Split one column value to multiple columns using tExtractDelimitedFields Talend Open Studio
In the earlier post here, I have shown, How to split column values to multiple records using tNormalize component. In this post, I will show you, How to extract value of single column into multiple columns in Talend Open studio using tExtractDelimitedFields component.
Job Design:
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)
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)
Input File:
emp_no;emp_name;emp_skills
101;Avinash Gupta;java,C++,sql
102;Vikas Gupta;oracle,HTML,JSP,AJAX
103;Mayank Arora;Talend,Abinitio,OBIEE
Input in run console
![](data:image/png;base64,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)
Notice there are only three column in Input.
Output in Run console
![](data:image/png;base64,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)
In the output we have split values of skills column to multiple skill columns in output.
Component properties of tExtractDelimitedFields component
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In the earlier post here, I have shown, How to split column values to multiple records using tNormalize component. In this post, I will show you, How to extract value of single column into multiple columns in Talend Open studio using tExtractDelimitedFields component.
Job Design:
Input File:
emp_no;emp_name;emp_skills
101;Avinash Gupta;java,C++,sql
102;Vikas Gupta;oracle,HTML,JSP,AJAX
103;Mayank Arora;Talend,Abinitio,OBIEE
Input in run console
Notice there are only three column in Input.
Output in Run console
In the output we have split values of skills column to multiple skill columns in output.
Component properties of tExtractDelimitedFields component
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Good job vikram, may i know how to create duplicate rows of a file based of certain constraints.
ReplyDeleteThanks Sajish, I would be happy to answer you.
DeleteRequest you to provide more details for ur query. It would be helpful if you can explain with example.
Hi Sir
ReplyDeleteIf the skill count comming from source is unknow like a person might have 10 skills then how to handle this,Please help me out.
Thanks
Deepthi
Hello sir,
ReplyDeleteWhat if we want to split two column at same time. Like here in your example emp skills. But what we can do if want to split emp_skills as well as emp_name(into firstName and lastName)?
Thanks,
kunj