Google AppEngine云编程实战：Python与Java示例

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"Code in the Cloud: A Guide to Cloud Programming with Google AppEngine" "云计算 Code in the Cloud" 是一本专注于介绍如何使用 Google AppEngine 平台进行云编程的英文书籍。这本书面向那些想要学习云计算技术和如何利用 Google AppEngine 开发应用的读者。作者通过 Python 和 Java 两种语言的示例，深入浅出地解释了如何在云端编写高效且可扩展的 Web 应用程序，避免了传统开发中涉及到的底层部署细节。 Google AppEngine 是谷歌提供的一种平台即服务（PaaS）产品，它允许开发者无需关注服务器硬件、操作系统安装和基础设施管理等琐碎事务，即可构建和运行应用程序。通过 AppEngine，开发者可以专注于编写业务逻辑，而平台会自动处理扩展性和可靠性问题。书中提到的核心概念包括： 1. **云计算基础**：讲解了云计算的基本原理，包括资源共享、弹性伸缩和按需付费模型，帮助读者理解云环境的优势。 2. **Google AppEngine 服务**：详述了 AppEngine 提供的各种服务，如数据存储（Datastore）、任务队列（Task Queues）、电子邮件服务、URL fetch 等，以及如何利用这些服务构建应用程序。 3. **Python 和 Java 开发**：书中的例子覆盖了两种主要的编程语言，Python 和 Java，使得具有这两种语言背景的开发者都能快速上手。 4. **应用架构设计**：探讨了如何设计能够在云环境中高效运行的应用架构，强调高灵活性和可扩展性。 5. **减少事故性复杂度**：书中讨论了如何通过 AppEngine 将非本质的复杂性（如基础设施管理）转移出去，让开发者能够集中精力于核心业务逻辑，降低事故性复杂度。 6. **实例分析**：通过具体的代码示例和清晰的解释，帮助读者理解如何在实际项目中应用所学知识。 7. **性能和扩展性**：介绍了如何在 AppEngine 上优化应用性能，以及如何设计可随着需求增长而自动扩展的应用。 8. **最佳实践**：提供了关于使用 AppEngine 进行开发的最佳实践，帮助读者避免常见错误，提高开发效率。 "Code in the Cloud" 是一本全面介绍 Google AppEngine 的实用指南，不仅适合初学者入门，也为有经验的开发者提供了深入理解和实践云开发的宝贵资源。通过阅读本书，读者将能够掌握在云端构建高效、可扩展的 Web 应用程序所需的关键技能。

CLOUDCOMPUTINGPROGRAMMINGSYSTEMS 16

ability to listen to snippets, read reviews, comment on things that

they’ve listened to, get suggestions for new things based on what

they like, and ultimately select things to purchase. That’s clearly

a service, and it makes sense to keep it in the cloud.

Large computations.

Is your application intended to perform a massive computation,

which you could never afford to do if you needed to buy your own

computers to run it? If so, the cloud allows you to purchase time

on a server farm of computers in an affordable way and run your

application. This is gr eat for people like genetics researchers, who

need to run massive computations but don’t have the money or

other resources to set up a dedicated data center for their com-

putations. Instead, they can purchase time on commercial data

centers, which they share with many other users.

1.2 Cloud Computing Programming Systems

There are multiple ways of programming the cloud. Before we start

actually writing programs, we’ll take a quick look at a few examples to

give you a sense of what sorts of options are available.

Amazon EC2

Amazon provides a variety of cloud-based services. Their main pro-

gramming tool is called EC2, Elastic Computing Cloud.

EC2 is really a family of related services. Compared to App Engine,

which provides a single, narrowly focused suite of APIs, EC2 is com-

pletely agnostic about programming APIs. It provides hundreds of dif-

ferent environments: you can run your application in EC2 using Linux,

Solaris, or W i n d o w s Server; you can store data using DB2, Informix,

MySQL, SQL Server, or Oracle; you can implement your code in Perl,

Python, Ruby, Java, C++, or C#; you can run it using IBM’s W e b S p h e r e

or sMash, Apache JBoss, Oracle W e b L o g i c , or Microsoft IIS. Depend-

ing on which combination you prefer and how much of each kind of

resource (storage, CPU, network bandwidth) you plan to use, the costs

vary from $0.10 per CPU hour and $0.10 per gigabyte of bandwidth to

around $0.74 per CPU hour for high-end instances.

