A broadcast variable. Broadcast variables allow the programmer to keep a read-only variable cached on each machine rather than shipping a copy of it with tasks. They can be used, for example, to give every node a copy of a large input dataset in an efficient manner. Spark also attempts to distribute broadcast variables using efficient broadcast algorithms to reduce communication cost.
After the broadcast variable is created, it should be used instead of the value v in any functions run on the cluster so that v is not shipped to the nodes more than once. In addition, the object v should not be modified after it is broadcast in order to ensure that all nodes get the same value of the broadcast variable (e.g. if the variable is shipped to a new node later).
import org.apache.spark.broadcast.Broadcast
val broadcastVar = spark.sparkContext.broadcast(Array(1, 2, 3))
broadcastVar.value
val df1 = List(1, 2, 3).toDF("id")
val df2 = List((1, "Spark"), (2, "Scala"), (3, "ML")).toDF("id", "name")
val t = spark.sparkContext.broadcast(df2)
// 大表与小表连接，df2为小表
val df = df1.join(t.value, "id")
// 异步删除广播变量在每个执行器缓存副本
t.unpersist()