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Chukonu: A Fully-Featured High-Performance Big Data Framework that Integrates a Native Compute Engine into Spark

Summary: Chukonu embeds a native compute engine in Spark via DAG splitting: Spark handles runtime features, while compile-time fragments undergo fusion, vectorization, and compaction. This preserves Spark’s ecosystem while delivering up to 71.6× speedup and 2.29× faster TPC-DS. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
13146
Venue
VLDB
Year
2022
Pagerank
5.1613298e-05
Overall Rank
10,076 | 30.87%
DOI
10.14778/3503585.3503596

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{yu_vldb22,
        title = {{Chukonu: A Fully-Featured High-Performance Big Data Framework that Integrates a Native Compute Engine into Spark}},
        author = {Yu, Bowen and Feng, Guanyu and Cao, Huanqi and Li, Xiaohan and Sun, Zhenbo and Wang, Haojie and Zhu, Xiaowei and Zheng, Weimin and Chen, Wenguang},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {4},
        pages = {872--885},
        doi = {10.14778/3503585.3503596},
        url = {https://doi.org/10.14778/3503585.3503596},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
6,614 Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine 2025 SIGMOD 5.8216658e-05
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Outgoing Citations (Sorted by Pagerank)

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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