我在flink数据集中加载了一个avro文件:
AvroInputFormat<GenericRecord> test = new AvroInputFormat<GenericRecord>(
new Path("PathToAvroFile")
, GenericRecord.class);
DataSet<GenericRecord> DS = env.createInput(test);
usersDS.print();
下面是打印ds的结果:
{"N_NATIONKEY": 14, "N_NAME": "KENYA", "N_REGIONKEY": 0, "N_COMMENT": " pending excuses haggle furiously deposits. pending, express pinto beans wake fluffily past t"}
{"N_NATIONKEY": 15, "N_NAME": "MOROCCO", "N_REGIONKEY": 0, "N_COMMENT": "rns. blithely bold courts among the closely regular packages use furiously bold platelets?"}
{"N_NATIONKEY": 16, "N_NAME": "MOZAMBIQUE", "N_REGIONKEY": 0, "N_COMMENT": "s. ironic, unusual asymptotes wake blithely r"}
{"N_NATIONKEY": 17, "N_NAME": "PERU", "N_REGIONKEY": 1, "N_COMMENT": "platelets. blithely pending dependencies use fluffily across the even pinto beans. carefully silent accoun"}
{"N_NATIONKEY": 18, "N_NAME": "CHINA", "N_REGIONKEY": 2, "N_COMMENT": "c dependencies. furiously express notornis sleep slyly regular accounts. ideas sleep. depos"}
{"N_NATIONKEY": 19, "N_NAME": "ROMANIA", "N_REGIONKEY": 3, "N_COMMENT": "ular asymptotes are about the furious multipliers. express dependencies nag above the ironically ironic account"}
{"N_NATIONKEY": 20, "N_NAME": "SAUDI ARABIA", "N_REGIONKEY": 4, "N_COMMENT": "ts. silent requests haggle. closely express packages sleep across the blithely"}
现在我想从ds数据集中创建一个表,它的模式与avro文件完全相同,我的意思是列应该是n\u nationkey、n\u name、n\u regionkey和n\u comment。
我知道用这句话:
tableEnv.registerDataSet("tbTest", DS, "field1, field2, ...");
我可以创建一个表并设置列,但我希望这些列能够从数据中自动推断出来。有可能吗?另外,我试过
tableEnv.registerDataSet("tbTest", DS);
但它创建了一个具有以下模式的表:
root
|-- f0: GenericType<org.apache.avro.generic.GenericRecord>
1条答案
按热度按时间iq0todco1#
GenericRecord
是表&sqlapi运行时的黑盒,因为字段数及其数据类型未定义。我建议使用avro生成的类SpecificRecord
. 这些特定类型也可以被flink的类型系统识别,您可以用适当的数据类型正确地处理各个字段。或者,您可以实现一个定制的udf,该udf提取具有适当数据类型的字段
getAvroInt(f0, "myField")
,getAvroString(f0, "myField")
等。一些伪代码: