Oracle 11g R2 VLDB与分区指南：优化与实践

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Oracle Database VLDB and Partitioning Guide 11g Release 2 (11.2) 是一份专为Oracle数据库11.2版本设计的技术指南，该文档主要关注大规模数据处理（Very Large Database, VLDB）和分区技术。VLDB是一种用于管理和操作海量数据的数据库架构，特别适用于那些需要处理大量数据、高并发和复杂查询的应用场景。在11g Release 2中，Oracle对其进行了优化和增强，以提高性能、可扩展性和管理效率。本书涵盖了以下关键知识点： 1. **概述**：介绍了VLDB的概念和在Oracle数据库中的应用，包括其对大数据处理的优势和挑战，以及与传统数据库系统相比的改进之处。 2. **分区策略**：详细讨论了分区技术，包括范围分区、列表分区、哈希分区等多种方法，以及如何根据业务需求选择合适的分区策略来提高查询性能和数据管理。 3. **物理设计最佳实践**：涵盖了如何设计有效的数据分布和索引，以及如何调整表和分区的物理结构以优化存储和访问性能。 4. **动态分区和自适应分区**：讲解了如何利用这些特性自动调整分区，以适应数据的增长和查询模式的变化。 5. **管理大型分布式环境**：指南涉及如何在分布式环境中部署和维护VLDB，包括网络架构、故障恢复和数据一致性等问题。 6. **性能调优**：提供了针对VLDB和分区的性能监控、分析工具的使用方法，以及如何通过调整参数和执行优化查询来提升系统性能。 7. **安全和备份恢复**：强调了在处理大规模数据时的安全措施和备份恢复策略，确保数据的完整性和保密性。 8. **案例研究和实战示例**：书中包含实际项目中的应用场景，通过实例演示如何在实际环境中实施VLDB和分区技术。 9. **许可证和法律条款**：提醒用户关于版权和使用限制，以及在使用软件时必须遵守的协议和法律规定。 Oracle Database VLDB and Partitioning Guide 11g Release 2 (11.2) 是一个全面的参考资源，对于开发人员、数据库管理员和数据分析师来说，它提供了深入理解并有效利用Oracle数据库处理大规模数据的必要知识和技术指导。通过学习和应用这份指南，用户可以提升数据处理能力，优化资源利用率，并应对不断增长的数据挑战。

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Related Documents

For more information, see the following documents in the Oracle Database

documentation set:

■ Oracle Database Concepts

■ Oracle Database Administrator's Guide

■ Oracle Database SQL Language Reference

■ Oracle Database Data Warehousing Guide

■ Oracle Database Performance Tuning Guide

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Introduction to Very Large Databases 1-1

Introduction to Very Large Databases

Modern enterprises frequently run mission-critical databases containing upwards of

several hundred gigabytes, and often several terabytes of data. These enterprises are

challenged by the support and maintenance requirements of very large databases

(VLDB), and must devise methods to meet those challenges. This chapter contains an

overview of VLDB topics, with emphasis on partitioning as a key component of the

VLDB strategy.

This chapter contains the following sections:

■ Introduction to Partitioning

■ VLDB and Partitioning

■ Partitioning As the Foundation for Information Lifecycle Management

■ Partitioning for Every Database

Introduction to Partitioning

Partitioning addresses key issues in supporting very large tables and indexes by

decomposing them into smaller and more manageable pieces called partitions, which

are entirely transparent to an application. SQL queries and Data Manipulation

Language (DML) statements do not need to be modified to access partitioned tables.

However, after partitions are defined, Data Definition Language (DDL) statements can

access and manipulate individual partitions rather than entire tables or indexes. This is

how partitioning can simplify the manageability of large database objects.

Each partition of a table or index must have the same logical attributes, such as

column names, data types, and constraints, but each partition can have separate

physical attributes, such as compression enabled or disabled, physical storage settings,

and tablespaces.

Partitioning is useful for many different types of applications, particularly applications

that manage large volumes of data. OLTP systems often benefit from improvements in

manageability and availability, while data warehousing systems benefit from

performance and manageability.

Partitioning offers these advantages:

■ It enables data management operations such as data loads, index creation and

rebuilding, and backup and recovery at the partition level, rather than on the

entire table. This results in significantly reduced times for these operations.

Note: Partitioning functionality is available only if you purchase the

Partitioning option.

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,

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