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Cardinality estimation in turn depends on estimates of the selection factor of predicates in the query. Traditionally, database systems estimate selectivities through fairly detailed statistics on the distribution of values in each column, such as histograms. This technique works well for estimation of selectivities of individual predicates.
In computer science, the count-distinct problem [1] (also known in applied mathematics as the cardinality estimation problem) is the problem of finding the number of distinct elements in a data stream with repeated elements. This is a well-known problem with numerous applications.
In SQL (Structured Query Language), the term cardinality refers to the uniqueness of data values contained in a particular column (attribute) of a database table. The lower the cardinality, the more duplicated elements in a column. Thus, a column with the lowest possible cardinality would have the same value for every row.
4D Server is used for Client-Server connectivity to the application. In this mode, 4D Server loads the structure file (4DB or 4DC) and also the datafile (4DD) and provides network access to 4D (in remote). Each workstation has a dynamically updated cache of the resources they are working with, while the 4D Server maintains the data and code.
SQL Anywhere (formerly known as Sybase Adaptive Server Anywhere and Watcom SQL) Proprietary SQL Azure (Cloud SQL Server) Proprietary SQLBase: Proprietary SQLite: Public Domain SQream DB: Proprietary SAP Advantage Database Server (formerly known as Sybase Advantage Database Server) Proprietary Teradata: Proprietary TiDB: Apache License 2.0 ...
In this example, the three lines next to the song entity indicate that an artist can have many songs. The two vertical lines next to the artist entity indicate songs can only have one performer. In the real world, data modeling is critical because as the data grows voluminous, tables linked by keys must be used to speed up programmed retrieval ...
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".
For example: SQL Server runs only on Microsoft Windows operating-systems (Starting with SQL Server 2017, SQL Server runs on Linux. It's the same SQL Server database engine, with many similar features and services regardless of your operating system [2]), while Oracle and MySQL can run on Solaris, Linux and other UNIX-based operating-systems as ...