【云星数据---Apache Flink实战系列(精品版)】：Apache Flink高级特性与高级应用019-Flink中参数传递和容错设定003

3.通过ExecutionConfig向Function传递参数

执行程序

package code.book.batch.sinksource.scalaimport org.apache.flink.api.common.functions.RichMapFunctionimport org.apache.flink.api.scala.{DataSet, ExecutionEnvironment, _}import org.apache.flink.configuration.Configuration/**  * Globally via the ExecutionConfig  * *  * Flink also allows to pass custom configuration values to the ExecutionConfig  * interface of the environment. Since the execution config is accessible in all  * (rich) user functions, the custom configuration will be available globally in all functions.  */object Parameters003scala {  def main(args: Array[String]): Unit = {    val env = ExecutionEnvironment.getExecutionEnvironment    //1.准备工人数据    case class Worker(name: String, salaryPerMonth: Double)    val workers: DataSet[Worker] = env.fromElements(      Worker("zhagnsan", 1356.67),      Worker("lisi", 1476.67)    )    //2.准备工作月份数据，作为参数用Configuration传递出去    val conf = new Configuration()    conf.setString("month", "4")    env.getConfig.setGlobalJobParameters(conf)    //3.接受参数进行计算（如果要用Configuration传参，需要用RichFunction接受）    workers.map(new RichMapFunction[Worker, Worker] {      private var m = 0      override def open(parameters: Configuration): Unit = {        super.open(parameters)        //3.1获取Configuration传递过来的参数        val globalParams = this.getRuntimeContext.getExecutionConfig.getGlobalJobParameters        m = globalParams.toMap.get("month").trim.toInt      }      override def map(w: Worker): Worker = {        //3.2计算最新工人工资信息        Worker(w.name, w.salaryPerMonth * m)      }    }).print  }}

执行效果

Worker(zhagnsan,5426.68)Worker(lisi,5906.68)