Product Description & Reviews
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
Features & Highlights
|Item Weight:||0 pounds|
|Item Size:||0 x 9.19 x 9.19 inches|
|Package Weight:||1.47 pounds|
|Package Size:||7 x 0 x 0 inches|
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