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https://issues.apache.org/jira/browse/SPARK-32159?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-32159:
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Fix Version/s: (was: 3.0.1)
Target Version/s: 3.0.1
> New udaf(Aggregator) has an integration bug with UnresolvedMapObjects
> serialization
> -----------------------------------------------------------------------------------
>
> Key: SPARK-32159
> URL: https://issues.apache.org/jira/browse/SPARK-32159
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Erik Erlandson
> Priority: Major
>
> The new user defined aggregator feature (SPARK-27296) based on calling
> 'functions.udaf(aggregator)' works fine when the aggregator input type is
> atomic, e.g. 'Aggregator[Double, _, _]', however if the input type is an
> array, like 'Aggregator[Array[Double], _, _]', it is tripping over the
> following:
> /**
> * When constructing [[MapObjects]], the element type must be given, which
> may not be available
> * before analysis. This class acts like a placeholder for [[MapObjects]],
> and will be replaced by
> * [[MapObjects]] during analysis after the input data is resolved.
> * Note that, ideally we should not serialize and send unresolved expressions
> to executors, but
> * users may accidentally do this(e.g. mistakenly reference an encoder
> instance when implementing
> * Aggregator). Here we mark `function` as transient because it may reference
> scala Type, which is
> * not serializable. Then even users mistakenly reference unresolved
> expression and serialize it,
> * it's just a performance issue(more network traffic), and will not fail.
> */
> case class UnresolvedMapObjects(
> {color:#de350b}@transient function: Expression => Expression{color},
> child: Expression,
> customCollectionCls: Option[Class[_]] = None) extends UnaryExpression with
> Unevaluable {
> override lazy val resolved = false
> override def dataType: DataType =
> customCollectionCls.map(ObjectType.apply).getOrElse
> { throw new UnsupportedOperationException("not resolved") }
> }
>
> *The '@transient' is causing the function to be unpacked as 'null' over on
> the executors, and it is causing a null-pointer exception here, when it tries
> to do 'function(loopVar)'*
> object MapObjects {
> def apply(
> function: Expression => Expression,
> inputData: Expression,
> elementType: DataType,
> elementNullable: Boolean = true,
> customCollectionCls: Option[Class[_]] = None): MapObjects =
> { val loopVar = LambdaVariable("MapObject", elementType, elementNullable)
> MapObjects(loopVar, {color:#de350b}function(loopVar){color}, inputData,
> customCollectionCls) }
> }
> *I believe it may be possible to just use 'loopVar' instead of
> 'function(loopVar)', whenever 'function' is null, but need second opinion
> from catalyst developers on what a robust fix should be*
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