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

Example 86 with DoubleColumnVector

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

the class DoubleToStringUnaryUDF method evaluate.

@Override
public void evaluate(VectorizedRowBatch batch) {
    if (childExpressions != null) {
        super.evaluateChildren(batch);
    }
    DoubleColumnVector inputColVector = (DoubleColumnVector) batch.cols[inputColumn];
    int[] sel = batch.selected;
    int n = batch.size;
    double[] vector = inputColVector.vector;
    BytesColumnVector outputColVector = (BytesColumnVector) batch.cols[outputColumnNum];
    boolean[] outputIsNull = outputColVector.isNull;
    outputColVector.initBuffer();
    boolean[] inputIsNull = inputColVector.isNull;
    if (n == 0) {
        // Nothing to do
        return;
    }
    // We do not need to do a column reset since we are carefully changing the output.
    outputColVector.isRepeating = false;
    if (inputColVector.isRepeating) {
        if (inputColVector.noNulls || !inputIsNull[0]) {
            // Set isNull before call in case it changes it mind.
            outputIsNull[0] = false;
            func(outputColVector, vector, 0);
        } else {
            outputIsNull[0] = true;
            outputColVector.noNulls = false;
        }
        outputColVector.isRepeating = true;
        return;
    }
    if (inputColVector.noNulls) {
        if (batch.selectedInUse) {
            if (!outputColVector.noNulls) {
                for (int j = 0; j != n; j++) {
                    final int i = sel[j];
                    // Set isNull before call in case it changes it mind.
                    outputIsNull[i] = false;
                    func(outputColVector, vector, i);
                }
            } else {
                for (int j = 0; j != n; j++) {
                    final int i = sel[j];
                    func(outputColVector, vector, i);
                }
            }
        } else {
            if (!outputColVector.noNulls) {
                // Assume it is almost always a performance win to fill all of isNull so we can
                // safely reset noNulls.
                Arrays.fill(outputIsNull, false);
                outputColVector.noNulls = true;
            }
            for (int i = 0; i != n; i++) {
                func(outputColVector, vector, i);
            }
        }
    } else /* there are NULLs in the inputColVector */
    {
        // Handle case with nulls. Don't do function if the value is null,
        // because the data may be undefined for a null value.
        outputColVector.noNulls = false;
        if (batch.selectedInUse) {
            for (int j = 0; j != n; j++) {
                int i = sel[j];
                outputColVector.isNull[i] = inputColVector.isNull[i];
                if (!inputColVector.isNull[i]) {
                    func(outputColVector, vector, i);
                }
            }
        } else {
            System.arraycopy(inputColVector.isNull, 0, outputColVector.isNull, 0, n);
            for (int i = 0; i != n; i++) {
                if (!inputColVector.isNull[i]) {
                    func(outputColVector, vector, i);
                }
            }
        }
    }
}

Example 87 with DoubleColumnVector

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

the class FilterDoubleColumnInList method evaluate.

