In my ongoing mission to use SQL rather than the older style direct file IO (which the IBM-i world knows as DDS) – I’ve found lots of improvements and things that I really like about SQL in general. But, one of the confusions for me is remembering the SQL’style of describing its functions.

In DDS its a file in SQL its a TABLE

In DDS its Record and Field in SQL its a ROW and COLUMN

Thats the easy but but remember the various ways you can join two files together (called a JOIN LOGICAL FILE in DDS) but SQL offers us some rich and easy ways of joining everything, partial matches or even things that dont match. Here is a snippet of a great article from the coding horror website:

A Visual Explanation of SQL Joins

I thought Ligaya Turmelle’s post on SQL joins was a great primer for novice developers. Since SQL joins appear to be set-based, the use of Venn diagrams to explain them seems, at first blush, to be a natural fit. However, like the commenters to her post, I found that the Venn diagrams didn’t quite match the SQL join syntax reality in my testing.

I love the concept, though, so let’s see if we can make it work. Assume we have the following two tables. Table A is on the left, and Table B is on the right. We’ll populate them with four records each.

id name id name
-- ---- -- ----
1 Pirate 1 Rutabaga
2 Monkey 2 Pirate
3 Ninja 3 Darth Vader
4 Spaghetti 4 Ninja

Let’s join these tables by the name field in a few different ways and see if we can get a conceptual match to those nifty Venn diagrams.

SELECT * FROM TableA INNER JOIN TableB ON TableA.name = TableB.name id name id name -- ---- -- ---- 1 Pirate 2 Pirate 3 Ninja 4 Ninja Inner join produces only the set of records that match in both Table A and Table B.
SELECT * FROM TableA FULL OUTER JOIN TableB ON TableA.name = TableB.name id name id name -- ---- -- ---- 1 Pirate 2 Pirate 2 Monkey null null 3 Ninja 4 Ninja 4 Spaghetti null null null null 1 Rutabaga null null 3 Darth Vader Full outer join produces the set of all records in Table A and Table B, with matching records from both sides where available. If there is no match, the missing side will contain null.
SELECT * FROM TableA LEFT OUTER JOIN TableB ON TableA.name = TableB.name id name id name -- ---- -- ---- 1 Pirate 2 Pirate 2 Monkey null null 3 Ninja 4 Ninja 4 Spaghetti null null Left outer join produces a complete set of records from Table A, with the matching records (where available) in Table B. If there is no match, the right side will contain null.
SELECT * FROM TableA LEFT OUTER JOIN TableB ON TableA.name = TableB.name WHERE TableB.id IS null id name id name -- ---- -- ---- 2 Monkey null null 4 Spaghetti null null To produce the set of records only in Table A, but not in Table B, we perform the same left outer join, then exclude the records we don’t want from the right side via a where clause.
SELECT * FROM TableA FULL OUTER JOIN TableB ON TableA.name = TableB.name WHERE TableA.id IS null OR TableB.id IS null id name id name -- ---- -- ---- 2 Monkey null null 4 Spaghetti null null null null 1 Rutabaga null null 3 Darth Vader To produce the set of records unique to Table A and Table B, we perform the same full outer join, then exclude the records we don’t want from both sides via a where clause.

There’s also a cartesian product or cross join, which as far as I can tell, can’t be expressed as a Venn diagram:

SELECT * FROM TableA
CROSS JOIN TableB

This joins “everything to everything” resulting in 4 x 4 = 16 rows, far more than we had in the original sets. If you do the math, you can see why this is a very dangerous join to run against large tables.