CTEs (common table expressions) are wonderful, they make SQL grokkable and maintainable. But, before some dev goes crazy refactoring all of the SQL in their codebase into maintainable CTEs: always benchmark. CTEs can cause your query planner to optimize incorrectly. In some cases, CTEs can force the query optimizer to choose a plan it otherwise is not choosing and be more performant - perhaps up to a certain point. (That point being the size of the tables in question/index/etc.)
I had some code from a vendor that was hanging in SQL Server and I looked at the code and they had composed everything together using smaller CTE queries and it took forever to run. They had taken various complex criteria and executed one query for each and then combined the results -- I ended up spending a day refactoring the whole thing to single SELECT with all the criteria and it ran instantly.
This was for a nightly data importer and it was filled with queries like that -- I only fixed the one giving us issues -- but I bet I could have reduced the total runtime by 90%.
Indeed, SQL is tricky like that because there are plenty of performance consequences for a language that is meant to be declarative and optimized by a query planner.
Unless you have realistic data in the test database the performance behavior of a query can be unpredictable.
In SQL you're describing the result that you want -- you aren't (and shouldn't be) saying how to achieve that result. The engine goes off and (hopefully) finds the optimal way to create the result you are describing. When you break queries down too far, the engine has more trouble finding the optimal path.
SQL Server can "see through" views and CTEs optimize them combined with a query but depending on the calculations it might have to generate and process intermediate data that it doesn't need. In my case above, the engine was reprocessing the same data set over and over, generating duplicate rows, and combining everything removing the duplicates.
My query was significantly simpler but also, in a way, harder to follow. It wasn't as clear what the intent was. Where they had nice named CTE subqueries, I had to use comments.
I agree but all systems have limitations and SQL engines get better at the job every year.
The result of the query is say declaration X. In this case, imagine you can construct a query to formulate X with out a CTE. The database goes off and computes X from the data.
But if you start adding CTE's for say readability or because you're building up the query piece by piece and testing it in stages. You might be adding additional declarations A, B, and C and combining them to ultimately get X. In theory, the database engine should be able to see that you're still trying to get X and perform the query that same way as if it was a single query without a CTE. And, in some cases, it can actually do that.
But if A, B, and C are complicated enough then it's just unable to determine that it all equals X in the end. This is a fairly understandable limitation of the engine -- SQL can get pretty complicated. It's also making the assumption that all these CTE's are actually needed to compute the result. It took me a whole day to convert a CTE based query into a non-CTE based query and get all the same results in the same way.
Yes, the more complicated it is, the more likely the optimizer is to get confused... but also the greater the likelihood of bugs and the greater the benefit of something that makes your query easier to read.
I have strongly encouraged reckless use of CTEs throughout our product. We use in-memory instances of SQLite to evaluate any queries which would leverage CTEs. These datasets are usually small enough to reside within L1 (and certainly within L2).
“By the time it doesn’t fit in [L2/RAM] you will have a different order of magnitude of engineering team” is one of my favorite adages. Arguably a bit less true with the venture model of growth-at-all-costs showing some cracks, but still very much a good mental model!
In my experience a huge portion of the userbase who loves CTEs are analysts or devs running queries on decently large datasets, and they mostly like them because of readability and don't understand performance possibilities.
I appreciate that tools like dbt allow materialization options as both CTEs and views/tables/etc because being able to pivot between them is super nice.
Note that there are basically no special performance considerations when using CTEs in recent versions of postgres… unless your CTE is recursive or does some weird side-effect (which is unlikely).
This is incorrect. If you use a CTE more than once in a query, Postgres will materialize that data into a temp table that has no indexes. If that CTE gets joined a lot, it will incur many O(N) searched through unindexed data.
I've seen cases where a few GBs of product data gets pulled into a CTE this way. Queries take 10s to complete from processing GBs of unindexed data
Wow, this is amazing. Just the other day I was staring at a query with multiple CTEs that took 20+ seconds to run. Ended up adding an additional WHERE clause on an indexed column to the slowest CTE, which took the execution time down to 100s of ms.
Just tried the original query, but with explicitly not materialized CTEs and the runtime was basically as fast as the manually pre-filtered solution.
No, but this would make an incredible Postgres extension.
(I’d also love one that lets Postgres use a covering index for primary storage. This can reduce data size and load less data off disk due to locality. MySQL has this by default and SQLite has it via WITHOUT ROWID tables.)
Strange take you have there in assuming they don't understand performance possibilities. Many of the problems that analysts and such work on aren't performance bound because focusing on the performance would be a net waste of time. "Don't optimize early" and all that. For example, I had to share SQL recently where the absolute most important thing, beyond all else was to make it readable. CTEs fit the role.
Postgres has materialization options for CTEs. You can ask it to rewrite the CTE as a join via "WITH foobar AS NOT MATERIALIZED (...)". Alternatively you can force materialization by writing "WITH foobar AS MATERIALIZED (...)"
Based on other comments, this has been done for psql, or at least to some extent. So that's the other thing... pre-emptively writing code in a non-intuitive way for performance reasons often leads to practices sticking around long past the rationale for them even being true.
I wrote some very elegant, readable SQL to perform a complex query. It was dog slow.
I handed it to a DBA, they ripped out the CTEs and replaced them all with temp tables. The query was an unreadable mess at the end, but boy was it orders of magnitude faster.
Did they do something else other than just popping CTE queries into temp tables? In my experience, _just_ doing that doesn't affect readability much at all.
