def main(): credentials = GoogleCredentials.get_application_default() http = credentials.authorize(httplib2.Http()) projectId = raw_input("Enter the project ID: ") datasetId = raw_input("Enter a dataset ID: ") tableId = raw_input("Enter a table name to load the data to: ") schema_path = raw_input("Enter the path to the schema file for the table: ") with open(schema_path, "r") as schema_file: schema = schema_file.read() data_path = raw_input("Enter the path to the data file: ") with open(data_path, "r") as data_file: data = data_file.read() resp, content = make_post(http, schema, data, projectId, datasetId, tableId) if resp.status == 200: job_resource = json.loads(content) service = get_service(credentials) poll_job(service, **job_resource["jobReference"]) print("Success!") else: print("Http error code: {}".format(resp.status))
def main(): credentials = GoogleCredentials.get_application_default() http = credentials.authorize(httplib2.Http()) projectId = raw_input('Enter the project ID: ') datasetId = raw_input('Enter a dataset ID: ') tableId = raw_input('Enter a table name to load the data to: ') schema_path = raw_input( 'Enter the path to the schema file for the table: ') with open(schema_path, 'r') as schema_file: schema = schema_file.read() data_path = raw_input('Enter the path to the data file: ') with open(data_path, 'r') as data_file: data = data_file.read() resp, content = make_post(http, schema, data, projectId, datasetId, tableId) if resp.status == 200: job_resource = json.loads(content) service = get_service(credentials) poll_job(service, **job_resource['jobReference']) print("Success!") else: print("Http error code: {}".format(resp.status))
def run(cloud_storage_path, projectId, datasetId, tableId, num_retries, interval): bigquery = get_service() resource = export_table(bigquery, cloud_storage_path, projectId, datasetId, tableId, num_retries) poll_job(bigquery, resource['jobReference']['projectId'], resource['jobReference']['jobId'], interval, num_retries)
def run(source_schema, source_csv, projectId, datasetId, tableId, interval, num_retries): service = get_service() job = load_table(service, source_schema, source_csv, projectId, datasetId, tableId, num_retries) poll_job(service, job['jobReference']['projectId'], job['jobReference']['jobId'], interval, num_retries)
def run(project_id, dataset_id, table_id, rows, num_retries): service = get_service() for row in rows: response = stream_row_to_bigquery(service, project_id, dataset_id, table_id, row, num_retries) yield json.dumps(response)
def run(project_id, query, timeout, num_retries): service = get_service() response = sync_query(service, project_id, query, timeout, num_retries) for page in paging(service, service.jobs().getQueryResults, num_retries=num_retries, **response['jobReference']): yield json.dumps(page['rows'])
def run(project_id, query_string, batch, num_retries, interval): service = get_service() query_job = async_query(service, project_id, query_string, batch, num_retries) poll_job(service, query_job['jobReference']['projectId'], query_job['jobReference']['jobId'], interval, num_retries) for page in paging(service, service.jobs().getQueryResults, num_retries=num_retries, **query_job['jobReference']): yield json.dumps(page['rows'])