Hi all, I'm writing to introduce a new PR that significantly improves how we handle large query results in the IoTDB Python client.
Fetching massive datasets all at once can often lead to memory issues and inefficiencies. To solve this, we are introducing a streaming DataFrame interface that allows users to fetch results in manageable chunks. This PR adds `has_next_df()` and `next_df()` methods to `SessionDataSet`, making it much easier to iterate through data. We've also implemented internal buffering within `IoTDBRpcDataSet` to manage these data chunks smoothly based on the specified `fetch_size`. Additionally, the core logic for processing results has been refactored to support both this new streaming approach and the traditional batch method. We have updated the example scripts to demonstrate how to use this new API, including specific examples for Table Mode usage. The PR link is: https://github.com/apache/iotdb/pull/17035 Best regards, -------------------- Yuan Tian
