  Online controlled experiment (also called A/B test or experiment) is the most
important tool for decision-making at a wide range of data-driven companies
like Microsoft, Google, Meta, etc. Metric computation is the core procedure for
reaching a conclusion during an experiment. With the growth of experiments and
metrics in an experiment platform, computing metrics efficiently at scale
becomes a non-trivial challenge. This work shows how metric computation in
WeChat experiment platform can be done efficiently using bit-sliced index (BSI)
arithmetic. This approach has been implemented in a real world system and the
performance results are presented, showing that the BSI arithmetic approach is
very suitable for large-scale metric computation scenarios.
