How Bitmap‑Based High‑Table Architecture Powers Mill‑Scale User Profiling and Real‑Time Crowd Selection
The article explains how a bitmap‑driven high‑table design (SelectDB) overcomes wide‑table storage bloat and latency to enable millisecond‑level crowd selection for tens of millions of users with hundreds of tag dimensions, while supporting dynamic tag expansion.
Profiling tens of millions of users across hundreds of tag dimensions and performing crowd selection within milliseconds is a stringent requirement in the gaming industry.
Traditional wide‑table solutions encounter two main problems: frequent tag changes cause storage bloat, and real‑time selection creates performance bottlenecks that prevent operators from responding promptly.
SelectDB implements a bitmap‑based high‑table architecture. User groups are stored as bitmaps; orthogonal bitmap operations combine multiple tags, delivering selection results in seconds while allowing tags to be added dynamically without increasing storage size.
This design eliminates the inefficiency of crowd estimation and enables precise push notifications at scale.
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