We were getting incorrect results from the DataFrame except method - all rows were being returned instead of the ones that intersected. Calling subtract on the underlying RDD returned the correct result.
We tracked it down to the use of coalesce - the following is the simplest example case we created that reproduces the issue:
val schema = new StructType().add("test", types.IntegerType )
val t1 = sql.createDataFrame(sql.sparkContext.parallelize(1 to 100).map(i=> Row(i)), schema)
val t2 = sql.createDataFrame(sql.sparkContext.parallelize(5 to 10).map(i=> Row(i)), schema)
val t3 = t1.join(t2, t1.col("test").equalTo(t2.col("test")), "leftsemi")
println("Count using normal except = " + t1.except(t3).count())
println("Count using coalesce = " + t1.coalesce(8).except(t3.coalesce(8)).count())
We should get the same result from both uses of except, but the one using coalesce returns 100 instead of 94.