topic How to find CSV issue? in Knowledge Management

How to find CSV issue?

andrew_burnett — Thu, 30 Mar 2023 15:47:33 GMT

We have error messages like " Corrupt csv header in CSV file , 2 columns with the same name 'Severity" & CSV file contains invalid field ''. How do I find this? My SHC has hundreds of CSV files, so it is hard to find issues even with grep.

Re: How to find CSV issue?

richgalloway — Thu, 30 Mar 2023 18:54:23 GMT

I've only seen those messages in search results so it's pretty easy to check the few lookups in my search. It becomes more difficult when there are automatic lookups to check. The search log should have more information, though.

Re: How to find CSV issue?

andrew_burnett — Thu, 30 Mar 2023 18:56:06 GMT

It's not in the search results as I get it, rather it's tracked by Mongo and that is how we're seeing it. So I don't have search.log indexed into Splunk and therefore have no visibility.

Re: How to find CSV issue?

richgalloway — Thu, 30 Mar 2023 20:44:17 GMT

I'm not sure what you mean by "tracked by Mongo". If there a corrupt KVStore lookup then you should be able to scan your collections.conf files for duplicate names, but would think problems there would be reported differently..

Re: How to find CSV issue?

stevediaz — Fri, 22 Sep 2023 10:35:03 GMT

Hello

To find and fix CSV header errors in multiple files, write a script to check for duplicate column names and invalid fields in the header row. Then, run the script on your CSV file directory.

For Python, a basic example might look like this:

import csv
import os

def check_csv_headers(file_path):
with open(file_path, 'r') as csvfile:
csvreader = csv.DictReader(csvfile)
headers = csvreader.fieldnames
if len(headers) != len(set(headers)):
print(f"Duplicate columns in: {file_path}")
if '' in headers:
print(f"Invalid field name in: {file_path}")

# Directory containing CSV files
directory = '/path/to/csv/files'

for filename in os.listdir(directory):
if filename.endswith('.csv'):
file_path = os.path.join(directory, filename)
check_csv_headers(file_path)

Save the script to a file, make it executable (if needed), and run it against your directory containing the CSV files.

python check_csv_headers.py

This approach automates the process of scanning your CSV files for errors and should help you efficiently locate and fix these issues across multiple files within your Splunk Heavy Forwarder.

You can also check https://community.splunk.com/t5/Knowledge-Management/bd-p/knowledge-management/CCSP Certification

Thank you