1. 程式人生 > >【雲星資料---Apache Flink實戰系列(精品版)】:Apache Flink高階特性與高階應用015-Flink中廣播變數和分散式快取001

【雲星資料---Apache Flink實戰系列(精品版)】:Apache Flink高階特性與高階應用015-Flink中廣播變數和分散式快取001

1.flink中的廣播變數

flink支援將變數廣播到worker上,以供程式運算使用。

執行程式

package code.book.batch.sinksource.scala
import java.util
import org.apache.flink.api.common.functions.RichMapFunction
import org.apache.flink.api.scala.{DataSet, ExecutionEnvironment, _}
import org.apache.flink.configuration.Configuration

object
BroadcastVariables001 {
def main(args: Array[String]): Unit = { val env = ExecutionEnvironment.getExecutionEnvironment //1.準備工人資料(用於map) case class Worker(name: String, salaryPerMonth: Double) val workers: DataSet[Worker] = env.fromElements( Worker("zhagnsan", 1356.67), Worker("lisi"
, 1476.67) ) //2準備統計資料(用於廣播,通過withBroadcastSet進行廣播) case class Count(name: String, month: Int) val counts: DataSet[Count] = env.fromElements( Count("zhagnsan", 4), Count("lisi", 5) ) //3.使用map資料和廣播資料進行計算 workers.map(new RichMapFunction[Worker, Worker] { private
var cwork: util.List[Count] = null override def open(parameters: Configuration): Unit = { super.open(parameters) // 3.1 訪問廣播資料 cwork = getRuntimeContext.getBroadcastVariable[Count]("countWorkInfo") } override def map(w: Worker): Worker = { //3.2解析廣播資料 var i = 0 while (i < cwork.size()) { val c = cwork.get(i) i += 1 if (c.name.equalsIgnoreCase(w.name)) { //有相應的資訊的返回值 return Worker(w.name, w.salaryPerMonth * c.month) } } //無相應的資訊的返回值 Worker("###", 0) } }).withBroadcastSet(counts, "countWorkInfo").print() } }

執行效果

Worker(zhagnsan,5426.68)
Worker(lisi,7383.35)