Apr 23, 2021

ClickHouse tips #6: Filtering data in subqueries to avoid joins

Sometimes you can replace joins on ClickHouse using where clauses, having the same performance as with Join engines. Learn how here.
Xoel López
Founder at TheirStack

Imagine that you want to join two tables, and filter by a column that comes from the table in the right side of the join. On ClickHouse the query a bit different than what you’d do in other databases like Postgres, and it will result in a big performance improvement.

Let’s say one of the tables is this events table, with 100M rows:

And the other table is this products one, with ~2M rows

If you will always filter the result after making the join as in the query above, you don’t need to make a join at all. ClickHouse saves data column-by-column, so filtering by the values in a column is a very fast operation. If you rewrite the query as follows, it would be just as fast. And you wouldn’t have create a Join table for it:

Tinybird lets you create real-time API endpoints on in minutes instead of hours of days, powered by ClickHouse. We’re still in private beta, but if you want to try out product, create an account here.

Do you like this post?

Related posts

Why we just released a huge upgrade to our VS Code Extension
More Data, More Apps: Improving data ingestion in Tinybird
ClickHouse tips #3: the transform function
ClickHouse JOINs... 100x faster
Simplifying event sourcing with scheduled data snapshots in Tinybird
Adding JOIN support for parallel replicas on ClickHouse
Tinybird Changelog: Faster CSV Imports
The 5 rules for writing faster SQL queries
Real-time analytics API at scale with billions of rows
Using Bloom filter indexes for real-time text search in ClickHouse

Build fast data products, faster.

Try Tinybird and bring your data sources together and enable engineers to build with data in minutes. No credit card required, free to get started.
Need more? Contact sales for Enterprise support.