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. Ansæt Map Reduce Developers

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    Gemeinsam mit meinem Kunden aus dem öffentlichen Bereich in Wiesbaden suche ich mehrere Senior Java Entwickler (m/w). Mir ist bewusst, dass unten "nur" die Skills angeführt sind, wobei ich Ihnen den Inhalt des Projektes und die Details gerne am Telefon näherbringe. Anforderungen: • Gute Kenntnisse in der Entwicklung mit o Java EE o ...

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    Its a telematics platform deployed on AWS environment. Data is being retreived via sockets from devices and stored in Hive cluster. Hadoop/Hive is being used for data storing and reporting purpose.

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    I have a task on spark,sqoop,hive. Need anyone who is familiar with spark sql, kafka and hive

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