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Horizontal partitioning splits one or more tables by row, usually within a single instance of a schema and a database server. It may offer an advantage by reducing index size (and thus search effort) provided that there is some obvious, robust, implicit way to identify in which partition a particular row will be found, without first needing to search the index, e.g., the classic example of the ...
In October 2007, IBM released DB2 9.5 with improved XML data transaction performance and improved storage savings. [4] In June 2009, IBM released DB2 9.7 with XML supported for database-partitioned, range-partitioned, and multi-dimensionally clustered tables as well as compression of XML data and indices. [5]
Vertical partitioning involves creating tables with fewer columns and using additional tables to store the remaining columns. [2] Generally, this practice is known as normalization . However, vertical partitioning extends further, and partitions columns even when already normalized.
DB2 9.7 added data compression for database indexes, temporary tables, and large objects. DB2 9.7 also supported native XML data in hash partitioning (database partitioning), range partitioning (table partitioning), and multi-dimensional clustering. These native XML features allow users to directly work with XML in data warehouse environments.
In computing, a materialized view is a database object that contains the results of a query.For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function.
A complete physical data model will include all the database artifacts required to create relationships between tables or to achieve performance goals, such as indexes, constraint definitions, linking tables, partitioned tables or clusters. Analysts can usually use a physical data model to calculate storage estimates; it may include specific ...
A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and storage space to maintain the index data structure. Indexes are used to quickly locate data without having to search every row in a database table every time said table is accessed.
Virtual Storage Access Method (VSAM) [1] is an IBM direct-access storage device (DASD) file storage access method, first used in the OS/VS1, OS/VS2 Release 1 (SVS) and Release 2 (MVS) operating systems, later used throughout the Multiple Virtual Storage (MVS) architecture and now in z/OS.