August 2017
Beginner to intermediate
278 pages
6h 40m
English
book
Building Data Streaming Applications with Apache Kafka
by Chanchal Singh, Manisha Sethi, Manish Kumar, Anshul Joshi
Content preview from Building Data Streaming Applications with Apache Kafka
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Pillars of Spark
The following are the important pillars of Spark:
Resilient Distributed Dataset (RDD): RDD is the backbone of Spark. RDD is an immutable, distributed, fault tolerant collection of objects. RDDs are divided into logical partitions which are computed on different worker machines.
In short, if you read any file in Spark, the data of that file will together form a single, large RDD. Any filtering operation on this RDD will produce a new RDD. Remember, RDD is immutable. This means that every time we modify the RDD, we have a new RDD. This RDD is divided into logical chunks known as partitions, which is a unit of parallelism in Spark. Each chunk or partition is processed on a separate distributed machine.
The following diagram ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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