Examples with MatrixBlock org.apache.sysml.runtime.matrix.data.MatrixBlock used on opensource projects

Example 86 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class BinarySPInstruction method processMatrixScalarBinaryInstruction.

protected void processMatrixScalarBinaryInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    // get input RDD
    String rddVar = (input1.getDataType() == DataType.MATRIX) ? input1.getName() : input2.getName();
    JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(rddVar);
    // get operator and scalar
    CPOperand scalar = (input1.getDataType() == DataType.MATRIX) ? input2 : input1;
    ScalarObject constant = (ScalarObject) ec.getScalarInput(scalar.getName(), scalar.getValueType(), scalar.isLiteral());
    ScalarOperator sc_op = (ScalarOperator) _optr;
    sc_op = sc_op.setConstant(constant.getDoubleValue());
    // execute scalar matrix arithmetic instruction
    JavaPairRDD<MatrixIndexes, MatrixBlock> out = in1.mapValues(new MatrixScalarUnaryFunction(sc_op));
    // put output RDD handle into symbol table
    updateUnaryOutputMatrixCharacteristics(sec, rddVar, output.getName());
    sec.setRDDHandleForVariable(output.getName(), out);
    sec.addLineageRDD(output.getName(), rddVar);
}

Example 87 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class CastSPInstruction method processInstruction.

@Override
@SuppressWarnings("unchecked")
public void processInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    String opcode = getOpcode();
    // get input RDD and prepare output
    JavaPairRDD<?, ?> in = sec.getRDDHandleForVariable(input1.getName(), InputInfo.BinaryBlockInputInfo);
    MatrixCharacteristics mcIn = sec.getMatrixCharacteristics(input1.getName());
    JavaPairRDD<?, ?> out = null;
    // convert frame-matrix / matrix-frame and set output
    if (opcode.equals(UnaryCP.CAST_AS_MATRIX_OPCODE)) {
        MatrixCharacteristics mcOut = new MatrixCharacteristics(mcIn);
        mcOut.setBlockSize(ConfigurationManager.getBlocksize(), ConfigurationManager.getBlocksize());
        out = FrameRDDConverterUtils.binaryBlockToMatrixBlock((JavaPairRDD<Long, FrameBlock>) in, mcIn, mcOut);
    } else if (opcode.equals(UnaryCP.CAST_AS_FRAME_OPCODE)) {
        out = FrameRDDConverterUtils.matrixBlockToBinaryBlockLongIndex(sec.getSparkContext(), (JavaPairRDD<MatrixIndexes, MatrixBlock>) in, mcIn);
    } else {
        throw new DMLRuntimeException("Unsupported spark cast operation: " + opcode);
    }
    // update output statistics and add lineage
    sec.setRDDHandleForVariable(output.getName(), out);
    updateUnaryOutputMatrixCharacteristics(sec, input1.getName(), output.getName());
    sec.addLineageRDD(output.getName(), input1.getName());
    // update schema information for output frame
    if (opcode.equals(UnaryCP.CAST_AS_FRAME_OPCODE)) {
        sec.getFrameObject(output.getName()).setSchema(UtilFunctions.nCopies((int) mcIn.getCols(), ValueType.DOUBLE));
    }
}

Example 88 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class CentralMomentSPInstruction method processInstruction.

@Override
public void processInstruction(ExecutionContext ec) {
    SparkExecutionContext sec = (SparkExecutionContext) ec;
    // parse 'order' input argument
    CPOperand scalarInput = (input3 == null ? input2 : input3);
    ScalarObject order = ec.getScalarInput(scalarInput.getName(), scalarInput.getValueType(), scalarInput.isLiteral());
    CMOperator cop = ((CMOperator) _optr);
    if (cop.getAggOpType() == AggregateOperationTypes.INVALID) {
        cop.setCMAggOp((int) order.getLongValue());
    }
    // get input
    JavaPairRDD<MatrixIndexes, MatrixBlock> in1 = sec.getBinaryBlockRDDHandleForVariable(input1.getName());
    // process central moment instruction
    CM_COV_Object cmobj = null;
    if (// w/o weights
    input3 == null) {
        cmobj = in1.values().map(new RDDCMFunction(cop)).fold(new CM_COV_Object(), new RDDCMReduceFunction(cop));
    } else // with weights
    {
        JavaPairRDD<MatrixIndexes, MatrixBlock> in2 = sec.getBinaryBlockRDDHandleForVariable(input2.getName());
        cmobj = in1.join(in2).values().map(new RDDCMWeightsFunction(cop)).fold(new CM_COV_Object(), new RDDCMReduceFunction(cop));
    }
    // create scalar output (no lineage information required)
    double val = cmobj.getRequiredResult(_optr);
    ec.setScalarOutput(output.getName(), new DoubleObject(val));
}

Example 89 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class ConvolutionSPInstruction method getBroadcast.

private Broadcast<MatrixBlock> getBroadcast(SparkExecutionContext sec, String name) {
    MatrixBlock mb = sec.getMatrixInput(name, getExtendedOpcode());
    sec.releaseMatrixInput(name, getExtendedOpcode());
    return sec.getSparkContext().broadcast(mb);
}

Example 90 with MatrixBlock

use of org.apache.sysml.runtime.matrix.data.MatrixBlock in project incubator-systemml by apache.

the class ReplicateBlockFunction method call.

@Override
public Iterator<Tuple2<MatrixIndexes, MatrixBlock>> call(Tuple2<MatrixIndexes, MatrixBlock> arg0) throws Exception {
    ArrayList<Tuple2<MatrixIndexes, MatrixBlock>> ret = new ArrayList<>();
    MatrixIndexes ixIn = arg0._1();
    MatrixBlock blkIn = arg0._2();
    long numBlocks = (long) Math.ceil((double) _len / _blen);
    if (// LHS MATRIX
    _left) {
        // replicate wrt # column blocks in RHS
        long i = ixIn.getRowIndex();
        for (long j = 1; j <= numBlocks; j++) {
            MatrixIndexes tmpix = new MatrixIndexes(i, j);
            MatrixBlock tmpblk = _deep ? new MatrixBlock(blkIn) : blkIn;
            ret.add(new Tuple2<>(tmpix, tmpblk));
        }
    } else // RHS MATRIX
    {
        // replicate wrt # row blocks in LHS
        long j = ixIn.getColumnIndex();
        for (long i = 1; i <= numBlocks; i++) {
            MatrixIndexes tmpix = new MatrixIndexes(i, j);
            MatrixBlock tmpblk = _deep ? new MatrixBlock(blkIn) : blkIn;
            ret.add(new Tuple2<>(tmpix, tmpblk));
        }
    }
    // output list of new tuples
    return ret.iterator();
}