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

Example 71 with VectorizedRowBatch

use of org.apache.hadoop.hive.ql.exec.vector.VectorizedRowBatch 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;
}

Example 72 with VectorizedRowBatch

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

the class TestVectorMathFunctions method getVectorizedRowBatchTimestampInStringOut.

public static VectorizedRowBatch getVectorizedRowBatchTimestampInStringOut(long[] epochSecondValues, int[] nanoValues) {
    Random r = new Random(345);
    VectorizedRowBatch batch = new VectorizedRowBatch(2);
    batch.size = epochSecondValues.length;
    TimestampColumnVector inV;
    BytesColumnVector outV;
    inV = new TimestampColumnVector(batch.size);
    outV = new BytesColumnVector(batch.size);
    for (int i = 0; i < batch.size; i++) {
        Timestamp randTimestamp = RandomTypeUtil.getRandTimestamp(r);
        epochSecondValues[i] = randTimestamp.toEpochSecond();
        nanoValues[i] = randTimestamp.getNanos();
        inV.set(i, randTimestamp.toSqlTimestamp());
    }
    batch.cols[0] = inV;
    batch.cols[1] = outV;
    return batch;
}

Example 73 with VectorizedRowBatch

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

the class TestVectorMathFunctions method getVectorizedRowBatchStringInTimestampOutFormatted.

public static VectorizedRowBatch getVectorizedRowBatchStringInTimestampOutFormatted() {
    VectorizedRowBatch batch = new VectorizedRowBatch(2);
    BytesColumnVector inV;
    inV = new BytesColumnVector();
    inV.initBuffer();
    inV.setVal(0, StandardCharsets.UTF_8.encode("2019-12-31 00:00:00.999999999").array());
    inV.setVal(1, StandardCharsets.UTF_8.encode("1776-07-04 17:07:06.177617761").array());
    inV.setVal(2, StandardCharsets.UTF_8.encode("2012-02-29 23:59:59.999999999").array());
    inV.setVal(3, StandardCharsets.UTF_8.encode("1580-08-08 00:00:00.0").array());
    inV.setVal(4, StandardCharsets.UTF_8.encode("0005-01-01 00:00:00.0").array());
    inV.setVal(5, StandardCharsets.UTF_8.encode("9999-12-31 23:59:59.999999999").array());
    batch.cols[0] = inV;
    batch.size = 6;
    return batch;
}

Example 74 with VectorizedRowBatch

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

the class TestVectorMathFunctions method testVectorPower.

@Test
public void testVectorPower() throws HiveException {
    VectorizedRowBatch b = getVectorizedRowBatchDoubleInDoubleOut();
    DoubleColumnVector resultV = (DoubleColumnVector) b.cols[1];
    b.cols[0].noNulls = true;
    VectorExpression expr = new FuncPowerDoubleToDouble(0, 2.0, 1);
    expr.evaluate(b);
    Assert.assertTrue(equalsWithinTolerance(0.5d * 0.5d, resultV.vector[4]));
}

Example 75 with VectorizedRowBatch

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

the class TestVectorMathFunctions method testVectorLog10.

@Test
public void testVectorLog10() throws HiveException {
    // 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], Double.MIN_VALUE);
}