Hadoop and BigData Online Training

Course Objective – Hadoop and BigData

The main objective of this course is to help you understand Complex Architectures of Hadoop and its components, guide you in the right direction to start with, and quickly start working with Hadoop and its components. It covers everything what you need as a Big Data Beginner. Learn about Big Data and Hadoop market, different job roles, technology trends, history of Hadoop, HDFS, Hadoop Ecosystem, Hive and Pig. In this course, we will see how as a beginner one should start with Hadoop. This course comes with a lot of hands-on examples which will help you learn Hadoop quickly.

Job Opportunities

Looking at the Hadoop market forecast, it looks promising and the upward trend will keep progressing with time. Hence, the job trend or Market is not a short lived phenomenon as Hadoop and its technologies are here to stay. Hadoop has the potential to improve job prospects whether you are a fresher or an experienced professional. The average salary for big data analytic professionals in the non-managerial role is 8.5 lakhs INR, whilst managers can earn an average of whopping 16 lakhs.

Course Duration

Total duration: 30 hours

Detailed course content

Module 1: Understanding Big Data and Hadoop

    • Hadoop Online Training Course Learning Objectives
    • Understand Big Data
    • The limitations of the existing solutions for Big Data problem
    • How Hadoop solves the Big Data problem
    • The common Hadoop ecosystem components

Hadoop Architecture, HDFS, Anatomy of File Write and Read
Rack Awareness.

Below topics will be discussed as part of Big Data, hadoop online training

  • Hadoop online training course, Big Data, Limitations and Solutions of existing Data Analytics Architecture
  • Hadoop, Hadoop Features, Hadoop Ecosystem, Hadoop 2.x core components
  • Hadoop Storage: HDFS, Hadoop Processing: MapReduce Framework, Anatomy of File Write and Read, Rack Awareness

Module 2: Hadoop Online Training Course MapReduce Framework – I

  • Hadoop Online Training Course Learning Objectives
  • Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS
  • YARN concepts in MapReduce

Below topics will be covered apart of MapReduce, hadoop online training

  • MapReduce Use Cases
  • Traditional way Vs MapReduce way
  • Why MapReduce
  • Hadoop 2.x MapReduce Architecture
  • Hadoop 2.x MapReduce Components
  • YARN MR Application Execution Flow
  • YARN Workflow
  • Anatomy of MapReduce Program
  • Demo on MapReduce.

Module 3: Hadoop MapReduce Framework – II

Learning Objectives

  • Input Splits in MapReduce
  • Combiner & Partitioner and Demos on MapReduce using different data sets

Below topics as part of MapReduce, hadoop online training

  • Input Split
  • Relation between Input Splits and HDFS Blocks
  • MapReduce Job Submission Flow
  • Demo of Input Splits
  • MapReduce: Combiner & Partitioner, Demo on de-identifying Health Care Data set, Demo on Weather Data set.

Module 4: Advance MapReduce

Learning Objectives

  • Advance MapReduce concepts such as Counters
  • Distributed Cache, MRunit
  • Reduce Join, Custom Input Format, Sequence Input Format and how to deal with complex MapReduce programs

Below topics will be discussed as part of MapReduce, hadoop online training

  • Counters
  • Distributed Cache
  • MRunit
  • Reduce Join
  • Custom Input Format
  • Sequence Input Format

Module 5: Pig

Learning Objectives

  • Types of use case we can use Pig
  • Tight coupling between Pig and MapReduce
  • Pig Latin scripting.

Below topics will be discussed as part of Pig, hadoop online training

  • About Pig
  • MapReduce Vs Pig
  • Pig Use Cases
  • Programming Structure in Pig
  • Pig Running Modes
  • Pig components
  • Pig Execution
  • Pig Latin Program
  • Data Models in Pig
  • Pig Data Types
  • Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Pig UDF, Pig Demo on Healthcare Data set.

Module 6: Hive

Learning Objectives

  • Hive concepts
  • Loading and Querying Data in Hive and Hive UDF

Below topics will be discussed as part of Hive, hadoop online training

  • Hive Background
  • Hive Use Case
  • About Hive
  • Hive Vs Pig
  • Hive Architecture and Components
  • Metastore in Hive
  • Limitations of Hive
  • Comparison with Traditional Database
  • Hive Data Types and Data Models
  • Partitions and Buckets
  • Hive Tables(Managed Tables and External Tables)
  • Importing Data
  • Querying Data
  • Managing Outputs
  • Hive Script
  • Hive UDF
  • Hive Demo on Healthcare Data set.

Module 7: Advance Hive and HBase

Learning Objectives

  • Advance Hive concepts such as UDF
  • Dynamic Partitioning.
  • HBase
  • Hbase Architecture and its components.

Below topics will be discussed as part of Hive, Hbase and hadoop online training

  • Hive QL
  • Joining Tables
  • Dynamic Partitioning
  • Custom Map/Reduce Scripts
  • Hive : Thrift Server, User Defined Functions

HBase:

  • Introduction to NoSQL Databases and HBase, HBase v/s RDBMS
  • HBase Components
  • HBase Architecture
  • HBase Cluster Deployment

Module 8: Advance HBase

Learning Objectives

  • Advance HBase concepts
  • Bulk Loading , Filters
  • Zookeeper

Below topics will be discussed as part of HBase, hadoop online training

  • HBase Data Model
  • HBase Shell
  • HBase Client API
  • Data Loading Techniques
  • Zookeeper Data Model
  • Zookeeper Service
  • Zookeeper
  • Demos on Bulk Loading
  • Getting and Inserting Data
  • Filters in HBase

Module 9: Oozie and Hadoop Project

Oozie is workflow scheduler system to manage apache hadoop jobs. Oozie is scalable, reliable and extensible system. Oozie is integrated with the rest of the hadoop stack supporting several types of hadoop jobs. Example:-java mapreduce, Streaming map-reduce, Pig, Hive, Sqoop. Oozie coordinator jobs are recurrent oozie workflow jobs triggered by time and data availability. It is something like CronTab in Linux or File Polar in Java. Yahoo is running 200k Jobs per day using Oozie.

Below topics will be discussed as part of Oozie, hadoop online training

  • Flume and Sqoop Demo
  • Oozie
  • Oozie Components
  • Oozie Workflow
  • Scheduling with Oozie
  • Demo on Oozie Workflow
  • Oozie Co-ordinator
  • Oozie Commands
  • Oozie Web Console
  • Hadoop Project Dem0

Trainer Profile

Trainer of this course has 8+ years of experience in the IT field.He presently gives training on Machine learning / AI /Deep Learning / Big Data / Data Science using R / HADOOP /IOT / Java / Cloud Computing /Ethical hacking/Linux.
For training enquiries please mail to [email protected] or call +91  8008 048 446.

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