First I believe you mean on the Dataset API rather than the dataframe API. You can easily add the partition index as a new column to your dataframe using spark_partition_id() Then a normal mapPartitions should work fine (i.e. you should create the appropriate case class which includes the partition id and then do mapPartitions).
Thanks, Assaf. From: Lalwani, Jayesh [mailto:jayesh.lalw...@capitalone.com] Sent: Thursday, August 03, 2017 5:20 PM To: email@example.com Subject: mapPartitioningWithIndex in Dataframe Are there any plans to add mapPartitioningWithIndex in the Dataframe API? Or is there any way to implement my own mapPartitionWithIndex for a Dataframe? I am implementing something which is logically similar to the randomSplit function. In 2.1, randomSplit internally does df.mapPartitionWithIndex and assigns a different seed for every partition by adding the partition’s index to the seed. I want to get a partition specific seed too. The problem is rdd.mapPartitionWithIndex doesn’t work in streaming. df.mapPartition works, but I don’t get index. Is there a way to extend Spark to add mapPartitionWithIndex at the Dataframe level ? I was digging into the 2.2 code a bit and it looks like in 2.2, all the Dataframe apis have been changed to be based around SparkStrategy. I couldn’t figure out how I can add my own custom strategy. Is there any documentation around this? If it makes sense to add this to Spark, I would be excited to make a contribution. ________________________________ The information contained in this e-mail is confidential and/or proprietary to Capital One and/or its affiliates and may only be used solely in performance of work or services for Capital One. The information transmitted herewith is intended only for use by the individual or entity to which it is addressed. If the reader of this message is not the intended recipient, you are hereby notified that any review, retransmission, dissemination, distribution, copying or other use of, or taking of any action in reliance upon this information is strictly prohibited. If you have received this communication in error, please contact the sender and delete the material from your computer.