Optimizers: The Low-Key MVP

TL;DR: The query optimizer is an important part of any analytical database system as it provides considerable performance improvements compared to hand-optimized queries, even as the state of your data changes.

Optimizers don't often give "main character" energy in the database community. Databases are usually popular because of their performance, ease of integration, or reliability. As someone who mostly works on the optimizer in DuckDB, I have been wanting to write a blog post about how important optimizers are and why they merit more recognition. In this blog post we will analyze queries that fall into one of three categories: unoptimized, hand-optimized, and optimized by the DuckDB query optimizer. I will also explain why built-in optimizers are almost always better than any hand optimizations. Hopefully, by the end of this blog post, you will agree that optimizers play a silent, but vital role when using a database. Let's first start by understanding where in the execution pipeline query optimization happens.

Before any data is read from the database, the given SQL text must be parsed and validated. If this process finishes successfully, a tree-based query plan is created. The query plan produced by the parser is naïve, and can be extremely inefficient depending on the query. This is where the optimizer comes in, the inefficient query plan is passed to the optimizer for modification and, you guessed it, optimization. The optimizer is made up of many optimization rules. Each rule has the ability to reorder, insert, and delete query operations to create a slightly more efficient query plan that is also logically equivalent. Once all the optimization rules are applied, the optimized plan can be much more efficient than the plan produced by the parser.

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