hadoop mapreduce tutorial

The new Java MapReduce API Version 0.20.0 of Hadoop contains a new Java MapReduce API, sometimes referred to as the context object, which is designed to make the API easier to extend in the future. The new API is incompatible with the previous API on the type, so it is necessary to rewrite the previous application to make the new API work. There are several notab

(implementing the Writablecomparable interface or calling the Setsortcomparatorclass function). In this way, the result of reduce acquisition is first sorted by key, followed by the value of the results, it should be noted that the user needs to implement Paritioner, so that only according to key data division. Hadoop explicitly supports two-time sorting, and in the configuration class there is a Setgroupingcomparatorclass () method that can be used

-15 11:10 /user/hadoop/wordcount/output/_logs-rw-r--r-- 1 hadoop supergroup 41 2014-09-15 11:11 /user/hadoop/wordcount/output/part-r-00000使用 hadoop fs –cat wordcount/output/part-r-00000命令查看输出结果，如下所示：#查看结果输出文件内容[[emailprotected] WordCount]$ hadoop fs -cat wordcount/output/p

Some of the pictures and text in this article come from HKU COMP7305 Cluster and Cloud Computing,professor:c.l.wang Hadoop Official Document: HTTP://HADOOP.APACHE.ORG/DOCS/R2.7.5/ Topology and hardware configuration First talk about the underlying structure of Hadoop, we are 4 people a group, each person a machine, install Xen, and then use Xen to open two VMs, is a total of 8 VMS, the configuration of the

(" Yarn.resourcemanager.hostname "," Node7 ");Execute Debug As, Java application in eclipse;Server environment (for a real enterprise operating environment)1, directly run the jar package method, refer to: http://www.cnblogs.com/raphael5200/p/5223684.html2, the local direct call, the execution of the process on the server (real Enterprise operating environment)A, the MR Program packaging (jar), directly into a local directory, I put in the E:\\jar\\wc.jarb, modify the source code of HadoopCopy

Mapreduce has a php interface. Ask who knows the underlying source code. If you want to learn, some php and java interactive mapreduce has a php interface. Ask who knows the underlying source code, want to learn There may be some php and java interactions. Reply content: Mapreduce has a php interface. Ask who knows the underlying source code and want to lear

Hadoop reading Notes (i) Introduction to Hadoop: http://blog.csdn.net/caicongyang/article/details/39898629Hadoop reading notes (ii) HDFS Shell operations: http://blog.csdn.net/caicongyang/article/details/41253927Hadoop reading Notes (iii) Java API operations hdfs:http://blog.csdn.net/caicongyang/article/details/41290955Hadoop reading Notes (iv) HDFS architecture: http://blog.csdn.net/caicongyang/article/det

(Deletedataduplicationreducer.class);Job.setoutputkeyclass (Text.class);Job.setoutputvalueclass (Text.class); Fileinputformat.addinputpath (Job,new Path (otherargs[0]));Fileoutputformat.setoutputpath (Job,new Path (otherargs[1]));System.exit (Job.waitforcompletion (true)? 0:1);}} 3 Execution procedures For information on how to execute a program, you can refer to the implementation procedure in the article "Application II of the Hadoop

From: http://caibinbupt.iteye.com/blog/336467 Everyone is familiar with file systems. Before analyzing HDFS, we didn't spend a lot of time introducing the background of HDFS. After all, you still have some understanding of file systems, there are also good documents. Before analyzing hadoop mapreduce, we should first understand how the system works, and then enter our Analysis Section. The following figure

is relatively large. This means that this node will have more blocks and more er will be generated when mapreduce is executed. However, if the CPU and other hardware are not improved, the performance of the current node will be dragged. Therefore, the increase of this node does not correspond to a linear increase in speed. But it will always be better than three nodes. In addition, by analyzing the working conditions of

What is a complete mapreduce job process? I believe that beginners who are new to hadoop and who are new to mapreduce have a lot of troubles. The figure below is from idea. ToThe wordcount in hadoop is used as an example (the startup line is shown below ): Hadoop