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https://issues.apache.org/jira/browse/SPARK-36733?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon reassigned SPARK-36733:
------------------------------------

    Assignee: Kousuke Saruta

> Perf issue in SchemaPruning when a struct has many fields
> ---------------------------------------------------------
>
>                 Key: SPARK-36733
>                 URL: https://issues.apache.org/jira/browse/SPARK-36733
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 3.1.2
>            Reporter: Kohki Nishio
>            Assignee: Kousuke Saruta
>            Priority: Major
>             Fix For: 3.3.0
>
>
> Seeing a significant performance degradation in query processing when a table 
> contains a significantly large number of fields (>10K).
> Here's the stacktraces while processing a query
> {code:java}
>    java.lang.Thread.State: RUNNABLE   java.lang.Thread.State: RUNNABLE at 
> scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:285) at 
> scala.collection.TraversableLike$$Lambda$296/874023329.apply(Unknown Source) 
> at scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36) 
> at 
> scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33) 
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198) at 
> scala.collection.TraversableLike.map(TraversableLike.scala:285) at 
> scala.collection.TraversableLike.map$(TraversableLike.scala:278) at 
> scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:198) at 
> org.apache.spark.sql.types.StructType.fieldNames(StructType.scala:108) at 
> org.apache.spark.sql.catalyst.expressions.SchemaPruning$.$anonfun$sortLeftFieldsByRight$1(SchemaPruning.scala:70)
>  at 
> org.apache.spark.sql.catalyst.expressions.SchemaPruning$.$anonfun$sortLeftFieldsByRight$1$adapted(SchemaPruning.scala:70)
>  at 
> org.apache.spark.sql.catalyst.expressions.SchemaPruning$$$Lambda$3963/249742655.apply(Unknown
>  Source) at 
> scala.collection.TraversableLike.$anonfun$filterImpl$1(TraversableLike.scala:303)
>  at scala.collection.TraversableLike$$Lambda$403/465534593.apply(Unknown 
> Source) at 
> scala.collection.IndexedSeqOptimized.foreach(IndexedSeqOptimized.scala:36) at 
> scala.collection.IndexedSeqOptimized.foreach$(IndexedSeqOptimized.scala:33) 
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:198) at 
> scala.collection.TraversableLike.filterImpl(TraversableLike.scala:302) at 
> scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:296) at 
> scala.collection.mutable.ArrayOps$ofRef.filterImpl(ArrayOps.scala:198) at 
> scala.collection.TraversableLike.filter(TraversableLike.scala:394) at 
> scala.collection.TraversableLike.filter$(TraversableLike.scala:394) at 
> scala.collection.mutable.ArrayOps$ofRef.filter(ArrayOps.scala:198) at 
> org.apache.spark.sql.catalyst.expressions.SchemaPruning$.sortLeftFieldsByRight(SchemaPruning.scala:70)
>  at 
> org.apache.spark.sql.catalyst.expressions.SchemaPruning$.$anonfun$sortLeftFieldsByRight$3(SchemaPruning.scala:75)
>  at 
> org.apache.spark.sql.catalyst.expressions.SchemaPruning$$$Lambda$3965/461314749.apply(Unknown
>  Source) {code}



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