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Although we have referred to the Hibernate types in passing, we have not discussed the terminology in any depth. In order to express the behavior of the mapping file elements, we need to make these fine distinctions explicit. Hibernate types fall into three broad categories: entities, components, and values.

Although the canvas element is great and very useful, you should not use the canvas element when another element will suffice. For example, it would not be a good idea to dynamically draw all the different headings for an HTML document on a canvas instead of simply using heading styles (H1, H2, and so on) that are meant for that purpose.

Once you have configured your cluster and started running jobs, life will happen, and you may need to recover from a failure. Here, we will look at how HDFS protects from many individual failures and how to recover from other failures. HDFS has two types of data, with different reliability requirements and recovery patterns. The NameNode stores the file system metadata and provides direct replication of the data and run-behind remote copies of the data. The DataNodes provide redundant storage by replicating data blocks to multiple DataNodes.

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The default Hadoop installation provides no protection from catastrophic NameNode server failures. The only default protection is that provided by a RAID 1 or RAID 5 storage device for the file system image and edit logs. You can avoid data loss and unrecoverable machine failures by running the secondary NameNode on an alternate machine. Storing the file system image and file system edit logs on multiple physical devices, or even multiple physical machines, also provides protection. When a NameNode server fails, best practices require that all the JobTracker and TaskTrackers be restarted after the NameNode is restarted. All incomplete HDFS blocks will be lost, but there should be no file or data loss for existing files or for completed blocks in actively written files.

In case your web page is accessed by a browser that does not support the canvas element or a subset of the HTML5 Canvas API features, it is a good idea to provide an alternate source (see Table 2-1 in the "Browser Support for HTML5 Canvas" section for more on browser support). For example, you can provide an alternate image or just some text that explains what the user could be enjoying if they actually used a modern browser. Listing 2-2 shows how alternate text can be specified inside a canvas element. Browsers that do not support the canvas element will simply render this fallback content. Listing 2-2. Use of fallback text inside a canvas element <canvas> Update your browser to enjoy canvas! </canvas> Instead of the previous text shown, you can also point to an image that can be displayed in case the browser does not support the canvas element.

Generally, an entity is a POJO class that has been mapped into the database using the <class> or <subclass> elements. An entity can also be a dynamic map (actually a Map of Maps). These are mapped against the database in the same way as a POJO, but with the default entity mode of the SessionFactory set to dynamic-map. The advantage of POJOs over the dynamic-map approach is that compile-time type safety is retained. Conversely, dynamic-maps are a quick way to get up and running when building prototypes. We recommend that you use the standard entity mode unless you need to sacrifice accuracy for timeliness. We have decided to omit discussion of some features pertaining to the XML mapping metadata. This permits an alternative representation of data as the contents of an XML document, instead of a POJO or Map. This is a somewhat experimental feature in Hibernate 3 and, at the time of this writing, we do not recommend that you use it. For more information, consult the Hibernate website (http://www.hibernate.org).

note Hadoop 0.19.0 has initial support for a sync operator that allows the flushing of HDFS blocks that

are not a full dfs.block.size value, but support for this is early and known to be unreliable. This feature has been disabled in Hadoop 0.19.1, but it may return in Hadoop 0.20.0.

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