输出结果,只按id降序排序,没有按value1升序排序。
package com.opensourceteams.module.bigdata.flink.example.tableapi.operation.orderBy import org.apache.flink.api.scala.{ExecutionEnvironment, _} import org.apache.flink.table.api.TableEnvironment import org.apache.flink.table.api.scala._ object Run { def main(args: Array[String]): Unit = { val env = ExecutionEnvironment.getExecutionEnvironment val tableEnv = TableEnvironment.getTableEnvironment(env) env.setParallelism(1) val dataSet = env.fromElements( (1,"a",10),(2,"b",20) ,(20,"f",200),(3,"c",30) ) //从dataset转化为 table val table = tableEnv.fromDataSet(dataSet) //注册table tableEnv.registerTable("user1",table) //查询table 所有数据 tableEnv.scan("user1").as('id,'name,'value1) //.orderBy('id.asc) //按id列,升序排序(注意是按分区来排序) .orderBy('id.desc) .orderBy('value1.asc) .first(1000) //print 输出 (相当于sink) .print() /** * 输出结果 * * 20,f,200 * 3,c,30 * 2,b,20 * 1,a,10 */ } }