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arXiv · 2103.02145

Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time

Doris Xin·Devin Petersohn·Dixin Tang·Yifan Wu·Joseph E. Gonzalez·Joseph M. Hellerstein·Anthony D. Joseph·Aditya G. Parameswaran
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Abstract

We propose opportunistic evaluation, a framework for accelerating interactions with dataframes. Interactive latency is critical for iterative, human-in-the-loop dataframe workloads for supporting exploratory data analysis. Opportunistic evaluation significantly reduces interactive latency by 1) prioritizing computation directly relevant to the interactions and 2) leveraging think time for asynchronous background computation for non-critical operators that might be relevant to future interactions. We show, through empirical analysis, that current user behavior presents ample opportunities for optimization, and the solutions we propose effectively harness such opportunities.

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Doris Xin, Devin Petersohn, Dixin Tang, Yifan Wu, Joseph E. Gonzalez, Joseph M. Hellerstein, Anthony D. Joseph, Aditya G. Parameswaran. 2021-03-03. Enhancing the Interactivity of Dataframe Queries by Leveraging Think Time. https://arxiv.org/abs/2103.02145

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