Google Cloud Platform提供了BigQuery数据传输服务，它可以将数据从外部数据源移动到BigQuery中。在某些情况下，外部数据源中的日期或月份可能只包含一个数字，例如1月可能只是1。但是，BigQuery默认情况下不支持这种格式。

为了正确加载包含单个数字日期和月份的数据，我们需要使用特殊的格式和函数来解析并将其转换为标准格式。以下是一个例子，该例子使用Dataflow接收CSV文件，其中包含单个数字日期和月份，然后通过BigQuery转换数据并将其插入到新的BigQuery表中。

import apache_beam as beam
import csv

class FormatDates(beam.DoFn):
    def process(self,element):
        day,month,year = element.split("/")
        if len(day) == 1:
            day = "0" + day
        if len(month) == 1:
            month = "0" + month
        element = "{}/{}/{}".format(day,month,year)
        return [element]

def run():
    PROJECT_ID = 'my-project'
    BUCKET = 'my-bucket'
    FILENAME = 'data.csv'
    DATASET = 'my-dataset'
    TABLE = 'my-table'
    SCHEMA = 'date:DATE, value:INTEGER'
    runner = 'DirectRunner'
    
    options = {
        "project": PROJECT_ID,
        "staging_location": "gs://{}/staging/".format(BUCKET),
        "temp_location": "gs://{}/temp/".format(BUCKET),
        "runner": runner,
    }
    p = beam.Pipeline(options=options)
    
    data = (p | "Read from CSV" >> 
            beam.io.ReadFromText("gs://{}/{}".format(BUCKET,FILENAME),
                                skip_header_lines = 1)
           )
    
    formatted = (data | "Format Dates" >> 
                 beam.ParDo(FormatDates())
                )
    
    formatted_table = (formatted | "Write to BigQuery" >> 
                       beam.io.gcp.bigquery.WriteToBigQuery(
                           table = "{}.{}".format(DATASET,TABLE),
                           schema = SCHEMA,
                           write_disposition = beam.io.BigQueryDisposition.WRITE_TRUNCATE,
                           create_disposition = beam.io.BigQueryDisposition.CREATE_IF_NEEDED,
                           method="STREAMING_INSERTS",
                           project = PROJECT_ID
                       )
                      )
    
    result = p.run()
    result.wait_until_finish()

if __name__ == "__main__":
    run()

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