You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@beam.apache.org by "Brian Hulette (Jira)" <ji...@apache.org> on 2021/11/16 22:30:00 UTC

[jira] [Created] (BEAM-13266) DataFrame API errors should identify culprit operation in user code

Brian Hulette created BEAM-13266:
------------------------------------

             Summary: DataFrame API errors should identify culprit operation in user code
                 Key: BEAM-13266
                 URL: https://issues.apache.org/jira/browse/BEAM-13266
             Project: Beam
          Issue Type: Improvement
          Components: dsl-dataframe
            Reporter: Brian Hulette


The DataFrame API aims to catch errors in pipeline code at pipeline construction time as much as possible. Ideally, flawed user code will be caught during proxy generation and bubble up an error from pandas.

However, there are edge cases where DataFrame operations validate at construction time, but  still produce errors at execution time, based on the actual data. For example a user might try to use the modulo operator on a string  column. This is a valid operation, but it performs string interpolation, not a modulo as the user intended.

The above situation will raise an error at execution time, but it has a very obtuse stacktrace, with a tree of evaluate/evaluate_at calls. The culprit from the user's code is nowhere in the astacktrace.

We should catch errors like this at execution time and add a pointer to the line in the user's
code that created this expression. We'll likely need to add this metadata to DataFrame expressions.




--
This message was sent by Atlassian Jira
(v8.20.1#820001)