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A query plan is an extended query tree that includes access paths for all operations in the query tree. $$\pi_$įollowing is the query tree for the above query.Īfter the query tree is generated, a query plan is made. Let us consider the query as the following. This process continues for all internal nodes until the root node is executed and replaced by the result table.įor example, let us consider the following schemas − The node is then replaced by the result table. The root represents the query as a whole.ĭuring execution, an internal node is executed whenever its operand tables are available. The relational algebra operations are represented as the internal nodes. The tables of the query are represented as leaf nodes.
Phases of query processing in dbms code#
Query optimization involves three steps, namely query tree generation, plan generation, and query plan code generation.Ī query tree is a tree data structure representing a relational algebra expression. Each block is then translated to equivalent relational algebra expression. If the query passes this step, the query is decomposed into smaller query blocks.
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Then it is parsed to look for syntactical errors and correctness of data types. Reduce the amount of memory and storage required for processing. Maximize system throughput (the number of requests that are processed in a given amount of time). Minimization of response time of query (time taken to produce the results to user’s query).
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In a centralized system, query processing is done with the following aim − In this chapter, we will look into query optimization in centralized system while in the next chapter we will study query optimization in a distributed system. Once the alternative access paths for computation of a relational algebra expression are derived, the optimal access path is determined.