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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
h79033cfdc671e8ff
Venue
CIDR
Year
2013
Pagerank
6.4229185e-05
Overall Rank
4,772 | 67.92%
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)

Showing 9 of 9 citing papers.

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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 0.00044066403
799 A Comparison of Join Algorithms for Log Processing in MapReduce 2010 SIGMOD 0.00013889081
1,101 Scalable Distributed Stream Processing 2003 CIDR 0.00012005389
2,526 Stream Warehousing with DataDepot 2009 SIGMOD 8.3432541e-05
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