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Hi team,
Please help me to ingest below data in data lake through file upload method
Sample file in below records:
PName | Birthdate |
Jery|doll | 2023-03-10T18:56:41+00:00|2023-08-10T18:56:41+00:00 |
Tom|Marry | 2023-05-10T18:56:41+00:00|2023-08-10T18:56:41+00:00 |
on below schema for reference schema structure for reference:
Please provide the suggestion or guide me on the same.
We are expecting to getting similar records at dataset level:
PName | Birthdate |
Jery|doll | 2023-03-10T18:56:41+00:00|2023-08-10T18:56:41+00:00 |
Tom|Marry | 2023-05-10T18:56:41+00:00|2023-08-10T18:56:41+00:00 |
Regards,
Sandip
해결되었습니다! 솔루션으로 이동.
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Hello, @sandip_surse
This solution will suit your needs:
Transform the arrays using the following method:
arrays_to_objects("birthDate", explode(Birthdate, "\|"), "XYZName", explode(PName, "\|"))
I couldn't find the correct name for the 'Name' field in your schema, so I used 'XYZName' as a placeholder above.
Once you've completed this step, kindly map it directly to the object array. Make sure to remove [0] from the data mapping.
Thanks,
Arpan
Please confirm a proper file format (.Parquet or JSON) for manual file uploads, not csv.
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For source connector Local File Upload, make sure you enable Error diagnostics to generate detailed error messages, then check for errors on failed ingestion status.
Please review docs:
https://experienceleague.adobe.com/docs/experience-platform/sources/connectors/local-system/local-fi...
https://experienceleague.adobe.com/docs/experience-platform/dataflows/ui/monitor-sources.html?lang=e...
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Hello, @sandip_surse
This solution will suit your needs:
Transform the arrays using the following method:
arrays_to_objects("birthDate", explode(Birthdate, "\|"), "XYZName", explode(PName, "\|"))
I couldn't find the correct name for the 'Name' field in your schema, so I used 'XYZName' as a placeholder above.
Once you've completed this step, kindly map it directly to the object array. Make sure to remove [0] from the data mapping.
Thanks,
Arpan
Thanks Arpan,
We are used similar way one more data prep function and now issue get fixed thanks...
to_array(true,split(attribute_Name,"|")
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