Map Reduce Jobs

Map Reduce is a programming model created to process big data sets. It's oftentimes utilized in the act of distributed computing for different devices. Map Reduce jobs involve the splitting of the input data-set into different chunks. These independent sectors are then processed in a parallel manner by map tasks. The framework will then sort the map outputs, and the results will be included in "reduce tasks." Usually, the input and output of Map Reduce Jobs are kept in a file-system. The framework is then left in charge of scheduling, monitoring, and re-executing tasks.

Map Reduce can be used in jobs such as pattern-based searching, web access log stats, document clustering, web link-graph reversal, inverted index construction, term-vector per host, statistical machine translation and machine learning. Text indexing, search, and tokenization can also be accomplished with the Map Reduce program.

Map Reduce can also be used in different environments such as desktop grids, dynamic cloud environments, volunteer computing environments and mobile environments. Those who want to apply for Map Reduce jobs can educate themselves with the many tutorials available in the internet. Focus should be put on studying the input reader, map function, partition function, comparison function, reduce function and output writer components of the program. Hire Map Reduce Developers


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    Perform Market basket Analysis on big data using Apriori or PCY algorithm. The code should be distributed in nature and written using Hadoop MapReduce and implementation of MRJob library is mandatory.

    ₹13164 (Avg Bid)
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    Hi I have an Apache Hadoop cluster on Virtual box I would like to use cloudera manager to manage the already existing Hadoop cluster ( all nodes are VMs) Also I want you to show me how to use Ranger KMS. Please if you don’t understand what I need don’t waste my time and yours

    ₹2231 (Avg Bid)
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    1 bids
    Devops engineer 2 days left

    Azure , java 8, CI/CD. Should know about azure specifics

    ₹46482 (Avg Bid)
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    10 bids

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