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An overview of query optimization in relational systems 1. Objective.
| Content Provider | CiteSeerX |
|---|---|
| Author | Chaudhuri, Surajit |
| Abstract | Them has been cxtensivc work in query optimization since the enrly ‘70s. It is hard to capture the breadth and depth of this large body of work in a short article. Therefore, I have decided to focus primarily on the optimization of SQL queries in relational dntnbasc systems and present my biased and incomplete view of this licld, The goal of this article is not to be comprehensive, but ratbcr to explain the foundations and present samplings of significant work in this area. I would like to apologize to the many contributors in this area whose work I have failed to explicitly ncknowlcdge due to oversight or lack of space. I take the liberty of trndlng tcchnicnl precision for ease of presentation. the qrrery execrrtiort engine. The query cxccution engine implements a set of physical operators, An operator takes as input one or more data streams and produces an output data stream. Examples of physical operators nrc (external) sort, sequential scan, index scan, nestedloop join, nnd sort-merge join. I refer to such operators as physical operators since they are not necessarily tied one-to-one with relntionnl operators, The simplest way to think of physical operntors is ns pieces of code that are used as building blocks to representation of such nn execution is a physical operator tree, as lllustrntcd in Figure I. The edges in an operator tree represent the data flow among the physical operators. We use the terms physical operator tree and executbt plan (or, simply plan) lnterchnngenbly. The execution engine is responsible for the execution of the plan that results in generating answers to the query. Therefore, the capabilities of the query execution engine dctcrminc the structure of the operator trees that are feasible. We rcfcr the reader to [20] for an overview of query evaluation techniques, |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Query Optimization Trndlng Tcchnicnl Precision Executbt Plan Qrrery Execrrtiort Engine Nn Execution Relational Dntnbasc System Operator Tree Relntionnl Operator Sql Query Term Physical Operator Tree Cxtensivc Work Data Flow Query Execution Engine Physical Operator Significant Work Building Block Present Sampling Data Stream Query Evaluation Technique N Piece Physical Operator Tree Physical Operntors Output Data Stream Short Article Nnd Sort-merge Join Relational System Execution Engine Nestedloop Join Incomplete View Large Body Query Cxccution Engine Sequential Scan Many Contributor |
| Content Type | Text |
| Resource Type | Article |
