Look Who it Was Random video

Raoul Gabriel Urma & Valentin Dalibard - Interactively Analyse 100GB of Data

690 views · Published 15 May 2017 · 45:11 · Indexed 26 October 2026

Channel: PyData · 2017 · Science & Technology

Watch on YouTube

Filmed at PyData London 2017
www.pydata.org

Description
In this highly interactive session, you will learn how to leverage Apache Spark, Amazon Elastic Map Reduce (EMR) and Apache Zeppelin to rapidly mine a large real-world data set. You will learn how to apply common Spark patterns to extract insights as well as learn useful performance and monitoring tips.

Abstract
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 will 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.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

We aim to be an accessible, community-driven conference, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

More from this channel