Examples with DMLRuntimeException org.apache.sysml.runtime.DMLRuntimeException used on opensource projects

Example 61 with DMLRuntimeException

use of org.apache.sysml.runtime.DMLRuntimeException in project incubator-systemml by apache.

the class RandSPInstruction method generateSequence.

private void generateSequence(SparkExecutionContext sec) {
    double lfrom = sec.getScalarInput(seq_from).getDoubleValue();
    double lto = sec.getScalarInput(seq_to).getDoubleValue();
    double lincr = sec.getScalarInput(seq_incr).getDoubleValue();
    // sanity check valid increment
    if (lincr == 0) {
        throw new DMLRuntimeException("ERROR: While performing seq(" + lfrom + "," + lto + "," + lincr + ")");
    }
    // handle default 1 to -1 for special case of from>to
    lincr = LibMatrixDatagen.updateSeqIncr(lfrom, lto, lincr);
    if (LOG.isTraceEnabled())
        LOG.trace("Process RandSPInstruction seq with seqFrom=" + lfrom + ", seqTo=" + lto + ", seqIncr" + lincr);
    // step 1: offset generation
    JavaRDD<Double> offsetsRDD = null;
    long nnz = UtilFunctions.getSeqLength(lfrom, lto, lincr);
    double totalSize = OptimizerUtils.estimatePartitionedSizeExactSparsity(nnz, 1, rowsInBlock, colsInBlock, // overestimate for on disk, ensures hdfs block per partition
    nnz);
    double hdfsBlkSize = InfrastructureAnalyzer.getHDFSBlockSize();
    long numBlocks = (long) Math.ceil(((double) nnz) / rowsInBlock);
    // a) in-memory offset rdd construction
    if (numBlocks < INMEMORY_NUMBLOCKS_THRESHOLD) {
        ArrayList<Double> offsets = new ArrayList<>();
        for (long i = 0; i < numBlocks; i++) {
            double off = lfrom + lincr * i * rowsInBlock;
            offsets.add(off);
        }
        // for load balancing: degree of parallelism such that ~128MB per partition
        int numPartitions = (int) Math.max(Math.min(totalSize / hdfsBlkSize, numBlocks), 1);
        // create offset rdd
        offsetsRDD = sec.getSparkContext().parallelize(offsets, numPartitions);
    } else // b) file-based offset rdd construction (for robustness wrt large number of blocks)
    {
        Path path = new Path(LibMatrixDatagen.generateUniqueSeedPath(dir));
        PrintWriter pw = null;
        try {
            FileSystem fs = IOUtilFunctions.getFileSystem(path);
            pw = new PrintWriter(fs.create(path));
            for (long i = 0; i < numBlocks; i++) {
                double off = lfrom + lincr * i * rowsInBlock;
                pw.println(off);
            }
        } catch (IOException ex) {
            throw new DMLRuntimeException(ex);
        } finally {
            IOUtilFunctions.closeSilently(pw);
        }
        // for load balancing: degree of parallelism such that ~128MB per partition
        int numPartitions = (int) Math.max(Math.min(totalSize / hdfsBlkSize, numBlocks), 1);
        // create seeds rdd
        offsetsRDD = sec.getSparkContext().textFile(path.toString(), numPartitions).map(new ExtractOffsetTuple());
    }
    // step 2: execute seq instruction over offset input
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = offsetsRDD.mapToPair(new GenerateSequenceBlock(rowsInBlock, lfrom, lto, lincr));
    // step 3: output handling
    MatrixCharacteristics mcOut = sec.getMatrixCharacteristics(output.getName());
    if (!mcOut.dimsKnown()) {
        mcOut.set(nnz, 1, rowsInBlock, colsInBlock, nnz);
    }
    sec.setRDDHandleForVariable(output.getName(), out);
}

Example 62 with DMLRuntimeException

use of org.apache.sysml.runtime.DMLRuntimeException in project incubator-systemml by apache.

