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Posted to issues@beam.apache.org by "ASF GitHub Bot (Jira)" <ji...@apache.org> on 2020/08/24 09:05:00 UTC
[jira] [Work logged] (BEAM-10524) Default decoder for
ReadFromBigQuery does not support repeatable fields
[ https://issues.apache.org/jira/browse/BEAM-10524?focusedWorklogId=473793&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-473793 ]
ASF GitHub Bot logged work on BEAM-10524:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 24/Aug/20 09:04
Start Date: 24/Aug/20 09:04
Worklog Time Spent: 10m
Work Description: kamilwu opened a new pull request #12671:
URL: https://github.com/apache/beam/pull/12671
A user reported failures in decoding fields with "REPEATED" mode while using `ReadFromBigQuery` transform with `use_json_exports` set to `True`.
------------------------
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Issue Time Tracking
-------------------
Worklog Id: (was: 473793)
Remaining Estimate: 0h
Time Spent: 10m
> Default decoder for ReadFromBigQuery does not support repeatable fields
> -----------------------------------------------------------------------
>
> Key: BEAM-10524
> URL: https://issues.apache.org/jira/browse/BEAM-10524
> Project: Beam
> Issue Type: Bug
> Components: sdk-py-core
> Affects Versions: 2.23.0
> Reporter: Roman Frigg
> Assignee: Kamil Wasilewski
> Priority: P2
> Time Spent: 10m
> Remaining Estimate: 0h
>
> The code in [https://github.com/apache/beam/blob/master/sdks/python/apache_beam/io/gcp/bigquery.py#L570]
> handles decoding fields with mode "REPEATABLE" incorrectly. This bug leads to the following stack trace when running a query that returns results with repeatable fields represented as JSON arrays. The corresponding stack trace looks as follows:
> {noformat}
> ...
> File "apache_beam/runners/common.py", line 1095, in apache_beam.runners.common._OutputProcessor.process_outputs
> File "/Users/roman/src/ml/data-pipelines/etl/venv/lib/python3.6/site-packages/apache_beam/io/concat_source.py", line 89, in read
> range_tracker.sub_range_tracker(source_ix)):
> File "/Users/roman/src/ml/data-pipelines/etl/venv/lib/python3.6/site-packages/apache_beam/io/textio.py", line 210, in read_records
> yield self._coder.decode(record)
> File "/Users/roman/src/ml/data-pipelines/etl/venv/lib/python3.6/site-packages/apache_beam/io/gcp/bigquery.py", line 566, in decode
> return self._decode_with_schema(value, self.fields)
> File "/Users/roman/src/ml/data-pipelines/etl/venv/lib/python3.6/site-packages/apache_beam/io/gcp/bigquery.py", line 580, in _decode_with_schema
> value[field.name], field.fields)
> File "/Users/roman/src/ml/data-pipelines/etl/venv/lib/python3.6/site-packages/apache_beam/io/gcp/bigquery.py", line 575, in _decode_with_schema
> value[field.name] = None
> TypeError: list indices must be integers or slices, not str{noformat}
>
> The fix could look something like this (untested):
> {code:python}
> def _decode_with_schema(self, value, schema_fields):
> for field in schema_fields:
> if field.name not in value:
> # The field exists in the schema, but it doesn't exist in this row.
> # It probably means its value was null, as the extract to JSON job
> # doesn't preserve null fields
> value[field.name] = None
> continue
> if field.type == 'RECORD':
> if field.mode == 'REPEATED':
> value[field.name] = [self._decode_with_schema(val, field.fields)
> for val in value[field.name]]
> else:
> value[field.name] = self._decode_with_schema(value[field.name],
> field.fields)
> else:
> try:
> converter = self._converters[field.type]
> except KeyError:
> # No need to do any conversion
> continue
> if field.mode == 'REPEATED':
> value[field.name] = map(converter, value[field.name])
> else:
> value[field.name] = converter(value[field.name])
> return value
> {code}
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