Big data and data analysis have long been popular key words in the IT world. Nowadays, they are no longer a choice but a necessity. Everyone is piling up and digging up data to find a meaning from big data. To achieve success in this “fact-finding” process, we need an appropriate analytics environment. Today I’d like to share with you how and what LINE has built for game analysis.
Last time I posted an article titled, “Analyzing Large Amounts of Security Data with Spark, Mesos, Zeppelin, and HDFS.” Today I will introduce how LINE applies cloud and stream processing technology to perform near-real-time processing on game data detected by AirArmor1.
1: AirArmor is a security solution for mobile games developed by LINE.
AirBorne DataCenter & Mesos (with DC/OS)
To analyze security data, we built our own system named AirBorne DataCenter. The system uses Apache Mesos as its base framework. And to process big data efficiently, the system implements open source components such as Kafka, Spark, Elasticsearch, Hadoop, Zeppelin, and Spring.
Hello. My name is ST and I develop mobile games here at LINE. In this post I would like to talk about the multi-threaded parallel processing method we are using with Cocos2d-x, the leading mobile game engine. I will go into more detail about how we improved upon the existing single-thread structure and enhanced performance using multi-threaded physics calculation.
Multi-Threaded physics calculation parallel processing architecture
Before we move on to the multi-threaded physics calculation parallel processing structure, we should take a look at the existing single-thread Cocos2d-x update loop.