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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.
Actual SQL implementations normally use other approaches, such as hash joins or sort-merge joins, since computing the Cartesian product is slower and would often require a prohibitively large amount of memory to store. SQL specifies two different syntactical ways to express joins: the "explicit join notation" and the "implicit join notation".
In tableau software, data blending is a technique to combine data from multiple data sources in the data visualization. [17] A key differentiator is the granularity of the data join. When blending data into a single data set, this would use a SQL database join, which would usually join at the most granular level, using an ID field where ...
MERGE is used to combine the data of multiple tables. It combines the INSERT and UPDATE elements. It is defined in the SQL:2003 standard; prior to that, some databases provided similar functionality via different syntax, sometimes called "upsert".
In SQL, an INNER JOIN prevents a cartesian product from occurring when there are two tables in a query. For each table added to a SQL Query, one additional INNER JOIN is added to prevent a cartesian product. Thus, for N tables in an SQL query, there must be N−1 INNER JOINS to prevent a cartesian product.
UNION can be useful in data warehouse applications where tables are not perfectly normalized. [2] A simple example would be a database having tables sales2005 and sales2006 that have identical structures but are separated because of performance considerations. A UNION query could combine results from both tables.
Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).
Views can represent a subset of the data contained in a table. Consequently, a view can limit the degree of exposure of the underlying tables to the outer world: a given user may have permission to query the view, while denied access to the rest of the base table. [2] Views can join and simplify multiple tables into a single virtual table. [2]