Oracle Coherence入门指南：实现应用服务器的高级架构

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Oracle Coherence是一款高级应用架构，专为构建可扩展、高性能和分布式计算环境而设计。该指南名为"Oracle Coherence Getting Started with Oracle Coherence Release 3.4"，发布于2008年11月，由Thomas Pfaeffle为主要作者，其他多位专家如Noah Arliss、Jason Howes等也做出了贡献。此文档涵盖了Oracle Coherence的核心概念和技术，旨在帮助开发者理解和实现在Oracle数据库之上实现高效的数据网格（Data Grid）和数据 Fabric。 Oracle Coherence是一个基于内存的数据管理和处理平台，它提供了一种强大的工具来存储、检索和管理大量关键业务数据。数据网格是Coherence架构中的关键组件，它允许数据在多个节点之间透明地复制和同步，从而实现高可用性和负载均衡。数据网格支持大规模并发访问，确保即使在分布式系统中也能保持一致性和性能。数据 Fabric概念进一步扩展了这个框架，它不仅仅关注数据，还包括消息传递、服务发现和协调。通过Data Fabric，应用程序能够无缝集成多种服务，包括数据库、消息队列和文件系统，形成一个统一的、低延迟的数据和消息处理基础设施。在使用Oracle Coherence时，开发者需要遵循严格的版权协议，确保软件的合法使用。未经许可，禁止进行修改、复制或分发，除非法律允许或者在许可证协议中有明确的规定。此外，文档还强调了软件的反逆工程限制，除非为了兼容性目的，否则解构或编译软件的行为被严格禁止。此指南详细介绍了如何设置和配置Coherence集群，实现分布式缓存、事务支持、安全性和性能优化。此外，还包括了示例代码和实战案例，以便读者在实际项目中快速上手并掌握Coherence的使用。学习者可以通过本资源深入了解Oracle Coherence如何在企业级应用中扮演核心角色，提升系统的可靠性和响应速度。

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Related Documents

For more information, see the following documents in the Oracle Coherence Release

3.4 documentation set:

■ User's Guide for Oracle Coherence

■ Developer's Guide for Oracle Coherence

Conventions

The following text conventions are used in this document:

Convention Meaning

boldface Boldface type indicates graphical user interface elements associated

with an action, or terms defined in text or the glossary.

italic Italic type indicates book titles, emphasis, or placeholder variables for

which you supply particular values.

monospace Monospace type indicates commands within a paragraph, URLs, code

in examples, text that appears on the screen, or text that you enter.

Defining a Data Grid 1-1

1Defining a Data Grid

The Oracle Coherence In-Memory Data Grid is a data management system for

application objects that are shared across multiple servers, require low response time,

very high throughput, predictable scalability, continuous availability and information

reliability. For clarity, each of these terms and claims is explained:

As a result of these capabilities, Oracle Coherence is ideally suited for use in

computationally intensive, stateful middle-tier applications. Coherence is targeted to

run in the application tier, and is often run in-process with the application itself, for

example in an Application Server Cluster.

The combination of these four capabilities results is the information within the Data

Grid being reliable for use by transactional applications.

■ A Data Grid is a system composed of multiple servers that work together to

manage information and related operations - such as computations - in a

distributed environment.

■ An In-Memory Data Grid is a Data Grid that stores the information in memory to

achieve very high performance, and uses redundancy—by keeping copies of that

information synchronized across multiple servers—to ensure the resiliency of the

system and the availability of the data in the event of server failure.

■ The application objects are the actual components of the application that contain

the information shared across multiple servers. These objects must survive a

possible server failure in order for the application to be continuously available.

These objects are typically built in an object-oriented language such as Java (for

example, POJOs), C++, C#, VB.NET or Ruby. Unlike a relational schema, the

application objects are often hierarchical and may contain information that is

pulled from any database.

■ The application objects must be shared across multiple servers because a

middleware application (such as eBay and Amazon.com) is horizontally scaled by

adding servers - each server running an instance of the application. Since the

application instance running on one server may read and write some of the same

information as an application instance on another server, the information must be

shared. The alternative is to always access that information from a shared

resource, such as a database, but this will lower performance by requiring both

remote coordinated access and Object/Relational Mapping (ORM), and decrease

scalability by making that shared resource a bottleneck.

■ Because an application object is not relational, to retrieve it from a relational

database the information must be mapped from a relational query into the object.

This is known as Object/Relational Mapping (ORM). Examples of ORM include

Java EJB 3.0, JPA, and ADO.NET. The same ORM technology allows the object to

be stored in a relational database by deconstructing the object (or changes to the

1-2 Oracle Coherence Getting Started with Oracle Coherence

object) into a series of SQL inserts, updates and deletes. Since a single object may

be composed of information from many tables, the cost of accessing objects from a

database using Object/Relational Mapping can be significant, both in terms of the

load on the database and the latency of the data access.

■ An In-Memory Data Grid achieves low response times for data access by keeping

the information in-memory and in the application object form, and by sharing that

information across multiple servers. In other words, applications may be able to

access the information that they require without any network communication and

without any data transformation step such as ORM. In cases where network

communication is required, the Oracle Coherence avoids introducing a Single

Point of Bottleneck (SPOB) by partitioning—spreading out—information across

the grid, with each server being responsible for managing its own fair share of the

total set of information.

■ High throughput of information access and change is achieved through four

different aspects of the In-Memory Data Grid:

■ Oracle Coherence employs a sophisticated clustering protocol that can achieve

wire speed throughput of information on each server. This allows the

aggregate flow of information to increase linearly with the number of servers.

■ By partitioning the information, as servers are added each one assumes

responsibility for its fair share of the total set of information, thus

load-balancing the data management responsibilities into smaller and smaller

portions.

■ By combining the wire speed throughput and the partitioning with automatic

knowledge of the location of information within the Data Grid, Oracle

Coherence routes all read and write requests directly to the servers that

manage the targeted information, resulting in true linear scalability of both

read and write operations; in other words, high throughput of information

access and change.

■ For queries, transactions and calculations, particularly those that operate

against large sets of data, Oracle Coherence can route those operations to the

servers that manage the target data and execute them in parallel.

■ By using dynamic partitioning to eliminate bottlenecks and achieving predictably

low latency regardless of the number of servers in the Data Grid, Oracle

Coherence provides predictable scalability of applications. While certain

applications can use Coherence to achieve linear scalability, that is largely

determined by the nature of the application, and thus varies from application to

application. More important is the ability of a customer to examine the nature of

their application and to be able to predict how many servers will be required to

achieve a certain level of scale, such as supporting a specified number of

concurrent users on a system or completing a complex financial calculation within

a certain number of minutes. One way that Coherence accomplishes this is by

executing large-scale operations, such as queries, transactions and calculations, in

parallel using all of the servers in the Data Grid.

■ One of the ways that Coherence can eliminate bottlenecks is to queue up

transactions that have occurred in memory and asynchronously write the result to

a system of record, such as an Oracle database. This is particularly appropriate in

systems that have extremely high rates of change due to the processing of many

small transactions, particularly when only the result must be made persistent.

Coherence both coalesces multiple changes to a single application object and

batches multiple modified application objects into a single database transaction,

meaning that a hundred different changes to each of a hundred different

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