topic Re: Incorrect reading csv format with inferSchema in Data Engineering

Incorrect reading csv format with inferSchema

Tracy_ — Wed, 01 Feb 2023 05:16:53 GMT

Hi All,

There is a CSV with a column ID (format: 8-digits & "D" at the end).

When trying to read a csv with .option("inferSchema", "true"), it returns the ID as double and trim the "D". Is there any idea (apart from inferSchema=False) to get correct result? Thanks for help!

Below options was tried and also failed.

options(delimiter=",", sep = ",", header=True, inferSchema=True,multiline=True, quote="\"", escape="\"")

Re: Incorrect reading csv format with inferSchema

Ajay-Pandey — Wed, 01 Feb 2023 07:17:22 GMT

Hi @tracy ng

By default, spark treating as a double value for all the numbers ending with D or F

I think you should connect with databricks regarding this.

Re: Incorrect reading csv format with inferSchema

Hubert-Dudek — Wed, 01 Feb 2023 09:33:58 GMT

It can be solved, for example, by specifying the schema with ID as string.

If you don't want to specify schema, better would be autoloader as you can specify hint:

spark.readStream
  .format("cloudFiles")
  .option("cloudFiles.format", "csv")
  .option("cloudFiles.schemaLocation", checkpoint_path)
  .option("cloudFiles.schemaHints", "ID String")
  .option("inferSchema", True)
  .option("mergeSchema", True)
  .load(folder)

Re: Incorrect reading csv format with inferSchema

Tracy_ — Thu, 02 Feb 2023 02:49:29 GMT

Thanks @Ajay Pandey.

Re: Incorrect reading csv format with inferSchema

Tracy_ — Thu, 02 Feb 2023 02:56:41 GMT

Thanks @Hubert Dudek ,

Becasue the reading file is used to loop different source from different directory with different schema and dynamic column name (sometimes named ID, sometime named SID etc.), it seems the autoloader is not applicable to the case. I wonder is there any option to disable this feature (treating column as double when there is trailing D).

Re: Incorrect reading csv format with inferSchema

Anonymous — Tue, 11 Apr 2023 04:52:21 GMT

Hi @tracy ng

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