TDengine 3.0 Stream Processing And Data Subscription - Tdengine Database

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Batch inserted data will first perform Lift and Combine operations on the vnode where the data was inserted
For aggregation across multiple vnodes, the aggregation stream task is deployed on a randomly selected vnode, combining the state of the first level of aggregation again
Execute lower on demand depending on the trigger mode
Two-level incremental aggregation reduces the amount of data transfer and spreads CPU-intensive computation across nodes
Disordered processing
In order to achieve correctness in various scenarios such as disorder, the streaming computation in TDengine 3.0 adopts a processing model based on event time, and Watermark is the upper bound for disorder tolerance, so to understand the processing of disorder data, we first need to understand Watermark.

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