Data Analysis Using Hadoop Tools

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Data Analysis Using Hadoop Tools

This course is part of Big Data Processing Using Hadoop Specialization

Instructor: Karthik Shyamsunder

Included with

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5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Learn to set up and configure Hive, Pig, HBase, and Spark for efficient big data analysis and processing within the Hadoop ecosystem.
Master Hive’s SQL-like queries for data retrieval, management, and optimization using partitions and joins to enhance query performance.
Understand Pig Latin for scripting data transformations, including the use of operators like join and debug to process large datasets effectively.
Gain expertise in NoSQL databases with HBase for real-time read/write operations, and use Spark’s core programming model for fast data processing.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

15 assignments

Taught in English

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This course is part of the Big Data Processing Using Hadoop Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 5 modules in this course

The course "Data Analysis Using Hadoop Tools" provides a thorough and hands-on introduction to key tools within the Hadoop ecosystem, such as Hive, Pig, HBase, and Apache Spark, for data processing, management, and analysis. Learners will gain practical experience with Hive's SQL-like interface for complex data querying, Pig Latin scripting for data transformation, and HBase's NoSQL capabilities for efficient big data management. The course also covers Apache Spark's powerful in-memory computation capabilities for high-performance data processing tasks. By the end, participants will be equipped with the skills to leverage these technologies within the Hadoop platform to address real-world big data challenges.

What makes this course unique is its comprehensive approach to integrating various Hadoop tools into a cohesive workflow. You'll not only learn how to use each tool individually but also understand how to effectively combine them to optimize data processing and analysis. Through hands-on exercises and examples, you'll gain the confidence and skills to tackle complex data challenges and extract valuable insights from big data. Whether you're looking to enhance your data analysis capabilities for work or want to deepen your knowledge of Hadoop and big data tools, this course offers valuable skills that will help you succeed.

This course provides a comprehensive overview of key tools within the Hadoop ecosystem, including Hive, Pig, HBase, and Apache Spark. You will learn how to set up and configure these technologies for data processing, management, and analysis. The course covers Hive's query execution, Pig's scripting language, and HBase's NoSQL capabilities. You'll also gain hands-on experience with Spark's core programming model for efficient big data processing. By the end, you'll be equipped to leverage these tools for optimized data analysis and management.

What's included

2 readings

In this module, we will cover MapReduce programming using a higher-level language called Hive which translates Hive SQL-like queries to MapReduce.

What's included

9 videos7 readings4 assignments

9 videos Total 107 minutes

Introduction - Hive 2 minutes
Hive Overview and Architecture 23 minutes
Setting up Hive 26 minutes
Simple Hive Example 20 minutes
Loading Data 9 minutes
Hive Statements 11 minutes
Partitions 6 minutes
Joins 8 minutes
Summary- Hive 2 minutes

7 readings Total 105 minutes

Hive Overview and Architecture 10 minutes
Setting up Hive 10 minutes
Simple Hive Example 10 minutes
Loading Data 10 minutes
Hive Statement 10 minutes
Partitions and Joins in Hive 15 minutes
Self-Reflective Reading: Balancing Hive, Java MapReduce, and Pig in Hadoop Architectures 40 minutes

4 assignments Total 105 minutes

Introduction to Hive: Overview, Architecture, and Setup 15 minutes
Working with Hive: Basic Examples, Data Loading, and Hive Statements 15 minutes
Advanced Hive: Partitions, Joins, and Summary 15 minutes
Data Analysis using Hive 60 minutes

In this module, we will cover MapReduce programming using a higher-level language called Pig which translates Pig Latin queries to MapReduce.

What's included

9 videos7 readings4 assignments

9 videos Total 132 minutes

Introduction - Pig 2 minutes
Pig: Overview and Architecture 22 minutes
Setting up Pig 8 minutes
Grunt Interactive Shell 18 minutes
Pig Latin Language Basics 10 minutes
Pig Data Types and Schema 15 minutes
Core Relational Operators 14 minutes
Join Operators 26 minutes
Debug Operators 17 minutes

7 readings Total 102 minutes

Pig: Overview and Architecture 15 minutes
Grunt Interactive Shell 7 minutes
Exploring Pig Latin Basics: Data Structures, Syntax, and Commands 10 minutes
Understanding Schemas, Data Types, and Functions in Apache Pig 10 minutes
Core Relational Operators in Pig Latin: An Overview 10 minutes
Exploring Relational Join Operators in Apache Pig 10 minutes
Self-Reflective Reading: Hive vs. Pig for Your Big Data Strategy 40 minutes

4 assignments Total 105 minutes

Introduction to Pig: Overview, Architecture, and Setup 15 minutes
Pig Fundamentals: Grunt Shell, Pig Latin Basics, and Data Types 15 minutes
Pig Advanced: Core Operators, Joins, Debugging, and Summary 15 minutes
Data Analysis using Pig 60 minutes

In this module, we will start with a primer of NoSQL databases and then dive into HBase, a NoSQL database built on top of Hadoop that allows for random, real-time read/write access to your Big Data.

What's included

8 videos3 readings3 assignments

8 videos Total 175 minutes

Introduction - HBase 2 minutes
NoSQL Primer 35 minutes
HBase Overview and Architecture 31 minutes
Setting up HBase 25 minutes
HBase Data Model 16 minutes
HBase Shell 33 minutes
CRUD operations using Java API 31 minutes
Summary - HBase 3 minutes

3 readings Total 60 minutes

HBase Overview and Architecture 10 minutes
HBase Data Model 10 minutes
Self-Reflective Reading: Coexisting Databases: Balancing NoSQL and RDBMS in Modern Applications 40 minutes

3 assignments Total 90 minutes

Introduction to HBase: NoSQL Basics, Architecture, and Setup 15 minutes
HBase Fundamentals: Data Model, Shell, CRUD Operations, and Summary 15 minutes
Hadoop NOSQL Database HBase 60 minutes

In this module, we will cover the Spark engine and framework and show how it integrates on the Hadoop platform.

What's included

8 videos5 readings4 assignments

8 videos Total 233 minutes

Introduction - Spark 3 minutes
Spark Overview 38 minutes
Spark Architecture 29 minutes
Setting up and Running Spark 55 minutes
Spark Core Programming Model 41 minutes
Hands-on Spark 39 minutes
Miscellaneous Spark Components 20 minutes
Summary - Spark 7 minutes

5 readings Total 85 minutes

Spark Architecture 15 minutes
Reading References 10 minutes
Setting up and Running Spark 10 minutes
Reading References 10 minutes
Self-Reflective Reading: Hadoop vs Spark: Competing or Complementary? 40 minutes

4 assignments Total 105 minutes

Introduction to Spark: Overview and Architecture 15 minutes
Spark Setup and Core Programming Model 15 minutes
Hands-On Spark: Core Components and Summary 15 minutes
Spark 60 minutes

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Instructor

Karthik Shyamsunder

Johns Hopkins University

4 Courses 1,277 learners

Offered by

Johns Hopkins University

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