the class ReblockSPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    // set the output characteristics
    CacheableData<?> obj = sec.getCacheableData(input1.getName());
    MatrixCharacteristics mc = sec.getMatrixCharacteristics(input1.getName());
    MatrixCharacteristics mcOut = sec.getMatrixCharacteristics(output.getName());
    mcOut.set(mc.getRows(), mc.getCols(), brlen, bclen, mc.getNonZeros());
    // get the source format form the meta data
    MetaDataFormat iimd = (MetaDataFormat) obj.getMetaData();
    if (iimd == null)
        throw new DMLRuntimeException("Error: Metadata not found");
    InputInfo iinfo = iimd.getInputInfo();
    // check for in-memory reblock (w/ lazy spark context, potential for latency reduction)
    if (Recompiler.checkCPReblock(sec, input1.getName())) {
        if (input1.getDataType() == DataType.MATRIX)
            Recompiler.executeInMemoryMatrixReblock(sec, input1.getName(), output.getName());
        else if (input1.getDataType() == DataType.FRAME)
            Recompiler.executeInMemoryFrameReblock(sec, input1.getName(), output.getName());
        return;
    }
    // execute matrix/frame reblock
    if (input1.getDataType() == DataType.MATRIX)
        processMatrixReblockInstruction(sec, iinfo);
    else if (input1.getDataType() == DataType.FRAME)
        processFrameReblockInstruction(sec, iinfo);
}

Example 63 with DMLRuntimeException

use of org.apache.sysml.runtime.DMLRuntimeException in project incubator-systemml by apache.

the class ReblockSPInstruction method processMatrixReblockInstruction.

@SuppressWarnings("unchecked")
protected void processMatrixReblockInstruction(SparkExecutionContext sec, InputInfo iinfo) {
    MatrixObject mo = sec.getMatrixObject(input1.getName());
    MatrixCharacteristics mc = sec.getMatrixCharacteristics(input1.getName());
    MatrixCharacteristics mcOut = sec.getMatrixCharacteristics(output.getName());
    if (iinfo == InputInfo.TextCellInputInfo || iinfo == InputInfo.MatrixMarketInputInfo) {
        // get the input textcell rdd
        JavaPairRDD<LongWritable, Text> lines = (JavaPairRDD<LongWritable, Text>) sec.getRDDHandleForVariable(input1.getName(), iinfo);
        // convert textcell to binary block
        JavaPairRDD<MatrixIndexes, MatrixBlock> out = RDDConverterUtils.textCellToBinaryBlock(sec.getSparkContext(), lines, mcOut, outputEmptyBlocks);
        // put output RDD handle into symbol table
        sec.setRDDHandleForVariable(output.getName(), out);
        sec.addLineageRDD(output.getName(), input1.getName());
    } else if (iinfo == InputInfo.CSVInputInfo) {
        // HACK ALERT: Until we introduces the rewrite to insert csvrblock for non-persistent read
        // throw new DMLRuntimeException("CSVInputInfo is not supported for ReblockSPInstruction");
        CSVReblockSPInstruction csvInstruction = null;
        boolean hasHeader = false;
        String delim = ",";
        boolean fill = false;
        double fillValue = 0;
        if (mo.getFileFormatProperties() instanceof CSVFileFormatProperties && mo.getFileFormatProperties() != null) {
            CSVFileFormatProperties props = (CSVFileFormatProperties) mo.getFileFormatProperties();
            hasHeader = props.hasHeader();
            delim = props.getDelim();
            fill = props.isFill();
            fillValue = props.getFillValue();
        }
        csvInstruction = new CSVReblockSPInstruction(null, input1, output, mcOut.getRowsPerBlock(), mcOut.getColsPerBlock(), hasHeader, delim, fill, fillValue, "csvrblk", instString);
        csvInstruction.processInstruction(sec);
        return;
    } else if (iinfo == InputInfo.BinaryCellInputInfo) {
        JavaPairRDD<MatrixIndexes, MatrixCell> binaryCells = (JavaPairRDD<MatrixIndexes, MatrixCell>) sec.getRDDHandleForVariable(input1.getName(), iinfo);
        JavaPairRDD<MatrixIndexes, MatrixBlock> out = RDDConverterUtils.binaryCellToBinaryBlock(sec.getSparkContext(), binaryCells, mcOut, outputEmptyBlocks);
        // put output RDD handle into symbol table
        sec.setRDDHandleForVariable(output.getName(), out);
        sec.addLineageRDD(output.getName(), input1.getName());
    } else if (iinfo == InputInfo.BinaryBlockInputInfo) {
        // BINARY BLOCK <- BINARY BLOCK (different sizes)
        JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
        boolean shuffleFreeReblock = mc.dimsKnown() && mcOut.dimsKnown() && (mc.getRows() < mcOut.getRowsPerBlock() || mc.getRowsPerBlock() % mcOut.getRowsPerBlock() == 0) && (mc.getCols() < mcOut.getColsPerBlock() || mc.getColsPerBlock() % mcOut.getColsPerBlock() == 0);
        JavaPairRDD<MatrixIndexes, MatrixBlock> out = in1.flatMapToPair(new ExtractBlockForBinaryReblock(mc, mcOut));
        if (!shuffleFreeReblock)
            out = RDDAggregateUtils.mergeByKey(out, false);
        // put output RDD handle into symbol table
        sec.setRDDHandleForVariable(output.getName(), out);
        sec.addLineageRDD(output.getName(), input1.getName());
    } else {
        throw new DMLRuntimeException("The given InputInfo is not implemented " + "for ReblockSPInstruction:" + InputInfo.inputInfoToString(iinfo));
    }
}

