Map Reduce Jobs and ContestsMap 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 Programmers on Freelancer
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|Multicast replication for Hadoop HDFS (Big Data)||The Hadoop HDFS is a popular open-source distributed storage system, which serves as the foundation of many important big-data technologies. The performance of data replication is crucial to HDFS, since it accounts for a major portion of network traffic in the entire cluster. In this research, we propose to enable multicast-based replication, which is expected to use less network bandwidth t...||7||Java, Big Data, Hadoop, Map Reduce||Sep 23, 2016||Sep 23, 20161d 9h||$351|
|map reduce||map reduce||5||Map Reduce||Sep 22, 2016||Sep 22, 20161d||$167|
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