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DHive: Query Execution Performance Analysis via Dataflow in Apache Hive

Summary: DHive provides dataflow-based visual analysis across query/job/task levels to expose root causes of slow Hive executions instead of mere time breakdowns. It links data movement with config and hardware metrics to pinpoint bottlenecks; open-source. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13437
Venue
VLDB
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,485 | 21.21%
DOI
10.14778/3611540.3611605

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@article{zhang_vldb23,
        title = {{DHive: Query Execution Performance Analysis via Dataflow in Apache Hive}},
        author = {Zhang, Chaozu and Shen, Qiaomu and Tang, Bo},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {12},
        pages = {3998--4001},
        doi = {10.14778/3611540.3611605},
        url = {https://doi.org/10.14778/3611540.3611605},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,743 VQLens: A Demonstration of Vector Query Execution Analysis 2025 SIGMOD 5.093636e-05
10,834 QOVIS: Understanding and Diagnosing Query Optimizer via a Visualization-assisted Approach 2025 VLDB 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

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