Massively Parallel Data Processing In Python Without The Effort Using Bodo

Summary

Python has beome the de facto language for working with data. That has brought with it a number of challenges having to do with the speed and scalability of working with large volumes of information.There have been many projects and strategies for overcoming these challenges, each with their own set of tradeoffs. In this episode Ehsan Totoni explains how he built the Bodo project to bring the speed and processing power of HPC techniques to the Python data ecosystem without requiring any re-work.

Announcements

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• Your host is Tobias Macey and today I’m interviewing Ehsan Totoni about Bodo, a system for automatically optimizing and parallelizing python code for massively parallel data processing and analytics

Interview

• Introduction
• How did you get involved in the area of data management?
• Can you describe what Bodo is and the story behind it?
• What are the techniques/technologies that teams might use to optimize or scale out their data processing workflows?
• Why have you focused your efforts on the Python lan