INVERSE DISTRIBUTION FUNCTION OPERATIONS IN A PARALLEL RELATIONAL DATABASE

Inverse distribution operations are performed on a large distributed parallel database comprising a plurality of distributed data segments to determine a data value at a predetermined percentile of a sorted dataset formed on one segment. Data elements from across the segments may be first grouped, either by partitioning keys or by hashing, the groups are sorted into a predetermined order, and data values corresponding to the desired percentile are picked up at a row location of the corresponding data element of each group. For a global dataset that is spread across the database segments, a local sort of data elements is performed on each segment, and the data elements from the local sorts are streamed in overall sorted order to one segment to form the sorted dataset.