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How Big Fish Games Developed Real-Time Analytics Using Kafka Streams and Elasticsearch

Big Fish Games a leading producer and distributor of casual and mid-core game hase distributed more than 2.5 billion games to customers in 150 countries, representing over 450 unique mobile games and over 3,500 unique PC games. Big Fish Games
uses Apache Kafka to process data generated across game play. Recently, they introduced real-time analytics of game data using Kafka Streams integrated with Elasticsearch. This allows to monitor the results of live operations and to make changes to these events after they have gone live. 

This presentation gives a detailed explanation of how Big Fish Games used Kafka Streams to transform raw data into Elasticsearch documents, and how the application was scaled to over a million daily active users. It will also touch on the limitations discovered with Kafka Connect integration with Elasticsearch and how to use Elasticsearch bulk processing with Kafka Streams. 

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You Must Construct Additional Pipelines: Pub-Sub on Kafka at Blizzard

Blizzard’s an American video game developer and publisher based in Irvine, California global data platform has become a driving force in both business and operational analytics. As more internal customers onboard with the system, there is increasing demand for custom applications to access this data in near real time. In order to avoid many independent teams with varying levels of Kafka expertise all accessing the firehose from their critical production Kafkas, Blizzard developed their own pub-sub system on top of Kafka to provide specific datasets to customers on their own cloud deployed Kafka clusters.

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How to keep our flock happy with Apache Flink on AWS

This is a detailed talk about Rovio's analytics pipeline and its use cases. Learn a brief history lesson on how a purely batch based system has evolved into hybrid streaming and batch system, and share how Rovio operate their production pipeline in AWS.

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Using Apache Spark to Predict Installer Retention from Messy Clickstream Data

Learn how Zynga utilizes the power of PySpark to  generate thousands of features without the need to manually interpret the events of each game.

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Hive to Spark—Journey and Lessons Learned

Learn how Unity, one of the largest game development platforms migrated to Spark from Hive. Spark is handy in processing and analyzing billions of their events daily.

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