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The performance of a query plan is determined largely by the order in which the tables are joined. For example, when joining 3 tables A, B, C of size 10 rows, 10,000 rows, and 1,000,000 rows, respectively, a query plan that joins B and C first can take several orders-of-magnitude more time to execute than one that joins A and C first.
Since SQL is declarative, there are typically many alternative ways to execute a given query, with widely varying performance. When a query is submitted to the database, the query optimizer evaluates some of the different, correct possible plans for executing the query and returns what it considers the best option.
In various SQL implementations, a hint is an addition to the SQL standard that instructs the database engine on how to execute the query. For example, a hint may tell the engine to use or not to use an index (even if the query optimizer would decide otherwise).
The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the ...
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
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The programming model becomes what a SQL statement would be like with multiple WHERE clauses. The combination of list-aware subjects and objects plus a pipeline approach can yield extremely expressive queries spanning many different domains of data. Here is a more comprehensive example that illustrates the pipeline using some syntax shortcuts.
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