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Big Data Analytics using Hadoop

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Overview
  • manipal overview icon
    Lucrative Career Option
    73% of organizations have already invested or plan to invest in big data.
  • manipal overview icon
    Job Opportunities
    Complete the Hadoop online training become eligible for over 1,500,000 jobs.
  • manipal overview icon
    Who Should Attend
    Beginners in analytics domain, engineering & non-engineering graduates.
  • manipal overview icon
    Salary Packages
    The average salary for an entry-level Big Data engineer is ₹5 lakhs per annum.
  • manipal overview icon
    Expert Faculty
    The Big Data certification course is taught by eminent big data experts.
manipal overview icon
Lucrative Career Option
73% of organizations have already invested or plan to invest in big data.
manipal overview icon
Job Opportunities
Complete the Hadoop online training become eligible for over 1,500,000 jobs.
manipal overview icon
Who Should Attend
Beginners in analytics domain, engineering & non-engineering graduates.
manipal overview icon
Salary Packages
The average salary for an entry-level Big Data engineer is ₹5 lakhs per annum.
manipal overview icon
Expert Faculty
The Big Data certification course is taught by eminent big data experts.
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Course Curriculum
1.1 Introduction to BIG DATA and Hadoop
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Introduction
Challenges of Processing Big Data
Distributed Systems
History of Hadoop
Hadoop Overview
Ecosystem of Hadoop
HDFS and Map Reduce Paradigm
Processing Pipeline
Big Data Technologies
Use Cases
Features of Hadoop
Summary

1.2 Hadoop Environment Setup
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Introduction
Hadoop Installation and Configuration
Hive Installation and Configuration
Pig Installation and Configuration
Sqoop Installation and Configuration
Oozie Installation and Configuration
Flume Installation and Configuration
Hbase Installation and Configuration
Hue Installation and Configuration

1.3 HDFS Architecture
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Introduction
HDFS Configuration Files
Data Storage in HDFS
Blocks and Splits
Metadata Files
Name Node – Demo
HDFS Data Storage – Demo
High Availability
Data Replication – Demo
Reliable Storage – Demo
HDFS Client
Data Node – Demo
HDFS Clients – Demo
HDFS Clients – Demo

1.4 HDFS Commands
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Introduction
HDFS Commands
Basic HDFS Commands - Demo
Read Anatomy in HDFS
Write Anatomy in HDFS
Additional HDFS Commands - Demo
HDFS File System API
HDFS File System API - Demo
HDFS Permission Management
Permission Management – Demo
Summary

1.5 MapReduce
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MapReduce 1 Architecture
MR and Traditional Approach
Architecture 1
Introduction to YARN
Architecture 2
Summary

2.1 MapReduce Programs
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Introduction
Executing a MapReduce Program - Demo
Datatypes and APIs
MapReduce Concepts
Mapper – Demo
MapReduce – Demo
Combiners – Demo
Partitioners – Demo
Debug logs & Printing in MR Jobs – Demo
Path Filters – Demo
Splits – Demo
Named Output – Demo Summary
Write MapReduce Keys and Values – Demo
Identity Mappers – Demo
Identity Reducers – Demo
Counters in Hadoop
MapReduce Counters – Demo
Input and Output Formats
About MR Unit
MR Unit – Demo
Summary

2.2 MapReduce and Job Execution
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Introduction
Job Flow
Job Submission
Job Initializing
Job Scheduling
Map Task Execution
Sort and Shuffle
Reduce Task Execution
Job Cleanup
Job Failure – Demo
Staggering Job – Demo
Scheduler
Summary

2.3 Hadoop Serialization and Compression
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Introduction -Serialization
Uses of Serialization
Serialization Techniques
Summary
Introduction - Compression
Uses of Compression
Compression Techniques
Summary

2.4 Advanced MapReduce Programming
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Introduction
Customization of Input Format APIs
Input Format and Record Readers – Demo
Distributed Cache
Distributed Cache – Demo
Map Side Joins
Sideways Joins
Map Side Joins – Demo
Reduce Side Joins
Reduce Side Joins – Demo
Sequence File Format
Sequence File Creation – Demo
Sequence File with MapReduce -Demo
Hadoop Streaming
Hadoop Streaming – Demo
Configuring Development Environment using Eclipse – Demo
Running MapReduce Jobs – Demo
Summary

2.5 Apache Hive
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Introduction
Hive vs RDBMS
Hive Architecture
Hive Components
Hive Schema Model
Hive Integration with Hadoop
Hive Query Language
Transformation in Hive
Hive Database Creation - Demo
Hive Tables - Demo
Hive Queries - Demo
Advanced Hive Partitioning - Demo
Bucketing - Demo
Advanced Concepts - Demo
Manage an XML or JSON files - Demo
Use a predefined SERDE - Demo
Summary

3.1 Apache Pig
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Introduction
MapReduce and Pig
Modes of Execution in Pig
Pig Client
Pig Datatypes and Operators
SQL vs Apache Pig
Pig Usage
Loading Data in Pig – Demo
Pig Dialects – Demo
Transformations in Pig – Demo
Debugging in Pig – Demo
Other capabilities in Pig - Demo

3.2 Apache Hbase
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Introduction
Categories of NoSQL Databases
Hbase Evolution
Hbase vs RDBMS
Hbase Architecture
Hbase Components
Column Family
Hbase Fundamentals
Hbase Client
Basic CRUD Operation Demo
Basic CRUD Operation
Zookeeper
Zookeeper Demo
Summary

3.3 Apache Sqoop, Oozie and Hue
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Introduction - Apache Sqoop
Sqoop Usage
Working with Sqoop – Demo
Advanced Sqoop
Hive Integration – Demo
Hbase Integration – Demo
Sqoop Scripts - Demo
Introduction - Apache Oozie
Oozie Client
Basic Workflow Setup
Types of Oozie Actions
Control Statements
Defining a Workflow
Run MapReduce with Oozie - Demo
Summary
Introduction - Apache Hue
Hue User Interface
Working with Hive using Hue
Working with Pig using Hue
Monitoring an Oozie Job using Hue
Apache Hue – Demo
Summary

3.4 Streaming
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Introduction Summary
Apache Flume Introduction
Flume Core Components
Launch Flume
Apache Flume - Demo
Apache Spark & Storm Introduction
Storm Concepts
Spark Streaming Concepts
Deployment Architecture
Summary

3.5 Hadoop Real Time Deployment and Distribution
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Introduction - Real time deployment
System architecture
Logical deployment overview
Physical deployment overview
Summary
Introduction - Big data software and tools
Streaming tools
NoSQL tools
Workflow Tools
Administration tools
Other ecosystem tools
Summary

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