我编写了一个python脚本，它读取csv并使用异步和并发将它们插入cassandra表中，但是并发比异步慢。我使用concurrent的目的是实现并行写入，从而加快在cassandra中索引csv文件的任务。
使用异步的代码：

for df in chunks:
            futures = []
            df = df.to_dict(orient='records')
            chunk_counter += 1
            for row in df:
                key = str(row["0"])
                row = json.dumps(row, default=str)
                futures.append(
                    self.session.execute_async(
                        insert_sql, [key, "version_1", row]
                    )
                )
                # batch.add(insert_sql, (key, "version_1", row))
            # self.session.execute(batch)
            for future in futures:
                self.log.debug(future)
                continue

使用concurrents的代码：

for df in chunks:
            futures = []
            df = df.to_dict(orient='records')
            chunk_counter += 1
            for row in df:
                key = str(row["0"])
                row = json.dumps(row, default=str)
                params = (key, row, )
                futures.append(
                    (
                        insert_sql,
                        params
                    )
                )
            results = execute_concurrent(
                self.session, futures, raise_on_first_error=False)
            for (success, result) in results:
                if not success:
                    self.handle_error(result)  # result will be an Exception