@Override
  public void evaluate(VectorizedRowBatch batch) throws HiveException {

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

    LongColumnVector inputColVector = (LongColumnVector) batch.cols[inputColumnNum[0]];
    LongColumnVector outputColVector = (LongColumnVector) batch.cols[outputColumnNum];
    int[] sel = batch.selected;
    boolean[] inputIsNull = inputColVector.isNull;
    boolean[] outputIsNull = outputColVector.isNull;
    int n = batch.size;
    long[] vector = inputColVector.vector;
    long[] outputVector = outputColVector.vector;

    // return immediately if batch is empty
    if (n == 0) {
      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]) {
        outputIsNull[0] = false;
        outputVector[0] = func(vector[0]);
      } else {
        outputIsNull[0] = true;
        outputColVector.noNulls = false;
      }
      outputColVector.isRepeating = true;
      return;
    }

    if (inputColVector.noNulls) {
      if (batch.selectedInUse) {

        // CONSIDER: For large n, fill n or all of isNull array and use the tighter ELSE loop.

        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] = func(vector[i]);
         }
        } else {
          for(int j = 0; j != n; j++) {
            final int i = sel[j];
            outputVector[i] = func(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++) {
          outputVector[i] = func(vector[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];
          outputIsNull[i] = inputIsNull[i];
          outputVector[i] = func(vector[i]);
        }
      } else {
        System.arraycopy(inputIsNull, 0, outputIsNull, 0, n);
        for(int i = 0; i != n; i++) {
          outputVector[i] = func(vector[i]);
        }
      }
    }
  }
Implement vectorized math function that takes a long (and optionally additional
constant argument(s)) and returns long. Use this for PMOD() etc.

Do NOT use this for simple math functions like sin/cos/exp etc. that just take
a single argument. For those, modify the template ColumnUnaryFunc.txt
and expand the template to generate needed classes.
ql/src/java/org/apache/hadoop/hive/ql/exec/vector/expressions/MathFuncLongToLong.java