Sameer Wadkar has more than 15 years of experience in implementing high-volume distributed systems for clients in the commercial and federal market space. For the past 5 years he has been engaged in implementing Big Data Systems that can handle more than 5 billion transactions a day.

Hari Rajaram is a Chief Architect & Big Data Practice Leader at Arcogent and has more than 17 years of experience in Information Technology, which encompasses finance, media, newspaper, and grants management industries.

True high-velocity and high-volume data stream processing requires more than just handling each record, one at a time, as it arrives. Unlike batch processing, where all data is available, stream processing has to handle incomplete data and late or out-of-order arrivals and at the same time be resilient to failure, all without compromising performance or accuracy. You've also got to incorporate event-time processing to make sure that your stream processing system is every bit as accurate as a batch processing system. And you need one system that performs both stream and batch processing. It's a tall order and Apache Flink is your solution.

Flink in Action makes the complex topic of stream processing with Flink easy to understand and apply. Starting with lots of use cases and crystal clear explanations, this book explains how batch and streaming event processing differ. Then you'll get the big picture of how Flink works, along with crucial topics like windowing and reprocessing. Next, you'll get hands-on by creating your own Flink project using step-by-step instructions and lots of annotated images. With the basics well in hand, you'll move on to advanced topics like the Flink API, Kafka, and fault tolerance. The last part of the book covers working with Flink along with external tools and libraries. By the end, you'll have a strong foundation in the concepts and the challenges of implementing streaming systems capable of handling high-velocity and high-volume streaming data and meeting those challenges with Flink.