LPStream: Fine-grained Lazy Provenance for Stream Processing
Summary: LPStream introduces fine-grained lazy provenance for stream processing, avoiding runtime provenance overhead. When needed, it replays from a suitable checkpoint to generate provenance, outperforming eager provenance and no-provenance baselines. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Masaya Yamada (LY Corporation; National Institute of Advanced Industrial Science and Technology; University of Tsukuba)
- 2. Hiroyuki Kitagawa (National Institute of Advanced Industrial Science and Technology; University of Tsukuba)
- 3. Salman Ahmed Shaikh (National Institute of Advanced Industrial Science and Technology)
- 4. Toshiyuki Amagasa (University of Tsukuba)
- 5. Akiyoshi Matono (National Institute of Advanced Industrial Science and Technology)
BibTeX Citation
@inproceedings{yamada_sigmod26,
title = {{LPStream: Fine-grained Lazy Provenance for Stream Processing}},
author = {Yamada, Masaya and Kitagawa, Hiroyuki and Shaikh, Salman Ahmed and Amagasa, Toshiyuki and Matono, Akiyoshi},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3749172},
url = {https://dl.acm.org/doi/10.1145/3749172},
year = {2026}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,899 | Toward Temporal Attribution Analytics in Dataflows | 2026 | VLDB | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 592 | Lineage Tracing for General Data Warehouse Transformations | 2001 | VLDB | 0.0001583562 |
| 596 | Linear Road: A Stream Data Management Benchmark | 2004 | VLDB | 0.00015766455 |
| 949 | Provenance and Scientific Workflows: Challenges and Opportunities | 2008 | SIGMOD | 0.00012897365 |
| 1,562 | Titian: Data Provenance Support in Spark | 2016 | VLDB | 0.00010192248 |
| 1,593 | DBNotes: A Post-It System for Relational Databases based on Provenance | 2005 | SIGMOD | 0.00010105032 |
| 1,722 | SMOKE: Fine-grained Lineage at Interactive Speed | 2018 | VLDB | 9.781628e-05 |
| 3,939 | Analyzing Efficient Stream Processing on Modern Hardware | 2019 | VLDB | 6.8967981e-05 |
| 7,340 | Ananke: A Streaming Framework for Live Forward Provenance | 2021 | VLDB | 5.5333914e-05 |
| 7,823 | Erebus: Explaining the Outputs of Data Streaming Queries | 2023 | VLDB | 5.4300469e-05 |
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