Course Detail


Hadoop Ecosystem Training (Hive, Pig, and Sqoop)

Course Added By - Kloudmagica (Admin)

25 - Learners
(1 - Total Reviews)  
$251.00
$35.14

Course Description

This Hadoop ecosystem training course is designed to establish and develop you into a Certified Big Data Expert. The training provides you with a unique and practical training experience on Hadoop ecosystem and exposes you to the best practices regarding Hive, Pig, and Sqoop. Once the course is fully accomplished, KloudMagica will award you with a Certification that certifies you as a Hadoop EcoSystem Expert and opens new and rich career opportunities.

 

 

Training Objectives

In order for KloudMagica to nurture you into a Hadoop EcosystemExpert, the course entails the following important objectives:

  • Learn data loading techniques using Sqoop
  • Perform data analytics using Pig and Hive

How will I benefit from learning Hadoop Ecosystem?

Big Data and Hadoop experts are quite high in demand and the market is expected to touch close to a 100 Billion by 2022. Due to the high demand, there is a shortage of experts in this field and when demand is more than supply, the prices hike and that means salaries are going to sky rocket for Big Data and Hadoop Experts.

Who would benefit the most from this course?

This training course is going to open new doors to career opportunities and success for a number of professionals such as:

  • Software Developers and Architects
  • Analytics Professionals
  • Senior IT professionals
  • Testing and Mainframe professionals
  • Data Management Professionals
  • Business Intelligence Professionals
  • Project Managers
  • Aspiring Data Scientists
  • Graduates looking to build a career in Big Data Analytics

 

Are there any prerequisites or prior qualifications/eligibility criteria for this course?

Not really, though basic knowledge of Java Essentials would be a plus. In order to make up for the same, KloudMagica is offering a complimentary access to “Java Essentials for Hadoop” course. Besides Java, knowledge of SQL and Linux could also be beneficial.

 

APACHE PIG

Pig, Session 1, Part 1

      PIG- Introduction
      What is PIG
      Advantages of PIG

Pig, Session 1, Part 2

      Modes of user Interaction with PIG
      Basic parts in Pig programming language
      Pig Compilation and Execution Stages

Pig, Session 2, Part 1

      Data Types    

  •          Simple
  •          Complex

      Case Sensitivity
      Instructions for Identifier

Pig, Session 3, Part 1

      SQL to Pig
      Relational Operators

Pig, Session 3, Part 2

      SQL to Pig
      Relational Operators

Pig, Session 3, Part 3

      SQL to Pig
      Relational Operators

Pig, Session 4, Part 1

      Relational Operators

Pig, Session 4, Part 2

      Relational Operators

Pig, Session 4, Part 3

      Relational Operators

Pig, Session 4, Part 4

      Relational Operators

Pig, Session 5, Part 1

      Relational Operators
      What is Pig UDF?
      Piggy Bank

Pig, Session 5, Part 2

      Basic Operators
      Functions
      Relational Operators-Revision

 

SQOOP (SQL-HAADOOP) BIG DATA TOOL

Sqoop, Session 1

      Data Load into Hadoop and Major Issues
      What is Sqoop?
      What is Sqoop Connectors?

Sqoop, Session 2

      What is Sqoop Connectors?
      SQOOP-METASTORE
      Commands and Syntax for Sqoop

Sqoop, Session 3

      Commands and Syntax for Sqoop

Sqoop, Session 4

      Commands and Syntax for Sqoop

Sqoop, Session 5

      Commands and Syntax for Sqoop

Sqoop, Session 6

      Commands and Syntax for Sqoop

Sqoop, Session 7

      Commands and Syntax for Sqoop

 

APACHE HIVE 

Hive, Session 1

      What is HIVE?
      HIVE query language capabilities
      Where HIVE is not useful?
      Difference between HIVE and rdbms
      Difference between HIVE and pig

Hive, Session 2

      HIVE architecture

Hive, Session 3

      Components in HIVE architecture
      HIVE architecture- query flow
      Data types

Hive, Session 4

      Joins
      HIVE reads and writes records
      Compression formats and codecs
      Encoding methods

Hive, Session 5

      Partitioning

Hive, Session 5

      HIVE bucketed tables
      View

 

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(Course Completed 0%)
Hive-Session-1.1 (What is HIVE + HIVE query language capabilities)
Hive-Session-1.2 (difference between HIVE and rdbms)
Hive-Session-1.3 (difference between HIVE and pig)
Hive-Session-2.1 (HIVE architecture)
Hive-Session-3.1 (Components in HIVE architecture + HIVE architecture- query flow)
Hive-Session-3.2 (Data types)
Hive-Session-4.1 (Joins)
Hive-Session-4.2 (HIVE reads and writes records + Compression formats and codecs)
Hive-Session-4.3 (Encoding methods)
Hive-Session-5.1 (Partitioning)
Hive-Session-6.1 (HIVE bucketed tables + View)
Pig-Session-1.1 (PIG- Introduction + What is PIG +Advantages of PIG)
Pig-Session-1.2 (Modes of user Interaction with PIG + Pig Compilation and Execution Stages)
Pig-Session-2 (Data Types )
Pig-Session-3.1 (SQL to Pig + Relational Operators)
Pig-Session-3.2 (SQL to Pig + Relational Operators)
Pig-Session-3.3 (SQL to Pig + Relational Operators)
Pig-Session-4.1 (Relational Operators)
Pig-Session-4.2 (Relational Operators)
Pig-Session-4.3 (Relational Operators)
Pig-Session-4.4 (Relational Operators)
Pig-Session-5.1 (Relational Operators +What is Pig UDF + Piggy Bank)
Pig-Session-5.2 (Basic Operators + Functions + Relational Operators-Revision)
Sqoop-Session-1 (Data Load into Hadoop and Major Issues + Sqoop Connectors?)
Sqoop-Session-2 (What is Sqoop Connectors?+ Commands and Syntax for Sqoop)
Sqoop-Session-3 (Commands and Syntax for Sqoop)
Sqoop-Session-4 (Commands and Syntax for Sqoop)
Sqoop-Session-5 (Commands and Syntax for Sqoop)
Sqoop-Session-6 (Commands and Syntax for Sqoop)
Sqoop-Session-7 (Commands and Syntax for Sqoop)

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