I'm so sorry, I just thought the issue wasn't resolved

Solution

1. Set maxFilesPerTrigger and maxBytesPerTrigger
2. Enable autpoptimize

Reason

for the first day, it processes larger files and then eventually process smaller files。

Detailed reason

Before performance drops：

1000 = (endOffset's index - startOffset's index) = （80999- 79999）

1305389 = numInputRows    

avg records per files is 1305389/1000 = 1305.389

After performance drops：1000 = (endOffset's index - startOffset's index) = （90999- 89999）

45644= numInputRows    

avg records per files is 45644/1000 = 45

From the comparison of (1) and (2), it can be seen that the number of files read by each batch before and after the performance drop (23:30) remains unchanged at 1000, but after 23:30 the number of 1000 total files changes. Less, it is most likely that the file size has become smaller, resulting in a smaller file, so the total number of read items has decreased. That is, for the first day, it processes larger files and then eventually processes smaller files.

Suggestion：

https://docs.microsoft.com/en-gb/azure/databricks/delta/delta-streaming#limit-input-rate

https://docs.microsoft.com/en-us/azure/databricks/delta/optimizations/auto-optimize

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​Finally, a big thank you to the Databricks team and the Microsoft team for their technical support.