【发布时间】:2020-02-16 18:21:09
【问题描述】:
新手在玩 Kafka 和 AVRO。
我正在尝试使用kafka-python、avro-python3 包和关注this answer 在 Python 3.7.3 中反序列化 AVRO 消息。
负责解码Kafka消息的函数是
def decode_message(msg_value, reader):
from io import BytesIO
from avro.io import BinaryDecoder
message_bytes = BytesIO(msg_value)
decoder = BinaryDecoder(message_bytes)
event_dict = reader.read(decoder)
return event_dict
其中reader 定义为avro.io.DatumReader 实例:
def create_reader(filename_path):
from avro.io import DatumReader
import avro.schema
schema = avro.schema.Parse(open(filename_path).read())
reader = DatumReader(schema)
return reader
不幸的是,它失败了。这是回溯:
<_io.BytesIO object at 0x7fab73fe5530>
<avro.io.BinaryDecoder object at 0x7fab74300090>
Traceback (most recent call last):
File "app.py", line 19, in <module>
kfk.read_messages(kafka_consumer, avro_reader)
File "/app/modules/consume_kafka.py", line 17, in read_messages
decoded_message = decode_message(msg_value, reader)
File "/app/modules/consume_kafka.py", line 50, in decode_message
event_dict = reader.read(decoder)
File "/usr/local/lib/python3.7/site-packages/avro/io.py", line 489, in read
return self.read_data(self.writer_schema, self.reader_schema, decoder)
File "/usr/local/lib/python3.7/site-packages/avro/io.py", line 534, in read_data
return self.read_record(writer_schema, reader_schema, decoder)
File "/usr/local/lib/python3.7/site-packages/avro/io.py", line 734, in read_record
field_val = self.read_data(field.type, readers_field.type, decoder)
File "/usr/local/lib/python3.7/site-packages/avro/io.py", line 512, in read_data
return decoder.read_utf8()
File "/usr/local/lib/python3.7/site-packages/avro/io.py", line 257, in read_utf8
input_bytes = self.read_bytes()
File "/usr/local/lib/python3.7/site-packages/avro/io.py", line 249, in read_bytes
assert (nbytes >= 0), nbytes
AssertionError: -40
我能够阅读该消息,它看起来像
b'Obj\x01\x04\x14avro.codec\x08null\x16avro.schema\xbe\t{"type":"record","name":"tracks","namespace":"integration","fields":[{"name":"name","type":"string"},{"name":"data","type":[{"type":"record","name":"track_upload_verified","namespace":"integration.tracks","fields":[{"name":"track_id","type":"string"},{"name":"audio_filename","type":"string"},{"name":"track_type","type":"string"}]},{"type":"record","name":"audio_processed","namespace":"integration.tracks","fields":[{"name":"track_id","type":"string"},{"name":"audio_mp3_filename","type":"string"},{"name":"waveform_samples","type":{"type":"array","items":"int"}},{"name":"duration","type":"string"}]}]}]}\x00\xc4\x8ad\xceF\x9c\xef\x99\n}#y7\x96\xba\xb4\x02\xe2\x01*track_upload_verified\x00H341aa6a3-5ecb-4ac0-8f27-bc2fe5abc9d4^tracks-audio/-1khgyI4kYfSf8hq2XiXZjg-1569510465\x08main\xc4\x8ad\xceF\x9c\xef\x99\n}#y7\x96\xba\xb4'
这是我所期望的,即生咬。
当我使用 this tool 对其进行验证时,我对架构非常确定。
有人遇到过类似的问题吗?
【问题讨论】:
-
我建议使用 Confluent Schema Registry 和他们的 python 客户端来处理 Avro
标签: python avro kafka-python