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DEVELOPMENT OF HADOOP TECHNOLOGY

this hadoop shows about the uses of hadoop and what is developing tool used in it.it very simple and easiest to know and better readability.<br><br>http://www.datawaretools.in/chennai-courses/hadoop-training-in-chennai/

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DEVELOPMENT OF HADOOP TECHNOLOGY

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  1. DEVELOPMENT OF HADOOP TECHNOLOGY

  2. Over view of HADOOP • Is an open source software platform for distributed storage and distribute processing of very large data sets on computer clusters built from commodity hardware.  • Hadoopservices provide for data storage, data processing, data access, data governance, security, and operations.

  3. BENEFITS OF HADOOP • Scalability and performance: Store he volume of data with an high speed and retrieve immediately. Reliability: if any one of the node is failure in the cluster it doesn’t bother about the node it will execute other node in the cloud computing process. • Flexibility: unlike traditional relational database management systems, storing huge amount of data. You can store data in any format, including semi-structured or unstructured formats, and then parse and apply schema to the data when read. • Low Cost: unlike proprietary software, Hadoop is open source and runs on low-cost commodity hardware.

  4. HADOOP FUNCTION • Every machine has a data node and a task tracker. Data node is also known as HDFS (Hadoop Distributed File System) and Task tracker is also known as map-reducers. • In the firm each every employee do the different job the give complete result so, • we use the database to store the complete without so Data node contains the entire set of data and Task tracker does all the operations. Thenode means system it has all the detail need to performed.

  5. CHALLENGES OF USING HADOOP • Data security: Give more security for our data • Easy to develop: It is much easier to find programmers with SQL skills than Map Reduce skills. • Full-fledged data management and governance: full-feature tools for data management, data cleansing, governance and metadata.

  6. TECHNOLOGY USED IN HADOOP • HDFS (Hadoop Distributed File System): is part of Hadoop and is known as a special file system which deals with distribution and storage of large set of data. • Hive: Hive was initiated by Facebook. Hive is data warehouse tool which is based on Hadoop and converts query language into Map Reduce jobs. • Hbase: Hbase is a Hadoop application which runs on top of HDFS. Hbase system represents set of table but Hbase is column oriented database management system i.e. different from the row oriented database management system. • Pig: is a high level procedural programming platform developed for simplifying large data sets query in Hadoop and MapReduce

  7. ADVANTAGES • High performance. • Flexibility. • Endurance. • It has power to recovery failed node. • Automatically decrease the overload of data. • Error recovery if data corrupted. • Low cost. • It is simple to use.

  8. DRAWBACKS • Not fit for the real time application. • Single user can operate the data. • When joining multiple dataset it become going to be complex. • It doesn’t have any encryption for storage data

  9. Hadoop Training in Chennai We are giving Hadoop Training in Chennai if you like this course contact our web site Thank you!

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