Example 64 with DMLRuntimeException

use of org.apache.sysml.runtime.DMLRuntimeException in project incubator-systemml by apache.

the class ReorgSPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    String opcode = getOpcode();
    // get input rdd handle
    JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = null;
    MatrixCharacteristics mcIn = sec.getMatrixCharacteristics(input1.getName());
    if (// TRANSPOSE
    opcode.equalsIgnoreCase("r'")) {
        // execute transpose reorg operation
        out = in1.mapToPair(new ReorgMapFunction(opcode));
    } else if (// REVERSE
    opcode.equalsIgnoreCase("rev")) {
        // execute reverse reorg operation
        out = in1.flatMapToPair(new RDDRevFunction(mcIn));
        if (mcIn.getRows() % mcIn.getRowsPerBlock() != 0)
            out = RDDAggregateUtils.mergeByKey(out, false);
    } else if (// DIAG
    opcode.equalsIgnoreCase("rdiag")) {
        if (mcIn.getCols() == 1) {
            // diagV2M
            out = in1.flatMapToPair(new RDDDiagV2MFunction(mcIn));
        } else {
            // diagM2V
            // execute diagM2V operation
            out = in1.filter(new FilterDiagBlocksFunction()).mapToPair(new ReorgMapFunction(opcode));
        }
    } else if (// ORDER
    opcode.equalsIgnoreCase("rsort")) {
        // Sort by column 'col' in ascending/descending order and return either index/value
        // get parameters
        long[] cols = _col.getDataType().isMatrix() ? DataConverter.convertToLongVector(ec.getMatrixInput(_col.getName())) : new long[] { ec.getScalarInput(_col.getName(), _col.getValueType(), _col.isLiteral()).getLongValue() };
        boolean desc = ec.getScalarInput(_desc.getName(), _desc.getValueType(), _desc.isLiteral()).getBooleanValue();
        boolean ixret = ec.getScalarInput(_ixret.getName(), _ixret.getValueType(), _ixret.isLiteral()).getBooleanValue();
        boolean singleCol = (mcIn.getCols() == 1);
        out = in1;
        if (cols.length > mcIn.getColsPerBlock())
            LOG.warn("Unsupported sort with number of order-by columns large than blocksize: " + cols.length);
        if (singleCol || cols.length == 1) {
            // extract column (if necessary) and sort
            if (!singleCol)
                out = out.filter(new IsBlockInRange(1, mcIn.getRows(), cols[0], cols[0], mcIn)).mapValues(new ExtractColumn((int) UtilFunctions.computeCellInBlock(cols[0], mcIn.getColsPerBlock())));
            // actual index/data sort operation
            if (// sort indexes
            ixret)
                out = RDDSortUtils.sortIndexesByVal(out, !desc, mcIn.getRows(), mcIn.getRowsPerBlock());
            else if (// sort single-column matrix
            singleCol && !desc)
                out = RDDSortUtils.sortByVal(out, mcIn.getRows(), mcIn.getRowsPerBlock());
            else if (// sort multi-column matrix w/ rewrite
            !_bSortIndInMem)
                out = RDDSortUtils.sortDataByVal(out, in1, !desc, mcIn.getRows(), mcIn.getCols(), mcIn.getRowsPerBlock(), mcIn.getColsPerBlock());
            else
                // sort multi-column matrix
                out = RDDSortUtils.sortDataByValMemSort(out, in1, !desc, mcIn.getRows(), mcIn.getCols(), mcIn.getRowsPerBlock(), mcIn.getColsPerBlock(), sec, (ReorgOperator) _optr);
        } else {
            // extract columns (if necessary)
            if (cols.length < mcIn.getCols())
                out = out.filter(new IsBlockInList(cols, mcIn)).mapToPair(new ExtractColumns(cols, mcIn));
            // append extracted columns (if necessary)
            if (mcIn.getCols() > mcIn.getColsPerBlock())
                out = RDDAggregateUtils.mergeByKey(out);
            // actual index/data sort operation
            if (// sort indexes
            ixret)
                out = RDDSortUtils.sortIndexesByVals(out, !desc, mcIn.getRows(), (long) cols.length, mcIn.getRowsPerBlock());
            else if (// sort single-column matrix
            cols.length == mcIn.getCols() && !desc)
                out = RDDSortUtils.sortByVals(out, mcIn.getRows(), cols.length, mcIn.getRowsPerBlock());
            else
                // sort multi-column matrix
                out = RDDSortUtils.sortDataByVals(out, in1, !desc, mcIn.getRows(), mcIn.getCols(), cols.length, mcIn.getRowsPerBlock(), mcIn.getColsPerBlock());
        }
    } else {
        throw new DMLRuntimeException("Error: Incorrect opcode in ReorgSPInstruction:" + opcode);
    }
    // store output rdd handle
    if (opcode.equalsIgnoreCase("rsort") && _col.getDataType().isMatrix())
        sec.releaseMatrixInput(_col.getName());
    updateReorgMatrixCharacteristics(sec);
    sec.setRDDHandleForVariable(output.getName(), out);
    sec.addLineageRDD(output.getName(), input1.getName());
}

