[sql] What is the difference between LATERAL and a subquery in PostgreSQL?

Since Postgres came out with the ability to do LATERAL joins, I've been reading up on it, since I currently do complex data dumps for my team with lots of inefficient subqueries that make the overall query take four minutes or more.

I understand that LATERAL joins may be able to help me, but even after reading articles like this one from Heap Analytics, I still don't quite follow.

What is the use case for a LATERAL join? What is the difference between a LATERAL join and a subquery?

First, Lateral and Cross Apply is same thing. Therefore you may also read about Cross Apply. Since it was implemented in SQL Server for ages, you will find more information about it then Lateral.

Second, according to my understanding, there is nothing you can not do using subquery instead of using lateral. But:

Consider following query.

Select A.*
, (Select B.Column1 from B where B.Fk1 = A.PK and Limit 1)
, (Select B.Column2 from B where B.Fk1 = A.PK and Limit 1)
FROM A 

You can use lateral in this condition.

Select A.*
, x.Column1
, x.Column2
FROM A LEFT JOIN LATERAL (
  Select B.Column1,B.Column2,B.Fk1 from B  Limit 1
) x ON X.Fk1 = A.PK

In this query you can not use normal join, due to limit clause. Lateral or Cross Apply can be used when there is not simple join condition.

There are more usages for lateral or cross apply but this is most common one I found.

Database table

Having the following blog database table storing the blogs hosted by our platform:

And, we have two blogs currently hosted:

Getting our report without using the SQL LATERAL JOIN

We need to build a report that extracts the following data from the blog table:

• the blog id
• the blog age, in years
• the date for the next blog anniversary
• the number of days remaining until the next anniversary.

If you're using PostgreSQL, then you have to execute the following SQL query:

SELECT
  b.id as blog_id,
  extract(
    YEAR FROM age(now(), b.created_on)
  ) AS age_in_years,
  date(
    created_on + (
      extract(YEAR FROM age(now(), b.created_on)) + 1
    ) * interval '1 year'
  ) AS next_anniversary,
  date(
    created_on + (
      extract(YEAR FROM age(now(), b.created_on)) + 1
    ) * interval '1 year'
  ) - date(now()) AS days_to_next_anniversary
FROM blog b
ORDER BY blog_id

As you can see, the age_in_years has to be defined three times because you need it when calculating the next_anniversary and days_to_next_anniversary values.

And, that's exactly where LATERAL JOIN can help us.

Getting the report using the SQL LATERAL JOIN

The following relational database systems support the LATERAL JOIN syntax:

• Oracle since 12c
• PostgreSQL since 9.3
• MySQL since 8.0.14

SQL Server can emulate the LATERAL JOIN using CROSS APPLY and OUTER APPLY.

LATERAL JOIN allows us to reuse the age_in_years value and just pass it further when calculating the next_anniversary and days_to_next_anniversary values.

The previous query can be rewritten to use the LATERAL JOIN, as follows:

SELECT
  b.id as blog_id,
  age_in_years,
  date(
    created_on + (age_in_years + 1) * interval '1 year'
  ) AS next_anniversary,
  date(
    created_on + (age_in_years + 1) * interval '1 year'
  ) - date(now()) AS days_to_next_anniversary
FROM blog b
CROSS JOIN LATERAL (
  SELECT
    cast(
      extract(YEAR FROM age(now(), b.created_on)) AS int
    ) AS age_in_years
) AS t
ORDER BY blog_id

And, the age_in_years value can be calculated one and reused for the next_anniversary and days_to_next_anniversary computations:

Much better, right?

The age_in_years is calculated for every record of the blog table. So, it works like a correlated subquery, but the subquery records are joined with the primary table and, for this reason, we can reference the columns produced by the subquery.

One thing no one has pointed out is that you can use LATERAL queries to apply a user-defined function on every selected row.

For instance:

CREATE OR REPLACE FUNCTION delete_company(companyId varchar(255))
RETURNS void AS $$
    BEGIN
        DELETE FROM company_settings WHERE "company_id"=company_id;
        DELETE FROM users WHERE "company_id"=companyId;
        DELETE FROM companies WHERE id=companyId;
    END; 
$$ LANGUAGE plpgsql;

SELECT * FROM (
    SELECT id, name, created_at FROM companies WHERE created_at < '2018-01-01'
) c, LATERAL delete_company(c.id);

That's the only way I know how to do this sort of thing in PostgreSQL.

The difference between a non-lateral and a lateral join lies in whether you can look to the left hand table's row. For example:

select  *
from    table1 t1
cross join lateral
        (
        select  *
        from    t2
        where   t1.col1 = t2.col1 -- Only allowed because of lateral
        ) sub

This "outward looking" means that the subquery has to be evaluated more than once. After all, t1.col1 can assume many values.

By contrast, the subquery after a non-lateral join can be evaluated once:

select  *
from    table1 t1
cross join
        (
        select  *
        from    t2
        where   t2.col1 = 42 -- No reference to outer query
        ) sub

As is required without lateral, the inner query does not depend in any way on the outer query. A lateral query is an example of a correlated query, because of its relation with rows outside the query itself.