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Narine Kokhlikyan edited comment on SPARK-12922 at 2/22/16 5:47 PM: -------------------------------------------------------------------- thanks, for creating this jira, [~sunrui] Have you already started to work on this ? This most probably depends on, [https://issues.apache.org/jira/browse/SPARK-12792]. We need this as soon as possible and I might start working on this. Do you have any time estimation how long will it take to get [https://issues.apache.org/jira/browse/SPARK-12792] reviewed ? cc: [~shivaram] Thanks, Narine was (Author: narine): thanks, for creating this jira, [~sunrui] Have you already started to work on this ? This most probably depends on, [https://issues.apache.org/jira/browse/SPARK-12792]. We need this as soon as possible and I might start working on this ? Do you have any time estimation how long will it take to get [https://issues.apache.org/jira/browse/SPARK-12792] reviewed ? Thanks, Narine > 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(). -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org