def _get_query_result()

in redash/query_runner/big_query.py [0:0]

• 43 lines of code
• 7 McCabe index (conditional complexity)

    def _get_query_result(self, jobs, query):
        project_id = self._get_project_id()
        job_data = self._get_job_data(query)
        insert_response = jobs.insert(projectId=project_id, body=job_data).execute()
        self.current_job_id = insert_response["jobReference"]["jobId"]
        current_row = 0
        query_reply = _get_query_results(
            jobs,
            project_id=project_id,
            location=self._get_location(),
            job_id=self.current_job_id,
            start_index=current_row,
        )

        logger.debug("bigquery replied: %s", query_reply)

        rows = []

        while ("rows" in query_reply) and current_row < int(query_reply["totalRows"]):
            for row in query_reply["rows"]:
                rows.append(transform_row(row, query_reply["schema"]["fields"]))

            current_row += len(query_reply["rows"])

            query_result_request = {
                "projectId": project_id,
                "jobId": query_reply["jobReference"]["jobId"],
                "startIndex": current_row,
            }

            if self._get_location():
                query_result_request["location"] = self._get_location()

            query_reply = jobs.getQueryResults(**query_result_request).execute()

        columns = [
            {
                "name": f["name"],
                "friendly_name": f["name"],
                "type": "string"
                if f.get("mode") == "REPEATED"
                else types_map.get(f["type"], "string"),
            }
            for f in query_reply["schema"]["fields"]
        ]

        data = {
            "columns": columns,
            "rows": rows,
            "metadata": {"data_scanned": int(query_reply["totalBytesProcessed"])},
        }

        return data