Note: Since we selected the main class when we exported wordcount.jar, there is no need to mention the main class in the command.Ĭommand: hadoop jar wordcount.jar / input / output :~$ hadoop jar wordcount.jar /input /outputġ6/11/27 22:52:20 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:ġ6/11/27 22:52:22 WARN mapreduce.JobResourceUploader: Hadoop command-line option Now run the wordcount.jar file with the following command. We have our input file on HDFS for the Wordcount program. If you get a warning like the one below, just click OK.Ĭheck if your Hadoop cluster is active or not. Now click on Browse and select the main class and finally click on Finish to create the JAR file. Select the Wordcount project and provide the path and name for the JAR file, I’ll keep it wordcount.jar, click Next twice. In the Java option, select the Jar file and click Next. Select the file option in Eclipse ide and click Export. In order to run this MapReduce program on a Hadoop cluster, we export the project as a JAR file. My MapReduce program is in my Eclipse IDE. #BEST PYTHON IDE UBUNTU 16.04 HOW TO#In this blog, I’ll show you how to export a Mapreduce program from the Eclipse IDE to a JAR file and run it on a Hadoop cluster. And mostly Eclipse IDE is used by developers for programming. Run the MapReduce programĪ MapReduce program is written in Java. ![]() Reduce: The values of similar keys are added. ![]() ![]() Shuffle: Common key-value pairs are grouped. Mapping: It forms a key-value pair, where Word is the key and 1 is the value assigned to each key. Split: It splits each line in the input file into words.
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