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This article will explain in detail the analysis of how to analyze Hadoop. The content of the article is of high quality, so the editor shares it for you as a reference. I hope you will have a certain understanding of the relevant knowledge after reading this article.

Hadoop:

A distributed storage and computing platform suitable for big data. The core of Hadoop is HDFS (Hadoop Distributed File System) hadoop distributed file system, and another is MapReduce parallel computing framework.

Hadoop distributed file system:

When the size of a dataset exceeds the storage capacity of an independent physical computer, it is necessary to Partition it and store it on several separate computers. A file system that manages storage across multiple computers in a network is called distributed file system (Distributed File System).

Hadoop has a distributed file system called HDFS, which is full Hadoop Distributed File System. In informal or old documents and configuration files, it is sometimes referred to as DFS for short.

MapReduce computing framework in Hadoop:

In Hadoop, in fact, the data is processed by MapReduce. First, Map filters the data or other operations. After the input of the reduce side and the output of the Map side during the output of the Map, the data are partitioned, sorted, grouped, aggregated and so on. Finally, the Reduce side outputs the processed data to HDFS for storage, and then the processed data can be extracted and other corresponding operations can be done.

This is the end of the analysis on how to analyze Hadoop. I hope the above content can be of some help to you and learn more knowledge. If you think the article is good, you can share it for more people to see.

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