Interpartition parallelism with queries that reference nicknames - performance expectations

For queries that reference a combination of local partitioned tables and nicknames, the optimizer can choose an execution plan that redistributes nickname data across appropriate partitions.

Redistribution plans can make queries run faster if the amount of nickname data in the join is smaller than the amount of local partitioned data. If the amount of nickname data in the join is considerably larger than the local data, then a parallel plan with redistribution of the nickname data is unlikely to be used. If the optimizer does not choose a parallel plan, the federated server performs the joins serially between nicknames and local tables at the coordinator partition.

For joins between two nicknames, an execution plan that distributes the data among all partitions of a computational partition group can be beneficial if it involves a large amount of data. The advantage of processing the large join in parallel offsets the additional cost of redistributing the data across multiple partitions. If the amount of nickname data is relatively small, the join is not expensive enough to merit the extra cost of redistributing the data across partitions. In general, the optimizer chooses computational partition group plans if the nicknames involved are large; otherwise, the federated server joins the nicknames serially at the coordinator partition.