use of org.apache.sysml.runtime.instructions.spark.functions.CopyFrameBlockPairFunction in project incubator-systemml by apache.
the class FrameConverterTest method runConverter.
@SuppressWarnings("unchecked")
private static void runConverter(ConvType type, MatrixCharacteristics mc, MatrixCharacteristics mcMatrix, List<ValueType> schema, String fnameIn, String fnameOut) throws IOException {
SparkExecutionContext sec = (SparkExecutionContext) ExecutionContextFactory.createContext();
JavaSparkContext sc = sec.getSparkContext();
ValueType[] lschema = schema.toArray(new ValueType[0]);
MapReduceTool.deleteFileIfExistOnHDFS(fnameOut);
switch(type) {
case CSV2BIN:
{
InputInfo iinfo = InputInfo.CSVInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<LongWritable, Text> rddIn = (JavaPairRDD<LongWritable, Text>) sc.hadoopFile(fnameIn, iinfo.inputFormatClass, iinfo.inputKeyClass, iinfo.inputValueClass);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.csvToBinaryBlock(sc, rddIn, mc, null, false, separator, false, 0).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2CSV:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
JavaPairRDD<LongWritable, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class);
JavaPairRDD<Long, FrameBlock> rddIn2 = rddIn.mapToPair(new CopyFrameBlockPairFunction(false));
CSVFileFormatProperties fprop = new CSVFileFormatProperties();
JavaRDD<String> rddOut = FrameRDDConverterUtils.binaryBlockToCsv(rddIn2, mc, fprop, true);
rddOut.saveAsTextFile(fnameOut);
break;
}
case TXTCELL2BIN:
{
InputInfo iinfo = InputInfo.TextCellInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<LongWritable, Text> rddIn = (JavaPairRDD<LongWritable, Text>) sc.hadoopFile(fnameIn, iinfo.inputFormatClass, iinfo.inputKeyClass, iinfo.inputValueClass);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.textCellToBinaryBlock(sc, rddIn, mc, lschema).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2TXTCELL:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
JavaPairRDD<LongWritable, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class);
JavaPairRDD<Long, FrameBlock> rddIn2 = rddIn.mapToPair(new CopyFrameBlockPairFunction(false));
JavaRDD<String> rddOut = FrameRDDConverterUtils.binaryBlockToTextCell(rddIn2, mc);
rddOut.saveAsTextFile(fnameOut);
break;
}
case MAT2BIN:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<MatrixIndexes, MatrixBlock> rddIn = (JavaPairRDD<MatrixIndexes, MatrixBlock>) sc.hadoopFile(fnameIn, iinfo.inputFormatClass, iinfo.inputKeyClass, iinfo.inputValueClass);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.matrixBlockToBinaryBlock(sc, rddIn, mcMatrix);
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2MAT:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<Long, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class).mapToPair(new LongWritableFrameToLongFrameFunction());
JavaPairRDD<MatrixIndexes, MatrixBlock> rddOut = FrameRDDConverterUtils.binaryBlockToMatrixBlock(rddIn, mc, mcMatrix);
rddOut.saveAsHadoopFile(fnameOut, MatrixIndexes.class, MatrixBlock.class, oinfo.outputFormatClass);
break;
}
case DFRM2BIN:
{
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
// Create DataFrame
SparkSession sparkSession = SparkSession.builder().sparkContext(sc.sc()).getOrCreate();
StructType dfSchema = FrameRDDConverterUtils.convertFrameSchemaToDFSchema(lschema, false);
JavaRDD<Row> rowRDD = FrameRDDConverterUtils.csvToRowRDD(sc, fnameIn, separator, lschema);
Dataset<Row> df = sparkSession.createDataFrame(rowRDD, dfSchema);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.dataFrameToBinaryBlock(sc, df, mc, false).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2DFRM:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<Long, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class).mapToPair(new LongWritableFrameToLongFrameFunction());
SparkSession sparkSession = SparkSession.builder().sparkContext(sc.sc()).getOrCreate();
Dataset<Row> df = FrameRDDConverterUtils.binaryBlockToDataFrame(sparkSession, rddIn, mc, lschema);
// Convert back DataFrame to binary block for comparison using original binary to converted DF and back to binary
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.dataFrameToBinaryBlock(sc, df, mc, true).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
default:
throw new RuntimeException("Unsuported converter type: " + type.toString());
}
sec.close();
}
use of org.apache.sysml.runtime.instructions.spark.functions.CopyFrameBlockPairFunction in project incubator-systemml by apache.
the class SparkExecutionContext method getRDDHandleForFrameObject.
