a storage level, we
//apply a narrow shallow copy to allow for short-circuit collects
if( input1.getDataType() == DataType.MATRIX )
out = SparkUtils.copyBinaryBlockMatrix(
(JavaPairRDD<MatrixIndexes,MatrixBlock>)in, false);
else if( input1.getDataType() == DataType.FRAME)
out = ((JavaPairRDD<Long,FrameBlock>)in)
.mapValues(new CopyFrameBlockFunction(false));
}
//convert mcsr into memory-efficient csr if potentially sparse
if( input1.getDataType()==DataType.MATRIX
&& OptimizerUtils.checkSparseBlockCSRConversion(mcIn)
&& !_level.equals(Checkpoint.SER_STORAGE_LEVEL) )
{
out = ((JavaPairRDD<MatrixIndexes,MatrixBlock>)out)
.mapValues(new CreateSparseBlockFunction(SparseBlock.Type.CSR));
}
//actual checkpoint into given storage level
out = out.persist( _level );
}
else {
out = in; //pass-through
}
// Step 3: In-place update of input matrix/frame rdd handle and set as output
// -------
// We use this in-place approach for two reasons. First, it is correct because our checkpoint
// injection rewrites guarantee that after checkpoint instructions there are no consumers on the
// given input. Second, it is beneficial because otherwise we need to pass in-memory objects and
// filenames to the new matrix object in order to prevent repeated reads from hdfs and unnecessary
// caching and subsequent collects. Note that in-place update requires us to explicitly handle
// lineage information in order to prevent cycles on cleanup.
CacheableData<?> cd = sec.getCacheableData( input1.getName() );
if( out != in ) { //prevent unnecessary lineage info
RDDObject inro = cd.getRDDHandle(); //guaranteed to exist (see above)
RDDObject outro = new RDDObject(out, output.getName()); //create new rdd object
outro.setCheckpointRDD(true); //mark as checkpointed
outro.addLineageChild(inro); //keep lineage to prevent cycles on cleanup
cd.setRDDHandle(outro);
}
sec.setVariable( output.getName(), cd);
}
}