
Liquid Clustering in Databricks: Keys, Speed & vs Partitioning
Most slow Databricks queries are not a compute problem. They are a data layout problem. When a Delta table scatters the rows you filter on across thousands of files, every query reads far more data than it needs, and adding a bigger cluster only rents more horsepower to read the same wasted bytes. Liquid clustering in Databricks fixes the layout

