Database Paper Browser

Back to papers

Large-Scale Metric Computation in Online Controlled Experiment Platform

Summary: Use bitsliced index (BSI) arithmetic to compute aggregates, variances and covariances for large-scale A/B experiments in WeChat, yielding scalable, inference-ready metric computation. Exploit Pareto-skewed activity and fixed query paradigms to optimize BSI encodings and operators; validated in production with strong performance. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13603
Venue
VLDB
Year
2024
Pagerank
4.1905499e-05
Overall Rank
11,085 | 22.96%
DOI
10.14778/3685800.3685823

Incoming Non-self Citations Over Time

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

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

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.

Rank Cited Paper Year Venue Pagerank
66 Spark SQL: Relational Data Processing in Spark 2015 SIGMOD 0.00061707583
121 Improved Query Performance with Variant Indexes 1997 SIGMOD 0.00045429472
3,858 Bit-Sliced Index Arithmetic 2001 SIGMOD 6.6893766e-05
Previous Page 1 / 1 Next

Semantically Similar Papers