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Did you finish the Photon whitepaper and think, wait, what? I know I did; it’s my job to understand it, explain it, and then use it. If your role involves using Apache Spark™ on Databricks, then you need to know about Photon and where to use it. Join me, chief dummy, nay "supreme" dummy, as I break down this whitepaper into easy to understand explanations that don’t require a computer science degree. Together we will unravel mysteries such as: - Why is a Java Virtual Machine the current bottleneck for Spark enhancements? - What does vectorized even mean? And how was it done before? - Why is the relationship status between Spark and Photon "complicated?" In this session, we’ll start with the basics of Apache Spark, the details we pretend to know, and where those performance cracks are starting to show through. Only then will we start to look at Photon, how it’s different, where the clever design choices are and how you can make the most of this in your own workloads. I’ve spent over 50 hours going over the paper in excruciating detail; every reference, and in some instances, the references of the references so that you don’t have to. Talk by: Holly Smith Connect with us: Website: https://databricks.com Twitter: / databricks LinkedIn: / databricks Instagram: / databricksinc Facebook: / databricksinc