Graph Analytics at Scale using SparkSQL and GraphFrames
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Jornaya
1001 E Hector St · Conshohocken, PA
How to find us
Jornaya is located at Suite 230. Turn right out of the elevator. Make a left and we are on the right side. If you are coming by Regional Rail, we are a minute walk from the Spring Mill Station (Norristown line).
Details
Chris Snyder, the Manager of Data Science at Jornaya, walks us through graph analytics at scale using SparkSQL and GraphFrames. In this talk, you will learn about work that has made graph algorithms in GraphFrames faster and more scalable. We will walk through some of these algorithms, in particular the connected components algorithm implemented in GraphFrames, and demonstrate their usage.
Graph analytics has a wide range of applications, from information propagation and network flow optimization to fraud and anomaly detection. Spark SQL lets you query structured data inside Spark programs, using either SQL or a familiar DataFrame API. GraphFrames is an open source project that leverages SparkSQL to execute graph algorithms at scale.
