Order of precedence in SQL: WHERE vs HAVING

Senior Data Engineer • Contractor / Freelancer • GCP & AWS Certified
Search for a command to run...

Senior Data Engineer • Contractor / Freelancer • GCP & AWS Certified
No comments yet. Be the first to comment.
Short, practical posts on SQL and BigQuery — from core language features to advanced query patterns. A reference for data practitioners at every level.
Here's a useful Dataform concept: pre_operations and post_operations. As the name implies, these represent a set of actions that run before and after the main operation (table, view, or SQL operations

BigQuery has always been a SQL engine for tabular data. Object tables add an interesting twist to that. Instead of rows containing values, an object table gives you one row per file — pointing at da

Query your data lake with warehouse-grade security and performance — without moving a single file.

Ever run a heavy BigQuery SQL query, processed gigabytes of data — and then accidentally closed the tab or forgot to save the results? 😬 Don't re-run it. Your results are still there. BigQuery automa

You can use query parameters in BigQuery hashtag#SQL (now in the console as well!) — but how are they different from variables, and when should you use each? Both parameters and variables act as place

If you're just getting started with SQL, this post is for you. So, it's worth looking at the order of precedence of SQL operators.
One particular case is WHERE vs HAVING, especially if you bind the aggregated column to the same column alias as in the input table.
This can save you from some unexpected results 😁
In short:
- WHERE = filter before aggregation
- HAVING = filter after aggregation
In the example below, the 'quantity' filtered in the HAVING clause is no longer the same 'quantity' in the original table, rather the SUM of quantities per each country bucket.
In practice, I'd rename the aggregated column to something like total_quantity to make it more readable.
Depending what we need, we pick which approach we take, filtering out records before or after aggregation.
Found it useful? Subscribe to my Analytics newsletter at notjustsql.com.
Enjoyed this? Here are some related articles you might find useful: