How to identify which columns we need to consider for liquid clustering from a table of 200+ columns
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01-03-2025 06:09 AM
In Databricks, when working with a table that has a large number of columns (e.g., 200), it can be challenging to determine which columns are most important for liquid clustering.
Objective: The goal is to determine which columns to select based on their ability to meaningfully contribute to the clustering process, thereby improving query performance and insights.
