Sqoop, Hive and Impala for Data Analysts (Formerly CCA 159)

Hands on Sqoop, Hive and Impala for Data Analysts

4.19 (714 reviews)

Udemy

platform

English

language

IT Certification

What you will learn

Overview of Big Data ecosystem such as Hadoop HDFS, YARN, Map Reduce, Sqoop, Hive, etc

Overview of HDFS Commands such as put or copyFromLocal, get or copyToLocal, cat, etc along with concepts such as block size, replication factor, etc

Managing Tables in Hive Metastore using DDL Commands

Load or Insert data into Hive Metastore Tables using commands such as LOAD and INSERT

Overview of Functions in Hive to manipulate strings, dates, etc

Writing Basic Hive QL Queries using WHERE, JOIN, GROUP BY, etc

Analytical or Windowing Functions in Hive

Overview of Impala and understanding similarities and differences between Hive and Impala

Getting Started with Sqoop by reviewing official documentation and also exploring commands such as Sqoop eval

Importing Data from RDBMS tables into HDFS using Sqoop Import

Importing Data from RDBMS tables into Hive tables using Sqoop Import

Exporting Data from Hive or HDFS to RDBMS tables using Sqoop Export

Incremental Imports using Sqoop Import into HDFS or Hive Tables

Charts

Students

Price

Rating & Reviews

Coupons Issued

Enrollment Distribution

Comidoc Review

Our Verdict

Udemy's 'Sqoop, Hive and Impala for Data Analysts' course boasts an extensive curriculum that targets essential tools for working with big data. Combined with a knowledgeable instructor, engaging teaching style, and real-world applications, this course is a solid choice for learners. However, challenges emerge through inconsistent quality of notes and organization while the fast-paced instruction accompanied by a strong accent may deter some students from fully embracing the learning experience.

What We Liked

Comprehensive coverage of Big Data ecosystem tools like Sqoop, Hive, and Impala, with real-world applications demonstrated.
Instructor's teaching style is engaging, easy to follow, and includes practical examples and hands-on exercises.
Covers both basics and advanced topics such as data modeling and performance optimization.
Provides a solid understanding of HDFS commands and concepts, block size, replication factor, etc.

Potential Drawbacks

Notes contain minimal information and could benefit from more detailed examples or solutions to exercises.
Some students find the instructor's accent difficult to understand; pace of instruction is considered fast in general.
Lacks a well-organized structure, with some topics repetitive and others not comprehensively covered.