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https://issues.apache.org/jira/browse/BEAM-8841?focusedWorklogId=393645&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-393645
]
ASF GitHub Bot logged work on BEAM-8841:
----------------------------------------
Author: ASF GitHub Bot
Created on: 26/Feb/20 17:38
Start Date: 26/Feb/20 17:38
Worklog Time Spent: 10m
Work Description: chunyang commented on pull request #10979: [BEAM-8841]
Support writing data to BigQuery via Avro in Python SDK
URL: https://github.com/apache/beam/pull/10979#discussion_r384653061
##########
File path: sdks/python/apache_beam/io/gcp/bigquery.py
##########
@@ -1361,87 +1369,18 @@ def __init__(
self.triggering_frequency = triggering_frequency
self.insert_retry_strategy = insert_retry_strategy
self._validate = validate
+ self._temp_file_format = temp_file_format or bigquery_tools.FileFormat.JSON
self.additional_bq_parameters = additional_bq_parameters or {}
self.table_side_inputs = table_side_inputs or ()
self.schema_side_inputs = schema_side_inputs or ()
- @staticmethod
- def get_table_schema_from_string(schema):
- """Transform the string table schema into a
- :class:`~apache_beam.io.gcp.internal.clients.bigquery.\
-bigquery_v2_messages.TableSchema` instance.
-
- Args:
- schema (str): The sting schema to be used if the BigQuery table to write
- has to be created.
-
- Returns:
- ~apache_beam.io.gcp.internal.clients.bigquery.\
-bigquery_v2_messages.TableSchema:
- The schema to be used if the BigQuery table to write has to be created
- but in the :class:`~apache_beam.io.gcp.internal.clients.bigquery.\
-bigquery_v2_messages.TableSchema` format.
- """
- table_schema = bigquery.TableSchema()
- schema_list = [s.strip() for s in schema.split(',')]
- for field_and_type in schema_list:
- field_name, field_type = field_and_type.split(':')
- field_schema = bigquery.TableFieldSchema()
- field_schema.name = field_name
- field_schema.type = field_type
- field_schema.mode = 'NULLABLE'
- table_schema.fields.append(field_schema)
- return table_schema
-
- @staticmethod
- def table_schema_to_dict(table_schema):
- """Create a dictionary representation of table schema for serialization
- """
- def get_table_field(field):
- """Create a dictionary representation of a table field
- """
- result = {}
- result['name'] = field.name
- result['type'] = field.type
- result['mode'] = getattr(field, 'mode', 'NULLABLE')
- if hasattr(field, 'description') and field.description is not None:
- result['description'] = field.description
- if hasattr(field, 'fields') and field.fields:
- result['fields'] = [get_table_field(f) for f in field.fields]
- return result
-
- if not isinstance(table_schema, bigquery.TableSchema):
- raise ValueError("Table schema must be of the type bigquery.TableSchema")
- schema = {'fields': []}
- for field in table_schema.fields:
- schema['fields'].append(get_table_field(field))
- return schema
-
- @staticmethod
- def get_dict_table_schema(schema):
- """Transform the table schema into a dictionary instance.
-
- Args:
- schema (~apache_beam.io.gcp.internal.clients.bigquery.\
-bigquery_v2_messages.TableSchema):
- The schema to be used if the BigQuery table to write has to be created.
- This can either be a dict or string or in the TableSchema format.
-
- Returns:
- Dict[str, Any]: The schema to be used if the BigQuery table to write has
- to be created but in the dictionary format.
- """
- if (isinstance(schema, (dict, vp.ValueProvider)) or callable(schema) or
- schema is None):
- return schema
- elif isinstance(schema, (str, unicode)):
- table_schema = WriteToBigQuery.get_table_schema_from_string(schema)
- return WriteToBigQuery.table_schema_to_dict(table_schema)
- elif isinstance(schema, bigquery.TableSchema):
- return WriteToBigQuery.table_schema_to_dict(schema)
- else:
- raise TypeError('Unexpected schema argument: %s.' % schema)
+ # Dict/schema methods were moved to bigquery_tools, but keep references
+ # here for backward compatibility.
+ get_table_schema_from_string = \
+ staticmethod(bigquery_tools.get_table_schema_from_string)
+ table_schema_to_dict = staticmethod(bigquery_tools.table_schema_to_dict)
+ get_dict_table_schema = staticmethod(bigquery_tools.get_dict_table_schema)
Review comment:
Moved these to avoid a cyclic import.
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Issue Time Tracking
-------------------
Worklog Id: (was: 393645)
Time Spent: 40m (was: 0.5h)
> Add ability to perform BigQuery file loads using avro
> -----------------------------------------------------
>
> Key: BEAM-8841
> URL: https://issues.apache.org/jira/browse/BEAM-8841
> Project: Beam
> Issue Type: Improvement
> Components: io-py-gcp
> Reporter: Chun Yang
> Priority: Minor
> Time Spent: 40m
> Remaining Estimate: 0h
>
> Currently, JSON format is used for file loads into BigQuery in the Python
> SDK. JSON has some disadvantages including size of serialized data and
> inability to represent NaN and infinity float values.
> BigQuery supports loading files in avro format, which can overcome these
> disadvantages. The Java SDK already supports loading files using avro format
> (BEAM-2879) so it makes sense to support it in the Python SDK as well.
> The change will be somewhere aroundÂ
> [{{BigQueryBatchFileLoads}}|https://github.com/apache/beam/blob/3e7865ee6c6a56e51199515ec5b4b16de1ddd166/sdks/python/apache_beam/io/gcp/bigquery_file_loads.py#L554].
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