I fear the issue is that this will create and destroy a XML parser object 2 mio times, which is very inefficient - it does not really look like a parser performance issue. Can't you do something about the format choice? Ask your supplier to deliver another format (ideally avro or sth like this?)?
Otherwise you could just create one XML Parser object / node, but sharing this among the parallel tasks on the same node is tricky.
The other possibility could be simply more hardware ...

On 20 Aug 2016, at 06:41, Diwakar Dhanuskodi <diwakar.dhanuskodi@gmail.com> wrote:

Yes . It accepts a xml file as source but not RDD. The XML data embedded  inside json is streamed from kafka cluster.  So I could get it as RDD. 
Right  now  I am using  spark.xml  XML.loadstring method inside  RDD map function  but  performance  wise I am not happy as it takes 4 minutes to parse XML from 2 million messages in a 3 nodes 100G 4 cpu each environment. 


Sent from Samsung Mobile.


-------- Original message --------
From: Felix Cheung <felixcheung_m@hotmail.com>
Date:20/08/2016 09:49 (GMT+05:30)
To: Diwakar Dhanuskodi <diwakar.dhanuskodi@gmail.com>, user <user@spark.apache.org>
Cc:
Subject: Re: Best way to read XML data from RDD

Have you tried

https://github.com/databricks/spark-xml
?




On Fri, Aug 19, 2016 at 1:07 PM -0700, "Diwakar Dhanuskodi" <diwakar.dhanuskodi@gmail.com> wrote:

Hi, 

There is a RDD with json data. I could read json data using rdd.read.json . The json data has XML data in couple of key-value paris. 

Which is the best method to read and parse XML from rdd. Is there any specific xml libraries for spark. Could anyone help on this.

Thanks.