Hadoop and Membase Case Study: AOL Advertising Architecture
Combining Hadoop and Membase to solve these challenges:
- How to analyze billions of user-related events, presented as a mix of structured and unstructured data, to infer demographic, psychographic and behavioral characteristics that are encapsulated into hundreds of millions of “cookie profiles”
- How to make hundreds of millions of cookie profiles available to their ad targeting platform with sub-millisecond, random read latency
- How to keep the user profiles fresh and current
In a much simplified form:
- crunch (nb: read it as pre-process and prepare) tons of data with Hadoop
- feed the results in a low latency, high throughput key-value store for serving them online
Original title and link: Hadoop and Membase Case Study: AOL Advertising Architecture (NoSQL databases © myNoSQL)
