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In this article, learn to boost databricks' performance with six proven optimization strategies for udfs, aqe, delta lake, broadcasts, and photon acceleration. This project benchmarks databricks delta pipelines on transactional workloads of different scales (9m, 142m, 250m rows) 1) query optimizer,2) photon native execution engine and 3) caching up to 20x faster performance azure databricks was already blazing fast compared to apache spark, and now, the photon powered delta engine enables even faster performance for modern analytics and ai workloads on azure.

Ever wondered what's under the bonnet of your databricks clusters Optimize databricks photon for peak performance Today, let's dive into the battle of the titans

Delta engine and photon engine

Boost databricks performance and cut costs with techniques like aqe, photon engine, delta lake, and liquid clustering Photon engine accelerates the performance of delta lake for sql and data frame workloads through three components An improved query optimizer, a caching layer that sits between the execution layer and the cloud object storage, and a native vectorized execution engine that’s written in c++.

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