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https://issues.apache.org/jira/browse/SPARK-12919?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Shivaram Venkataraman resolved SPARK-12919.
-------------------------------------------
Resolution: Fixed
Fix Version/s: 2.0.0
Issue resolved by pull request 12493
[https://github.com/apache/spark/pull/12493]
> Implement dapply() on DataFrame in SparkR
> -----------------------------------------
>
> Key: SPARK-12919
> URL: https://issues.apache.org/jira/browse/SPARK-12919
> Project: Spark
> Issue Type: Sub-task
> Components: SparkR
> Affects Versions: 1.6.0
> Reporter: Sun Rui
> Fix For: 2.0.0
>
>
> dapply() applies an R function on each partition of a DataFrame and returns a
> new DataFrame.
> The function signature is:
> {code}
> dapply(df, function(localDF) {}, schema = NULL)
> {code}
> R function input: local data.frame from the partition on local node
> R function output: local data.frame
> Schema specifies the Row format of the resulting DataFrame. It must match the
> R function's output.
> If schema is not specified, each partition of the result DataFrame will be
> serialized in R into a single byte array. Such resulting DataFrame can be
> processed by successive calls to dapply() or collect(), but can't be
> processed by normal DataFrame operations.
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