We apply the one-shot semi-join execution strategy, which allows parallelism and processes multiple semi-joins simultaneously, to optimize the transmission cost of distributed queries. The queryoptimization problem b...
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We apply the one-shot semi-join execution strategy, which allows parallelism and processes multiple semi-joins simultaneously, to optimize the transmission cost of distributed queries. The queryoptimization problem based on this strategy is NP-hard. Nevertheless, in practice most of the parameters needed for queryoptimization, such as relation cardinality and selectivity, are of fixed-precision, i.e. their binary representations have no more than a fixed number of digits after the binary point. Imposing this fixed-precision constraint, we develop an efficient distributedquery processing algorithm. For situations where the fixed-precision constraint does not apply, we propose a method to truncate the parameters and use the same algorithm to find near-optimal solutions. By analysing the truncation errors, we provide a quantitative comparison between the near-optimal solutions and the optimal ones.
A multidatabase system (MDBS) integrates information from autonomous local databases managed by heterogeneous database management systems (DBMS) in a distributed environment. For a query involving more than one databa...
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A multidatabase system (MDBS) integrates information from autonomous local databases managed by heterogeneous database management systems (DBMS) in a distributed environment. For a query involving more than one database, global queryoptimization should be performed to achieve good overall system performance. The significant differences between an MDBS and a traditional distributed database system (DDBS) make queryoptimization in the former more challenging than in the latter. Challenges for queryoptimization in an MDBS are discussed in this paper. A two-phase optimization approach for processing a query in an MDBS is proposed. Several global queryoptimization techniques suitable for an MDBS, such as semantic queryoptimization, queryoptimization via probing queries, parametric queryoptimization and adaptive queryoptimization, are suggested. The architecture of a global query optimizer incorporating these techniques is designed.
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