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When a user starts a data-retrieval operation, the user s SQL statement goes through several sequential steps that together constitute query processing. One of the great benefits of using the SQL language is that it isn t a procedural language in which you have to specify the steps to be followed to achieve the statement s goal. In other words, you don t have to state how to do something; rather, you just state what you need from the database. Query processing is the transformation of your SQL statement into an efficient execution plan to return the requested data from the database. Query optimization is the process of choosing the most efficient execution plan. The goal is to achieve the result with the least cost in terms of resource usage. Resources include the I/O and CPU usage on the server where your database is running. This also means that the goal is to reduce the total execution time of the query, which is simply the sum of the execution times of all the component operations of the query. This optimization of throughput may not be the same as minimizing response time. If you want to minimize the time it takes to get the first n rows of a query instead of the entire output of the query, the Optimizer may choose a different plan. If you choose to minimize the response time for all the query data, you may also choose to parallelize the operation. A user s SQL statement goes through the parsing, optimizing, and execution stages. If the SQL statement is a query, data has to be retrieved, so there s an additional fetch stage before the SQL statement processing is complete. In the next sections you ll examine what Oracle does during each of these steps.

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Parsing primarily consists of checking the syntax and semantics of the SQL statements. The end product of the parse stage of query compilation is the creation of the parse tree, which represents the query s structure. The SQL statement is decomposed into a relational algebra query that s analyzed to see whether it s syntactically correct. The query then undergoes semantic checking. The data dictionary is consulted to ensure that the tables and the individual columns that are referenced in the query do exist, as well as all the object privileges. In addition, the column types are checked to ensure that the data matches the column definitions. The statement is normalized so it can be processed more efficiently. The query is rejected if it is incorrectly formulated. Once the parse tree passes all the syntactic and semantic checks, it s considered a valid parse tree, and it s sent to the logical query plan generation stage. All these operations take place in the library cache portion of the SGA.

Here s the output:

During the optimization phase, Oracle uses its optimizer which is a cost-based optimizer (CBO) to choose the best access method for retrieving data for the tables and indexes referred to in the query. Using statistics that you provide and any hints specified in the SQL queries, the CBO produces an optimal execution plan for the SQL statement.

The optimization phase can be divided into two distinct parts: the query rewrite phase and the physical execution plan generation phase. Let s look at these two optimization phases in detail.

In this phase, the parse tree is converted into an abstract logical query plan. This is an initial pass at an actual query plan, and it contains only a general algebraic reformulation of the initial query. The various nodes and branches of the parse tree are replaced by operators of relational algebra. Note that the query rewriting here isn t the same as the query rewriting that s involved in using materialized views.


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