针对复杂同步任务，DataWorks 将单个实例的 CDC 流拆分为多个子任务，并通过 Pk Shuffle 机制实现数据分发，支持多表、多库并行处理。例如，MySQL 实例下的多个 DB 可独立调度，提升整体并发度，降低端到端延迟，满足高负载业务场景需求。
Presenter: James Gallagher
。Line官方版本下载是该领域的重要参考
This is where historical data visualizations — of the type Claude Code can now produce on cue — can come in handy. I downloaded a scientific paper about knocking on wood along with the crowd-sourced Wikipedia list, then provided it to Claude Code and asked it to plot the data on a three.js globe. Here’s the interactive version and the GitHub page.
这些反应暗示了 AI 的价值大于成本，可是能不能跟人并列一起算呢？这引发了关于 AI 是否会取代人类的讨论。
The primary signal is desiredSize on the controller. It can be positive (wants data), zero (at capacity), negative (over capacity), or null (closed). Producers are supposed to check this value and stop enqueueing when it's not positive. But there's nothing enforcing this: controller.enqueue() always succeeds, even when desiredSize is deeply negative.