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A SQL query to a modern relational DBMS does more than just selections and joins. In particular, SQL queries often nest several layers of SPJ blocks (Select-Project-Join), by means of group by, exists, and not exists operators. In some cases such nested SQL queries can be flattened into a select-project-join query, but not always. Query plans ...
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.
Conjunctive queries also correspond to select-project-join queries in relational algebra (i.e., relational algebra queries that do not use the operations union or difference) and to select-from-where queries in SQL in which the where-condition uses exclusively conjunctions of atomic equality conditions, i.e. conditions constructed from column ...
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.
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.
A query failing to be sargable is known as a non-sargable query and typically has a negative effect on query time, so one of the steps in query optimization is to convert them to be sargable. The effect is similar to searching for a specific term in a book that has no index, beginning at page one each time, instead of jumping to a list of ...
Covering indexes are each for a specific table. Queries which JOIN/ access across multiple tables, may potentially consider covering indexes on more than one of these tables. [7] A covering index can dramatically speed up data retrieval but may itself be large due to the additional keys, which slow down data insertion and update.
Additionally there is a single-row version, UPDATE OR INSERT INTO tablename (columns) VALUES (values) [MATCHING (columns)], but the latter does not give you the option to take different actions on insert versus update (e.g. setting a new sequence value only for new rows, not for existing ones.)