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Scala Data Analysis Cookbook by Arun Manivannan

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Using Spark as an ETL tool

In the previous recipe, we subscribed to a Twitter stream and stored it in ElasticSearch. Another common source of streaming is Kafka, a distributed message broker. In fact, it's a distributed log of messages, which in simple terms means that there can be multiple brokers that has the messages partitioned among them.

In this recipe, we'll be subscribing the data that we ingested into ElasticSearch in the previous recipe and publishing the messages into Kafka. Soon after we publish the data to Kafka, we'll be subscribing to Kafka using the Spark Stream API. While this is a recipe that demonstrates treating ElasticSearch data as an RDD and publishing to Kafka using a KryoSerializer, the true intent of this recipe is to ...

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