Hadoop Training
Introduction to Hadoop Training The Apache Hadoop is an open source software and highly scalable distributed platform enables applications to run on thousands of nodes involving thousands of terabytes of data. It can efficiently process large volume of unstructured data in relatively less time. MapReduce decomposes the data into map to reduce tasks and schedules for remote execution on data nodes. Big Data Hadoop Training curriculum is designed to briefly explain the concepts of HDFS and map reduce and also teach how to write map reduce programs and Implementing in HBase. Assimilate to write Hive and pig scripts. Inherit the advantages of Hadoop sqoop, how to run scripts to transfer data between Hadoop and RDBMS.
Course Curriculum Unit 1: Need for Big Data Hadoop Topics:- Introduction to Big Data hadoop,Problem with existing traditional system, Requirements for new approach,Comparing SQL databases and NOSQL(Hadoop).
Unit 2: Hadoop Training Basic Concepts Topics:- An Overview of Hadoop, Configuring a Hadoop in Ubuntu OS, First example in Hadoop. Unit 3: The Hadoop Distributed File System
Topic:- Name nodes, Data nodes, The Hadoop Command-Line Interface, Reading and writing data using Java, Hadoop Archives.
Unit 4: Big Data Hadoop Best Practice
Unit 5: Introduction to HBASE Topic:- What is HBase?, HBase Architecture in Hadoop, Hadoop HBase API, Managing large data sets with HBase, Using HBase in Hadoop applications.
Unit 6: Introduction to Hadoop Zookeeper Topic:- Summary, Sample Applications, References of training.
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