In this paper, the performance and 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 performance gain from parallelism. A new hash-join algorithm 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 introduced Pipelining hash-join algorithm yields a better performance for multi-join queries. 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.
- DB-PDB: PARALLEL DATABASES
Wilschut, A. N., & Apers, P. M. G. (1993). Dataflow Query Execution in a Parallel, Main-memory Environment. Distributed and parallel databases, 1(1), 103-128. [10.1007/BF01277522]. https://doi.org/10.1007/BF01277522