[p2t2p]

I think about my self as quite SQL-savvy person, I used to optimize quite complex queries and is able to read plans for Oracle, Postgres and MySQL.

And yet, I've got not idea why would anybody need right join.

Have you guys ever had a case when you'd need a right join? I've been to the field for 15 years and yet to see people using right join in the wild.

Like the last example in this link - why would you do that? Most probably your business logic focuses on dogs, something like "find dogs with no owner" or something, In this case it is much more readable and straight forward to go with left join or even with sub-select where you'd have something like 'select * from dogs where owner_id not in (select id from owners)'.

Have you used right joins and if you have can you explain the use case?

[saulrh]

I think that I've almost used a right join before, but not for anything like a legitimate use case. I was attempting to out-think an in-house DB's optimizer that was doing a hash join in the wrong direction. There may have been some rough spots in some of that DB's specialized SQL extensions that played into the problem. I think I ended up using a full outer join plastered with optimizer hints. Like you said, if you're using a right join, probably not unlikely that you're doing something wrong.

[notafraudster]

I use right_join never in SQL, but often in offline data analysis (e.g. in R). Modern R has an operator called the "pipe" (%>%) which allows left to right evaluation of functions, and so it's fairly common to write code that basically reads like, say, chained method invocations in JavaScript (i.e. object.method1().method2().method3()). The operator works so that the invoking object is automatically passed as the first argument of the function, so func(x, y) is the same as x %>% func(y). You might see where this is going.

Think of left join as a join from x to y, and a right join as a join from y to x, where x is the data we keep all of and y is the data we keep only when there's a match.

Then, in R, I often use right joins when my "y" data requires preprocessing, resulting in lines of code that are like: (y %>% preprocess1() %>% preprocess2() %>% right_join(x)). I could of course write this as "y_preprocessed = y %>% preprocess1() %>% ...; x %>% left_join(y_preprocessed)" but I think the former is actually a little syntactically clearer.

[wodenokoto]

I tend to do like

    x %>% left_join(y %>% preprocess1() %>% preprocess2())

But yes, my understanding is that right and left joins are the exact same function, just with the order of input switched.

[tempguy9999]

A right join is a left join flipped so you never formally need one, like you said.

I believe I used one once, exactly once ever, about a year ago. That was because I was fighting an almighty 5 page CTE charlie fox of a query and had to turn an inner join into an outer join to get data otherwise excluded. It just so happened the data missing was on the right so I made it a right join. Had it not been so awful I'd have flipped it into a left join, my usual style, but I couldn't bear rewriting it.

(background: it was complex but could not be broken down or it lost efficiency. Part of the length was long explicit lists of fields 'select a, b, c, d, ...' which were unavoidable, but it was just plain complex too. The inner join suddenly became an outer join because we found data missing - the DB was a commercial one written by some clueless people with little consistency and absolutely no documentation. I hope I never see that again).

[gav]

I struggle to think of time I used a right join in the 20-odd years I've used SQL.

The example shows a case where you'd want foreign keys to enforce referential integrity, though FKs aren't fashionable these days. You shouldn't be able to have an entry for owner_id 8 in the Dogs table without a corresponding Owner.

[paulddraper]

A right join is simply a commuted left join, so barring some bizzare DMBS optimizer oddity, there's no nothing you couldn't trivially replace with left join or vice versa.

I just checked some code, saw 357 left joins and 1 right join.

    SELECT p.password, u.id
    FROM password p
      RIGHT JOIN "user" u ON p.user_id = u.id

[replyguy912]

Agree on struggling for real scenarios where you'd use a right-join, but your example with

select * from dogs where owner_id not in (select id from owners)

You wouldn't actually recommend something like this would you? The query plans for sub-selects vs. left-joins are very different, with lots of implementations having limits on the "in" clause.

Kind of funny that the way you'd feel if you saw a right join is similar to how I feel about sub-selects!

[p2t2p]

I would say "it depends". I have seen when replacing bunch of joins with sub selects improved performance. I have seen otherwise as well. It all depends on the nature of your data, RDBMS you're using and statistics it has accumulated.

I haven't seen anybody hitting "in" clause limits in query like mine but we did hit such a limit once when we were passing a hardcoded list of IDS from client side. Something like "where blah in (id1, id2, id3.... idn)". I remember that one failing on MS SQL.

[onlyrealcuzzo]

I'm by no means a SQL expert. But I just used a right join a few days ago (for the first time ever).

I thought it made sense to start the SELECT from one table. From there, I could left join to another table, and from that table I could only right join to get what I needed.

I'd love to know, is there another way around that? I know I could have started from a different table, but I think the query makes more sense starting from where I did.

[lenzm]

Any right join could be written as a left join. What you describe is the use case for a right join - it makes the query more readable.