configuration file are:
Run the ": WQ" command to save and exit.
Through the above configuration, we have completed the simplest pseudo-distributed configuration.
Next, format the hadoop namenode:
Enter "Y" to complete the formatting process:
Start hadoop!
Start hadoop as follows:
Use the JPS command that comes with Java to query all daemon processes:
Star
Copy an objectThe content of the copied "input" folder is as follows:The content of the "conf" file under the hadoop installation directory is the same.Now, run the wordcount program in the pseudo-distributed mode we just built:After the operation is complete, let's check the output result:Some statistical results are as follows:At this time, we will go to the hadoop Web console and find that we have submit
Copy an object The content of the copied "input" folder is as follows: The content of the "conf" file under the hadoop installation directory is the same. Now, run the wordcount program in the pseudo-distributed mode we just built: After the operation is complete, let's check the output result: Some statistical results are as follows: At this time, we will go to the hadoop Web
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This course focuses onSpark, the hottest, most popular and promising technology in the big Data world today. In this course, from shallow to deep, based on a large number of case studies, in-depth analysis and explanation of Spark, and will contain completely from the enterprise real complex business needs to extract the actual case. The course will cover Scala programming, spark core programming,
The main contents of this section
Hadoop Eco-Circle
Spark Eco-Circle
1. Hadoop Eco-CircleOriginal address: http://os.51cto.com/art/201508/487936_all.htm#rd?sukey= a805c0b270074a064cd1c1c9a73c1dcc953928bfe4a56cc94d6f67793fa02b3b983df6df92dc418df5a1083411b53325The key products in the Hadoop ecosystem ar
Introduction to spark Basics, cluster build and Spark ShellThe main use of spark-based PPT, coupled with practical hands-on to enhance the concept of understanding and practice.Spark Installation DeploymentThe theory is almost there, and then the actual hands-on experiment:Exercise 1 using Spark Shell (native mode) to
-OPENJDK-AMD64You will then need to make the environment variable effective, and execute the following code:SOURCE ~/.BASHRC # makes variable settings effectiveWhen set up, let's check to see if it's set correctly:echo $JAVA _home -version$java_home/bin/java-version # As with direct execution java-versionIf set correctly, the $JAVA_HOME/bin/java -version Java version information is output, and java -version the output is the same as shown in the following example:In this way, the Java r
absrtact: This article mainly introduces TalkingData in the process of building big data platform, introducing spark gradually, and build mobile big data platform based on Hadoop yarn and spark.Now, Spark has been widely recognized and supported at home: In 2014, spark Summit China in Beijing, the scene is hot, the sam
Reprinted from http://www.csdn.net/article/2015-06-08/2824889http://www.zhihu.com/question/26568496Now, Spark has been widely recognized and supported at home: In 2014, spark Summit China in Beijing, the scene is hot, the same year, Spark Meetup in Beijing, Shanghai, Shenzhen and Hangzhou four cities, of which only Beijing has successfully held 5 times, The conte
installed in order to use spark, but it is also possible to not start Hadoop if you use the spark process without using HDFS. In addition, the commands and directories that appear in the next tutorial, if not described, are generally the current path with the installation directory (/usr/local/
Reprinted from: http://www.cnblogs.com/spark-china/p/3941878.html
Prepare a second, third machine running Ubuntu system in VMware;
Building the second to third machine running Ubuntu in VMware is exactly the same as building the first machine, again not repeating it.Different points from installing the first Ubuntu machine are:1th: We name the second to third Ubuntu machine for Slave1, Slave2, as shown in:There are three virtual machines
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