I don't have the exact answer for you but I would look for something using explode method on DataFrame  

On Thu, Dec 24, 2015 at 7:34 AM Bharathi Raja <rajakbv@yahoo.com> wrote:
Thanks Gokul, but the file I have had the same format as I have mentioned. First two columns are not in Json format.

Thanks,
Raja

From: Gokula Krishnan D
Sent: ‎12/‎24/‎2015 2:44 AM
To: Eran Witkon
Cc: raja kbv; user@spark.apache.org

Subject: Re: How to Parse & flatten JSON object in a text file using Spark &Scala into Dataframe

You can try this .. But slightly modified the  input structure since first two columns were not in Json format. 

Inline image 1

Thanks & Regards, 
Gokula Krishnan (Gokul)

On Wed, Dec 23, 2015 at 9:46 AM, Eran Witkon <eranwitkon@gmail.com> wrote:
Did you get a solution for this?

On Tue, 22 Dec 2015 at 20:24 raja kbv <rajakbv@yahoo.com.invalid> wrote:
Hi,

I am new to spark.

I have a text file with below structure.

 
(employeeID: Int, Name: String, ProjectDetails: JsonObject{[{ProjectName, Description, Duriation, Role}]})
Eg:
(123456, Employee1, {“ProjectDetails”:[
                                                         { “ProjectName”: “Web Develoement”, “Description” : “Online Sales website”, “Duration” : “6 Months” , “Role” : “Developer”}
                                                         { “ProjectName”: “Spark Develoement”, “Description” : “Online Sales Analysis”, “Duration” : “6 Months” , “Role” : “Data Engineer”}
                                                         { “ProjectName”: “Scala Training”, “Description” : “Training”, “Duration” : “1 Month” }
                                                          ]
                                                }
 
 
Could someone help me to parse & flatten the record as below dataframe using scala?
 
employeeID,Name, ProjectName, Description, Duration, Role
123456, Employee1, Web Develoement, Online Sales website, 6 Months , Developer
123456, Employee1, Spark Develoement, Online Sales Analysis, 6 Months, Data Engineer
123456, Employee1, Scala Training, Training, 1 Month, null
 

Thank you in advance.

Regards,
Raja