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CLOUDCOMPUTINGPROGRAMMINGSYSTEMS 17

Amazon S3

Amazon provides another extremely interesting cloud service, which is

very different from most other cloud offerings. S3, Simple Storage Ser-

vice, is a pure storage system. It doesn’t provide the ability to run pro-

grams; it doesn’t provide any ﬁlesystem; it doesn’t provide any index-

ing. It’s pure block storage: you can allocate a chunk of storage that

has a unique identiﬁer, and then you can read and write bytes from

that chunk using its identiﬁer.

A variety of systems have been created that use S3 for storage: web-

based ﬁlesystems, native OS ﬁlesystems, database systems, and table

storage systems. It’s a wonderful example of the cloud’s resource-based

paradigm: the computation involved in storage is completely separated

from the actual data storage itself. When you need storage, you buy a

bunch of bytes of storage space from S3. When you need computation,

you buy EC2 resources.

S3 is a really fascinating system. It’s very focused: it does exactly one

thing and does it in an incredibly narrow way. But in an important

sense, that’s exactly what the cloud is about. S3 is a perfectly focused

service; it stores bytes for you.

S3 charges are based on two criteria: how much data you store and how

much network bandwidth you use storing and retrieving your data.

Amazon currently charges $0.15 per gigabyte per month and about

$0.10 per gigabyte uploaded and $0.17 per gigabyte downloaded.

On a related note, Google provides a very similar cloud service, called

Google Developer Storage, which replicates the basic features of S3 in

the Google cloud.

IBM Computing on Demand

IBM provides a cloud service platform based on IBM’s suite of web ser-

vice development that uses W e b S p h e r e , DB2, and Lotus collaboration

tools. The environment is the same as the IBM-based environment on

EC2, but it runs in IBM’s data centers instead of Amazon’s.

Microsoft Azure

Microsoft has developed and deployed a cloud platform called Azure.

Azure is a W i n d o w s - b a s e d platform that uses a combination of stan-

dard web services technologies (such as SOAP, REST, Servlets, and

ASPs) and Microsoft’s proprietary APIs, like Silverlight. As a result,

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CLOUDCOMPUTINGPROGRAMMINGSYSTEMS 18

you get the ability to create extremely powerful applications that look

very much like standard desktop applications. But the downside is it’s

closely tied to the W i n d o w s platform, so the application clients run

primarily on W i n d o w s . While there are Silverlight implementations for

other platforms, the applications tend to only be reliable on W i n d o w s

platforms and only fully functional in Internet Explorer.

So that’s the cloud. Now that we know what it is, we’re going to start

learning about how to build applications in the cloud. Google has put

together a really terriﬁc platform, called App Engine, for you to build

and run your own cloud applications.

In the rest of the book, we’re going to look in detail at the key pieces

of building cloud-based web applications. W e ’ l l start of f working in

Python. Python’s great for learning the basics: it lets you see what’s

going on, and it makes it easy to quickly try different approaches and

see what happens.

W e ’ l l go through the full stack of techniques that you need for build-

ing a Google App Engine application in Python, starting with the basic

building blocks: HTTP, services, and handlers. Then we’ll look at how

you work with persistent data in the cloud using the App Engine data-

store service. And then, we’ll look at how to build user interfaces for

your applications using HTTP, CSS, and AJAX.

From there, we’ll leave Python for a while and move into Java. In my

opinion, Java can be a lot more convenient for building complex appli-

cations. Not that Python can’t or shouldn’t be used for advanced App

Engine development, but my preference is to use Java. And App Engine

provides access to an absolutely brilliant framework called GWT, which

abstracts away most of the boilerplate plumbing of a web-based cloud

application, allowing you to focus on the interesting parts. W e ’ l l spend

some time learning about how to build beautiful user interfaces using

GWT and how to do AJAX-style communication using GWT’s remote

procedure call service.

Finally, we’ll spend some time looking at the most complicated aspects

of real web development. W e ’ l l look at the details of how you can do

sophisticated things using the App Engine datastore service, how to

implement server-side processing and computation using things like

cron, and how to integrate security and authentication into your App

Engine application.

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