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Spark Streaming and GraphX

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Bogdan P.
Spark Streaming and GraphX

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Again our friends from Databricks (the creators of Spark) will give a remote talk at the Vienna Spark Meetup . Many thanks to Denny Lee for his great support!

Denny managed to get two star Spark Streaming speakers from Databricks to talk at this meetup:

• for the first 15min, we will do a quick jump start into Spark Streaming with Prakash Chockalingam*, Solutions Architect at Databricks.

• for the remaining 30min, we will have Tathagata "TD" Das** talk about building robust, scalable, and adaptive applications on Spark Streaming. TD is the lead developer behind Spark Streaming.

Furthermore I'm very happy to announce a talk provided by somebody from the local Spark community in Vienna: Roland Boubela from the Medical University of Vienna will talk about how he uses Spark GraphX.

Title: "Using Apache Spark's GraphX library for the analysis of functional neuroimaging data"

Abstract: "Graph theoretical approaches are well established in the analysis of functional magnetic resonance imaging (fMRI) data. Typically, with this kind of data a graph is constructed using correlations of the measured time series from the different volume elements resulting in a sparse graph with a lot of nodes and a few edges. In this talk, an overview of Apache Spark's GraphX library with examples in neuroimaging will be given, along with a brief introduction to graph methods used in fMRI data. "

Schedule:

19:00 - Start with some drinks and networking

19:15 - "Jump start into Spark Streaming" with Prakash Chockalingam

19:30 - Tathagata "TD" Das talks about "Building robust, scalable, and adaptive applications on Spark Streaming"

20:00 - 5 min break

20:05 - Roland Boubela talks about "Using Apache Spark's GraphX library for the analysis of functional neuroimaging data"

20:50 - Spark swag giveaway, food, more drinks & chatting.

Looking forward to see you at the Novomatic Forum!

  • ... Prakash is currently a Solutions Architect at Databricks and focuses on helping customers building their big data infrastructure based on his decade-long experience on building large scale distributed systems and machine learning infrastructure at companies including Netflix and Yahoo. Prior to joining Databricks, he was with Netflix designing and building their recommendation infrastructure that serves out millions of recommendations to Netflix users every day.

** ... Tathagata is an Apache Spark committer and a member of the PMC. He is the lead developer behind Spark Streaming, which he started as a graduate student in the UC Berkeley AMPLab. He is currently employed at Databricks. Prior to Databricks, Tathagata has worked at the AMPLab, conducting research in data-center frameworks and networks with professors Scott Shenker and Ion Stoica.

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