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An INSERT statement can also be used to retrieve data from other tables, modify it if necessary and insert it directly into the table. All this is done in a single SQL statement that does not involve any intermediary processing in the client application.
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 SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
Data storage in large databases is layered and chunked, with the table storage arranged into 'blocks'. Each block contains perhaps 1MB in each chunk [iii] [13] and they are retrieved by requesting specific blocks from a disk-based storage layer. BRIN are a lightweight in-memory summary layer above this: each tuple in the index summarises one ...
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.)
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The data rows may be spread throughout the table regardless of the value of the indexed column or expression. The non-clustered index tree contains the index keys in sorted order, with the leaf level of the index containing the pointer to the record (page and the row number in the data page in page-organized engines; row offset in file ...
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