org.apache.flink.table.api.TableException:结果的 Arity [3] 与请求类

Question

我有一个简单的测试用例来学习如何使用Table API和案例/时间，如下所示：

import org.apache.flink.api.scala.ExecutionEnvironment
import org.apache.flink.table.api.TableEnvironment
import org.apache.flink.api.scala._
case class Person(name: String, age: Int)
object TableTest {
  def main(args: Array[String]): Unit = {
    val env = ExecutionEnvironment.getExecutionEnvironment
    val te = TableEnvironment.getTableEnvironment(env)
    val ds = env.fromCollection(Seq(Person("a",20), Person("b",40), Person("c", 60)))
    te.registerDataSet("person", ds)
    te.toDataSet[Person](table).print()

    val table = te.sqlQuery(
      """
         select name,age,
             case
                when age <= 20 then 'A'
                when age <=40 then 'B'
                when age <= 60 then 'C'
                else 'D'
            end as age_level
            from person
      """.stripMargin(' '))
    te.toDataSet[Person](table).print()
  }
}

当我运行它时，我遇到以下异常，age_level是计算列，我不知道为什么会发生错误

Exception in thread "main" org.apache.flink.table.api.TableException: Arity [3] of result [ArrayBuffer(String, Integer, String)] does not match the number[2] of requested type [com.flink.table.Person(name: String, age: Integer)].
    at org.apache.flink.table.api.TableEnvironment.generateRowConverterFunction(TableEnvironment.scala:1165)
    at org.apache.flink.table.api.BatchTableEnvironment.getConversionMapper(BatchTableEnvironment.scala:339)
    at org.apache.flink.table.api.BatchTableEnvironment.translate(BatchTableEnvironment.scala:504)
    at org.apache.flink.table.api.BatchTableEnvironment.translate(BatchTableEnvironment.scala:476)
    at org.apache.flink.table.api.scala.BatchTableEnvironment.toDataSet(BatchTableEnvironment.scala:141)
    at com.flink.table.TableTest$.main(TableTest.scala:37)
    at com.flink.table.TableTest.main(TableTest.scala)

Answer 1

问题是要转换为DataSet[Person]的表具有三个属性：(name, age, age_level)而Person案例类只有两个字段：(name, age) 。

您可以实现一个新的案例类

case class PersonWithAgeLevel(name: String, age: Int, age_level: String)

并将表转换为DataSet[PersonWithAgeLevel]。