/**
* FIXME: currently this implementation assumes matrix representations but frame signature
* in order to support the old transform implementation.
*
* @param fo frame object
* @param inputInfo input info
* @return JavaPairRDD handle for a frame object
*/
@SuppressWarnings("unchecked")
public JavaPairRDD<?, ?> getRDDHandleForFrameObject(FrameObject fo, InputInfo inputInfo) {
// NOTE: MB this logic should be integrated into FrameObject
// However, for now we cannot assume that spark libraries are
// always available and hence only store generic references in
// matrix object while all the logic is in the SparkExecContext
InputInfo inputInfo2 = (inputInfo == InputInfo.BinaryBlockInputInfo) ? InputInfo.BinaryBlockFrameInputInfo : inputInfo;
JavaSparkContext sc = getSparkContext();
JavaPairRDD<?, ?> rdd = null;
// rdd operations if already executed and cached
if (fo.getRDDHandle() != null && (fo.getRDDHandle().isCheckpointRDD() || !fo.isCached(false))) {
// return existing rdd handling (w/o input format change)
rdd = fo.getRDDHandle().getRDD();
} else // CASE 2: dirty in memory data or cached result of rdd operations
if (fo.isDirty() || fo.isCached(false)) {
// get in-memory matrix block and parallelize it
// w/ guarded parallelize (fallback to export, rdd from file if too large)
MatrixCharacteristics mc = fo.getMatrixCharacteristics();
boolean fromFile = false;
if (!OptimizerUtils.checkSparkCollectMemoryBudget(mc, 0) || !_parRDDs.reserve(OptimizerUtils.estimatePartitionedSizeExactSparsity(mc))) {
if (fo.isDirty()) {
// write only if necessary
fo.exportData();
}
rdd = sc.hadoopFile(fo.getFileName(), inputInfo2.inputFormatClass, inputInfo2.inputKeyClass, inputInfo2.inputValueClass);
// cp is workaround for read bug
rdd = ((JavaPairRDD<LongWritable, FrameBlock>) rdd).mapToPair(new CopyFrameBlockPairFunction());
fromFile = true;
} else {
// default case
// pin frame in memory
FrameBlock fb = fo.acquireRead();
rdd = toFrameJavaPairRDD(sc, fb);
// unpin frame
fo.release();
_parRDDs.registerRDD(rdd.id(), OptimizerUtils.estimatePartitionedSizeExactSparsity(mc), true);
}
// keep rdd handle for future operations on it
RDDObject rddhandle = new RDDObject(rdd);
rddhandle.setHDFSFile(fromFile);
fo.setRDDHandle(rddhandle);
} else // CASE 3: non-dirty (file exists on HDFS)
{
// For binary block, these are: SequenceFileInputFormat.class, MatrixIndexes.class, MatrixBlock.class
if (inputInfo2 == InputInfo.BinaryBlockFrameInputInfo) {
rdd = sc.hadoopFile(fo.getFileName(), inputInfo2.inputFormatClass, inputInfo2.inputKeyClass, inputInfo2.inputValueClass);
// note: this copy is still required in Spark 1.4 because spark hands out whatever the inputformat
// recordreader returns; the javadoc explicitly recommend to copy all key/value pairs
// cp is workaround for read bug
rdd = ((JavaPairRDD<LongWritable, FrameBlock>) rdd).mapToPair(new CopyFrameBlockPairFunction());
} else if (inputInfo2 == InputInfo.TextCellInputInfo || inputInfo2 == InputInfo.CSVInputInfo || inputInfo2 == InputInfo.MatrixMarketInputInfo) {
rdd = sc.hadoopFile(fo.getFileName(), inputInfo2.inputFormatClass, inputInfo2.inputKeyClass, inputInfo2.inputValueClass);
// cp is workaround for read bug
rdd = ((JavaPairRDD<LongWritable, Text>) rdd).mapToPair(new CopyTextInputFunction());
} else if (inputInfo2 == InputInfo.BinaryCellInputInfo) {
throw new DMLRuntimeException("Binarycell not supported for frames.");
} else {
throw new DMLRuntimeException("Incorrect input format in getRDDHandleForVariable");
}
// keep rdd handle for future operations on it
RDDObject rddhandle = new RDDObject(rdd);
rddhandle.setHDFSFile(true);
fo.setRDDHandle(rddhandle);
}
return rdd;
}
use of org.apache.sysml.runtime.instructions.spark.functions.CopyFrameBlockPairFunction in project systemml by apache.
the class SparkExecutionContext method getRDDHandleForFrameObject.
/**
* FIXME: currently this implementation assumes matrix representations but frame signature
* in order to support the old transform implementation.
