Hi, I am using spark sql in a way like this: sqlContext.sql(“select * from table limit 10000”).map(...).collect()
The problem is that the limit clause will collect all the 10,000 records into a single partition, resulting the map afterwards running only in one partition and being really slow.I tried to use repartition, but it is kind of a waste to collect all those records into one partition and then shuffle them around and then collect them again. Is there a way to work around this? BTW, there is no order by clause and I do not care which 10000 records I get as long as the total number is less or equal then 10000.
