Disadvantages Of Map Reduce

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Map Reduce Introduction: MapReduce is a simple and powerful programming model which enables development of scalable parallel applications to process large amount of data which is scattered on a cluster of machines. The original implementations of Map Reduce framework had some limitations which have been faced by many research follow up work after its introduction. It is gaining a lot of attraction in both research and industrial community as it has the capacity of processing large data. Map reduce framework used in different applications and for different purposes. Reason Behind Development of Map Reduce: IT giant companies faced the problem of analysing huge sets of data (order of petabytes) E.g. PageRank, web access logs, etc. Algorithm to…show more content…
• It is compared with “filtering then group by aggregation” query processing in a DBMS. • It is simple and easy to use – the MapReduce model is simple but expressive. With MapReduce,a programmer defines job with only Map and Reduce functions, without to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). • Independent of the storage – MapReduce is basically independent from underlying storage layers. It can work on Big Table and others. Many projects at Google store data in Big Table which have different demands from Bigtable, in terms of data size.Bigtable has successfully provided a flexible, high-performance solution for all of these Google products such as Google Earth, Google Finance. • Fault Tolerance – MapReduce is highly fault tolerant, continues working in spite of failures per analysis job at Google. Map Reduce is not suitable for: • Real-time processing. • It's not always very easy to implement each and everything as a MapReduce program. • No high-level language – it does not support any high level language like SQL in DBMS and any query optimization
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