Hi,
I am posed with an elementary level issue. The requirement is to read multiple files with similar schemas and load into a table. The problem is that each of these files have column names as header.
When I try reading all the files of a specific pattern using the 'FILE PATTERN' property in the Sequential File stage, all but the header of the first file appear as part of the data. The data looks something like
a,b,c,d,e
c,v,b,n,n
COL1,COL2,COL3,COL4,COL5
a,d,g,h,s
COL1,COL2,COL3,COL4,COL5
a,c,v,b,n
q,e,w,q,s
The 'First Name iS Column Name' property has been set to true. I want the data to be read without the column names
Reading Multiple Flat Files with Headers using File Pattern
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Reading Multiple Flat Files with Headers using File Pattern
Jerome
Data Integration Consultant at AWS
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Life is really simple, but we insist on making it complicated.
Data Integration Consultant at AWS
Connect With Me On LinkedIn
Life is really simple, but we insist on making it complicated.
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The number of files will vary everyday. We are performing validations on a per-file basis based on the suffix of the file.
Jerome
Data Integration Consultant at AWS
Connect With Me On LinkedIn
Life is really simple, but we insist on making it complicated.
Data Integration Consultant at AWS
Connect With Me On LinkedIn
Life is really simple, but we insist on making it complicated.
Re: Reading Multiple Flat Files with Headers using File Patt
The same kind of topic has already been discussed.
Please check whether the solution can help you to resolve your problem.
[url]viewtopic.php?t=125243&highlight=removing+header[/url]
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Pons
Please check whether the solution can help you to resolve your problem.
[url]viewtopic.php?t=125243&highlight=removing+header[/url]
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Pons
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Thank you. Alternatives provided at viewtopic.php?t=125243&highlight=removing+header were useful
Jerome
Data Integration Consultant at AWS
Connect With Me On LinkedIn
Life is really simple, but we insist on making it complicated.
Data Integration Consultant at AWS
Connect With Me On LinkedIn
Life is really simple, but we insist on making it complicated.