@Override
public void evaluate(VectorizedRowBatch batch) {
    if (childExpressions != null) {
        super.evaluateChildren(batch);
    }
    DoubleColumnVector inputColVector = (DoubleColumnVector) batch.cols[inputCol];
    int[] sel = batch.selected;
    boolean[] nullPos = inputColVector.isNull;
    int n = batch.size;
    double[] vector = inputColVector.vector;
    // return immediately if batch is empty
    if (n == 0) {
        return;
    }
    if (inputColVector.noNulls) {
        if (inputColVector.isRepeating) {
            if (!(inSet.lookup(vector[0]))) {
                // Entire batch is filtered out.
                batch.size = 0;
            }
        } else if (batch.selectedInUse) {
            int newSize = 0;
            for (int j = 0; j != n; j++) {
                int i = sel[j];
                if (inSet.lookup(vector[i])) {
                    sel[newSize++] = i;
                }
            }
            batch.size = newSize;
        } else {
            int newSize = 0;
            for (int i = 0; i != n; i++) {
                if (inSet.lookup(vector[i])) {
                    sel[newSize++] = i;
                }
            }
            if (newSize < n) {
                batch.size = newSize;
                batch.selectedInUse = true;
            }
        }
    } else {
        if (inputColVector.isRepeating) {
            // Repeating property will not change.
            if (!nullPos[0]) {
                if (!inSet.lookup(vector[0])) {
                    // Entire batch is filtered out.
                    batch.size = 0;
                }
            } else {
                batch.size = 0;
            }
        } else if (batch.selectedInUse) {
            int newSize = 0;
            for (int j = 0; j != n; j++) {
                int i = sel[j];
                if (!nullPos[i]) {
                    if (inSet.lookup(vector[i])) {
                        sel[newSize++] = i;
                    }
                }
            }
            // Change the selected vector
            batch.size = newSize;
        } else {
            int newSize = 0;
            for (int i = 0; i != n; i++) {
                if (!nullPos[i]) {
                    if (inSet.lookup(vector[i])) {
                        sel[newSize++] = i;
                    }
                }
            }
            if (newSize < n) {
                batch.size = newSize;
                batch.selectedInUse = true;
            }
        }
    }
}

Example 88 with DoubleColumnVector

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

the class FuncDecimalToDouble method evaluate.

@Override
public void evaluate(VectorizedRowBatch batch) {
    if (childExpressions != null) {
        super.evaluateChildren(batch);
    }
    DecimalColumnVector inputColVector = (DecimalColumnVector) batch.cols[inputColumn];
    int[] sel = batch.selected;
    int n = batch.size;
    DoubleColumnVector outputColVector = (DoubleColumnVector) batch.cols[outputColumnNum];
    boolean[] inputIsNull = inputColVector.isNull;
    boolean[] outputIsNull = outputColVector.isNull;
    if (n == 0) {
        // Nothing to do
        return;
    }
    // We do not need to do a column reset since we are carefully changing the output.
    outputColVector.isRepeating = false;
    if (inputColVector.isRepeating) {
        if (inputColVector.noNulls || !inputIsNull[0]) {
            // Set isNull before call in case it changes it mind.
            outputIsNull[0] = false;
            func(outputColVector, inputColVector, 0);
        } else {
            outputIsNull[0] = true;
            outputColVector.noNulls = false;
        }
        outputColVector.isRepeating = true;
        return;
    }
    if (inputColVector.noNulls) {
        if (batch.selectedInUse) {
            if (!outputColVector.noNulls) {
                for (int j = 0; j != n; j++) {
                    final int i = sel[j];
                    // Set isNull before call in case it changes it mind.
                    outputIsNull[i] = false;
                    func(outputColVector, inputColVector, i);
                }
            } else {
                for (int j = 0; j != n; j++) {
                    final int i = sel[j];
                    func(outputColVector, inputColVector, i);
                }
            }
        } else {
            if (!outputColVector.noNulls) {
                // Assume it is almost always a performance win to fill all of isNull so we can
                // safely reset noNulls.
                Arrays.fill(outputIsNull, false);
                outputColVector.noNulls = true;
            }
            for (int i = 0; i != n; i++) {
                func(outputColVector, inputColVector, i);
            }
        }
    } else /* there are nulls in the inputColVector */
    {
        // Carefully handle NULLs...
        outputColVector.noNulls = false;
        if (batch.selectedInUse) {
            for (int j = 0; j != n; j++) {
                int i = sel[j];
                outputColVector.isNull[i] = inputColVector.isNull[i];
                if (!inputColVector.isNull[i]) {
                    func(outputColVector, inputColVector, i);
                }
            }
        } else {
            System.arraycopy(inputColVector.isNull, 0, outputColVector.isNull, 0, n);
            for (int i = 0; i != n; i++) {
                if (!inputColVector.isNull[i]) {
                    func(outputColVector, inputColVector, i);
                }
            }
        }
    }
}

Example 89 with DoubleColumnVector

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

the class FuncDoubleToDecimal method evaluate.

