Introduction To Apache Flink Stream Processing For Real Time

All Indian Reprints of O'Reilly are printed in Grayscale. There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensorsand 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, telecomand 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 Flinkand learn how it handles time and stateful computation Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance All Indian Reprints of O'Reilly are printed in Grayscale. There’s growing interest in learning how to analyze streaming data in large-scale systems such as web traffic, financial transactions, machine logs, industrial sensorsand 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, telecomand 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 Flinkand learn how it handles time and stateful computation Examine how Flink processes both streaming (unbounded) and batch (bounded) data without sacrificing performance