Issue No. 04 - December (1990 vol. 2)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/69.63253
<p>The effectiveness of parallel processing of relational join operations is examined. The skew in the distribution of join attribute values and the stochastic nature of the task processing times are identified as the major factors that can affect the effective exploitation of parallelism. Expressions for the execution time of parallel hash join and semijoin are derived and their effectiveness analyzed. When many small processors are used in the parallel architecture, the skew can result in some processors becoming sources of bottleneck while other processors are being underutilized. Even in the absence of skew, the variations in the processing times of the parallel tasks belonging to a query can lead to high task synchronization delay and impact the maximum speedup achievable through parallel execution. For example, when the task processing time on each processor is exponential with the same mean, the speedup is proportional to P/ln(P) where P is the number of processors. Other factors such as memory size, communication bandwidth, etc., can lead to even lower speedup. These are quantified using analytical models.</p>
parallel processing; relational join operations; skew; distribution; join attribute values; stochastic nature; task processing times; execution time; parallel hash join; semijoin; small processors; parallel architecture; high task synchronization delay; maximum speedup; parallel execution; database theory; parallel programming; relational databases; storage management
M. Lakshmi and P. Yu, "Effectiveness of Parallel Joins," in IEEE Transactions on Knowledge & Data Engineering, vol. 2, no. , pp. 410-424, 1990.