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https://issues.apache.org/jira/browse/BEAM-14146?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Rahul Iyer updated BEAM-14146:
------------------------------
Description:
We have a Python Streaming Dataflow job that writes to BigQuery using the
{{FILE_LOADS}} method and {{auto_sharding}} enabled. When we try to drain the
job it fails with the following error,
{code:python}
"/usr/local/lib/python3.7/site-packages/apache_beam/io/gcp/bigquery_tools.py",
line 1000, in perform_load_job ValueError: Either a non-empty list of
fully-qualified source URIs must be provided via the source_uris parameter or
an open file object must be provided via the source_stream parameter.
{code}
Our {{WriteToBigQuery}} configuration,
{code:python}
beam.io.WriteToBigQuery(
table=options.output_table,
schema=bq_schema,
create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED,
write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND,
insert_retry_strategy=RetryStrategy.RETRY_ON_TRANSIENT_ERROR,
method=beam.io.WriteToBigQuery.Method.FILE_LOADS,
additional_bq_parameters={
"timePartitioning": {
"type": "HOUR",
"field": "bq_insert_timestamp",
},
"schemaUpdateOptions": ["ALLOW_FIELD_ADDITION", "ALLOW_FIELD_RELAXATION"],
},
triggering_frequency=120,
with_auto_sharding=True,
)
{code}
We are also noticing that the job only fails to drain when there are actual
schema updates. If there are no schema updates the job drains without the above
error.
was:
We have a Python Streaming Dataflow job that writes to BigQuery using the
{{FILE_LOADS}} method and {{auto_sharding}} enabled. When we try to drain the
job it fails with the following error,
{code:python}
"/usr/local/lib/python3.7/site-packages/apache_beam/io/gcp/bigquery_tools.py",
line 1000, in perform_load_job ValueError: Either a non-empty list of
fully-qualified source URIs must be provided via the source_uris parameter or
an open file object must be provided via the source_stream parameter.
{code}
Our {{WriteToBigQuery}} configuration,
{code:python}
beam.io.WriteToBigQuery(
table=options.output_table,
schema=bq_schema,
create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED,
write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND,
insert_retry_strategy=RetryStrategy.RETRY_ON_TRANSIENT_ERROR,
method=beam.io.WriteToBigQuery.Method.FILE_LOADS,
additional_bq_parameters={
"timePartitioning": {
"type": "HOUR",
"field": "bq_insert_timestamp",
},
"schemaUpdateOptions": ["ALLOW_FIELD_ADDITION", "ALLOW_FIELD_RELAXATION"],
},
triggering_frequency=120,
with_auto_sharding=True,
)
{code}
> Python Streaming job failing to drain with BigQueryIO write errors
> ------------------------------------------------------------------
>
> Key: BEAM-14146
> URL: https://issues.apache.org/jira/browse/BEAM-14146
> Project: Beam
> Issue Type: Bug
> Components: io-py-gcp, sdk-py-core
> Affects Versions: 2.37.0
> Reporter: Rahul Iyer
> Priority: P2
>
> We have a Python Streaming Dataflow job that writes to BigQuery using the
> {{FILE_LOADS}} method and {{auto_sharding}} enabled. When we try to drain the
> job it fails with the following error,
> {code:python}
> "/usr/local/lib/python3.7/site-packages/apache_beam/io/gcp/bigquery_tools.py",
> line 1000, in perform_load_job ValueError: Either a non-empty list of
> fully-qualified source URIs must be provided via the source_uris parameter or
> an open file object must be provided via the source_stream parameter.
> {code}
> Our {{WriteToBigQuery}} configuration,
> {code:python}
> beam.io.WriteToBigQuery(
> table=options.output_table,
> schema=bq_schema,
> create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED,
> write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND,
> insert_retry_strategy=RetryStrategy.RETRY_ON_TRANSIENT_ERROR,
> method=beam.io.WriteToBigQuery.Method.FILE_LOADS,
> additional_bq_parameters={
> "timePartitioning": {
> "type": "HOUR",
> "field": "bq_insert_timestamp",
> },
> "schemaUpdateOptions": ["ALLOW_FIELD_ADDITION", "ALLOW_FIELD_RELAXATION"],
> },
> triggering_frequency=120,
> with_auto_sharding=True,
> )
> {code}
> We are also noticing that the job only fails to drain when there are actual
> schema updates. If there are no schema updates the job drains without the
> above error.
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