September 2017
Beginner to intermediate
360 pages
8h 13m
English
book
Practical Real-time Data Processing and Analytics
by Shilpi Saxena, Selva raj Ramasamy, Prateek Bhati, Saurabh Gupta
Content preview from Practical Real-time Data Processing and Analytics
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Summary
In this chapter, we introduced the readers to Apache Spark compute engine, and we talked about the various components of Spark framework and its schedulers. We touched upon the advantages that provide edge to spark as a scalable, high performing compute engine. The users were also acquainted with the not-so sparkling features of Spark—when it's not the best fit to be used. We walked the users through some practical realtime industry wide use cases. Next we got into the layered architecture of Spark and its internal working across the cluster. In the end we touched upon the pragmatic concepts of Spark: RDD, DataFrame, and datasets.
The next chapter will touch upon the spark APIs and execution of all components through working code ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.