Examples with DoubleColumnVector org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector used on opensource projects

Example 11 with DoubleColumnVector

use of org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector in project hive by apache.

the class TestVectorScalarColArithmetic method testLongScalarDivide.

@Test
public void testLongScalarDivide() {
    VectorizedRowBatch batch = TestVectorArithmeticExpressions.getVectorizedRowBatch2LongInDoubleOut();
    LongColDivideLongScalar expr = new LongColDivideLongScalar(0, 100, 2);
    batch.cols[0].isNull[0] = true;
    batch.cols[0].noNulls = false;
    DoubleColumnVector out = (DoubleColumnVector) batch.cols[2];
    // set now so we can verify it changed
    out.noNulls = true;
    out.isRepeating = true;
    expr.evaluate(batch);
    // verify NULL output in entry 0 is correct
    assertFalse(out.noNulls);
    assertTrue(out.isNull[0]);
    assertTrue(Double.isNaN(out.vector[0]));
    // check entries beyond first one
    for (int i = 1; i != batch.size; i++) {
        assertTrue(equalsWithinTolerance((i * 37) / 100d, out.vector[i]));
    }
    assertFalse(out.isRepeating);
}

Example 12 with DoubleColumnVector

use of org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector in project hive by apache.

the class TestVectorMathFunctions method testVectorSqrt.

@Test
public void testVectorSqrt() {
    VectorizedRowBatch b = getVectorizedRowBatchDoubleInDoubleOut();
    DoubleColumnVector resultV = (DoubleColumnVector) b.cols[1];
    b.cols[0].noNulls = true;
    VectorExpression expr = new FuncSqrtDoubleToDouble(0, 1);
    expr.evaluate(b);
    Assert.assertEquals(Math.sqrt(0.5d), resultV.vector[4]);
}

Example 13 with DoubleColumnVector

use of org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector in project hive by apache.

the class TestVectorMathFunctions method testVectorLog10.

@Test
public void testVectorLog10() {
    // test double->double version
    VectorizedRowBatch b = getVectorizedRowBatchDoubleInDoubleOut();
    DoubleColumnVector resultV = (DoubleColumnVector) b.cols[1];
    b.cols[0].noNulls = true;
    VectorExpression expr = new FuncLog10DoubleToDouble(0, 1);
    expr.evaluate(b);
    Assert.assertTrue(equalsWithinTolerance(Math.log(0.5d) / Math.log(10), resultV.vector[4]));
    // test long->double version
    b = getVectorizedRowBatchLongInDoubleOut();
    resultV = (DoubleColumnVector) b.cols[1];
    b.cols[0].noNulls = true;
    expr = new FuncLog10LongToDouble(0, 1);
    expr.evaluate(b);
    Assert.assertEquals(Math.log(1) / Math.log(10), resultV.vector[3]);
}

Example 14 with DoubleColumnVector

use of org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector in project hive by apache.

the class TestVectorMathFunctions method testVectorLn.

@Test
public void testVectorLn() {
    // test double->double version
    VectorizedRowBatch b = getVectorizedRowBatchDoubleInDoubleOut();
    DoubleColumnVector resultV = (DoubleColumnVector) b.cols[1];
    b.cols[0].noNulls = true;
    VectorExpression expr = new FuncLnDoubleToDouble(0, 1);
    expr.evaluate(b);
    Assert.assertEquals(Math.log(0.5), resultV.vector[4]);
    // test long->double version
    b = getVectorizedRowBatchLongInDoubleOut();
    resultV = (DoubleColumnVector) b.cols[1];
    b.cols[0].noNulls = true;
    expr = new FuncLnLongToDouble(0, 1);
    expr.evaluate(b);
    Assert.assertEquals(Math.log(2), resultV.vector[4]);
}

Example 15 with DoubleColumnVector

use of org.apache.hadoop.hive.ql.exec.vector.DoubleColumnVector in project hive by apache.

the class TestVectorMathFunctions method getVectorizedRowBatchDoubleInDoubleOut.

public static VectorizedRowBatch getVectorizedRowBatchDoubleInDoubleOut() {
    VectorizedRowBatch batch = new VectorizedRowBatch(2);
    DoubleColumnVector inV;
    DoubleColumnVector outV;
    outV = new DoubleColumnVector();
    inV = new DoubleColumnVector();
    inV.vector[0] = -1.5d;
    inV.vector[1] = -0.5d;
    inV.vector[2] = -0.1d;
    inV.vector[3] = 0d;
    inV.vector[4] = 0.5d;
    inV.vector[5] = 0.7d;
    inV.vector[6] = 1.5d;
    inV.vector[7] = 1.2345678d;
    batch.cols[0] = inV;
    batch.cols[1] = outV;
    batch.size = 8;
    return batch;
}