There's growing interest in learning how to analyze streaming data in
large-scale systems such as web traffic, financial transactions, machine
logs, industrial sensors, and many others. But analyzing data streams at
scale has been difficult to do well--until now. This practical book
delivers a deep introduction to Apache Flink, a highly innovative open
source stream processor with a surprising range of capabilities.
Authors Ellen Friedman and Kostas Tzoumas show technical and
nontechnical readers alike how Flink is engineered to overcome
significant tradeoffs that have limited the effectiveness of other
approaches to stream processing. You'll also learn how Flink has the
ability to handle both stream and batch data processing with one
technology.
- Learn the consequences of not doing streaming well--in retail and
marketing, IoT, telecom, and banking and finance
- Explore how to design data architecture to gain the best advantage
from stream processing
- Get an overview of Flink's capabilities and features, along with
examples of how companies use Flink, including in production
- Take a technical dive into Flink, and learn how it handles time and
stateful computation
- Examine how Flink processes both streaming (unbounded) and batch
(bounded) data without sacrificing performance