为了知道找不到匹配的记录，输入必须是有界的——因此我们将使用 BatchTableEnvironment ，而不是 StreamTableEnvironment . (通过流式输入，匹配的记录可能最终到达并满足查询。只有批量输入才能证明没有匹配。）

import org.apache.flink.api.common.functions.FlatMapFunction
import org.apache.flink.api.scala.ExecutionEnvironment
import org.apache.flink.table.api.scala.BatchTableEnvironment
import org.apache.flink.types.Row
import org.apache.flink.api.scala._
import org.apache.flink.table.api.scala._
import org.apache.flink.util.Collector

class MissingResultException() extends Exception {}

object Phone {
  case class Visitor(name: String, id: String)

  @throws[Exception]
  def main(args: Array[String]): Unit = {
    val env = ExecutionEnvironment.getExecutionEnvironment
    val tableEnv = BatchTableEnvironment.create(env)

    val rawInput = env.fromElements(
      ("01", "sam", "23354"),
      ("02", "jake", "23352"),
      ("03", "kim", "23351"))

    val events = tableEnv.fromDataSet(rawInput, 'id, 'name, 'phone)
    tableEnv.registerTable("events", events)
    val resultTable = tableEnv
      .from("events")
      .select('id, 'name, 'phone)
      .where("phone === 'missing'")

    val results = resultTable.toDataSet[Row]

    results
      .map(row => new Visitor(row.getField(1).toString, row.getField(0).toString))
      .print

    val count: DataSet[Long] = env.fromElements(results.count())

    count
      .flatMap(new FlatMapFunction[Long, Collector[Long]]{

        override def flatMap(x: Long, collector: Collector[Collector[Long]]): Unit = {
          if (x == 0L) {
            throw new MissingResultException
          }
        }})

      .print()
  }
}

我用来检测结果集为空的方法感觉有点像黑客，但我想不出更好的方法了。请注意 print() 最后是必要的，尽管没有什么可打印的，因为任何没有最终输入到接收器的计算都会被优化掉，而不会执行。