Last Updated on December 30, 2023 by GeeksGod
Course : MAPREDUCE – Big Data with Hands-on MapReduce
Free Udemy Coupon for Big Data MapReduce
MapReduce can be defined as the sub-module of Hadoop that offers huge scalability of data spread across numerous commodity clusters. MapReduce comprises of two things that work consecutively to process the analytics. The process in both the different parts is done in a parallel manner, helping save a lot of time while working with significant data. In the traditional data analysis approach, the data was analyzed serially, but MapReduce overcomes that problem.
As the name suggests, MapReduce involves mapping and reducing processes, which are done by mappers and reducers. The dataset gets divided equally among different mappers, and all of them process or analyze the data in parallel. Once the mapper produces the outcome, reducers come in to generate the final result by collecting the data from all the mappers and processing their outcome.
For instance, if Flipkart needs to find out the total sell in 2018 in Mumbai, the entire process will flow as follows:
1. Dataset Division
The entire dataset will be divided into months. This means that the sell data of one year will be divided into 12 months, indicating how much they made each month from which location.
The dataset will be assigned to 12 mappers, each responsible for finding out in which city and how much goods were sold.
After the mappers generate the report, now it comes to the turn of reducers. The reducers will grab the sell value from every month for the Mumbai location. Eventually, they will sum up the sell values to generate the final outcome.
In this Free Udemy Coupon for Big Data MapReduce training course, you will learn something that is going to be the next big thing, generating lots of opportunities in the near future. You will learn how to work with mass data, including unstructured data. Working with various kinds of data and trying to get all of them on the same page is what you will study here. In technical terms, you will gain practical insight into the working of data scientists. In addition to data processing, you will also learn how to develop programs in HIVE, PIG, MapReduce, and Sqoop.
Every organization has its requirement for data analysis, so it is essential to develop a customized program that can generate the desired output. In this course, you will see and learn how the sub-modules of Hadoop like PIG or HIVE could be used to reduce the complexity of the program. You will also learn which framework should be used in different cases. By the time you complete the MapReduce certification, you will be knowledgeable enough to work with abundant data.