Special character handling for file processing

Question

Hello,

I have some CSV files as feeds into datalake storage, this file will contain data /records with some special characters eg '/'

We need to process the file from one container to another and we will need to remove some of the these special characters kind of transformation. Likely it can be done via databricks. Is there any limitations to handle these special characters through datalake or databricks for the processing.

Answer 1

Hello Sourav,

Thanks for posting your question in the Microsoft Q&A forum.

Azure Data Lake Storage can store files containing any type of character, including special characters like '/'. There are no specific limitations or restrictions on the characters that can be present in the files stored in Data Lake Storage.

Databricks supports processing files with special characters, including CSV files. When reading CSV files into Databricks using Spark, you can specify appropriate options to handle special characters. For example, setting the multiLine option to true allows handling CSV files that contain newline characters within fields. Databricks also provides various string manipulation functions (e.g., replace, trim, regexp_replace) that can be used to remove or transform special characters as needed.

In Databricks, you can use Spark DataFrame transformations or SQL queries to remove or transform special characters in your data. For instance, you can use the replace function to remove the '/' character from specific columns or use regular expressions with the regexp_replace function for more complex transformations.

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