@Override
public void evaluate(VectorizedRowBatch batch) {
    if (childExpressions != null) {
        super.evaluateChildren(batch);
    }
    DoubleColumnVector inputColVector = (DoubleColumnVector) batch.cols[inputColumn];
    int[] sel = batch.selected;
    int n = batch.size;
    DecimalColumnVector outputColVector = (DecimalColumnVector) batch.cols[outputColumnNum];
    boolean[] inputIsNull = inputColVector.isNull;
    boolean[] outputIsNull = outputColVector.isNull;
    if (n == 0) {
        // Nothing to do
        return;
    }
    // We do not need to do a column reset since we are carefully changing the output.
    outputColVector.isRepeating = false;
    if (inputColVector.isRepeating) {
        if (inputColVector.noNulls || !inputIsNull[0]) {
            // Set isNull before call in case it changes it mind.
            outputIsNull[0] = false;
            func(outputColVector, inputColVector, 0);
        } else {
            outputIsNull[0] = true;
            outputColVector.noNulls = false;
        }
        outputColVector.isRepeating = true;
        return;
    }
    if (inputColVector.noNulls) {
        if (batch.selectedInUse) {
            if (!outputColVector.noNulls) {
                for (int j = 0; j != n; j++) {
                    final int i = sel[j];
                    // Set isNull before call in case it changes it mind.
                    outputIsNull[i] = false;
                    func(outputColVector, inputColVector, i);
                }
            } else {
                for (int j = 0; j != n; j++) {
                    final int i = sel[j];
                    func(outputColVector, inputColVector, i);
                }
            }
        } else {
            if (!outputColVector.noNulls) {
                // Assume it is almost always a performance win to fill all of isNull so we can
                // safely reset noNulls.
                Arrays.fill(outputIsNull, false);
                outputColVector.noNulls = true;
            }
            for (int i = 0; i != n; i++) {
                func(outputColVector, inputColVector, i);
            }
        }
    } else /* there are nulls in the inputColVector */
    {
        // Carefully handle NULLs...
        outputColVector.noNulls = false;
        if (batch.selectedInUse) {
            for (int j = 0; j != n; j++) {
                int i = sel[j];
                outputColVector.isNull[i] = inputColVector.isNull[i];
                if (!inputColVector.isNull[i]) {
                    func(outputColVector, inputColVector, i);
                }
            }
        } else {
            System.arraycopy(inputColVector.isNull, 0, outputColVector.isNull, 0, n);
            for (int i = 0; i != n; i++) {
                if (!inputColVector.isNull[i]) {
                    func(outputColVector, inputColVector, i);
                }
            }
        }
    }
}

Example 90 with DoubleColumnVector

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

the class FuncRand method evaluate.

@Override
public void evaluate(VectorizedRowBatch batch) {
    if (childExpressions != null) {
        this.evaluateChildren(batch);
    }
    DoubleColumnVector outputColVector = (DoubleColumnVector) batch.cols[outputColumnNum];
    int[] sel = batch.selected;
    int n = batch.size;
    double[] outputVector = outputColVector.vector;
    outputColVector.isRepeating = false;
    boolean[] outputIsNull = outputColVector.isNull;
    // return immediately if batch is empty
    if (n == 0) {
        return;
    }
    if (batch.selectedInUse) {
        if (!outputColVector.noNulls) {
            for (int j = 0; j != n; j++) {
                final int i = sel[j];
                // Set isNull before call in case it changes it mind.
                outputIsNull[i] = false;
                outputVector[i] = random.nextDouble();
            }
        } else {
            for (int j = 0; j != n; j++) {
                final int i = sel[j];
                outputVector[i] = random.nextDouble();
            }
        }
    } else {
        if (!outputColVector.noNulls) {
            // Assume it is almost always a performance win to fill all of isNull so we can
            // safely reset noNulls.
            Arrays.fill(outputIsNull, false);
            outputColVector.noNulls = true;
        }
        for (int i = 0; i != n; i++) {
            outputVector[i] = random.nextDouble();
        }
    }
}