Book Image

PostgreSQL 11 Administration Cookbook

By : Simon Riggs, Gianni Ciolli, Sudheer Kumar Meesala
Book Image

PostgreSQL 11 Administration Cookbook

By: Simon Riggs, Gianni Ciolli, Sudheer Kumar Meesala

Overview of this book

PostgreSQL is a powerful, open source database management system with an enviable reputation for high performance and stability. With many new features in its arsenal, PostgreSQL 11 allows you to scale up your PostgreSQL infrastructure. This book takes a step-by-step, recipe-based approach to effective PostgreSQL administration. The book will introduce you to new features such as logical replication, native table partitioning, additional query parallelism, and much more to help you to understand and control, crash recovery and plan backups. You will learn how to tackle a variety of problems and pain points for any database administrator such as creating tables, managing views, improving performance, and securing your database. As you make steady progress, the book will draw attention to important topics such as monitoring roles, backup, and recovery of your PostgreSQL 11 database to help you understand roles and produce a summary of log files, ensuring high availability, concurrency, and replication. By the end of this book, you will have the necessary knowledge to manage your PostgreSQL 11 database efficiently.
Table of Contents (19 chapters)
Title Page
Copyright and Credits
About Packt

Identifying and removing duplicates

Relational databases work on the idea that items of data can be uniquely identified. However hard we try, there will always be bad data arriving from somewhere. This recipe shows you how to diagnose that and clean up the mess.

Getting ready

Let's start by looking at our example table, cust. It has a duplicate value in customerid:

postgres=# SELECT * FROM cust;
 customerid | firstname | lastname | age
          1 | Philip    | Marlowe  |  38
          2 | Richard   | Hannay   |  42
          3 | Holly     | Martins  |  25
          4 | Harry     | Palmer   |  36
          4 | Mark      | Hall     |  47
(5 rows)

Before you delete duplicate data, remember that sometimes it isn't the data that is wrong: it is your understanding of it. In those cases, it may be that you haven't properly normalized your database model, and that you need to include additional tables to account for the shape of the data. You might also find...