16. Databricks | Spark | Pyspark | Bad Records Handling | Permissive;DropMalformed;FailFast

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Комментарии
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Very well presented, I am learning many things from your channel. Thanks for your efforts. Kindly upload all the datasets and code in Git repo for practice. Please create a similar playlist for synapse and ADF too.

ramanaswamy
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Instead of getting whole row data in separate column in permissive mode, can i get only that particular incorrect data
If possible, how??
Pls give me a solution

Daarko
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Can we find out the reason if there are a large number of columns as to why the records was corrupted?

mohitupadhayay
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Hi sir, I tried so many times but PERMISSIVE mode is not working, could you please share this notebook

Cskfans
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superb, How can we change bad records in to strucred like in the example aug month Produnits are thousand like we change and write 1000. could u please explain it

sravankumar
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Hi Sir,

But if we put integer value in string type column(ex.-in first_name column value like 54567), it does not consider that record as bad record using mode as PERMISSIVE. how to handle such bad records.

sachinchandanshiv
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I want to fix the character length while defining the schema how I can do that like interger I want only 3 characters allowed

mohammadzeeshan
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Thanks for video, plz zoom little bit more

kunsothvenkatesh
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Great explanation, Sir... Is it possible to use these corrupt records mode... for serialized files like parquet, avro -- Reads, Sir... ?
Thank you for your support and guidance, Sir...

gurumoorthysivakolunthu
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for those who cant get any mode to work check your data frame and file names correctly

devhashira
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Can we do this for XML files?
I googled but couldn't find anything on internet.

mohitupadhayay