1.Partitioned Tables and Indexes
You can partition tables and indexes. Partitioning helps to support very large tables and indexes by enabling you to divide the tables and indexes into smaller and more manageable pieces called partitions. SQL queries and DML statements do not have to be modified to access partitioned tables and indexes. Partitioning is transparent to the application.
After partitions are defined, certain operations become more efficient. For example, for some queries, the database can generate query results by accessing only a subset of partitions, rather than the entire table. This technique (called partition pruning) can provide order-of-magnitude gains in improved performance. In addition, data management operations can take place at the partition level, rather than on the entire table. This results in reduced times for operations such as data loads; index creation and rebuilding; and backup and recovery.
Each partition can be stored in its own tablespace, independent of other partitions. Because different tablespaces can be on different disks, this provides a table structure that can be better tuned for availability and performance. Storing partitions in different tablespaces on separate disks can also optimize available storage usage, because frequently accessed data can be placed on high-performance disks, and infrequently retrieved data can be placed on less expensive storage.
Partitioning is useful for many types of applications that manage large volumes of data. Online transaction processing (OLTP) systems often benefit from improvements in manageability and availability, while data warehousing systems benefit from increased performance and manageability.
As with tables, you can partition an index. In most situations, it is useful to partition an index when the associated table is partitioned, and to partition the index using the same partitioning scheme as the table. (For example, if the table is range-partitioned by sales date, then you create an index on sales date and partition the index using the same ranges as the table partitions.) This is known as a local partitioned index. However, you do not have to partition an index using the same partitioning scheme as its table. You can also create a nonpartitioned, or global, index on a partitioned table.
Table Compression is suitable for both OLTP applications and data warehousing applications. Compressed tables require less disk storage and result in improved query performance due to reduced I/O and buffer cache requirements. Compression is transparent to applications and incurs minimal overhead during bulk loading or regular DML operations such as INSERT, UPDATE or DELETE.