如何在Spark / Hive中将大部分数据合并到单个目录中

Question

I have a requirement, Huge data is partitioned and inserting it into Hive.To bind this data, I am using DF.Coalesce(10) . Now i want to bind this portioned data to single directory, if I use DF.Coalesce(1) will the performance decrease? or do I have any other process to do so?

Answer 1

From what I understand is that you are trying to ensure that there are less no of files per partition. So, by using coalesce(10) , you will get max 10 files per partition. I would suggest using repartition($"COL") , here COL is the column used to partition the data. This will ensure that your "huge" data is split based on the partition column used in HIVE. df.repartition($"COL")