Bigdata Hadoop Online Training

Big Data is one of the most sought after technology in the market in today’s day and age is Big Data.

Big data means big information, it collection large volume of data through traditional computing techniques Hadoop. Hadoop provides that ability to store the large scale data on HDFS process. Big Data is one of the driving employment contracting on the world. It is the most important structure for data to vast arrangements of information to implement, and it quickly transforming into most needed advancements in various Professionals like.

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Course Information

Big Data is one of the most sought after technology in the market in today’s day and age is Big Data.

Big data means big information, it collection large volume of data through traditional computing techniques Hadoop. Hadoop provides that ability to store the large scale data on HDFS process. Big Data is one of the driving employment contracting on the world. It is the most important structure for data to vast arrangements of information to implement, and it quickly transforming into most needed advancements in various Professionals like.

  • Software Developers
  • Banking Data
  • Data Mining
  • Testing Professionals
  • Stock Exchange Data
  • Project Managers
  • Networks and Devices Data
Who Can Take This Course?
Who Can Take This Course?

It is an awesome stage to go into Hadoop industry. Big Data is building up everywhere throughout the world and changing over into extraordinary opportunities. Here are a couple of Professional IT groups who are continuously getting a charge out of the advantages moving into Big Data area:

  • Software Developers
  • Analytics Experts
  • Data warehouse professionals
  • Fresher’s
  • Architects Experts
What Are The Prerequisites?

Should have the essential information on Core Java and basic Knowledge Hadoop. It definitely plus for beginners to reduce the learning time.SQL will profit yet not mandatory. As part of Big Data Hadoop Training  can give a complete self- managed course on core java.

Big Data is a concept and Hadoop is a framework for it. The course begins with learning the basics of Linux. This is the foundation that is required to excel the concept of Big Data. While learning the basics of Big Data, students will be introduced to few basic concepts of Big Data such as word count programs. This would slowly scale to little complex and advanced topics of writing triggers and storing procedures to Hadoop’s database.

Students will be introduced to the concept of NoSQL database. What is a No SQL database? Why is it used instead of RDBMS databases? These questions will be answered by the end of the course onBig Data and Hadoop.

Students of Online IT Guru will also know the differences and challenges of both NoSQL database and HBase. A Virtual Machine will be given to all the participants along with Big Data frameworks like Hadoop, LinkedIn Samza and Twitter Storm.These frameworks are installed and configured on CentOS with code and datasets to continue with the said process. With the Virtual machine, learning Big Data is made easier.

Added Advantage With ASTS!

With the help of training received from Online IT Guru, students can be Cloudera certified Developer for Apache Hadoop, a certification issued by Apache Hadoop. This certification could give the students that huge boost in their careers.

Hands-On Experience

Students receive all the real time experience they could get through the assignments given by our experienced faculty who have worked earlier in the industry with Big Data and Hadoop framework.

Core topics of BIG DATA HADOOP Online Course

Introduction to BigData and its Eco-system

– What is Big Data?   – Hadoop – Big Data Overview   – Hadoop – Big Data Solution   – Hadoop – Introduction    – Introduction to Hadoop Eco system

Introduction to HDFS and its Command-Line Interface

– Hadoop – HDFS Overview   – Features of HDFS   – HDFS Architecture   – Hadoop – HDFS Operations

Environment Setup

Introduction to MapReduce (in Java) Core Java Basics

– Hadoop – MapReduce Overview   – MapReduce Architecture   – YARN Architecture InputFormat

InputSplits,  RecordReader,  Mapper,  Reducer,  Partitioner and Combiner

Basic MapReduce Programming ( word count execution in both local and cluster mode)

Advanced MapReduce Programming

– Use Custom Record reader   – Use Custom Partitioner

Identity Mapper/Reducer,  Distributed Cache,  Arbitable Offset,  Writable and Writable Comparable Interface

Data Ingestion in to Hadoop

– Apache Sqoop   – Apache Flume

Introduction to Hive (Regular Hive + Hive on Tez)

– Hive Introduction   – Hive Datatypes   -Hive Managed Tables and External Tables  – Hive DDL Operations  – Hive DML operations  – Hive Partitions and Bucketing  – Hive Joins  – Hive Built-in functions  – Hive UDF’s  – Use FileFormat like Avro, Sequence, RC and ORC  Hive SERDE’s

Performance Tuning in Hive  – Hive JDBC connectivity

Introduction to PIG

– PIG Introduction (About Pig , HIVE vs PIG)   – PIG Datatypes   – PIG operators  – PIG UDF’s  – Process dataset in PIG script using PiggyBank jars

Introductito Workflow Processing

– Apache Oozie   – WordCount Program execution using Oozie workflow   – Oozie workflow for sqoop , hive and pig

Introduction to Scala Programming Language and basics

Introduction to SPARK   – Spark Introduction   – Spark Architecture   – Spark RDD’s

– Spark Components( Streaming and Spark SQL)   -Programming in Spark + Spark Streaming

Introduction to Kafka

Introduction to NoSql Databases

– Hbase Introduction    – Hbase Architecture    – HBase Commands   – Mongo Db

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