Python menginstal BigQuery
pip install google-cloud-bigquery
TELLI Hichem
pip install google-cloud-bigquery# Here is a sample code from https://cloud.google.com/bigquery/docs/samples/bigquery-add-column-load-append#bigquery_add_column_load_append-python
# from google.cloud import bigquery
# client = bigquery.Client()
# project = client.project
# dataset_ref = bigquery.DatasetReference(project, 'my_dataset')
# filepath = 'path/to/your_file.csv'
# Retrieves the destination table and checks the length of the schema
table_id = "my_table"
table_ref = dataset_ref.table(table_id)
table = client.get_table(table_ref)
print("Table {} contains {} columns.".format(table_id, len(table.schema)))
# Configures the load job to append the data to the destination table,
# allowing field addition
job_config = bigquery.LoadJobConfig()
job_config.write_disposition = bigquery.WriteDisposition.WRITE_APPEND
job_config.schema_update_options = [
bigquery.SchemaUpdateOption.ALLOW_FIELD_ADDITION
]
# In this example, the existing table contains only the 'full_name' column.
# 'REQUIRED' fields cannot be added to an existing schema, so the
# additional column must be 'NULLABLE'.
job_config.schema = [
bigquery.SchemaField("full_name", "STRING", mode="REQUIRED"),
bigquery.SchemaField("age", "INTEGER", mode="NULLABLE"),
]
job_config.source_format = bigquery.SourceFormat.CSV
job_config.skip_leading_rows = 1
with open(filepath, "rb") as source_file:
job = client.load_table_from_file(
source_file,
table_ref,
location="US", # Must match the destination dataset location.
job_config=job_config,
) # API request
job.result() # Waits for table load to complete.
print(
"Loaded {} rows into {}:{}.".format(
job.output_rows, dataset_id, table_ref.table_id
)
)
# Checks the updated length of the schema
table = client.get_table(table)
print("Table {} now contains {} columns.".format(table_id, len(table.schema)))