Worried you’ll miss us?
Subscribe to get our articles and updates in your inbox.
Given this table, which row will the following query return?
SELECT * FROM users LIMIT 1;
First one? Last one? Dig in your RDBMS documentation long enough and you’ll find a statement like this…
“If ORDER BY is not given, the rows are returned in whatever order the system finds fastest to produce”
In reality the returned results are usually insert order but that is not guaranteed. The frequency is high enough to fool you during development but that lack of guarantee can cause real bugs when you ship to production.
Core SQL Server architect, Conor Cunningham equates depending on query order without an
ORDER BY clause to driving a car without a seatbelt. He even goes on to provide a reproducible example that spits out results in an “unexpected” order using a
SELECT statement without the corresponding
How Can We Find Order Dependent Queries?
The tricky part in a fairly complex application is ensuring you’ve done just that. You may generate thousands of unique queries and some of them are order dependent. What happens when one inevitably slips through without
Obviously users will encounter rows of data moving around seemingly at random. Depending on your application this could range from annoying to catastrophic. (Imagine showing data points in a jumbled order for a stock ticker)
The more sinister bug is when you limit your query to a single row and you’re oh-so-sure that
WHERE clause narrows the results down to a single row. Oh wait, turns out you were wrong but you’ll never be the wiser until the query optimizer decides maybe those other rows want a turn in the spotlight.
Also just because you have an
ORDER BY statement doesn’t mean you won’t have ties. You might order by that datetime column but what happens when two rows get inserted within the same second? For those rows with ties you’re back to square one, leaving which row appears first up to the query optimizer.
To help surface these issues during development I propose exaggerating the randomness of results in queries missing an
ORDER BY. If you don’t care about order then let’s lose the pretense of getting results in insert order usually. Instead you get a randomized order. Doing this on development/testing databases will help ensure that if ambiguous sort bugs exist, developers are likely to see them.
If you squint, you’ll see this concept has parallels to Chaos Engineering. We want to intentionally wreck weak assumptions in a controlled manner.
I accomplished this with the following hack for PostgreSQL. It will do a one time scramble of data order physically.
This script iterates through all the tables and adds a column
_rand which we’ll use to create an index. Clustering a table on that index causes the behavior we’re looking for.
SELECT id, email FROM users;
After running this against your development database you can poke around and look for buggy behavior. The catch though is that newly inserted data won’t be affected.
INSERT INTO users (email) VALUES ('email@example.com')
INSERT INTO users (email) VALUES ('firstname.lastname@example.org')
INSERT INTO users (email) VALUES ('email@example.com')
To fix this we need to run
CLUSTER after new data has been inserted. We can run it against a specific table with
CLUSTER users or against all tables with
So periodically you must
CLUSTER. One option is hooking into your ORM or testing framework hooks to run
CLUSTER after new rows are inserted. Here’s how to accomplish this in Rails:
By adding the callback combined with the Postgres snippet in a migration I was able to run against test suites here at Simple Thread and surface real issues. This method still feels a bit hacky so if you have a better way to accomplish this I’d love to hear it!
Rico Mariani says we should architect our system in a way that creates a pit of success. When it comes to writing long queries in a complex system it seems all too easy to miss an
ORDER BY when you need it. The least we can do is ensure rare behavior bubbles its way to the surface for developers during testing to see on a regular basis.
Loved the article? Hated it? Didn’t even read it?
We’d love to hear from you.