[jira] [Created] (SPARK-12922) Implement gapply() on DataFrame in SparkR

["Sun Rui (JIRA)" <ji...@apache.org>]

Sun Rui created SPARK-12922:
-------------------------------

             Summary: Implement gapply() on DataFrame in SparkR
                 Key: SPARK-12922
                 URL: https://issues.apache.org/jira/browse/SPARK-12922
             Project: Spark
          Issue Type: Sub-task
          Components: SparkR
    Affects Versions: 1.6.0
            Reporter: Sun Rui


gapply() applies an R function on groups grouped by one or more columns of a DataFrame, and returns a DataFrame. It is like GroupedDataSet.flatMapGroups() in the Dataset API.

Two API styles are supported:
1.
{code}
gd <- groupBy(df, col1, ...)
gapply(gd, function(grouping_key, group) {}, schema)
{code}
2.
{code}
gapply(df, grouping_columns, function(grouping_key, group) {}, schema) 
{code}

R function input: grouping keys value
		           a local data.frame of this grouped data 
R function output: local data.frame

Schema specifies the Row format of the output of the R function. It must match the R function's output.

Note that map-side combination (partial aggregation) is not supported, user could do map-side combination via dapply().





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