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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
13602
Venue
VLDB
Year
2024
Pagerank
4.1945683e-05
Overall Rank
11,082 | 22.91%
DOI
10.14778/3685800.3685823

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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 0.00061639801
121 Improved Query Performance with Variant Indexes 1997 SIGMOD 0.00045447517
3,856 Bit-Sliced Index Arithmetic 2001 SIGMOD 6.6942616e-05
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