python-在Beam中读取和写入序列化的protobuf

我想将序列化的protobuf消息的PCollection写入文本文件并将其读回应该很容易.但是经过几次尝试,我却没有这样做.如果有人有任何评论,将不胜感激.

// definition of proto.

syntax = "proto3";
package test;
message PhoneNumber {
  string number = 1;
  string country = 2;
}

我下面的python代码实现了一个简单的Beam管道,可将文本写入序列化的protobuf.

# Test python code
import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
import phone_pb2

class ToProtoFn(beam.DoFn):
  def process(self, element):
    phone = phone_pb2.PhoneNumber()
    phone.number, phone.country = element.strip().split(',')
    yield phone.SerializeToString()

with beam.Pipeline(options=PipelineOptions()) as p:
  lines = (p 
      | beam.Create(["123-456-789,us", "345-567-789,ca"])
      | beam.ParDo(ToProtoFn())
      | beam.io.WriteToText('/Users/greeness/data/phone-pb'))

管道可以成功运行,并生成包含内容的文件：

$cat ~/data/phone-pb-00000-of-00001 


123-456-789us


345-567-789ca

然后,我编写另一个管道以读取序列化的protobuf,并使用ParDo对其进行解析.

class ToCsvFn(beam.DoFn):
  def process(self, element):
    phone = phone_pb2.PhoneNumber()
    phone.ParseFromString(element)
    yield ",".join([phone.number, phone.country])

with beam.Pipeline(options=PipelineOptions()) as p:
  lines = (p 
      | beam.io.ReadFromText('/Users/greeness/data/phone*')
      | beam.ParDo(ToCsvFn())
      | beam.io.WriteToText('/Users/greeness/data/phone-csv'))

运行该错误消息.

  File "/Library/Python/2.7/site-packages/apache_beam/runners/common.py", line 458, in process_outputs
  for result in results:
  File "phone_example.py", line 37, in process
phone.ParseFromString(element)
  File "/Library/Python/2.7/site-packages/google/protobuf/message.py", line 185, in ParseFromString
  self.MergeFromString(serialized)
  File "/Library/Python/2.7/site-packages/google/protobuf/internal/python_message.py", line 1069, in MergeFromString
  raise message_mod.DecodeError('Truncated message.')
  DecodeError: Truncated message. [while running 'ParDo(ToCsvFn)']

因此,看起来序列化的protobuf字符串无法解析.我想念什么吗？谢谢你的帮助！

解决方法:

我通过实施的tfrecordio.py找到了一个临时解决方案.

下面的代码正在工作.但是我仍然欢迎任何可以解决上述问题的评论.

import apache_beam as beam
from apache_beam.options.pipeline_options import PipelineOptions
import phone_pb2

def WriteTextToTFRecord():
  class ToProtoFn(beam.DoFn):
    def process(self, element):
      phone = phone_pb2.PhoneNumber()
      phone.number, phone.country = element.strip().split(',')
      yield phone
  with beam.Pipeline(options=PipelineOptions()) as p:
    lines = p | beam.Create(["123-456-789,us", "345-567-789,ca"])
    processed = (
        lines
        | beam.ParDo(ToProtoFn())
        | beam.io.WriteToTFRecord('/Users/greeness/data/phone-pb',
                                  coder=beam.coders.ProtoCoder(phone_pb2.PhoneNumber().__class__)))

def ReadTFRecordAndSaveAsCSV():
  class ToCsvFn(beam.DoFn):
    def process(self, element):
      yield ','.join([element.number, element.country])
  with beam.Pipeline(options=PipelineOptions()) as p:
    lines = (p
      | beam.io.ReadFromTFRecord('/Users/greeness/data/phone-pb-*',
                                 coder=beam.coders.ProtoCoder(phone_pb2.PhoneNumber().__class__))
      | beam.ParDo(ToCsvFn())
      | beam.io.WriteToText('/Users/greeness/data/phone-csv'))

if __name__ == '__main__':
  WriteTextToTFRecord()
  ReadTFRecordAndSaveAsCSV()

标签：protocol-buffers,apache-beam,apache-beam-io,python
来源： https://codeday.me/bug/20191025/1928482.html