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https://issues.apache.org/jira/browse/SPARK-17416?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Daniel Shields updated SPARK-17416:
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Description:
I propose that the following overload be added to Dataset[T]:
def groupByKey[K, V](keyFunc: T => K, valueFunc: T => V)(implicit arg0:
Encoder[K], arg1: Encoder[V])
This would simplify a number of use cases. For example, consider the following
classic MapReduce query:
rdd.flatMap(f).reduceByKey(g) // where f returns a list of tuples
An idiomatic way to write this with Spark 2.0 would be:
dataset.flatMap(f).groupByKey(_._1, _._2).reduceGroups(g)
Without the groupByKey overload suggested above, this must be written as:
dataset.flatMap(f).groupByKey(_._1).reduceGroups((a, b) => g(a._2, b._2))
was:
I propose that the following overload be added to Dataset[T]:
def groupByKey[K, V](keyFunc: T => K, valueFunc: T => V)(implicit arg0:
Encoder[K], implicit arg1: Encoder[V])
This would simplify a number of use cases. For example, consider the following
classic MapReduce query:
rdd.flatMap(f).reduceByKey(g) // where f returns a list of tuples
An idiomatic way to write this with Spark 2.0 would be:
dataset.flatMap(f).groupByKey(_._1, _._2).reduceGroups(g)
Without the groupByKey overload suggested above, this must be written as:
dataset.flatMap(f).groupByKey(_._1).reduceGroups((a, b) => g(a._2, b._2))
> Add Dataset.groupByKey overload that takes a value selector function
> --------------------------------------------------------------------
>
> Key: SPARK-17416
> URL: https://issues.apache.org/jira/browse/SPARK-17416
> Project: Spark
> Issue Type: New Feature
> Reporter: Daniel Shields
>
> I propose that the following overload be added to Dataset[T]:
> def groupByKey[K, V](keyFunc: T => K, valueFunc: T => V)(implicit arg0:
> Encoder[K], arg1: Encoder[V])
> This would simplify a number of use cases. For example, consider the
> following classic MapReduce query:
> rdd.flatMap(f).reduceByKey(g) // where f returns a list of tuples
> An idiomatic way to write this with Spark 2.0 would be:
> dataset.flatMap(f).groupByKey(_._1, _._2).reduceGroups(g)
> Without the groupByKey overload suggested above, this must be written as:
> dataset.flatMap(f).groupByKey(_._1).reduceGroups((a, b) => g(a._2, b._2))
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