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To receive messages, you just have to add an event handler to your page. When a message arrives, you can check its origin and decide whether or not to do something with the message. Listing 5-1 shows an event listener that passes the message to a messageHandler function. Listing 5-1. An event listener for message events window.addEventListener( message , messageHandler, true); function messageHandler(e) { switch(e.origin) { case friend.example.com : // process message processMessage(e.data); break; default: // message origin not recognized // ignoring message } } A message event is a DOM event with data and origin properties. The data property is the actual message that the sender passed along and the origin property is the sender s origin. Using the origin property, it is easy for the receiving side to ignore messages from untrusted sources; the origin can simply be checked against a list of allowed origins. As shown in Figure 5-1, the postMessage API provides a way to communicate between a chat widget iframe hosted at http://chat.example.net and an HTML page that contains the chat widget iframe hosted at http://portal.example.com (two different origins).

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Specifies how the class member should be accessed: field for direct field access, or attribute for access via the get and set methods. When in lazy-load mode, this specifies the number of occurrences to acquire in each access. Determines how changes to the parent entity will affect the linked relation. The database catalog against which queries should apply. SQL to create a multirow check constraint for schema generation.

There are several basic strategies for running a MapReduce job under the debugger. Here, we ll start with simplest and move to the more complex methods.

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RDLC/ rdlc UPC-A Barcode Generation Control/Library
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When running MapReduce jobs under a debugger, it is important to drastically increase the value of the configuration key mapred.task.timeout. The default value is 600000, or 10 minutes. When you are single-stepping through a map or reduce task, it is common for more than 10 minutes to pass. If the value has not been lengthened, the task you are debugging will be killed. You can set the task timeout length to a large long value via the bin/hadoop jar command line, using -Dmapred.task.timeout, after the main class specification, if the job uses the GenericOptionsParser that the ToolRunner class provides. For example, to set a 2-hour timeout, uses the value 7200000, as follows: bin/hadoop jar job.jar main.class -Dmapred.task.timeout=7200000 other arguments This value is parsed as a long, so values up to 9223372036854775807 will work on 32-bit JVMs.

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In this example, the chat widget is contained in an iframe, so it does not have direct access to the parent window. When the chat widget receives a chat message, it can use postMessage to send a message to the main page so that the page can alert the user of the chat widget that a new message has been received. Similarly, the page can send messages about the user s status to the chat widget. Both the page and the widget can listen for messages from each other by adding the respective origins to a white list of allowed origins. Before the introduction of postMessage, communicating between iframes could sometimes be accomplished by direct scripting. A script running in one page would attempt to manipulate another document. This might not be allowed due to security restrictions. Instead of direct programmatic access, postMessage provides asynchronous message passing between JavaScript contexts. As shown in Figure 5-2, without postMessage, cross origin communication would result in security errors, enforced by browsers to prevent cross-site scripting attacks.

The normal process of job submission involves the JobClient class storing all of the relevant information about the job in HDFS, and then making an RPC call to the JobTracker to submit the job for execution. The JobClient determines the address of the JobTracker through the configuration value of the configuration key mapred.job.tracker. This configuration key may have the value of local, in which case the entire MapReduce job will be run in the JVM that is submitting the job. This is ideal for debugging small-scale problems. There are some restrictions to this technique. The cause of most of the restrictions is that the map and reduce tasks do not run in their own JVMs. There is no way to change the JVM working directory, classpath, or other command-line configured options. A significant result of this is that the DistributedCache behavior is very different. If your job relies on the DistributedCache, this method will not be a good debugging choice. The lifetime of your

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