About For Books Stream Processing with Apache Spark: Best Practices for Scaling and Optimizing
- 4 years ago
https://msc.realfiedbook.com/?book=1491944242
To build analytics tools that provide faster insights, knowing how to process data in real time is a must, and moving from batch processing to stream processing is absolutely required. Fortunately, the Spark in-memory framework/platform for processing data has added an extension devoted to fault-tolerant stream processing: Spark Streaming.If you're familiar with Apache Spark and want to learn how to implement it for streaming jobs, this practical book is a must.Understand how Spark Streaming fits in the big pictureLearn core concepts such as Spark RDDs, Spark Streaming clusters, and the fundamentals of a DStreamDiscover how to create a robust deploymentDive into streaming algorithmicsLearn how to tune, measure, and monitor Spark Streaming
To build analytics tools that provide faster insights, knowing how to process data in real time is a must, and moving from batch processing to stream processing is absolutely required. Fortunately, the Spark in-memory framework/platform for processing data has added an extension devoted to fault-tolerant stream processing: Spark Streaming.If you're familiar with Apache Spark and want to learn how to implement it for streaming jobs, this practical book is a must.Understand how Spark Streaming fits in the big pictureLearn core concepts such as Spark RDDs, Spark Streaming clusters, and the fundamentals of a DStreamDiscover how to create a robust deploymentDive into streaming algorithmicsLearn how to tune, measure, and monitor Spark Streaming
[Read] Stream Processing with Apache Spark: Best Practices for Scaling and Optimizing Apache
pistolli
[Read] Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of
jifawe5769