CLASH: A High-Level Abstraction for Optimized, Multi-Way Stream Joins over Apache Storm
Summary: CLASH provides a high-level abstraction atop Apache Storm for native multi-way stream joins. It introduces MultiStream, a join operator that trades intermediate materialization for communication cost, with automated plan optimization and a SQL-like interface to deploy Storm topologies. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Manuel Dossinger (Technical University of Kaiserslautern)
- 2. Sebastian Michel (Technical University of Kaiserslautern)
- 3. Constantin Roudsarabi (Technical University of Kaiserslautern)
BibTeX Citation
@inproceedings{dossinger_sigmod19,
title = {{CLASH: A High-Level Abstraction for Optimized, Multi-Way Stream Joins over Apache Storm}},
author = {Dossinger, Manuel and Michel, Sebastian and Roudsarabi, Constantin},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3320217},
url = {https://dl.acm.org/doi/10.1145/3299869.3320217},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,873 | Unraveling the Impact of Window Semantics: Optimizing Join Order for Efficient Stream Processing | 2025 | VLDB | 5.093636e-05 |
| 11,181 | Low-Latency Adaptive Distributed Stream Join System Based on a Flexible Join Model | 2024 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,016 | Rate-Based Query Optimization for Streaming Information Sources | 2002 | SIGMOD | 0.00012645699 |
| 1,171 | Photon: Fault-tolerant and Scalable Joining of Continuous Data Streams | 2013 | SIGMOD | 0.00011826434 |
| 2,513 | Tuple Routing Strategies for Distributed Eddies | 2003 | VLDB | 8.48462e-05 |
| 2,892 | Scalable and Adaptive Online Joins | 2014 | VLDB | 7.9852178e-05 |
| 3,532 | Scalable Distributed Stream Join Processing | 2015 | SIGMOD | 7.3369085e-05 |
| 7,617 | Squall: Scalable Real-time Analytics | 2016 | VLDB | 5.5811128e-05 |
| 9,501 | Tracking Set Correlations at Large Scale | 2014 | SIGMOD | 5.2592462e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,369 | How Soccer Players Would do Stream Joins | 2011 | SIGMOD |
| 2 | 6,108 | Providing Streaming Joins as a Service at Facebook | 2018 | VLDB |
| 3 | 6,012 | Parallel Index-based Stream Join on a Multicore CPU | 2020 | SIGMOD |
| 4 | 7,617 | Squall: Scalable Real-time Analytics | 2016 | VLDB |
| 5 | 3,578 | Advanced Join Strategies for Large-Scale Distributed Computation | 2014 | VLDB |
| 6 | 6,482 | AStream: Ad-hoc Shared Stream Processing | 2019 | SIGMOD |
| 7 | 1,093 | Maximizing the Output Rate of Multi-Way Join Queries over Streaming Information Sources | 2003 | VLDB |
| 8 | 11,181 | Low-Latency Adaptive Distributed Stream Join System Based on a Flexible Join Model | 2024 | SIGMOD |
| 9 | 3,532 | Scalable Distributed Stream Join Processing | 2015 | SIGMOD |
| 10 | 7,856 | AJoin: Ad-hoc Stream Joins at Scale | 2020 | VLDB |