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In SQL (Structured Query Language), the term cardinality refers to the uniqueness of data values contained in a particular column (attribute) of a database table. The lower the cardinality, the more duplicated elements in a column. Thus, a column with the lowest possible cardinality would have the same value for every row.
Oracle implements hints by using specially-crafted comments in the query that begin with a + symbol, thus not affecting SQL compatibility. [2] EDB Postgres Advanced Server (a proprietary version of PostgreSQL from EnterpriseDB) offers hints compatible with those of Oracle. [3] [4] Microsoft SQL Server offers hints via the OPTION keyword [5]
Cardinality estimation in turn depends on estimates of the selection factor of predicates in the query. Traditionally, database systems estimate selectivities through fairly detailed statistics on the distribution of values in each column, such as histograms. This technique works well for estimation of selectivities of individual predicates.
In some databases the query plan can be reviewed, problems found, and then the query optimizer gives hints on how to improve it. In other databases, alternatives to express the same query (other queries that return the same results) can be tried. Some query tools can generate embedded hints in the query, for use by the optimizer.
In computer science, the count-distinct problem [1] (also known in applied mathematics as the cardinality estimation problem) is the problem of finding the number of distinct elements in a data stream with repeated elements. This is a well-known problem with numerous applications.
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The second example shows a SQL statement which returns the name of all fruits in the fruits table. Because this statement has no condition - no WHERE clause - the database engine will use a table scan to load and return the data for this query even if the fruits table has an index on the name column because accessing - i.e. scanning - the table ...