In-Memory Indexed Caching for Distributed Data Processing

@article{Uta2022InMemoryIC,
  title={In-Memory Indexed Caching for Distributed Data Processing},
  author={Alexandru Uta and Bogdan Ghit and Ankur Dave and Jan S. Rellermeyer and Peter A. Boncz},
  journal={2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)},
  year={2022},
  pages={104-114}
}
  • Alexandru UtaBogdan Ghit P. Boncz
  • Published 12 December 2021
  • Computer Science
  • 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
Powerful abstractions such as dataframes are only as efficient as their underlying runtime system. The de-facto distributed data processing framework, Apache Spark, is poorly suited for the modern cloud-based data-science workloads due to its outdated assumptions: static datasets analyzed using coarse-grained transformations. In this paper, we introduce the Indexed DataFrame, an in-memory cache that supports a dataframe abstraction which incorporates indexing capabilities to support fast lookup… 

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