September 2017
Beginner to intermediate
360 pages
8h 13m
English
At a very high–level, the data flow pipeline with Spark is very similar to the Storm architecture depicted in the previous figure, but one the most critical aspects of this flow is that Spark leverages HDFS as a distributed storage layer. Here, have a look before we get into further dissection of the overall flow and its nitty–gritty:

As with a typical real–time analytic pipeline, we ingest the data using one of the streaming data grabbing agents like Flume or Logstash. We introduce Kafka to ensure decoupling into the system between the sources agents. Then, we have the Spark streaming component that provides a distributed ...
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