Achieving Lakehouse Models with Spark 3.0
It’s very easy to be distracted by the latest and greatest approaches with technology, but sometimes there’s a reason old approaches stand the test of time. Star Schemas & Kimball is one of those things that isn’t going anywhere, but as we move towards the “Data Lakehouse” paradigm – how appropriate is this modelling technique, and how can we harness the Delta Engine & Spark 3.0 to maximise it’s performance? This session looks through the historical problems of attempting to build star-schemas in a lake and steps through a series of technical examples using features such as Delta file formats, Dynamic Partition Pruning and Adaptive Query Execution to tackle these problems. About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business. Read more here: https://databricks.com/product/unifie... See all the previous Summit sessions: Connect with us: Website: https://databricks.com Facebook: / databricksinc Twitter: / databricks LinkedIn: / databricks Instagram: / databricksinc Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-nam...

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