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An SQL UPDATE statement changes the data of one or more records in a table. Either all the rows can be updated, or a subset may be chosen using a condition. The UPDATE statement has the following form: [1] UPDATE table_name SET column_name = value [, column_name = value ...] [WHERE condition]
A relational database management system uses SQL MERGE (also called upsert) statements to INSERT new records or UPDATE or DELETE existing records depending on whether condition matches. It was officially introduced in the SQL:2003 standard, and expanded [citation needed] in the SQL:2008 standard.
An inner join (or join) requires each row in the two joined tables to have matching column values, and is a commonly used join operation in applications but should not be assumed to be the best choice in all situations. Inner join creates a new result table by combining column values of two tables (A and B) based upon the join-predicate.
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
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Title Authors ----- ----- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1 Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:
The right outer join ( ) behaves almost identically to the left outer join, but the roles of the tables are switched. The right outer join of relations R and S is written as R S. [e] The result of the right outer join is the set of all combinations of tuples in R and S that are equal on their common attribute names, in addition to tuples in S ...
The hash join is an example of a join algorithm and is used in the implementation of a relational database management system.All variants of hash join algorithms involve building hash tables from the tuples of one or both of the joined relations, and subsequently probing those tables so that only tuples with the same hash code need to be compared for equality in equijoins.