Question

我正在使用Python Apache Beam Dataflow开发一个项目，我需要从启动数据流模板提供的运行时参数中命名bigquery表。。 / p>

到目前为止，我还没有运气，它要么为我提供了运行时参数的定义，要么为空字符串。

所以我基本上需要以某种方式工作：

class CustomPipelineOptions(PipelineOptions):

    @classmethod
    def _add_argparse_args(cls, parser):
        parser.add_value_provider_argument(
            '--path',
            type=str,
            help='csv storage path')
        parser.add_value_provider_argument(
            '--table_name',
            type=str,
            help='Table Id')
def run()
    def rewrite_values(element):
        """ Rewrite default env values"""
        try:
            logging.info("File Path with str(): {}".format(str(custom_options.path)))
            logging.info("----------------------------")
            logging.info("element: {}".format(element))
            project_id = str(cloud_options.project)
            file_path = custom_options.path.get()
            table_name = custom_options.table_name.get()

            logging.info("project: {}".format(project_id))
            logging.info("File path: {}".format(file_path))
            logging.info("language: {}".format(table_name))
            logging.info("----------------------------")
        except Exception as e:
            logging.info("Error format----------------------------")
            raise KeyError(e)

        return file_path

    pipeline_options = PipelineOptions()
    cloud_options = pipeline_options.view_as(GoogleCloudOptions)
    custom_options = pipeline_options.view_as(CustomPipelineOptions)
    pipeline_options.view_as(SetupOptions).save_main_session = True

    # Beginning of the pipeline
    p = beam.Pipeline(options=pipeline_options)

    init_data = (p
                 | beam.Create(["Start"])
                 | beam.FlatMap(rewrite_values))

pipeline processing, running pipeline etc.

save_data_bigquery = (table_data | "Get all numbers" >> beam.ParDo(GetAllNumbers())
                      | 'Flat items' >> beam.FlatMap(flat_item)
                      | 'Write to BigQuery' >> beam.io.WriteToBigQuery(project=project_id,
                                                                       dataset="defined_dataset",
                                                                       table=table_name, **********
                                                                       schema="id:STRING",
                                                                       batch_size=10000)
                      )

我在麻烦中为writetobigquery函数命名表，我也尝试过使用custom_options.table_name，将变量声明为global等。

我创建了一个自定义DoFn来写入BigQuery，尽管这是我的首选方法。

Answer 1

我尝试编写一个BQ_writer类，并在其中编写了实际的WriteToBigQuery。

class BQ_writer(beam.DoFn):
    def __init__(self, schema, output):
        self.output = output
        self.schema = schema

    def process(self, element):
        schema_l = self.schema.get()
        output_table_l = self.output.get()
        logging.info('Writing to table and schema: {}  {}'.format(output_table_l,schema_l))
        beam.io.WriteToBigQuery(output_table_l,
                                schema=schema_l,
                                create_disposition=beam.io.BigQueryDisposition.CREATE_IF_NEEDED,
                                write_disposition=beam.io.BigQueryDisposition.WRITE_APPEND)

，然后在管道中：

| 'WriteToBigQuery' >> beam.ParDo(BQ_writer(useroptions.schema,useroptions.output))

这很好用，并且构建的流没有错误。但是在大查询表中找不到数据。可能是我们不能在ParDo函数中使用WriteToBigQuery。欢迎提出建议，从这里开始。

从模板运行时参数，Python，Apache Beam，数据流命名BigQuery表

1 个答案: