Learning Spark Streaming Best Practices for Scaling and Optimizing Apache Spark
Auteurs : Garillot Francois, Maas Gerard
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 picture
- Learn core concepts such as Spark RDDs, Spark Streaming clusters, and the fundamentals of a DStream
- Discover how to create a robust deployment
- Dive into streaming algorithmics
- Learn how to tune, measure, and monitor Spark Streaming
Date de parution : 06-2019
Ouvrage de 300 p.
Disponible chez l'éditeur (délai d'approvisionnement : 12 jours).
Prix indicatif 78,12 €
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