Introduction to Apache Kudu — DESCRIPTION ONLY

Difficulty
Basic
Course Length
4 hours
Instructor
OnDemand Moderation
Price
Free

Description

Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription. 

About This Course

Cloudera's Introduction to Apache Kudu course teaches students the basics of Apache Kudu, a data storage system for the Hadoop platform that is optimized for both analytical queries and the ability to read and write individual records. The course covers common Kudu use cases and Kudu architecture. Students will learn how to create, manage, and query Kudu tables using Impala, and to develop Spark applications that use data stored in Kudu.

Course Length

This module includes 1 hour of video content. Hands-on exercises will take approximately 3 hours. Subscribers to the Cloudera OnDemand Full Library are given 100 hours of lab time to use across all courses.

Audience and Prerequisites

This material is intended for a broad audience of students involved with either software development or data analysis. This would include software developers, data engineers, DBAs, data scientists, and data analysts.

Students should know SQL. Familiarity with Impala is preferred but not required. Students should also know how to develop Apache Spark applications using either Python or Scala. Basic Linux experience is expected.

Note: Enrolling here will not give you access to the actual course. The course is available by purchasing the Full OnDemand Library subscription. 

Objectives

Through instructor-led discussion, as well as hands-on exercises, participants will learn topics including:

  • A high-level explanation of Kudu
  • How does it compares to other relevant storage systems and which use cases would be best implemented with Kudu
  • Learn about Kudu’s architecture as well as how to design tables that will store data for optimum performance.
  • Learn data management techniques on how to insert, update, or delete records from Kudu tables using Impala, as well as bulk loading methods
  • Finally, develop Apache Spark applications with Apache Kudu

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