Example usage for org.apache.hadoop.util StringUtils camelize

List of usage examples for org.apache.hadoop.util StringUtils camelize

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In this page you can find the example usage for org.apache.hadoop.util StringUtils camelize.

Prototype

public static String camelize(String s)

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Convert SOME_STUFF to SomeStuff

Usage

From source file:org.apache.accumulo.core.client.mapreduce.lib.impl.ConfiguratorBase.java

License:Apache License

/**
 * Provides a configuration key for a given feature enum, prefixed by the implementingClass
 *
 * @param implementingClass//from  w w  w.j  a  v a  2  s.  c o m
 *          the class whose name will be used as a prefix for the property configuration key
 * @param e
 *          the enum used to provide the unique part of the configuration key
 * @return the configuration key
 * @since 1.6.0
 */
protected static String enumToConfKey(Class<?> implementingClass, Enum<?> e) {
    return implementingClass.getSimpleName() + "." + e.getDeclaringClass().getSimpleName() + "."
            + StringUtils.camelize(e.name().toLowerCase());
}

From source file:org.apache.accumulo.core.client.mapreduce.lib.impl.ConfiguratorBase.java

License:Apache License

/**
 * Provides a configuration key for a given feature enum.
 *
 * @param e//w  ww.  j a  v a  2s. c  om
 *          the enum used to provide the unique part of the configuration key
 * @return the configuration key
 */
protected static String enumToConfKey(Enum<?> e) {
    return e.getDeclaringClass().getSimpleName() + "." + StringUtils.camelize(e.name().toLowerCase());
}

From source file:org.apache.accumulo.core.client.mapreduce.lib.util.ConfiguratorBase.java

License:Apache License

/**
 * Provides a configuration key for a given feature enum, prefixed by the implementingClass
 *
 * @param implementingClass/* w w w.j a  v  a  2s .c om*/
 *          the class whose name will be used as a prefix for the property configuration key
 * @param e
 *          the enum used to provide the unique part of the configuration key
 * @return the configuration key
 * @deprecated since 1.6.0; Configure your job with the appropriate InputFormat or OutputFormat.
 * @since 1.5.0
 */
@Deprecated
protected static String enumToConfKey(Class<?> implementingClass, Enum<?> e) {
    return implementingClass.getSimpleName() + "." + e.getDeclaringClass().getSimpleName() + "."
            + StringUtils.camelize(e.name().toLowerCase());
}

From source file:org.apache.sysml.test.integration.functions.codegen.CPlanVectorPrimitivesTest.java

License:Apache License

@SuppressWarnings("incomplete-switch")
private static void testVectorAggPrimitive(UnaryType aggtype, InputType type1) {
    try {/*  w w w  . j  a  v  a  2  s  . com*/
        //generate input data
        double sparsity = (type1 == InputType.VECTOR_DENSE) ? sparsity1 : sparsity2;
        MatrixBlock in = MatrixBlock.randOperations(m, n, sparsity, -1, 1, "uniform", 7);

        //get vector primitive via reflection
        String meName = "vect" + StringUtils.camelize(aggtype.name().split("_")[1].substring(0, 3));
        Method me = (type1 == InputType.VECTOR_DENSE)
                ? LibSpoofPrimitives.class.getMethod(meName,
                        new Class[] { double[].class, int.class, int.class })
                : LibSpoofPrimitives.class.getMethod(meName,
                        new Class[] { double[].class, int[].class, int.class, int.class, int.class });

        for (int i = 0; i < m; i++) {
            //execute vector primitive via reflection
            Double ret1 = (Double) ((type1 == InputType.VECTOR_DENSE)
                    ? me.invoke(null, in.getDenseBlock(), i * n, n)
                    : me.invoke(null, in.getSparseBlock().values(i), in.getSparseBlock().indexes(i),
                            in.getSparseBlock().pos(i), in.getSparseBlock().size(i), n));

