Riot Games

Customer Case Study

Riot Games’ goal is to be the world’s most player-focused gaming company in the world. Founded in 2006, and based in LA, Riot Games is best known for the League of Legends game. Over 100 million gamers play every month.

Industry

Media and Entertainment

Vertical Use Case

Improving gaming experience through:
• Network performance monitoring
• Combating in-game abusive language

Technical Use Case

• Data Ingest and ETL
• Streaming
• Machine Learning
• Deep Learning

The Challenges

Data and ecosystem was scaling, but analytic tools were unable to scale up.
Workflow was inefficient; and the data was separated from the tools they were using.
Iterative query development was hard to do.
Data pulls were slow.
Gameplay quality is highly dependent on network connection and in-game experience.

The Solution

Databricks allows Riot Games to improve the gaming experience of their players by providing scalable, fast analytics:

Able to detect network anomalies in network traffic to improve the experience for 67M+ monthly active players.
Leveraged machine learning and deep learning to curb abusive language dramatically, improving player engagement and satisfaction levels.
Accelerated data exploration efficiency more than 100% vs EMR.
Spark Streaming eliminates lag by providing performance alerts: 17,000 unique ISPs, 250,000 network stat messages per second.

We use Apache Spark™ and Databricks to augment our data analytics and data science programs. Specifically, we highlight how Spark has significantly decreased SQL query times when reading from our large HIVE data stores, providing a massively popular recommender system for our players, and using Spark streaming to monitor the internet and alert when players experience a poor network connection.

Colin Borys Data Scientist, Riot Games

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