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Revert workaround in SparkR to retain grouped cols #15

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Merged
merged 1 commit into from
May 8, 2015
Merged

Revert workaround in SparkR to retain grouped cols #15

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4 changes: 1 addition & 3 deletions R/pkg/R/group.R
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Original file line number Diff line number Diff line change
Expand Up @@ -103,9 +103,7 @@ setMethod("agg",
}
}
jcols <- lapply(cols, function(c) { c@jc })
# the GroupedData.agg(col, cols*) API does not contain grouping Column
sdf <- callJStatic("org.apache.spark.sql.api.r.SQLUtils", "aggWithGrouping",
x@sgd, listToSeq(jcols))
sdf <- callJMethod(x@sgd, "agg", jcols[[1]], listToSeq(jcols[-1]))
} else {
stop("agg can only support Column or character")
}
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11 changes: 0 additions & 11 deletions sql/core/src/main/scala/org/apache/spark/sql/api/r/SQLUtils.scala
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Expand Up @@ -72,17 +72,6 @@ private[r] object SQLUtils {
sqlContext.createDataFrame(rowRDD, schema)
}

// A helper to include grouping columns in Agg()
def aggWithGrouping(gd: GroupedData, exprs: Column*): DataFrame = {
val aggExprs = exprs.map { col =>
col.expr match {
case expr: NamedExpression => expr
case expr: Expression => Alias(expr, expr.simpleString)()
}
}
gd.toDF(aggExprs)
}

def dfToRowRDD(df: DataFrame): JavaRDD[Array[Byte]] = {
df.map(r => rowToRBytes(r))
}
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