Title:
Making Pandas Faster with Ray and Apache Arrow

Description:
In this work, we are transparently distributing Pandas DataFrames in order to take full advantage of multiple cores or a cluster of resources using Ray and Apache Arrow. Users can access these advantages in their existing Pandas workflows with the change of a single line of code. Pandas users do not need to learn a new library, and knowledge of distributed computing is not required.



Presenter(s):
 Speaker: Devin Petersohn, University of California, Berkeley
 Speaker: Robert Nishihara, University of California, Berkeley
 Speaker: Philipp Moritz, University of California, Berkeley
 Speaker: Simon Mo, University of California, Berkeley
 Speaker: Helen Che, University of California, Berkeley
 Speaker: Peter Veerman, University of California, Berkeley
 Speaker: Harikaran Subbaraj, University of California, Berkeley
 Speaker: Rohan Singh, University of California, Berkeley
 Speaker: Joseph Gonzalez, University of California, Berkeley
 Speaker: Ion Stoica, University of California, Berkeley
 Speaker: Anthony Joseph, University of California, Berkeley