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A JSP has all its code in a single, monolithic structure Although business logic may be delegated into Java objects, it is still mixed into the application and presentation logic Unlike unit testing methods in a Java class, it is not possible to test and run JSP fragments independently JSPs can quickly become overloaded with code, sacrificing manageability and comprehensibility

Starfish isn t the only Ruby implementation of MapReduce available It does happen to be the easiest to get up and running, however, which is why it is used to demonstrate MapReduce in this book

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as we do for vectors It is worth noting that because the compare function operates on Student_info objects, we can use the same compare function to sort a list of Student_info records that we used to sort a vector of them

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In producing output, simple scripts mix the text, HTML, or XML encoding of the result with the dynamic data This couples the page s markup, its look and feel, with the other layers Changing the Web site s look or adapting the application to multiple output devices becomes extremely difficult The latter is becoming increasingly important as the Web expands to include mobile devices such as Internet-connected mobile phones and other embedded devices JSPs help address this last issue by letting Web designers create and maintain the look and feel of the pages, letting Java programmers provide presentation logic in annotations This is generally considered the most appropriate use for server pages

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The code that extracts records for failing students is a good example of the effect of data structure choices on performance The code accesses elements sequentially, which generally implies that a vector is the best choice On the other hand, we also delete elements from the interior of the container, thus favoring lists As with any performance-related question, the data structure that is "best" depends on whether performance even matters Performance is a tricky subject that is generally outside the scope of this book, but it is worth noting that the choice of data structure can have a profound effect on a program's performance For small inputs, lists are slower than vectors For large inputs, a program that uses vectors in an inappropriate way can run much more slowly than it would if it were to use lists It can be surprising how quickly performance degrades as the input grows To test our programs' performance, we used three files of student records The first file had 735 records The second file was ten times as big, and the third, ten times bigger than that, or 73,500 records The following table records the time, in seconds, that it took to execute the programs on each file size:

A layered architecture is a system containing multiple, strongly separated tiers (layers) with minimal dependencies and interactions between the layers Such a system has good separation of concerns, meaning that you can deal with different areas of the application code in isolation, with minimal or no side effects to different layers By separating the system s different pieces, you make the software adaptable so that you can easily change and enhance it as requirements change The layers include input and output logic for presentation, application logic, business logic, and persistence These layers can be related back to the basic three-tier structure we described earlier; the input layer is a part of the presentation layer

SkyNet, http://skynetrubyforgeorg/, is an implementation of MapReduce written by Adam Pisoni It offers more features, customization, and tighter integration with Rails than Starfish does However, it does this at the expense of a difficult setup and difficult-to-understand workflow I have heard good things about it, but I can t speak to it directly because I had a tremendously difficult time getting it up and running MRToolkit, http://codegooglecom/p/mrtoolkit/, appeared on the scene shortly after I had completed the first draft of this book, so unfortunately I wasn t able to properly write about it The project came out, of all places, The New York Times Company The documentation suggests a fairly simple and well-thought-out API for creating MapReduce jobs MRToolkit sits atop the Apache Hadoop project, http://hadoopapacheorg/, which it uses to do most of the heavy lifting Although installing and running Hadoop can be a little cumbersome, it is a widely used and battle-tested platform, which means that MRToolkit is definitely a framework worth checking out

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