23 febrero, 2024

What is MapReduce in Hadoop? | Bootcamps

MapReduce in Hadoop is part of the fundamental components to develop the main functions of this system. So, together with HDFS, YARN and Commonthe efficient structure of software that Hadoop offers could not be carried out. Therefore, if you seek to understand this softwareit is very important to start from its main components.

Because of this, in this post we expose you What is MapReduce and how does it work in Hadoop?

What is MapReduce in Hadoop?

MapReduce is one of the essential modules of Hadoop. This is developed based on two key components:

Map (Reading and formatting data): consists of the ability to read and format data within the internal structure of Hadoop.Reduce (Applying transformations and operations on all of the data): in Spanish this translates as the applying transformations and operations on all data.

MapReduce on Hadoop: General word count

Well then, The function of MapReduce is to develop a general word count. This process is based on data reduction through certain selection and analysis processes to facilitate the study of information.

For example, if you wanted to carry out a linguistic study of Don Quixote de la Mancha, you could reduce the work If the word count divides it into seven parts, then into five and so on.

This is how MapReduce works: Counts all the words, then splits the data, splits it again, and repeats until the data is reduced to the maximum. Now, to carry out this system, MapReduce has a series of processes:

Input (entrance): The first of them consists of the aggregation of the textual information to be processed.Splitting (pull apart): refers to the process of data division.Mapping (mapping): information mapping, i.e. the identification and classification of data.Shuffling (shuffle): This process consists of relocation of data according to their relationship.Reducing (reduce): the peak of its function is to reduce. Hadoop MapReduce carries out its main objective of reduce information based on data analysis parameters.Final result: finally, they throw the results of simplified information.

What is the next step?

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