perf(i18n): cache parametrised renders and reuse action snapshot factory - #128
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Spark sampling (j9YE2XtMP3) shows per-tick viewer rendering spends its time in MiniMessage deserialization under LocalizedMessages.plain with placeholder TagResolvers: - Cache Map-based render/plain by (locale, key, sorted placeholder entries) via Caffeine (max 512): hot paths publicSeatStatus, publicCenterText and botDisplayName now hit a single deserialize per stable placeholder set instead of per tick. - Add formatNumber + Map overloads to MessageService facade so hot callers can use the cached path without constructing TagResolvers. - Reuse one PlayerActionSnapshotFactory per session (was 3-4 news per bot tick) and replace hasAction stream().anyMatch with a plain loop. Behaviour is unchanged: placeholder maps are resolved by tag name, so iteration order does not affect output; bundles are immutable after load.
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Arbousier1
added
performance-ab
BotActionSchedulerTest and SichuanBotPreparationSchedulerTest mock MahjongTableSession, which now exposes actionSnapshotFactory(). Stub it to return a real PlayerActionSnapshotFactory so the shared per-session factory path is exercised by the scheduler tests.
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Summary
Spark 采样（https://spark.lucko.me/j9YE2XtMP3）显示每 tick 观众渲染大量时间花在
LocalizedMessages.plain的 MiniMessage 反序列化（renderWithTags/deserialize热点，MessageService.plain栈）与 G1 分配（allocate_new_tlab热点）上。三个改动（行为不变）：
LocalizedMessages.render/plain(Locale, key, Map)现按(locale, key, 排序后的占位符条目)用 Caffeine（max 512）缓存；热路径publicSeatStatus/publicCenterText/botDisplayName每 tick 只对稳定占位符集反序列化一次。占位符按 tag 名解析，Map 迭代顺序不影响输出；bundle 加载后不可变。render/plain(Locale, key, Map)+formatNumber委托，热调用方无需构造 TagResolver 数组。GbBotStrategy.hasActionstream → for 循环。门禁
性能 label：
performance-ab+performance-i18n（i18n profile 为 PR-A #126 新增，含 bot-name / seat-status / center-text 等带占位符渲染基准）。Test plan
compileJava（JDK 25 toolchain）通过-PmahjongJavaTarget=25，getFirst 需要 Java 21+ API）