I ran the program in URL of stackoverflow with Spark 2.2.1 and master. I cannot see the exception even when I disabled whole-stage codegen. Am I wrong? We would appreciate it if you could create a JIRA entry with simple standalone repro.
In addition to this report, I realized that this program produces incorrect results. I created a JIRA entry https://issues.apache.org/jira/browse/SPARK-22934. Best Regards, Kazuaki Ishizaki From: Herman van Hövell tot Westerflier <hvanhov...@databricks.com> To: Jacek Laskowski <ja...@japila.pl> Cc: dev <dev@spark.apache.org> Date: 2017/12/31 21:44 Subject: Re: Whole-stage codegen and SparkPlan.newPredicate Hi Jacek, In this case whole stage code generation is turned off. However we still use code generation for a lot of other things: projections, predicates, orderings & encoders. You are currently seeing a compile time failure while generating a predicate. There is currently no easy way to turn code generation off entirely. The error itself is not great, but it still captures the problem in a relatively timely fashion. We should have caught this during analysis though. Can you file a ticket? - Herman On Sat, Dec 30, 2017 at 9:16 AM, Jacek Laskowski <ja...@japila.pl> wrote: Hi, While working on an issue with Whole-stage codegen as reported @ https://stackoverflow.com/q/48026060/1305344 I found out that spark.sql.codegen.wholeStage=false does *not* turn whole-stage codegen off completely. It looks like SparkPlan.newPredicate [1] gets called regardless of the value of spark.sql.codegen.wholeStage property. $ ./bin/spark-shell --conf spark.sql.codegen.wholeStage=false ... scala> spark.sessionState.conf.wholeStageEnabled res7: Boolean = false That leads to an issue in the SO question with whole-stage codegen regardless of the value: ... at org.apache.spark.sql.execution.SparkPlan.newPredicate(SparkPlan.scala:385) at org.apache.spark.sql.execution.FilterExec$$anonfun$18.apply(basicPhysicalOperators.scala:214) at org.apache.spark.sql.execution.FilterExec$$anonfun$18.apply(basicPhysicalOperators.scala:213) at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndexInternal$1$$anonfun$apply$24.apply(RDD.scala:816) ... Is this a bug or does it work as intended? Why? [1] https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkPlan.scala?utf8=%E2%9C%93#L386 Pozdrawiam, Jacek Laskowski ---- https://about.me/JacekLaskowski Mastering Spark SQL https://bit.ly/mastering-spark-sql Spark Structured Streaming https://bit.ly/spark-structured-streaming Mastering Apache Spark 2 https://bit.ly/mastering-apache-spark Follow me at https://twitter.com/jaceklaskowski