*
* @param fo frame object
* @param inputInfo input info
* @return JavaPairRDD handle for a frame object
*/
@SuppressWarnings("unchecked")
public JavaPairRDD<?, ?> getRDDHandleForFrameObject(FrameObject fo, InputInfo inputInfo) {
// NOTE: MB this logic should be integrated into FrameObject
// However, for now we cannot assume that spark libraries are
// always available and hence only store generic references in
// matrix object while all the logic is in the SparkExecContext
InputInfo inputInfo2 = (inputInfo == InputInfo.BinaryBlockInputInfo) ? InputInfo.BinaryBlockFrameInputInfo : inputInfo;
JavaSparkContext sc = getSparkContext();
JavaPairRDD<?, ?> rdd = null;
// rdd operations if already executed and cached
if (fo.getRDDHandle() != null && (fo.getRDDHandle().isCheckpointRDD() || !fo.isCached(false))) {
// return existing rdd handling (w/o input format change)
rdd = fo.getRDDHandle().getRDD();
} else // CASE 2: dirty in memory data or cached result of rdd operations
if (fo.isDirty() || fo.isCached(false)) {
// get in-memory matrix block and parallelize it
// w/ guarded parallelize (fallback to export, rdd from file if too large)
MatrixCharacteristics mc = fo.getMatrixCharacteristics();
boolean fromFile = false;
if (!OptimizerUtils.checkSparkCollectMemoryBudget(mc, 0) || !_parRDDs.reserve(OptimizerUtils.estimatePartitionedSizeExactSparsity(mc))) {
if (fo.isDirty()) {
// write only if necessary
fo.exportData();
}
rdd = sc.hadoopFile(fo.getFileName(), inputInfo2.inputFormatClass, inputInfo2.inputKeyClass, inputInfo2.inputValueClass);
// cp is workaround for read bug
rdd = ((JavaPairRDD<LongWritable, FrameBlock>) rdd).mapToPair(new CopyFrameBlockPairFunction());
fromFile = true;
} else {
// default case
// pin frame in memory
FrameBlock fb = fo.acquireRead();
rdd = toFrameJavaPairRDD(sc, fb);
// unpin frame
fo.release();
_parRDDs.registerRDD(rdd.id(), OptimizerUtils.estimatePartitionedSizeExactSparsity(mc), true);
}
// keep rdd handle for future operations on it
RDDObject rddhandle = new RDDObject(rdd);
rddhandle.setHDFSFile(fromFile);
fo.setRDDHandle(rddhandle);
} else // CASE 3: non-dirty (file exists on HDFS)
{
// For binary block, these are: SequenceFileInputFormat.class, MatrixIndexes.class, MatrixBlock.class
if (inputInfo2 == InputInfo.BinaryBlockFrameInputInfo) {
rdd = sc.hadoopFile(fo.getFileName(), inputInfo2.inputFormatClass, inputInfo2.inputKeyClass, inputInfo2.inputValueClass);
// note: this copy is still required in Spark 1.4 because spark hands out whatever the inputformat
// recordreader returns; the javadoc explicitly recommend to copy all key/value pairs
// cp is workaround for read bug
rdd = ((JavaPairRDD<LongWritable, FrameBlock>) rdd).mapToPair(new CopyFrameBlockPairFunction());
} else if (inputInfo2 == InputInfo.TextCellInputInfo || inputInfo2 == InputInfo.CSVInputInfo || inputInfo2 == InputInfo.MatrixMarketInputInfo) {
rdd = sc.hadoopFile(fo.getFileName(), inputInfo2.inputFormatClass, inputInfo2.inputKeyClass, inputInfo2.inputValueClass);
// cp is workaround for read bug
rdd = ((JavaPairRDD<LongWritable, Text>) rdd).mapToPair(new CopyTextInputFunction());
} else if (inputInfo2 == InputInfo.BinaryCellInputInfo) {
throw new DMLRuntimeException("Binarycell not supported for frames.");
} else {
throw new DMLRuntimeException("Incorrect input format in getRDDHandleForVariable");
}
// keep rdd handle for future operations on it
RDDObject rddhandle = new RDDObject(rdd);
rddhandle.setHDFSFile(true);
fo.setRDDHandle(rddhandle);
}
return rdd;
}
use of org.apache.sysml.runtime.instructions.spark.functions.CopyFrameBlockPairFunction in project systemml by apache.
the class FrameConverterTest method runConverter.
