@Override
    public AggregationBuffer getNewAggregationBuffer() throws HiveException {
      StdAgg result = new StdAgg();
      reset(result);
      return result;
    }
Evaluate the variance using the algorithm described by Chan, Golub, and LeVeque in
"Algorithms for computing the sample variance: analysis and recommendations"
The American Statistician, 37 (1983) pp. 242--247.

variance = variance1 + variance2 + n/(m*(m+n)) * pow(((m/n)*t1 - t2),2)

where: - variance is sum[x-avg^2] (this is actually n times the variance)
and is updated at every step. - n is the count of elements in chunk1 - m is
the count of elements in chunk2 - t1 = sum of elements in chunk1, t2 =
sum of elements in chunk2.

This algorithm was proven to be numerically stable by J.L. Barlow in
"Error analysis of a pairwise summation algorithm to compute sample variance"
Numer. Math, 58 (1991) pp. 583--590
ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDAFVariance.java