[jira] [Created] (BEAM-8452) TriggerLoadJobs.process in bigquery_file_loads schema is type str

["Noah Goodrich (Jira)" <ji...@apache.org>]

Noah Goodrich created BEAM-8452:
-----------------------------------

             Summary: TriggerLoadJobs.process in bigquery_file_loads schema is type str
                 Key: BEAM-8452
                 URL: https://issues.apache.org/jira/browse/BEAM-8452
             Project: Beam
          Issue Type: Bug
          Components: sdk-py-core
    Affects Versions: 2.15.0, 2.16.0
            Reporter: Noah Goodrich
            Assignee: Noah Goodrich


 I've found a first issue with the BigQueryFileLoads Transform and the type of the schema parameter.
{code:java}
Triggering job beam_load_2019_10_11_140829_19_157670e4d458f0ff578fbe971a91b30a_1570802915 to load data to BigQuery table <TableReference
 datasetId: 'pyr_monat_dev'
 projectId: 'icentris-ml-dev'
 tableId: 'tree_user_types'>.Schema: {"fields": [{"name": "id", "type": "INTEGER", "mode": "required"}, {"name": "description", "type": "STRING", "mode": "nullable"}]}. Additional parameters: {}
Retry with exponential backoff: waiting for 4.875033410381894 seconds before retrying _insert_load_job because we caught exception: apitools.base.protorpclite.messages.ValidationError: Expected type <clas
s 'apache_beam.io.gcp.internal.clients.bigquery.bigquery_v2_messages.TableSchema'> for field schema, found {"fields": [{"name": "id", "type": "INTEGER", "mode": "required"}, {"name": "description", "type"
: "STRING", "mode": "nullable"}]} (type <class 'str'>)
 Traceback for above exception (most recent call last):
  File "/opt/conda/lib/python3.7/site-packages/apache_beam/utils/retry.py", line 206, in wrapper
    return fun(*args, **kwargs)
  File "/opt/conda/lib/python3.7/site-packages/apache_beam/io/gcp/bigquery_tools.py", line 344, in _insert_load_job
    **additional_load_parameters
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 791, in __init__
    setattr(self, name, value)
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 973, in __setattr__
    object.__setattr__(self, name, value)
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 1652, in __set__
    super(MessageField, self).__set__(message_instance, value)
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 1293, in __set__
    value = self.validate(value)
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 1400, in validate
    return self.__validate(value, self.validate_element)
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 1358, in __validate
    return validate_element(value)   
  File "/opt/conda/lib/python3.7/site-packages/apitools/base/protorpclite/messages.py", line 1340, in validate_element
    (self.type, name, value, type(value)))
 
{code}
 

The triggering code looks like this:

 
options.view_as(DebugOptions).experiments = ['use_beam_bq_sink']
        # Save main session state so pickled functions and classes
        # defined in __main__ can be unpickled
        options.view_as(SetupOptions).save_main_session = True
        custom_options = options.view_as(LoadSqlToBqOptions)
        with beam.Pipeline(options=options) as p:
            (p
                | "Initializing with empty collection" >> beam.Create([1])
                | "Reading records from CloudSql" >> beam.ParDo(ReadFromRelationalDBFn(
                    username=custom_options.user,
                    password=custom_options.password,
                    database=custom_options.database,
                    table=custom_options.table,
                    key_field=custom_options.key_field,
                    batch_size=custom_options.batch_size))
                | "Converting Row Object for BigQuery" >> beam.ParDo(BuildForBigQueryFn(custom_options.bq_schema))
                | "Writing to BigQuery" >> beam.io.WriteToBigQuery(
                        table=custom_options.bq_table,
                        schema=custom_options.bq_schema,
                        write_disposition=beam.io.BigQueryDisposition.WRITE_TRUNCATE,
                        create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED))
 

 



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