Challenges Involved in Big Data Processing & Methods to Solve Big Data Processing Problems
نویسندگان
چکیده
منابع مشابه
Big Data Processing: Big Challenges and Opportunities
With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as...
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Almost six years ago we started the Spark project at UC Berkeley. Spark is a cluster computing engine that is optimized for inmemory processing, and unifies support for a variety of workloads, including batch, interactive querying, streaming, and iterative computations. Spark is now the most active big data project in the open source community, and is already being used by over one thousand org...
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Motivation Today, “Big Data” is a new information overloading problem in many different areas. Such areas include health cares (e.g., medical records, bioinformatics), e-sciences (e.g., physics, chemistry, and geology), and social sciences (e.g., politics). Thus, as we have various types of feasible data from a number of available sources, it is becoming increasingly more difficult to efficient...
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The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that realtime query processing and in-stream processing is the immediate need in many practical applications. In recent years, this idea got a lot of traction and a whole bunch of solutions like Twitter’s Storm, Yahoo’s S4, Cloudera’s Impala, A...
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ژورنال
عنوان ژورنال: International Journal for Research in Applied Science and Engineering Technology
سال: 2017
ISSN: 2321-9653
DOI: 10.22214/ijraset.2017.8118