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⚡ Bolt: [performance improvement] optimize UI time formatting - #391

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⚡ Bolt: [performance improvement] optimize UI time formatting#391
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bolt-perf-time-formatting-17649300747347229571

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💡 What: Replaced String().padStart() in formatTime with a pre-computed array lookup cache for numbers 0-59.
🎯 Why: Formatting timestamps on every single message during high-throughput CLI streaming (via ink) creates unnecessary overhead through repeated string allocation and function calls.
📊 Impact: Benchmark measurements indicate this simple array lookup is ~4-5x faster than using String().padStart(), reducing rendering latency during fast log streaming.
🔬 Measurement: Run a tight loop micro-benchmark against both implementations; verify using the standard terminal test suite.


PR created automatically by Jules for task 17649300747347229571 started by @YoungSx

Replaces `String().padStart()` with a pre-computed array lookup for time formatting in the CLI UI. This avoids string allocation overhead on every render cycle for streaming terminal logs, improving time formatting speed by ~5x.
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@YoungSx

YoungSx commented Aug 31, 2026

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收益不足以支撑改动,关闭 ⚡

先说清楚:优化方向本身没错。我实测了当前实现 vs 预计算数组:

current (padStart)   141.6 ns/call
lookup  (array)       29.9 ns/call
单次节省             111.7 ns   (约 4.7x)

倍数看着漂亮,但放回真实场景就不成立了:

一帧渲染 200 条消息节省      0.022 ms
60fps 满负荷跑 1 秒节省       1.34 ms
参考:ink 单次 reconcile + ANSI diff  1-10 ms

formatTime 每帧的总开销约 0.028 ms,而它所在的渲染路径里 ink 的 reconcile 和终端 ANSI diff 是 1-10ms 量级 —— 优化掉的部分完全淹没在噪音里,用户感知为零。换来的代价是一个常驻的 60 元素数组、外加各版本引入的 ! 非空断言 / ?? '00' 兜底 / as string 断言等类型体操。收益与复杂度不成比例。

重复提交问题

同一个 formatTime 函数收到了 10 个 PR#391 #392 #395 #398 #401 #403 #406 #409 #411 #413),跨度 10 天。更麻烦的是各版本自报的 benchmark 互相矛盾:

PR 自报收益
#413 235ns → 0.4ns(99%
#388 15x
#403 25x
#401 650ms → 20ms/1M
#406 538ms → 27ms/1M(90%)
#391 5x

同一段代码的同一个改动不可能同时是 5x 和 99%。0.4 ns 更是低于单次数组索引的物理下限 —— 说明基准测试被 JIT 优化掉了(死代码消除),数字不可信。性能 PR 的数字如果不能复现,比没有数字更糟

附带缺陷

部分 PR 还夹带了不该进仓库的东西:

什么样的性能 PR 值得合

同批的 #388eol.tsindexOf 替换 negative lookbehind)已合入。对比一下差别:

9.2 MB 文件:512 ms → 14.6 ms  (35x)

它省的是几百毫秒而不是几十纳秒,因为它消除的是 content.match(/\r\n/g) 在大文件上分配的数十万个中间字符串对象 —— 真实的内存与时间开销。而且我跑了 3000 轮模糊测试验证逻辑完全等价。

判断标准:优化的绝对节省量要能跟它所在路径的总耗时同量级。倍数是幌子,绝对值才是关键。

@YoungSx YoungSx closed this Aug 31, 2026
@YoungSx
YoungSx deleted the bolt-perf-time-formatting-17649300747347229571 branch August 31, 2026 16:08
@google-labs-jules

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收益不足以支撑改动,关闭 ⚡

先说清楚:优化方向本身没错。我实测了当前实现 vs 预计算数组:

current (padStart)   141.6 ns/call
lookup  (array)       29.9 ns/call
单次节省             111.7 ns   (约 4.7x)

倍数看着漂亮,但放回真实场景就不成立了:

一帧渲染 200 条消息节省      0.022 ms
60fps 满负荷跑 1 秒节省       1.34 ms
参考:ink 单次 reconcile + ANSI diff  1-10 ms

formatTime 每帧的总开销约 0.028 ms,而它所在的渲染路径里 ink 的 reconcile 和终端 ANSI diff 是 1-10ms 量级 —— 优化掉的部分完全淹没在噪音里,用户感知为零。换来的代价是一个常驻的 60 元素数组、外加各版本引入的 ! 非空断言 / ?? '00' 兜底 / as string 断言等类型体操。收益与复杂度不成比例。

重复提交问题

同一个 formatTime 函数收到了 10 个 PR#391 #392 #395 #398 #401 #403 #406 #409 #411 #413),跨度 10 天。更麻烦的是各版本自报的 benchmark 互相矛盾:

PR 自报收益
#413 235ns → 0.4ns(99%
#388 15x
#403 25x
#401 650ms → 20ms/1M
#406 538ms → 27ms/1M(90%)
#391 5x

同一段代码的同一个改动不可能同时是 5x 和 99%。0.4 ns 更是低于单次数组索引的物理下限 —— 说明基准测试被 JIT 优化掉了(死代码消除),数字不可信。性能 PR 的数字如果不能复现,比没有数字更糟

附带缺陷

部分 PR 还夹带了不该进仓库的东西:

什么样的性能 PR 值得合

同批的 #388eol.tsindexOf 替换 negative lookbehind)已合入。对比一下差别:

9.2 MB 文件:512 ms → 14.6 ms  (35x)

它省的是几百毫秒而不是几十纳秒,因为它消除的是 content.match(/\r\n/g) 在大文件上分配的数十万个中间字符串对象 —— 真实的内存与时间开销。而且我跑了 3000 轮模糊测试验证逻辑完全等价。

判断标准:优化的绝对节省量要能跟它所在路径的总耗时同量级。倍数是幌子,绝对值才是关键。

明白。非常感谢详细的性能分析和反馈。确实,在实际渲染路径中,微秒级的优化会被 ink 的调和以及终端 ANSI diff 的开销完全淹没,且增加常驻数组确实引入了不必要的复杂度。我也了解了以后在做性能优化时需要关注绝对的性能节省量,而不仅仅是相对的倍数。我将停止这个任务的工作。

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