python avro 数据格式使用demo

{"name": "UEProcedures",

 "type": "record",

 "fields": [

     {"name": "imsi", "type": "string"},

     {"name": "time_at", "type": "string"},

     {"name": "procedures", "type": {"type": "array", "items": {

	      "type": "record",

	      "name": "SignalProcedure",

	      "fields" : [

	      {"name": "timestamp", "type": "string"},

	      {"name": "procedure_tag", "type": "string"}

	      ]

         }}

     }

 ]

}

　ue_procedure.avsc数据格式说明，python3 下的示例代码：

import avro.schema

from avro.datafile import DataFileReader, DataFileWriter

from avro.io import DatumReader, DatumWriter

schema = avro.schema.Parse(open('ue_procedure.avsc', "r").read())

writer = DataFileWriter(open("ue_procedures.avro", "wb"), DatumWriter(), schema)

writer.append({"imsi": "UE001", "time_at": "2018-04-09 12:15", "procedures": [{"timestamp": "2019-04-09 12:01", "procedure_tag": "A"}, {"timestamp": "2019-04-09 12:02", "procedure_tag": "B"}]})

writer.append({"imsi": "UE002", "time_at": "2018-04-09 12:15", "procedures": [{"timestamp": "2019-04-09 12:01", "procedure_tag": "A"}, {"timestamp": "2019-04-09 12:02", "procedure_tag": "B"}]})

writer.close()

reader = DataFileReader(open("ue_procedures.avro", "rb"), DatumReader())

for ue in reader:

    print(ue)

reader.close()

　输出：

{'imsi': 'UE001', 'time_at': '2018-04-09 12:15', 'procedures': [{'timestamp': '2019-04-09 12:01', 'procedure_tag': 'A'}, {'timestamp': '2019-04-09 12:02', 'procedure_tag': 'B'}]}
{'imsi': 'UE002', 'time_at': '2018-04-09 12:15', 'procedures': [{'timestamp': '2019-04-09 12:01', 'procedure_tag': 'A'}, {'timestamp': '2019-04-09 12:02', 'procedure_tag': 'B'}]}

另外使用map的示例：

{"name": "UEStat",

 "type": "record",

 "fields": [

     {"name": "imsi", "type": "string"},

     {"name": "time_at", "type": "string"},

     {"name": "procedures_total_cnt", "type": "long"},

     {"name": "is_over15_time_detach_minus_attach", "type": "boolean"},

     {"name": "detail_procedures_cnt", "type": {"type": "map", "values": "long"}}

 ]

}

import avro.schema

from avro.datafile import DataFileReader, DataFileWriter

from avro.io import DatumReader, DatumWriter

schema = avro.schema.Parse(open('chr_ue_stat.avsc', "r").read())

writer = DataFileWriter(open("chr_ue_stat.avro", "wb"), DatumWriter(), schema)

writer.append({"imsi": "UE001", "time_at": "2018-04-09 12:15", "is_over15_time_detach_minus_attach": True, "procedures_total_cnt":789, "detail_procedures_cnt": {"A": 123, "B": 342}})

writer.append({"imsi": "UE002", "time_at": "2018-04-09 12:15", "is_over15_time_detach_minus_attach": False, "procedures_total_cnt": 876, "detail_procedures_cnt": {"C":1123, "D": 313}})

writer.close()

reader = DataFileReader(open("ue_procedures.avro", "rb"), DatumReader())

for ue in reader:

    print(ue)

reader.close()

　输出：

参考：https://avro.apache.org/docs/1.8.2/gettingstartedpython.html　

巴特西

python avro 数据格式使用demo

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