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  2. Set operations (SQL) - Wikipedia

    en.wikipedia.org/wiki/Set_operations_(SQL)

    A UNION query could combine results from both tables. Note that UNION ALL does not guarantee the order of rows. Rows from the second operand may appear before, after, or mixed with rows from the first operand. In situations where a specific order is desired, ORDER BY must be used. Note that UNION ALL may be much faster than plain UNION.

  3. Merge (SQL) - Wikipedia

    en.wikipedia.org/wiki/Merge_(SQL)

    A right join is employed over the Target (the INTO table) and the Source (the USING table / view / sub-query)--where Target is the left table and Source is the right one. The four possible combinations yield these rules:

  4. Correlated subquery - Wikipedia

    en.wikipedia.org/wiki/Correlated_subquery

    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.

  5. Join (SQL) - Wikipedia

    en.wikipedia.org/wiki/Join_(SQL)

    One can classify query-plans involving joins as follows: [12] left-deep using a base table (rather than another join) as the inner operand of each join in the plan right-deep using a base table as the outer operand of each join in the plan bushy neither left-deep nor right-deep; both inputs to a join may themselves result from joins

  6. Having (SQL) - Wikipedia

    en.wikipedia.org/wiki/Having_(SQL)

    If a query contains GROUP BY, rows from the tables are grouped and aggregated. After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.

  7. View (SQL) - Wikipedia

    en.wikipedia.org/wiki/View_(SQL)

    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]

  8. DUAL table - Wikipedia

    en.wikipedia.org/wiki/DUAL_table

    The idea was that you could do a JOIN to the DUAL table and create two rows in the result for every one row in your table. Then, by using GROUP BY, the resulting join could be summarized to show the amount of storage for the DATA extent and for the INDEX extent(s). The name, DUAL, seemed apt for the process of creating a pair of rows from just one.

  9. Nested set model - Wikipedia

    en.wikipedia.org/wiki/Nested_set_model

    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".