以下是一个使用 Apache Beam 和 GCP 创建目录，并上传 Avro 文件的示例代码：

import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
from apache_beam.io.gcp.gcsio import GcsIO

def create_directory(pipeline, gcs_path):
    gcs_io = GcsIO()
    gcs_io.mkdirs(gcs_path)

def upload_avro_files(pipeline, avro_files, gcs_path):
    pipeline | "Read Avro Files" >> beam.io.ReadFromAvro(avro_files) \
             | "Write Avro Files" >> beam.io.WriteToAvro(gcs_path)

def run_pipeline(avro_files, gcs_path):
    options = PipelineOptions()
    pipeline = beam.Pipeline(options=options)

    create_directory(pipeline, gcs_path)
    upload_avro_files(pipeline, avro_files, gcs_path)

    result = pipeline.run()
    result.wait_until_finish()

if __name__ == "__main__":
    avro_files = "path/to/avro/files/*.avro"
    gcs_path = "gs://your-bucket/destination/"

    run_pipeline(avro_files, gcs_path)

在上面的代码中，create_directory 函数使用 GcsIO 创建一个新的目录。upload_avro_files 函数使用 ReadFromAvro 和 WriteToAvro 函数来读取 Avro 文件并将其写入 GCS。run_pipeline 函数创建一个 Apache Beam 流水线，并按顺序调用 create_directory 和 upload_avro_files 函数。最后，run_pipeline 函数运行并等待流水线完成。

请注意，你需要根据你的实际情况修改 avro_files 和 gcs_path 变量的值。