[jira] [Assigned] (SPARK-23251) ClassNotFoundException: scala.Any when there's a missing implicit Map encoder
[ https://issues.apache.org/jira/browse/SPARK-23251?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-23251: Assignee: Apache Spark > ClassNotFoundException: scala.Any when there's a missing implicit Map encoder > - > > Key: SPARK-23251 > URL: https://issues.apache.org/jira/browse/SPARK-23251 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.3.1 > Environment: mac os high sierra, centos 7 >Reporter: Bruce Robbins >Assignee: Apache Spark >Priority: Minor > > In branch-2.2, when you attempt to use row.getValuesMap[Any] without an > implicit Map encoder, you get a nice descriptive compile-time error: > {noformat} > scala> df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > :26: error: Unable to find encoder for type stored in a Dataset. > Primitive types (Int, String, etc) and Product types (case classes) are > supported by importing spark.implicits._ Support for serializing other types > will be added in future releases. > df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > ^ > scala> implicit val mapEncoder = > org.apache.spark.sql.Encoders.kryo[Map[String, Any]] > mapEncoder: org.apache.spark.sql.Encoder[Map[String,Any]] = class[value[0]: > binary] > scala> df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > res1: Array[Map[String,Any]] = Array(Map(stationName -> 007026 9, year -> > 2014), Map(stationName -> 007026 9, year -> 2014), Map(stationName -> > 007026 9, year -> 2014), > etc... > {noformat} > > On the latest master and also on branch-2.3, the transformation compiles (at > least on spark-shell), but throws a ClassNotFoundException: > > {noformat} > scala> df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > java.lang.ClassNotFoundException: scala.Any > at > scala.reflect.internal.util.AbstractFileClassLoader.findClass(AbstractFileClassLoader.scala:62) > at java.lang.ClassLoader.loadClass(ClassLoader.java:424) > at java.lang.ClassLoader.loadClass(ClassLoader.java:357) > at java.lang.Class.forName0(Native Method) > at java.lang.Class.forName(Class.java:348) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.javaClass(JavaMirrors.scala:555) > at > scala.reflect.runtime.JavaMirrors$JavaMirror$$anonfun$classToJava$1.apply(JavaMirrors.scala:1211) > at > scala.reflect.runtime.JavaMirrors$JavaMirror$$anonfun$classToJava$1.apply(JavaMirrors.scala:1203) > at > scala.reflect.runtime.TwoWayCaches$TwoWayCache$$anonfun$toJava$1.apply(TwoWayCaches.scala:49) > at scala.reflect.runtime.Gil$class.gilSynchronized(Gil.scala:19) > at scala.reflect.runtime.JavaUniverse.gilSynchronized(JavaUniverse.scala:16) > at > scala.reflect.runtime.TwoWayCaches$TwoWayCache.toJava(TwoWayCaches.scala:44) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.classToJava(JavaMirrors.scala:1203) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.runtimeClass(JavaMirrors.scala:194) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.runtimeClass(JavaMirrors.scala:54) > at > org.apache.spark.sql.catalyst.ScalaReflection$.getClassFromType(ScalaReflection.scala:700) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$dataTypeFor$1.apply(ScalaReflection.scala:84) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$dataTypeFor$1.apply(ScalaReflection.scala:65) > at > scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:56) > at > org.apache.spark.sql.catalyst.ScalaReflection$class.cleanUpReflectionObjects(ScalaReflection.scala:824) > at > org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:39) > at > org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$dataTypeFor(ScalaReflection.scala:64) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor$1.apply(ScalaReflection.scala:512) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor$1.apply(ScalaReflection.scala:445) > at > scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:56) > at > org.apache.spark.sql.catalyst.ScalaReflection$class.cleanUpReflectionObjects(ScalaReflection.scala:824) > at > org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:39) > at > org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor(Scala
[jira] [Assigned] (SPARK-23251) ClassNotFoundException: scala.Any when there's a missing implicit Map encoder
