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The solution for Big data HADOOP

The solution for Big data HADOOP. J. Sai Krishna and G. Sravya Lahari 2 nd B.Tech (CSE) K.O.R.M College of Engineering Kadapa. Contents. Data – trends in storing data. Bigdata – problems in IT industry Introduction to HADOOP HDFS (Hadoop Distributed File System) MapReduce

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The solution for Big data HADOOP

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  1. The solution for Big data HADOOP J. Sai Krishna and G. Sravya Lahari 2nd B.Tech (CSE) K.O.R.M College of Engineering Kadapa

  2. Contents • Data – trends in storing data. • Bigdata – problems in IT industry • Introduction to HADOOP • HDFS (Hadoop Distributed File System) • MapReduce • Prominent users of Hadoop. • Conclusion

  3. Data – trends in storing data • What is data--- Any real world symbol (character, numeric, special character) or a of group of them is said to be data it may be of the visual or audio or scriptural ,etc

  4. Big data • What is big data—In IT, it is a collection of data sets so large and complex data that it becomes difficult to process using on-hand database management tools or traditional data processing applications. • As of 2012, limits on the size of data sets that are feasible to process in reasonable time were on the order of Exabyte of data.

  5. BIGDATA and problems with it. • Daily about 0.5 Petabytes of updates are being made into FACEBOOK including 40 millions photos. • Daily, YOUTUBE is loaded with videos that can be watched for one year continuously • Limitations are encountered due to large data sets in many areas, including meteorology, genomics, complex physics simulations, and biological and environmental research. • Also affect Internet search, finance and business informatics. • The challenges include in capture, retrieval, storage,search, sharing, analysis, and visualization.

  6. HADOOP THEN WHAT COULD BE THE SOLUTION FOR BIGDATA

  7. What is Hadoop? • It is a opensource software written in java • Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. • It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.

  8. The project includes these modules: • Hadoop Common • Hadoop Distributed File System (HDFS) • Hadoop MapReduce

  9. 1.Hadoop Commons • It provides access to the filesystems supported by Hadoop. • The Hadoop Common package contains the necessary JAR files and scripts needed to start Hadoop. • The package also provides source code, documentation, and a contribution section which includes projects from theHadoop Community (Avro, Cassandra, Chukwa, Hbase, Hive, Mahout, Pig, ZooKeeper)

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