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LogKV: Exploiting Key-Value Stores for Event Log Processing

Summary: LogKV repurposes key-value stores as a unified backend for interactive and batch log analytics, supporting time-range scans, windowed joins, reference-table joins and aggregations. Introduces novel ingestion, load‑balancing, storage‑layout and query‑processing techniques to exploit KV scalability; preliminary results show promising performance. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
201
Venue
CIDR
Year
2013
Pagerank
6.5125667e-05
Overall Rank
4,779 | 67.22%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{cao_cidr13,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '13},
        title = {{LogKV: Exploiting Key-Value Stores for Event Log Processing}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Cao, Zhao and Chen, Shimin and Li, Feifei and Wang, Min and Wang, X. Sean},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

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

Rank Cited Paper Year Venue Pagerank
47 PNUTS: Yahoo!'s Hosted Data Serving Platform 2008 VLDB 0.00044503718
769 A Comparison of Join Algorithms for Log Processing in MapReduce 2010 SIGMOD 0.00014166872
1,090 Scalable Distributed Stream Processing 2003 CIDR 0.0001224178
2,502 Stream Warehousing with DataDepot 2009 SIGMOD 8.4972586e-05
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