University of Cambridge > > Cambridge Spark talks > Big Data! Interactively Analyse 100GB of Data using Spark, Amazon EMR and Zeppelin

Big Data! Interactively Analyse 100GB of Data using Spark, Amazon EMR and Zeppelin

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Chih-Chun Chen.

Register via eventbrite:

You may have been hearing a lot of buzz around Big Data, Apache Spark, Amazon Elastic Map Reduce (EMR) and Apache Zeppelin. What’s the fuss about, and how can you benefit from these state of the art technologies?

In this highly interactive session, you will learn how to leverage Spark to rapidly mine a large real-world data set. We will conduct the analysis live entirely using an iPython Notebook to show you how easy it can be to get to grips with these technologies.

In the first part of the session, we characterise what Big Data is. We will then use a sample of data from the Open Library dataset, and you will learn how to apply common Spark patterns to extract insights and aggregate data. In the second part of the session, you will see how to leverage Spark on Amazon EMR to scale your data processing queries over a cluster of machines and interactively analyse a large data set (100GB) with a Zeppelin Notebook. Along the way, you will learn gotchas as well as useful performance and monitoring tips.

This talk is part of the Cambridge Spark talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2022, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity