Use partitioning to manage large tables and indexes by dividing them into smaller, more manageable pieces. Partitions, like a large-scale index, provide faster and easier access to data.
Each partition can reside on a separate segment. Partitions are database objects and can be managed independently. You can, for example, load data and create indexes at the partition level. Yet partitions are transparent to the end user, who can select, insert, and delete data using the same DML commands whether the table is partitioned or not.
Adaptive Server supports horizontal partitioning, in which a selection of table rows can be distributed among disk devices. Individual table or index rows are assigned to a partition according to a partitioning strategy.
Partitioning is the basis for parallel processing, which can significantly improve performance.
Semantics-based partitioning
is licensed separately. To enable semantic partitioning at a licensed
site, set the value of the enable semantic partitioning configuration
parameter to 1. See Chapter 5, “Setting Configuration Parameters,” in
the System Administration Guide: Volume 1.
Partitioning:
Improves scalability.
Improves performance – concurrent multiple I/O on different partitions, and multiple threads on multiple CPUs working concurrently on multiple partitions.
Provides faster response time.
Provides partition transparency to applications.
Supports very large database (VLDB) – concurrent scanning of multiple partitions of very large tables.
Provides range partitioning to manage historical data.
By
default, Adaptive Server creates tables with a single partition
and uses a round-robin partitioning strategy. These tables are described
as “unpartitioned” to distinguish between tables
created or modified without partitioning syntax (the default) and
those created with partitioning syntax.
