TDengine 3.0 Stream Processing And Data Subscription - Tdengine Database

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Testing the impact of streams on write performance: write latency vs. throughput for the case with and without streams
Test stream result latency at large write throughput
Validate several major scenarios such as scalar functions, individual aggregation per sub-table, and multiple vgroup super-table aggregation, respectively
Roadmap
The next optimizations for the TDengine 3.0 streaming engine will be divided into the following areas.

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Stream engine implementation
After explaining what TDengine’s stream engine is and the relationship between data subscriptions and streams, let’s take a look at how TDengine’s stream processing is implemented. Of course, there are a lot of details and a lot of content, so due to time constraints, I will only pick the 3 most important parts, which I think are the most interesting parts to explain, that is, "event-driven", "incremental computation" and "Chaotic Processing".

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