Examples of org.apache.hadoop.hive.ql.exec.vector.ColumnVector

Package org.apache.hadoop.hive.ql.exec.vector

Examples of org.apache.hadoop.hive.ql.exec.vector.ColumnVector

org.apache.hadoop.hive.ql.exec.vector.ColumnVector
ColumnVector contains the shared structure for the sub-types, including NULL information, and whether this vector repeats, i.e. has all values the same, so only the first one is set. This is used to accelerate query performance by handling a whole vector in O(1) time when applicable. The fields are public by design since this is a performance-critical structure that is used in the inner loop of query execution.

  @Override
  public void evaluate(VectorizedRowBatch batch) {
    if (childExpressions != null) {
      super.evaluateChildren(batch);
    }
    ColumnVector inputColVector = batch.cols[colNum];
    int[] sel = batch.selected;
    boolean[] nullPos = inputColVector.isNull;
    int n = batch.size;
    if (n <= 0) {
      // Nothing to do

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  @Override
  public VectorizedRowBatch produceNextBatch() {
    batch.size = 0;
    batch.selectedInUse = false;
    for (int i=0; i < types.length; ++i) {
      ColumnVector col = batch.cols[i];
      col.noNulls = true;
      col.isRepeating = false;
    }
    while (!eof && batch.size < this.batchSize){
      int r = batch.size;

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    if (childExpressions != null) {
      super.evaluateChildren(batch);
    }


    BytesColumnVector outV = (BytesColumnVector) batch.cols[outputColumn];
    ColumnVector inputCol = batch.cols[this.colNum];
    /* every line below this is identical for evaluateLong & evaluateString */
    final int n = inputCol.isRepeating ? 1 : batch.size;
    int[] sel = batch.selected;


    if(batch.size == 0) {

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    }
    batch1.size = BOOLEAN_COLUMN_TEST_SIZE;
    batch1.selectedInUse = false;


    // Swap column vectors to simulate change in data
    ColumnVector tmp = batch1.cols[0];
    batch1.cols[0] = batch1.cols[1];
    batch1.cols[1] = tmp;


    orExpr.evaluate(batch1);

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    // Evaluate batch1 so that temporary arrays in the expression
    // have residual values to interfere in later computation
    orExpr.evaluate(batch1);


    // Swap column vectors, but keep selected vector unchanged
    ColumnVector tmp = batch1.cols[0];
    batch1.cols[0] = batch1.cols[1];
    batch1.cols[1] = tmp;
    // Make sure row-7 is in the output.
    batch1.cols[1].isNull[7] = false;
    ((LongColumnVector) batch1.cols[1]).vector[7] = 0;

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    }
  }


  private void testDateAddColScalar(VectorExpression.Type colType1, boolean isPositive) {
    LongColumnVector date1 = newRandomLongColumnVector(10000, size);
    ColumnVector col1 = castTo(date1, colType1);
    long scalar2 = newRandom(1000);
    BytesColumnVector output = new BytesColumnVector(size);


    VectorizedRowBatch batch = new VectorizedRowBatch(2, size);
    batch.cols[0] = col1;

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  }


  private void testDateAddColCol(VectorExpression.Type colType1, boolean isPositive) {
    LongColumnVector date1 = newRandomLongColumnVector(10000, size);
    LongColumnVector days2 = newRandomLongColumnVector(1000, size);
    ColumnVector col1 = castTo(date1, colType1);


    BytesColumnVector output = new BytesColumnVector(size);


    VectorizedRowBatch batch = new VectorizedRowBatch(3, size);
    batch.cols[0] = col1;

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  public void testDateDiffScalarCol() {
    for (VectorExpression.Type scalarType1 : dateTimestampStringTypes) {
      for (VectorExpression.Type colType2 : dateTimestampStringTypes) {
        LongColumnVector date2 = newRandomLongColumnVector(10000, size);
        LongColumnVector output = new LongColumnVector(size);
        ColumnVector col2 = castTo(date2, colType2);
        VectorizedRowBatch batch = new VectorizedRowBatch(2, size);
        batch.cols[0] = col2;
        batch.cols[1] = output;
        long scalar1 = newRandom(1000);

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    if (childExpressions != null) {
      super.evaluateChildren(batch);
    }


    ColumnVector inputColVector1 = batch.cols[colNum1];
    ColumnVector inputColVector2 = batch.cols[colNum2];
    int[] sel = batch.selected;
    int n = batch.size;


    LongColumnVector outV = (LongColumnVector) batch.cols[outputColumn];
    long[] outputVector = outV.vector;

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    if (childExpressions != null) {
      super.evaluateChildren(batch);
    }


    LongColumnVector outV = (LongColumnVector) batch.cols[outputColumn];
    ColumnVector inputCol = batch.cols[this.colNum];
    /* every line below this is identical for evaluateLong & evaluateString */
    final int n = inputCol.isRepeating ? 1 : batch.size;
    int[] sel = batch.selected;


    if(batch.size == 0) {

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