What SQL Joins and Quilting Have in Common?

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When I think of joins, I think of quilts.


Let’s be real—JOINS are not always simple. Especially when your tables don’t have a primary key. Or when the data model is not documented anywhere and you’re just trying to make sense of it all.

Picture this:

You’re at your desk, staring at your screen (remember to blink).

You’re writing a query to count the number of employees per department. 

It should be simple

Two tables: employees and departments. A quick JOIN, a simple GROUP BY, and done. Right?

You hit "Execute"

Boom—5,732 rows.

That can’t be right. Your company only has 200 employees.

You frown. You try DISTINCT. Still too many rows. You tweak the join condition, change the table order, throw in a LIMIT just to see something normal—but nothing works. It’s still chaos.

Welcome to the world of SQL joins—where your logic seems sound, but your results make no sense.


Why This Happens

Joins are powerful—but they’re picky. If you join on the wrong column, or if your keys aren’t unique, your result set can explode. Literally.

And the worst part? SQL won’t stop you. 

There’s no red warning box. 

Just a mountain of rows that look fine... until someone asks:

Why does your dashboard show five thousand employees and three CFOs?


Let’s Talk Quilts

If this is your first time struggling with joins, here’s a helpful way to think about it:

Tables are like fabric squares. Joins are the stitches.

When each square lines up—same size, same shape—you can sew them together into a beautiful quilt.

But if your patches don’t match, things get messy fast! 

You get duplicate rows. Gaps. Misaligned columns. Your result isn’t a clean pattern—it’s a tangled mess.


How to Know You’ve Sewn It Wrong

Joins don’t always fail loudly. Sometimes they fail quietly. But here are a few signs that something’s gone wrong:

  • Your row count is way higher (or lower) than expected

  • You're using DISTINCT like duct tape

  • Your results have NULLs where you expected data

  • You’re not sure which columns are unique—or if they’re even keys at all

If that sounds familiar, pause. Don’t just rewrite the query. Look at the data.


What Helped Me Learn

I didn’t really “get” joins until I stopped focusing just on the syntax and started thinking about relationships and intent.

  • What kind of relationship is this—one-to-many, many-to-many?

  • Are my keys actually unique, or am I stitching duplicate fabric patches together?

  • Am I checking the row count after the join? (If not, you should.)

  • Do I understand how NULLs will behave when I use a LEFT JOIN vs an INNER JOIN?

Once I started treating joins like design problems—where clarity and structure matter—it got a lot easier.




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