Github user falaki commented on a diff in the pull request:
https://github.com/apache/spark/pull/10118#discussion_r46514167
--- Diff: R/pkg/R/DataFrame.R ---
@@ -822,21 +822,21 @@ setMethod("collect",
# Get a column of complex type returns a list.
# Get a cell from a column of complex type returns a list
instead of a vector.
col <- listCols[[colIndex]]
- colName <- dtypes[[colIndex]][[1]]
if (length(col) <= 0) {
- df[[colName]] <- col
+ df[[colIndex]] <- col
} else {
colType <- dtypes[[colIndex]][[2]]
# Note that "binary" columns behave like complex types.
if (!is.null(PRIMITIVE_TYPES[[colType]]) && colType !=
"binary") {
vec <- do.call(c, col)
stopifnot(class(vec) != "list")
- df[[colName]] <- vec
+ df[[colIndex]] <- vec
} else {
- df[[colName]] <- col
+ df[[colIndex]] <- col
}
}
}
+ names(df) <- names(x)
--- End diff --
This is slightly different from 1.5. We will get exact same column names in
local data.frame. In Spark 1.5 subsequent instances of the same name are
appended with numbers. I am not sure which one is better. In fact I slightly
prefer your suggested behavior. But just in case others want to chime in: cc
@shivaram
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