Query Processing

In most database systems, queries are posed in a non-procedural language like SQL and as we have noted earlier such queries do not involve any reference to access paths or the order of evaluation of operations. The query processing of such queries by a DBMS usually involves the following four phases:

1. Parsing
2. Optimization
3. Code Generation
4. Execution

The parser basically checks the query for correct syntax and translates it into a conventional parse-tree (often called a query-tree) or some other internal representation. If the parser returns with no errors, and the query uses some user-defined views, it is necessary to expand the query by making appropriate substitutions for the views. It is then necessary to check the query for semantic correctness by consulting the system catalogues and check for semantic errors and type compatibility in both expressions and predicate comparisons. The optimizer is then invoked with the internal representation of the query as input so that a query plan or execution plan may be devised for retrieving the information that is required. The optimizer carries out a number of operations. It relates the symbolic names in the query to data base objects and checks their existence and checks if the user is authorized to perform the operations that the query specifies.

In formulating the plans, the query optimizer obtains relevant information from the metadata that the system maintains and attempts to model the estimated costs of performing many alternative query plans and then selects the best amongst them. The metadata or system catalog consists of descriptions of all the databases that a DBMS maintains. Often, the query optimizer would at least retrieve the following information:

1. Cardinality of each relation of interest.
2. The number of pages in each relation of interest.
3. The number of distinct keys in each index of interest.
4. The number of pages in each index of interest.

The above information and perhaps other information will be used by the optimizer in modeling the cost estimation for each alternative query plan. Considerable other information is normally available in the system catalog:

1. Name of each relation and all its attributes and their domains.
2. Information about the primary key and foreign keys of each relation.
3. Descriptions of views.
4. Descriptions of storage structures.
5. Other information including information about ownership and security issues.

Often this information is updated only periodically and not at every update/insert/delete. Also, the system catalog is often stored as a relational database itself making it easy to query the catalog if a user is authorized to do so.

Information in the catalog is very important of course since query processing makes use of this information extensively. Therefore more comprehensive and more accurate information a database maintains the better optimization it can carry out but maintaining more comprehensive and more accurate information also introduces additional overheads and a good balance therefore must be found.

The catalog information is also used by the optimizer in access path selection. These statistics are often updated only periodically and are therefore not always accurate.

An important part of the optimizer is the component that consults the metadata stored in the database to obtain statistics about the referenced relations and the access paths available on them. These are used to determine the most efficient order of the relational operations and the most efficient access paths.

If the optimizer finds no errors and outputs an execution plan, the code generator is then invoked. The execution plan is used by the code generator to generate the machine language code and any associated data structures. This code may now be stored if the code is likely to be executed more than once. To execute the code, the machine transfers control to the code which is then executed.


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