Zoltan Zvara, Research Scientist at Hungarian Academy of Sciences

Zoltan Zvara

Research Scientist, Hungarian Academy of Sciences

Zoltán is a researcher and project lead at the Hungarian Academy of Sciences. His main expertise and interest is the data partitioning and scheduling of distributed data processing frameworks. His current work includes research and development on distributed tracing in Spark and QoS scheduling on Hadoop YARN. Zoltán is a speaker in various Big Data related conferences and meetups, including Hadoop Summit.


Handling Data Skew Adaptively In Spark Using Dynamic Repartitioning

We propose a lightweight on-the-fly Dynamic Repartitioning module for Spark, which can adaptively repartition data during execution with negligible overhead to provide a close-to-uniform partitioning. In our experiments with distributions common in practice (for example… Read more