Scaling an Online Statistics Computation System

Student: Lavrenov Nikolay

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2020

The Yandex anti-fraud team analyzes a large volume of logs and calculates various statistics on them. For this purpose, they are currently using the Mapreduce-based architecture, for which the logs divided into blocks of several minutes. Thus, fraud decisions are available in a few minutes, because they are based on statistics counted during MapReduce. For some services, such a delay of minutes is too long, for example, for UGC (user-generated content) services, where spammers can send a lot of messages/comments in a few minutes. Without statistics, they can not be filtered. The development of an architecture that helps solve these problems discussed below.

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