VLDB and Partitioning
1-2 Oracle Database VLDB and Partitioning Guide
■ It improves query performance. Often the results of a query can be achieved by
accessing a subset of partitions, rather than the entire table. For some queries, this
technique (called partition pruning) can provide order-of-magnitude gains in
performance.
■ It significantly reduces the impact of scheduled downtime for maintenance
operations.
Partition independence for partition maintenance operations lets you perform
concurrent maintenance operations on different partitions of the same table or
index. You can also run concurrent
SELECT
and DML operations against partitions
that are unaffected by maintenance operations.
■ It increases the availability of mission-critical databases if critical tables and
indexes are divided into partitions to reduce the maintenance windows, recovery
times, and impact of failures.
■ Parallel execution provides specific advantages to optimize resource utilization,
and minimize execution time. Parallel execution against partitioned objects is key
for scalability in a clustered environment. Parallel execution is supported for
queries and for DML and DDL.
Partitioning enables faster data access within an Oracle database. Whether a database
has 10 GB or 10 TB of data, partitioning can improve data access by orders of
magnitude. Partitioning can be implemented without requiring any modifications to
your applications. For example, you could convert a nonpartitioned table to a
partitioned table without needing to modify any of the
SELECT
statements or DML
statements that access that table. You do not need to rewrite your application code to
take advantage of partitioning.
VLDB and Partitioning
A very large database has no minimum absolute size. Although a VLDB is a database
like smaller databases, there are specific challenges in managing a VLDB. These
challenges are related to the sheer size and the cost-effectiveness of performing
operations against a system of that size.
Several trends have been responsible for the steady growth in database size:
■ For a long time, systems have been developed in isolation. Companies have
started to see the benefits of combining these systems to enable cross-departmental
analysis while reducing system maintenance costs. Consolidation of databases and
applications is a key factor in the ongoing growth of database size.
■ Many companies face regulations for storing data for a minimum amount of time.
The regulations generally result in more data being stored for longer periods of
time.
■ Companies grow by expanding sales and operations or through mergers and
acquisitions, causing the amount of generated and processed data to increase. At
the same time, the user population that relies on the database for daily activities
increases.
Partitioning is a critical feature for managing very large databases. Growth is the basic
challenge that partitioning addresses for very large databases, and partitioning enables
a divide and conquer technique for managing the tables and indexes in the database,
especially as those tables and indexes grow. Partitioning is the feature that allows a
database to scale for very large data sets while maintaining consistent performance,
without unduly increasing administrative or hardware resources.
Chapter 3,
我的内容管理
展开
