![]() ![]() sequence_option is an option supported by ALTER SEQUENCE such as INCREMENT BY. These forms alter the sequence that underlies an existing identity column. If DROP IDENTITY IF EXISTS is specified and the column is not an identity column, no error is thrown. Like SET DEFAULT, these forms only affect the behavior of subsequent INSERT and UPDATE commands they do not cause rows already in the table to change. These forms change whether a column is an identity column or change the generation attribute of an existing identity column. RENAME CONSTRAINT constraint_name TO new_constraint_nameĪLTER TABLE ALL IN TABLESPACE name ]ĪTTACH PARTITION partition_name AS IDENTITY However, there are some really interesting behaviors.ALTER TABLE name In fact, most behaviors I’m used to, I can see: DISTINCT, WITH, UNION, ORDER BY and more. I can specify columns from the defined tables and use the alias of those tables to make the code clearer (and shorter). Finally, you decide what is being returned, SELECT.īy the nature of how a query works, all the examples I’ve listed so far show the basics of the SELECT operation. Then you apply filters to that data: WHERE. In a simple query, you simply define where the data is originating: FROM. I chose the order, FROM, WHERE, SELECT, because in PostgreSQL, as in SQL Server, this is the actual order of operations. These all perform the same logical functions. The standard join operators are the same: INNER, LEFT/ RIGHT OUTER, CROSS, FULL OUTER. The first big difference is in the use of JOIN operations. So much of the FROM clause in PGSQL is the same as T-SQL. ![]() Aliasing, everything, pretty much the way it works in T-SQL because that’s the way it works in the ANSI SQL Standard, to which PostgreSQL complies very closely. List table names, and/or, define a table through a sub- SELECT. While it can help to visualize this way, it certainly is not implemented this way. Yet, I know (reading ahead in the docs) that execution plans in PostgreSQL are similar to SQL Server and this description leads us down a path: virtual table, that’s not accurate, depending on the whole query, structures involved and statistics. It sounds like the FROM clause is a temporary table or something. The result of the FROM list is an intermediate virtual table that can then be subject to transformations by the WHERE, GROUP BY, and HAVING clauses and is finally the result of the overall table expression. Take this further explanation of what defines a table expression: While I wouldn’t myself define it this way, I find it to be interestingly more accurate than simply saying “table.” However, since you can make a query on a table expression, it is more than simply saying “tables.” Not all the definitions are useful though. Trivial table expressions simply refer to a table on disk, a so-called base table, but more complex expressions can be used to modify or combine base tables in various ways. I actually love how the PostgreSQL document defines what you’re doing in the FROM clause: After executing that script, execute the Sample The rest of the code in this article is in the 10_Select folder. The objects and database you will need can be created/reset using the CreateDatabase.sql script, then adding sample data using the SampleData.sql script. If you wish to execute the code or look at the data structures, the code is in my ScaryDBA/LearningPostgreSQL repository here. In the sample database I’ve created as a part of this ongoing series, I created a couple of schemas and organized my tables within them. And hoo boy, there’s some fun stuff in there. This won’t be a fundamental how-to on querying PostgreSQL, but instead an exploration of the gotchas you’re likely to experience coming in with existing knowledge of how you think these things should work. For this entry in the series, I’m going to focus on the core behaviors of SELECT, FROM and WHERE with an emphasis on what’s different from SQL Server. Instead, for this series, I’m just going to assume I may have more than one article on querying PostgreSQL. Further, since so much of this functionality is effectively identical to where I’m more comfortable, SQL Server, I’m not turning this into a PostgreSQL 101 on the SELECT statement. I honestly can’t do it justice in a single article. ![]() From standard SELECT… FROM… WHERE to windowing functions and recursive queries, PostgreSQL has it all. Further, PostgreSQL has an incredibly rich, wide, and varied set of mechanisms for retrieving data. Working with data in PostgreSQL is no exception. Writing queries to retrieve the data from a database is probably the single most common task when it comes to working with data. ![]()
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