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.
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);
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...