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A hierarchical query is a type of SQL query that handles hierarchical model data. They are special cases of more general recursive fixpoint queries, which compute transitive closures . In standard SQL:1999 hierarchical queries are implemented by way of recursive common table expressions (CTEs).
Without an ORDER BY clause, the order of rows returned by an SQL query is undefined. The DISTINCT keyword [5] eliminates duplicate data. [6] The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater
The query optimizer attempts to determine the most efficient way to execute a given query by considering the possible query plans. [1] Generally, the query optimizer cannot be accessed directly by users: once queries are submitted to the database server, and parsed by the parser, they are then passed to the query optimizer where optimization ...
The input and output domains may be the same, such as for SUM, or may be different, such as for COUNT. Aggregate functions occur commonly in numerous programming languages, in spreadsheets, and in relational algebra. The listagg function, as defined in the SQL:2016 standard [2] aggregates data from multiple rows into a single concatenated string.
The internal bitmap is discarded after the query. If there are too many rows in the table to use 1 bit per row, a "lossy" bitmap is created instead, with a single bit per disk page. In this case, the bitmap is just used to determine which pages to fetch; the filter criteria are then applied to all rows in matching pages.
Microsoft SQL Server 2017: RC1: Proprietary: SQL/T-SQL, R, Python: Offers graph database abilities to model many-to-many relationships. The graph relationships are integrated into Transact-SQL, and use SQL Server as the foundational database management system. [36] NebulaGraph: 3.7.0: 2024-03: Open Source Edition is under Apache 2.0, Common ...
A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items. Vector databases typically implement one or more Approximate Nearest Neighbor algorithms, [1] [2] [3] so that one can search the database with a query vector to retrieve the closest matching database records.
For example, it is easy to support COUNT, MAX, MIN, and SUM in OLAP, since these can be computed for each cell of the OLAP cube and then rolled up, since on overall sum (or count etc.) is the sum of sub-sums, but it is difficult to support MEDIAN, as that must be computed for every view separately: the median of a set is not the median of ...