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Figure 8-1. Slow script warning in Firefox As powerful as Web Workers are, there are also certain things they cannot do. For example, when a script is executing inside a Web Worker it cannot access the web page s window object (window.document), which means that Web Workers don t have direct access to the web page and the DOM API. Although Web Workers cannot block the browser UI, they can still consume CPU cycles and make the system less responsive. Let s say you want to create a web application that has to perform some background number crunching, but you do not want those tasks to interfere with the interactivity of the web page itself. Using Web Workers, you can spawn a Web Worker to perform the tasks and add an event listener to listen to messages from the Web Worker as they are sent. Another use case for Web Workers could be an application that listens for broadcast news messages from a back-end server, posting messages to the main web page as they are received from the back-end server. This Web Worker might use Web Sockets or Server-Sent Events to talk to the back-end server. In this chapter, we ll explore what you can do with Web Workers. First, we ll discuss how Web Workers work and the level of browser support available at the time of this writing. Then, we ll discuss how you can use the APIs to create new workers and how to communicate between a worker and the context that spawned it. Finally, we ll show you how you can build an application with Web Workers.

Greenplum, http://www.greenplum.com/, provides petabyte-scale, scalable database analytics. It provides a download link to allow you to try its software. It also provides an in-database MapReduce that interoperates with SQL.

Anything. The database or driver does not support transactions. Dirty, nonrepeatable, and phantom reads. Nonrepeatable reads and phantom reads. Phantom reads. The rule must be obeyed absolutely.

The CloudBase project, http://cloudbase.sourceforge.net/, provides a high-performance, data warehousing system built on top of MapReduce, with an ANSI SQL API. The project is developed by business.com to speed terabyte scale web log analysis. The current release version is 1.3. CloudBase is released under GLP 2.0. The web site provides detailed instructions for running CloudBase instances on Amazon s elastic compute (EC2) service.

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Sometimes you need additional compute resources for only a short time, you want to experiment with particular configurations, or you just don t want to manage your own hardware. Cloud service vendors provide the ability to spin up clusters of almost arbitrary size and capacities for short to long durations. The best-known cloud server provider at the time of writing is Amazon, and there is direct support for running Hadoop in its cloud.

Browser support for Web Workers is at varying stages and will continue to evolve. As shown in Table 8-1, Web Workers is already supported in many browsers at the time of this writing. Table 8-1. Opera Supported in version 10.6 and greater

Amazon, http://aws.amazon.com, provides a large set of cloud computing services: Its simple storage S3 service, http://aws.amazon.com/s3/, provides large persistent data storage. Its EC2 service, http://aws.amazon.com/ec2/, provides on-demand computing clusters built of virtual computers with a variety of capacities and operating systems. The SimpleDB, http://aws.amazon.com/simpledb/, provides a production-grade, distributed, column-oriented database. The Elastic Block Store (EBS), http://aws.amazon.com/ebs/, provides persistent storage within EC2 and is ideal for longer-running HDFS clusters. The Elastic MapReduce service provides on-demand Hadoop clusters, using S3 as the job input and output file system.

A dirty read may see the in-progress changes of an uncommitted transaction. As in our example, it could see the wrong zip code for an address. A nonrepeatable read sees different data for the same query. For example, it might determine a specific user s zip code at the beginning of the transaction and again at the end, and get a different answer both times without making any updates. A phantom read sees different numbers of rows for the same query. For example, it might see 100 users in the database at the beginning of the query and 105 at the end without making any updates. Hibernate treats the isolation as a global setting you apply the configuration option hibernate.connection.isolation in the usual manner, setting it to one of the values permitted in Table 9-2. This is not always ideal. You will sometimes want to treat one particular transaction at a high (usually serializable) level of isolation, while permitting lower degrees of isolation for others. To do so, you will need to obtain the JDBC connection directly, alter the isolation level, begin the transaction, roll back or clean up the transaction as appropriate, and reset the isolation level back to its original value before releasing the connection for general usage. The createUser() method (discussed in the Deadlock section later in this chapter) demonstrates the additional complexity that the connection-specific transaction isolation involves.

The one significant downside to Hadoop in the Amazon cloud is that there is no real data locality something Hadoop works hard to achieve.

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