anoopj commented on PR #16006: URL: https://github.com/apache/iceberg/pull/16006#issuecomment-4269071229
> How do we behave when we use non-vectorized readers in Spark? Are we able to use read them? How hard would it be to more lenient and implement a conversion? What would be the performance cost? This is a good point. Looks like the non-vectorized readers are more [lenient](https://github.com/apache/iceberg/blob/ecbe8a84b1897015bdaf0e7c3fdcbb8575aa9971/parquet/src/main/java/org/apache/iceberg/data/parquet/BaseParquetReaders.java#L197-L213). It allows the conversion, as long as it's not lossy. e.g. Allow reading a `uint32` as Iceberg `long`, `uint16` as `int` etc. The PR is blanket rejecting them. Let's try to be consistent with the non-vectorized reader. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
