《云端代码》：Google.AppEngine实战指南

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"《云端代码：利用Google.AppEngine编程》是一本专为想要了解云计算以及如何运用Google App Engine进行开发的读者精心撰写的指南。作者以其通俗易懂、少炒作、多事实的风格，深入浅出地讲解了这项技术，使读者能够轻松上手。该书特别之处在于不仅提供了Python示例，还涵盖了Java，这使得不同背景的开发者都能找到适合自己的学习路径。书中强调的核心理念是，通过Google App Engine平台，开发者可以专注于构建高灵活性和可扩展性的网络应用，而无需过多关注底层部署细节，如服务器硬件选择、操作系统安装及长期支持等问题。这些通常被视为开发过程中繁琐且非核心的复杂性，但在云端代码的世界里，开发者可以将精力集中在真正关键的业务逻辑上。评论者Fred Daoud，作为《Stripes》和《Java Web Development Is Fun Again》以及《Getting Started with Apache Click》的作者，对本书赞不绝口，他认为这本书为读者提供了一个实用的学习工具，帮助他们避免过去开发过程中经常遇到的困扰。另一名高级分析师Lyle Johnson也给予了高度评价，他提到书中的代码简洁，注释详尽，解释清晰，这些都是优质编程教材的重要特征。《云端代码：利用Google.AppEngine编程》是一本理想的入门书籍，无论你是初学者还是经验丰富的开发者，都能从中受益匪浅，提升你的云计算技能，并学会如何利用Google App Engine这个强大的工具来简化并加速你的应用程序开发过程。通过阅读这本书，开发者可以更好地理解云计算的力量，掌握在云环境中高效开发的策略，从而实现更高层次的技术创新和业务增长。"

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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