<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Photon Engine on AI VOID</title><link>https://ai-blog.noorshomelab.dev/tags/photon-engine/</link><description>Recent content in Photon Engine on AI VOID</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 19 Dec 2025 00:00:00 +0000</lastBuildDate><atom:link href="https://ai-blog.noorshomelab.dev/tags/photon-engine/index.xml" rel="self" type="application/rss+xml"/><item><title>Performance Optimization: Queries and Clusters</title><link>https://ai-blog.noorshomelab.dev/databricks-mastery-2025/performance-optimization/</link><pubDate>Fri, 19 Dec 2025 00:00:00 +0000</pubDate><guid>https://ai-blog.noorshomelab.dev/databricks-mastery-2025/performance-optimization/</guid><description>&lt;h2 id="introduction-turbocharging-your-databricks-workloads"&gt;Introduction: Turbocharging Your Databricks Workloads&lt;/h2&gt;
&lt;p&gt;Welcome to Chapter 10, where we shift our focus from just &lt;em&gt;making things work&lt;/em&gt; to &lt;em&gt;making things fly&lt;/em&gt;! In the world of big data, efficiency isn&amp;rsquo;t just a nice-to-have; it&amp;rsquo;s crucial for managing costs, getting faster insights, and handling ever-growing datasets. This chapter is all about unlocking the full potential of your Databricks environment by optimizing both your data queries and the underlying compute clusters.&lt;/p&gt;</description></item></channel></rss>