Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/8450#issuecomment-149068999
@marmbrus Actually there are some other existed DF APIs like:
```scala
def select(col: String, cols: String*)
def groupBy(col1: String, cols: String*)
def rollup(col1: String, cols: String*)
def orderBy(sortCol: String, sortCols: String*)
// So people can write code like:
df.select("a", "b", "c")
df.groupBy("a", "b", "c")
df.rollup("a", "b", "c")
df.orderBy("a", "b", "c")
...
```
But the definition of dropDuplicates / join are like:
```scala
def dropDuplicates(colNames: Seq[String])
def dropDuplicates(colNames: Array[String])
def join(right: DataFrame, usingColumns: Seq[String])
// Then people will write code like:
df.dropDuplicates(Seq("a", "b", "c"))
df.dropDuplicates(Array("a", "b", "c"))
df.join(otherDF, Seq("a", "b", "c"))
```
I was thinking to make the same accessing pattern for user, not sure if you
have any other concern.
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