Re: Datastream[Row] covert to table exception

Posted by Timo Walther on
URL: http://deprecated-apache-flink-user-mailing-list-archive.369.s1.nabble.com/Datastream-Row-covert-to-table-exception-tp20597p20606.html

Sorry, I didn't see you last mail. The code looks good actually. What is the result of `inputStream.getType` if you print it to the console?

Timo

Am 07.06.18 um 08:24 schrieb Timo Walther:

Hi,

Row is a very special datatype where Flink cannot generate serializers based on the generics. By default DeserializationSchema uses reflection-based type analysis, you need to override the getResultType() method in WormholeDeserializationSchema. And specify the type information manually there.

Hope this helps.

Regards,
Timo

Am 06.06.18 um 13:22 schrieb 孙森:

Hi ,

    

     

I've tried to to specify such a schema, when I read from kafka, and covert inputstream to table . But I got the exception:

• Exception in thread "main" org.apache.flink.table.api.TableException: An input of GenericTypeInfo cannot be converted to Table. Please specify the type of the input with a RowTypeInfo

And the code here:

private def getSchemaMap(jsonSchema: String) = {
    val umsSchema = JsonUtils.json2caseClass[UmsSchema](jsonSchema)
    val fields = umsSchema.fields_get
    val fieldNameList = ListBuffer.empty[String]
    val fieldTypeList = ListBuffer.empty[TypeInformation[_]]
    fields.foreach {
      field =>
        fieldNameList.append(field.name)
        fieldTypeList.append(fieldTypeMatch(field.`type`))
    }
    println(fieldNameList)
    println(fieldTypeList)
    (fieldNameList.toArray, fieldTypeList.toArray)
  }


  private def fieldTypeMatch(umsFieldType: UmsFieldType): TypeInformation[_] = {
    umsFieldType match {
      case STRING => Types.STRING
      case INT => Types.INT
      case LONG => Types.LONG
      case FLOAT => Types.FLOAT
      case DOUBLE => Types.DOUBLE
      case BOOLEAN => Types.BOOLEAN
      case DATE => Types.SQL_DATE
      case DATETIME => Types.SQL_TIMESTAMP
      case DECIMAL => Types.DECIMAL
    }
  }
}


 val myConsumer: FlinkKafkaConsumer010[Row] = new FlinkKafkaConsumer010(topics, new WormholeDeserializationSchema(jsonSchema), properties)
 val inputStream: DataStream[Row] = env.addSource(myConsumer)
 val tableEnv = TableEnvironment.getTableEnvironment(env)<<—————exception here

Thanks !

sen