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Mastering Tableau 2019.1 - Second Edition

You're reading from  Mastering Tableau 2019.1 - Second Edition

Product type Book
Published in Feb 2019
Publisher
ISBN-13 9781789533880
Pages 558 pages
Edition 2nd Edition
Languages
Authors (2):
Marleen Meier Marleen Meier
Profile icon Marleen Meier
David Baldwin David Baldwin
Profile icon David Baldwin
View More author details
Toc

Table of Contents (20) Chapters close

Preface 1. Section 1: Tableau Concepts, Basics
2. Getting Up to Speed - A Review of the Basics 3. All About Data - Getting Your Data Ready 4. Tableau Prep 5. All About Data - Joins, Blends, and Data Structures 6. All About Data - Data Densification, Cubes, and Big Data 7. Table Calculations 8. Level of Detail Calculations 9. Section 2: Advanced Calculations, Mapping, Visualizations
10. Beyond the Basic Chart Types 11. Mapping 12. Tableau for Presentations 13. Visualization Best Practices and Dashboard Design 14. Advanced Analytics 15. Improving Performance 16. Section 3: Connecting Tableau to R, Python, and Matlab
17. Interacting with Tableau Server 18. Programming Tool Integration 19. Other Books You May Enjoy

Massively parallel processing

Big data may be semi-structured or unstructured. The massively parallel processing (MPP) architecture structures big data to enable easy querying for reporting and analytic purposes. MPP systems are sometimes referred to as shared nothing systems. This means that data is partitioned across many servers (otherwise known as nodes) and each server processes queries locally.

Let's explore MPP in detail using the following diagram as a point of reference:

Please see following, an explanation of the diagram:

  • The process begins by the Client issuing a query that is then passed to the Master Node.
  • The Master Node contains information, such as the data dictionary and session information, which it uses to generate an execution plan designed to retrieve the needed information from each underlying Node.
  • Parallel Execution represents the implementation...
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