Apply a logic for a particular column in dataframe in spark

I have a Dataframe and it has been imported from mysql

dataframe_mysql.show()
+----+---------+---------------------------------------------------+
|  id|accountid|                                            xmldata|
+----+---------+---------------------------------------------------+
|1001|    12346|<AccountSetup xmlns:xsi="test"><Customers test="...|
|1002|    12346|<AccountSetup xmlns:xsi="test"><Customers test="...|
|1003|    12346|<AccountSetup xmlns:xsi="test"><Customers test="...|
|1004|    12347|<AccountSetup xmlns:xsi="test"><Customers test="...|
+----+---------+---------------------------------------------------+

In the xmldata column there is xml tags inside, I need to parse it in a structured data in a seperate dataframe.

Previously I had the xml file alone in a text file, and loaded in a spark dataframe using "com.databricks.spark.xml"

spark-shell --packages com.databricks:spark-xml_2.10:0.4.1,com.databricks:spark-csv_2.10:1.5.0
val sqlContext =new org.apache.spark.sql.SQLContext(sc)
val df = sqlContext.read.format("com.databricks.spark.xml").option("rowTag","Account").load("../Account.xml")

the final output I got as structured one

df.show() +----------+--------------------+--------------------+-------------+.... |AcctNbr |AddlParties |Addresses |ApplicationIn|.... -----------+--------------------+--------------------+-------------+.... |AAAAAAAAAA|[[Securzxcdd cxcs...|[WrappedArray([D,...| T|.... +----------+--------------------+--------------------+-------------+....

Please advice how to achieve the this when I have the xml content inside a dataframe. I am new to spark and scala.