S. Chaudhuri and K. Shim. Complex queries: A unified approach. Technical report, Hewlett-Packard Laboratories, Palo Alto, In preparation to submit for publication 1995. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
An Overview of Cost-based Optimization of Queries with.. - Chaudhuri, Shim (1995) (4 citations) Self-citation (Chaudhuri Shim) (Correct)
....that enable us to optimize queries containing Group By and join. ffl Optimization algorithms that can incorporate the above transformations without increasing the search space dramatically. We begin by considering optimization of single block SQL queries. We refer the readers to [CS94, CS95, CS96] for the technical details. 2 Transformations for Single Block SQL There are several transformations that make it possible for a group by to precede a join. The conditions that make such transformations possible fall in the following broad categories: R1 R2 Join G R1 G1 R2 Join (e) a) ....
....CS96] The problem of optimization using the transformations was addressed by us in [CS94] for single block SQL queries and in [CS96] for multi block SQL queries. A comprehensive treatment of the transformations as well as the optimization algorithms discussed in this article is forthcoming in [CS95] ....
S. Chaudhuri and K. Shim. Complex queries: A unified approach. Technical report, Hewlett-Packard Laboratories, Palo Alto, In preparation to submit for publication 1995.
Optimizing Queries with Aggregate Views - Chaudhuri, Shim (1996) (16 citations) Self-citation (Chaudhuri Shim) (Correct)
....on a query with nested subqueries is a query that is a join 3 of base tables and one or more aggregate views. Thus, using Kim s transformation, the result of optimizing queries containing aggregate views can be used for optimizing an important class of queries with correlated nested subqueries [CS96] Unfortunately, the techniques for optimizing queries with aggregate views have been limited to propagating predicates across query blocks [MFPR90, LMS94] to reduce the cost of optimizing each query block. However, subsequent to this preprocessing, each query block is optimized locally using the ....
....) where G is a group by operator and V is a SPJ query. To simplify the presentation, we assume that every aggregate view is also a single block query, the database contains no NULLs and there are no outerjoins in the query. In the full version of our paper, we show how to relax these restrictions [CS96] We can view our queries algebraically in terms of operators. An operator tree reflects the partial order on evaluation of operators in a query. In this paper, we use the term operator tree and execution plan alternatively. In this paper, we will consider join and group by operators. A join ....
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S. Chaudhuri and K. Shim. Complex queries: A unified approach. Technical report, Hewlett-Packard Laboratories, Palo Alto, In preparation, 1996.
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