Example 65 with DMLRuntimeException

use of org.apache.sysml.runtime.DMLRuntimeException in project incubator-systemml by apache.

the class ReorgSPInstruction method updateReorgMatrixCharacteristics.

private void updateReorgMatrixCharacteristics(SparkExecutionContext sec) {
    MatrixCharacteristics mc1 = sec.getMatrixCharacteristics(input1.getName());
    MatrixCharacteristics mcOut = sec.getMatrixCharacteristics(output.getName());
    // infer initially unknown dimensions from inputs
    if (!mcOut.dimsKnown()) {
        if (!mc1.dimsKnown())
            throw new DMLRuntimeException("Unable to compute output matrix characteristics from input.");
        if (getOpcode().equalsIgnoreCase("r'"))
            mcOut.set(mc1.getCols(), mc1.getRows(), mc1.getColsPerBlock(), mc1.getRowsPerBlock());
        else if (getOpcode().equalsIgnoreCase("rdiag"))
            mcOut.set(mc1.getRows(), (mc1.getCols() > 1) ? 1 : mc1.getRows(), mc1.getRowsPerBlock(), mc1.getColsPerBlock());
        else if (getOpcode().equalsIgnoreCase("rsort")) {
            boolean ixret = sec.getScalarInput(_ixret.getName(), _ixret.getValueType(), _ixret.isLiteral()).getBooleanValue();
            mcOut.set(mc1.getRows(), ixret ? 1 : mc1.getCols(), mc1.getRowsPerBlock(), mc1.getColsPerBlock());
        }
    }
    // infer initially unknown nnz from input
    if (!mcOut.nnzKnown() && mc1.nnzKnown()) {
        boolean sortIx = getOpcode().equalsIgnoreCase("rsort") && sec.getScalarInput(_ixret.getName(), _ixret.getValueType(), _ixret.isLiteral()).getBooleanValue();
        if (sortIx)
            mcOut.setNonZeros(mc1.getRows());
        else
            // default (r', rdiag, rsort data)
            mcOut.setNonZeros(mc1.getNonZeros());
    }
}