alamb opened a new issue, #7301: URL: https://github.com/apache/arrow-datafusion/issues/7301
### Is your feature request related to a problem or challenge? As described in detail by @liukun4515 and @tustvold and @viirya on https://github.com/apache/arrow-datafusion/pull/6832, DataFusion's decimal devision semantics. @liukun4515 notes https://github.com/apache/arrow-datafusion/pull/6832#issuecomment-1680098056 that spark has the config to control the precision loss : https://github.com/apache/spark/blob/2be20e54a2222f6cdf64e8486d1910133b43665f/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/arithmetic.scala#L246 And @tustvold notes For people looking to emulate spark which only supports precision up to 38, casting to Decimal256 and then truncating down to Decimal128 will be equivalent, and is what a precision loss arithmetic kernel would do ### Describe the solution you'd like If anyone needs spark compatible decimal division rules, I suggest: 1. Add a new config option 2. Apply the rewrite suggested by @tustvold (cast to Decimal256, divide, and then cast to Decimal128) as an [AnalyzerRule](https://docs.rs/datafusion/latest/datafusion/optimizer/analyzer/trait.AnalyzerRule.html#) ### Describe alternatives you've considered See ticket -- we discussed at length changing the semantics of division in arrow-rs and concluded there was no one agreed upon ideal behavior ### Additional context _No response_ -- 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]
