SQL Access on Hadoop (Big SQL v4)

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SQL Access on Hadoop (Big SQL v4)

with Henry L. Quach

Analysts, developers, and administrators who are interested in using SQL access on their Hadoop data.

Time to complete:
4 hours

Available in:

Big SQL is another tool to work with your Hadoop data. Big SQL provides a common and familiar syntax for those that are already using SQL with their relational data to work with their big data. There is no learning curve here. Big SQL is about applying SQL to your existing data – there are no proprietary storage formats.

This course will help you understand the Big SQL architecture and show the different methods for working with Big SQL. The course will list and explain the Big SQL data types and show how to create Big SQL schemas and table. The course will also cover the different file formats supported by Big SQL such as parquet and ORC.

In the lab exercises, you will get a chance to learn how to connect to the Big SQL server and load in some sample data. Then you will see how easy it is to use Big SQL to work with the data.

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This course was tested and validated for v4 of the QSE Docker Image.

Please download the v4 Docker Image to complete the lab exercises.



Course Syllabus

After completing this course, you should be able to:

  • Describe the Big SQL architecture and understand the Big SQL terminologies
  • Understand and use different methods for working with Big SQL
  • List and explain the Big SQL data types
  • Create Big SQL schemas and tables
  • Understand and use the file formats supported by Big SQL
  • Create and use partitioned tables

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be taken as many times as you wish.
  • Labs can be performed on the Cloud, or using a 64-bit system. If using a 64-bit system, you can install the required software (Linux-only), or use the supplied Docker image.
  • More details are provided in the section "Labs setup".
  • Students passing the course (by passing the final exam) will have immediate access to printing their online certificate of achievement.
  • Your name in the certificate will appear exactly as entered in your profile in BigDataUniversity.com.
  • If you did not pass the course, you can take it again at any time.


Have taken the Hadoop Fundamentals – on Big Data University

Recommended skills prior to taking this course

  • Basic understanding of Apache Hadoop and Big Data.
  • Basic Linux Operating System knowledge

Grading Scheme

The minimum passing mark for the course is 60%, where the final test is worth 100% of the course mark. You have 3 attempts to take the test