Unable to read wild character by databricks

Question

Unable to read wild character by databricks

Shambhu Rai 1,411

hi expert, Databricks unable to read wild character in column available in CSV ...tried reading using utf, and ansi but not working that is Select col1 from table1 but column contains 'Säck' wild character

Sedat SALMAN 14,170 Reputation points MVP

2024-01-07T22:48:03.04+00:00

Azure Databricks provides options to handle malformed CSV records. In addition to trying different approaches to reading the CSV file, like read_files in SQL, you can experiment with the different modes (PERMISSIVE, DROPMALFORMED, FAILFAST) to handle malformed records, inspect problematic records using the _corrupt_record column or badRecordsPath option, and think about adjusting Java system properties related to encoding.

https://learn.microsoft.com/en-us/azure/databricks/query/formats/csv
Shambhu Rai 1,411 Reputation points

2024-01-07T23:09:31.8366667+00:00

Sir this question is related to databricks
Shambhu Rai 1,411 Reputation points

2024-01-07T23:11:16.13+00:00

Can you give one example please as I tried this but did not worked

Accepted answer

0 additional answers

Your answer

Sedat SALMAN 14,170 Reputation points MVP

2024-01-07T22:48:03.04+00:00

Azure Databricks provides options to handle malformed CSV records. In addition to trying different approaches to reading the CSV file, like read_files in SQL, you can experiment with the different modes (PERMISSIVE, DROPMALFORMED, FAILFAST) to handle malformed records, inspect problematic records using the _corrupt_record column or badRecordsPath option, and think about adjusting Java system properties related to encoding.

https://learn.microsoft.com/en-us/azure/databricks/query/formats/csv
Shambhu Rai 1,411 Reputation points

2024-01-07T23:09:31.8366667+00:00

Sir this question is related to databricks
Shambhu Rai 1,411 Reputation points

2024-01-07T23:11:16.13+00:00

Can you give one example please as I tried this but did not worked

Answer 1

hi I have added more detailed explanation to my previous answer

Azure Databricks offers different modes for handling malformed records when reading CSV files:

PERMISSIVE (default): Inserts nulls for fields that couldn't be parsed correctly.
DROPMALFORMED: Drops lines with fields that couldn't be parsed.
FAILFAST: Aborts reading if any malformed data is found.

as stated in the link

https://learn.microsoft.com/en-us/azure/databricks/query/formats/csv

you can set mode and encoding at the same time

df = (spark.read
      .format("csv")
      .option("mode", "PERMISSIVE")  # Set the mode for handling malformed records
      .option("charset", "UTF-8")    # Set the encoding
      .load("path_to_your_csv_file"))

Share via

Unable to read wild character by databricks

0 additional answers

Your answer