<strong style="font-size : medium">Python on Storm: PyData meets Big Data

RSVPs will cost $5. (Refundable)All proceeds go towards nonprofit organization,Girls Who Code. Launched in Spring 2012, Girls Who Code is anationalnonprofit organization working to close the gender gap in the technology and engineering sectors. With your support, Girls Who Code works to educate, inspire, and equip high school girls with the skills and resources to pursue opportunities in computing fields. I got inspired by article in in Forbes magazine,STEM Fields And The Gender Gap: Where Are The Women?

Now back to agenda:

Abstract:

Storm lets us operate on real-time streams in an efficient and reliable manner. But can we leverage the amazing PyData stack available in the Python ecosystem to analyze this data?

Until recently, there were no good options to do so. A new open source project, streamparse, makes working with real-time data streams easy for Pythonistas, by integrating Python code with Apache Storm. This talk will explore the history of Python and Storm interoperability options, starting with the Nathan Marz's original storm.py implementation, AirSage's Petrel, Parse.ly's streamparse, and recently, Yelp's pyleus.

The talk will also explore a real-world use of Storm. It will show how Parse.ly is using Python and Storm in production to do real-time content analytics on nearly 10 billion web analytics events per month, over 5,000 events per second at peak. It will also show where Storm fits in our "Lambda Architecture", where we use Pandas/IPython for in-memory analysis and PySpark for batch rebuilds/recomputations. It will then lay out a roadmap for the streamparse project and how Storm and Python can better interoperate in 2015, especially learning from recent ecosystem innovations, such as Spark.

Speaker:Andrew Montalenti @amontalenti

Andrew is the co-founder and CTO of Parse.ly, a Python-built tech startup that helps top online publishers understand what content their audience is interested in -- and why.

Prior to starting Parse.ly, Andrew was a technologist with nearly a decade of experience in finance, high tech, and online media. He earned a degree in Computer Science from NYU. A dedicated Pythonista, JavaScript hacker, and open source advocate, Andrew is also a published technical author and editor. He has presented at PyData NYC 2012, PyCon 2013, and several other technology conferences.

Agenda:

6 :30 pm: Guest arrival & networking.

7:00 pm: Python on Storm: PyData meets Big Data

8.00 pm: Event ends.

Thanks

Eugene Dvorkin

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