hadoop admin and development training classes online with ppts, hadoop administration and development introduction for beginners. For more info: http://kerneltraining.com/hadoop-administration-and-development/ E-mail: sales@kerneltraining.com Phone no: +91 8099 77 6681 About Course: This course combines Hadoop Admin and Hadoop Development objectives. Hadoop Admin covers Configuring, Deploying and Maintaining a Hadoop Cluster. When you learn about Hadoop Development, MapReduce application in Java programming is dealt in detail. Hadoop Development course also includes debugging, managing jobs, improving performance, working with custom data, managing workflows, and using other programming languages. Through the training, you can get better practical hands-on exercise, project work guidance, and open discussion on Hadoop large data sets in enterprises. Course Objective • Introduction to Big Data, Hadoop & HDFS & Administration • Hadoop Map-reduce concepts and features • Hadoop Administration concepts • Apache Hive • Apache Pig • Apache Flume & Sqoop • Apache HBASE Concepts, YARN & MR V2 • Apache Oozie workflow concepts • Introduction to Apache Storm • Introduction to Apache Spark • Real World Final Project Banking POC Course Targeted Audience: The Hadoop Development and Admin course targets System Administrators, IT managers and Support Engineers who can work on Hadoop clusters in production or development environments. In addition to, the course also targets developers who want to work on Java MapReduce applications for Hadoop 2.0. Prerequisites: Prior knowledge about for Hadoop not required. Graduates with some prior experience in Core Java and good analytical skills can undergo Hadoop analysis training. Basic knowledge of UNIX, sql scripting. Well applicable for people proficient with Object Oriented Programming language (OOPS) and JAVA. Training Format: Training at Kernel Technology will be instructor-led lecture and discussion. Course will end with hands-on labs experience along with project completion. Certification of the course after successful completion of quiz.Course Curriculum: Module 1 Introduction to Big Data and Hadoop Module 2 Understanding the Cluster Administration Module 3 Map Reduce Module 4 How Map-Reduce Works Module 5 Map Reduce Types and Formats Module 6 Map Reduce Features Hadoop Administration: Module 1 Installation [SQOOP, Pig and pig Latin, HBASE, Hadoop 2.0, MRv2 and YARN Apache Module 2 Clusters Module 3 Hive Module 4 SQOOP Module 5 Pig and Pig Latin Module 6 HBASE Module 7 Hadoop 2.0, MRv2 and YARN Module 8 Apache Flume Module 9 Oozie Module 10 Introduction to Apache Storm Module 11

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• System logfiles produced by Hadoop are stored in $HADOOP_INSTALL/logs by default
• Each Hadoop daemon running on a machine produces two logfiles.
• The first is the log output written via log4j. This file, which ends in .log, should be the first
port of call when diagnosing problems, since most application log messages are written here.
• Old logfiles are never deleted, so you should arrange for them to be periodically deleted or
archived, so as to not run out of disk space on the local node.
• The second logfile is the combined standard output and standard error log. This logfile,
which ends in .out, usually contains little or no output, since Hadoop uses log4j for Logging.
Only the last five logs are retained. Old logfiles are suffixed with a number between 1 and 5,
with 5 being the oldest file.

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