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WHO SHOULD ATTEND?
  • Analytics Professionals
  • IT Professionals
  • Software Testing Professionals
  • Mainframe Professionals
  • Software Developers & Architects
  • Graduates who are willing to build a career in Big Data
KEY FEATURES
  • There are 3 training centers where you can appear as per your convenience in Kothrud, Shivajinagar and Wakad.
  • Learn Big Data Hadoop the most needed technology for IT Professionals from industrial experienced trainer
  • Weekend batches as per your suitability of individuals.
  • Live Projects to follow up and get hands-on to solidify your understanding
  • Give a personalized attention to each & every candidate during the training sessions.
  • We have limited our batch sizes to a maximum of 10.
  • We have qualified & certified trainers who are working hands-on Big Data Hadoop.
  • Interactive sessions with industry experts
  • We provide 100% Job Assistance after completion of training program
  • There are 3 training centers where you can appear as per your convenience in Kothrud, Shivajinagar and Wakad.
    • If you are located in Kothrud or nearby areas like Karve Nagar, Warje-Malwadi, Bhusari Colony etc. then our branch in located a short distance away from you i.e. Vanaz Corner, Kothrud.
    • If you are located in Pimpri Chinchwad or nearby areas like Pimple Saudagar, Wakad, Chinchwad, Balewadi, Sangvi, Dapodi etc. then you can visit our branch in Wakad near Kalewadi Phata.
    • If you are located in Shivajinagar or nearby areas then you can visit our branch in Fergusson College Road, Shivajinagar.

Outline

Hadoop course Content

  • The Motivation for Hadoop
  • Problems with traditional large-scale systems
  • Requirements for a new approach
  • Hadoop: Basic Concepts
  • What is Hadoop?
  • The Hadoop Distributed File System
  • Hadoop Map Reduce Works
  • Anatomy of a Hadoop Cluster
  • Hadoop demons
  • Master Daemons
  • Name node
  • Job Tracker
  • Secondary name node
  • Slave Daemons
  • Job tracker
  • Task tracker

HDFS (Hadoop Distributed File System)

  • Blocks and Splits
  • Input Splits
  • HDFS Splits
  • Data Replication

Hadoop Administration:

  • Setup Hadoop cluster (Apache & Cloudera)
  • Pseudo-distributed Mode
  • Make a fully distributed Hadoop cluster on a single laptop/desktop
  • Install and configure Apache Hadoop on a multi node cluster in lab
  • Install and configure Cloudera Hadoop distribution in fully distributed mode
  • Monitoring the cluster
  • Getting used to management console of Cloudera
  • Name Node in Safe mode
  • Meta Data Backup
  • Ganglia and Nagios – Cluster monitoring

Hadoop Development:

Writing a MapReduce Program

  • Examining a Sample MapReduce Program
  • With several examples
  • Basic API Concepts
  • The Driver Code
  • The Mapper
  • The Reducer
  • Hadoop’s Streaming API

Debugging MapReduce Programs

  • Testing with MRUnit
  • Logging
  • Other Debugging Strategies.

Advanced MapReduce Programming

  • The Secondary Sort
  • Customized Input Formats and Output Formats
  • Joins in MapReduce

Performing several Hadoop jobs

  • The configure and close Methods
  • Sequence Files
  • Record Reader
  • Record Writer
  • Role of Reporter
  • Output Collector
  • Counters
  • Directly Accessing HDFS
  • ToolRunner
  • Using The Distributed Cache

Hadoop Analyst

Hive

  • Hive concepts
  • Hive architecture
  • Install and configure hive on cluster
  • Different type of tables in hive
  • Hive library functions
  • Buckets
  • Partitions
  • Joins in hive
  • Inner joins & Outer Joins
  • Hive UDF

PIG

  • Pig basics
  • Install and configure PIG on a cluster
  • PIG Library functions
  • Pig Vs Hive
  • Write sample Pig Latin scripts
  • Modes of running PIG
  • Running in Grunt shell
  • Running as Java program
  • PIG UDFs
  • Pig Macros
  • Debugging PIG

HBase

  • HBase concepts
  • HBase architecture
  • HBase basics
  • Region server architecture
  • File storage architecture
  • Column access
  • Scans
  • Install and configure HBase on a multi node cluster
  • Create database, Develop and run sample applications
  • Access data stored in HBase using clients like Java, Python and Pearl
  • Map Reduce client to access the HBase data
  • HBase admin tasks

Sqoop

  • Install and configure Sqoop on cluster
  • Connecting to RDBMS
  • Installing MySQL
  • Import data from Oracle/MySQL to hive
  • Export data to Oracle/MySQL
  • Internal mechanism of import/export

Oozie

  • Oozie architecture
  • XML file specifications
  • Install and configuring Oozie and Apache
  • Specifying Work flow
  • Action nodes
  • Control nodes
  • Oozie job coordinator

Zookeeper

CDH4 Enhancements:

  • Name Node High – Availability
  • Name Node federation
  • Fencing

  MapReduce Version –2

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Training Institute Pune is a leading institute in Pune conducting training programs for various software fields & provides certification for both individuals and organizations.Training Institute Pune is subsidiary of Optimized Infotech which offers IT services and training.

We have built a strong reputation to provide an excellent service to individuals with a team of fully qualified professionals. We deliver training to the employed and unemployed individuals to enhance their knowledge & qualities in desired field. We design a training program for additional qualifications beneficial for future & for great career start to candidate undergoing training at our Institute.

Institute offers a wide variety of software classes and access to the concepts and skill development reinforced through training & consulting and certification. The institute is taking a lead in spreading an innovative form of learning that provides you with theoretical as well as practical training.

OUR OBJECTIVE
Our objective is to cater all individuals ranging from beginner level to the IT professionals. Our motto is to provide interactive environment so that the candidates can excel themselves in their desired field & help them grow their career. We put efforts to honestly serve the society & to provide excellent training & classes facilities to our candidates. ...

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