            //execute comparison operation
            MatrixBlock in2 = in.sliceOperations(i, i, 0, n - 1, new MatrixBlock());
            Double ret2 = -1d;
            switch (aggtype) {
            case ROW_SUMS:
                ret2 = in2.sum();
                break;
            case ROW_MAXS:
                ret2 = in2.max();
                break;
            case ROW_MINS:
                ret2 = in2.min();
                break;
            }

            //compare results
            TestUtils.compareCellValue(ret1, ret2, eps, false);
        }
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    }
}

From source file:org.apache.sysml.test.integration.functions.codegen.CPlanVectorPrimitivesTest.java

License:Apache License

private static void testVectorUnaryPrimitive(UnaryType utype, InputType type1) {
    try {/*from www  .  j  ava  2s .c om*/
        //generate input data
        double sparsity = (type1 == InputType.VECTOR_DENSE) ? sparsity1 : sparsity2;
        MatrixBlock in = MatrixBlock.randOperations(m, n, sparsity, -1, 1, "uniform", 7);

        //get vector primitive via reflection
        String meName = "vect" + StringUtils.camelize(utype.name().split("_")[1]) + "Write";
        Method me = (type1 == InputType.VECTOR_DENSE)
                ? LibSpoofPrimitives.class.getMethod(meName,
                        new Class[] { double[].class, int.class, int.class })
                : LibSpoofPrimitives.class.getMethod(meName,
                        new Class[] { double[].class, int[].class, int.class, int.class, int.class });

        for (int i = 0; i < m; i++) {
            //execute vector primitive via reflection
            double[] ret1 = (double[]) ((type1 == InputType.VECTOR_DENSE)
                    ? me.invoke(null, in.getDenseBlock(), i * n, n)
                    : me.invoke(null, in.getSparseBlock().values(i), in.getSparseBlock().indexes(i),
                            in.getSparseBlock().pos(i), in.getSparseBlock().size(i), n));

            //execute comparison operation
            String opcode = utype.name().split("_")[1].toLowerCase();
            UnaryOperator uop = new UnaryOperator(Builtin.getBuiltinFnObject(opcode));
            double[] ret2 = DataConverter
                    .convertToDoubleVector(((MatrixBlock) in.sliceOperations(i, i, 0, n - 1, new MatrixBlock())
                            .unaryOperations(uop, new MatrixBlock())), false);

            //compare results
            TestUtils.compareMatrices(ret1, ret2, eps);
        }
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    }
}

From source file:org.apache.sysml.test.integration.functions.codegen.CPlanVectorPrimitivesTest.java

License:Apache License

private static void testVectorBinaryPrimitive(BinType bintype, InputType type1, InputType type2) {
    try {/* w  w w .  j a  va 2  s.c  o m*/
        //generate input data (scalar later derived if needed)
        double sparsityA = (type1 == InputType.VECTOR_DENSE) ? sparsity1 : sparsity2;
        MatrixBlock inA = MatrixBlock.randOperations(m, n, sparsityA, -5, 5, "uniform", 3);
        double sparsityB = (type2 == InputType.VECTOR_DENSE) ? sparsity1 : sparsity2;
        MatrixBlock inB = MatrixBlock.randOperations(m, n, sparsityB, -5, 5, "uniform", 7);

        //get vector primitive via reflection
        String meName = "vect" + StringUtils.camelize(bintype.name().split("_")[1]) + "Write";
        Method me = null;
        if (type1 == InputType.SCALAR && type2 == InputType.VECTOR_DENSE)
            me = LibSpoofPrimitives.class.getMethod(meName,
                    new Class[] { double.class, double[].class, int.class, int.class });
        else if (type1 == InputType.VECTOR_DENSE && type2 == InputType.SCALAR)
            me = LibSpoofPrimitives.class.getMethod(meName,
                    new Class[] { double[].class, double.class, int.class, int.class });
        else if (type1 == InputType.VECTOR_DENSE && type2 == InputType.VECTOR_DENSE)
            me = LibSpoofPrimitives.class.getMethod(meName,
                    new Class[] { double[].class, double[].class, int.class, int.class, int.class });
        else if (type1 == InputType.VECTOR_SPARSE && type2 == InputType.SCALAR)
            me = LibSpoofPrimitives.class.getMethod(meName,
                    new Class[] { double[].class, double.class, int[].class, int.class, int.class, int.class });
        else if (type1 == InputType.SCALAR && type2 == InputType.VECTOR_SPARSE)
            me = LibSpoofPrimitives.class.getMethod(meName,
                    new Class[] { double.class, double[].class, int[].class, int.class, int.class, int.class });
        else if (type1 == InputType.VECTOR_SPARSE && type2 == InputType.VECTOR_DENSE)
            me = LibSpoofPrimitives.class.getMethod(meName, new Class[] { double[].class, double[].class,
                    int[].class, int.class, int.class, int.class, int.class });

