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Spark, IPython, Kafka

by C. Ross Jam on September 30, 2014

A couple of good overviews from the fine folks at Cloudera

First, Gwen Shapira & Jeff Holoman on “Apache Kafka for Beginners”

Apache Kafka is creating a lot of buzz these days. While LinkedIn, where Kafka was founded, is the most well known user, there are many companies successfully using this technology.

So now that the word is out, it seems the world wants to know: What does it do? Why does everyone want to use it? How is it better than existing solutions? Do the benefits justify replacing existing systems and infrastructure?

In this post, we’ll try to answers those questions. We’ll begin by briefly introducing Kafka, and then demonstrate some of Kafka’s unique features by walking through an example scenario. We’ll also cover some additional use cases and also compare Kafka to existing solutions.

And Uri Laserson on “How-to: Use IPython Notebook with Apache Spark”

Here I will describe how to set up IPython Notebook to work smoothly with PySpark, allowing a data scientist to document the history of her exploration while taking advantage of the scalability of Spark and Apache Hadoop.

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