[ https://issues.apache.org/jira/browse/SPARK-23251?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-23251: Assignee: (was: Apache Spark) > ClassNotFoundException: scala.Any when there's a missing implicit Map encoder > - > > Key: SPARK-23251 > URL: https://issues.apache.org/jira/browse/SPARK-23251 > Project: Spark > Issue Type: Bug > Components: SQL >Affects Versions: 2.3.1 > Environment: mac os high sierra, centos 7 >Reporter: Bruce Robbins >Priority: Minor > > In branch-2.2, when you attempt to use row.getValuesMap[Any] without an > implicit Map encoder, you get a nice descriptive compile-time error: > {noformat} > scala> df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > :26: error: Unable to find encoder for type stored in a Dataset. > Primitive types (Int, String, etc) and Product types (case classes) are > supported by importing spark.implicits._ Support for serializing other types > will be added in future releases. > df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > ^ > scala> implicit val mapEncoder = > org.apache.spark.sql.Encoders.kryo[Map[String, Any]] > mapEncoder: org.apache.spark.sql.Encoder[Map[String,Any]] = class[value[0]: > binary] > scala> df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > res1: Array[Map[String,Any]] = Array(Map(stationName -> 007026 9, year -> > 2014), Map(stationName -> 007026 9, year -> 2014), Map(stationName -> > 007026 9, year -> 2014), > etc... > {noformat} > > On the latest master and also on branch-2.3, the transformation compiles (at > least on spark-shell), but throws a ClassNotFoundException: > > {noformat} > scala> df.map(row => row.getValuesMap[Any](List("stationName", > "year"))).collect > java.lang.ClassNotFoundException: scala.Any > at > scala.reflect.internal.util.AbstractFileClassLoader.findClass(AbstractFileClassLoader.scala:62) > at java.lang.ClassLoader.loadClass(ClassLoader.java:424) > at java.lang.ClassLoader.loadClass(ClassLoader.java:357) > at java.lang.Class.forName0(Native Method) > at java.lang.Class.forName(Class.java:348) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.javaClass(JavaMirrors.scala:555) > at > scala.reflect.runtime.JavaMirrors$JavaMirror$$anonfun$classToJava$1.apply(JavaMirrors.scala:1211) > at > scala.reflect.runtime.JavaMirrors$JavaMirror$$anonfun$classToJava$1.apply(JavaMirrors.scala:1203) > at > scala.reflect.runtime.TwoWayCaches$TwoWayCache$$anonfun$toJava$1.apply(TwoWayCaches.scala:49) > at scala.reflect.runtime.Gil$class.gilSynchronized(Gil.scala:19) > at scala.reflect.runtime.JavaUniverse.gilSynchronized(JavaUniverse.scala:16) > at > scala.reflect.runtime.TwoWayCaches$TwoWayCache.toJava(TwoWayCaches.scala:44) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.classToJava(JavaMirrors.scala:1203) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.runtimeClass(JavaMirrors.scala:194) > at > scala.reflect.runtime.JavaMirrors$JavaMirror.runtimeClass(JavaMirrors.scala:54) > at > org.apache.spark.sql.catalyst.ScalaReflection$.getClassFromType(ScalaReflection.scala:700) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$dataTypeFor$1.apply(ScalaReflection.scala:84) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$dataTypeFor$1.apply(ScalaReflection.scala:65) > at > scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:56) > at > org.apache.spark.sql.catalyst.ScalaReflection$class.cleanUpReflectionObjects(ScalaReflection.scala:824) > at > org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:39) > at > org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$dataTypeFor(ScalaReflection.scala:64) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor$1.apply(ScalaReflection.scala:512) > at > org.apache.spark.sql.catalyst.ScalaReflection$$anonfun$org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor$1.apply(ScalaReflection.scala:445) > at > scala.reflect.internal.tpe.TypeConstraints$UndoLog.undo(TypeConstraints.scala:56) > at > org.apache.spark.sql.catalyst.ScalaReflection$class.cleanUpReflectionObjects(ScalaReflection.scala:824) > at > org.apache.spark.sql.catalyst.ScalaReflection$.cleanUpReflectionObjects(ScalaReflection.scala:39) > at > org.apache.spark.sql.catalyst.ScalaReflection$.org$apache$spark$sql$catalyst$ScalaReflection$$serializerFor(ScalaReflection.scala:445) >