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If you’re working with an AWS Glue ETL job in Python and trying to update records in Salesforce based on data retrieved from a Snowflake table, you might encounter an error like this: “Error Category: UNCLASSIFIED_ERROR; Failed Line Number: 25; An error occurred while calling o170.pyWriteDynamicFrame. Index 0 out of bounds for length 0.”
Here’s a straightforward way to troubleshoot and fix this issue:
First, ensure your Snowflake query is returning the expected data. You mentioned it returns one record with an Id that exists in Salesforce. Confirm this by logging the output instead of assuming. When you load the data into a DynamicFrame and perform renaming, check it still contains data by printing its contents or converting it to a list.
Next, pay attention to how field names are handled during the renaming process. In your script, you’re using quotes around field names like "Other field"
and "Id"
. When you rename these fields, do not include quotes around the new field names. For example:
python
Snowflake_source = Snowflake_source.rename_field(“\”Other field\””, “Other_Field__c”).rename_field(“\”Id\””, “Id”)
This might cause issues because the quotes are part of the string, which could lead to mismatches or empty data being sent to Salesforce.
It’s usually better to rename fields without quotes, like this:
python
Snowflake_source = Snowflake_source.rename_field(“Other field”, “Other_Field__c”).rename_field(“Id”, “Id”)
Additionally, when sending data to Salesforce, make sure the field names match exactly what Salesforce expects. Including quotes in field names when defining connection_options
can cause problems. In your code, you’re passing the renamed fields directly, but if the field names in the data don’t exactly match the Salesforce object schema, the write operation may fail silently or produce empty requests.
Another thing to check is how the data types are handled. Since your Snowflake timestamp is being sent to Salesforce, converting it to a string explicitly before renaming or transferring might help avoid format issues.
To summarize:
- Confirm your Snowflake query returns the expected data.
- Avoid adding quotes around field names during renaming.
- Ensure the field names you send match Salesforce field names exactly.
- Convert date/time fields to string format if necessary before sending.
- Log the data right before the write operation to verify the contents.
Following these steps should help resolve the indexing error and ensure your data updates in Salesforce smoothly.