Book Image

Teradata Cookbook

By : Abhinav Khandelwal, Viswanath Kasi, Rajsekhar Bhamidipati
Book Image

Teradata Cookbook

By: Abhinav Khandelwal, Viswanath Kasi, Rajsekhar Bhamidipati

Overview of this book

Teradata is an enterprise software company that develops and sells its eponymous relational database management system (RDBMS), which is considered to be a leading data warehousing solutions and provides data management solutions for analytics. This book will help you get all the practical information you need for the creation and implementation of your data warehousing solution using Teradata. The book begins with recipes on quickly setting up a development environment so you can work with different types of data structuring and manipulation function. You will tackle all problems related to efficient querying, stored procedure searching, and navigation techniques. Additionally, you’ll master various administrative tasks such as user and security management, workload management, high availability, performance tuning, and monitoring. This book is designed to take you through the best practices of performing the real daily tasks of a Teradata DBA, and will help you tackle any problem you might encounter in the process.
Table of Contents (19 chapters)
Title Page
Dedication
Packt Upsell
Contributors
Preface
Index

Creating a partitioned primary index to improve performance


A PPI is a type of index that enables users to set up databases that provide performance benefits from a data locality, while retaining the benefits of scalability inherent in the hash architecture of the Teradata database. This is achieved by hashing rows to different virtual AMPs, as is done with a normal PI, but also by creating local partitions within each virtual AMP.

Normal PI access remains unchanged, but in the case of a range query for example, each virtual AMP is able to immediately focus its search on specific partitions within its workspace.

If the PPI column is specified in the join condition, the system knows the range of values in a query and it scans only the portions of the table that correspond to those dates. Table can be or have:

Non-partitioned primary index: A traditional non-partitioned PI allows the data rows of a table to be:

  • Hash partitioned (that is, distributed) to the AMPs by the hash value of the primary...