        for (int i = 0; i < m; i++) {
            //execute vector primitive via reflection
            double[] ret1 = null;
            if (type1 == InputType.SCALAR && type2 == InputType.VECTOR_DENSE)
                ret1 = (double[]) me.invoke(null, inA.max(), inB.getDenseBlock(), i * n, n);
            else if (type1 == InputType.VECTOR_DENSE && type2 == InputType.SCALAR)
                ret1 = (double[]) me.invoke(null, inA.getDenseBlock(), inB.max(), i * n, n);
            else if (type1 == InputType.VECTOR_DENSE && type2 == InputType.VECTOR_DENSE)
                ret1 = (double[]) me.invoke(null, inA.getDenseBlock(), inB.getDenseBlock(), i * n, i * n, n);
            else if (type1 == InputType.VECTOR_SPARSE && type2 == InputType.SCALAR)
                ret1 = (double[]) me.invoke(null, inA.getSparseBlock().values(i), inB.max(),
                        inA.getSparseBlock().indexes(i), inA.getSparseBlock().pos(i),
                        inA.getSparseBlock().size(i), n);
            else if (type1 == InputType.SCALAR && type2 == InputType.VECTOR_SPARSE)
                ret1 = (double[]) me.invoke(null, inA.max(), inB.getSparseBlock().values(i),
                        inB.getSparseBlock().indexes(i), inB.getSparseBlock().pos(i),
                        inB.getSparseBlock().size(i), n);
            else if (type1 == InputType.VECTOR_SPARSE && type2 == InputType.VECTOR_DENSE)
                ret1 = (double[]) me.invoke(null, inA.getSparseBlock().values(i), inB.getDenseBlock(),
                        inA.getSparseBlock().indexes(i), inA.getSparseBlock().pos(i), i * n,
                        inA.getSparseBlock().size(i), n);

            //execute comparison operation
            String opcode = Hop.getBinaryOpCode(OpOp2.valueOf(bintype.name().split("_")[1]));
            MatrixBlock in1 = inA.sliceOperations(i, i, 0, n - 1, new MatrixBlock());
            MatrixBlock in2 = inB.sliceOperations(i, i, 0, n - 1, new MatrixBlock());
            double[] ret2 = null;
            if (type1 == InputType.SCALAR) {
                ScalarOperator bop = InstructionUtils.parseScalarBinaryOperator(opcode, true);
                bop = bop.setConstant(inA.max());
                ret2 = DataConverter.convertToDoubleVector(
                        (MatrixBlock) in2.scalarOperations(bop, new MatrixBlock()), false);
            } else if (type2 == InputType.SCALAR) {
                ScalarOperator bop = InstructionUtils.parseScalarBinaryOperator(opcode, false);
                bop = bop.setConstant(inB.max());
                ret2 = DataConverter.convertToDoubleVector(
                        (MatrixBlock) in1.scalarOperations(bop, new MatrixBlock()), false);
            } else { //vector-vector
                BinaryOperator bop = InstructionUtils.parseBinaryOperator(opcode);
                ret2 = DataConverter.convertToDoubleVector(
                        (MatrixBlock) in1.binaryOperations(bop, in2, new MatrixBlock()), false);
            }

            //compare results
            TestUtils.compareMatrices(ret1, ret2, eps);
        }
    } catch (Exception ex) {
        throw new RuntimeException(ex);
    }
}