@SuppressWarnings("unchecked")
private static void runConverter(ConvType type, MatrixCharacteristics mc, MatrixCharacteristics mcMatrix, List<ValueType> schema, String fnameIn, String fnameOut) throws IOException {
SparkExecutionContext sec = (SparkExecutionContext) ExecutionContextFactory.createContext();
JavaSparkContext sc = sec.getSparkContext();
ValueType[] lschema = schema.toArray(new ValueType[0]);
MapReduceTool.deleteFileIfExistOnHDFS(fnameOut);
switch(type) {
case CSV2BIN:
{
InputInfo iinfo = InputInfo.CSVInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<LongWritable, Text> rddIn = (JavaPairRDD<LongWritable, Text>) sc.hadoopFile(fnameIn, iinfo.inputFormatClass, iinfo.inputKeyClass, iinfo.inputValueClass);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.csvToBinaryBlock(sc, rddIn, mc, null, false, separator, false, 0).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2CSV:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
JavaPairRDD<LongWritable, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class);
JavaPairRDD<Long, FrameBlock> rddIn2 = rddIn.mapToPair(new CopyFrameBlockPairFunction(false));
CSVFileFormatProperties fprop = new CSVFileFormatProperties();
JavaRDD<String> rddOut = FrameRDDConverterUtils.binaryBlockToCsv(rddIn2, mc, fprop, true);
rddOut.saveAsTextFile(fnameOut);
break;
}
case TXTCELL2BIN:
{
InputInfo iinfo = InputInfo.TextCellInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<LongWritable, Text> rddIn = (JavaPairRDD<LongWritable, Text>) sc.hadoopFile(fnameIn, iinfo.inputFormatClass, iinfo.inputKeyClass, iinfo.inputValueClass);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.textCellToBinaryBlock(sc, rddIn, mc, lschema).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2TXTCELL:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
JavaPairRDD<LongWritable, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class);
JavaPairRDD<Long, FrameBlock> rddIn2 = rddIn.mapToPair(new CopyFrameBlockPairFunction(false));
JavaRDD<String> rddOut = FrameRDDConverterUtils.binaryBlockToTextCell(rddIn2, mc);
rddOut.saveAsTextFile(fnameOut);
break;
}
case MAT2BIN:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<MatrixIndexes, MatrixBlock> rddIn = (JavaPairRDD<MatrixIndexes, MatrixBlock>) sc.hadoopFile(fnameIn, iinfo.inputFormatClass, iinfo.inputKeyClass, iinfo.inputValueClass);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.matrixBlockToBinaryBlock(sc, rddIn, mcMatrix);
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2MAT:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<Long, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class).mapToPair(new LongWritableFrameToLongFrameFunction());
JavaPairRDD<MatrixIndexes, MatrixBlock> rddOut = FrameRDDConverterUtils.binaryBlockToMatrixBlock(rddIn, mc, mcMatrix);
rddOut.saveAsHadoopFile(fnameOut, MatrixIndexes.class, MatrixBlock.class, oinfo.outputFormatClass);
break;
}
case DFRM2BIN:
{
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
// Create DataFrame
SparkSession sparkSession = SparkSession.builder().sparkContext(sc.sc()).getOrCreate();
StructType dfSchema = FrameRDDConverterUtils.convertFrameSchemaToDFSchema(lschema, false);
JavaRDD<Row> rowRDD = FrameRDDConverterUtils.csvToRowRDD(sc, fnameIn, separator, lschema);
Dataset<Row> df = sparkSession.createDataFrame(rowRDD, dfSchema);
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.dataFrameToBinaryBlock(sc, df, mc, false).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
case BIN2DFRM:
{
InputInfo iinfo = InputInfo.BinaryBlockInputInfo;
OutputInfo oinfo = OutputInfo.BinaryBlockOutputInfo;
JavaPairRDD<Long, FrameBlock> rddIn = sc.hadoopFile(fnameIn, iinfo.inputFormatClass, LongWritable.class, FrameBlock.class).mapToPair(new LongWritableFrameToLongFrameFunction());
SparkSession sparkSession = SparkSession.builder().sparkContext(sc.sc()).getOrCreate();
Dataset<Row> df = FrameRDDConverterUtils.binaryBlockToDataFrame(sparkSession, rddIn, mc, lschema);
// Convert back DataFrame to binary block for comparison using original binary to converted DF and back to binary
JavaPairRDD<LongWritable, FrameBlock> rddOut = FrameRDDConverterUtils.dataFrameToBinaryBlock(sc, df, mc, true).mapToPair(new LongFrameToLongWritableFrameFunction());
rddOut.saveAsHadoopFile(fnameOut, LongWritable.class, FrameBlock.class, oinfo.outputFormatClass);
break;
}
default:
throw new RuntimeException("Unsuported converter type: " + type.toString());
}
sec.close();
}
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