[jira] [Created] (SPARK-32813) Reading parquet rdd in non columnar mode fails in multithreaded environment

["Vladimir Klyushnikov (Jira)" <ji...@apache.org>]

Vladimir Klyushnikov created SPARK-32813:
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             Summary: Reading parquet rdd in non columnar mode fails in multithreaded environment
                 Key: SPARK-32813
                 URL: https://issues.apache.org/jira/browse/SPARK-32813
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 3.0.0
            Reporter: Vladimir Klyushnikov


Reading parquet rdd in non columnar mode (i.e. with list fields)  if Spark session was  created in one thread and rdd is being read in another  - so InheritableThreadLocal  with active session is not propagated. Code below was working perfectly in Spark 2.X, but fails in Spark 3  
{code:scala}
import java.util.concurrent.Executors

import org.apache.spark.sql.SparkSession

import scala.concurrent.{Await, ExecutionContext, Future}
import scala.concurrent.duration._

object Main {

  final case class Data(list: List[Int])

  def main(args: Array[String]): Unit = {

    val executor1 = Executors.newSingleThreadExecutor()
    val executor2 = Executors.newSingleThreadExecutor()
    try {
      val ds = Await.result(Future {
        val session = SparkSession.builder().appName("test").master("local[*]").getOrCreate()
        import session.implicits._

        session.createDataset(Data(1 :: Nil) :: Nil).write.parquet("test.parquet")
        session.read.parquet("test.parquet").as[Data]
      }(ExecutionContext.fromExecutorService(executor1)), 1.minute)

      Await.result(Future {
        ds.rdd.collect().foreach(println(_))
      }(ExecutionContext.fromExecutorService(executor2)), 1.minute)

    } finally {
      executor1.shutdown()
      executor2.shutdown()
    }
  }
}
{code}
This code fails with following exception:
{noformat}
Exception in thread "main" java.util.NoSuchElementException: None.getException in thread "main" java.util.NoSuchElementException: None.get at scala.None$.get(Option.scala:529) at scala.None$.get(Option.scala:527) at org.apache.spark.sql.execution.FileSourceScanExec.needsUnsafeRowConversion$lzycompute(DataSourceScanExec.scala:178) at org.apache.spark.sql.execution.FileSourceScanExec.needsUnsafeRowConversion(DataSourceScanExec.scala:176) at org.apache.spark.sql.execution.FileSourceScanExec.doExecute(DataSourceScanExec.scala:462) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:175) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:213) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:210) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:171) at org.apache.spark.sql.execution.DeserializeToObjectExec.doExecute(objects.scala:96) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:175) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:213) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:210) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:171) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:122) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:121) at org.apache.spark.sql.Dataset.rdd$lzycompute(Dataset.scala:3198) at org.apache.spark.sql.Dataset.rdd(Dataset.scala:3196){noformat}



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