  While cluster computing frameworks are continuously evolving to provide
real-time data analysis capabilities, Apache Spark has managed to be at the
forefront of big data analytics for being a unified framework for both, batch
and stream data processing. There is also a renewed interest is Near Data
Computing (NDC) due to technological advancement in the last decade. However,
it is not known if NDC architectures can improve the performance of big data
processing frameworks such as Apache Spark. In this position paper, we
hypothesize in favour of NDC architecture comprising programmable logic based
hybrid 2D integrated processing-in-memory and in-storage processing for Apache
Spark, by extensive profiling of Apache Spark based workloads on Ivy Bridge
Server.
