可能原因是在Python SDK中，不支持将BigQuery表作为Pub/Sub主题直接使用。解决方法是，使用Dataflow的Streaming Engine，利用自定义的 PubsubToBigQuery 类将Pub/Sub消息写入到BigQuery表中。

以下是一个示例代码：

import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions, StandardOptions

class PubsubToBigQuery(beam.DoFn):
    def __init__(self,dataset,table):
        self.dataset = dataset
        self.table = table

    def start_bundle(self):
        self.bigquery_client = bigquery.Client()
        self.dataset_ref = self.bigquery_client.dataset(self.dataset)
        self.table_ref = self.dataset_ref.table(self.table)

    def process(self, element, timestamp=beam.DoFn.TimestampParam):
        try:
            row = {
                "column1": element['column1'],
                "column2": element['column2'],
                "timestamp": timestamp
            }
            errors = self.bigquery_client.insert_rows_json(self.table_ref, [row], ignore_unknown_values=True)
            if errors:
                raise Exception(errors)
            else:
                return [element['column1']]
        except Exception as e:
            return []

def run():
    pipeline_options = PipelineOptions()
    pipeline_options.view_as(StandardOptions).streaming = True
    p = beam.Pipeline(options=pipeline_options)

    (p | "Read from Pub/Sub" >> beam.io.ReadFromPubSub(subscription="projects/{project}/subscriptions/{subscription}")
       | "Transform message" >> beam.Map(lambda x: json.loads(x))
       | "Write to BigQuery" >> beam.ParDo(PubsubToBigQuery(dataset='my_dataset', table='my_table')))
    
    p.run().wait_until_finish()

在此示例中，Pub/Sub消息将从指定的订阅中读取，然后将每条消息转换为JSON，并将其传递给 PubsubToBigQuery 类。类将转换后的消息写入到指定的 BigQuery 表中。在表格结构的之后，您