Mojang Reduces Processing Time 66% With Azure Databricks
Mojang StudiosDelta Lake · Apache Spark · Azure Cognitive ServicesMojang Studios, developer of Minecraft (over 300 million copies sold), migrated from Azure HDInsight and Apache Hive to Databricks on Azure to unify data science workflows for player telemetry analysis and personalized content recommendations in the Minecraft Marketplace, plus social-media sentiment analysis via Azure Cognitive Services. This reduced data processing time by 66%, delivered 2.5x better AI content recommendations, and cut compute costs by 20%.
Overview
Mojang Studios, developer of Minecraft (over 300 million copies sold), migrated from Azure HDInsight and Apache Hive to Databricks on Azure to unify data science workflows for player telemetry analysis and personalized content recommendations in the Minecraft Marketplace, plus social-media sentiment analysis via Azure Cognitive Services. This reduced data processing time by 66%, delivered 2.5x better AI content recommendations, and cut compute costs by 20%.
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Inspect the highlighted sourceThe challenge
As the size of the Minecraft player base grew, the combination of virtual machines, Azure HDInsight and Apache Hive struggled to scale. Data scientists needed to download individual data sets from relational databases and coalesce them in virtual machines, collaboration was limited because they coded in different languages, and data scientists were forced to narrow their analysis to a single day of behavioral data for many analyses.
The solution
Mojang Studios' main machine learning and AI use cases revolve around optimizing recommendations in Minecraft Marketplace. The company uses algorithms that borrow best practices from several industries to deliver personalized recommendations for millions of players each day. A similarity search engine, powered by several Microsoft algorithms, lets players click on similar content that will enhance their gaming experience. Mojang Studios also integrated its Databricks environment with Azure Cognitive Services to use natural language processing to gauge what 130 million users are saying on social media.
Sources
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