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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 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.
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 ...
This is an important element of SQL. Statements, which may have a persistent effect on schemata and data, or may control transactions, program flow, connections, sessions, or diagnostics. SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar.
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The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases.. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".