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PostgreSQL 11 Administration Cookbook

You're reading from   PostgreSQL 11 Administration Cookbook Over 175 recipes for database administrators to manage enterprise databases

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789537581
Length 600 pages
Edition 1st Edition
Languages
Concepts
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Authors (3):
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Gianni Ciolli Gianni Ciolli
Author Profile Icon Gianni Ciolli
Gianni Ciolli
Sudheer Kumar Meesala Sudheer Kumar Meesala
Author Profile Icon Sudheer Kumar Meesala
Sudheer Kumar Meesala
Simon Riggs Simon Riggs
Author Profile Icon Simon Riggs
Simon Riggs
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Toc

Table of Contents (14) Chapters Close

Preface 1. First Steps FREE CHAPTER 2. Exploring the Database 3. Configuration 4. Server Control 5. Tables and Data 6. Security 7. Database Administration 8. Monitoring and Diagnosis 9. Regular Maintenance 10. Performance and Concurrency 11. Backup and Recovery 12. Replication and Upgrades 13. Other Books You May Enjoy

Enforcing the same name and definition for columns


Sensibly designed databases have smooth, easy-to-understand definitions. This allows all users to understand the meaning of data in each table. It is an important way of removing data quality issues.

Getting ready

If you want to run the queries in this recipe as a test, then use the following examples. Alternatively, you can just check for problems in your own database:

CREATE SCHEMA s1;
CREATE SCHEMA s2;
CREATE TABLE s1.X(col1 smallint,col2 TEXT); 
CREATE TABLE s2.X(col1 integer,col3 NUMERIC);

How to do it...

First, we will show you how to identify columns that are defined in different ways in different tables, using a query against the catalog. We use an information_schema query, as follows:

SELECT
 table_schema
,table_name
,column_name
,data_type
  ||coalesce(' ' || text(character_maximum_length), '')
  ||coalesce(' ' || text(numeric_precision), '')
  ||coalesce(',' || text(numeric_scale), '')
  as data_type
FROM information_schema.columns...
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