Error using VectorAssembler after Pandas GROUPED_AGG UDF

Using VectorAssembler after a Pandas GROUPED_AGG and join causes an opaque error:

Caused by: java.lang.UnsupportedOperationException: Cannot evaluate expression: apply_impl(input[1, struct<t:bigint,val:bigint>, true].val)

However, inserting a .cache() between the VectorAssembler and join seems to prevent VectorAssembler & Pandas UDF from interacting to cause this error.

E py4j.protocol.Py4JJavaError: An error occurred while calling o259.collectToPython.
E : org.apache.spark.sql.catalyst.errors.package$TreeNodeException: execute, tree:
E Exchange hashpartitioning(foo_id_SummaryAggregator_AOG2FHR#34L, 4)
E +- *(4) Filter AtLeastNNulls(n, apply_impl(foo_explode_SummaryAggregator_AOG2FHR#20.val),apply_impl(foo_explode_SummaryAggregator_AOG2FHR#20.val))
E +- Generate explode(foo#11), foo_id_SummaryAggregator_AOG2FHR#34L, true, foo_explode_SummaryAggregator_AOG2FHR#20
E +- *(3) Project foo#11, monotonically_increasing_id() AS foo_id_SummaryAggregator_AOG2FHR#34L
E +- Scan ExistingRDDfoo#11,id#12L
{{E }}
E at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:56)
E at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.doExecute(ShuffleExchangeExec.scala:119)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:391)
E at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:121)
E at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.python.AggregateInPandasExec.doExecute(AggregateInPandasExec.scala:80)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.InputAdapter.inputRDDs(WholeStageCodegenExec.scala:391)
E at org.apache.spark.sql.execution.SortExec.inputRDDs(SortExec.scala:121)
E at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.InputAdapter.doExecute(WholeStageCodegenExec.scala:383)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.joins.SortMergeJoinExec.inputRDDs(SortMergeJoinExec.scala:386)
E at org.apache.spark.sql.execution.ProjectExec.inputRDDs(basicPhysicalOperators.scala:41)
E at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:627)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan.getByteArrayRdd(SparkPlan.scala:247)
E at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:296)
E at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3263)
E at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:3260)
E at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3370)
E at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
E at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
E at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
E at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3369)
E at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:3260)
E at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
E at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
E at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
E at java.lang.reflect.Method.invoke(Method.java:498)
E at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
E at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
E at py4j.Gateway.invoke(Gateway.java:282)
E at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
E at py4j.commands.CallCommand.execute(CallCommand.java:79)
E at py4j.GatewayConnection.run(GatewayConnection.java:238)
E at java.lang.Thread.run(Thread.java:748)
E Caused by: java.lang.UnsupportedOperationException: Cannot evaluate expression: apply_impl(input[1, struct<t:bigint,val:bigint>, true].val)
E at org.apache.spark.sql.catalyst.expressions.Unevaluable$class.doGenCode(Expression.scala:261)
E at org.apache.spark.sql.catalyst.expressions.PythonUDF.doGenCode(PythonUDF.scala:50)
E at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:108)
E at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:105)
E at scala.Option.getOrElse(Option.scala:121)
E at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:105)
E at org.apache.spark.sql.catalyst.expressions.AtLeastNNonNulls$$anonfun$4.apply(nullExpressions.scala:402)
E at org.apache.spark.sql.catalyst.expressions.AtLeastNNonNulls$$anonfun$4.apply(nullExpressions.scala:401)
E at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
E at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
E at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
E at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
E at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
E at scala.collection.AbstractTraversable.map(Traversable.scala:104)
E at org.apache.spark.sql.catalyst.expressions.AtLeastNNonNulls.doGenCode(nullExpressions.scala:401)
E at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:108)
E at org.apache.spark.sql.catalyst.expressions.Expression$$anonfun$genCode$2.apply(Expression.scala:105)
E at scala.Option.getOrElse(Option.scala:121)
E at org.apache.spark.sql.catalyst.expressions.Expression.genCode(Expression.scala:105)
E at org.apache.spark.sql.execution.FilterExec.org$apache$spark$sql$execution$FilterExec$$genPredicate$1(basicPhysicalOperators.scala:139)
E at org.apache.spark.sql.execution.FilterExec$$anonfun$13.apply(basicPhysicalOperators.scala:179)
E at org.apache.spark.sql.execution.FilterExec$$anonfun$13.apply(basicPhysicalOperators.scala:163)
E at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
E at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
E at scala.collection.immutable.List.foreach(List.scala:392)
E at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
E at scala.collection.immutable.List.map(List.scala:296)
E at org.apache.spark.sql.execution.FilterExec.doConsume(basicPhysicalOperators.scala:163)
E at org.apache.spark.sql.execution.CodegenSupport$class.consume(WholeStageCodegenExec.scala:189)
E at org.apache.spark.sql.execution.InputAdapter.consume(WholeStageCodegenExec.scala:374)
E at org.apache.spark.sql.execution.InputAdapter.doProduce(WholeStageCodegenExec.scala:403)
E at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:90)
E at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:85)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:85)
E at org.apache.spark.sql.execution.InputAdapter.produce(WholeStageCodegenExec.scala:374)
E at org.apache.spark.sql.execution.FilterExec.doProduce(basicPhysicalOperators.scala:125)
E at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:90)
E at org.apache.spark.sql.execution.CodegenSupport$$anonfun$produce$1.apply(WholeStageCodegenExec.scala:85)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.CodegenSupport$class.produce(WholeStageCodegenExec.scala:85)
E at org.apache.spark.sql.execution.FilterExec.produce(basicPhysicalOperators.scala:85)
E at org.apache.spark.sql.execution.WholeStageCodegenExec.doCodeGen(WholeStageCodegenExec.scala:544)
E at org.apache.spark.sql.execution.WholeStageCodegenExec.doExecute(WholeStageCodegenExec.scala:598)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
E at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
E at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
E at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
E at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.prepareShuffleDependency(ShuffleExchangeExec.scala:92)
E at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:128)
E at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
E at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
E ... 69 more