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https://issues.apache.org/jira/browse/BEAM-14383?focusedWorklogId=765049&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-765049
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ASF GitHub Bot logged work on BEAM-14383:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 02/May/22 17:06
Start Date: 02/May/22 17:06
Worklog Time Spent: 10m
Work Description: TheNeuralBit commented on PR #17517:
URL: https://github.com/apache/beam/pull/17517#issuecomment-1115130311
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Issue Time Tracking
-------------------
Worklog Id: (was: 765049)
Time Spent: 2h 20m (was: 2h 10m)
> Improve "FailedRows" errors returned by beam.io.WriteToBigQuery
> ---------------------------------------------------------------
>
> Key: BEAM-14383
> URL: https://issues.apache.org/jira/browse/BEAM-14383
> Project: Beam
> Issue Type: Improvement
> Components: io-py-gcp
> Reporter: Oskar Firlej
> Priority: P2
> Time Spent: 2h 20m
> Remaining Estimate: 0h
>
> `WriteToBigQuery` pipeline returns `errors` when trying to insert rows that
> do not match the BigQuery table schema. `errors` is a dictionary that
> cointains one `FailedRows` key. `FailedRows` is a list of tuples where each
> tuple has two elements: BigQuery table name and the row that didn't match the
> schema.
> This can be verified by running the `BigQueryIO deadletter pattern`
> https://beam.apache.org/documentation/patterns/bigqueryio/
> Using this approach I can print the failed rows in a pipeline. When running
> the job, logger simultaneously prints out the reason why the rows were
> invalid. The reason should also be included in the tuple in addition to the
> BigQuery table and the raw row. This way next pipeline could process both the
> invalid row and the reason why it is invalid.
> During my reasearch i found a couple of alternate solutions, but i think they
> are more complex than they need to be. Thats why i explored the beam source
> code and found the solution to be an easy and simple change.
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