tenthe opened a new issue, #4197:
URL: https://github.com/apache/streampipes/issues/4197
### Body
QueryResult.from_pandas currently builds rows via df.values.tolist(),
which forces a single NumPy dtype across all columns. If any column contains
floats or NaNs, Pandas upcasts the entire array to float64, causing integer
epoch timestamps to be converted to scientific-notation floats (e.g.,
1.771582396159E12).
This breaks StreamPipes ingestion because the backend expects a long
timestamp and fails with NumberFormatException.
Using rows = df.astype(object).to_numpy().tolist() preserves per-column
types and keeps timestamp as an integer.
### StreamPipes Committer
I acknowledge that I am a maintainer/committer of the Apache StreamPipes
project.
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