[GitHub] [iceberg] zohar-plutoflume commented on issue #7998: performance degradation after migrating to spark 3.3.1 when using iceberg merge into

["zohar-plutoflume (via GitHub)" <gi...@apache.org>]

zohar-plutoflume commented on issue #7998:
URL: https://github.com/apache/iceberg/issues/7998#issuecomment-1623909451

   after looking into it a bit more I think iceberg is not using the spark dynamic filtering but does it on its own, using the RowLevelCommandDynamicPruning
   however it seems like it has a similar condition check:
   private def isCandidate(command: RowLevelCommand): Boolean = command.condition match {
       case Some(cond) if cond != Literal.TrueLiteral => true
       case _ => false
     }
   
   and I wonder what would be a work around it 


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