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The intermediate map task outputs are a set of sequence files, one per reduce task. As these files must be transferred across the network, a low-overhead compression type, such as gzip or LZO, can provide a substantial reduction in network traffic for little CPU cost. The blog entry at http://blog.oskarsson.nu/2009/03/hadoop-feat-lzo-save-disk-space-and.html has some interesting information about compression CPU and size reductions for different Hadoop codecs. Table 5-4 summarizes the compression speed results. For pretty decent compression LzoCodec provides high throughput.

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<h1>Cross-Origin Portal</h1> <p><b>Origin</b>: http://portal.example.com:9999</p> Status <input type="text" id="statusText" value="Online"> <button id="sendButton">Change Status</button> <p> This uses postMessage to send a status update to the widget iframe contained in the portal page. </p> <iframe id="widget" src="http://chat.example.net:9999/postMessageWidget.html"></iframe> <p> <button id="stopButton">Stop Blinking Title</button> </p> Listing 5-4 shows the code for the portal page postMessageWidget.html. Listing 5-4. Contents of postMessageWidget.html <!DOCTYPE html> <title>widget</title> <link rel="stylesheet" href="styles.css"> <script> var targetOrigin = "http://portal.example.com:9999"; function messageHandler(e) { if (e.origin === "http://portal.example.com:9999") { document.getElementById("status").textContent = e.data; } else { // ignore messages from other origins } } function sendString(s) { window.top.postMessage(s, targetOrigin); } function loadDemo() { document.getElementById("actionButton").addEventListener("click", function() { var messageText = document.getElementById("messageText").value; sendString(messageText); }, true); } window.addEventListener("load", loadDemo, true); window.addEventListener("message", messageHandler, true); </script> <h1>Widget iframe</h1> <p><b>Origin</b>: http://chat.example.net:9999</p> <p>Status set to: <strong id="status"></strong> by containing portal.<p>

BLOCK set for compression, to determine which combination gave the overall performance for the job. At

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Map output block-level compression may be specified by the job or in the site configuration. If compressed, map output, destined for a reduce task, is always BLOCK compressed. Listing 5-18 provides an XML block suitable for inclusion in the conf/hadoop-site.xml file to make LZO compression the default for the map task outputs. Listing 5-18. A hadoop-site.xml Specification for Map Output Level Compression with LZO <property> <name>mapred.compress.map.output</name> <value>true</value> <description>Should the outputs of the maps be compressed before being sent across the network. Uses SequenceFile compression. </description> </property> <property> <name>mapred.map.output.compression.codec</name> <value>org.apache.hadoop.io.compress.LzoCodec</value> <description>If the map outputs are compressed, how should they be compressed Use Lzo fast even though not as good compression. </description> </property> Listing 5-19 demonstrates configuring a cluster to always use compression for final output files, and if the final output file is a sequence file, to use BLOCK compression. Listing 5-19. A hadoop-site.xml Specification for Final Output Files to be Compressed with LZO, and If Sequence Files, BLOCK-Compressed <property> <name>mapred.output.compress</name> <value>true</value> <description>Should the job outputs be compressed </description> </property>

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How to add Barcode to Local Reports ( RDLC ) before report ...
In the following guide we'll create a local report ( RDLC file) which features barcoding capabilities by using Bytescout Barcode SDK. Follow these steps:.

Specifies the optimistic locking strategy to use. Specifies whether an outer-join should be used. Allows a custom ClassPersister object to be used when persisting this class. The database schema against which queries should apply. A subselect of the contents of the underlying table. A class can only use a subselect if it is immutable and read-only (because the SQL defined here cannot be reversed). Generally, the use of a database view is preferable.

<div> <input type="text" id="messageText" value="Widget notification."> <button id="actionButton">Send Notification</button> </div> <p> This will ask the portal to notify the user. The portal does this by flashing the title. If the message comes from an origin other than http://chat.example.net:9999, the portal page will ignore it. </p>

<property> <name>mapred.output.compression.type</name> <value>BLOCK</value> <description>The type of compression to use for final output sequence files. May be BLOCK, RECORD or None. </description> </property> <property> <name>mapred.output.compression.codec</name> <value>org.apache.hadoop.io.compress.LzoCodec</value> <description>If the job outputs are compressed, how should they be compressed Use Lzo fast even though not as good compression. </description> </property> Listings 5-20 and 5-21 demonstrate specifying the compression codec and type via settings on the JobConf object. Listing 5-20. Setting Intermediate Map Output Compression via the JobConf conf. setCompressMapOutput(true); conf. setMapOutputCompressorClass(LzoCodec.class); Listing 5-21. Setting Final Output Compression via the JobConf FileOutputFormat.setOutputCompress (conf, true); FileOutputFormat.setOutputCompressorClass(LzoCodec.class); SequenceFileOutputFormat.setOutputCompressionType(conf,CompressionType.BLOCK);

The Hadoop framework knows how to unpack JAR, zip, and tar files, but this is only automatically done for archives passed via the DistributedCache object The class org.apache.hadoop. fs.FileUtil provides two static methods that may be used to unpack these files: unTar() for tar files and unzip() for zip files. The archives may be unpacked only onto the native file system, not into HDFS.

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