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
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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.
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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
2 readings•Total 15 minutes
- Course Overview•5 minutes
- Instructor Biography: Prof. Karthik Shyamsunder•10 minutes
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
- Data Analysis using Hive •60 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
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
- Data Analysis using Pig•60 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
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
- Hadoop NOSQL Database HBase•60 minutes
- Introduction to HBase: NoSQL Basics, Architecture, and Setup•15 minutes
- HBase Fundamentals: Data Model, Shell, CRUD Operations, and Summary•15 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
- Spark•60 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
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