【云星数据---Apache Flink实战系列(精品版)】：Apache Flink高级特性与高级应用015-Flink中广播变量和分布式缓存001

1.flink中的广播变量

flink支持将变量广播到worker上，以供程序运算使用。

执行程序

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.准备工人数据（用于map）
case class Worker(name: String, salaryPerMonth: Double)
val workers: DataSet[Worker] = env.fromElements(
Worker("zhagnsan", 1356.67),
Worker("lisi", 1476.67)
)
//2准备统计数据(用于广播，通过withBroadcastSet进行广播)
case class Count(name: String, month: Int)
val counts: DataSet[Count] = env.fromElements(
Count("zhagnsan", 4),
Count("lisi", 5)
)

//3.使用map数据和广播数据进行计算
workers.map(new RichMapFunction[Worker, Worker] {
private var cwork: util.List[Count] = null

override def open(parameters: Configuration): Unit = {
super.open(parameters)
// 3.1 访问广播数据
cwork = getRuntimeContext.getBroadcastVariable[Count]("countWorkInfo")
}

override def map(w: Worker): Worker = {
//3.2解析广播数据
var i = 0
while (i < cwork.size()) {
val c = cwork.get(i)
i += 1
if (c.name.equalsIgnoreCase(w.name)) {
//有相应的信息的返回值
return Worker(w.name, w.salaryPerMonth * c.month)
}
}
//无相应的信息的返回值
Worker("###", 0)
}
}).withBroadcastSet(counts, "countWorkInfo").print()
}
}

执行效果

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