Implementing a CDC Performance Feature With the Help of ChatGPT

TiCDC is a change data capture (CDC) solution that replicates incremental data changes in real time for TiDB, a distributed SQL database. Previously, TiCDC faced a challenge in its communication with downstream TiDB clusters using query commands, which led to higher CPU usage on SQL parsing and compiling. This issue was particularly significant in larger distributed database systems, where the increased workload could reduce performance and slow down data replication times. Moreover, the lack of plan cache hits further exacerbated the problem, resulting in even slower performance.

Thanks to ChatGPT, a natural language processing and artificial intelligence tool from OpenAI, I was able to resolve these issues. I implemented a TiCDC performance feature that improves the communication between TiCDC and downstream TiDB clusters.

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