In Part 1, we covered why multi-table transactions matter. Now let's build one. We'll create the tables from the claim wrap-up scenario, load sample P&C insurance data, and walk through what happens when the wrap-up succeeds, when it fails, and when...
Part 3 of 3: Databricks Streaming ArchitectureBy the end of Part 1 & Part 2, we knew what the real answer was. We just hadn’t committed to it yet.Not because it wouldn’t work. We tested it. We documented it. The code was ready. The answer was one clu...
Hi all.If you've ever manually promoted resources from dev to prod on Databricks — copying notebooks, updating configs, hoping nothing breaks — this post is for you.I've been building a CI/CD setup for a Speech-to-Text pipeline on Databricks, and I w...
Hi, Great question! Databricks Asset Bundles (DABs) are the recommended approach for CI/CD on Databricks. Here is a comprehensive walkthrough. WHAT ARE DATABRICKS ASSET BUNDLES? DABs let you define your Databricks resources (jobs, pipelines, dashboar...
Delta Lake 4.0 is the next major open-source release aligned with Spark 4.x, adding first-class Variant for semi-structured data, safer Type Widening, improved DROP FEATURE, better transaction log handling, and a new multi-engine story via Delta Kern...
Problem StatementIn one of my recent projects, I faced a significant challenge: Writing a huge dataset of 11,582,763,212 rows and 2,068 columns to a Databricks managed Delta table.The initial write operation took 22.4 hours using the following setup:...
Hey @Louis_Frolio ,Thank you for the thoughtful feedback and great suggestions!A few clarifications:AQE is already enabled in my setup, and it definitely helped reduce shuffle overhead during the write.Regarding Column Pruning, in this case, the fina...
