Dataflow query execution in a parallel main-memory environment

In this paper, the performance of characteristics of the execution of various join-trees on a parallel DBMS are studied. The results of this study, are a step into the direction of the design of a query optimization strategy that is fit for parallel execution of complex queries. Among others, synchronization issues are identified to limit the perfo rmance gain from parallelism. A new hash-join algorithm, called Pipelining hash-join is introduced that has fewer synchronization constraints than the known hash-join algorithms. Also, the behavior of individual join operations in a join-tree is studied in a simulation experiment. The results show that the Pipelining hash-join algorithms yields a better performance for multi-join queries. Also, the format of the optimal join-tree appears to depend on the size of the operands of the join: A multi-join between small operands performs best with a bushy schedule; larger operands are better off with a linear schedule. The results from the simulation study are confirmed with an analytic model for dataflow query execution.