Spark广播变量使用示例

原创

a772304419 2022-01-19 09:43:01 ©著作权

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Spark广播变量使用示例

实现原理

广播变量用来高效分发较大的对象。向所有工作节点发送一个较大的只读值，以供一个或多个 Spark 操作使用。比如，如果你的应用需要向所有节点发送一个较大的只读查询表，广播变量用起来都很顺手。在多个并行操作中使用同一个变量，但是 Spark 会为每个任务分别发送。

代码

package com.zxl.spark.core

import org.apache.spark.broadcast.Broadcast
import org.apache.spark.rdd.RDD
import org.apache.spark.{SparkConf, SparkContext}

object BroadcastDemo {
  def main(args: Array[String]): Unit = {
    val conf: SparkConf = new SparkConf().setMaster("local[4]").setAppName("BroadcastDemo")
    val sc: SparkContext = new SparkContext(conf)
    val rdd: RDD[(String, Int)] = sc.makeRDD(List( ("a",1), ("b", 2), ("c", 3), ("d", 4) ),4)
    val list: List[(String, Int)] = List(("a", 4), ("b", 5), ("c", 6), ("d", 7))
    val broadcast: Broadcast[List[(String, Int)]] = sc.broadcast(list)
    rdd.map{
      case (key,num)=>{
        var num2=0
        for ((k,v) <- broadcast.value) {
          if (k==key){
            num2=v
          }
        }
        (key,(num,num2))
      }
    }.collect().foreach(println)
  }
}

执行日志

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com.zxl.spark.core.BroadcastDemo
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
21/08/18 14:44:44 INFO SparkContext: Running Spark version 3.1.1
21/08/18 14:44:44 INFO ResourceUtils: ==============================================================
21/08/18 14:44:44 INFO ResourceUtils: No custom resources configured for spark.driver.
21/08/18 14:44:44 INFO ResourceUtils: ==============================================================
21/08/18 14:44:44 INFO SparkContext: Submitted application: BroadcastDemo
21/08/18 14:44:44 INFO ResourceProfile: Default ResourceProfile created, executor resources: Map(cores -> name: cores, amount: 1, script: , vendor: , memory -> name: memory, amount: 1024, script: , vendor: , offHeap -> name: offHeap, amount: 0, script: , vendor: ), task resources: Map(cpus -> name: cpus, amount: 1.0)
21/08/18 14:44:44 INFO ResourceProfile: Limiting resource is cpu
21/08/18 14:44:44 INFO ResourceProfileManager: Added ResourceProfile id: 0
21/08/18 14:44:44 INFO SecurityManager: Changing view acls to: 张学亮,ÕÅѧÁÁ
21/08/18 14:44:44 INFO SecurityManager: Changing modify acls to: 张学亮,ÕÅѧÁÁ
21/08/18 14:44:44 INFO SecurityManager: Changing view acls groups to: 
21/08/18 14:44:44 INFO SecurityManager: Changing modify acls groups to: 
21/08/18 14:44:44 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users  with view permissions: Set(张学亮, ÕÅѧÁÁ); groups with view permissions: Set(); users  with modify permissions: Set(张学亮, ÕÅѧÁÁ); groups with modify permissions: Set()
21/08/18 14:44:45 INFO Utils: Successfully started service 'sparkDriver' on port 56188.
21/08/18 14:44:45 INFO SparkEnv: Registering MapOutputTracker
21/08/18 14:44:45 INFO SparkEnv: Registering BlockManagerMaster
21/08/18 14:44:45 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
21/08/18 14:44:45 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
21/08/18 14:44:45 INFO SparkEnv: Registering BlockManagerMasterHeartbeat
21/08/18 14:44:45 INFO DiskBlockManager: Created local directory at C:\Users\zhang\AppData\Local\Temp\blockmgr-9d014bd5-0519-4a17-8982-462103a3e295
21/08/18 14:44:45 INFO MemoryStore: MemoryStore started with capacity 1987.5 MiB
21/08/18 14:44:45 INFO SparkEnv: Registering OutputCommitCoordinator
21/08/18 14:44:45 INFO Utils: Successfully started service 'SparkUI' on port 4040.
21/08/18 14:44:45 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://ZXLT:4040
21/08/18 14:44:46 INFO Executor: Starting executor ID driver on host ZXLT
21/08/18 14:44:46 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 56223.
21/08/18 14:44:46 INFO NettyBlockTransferService: Server created on ZXLT:56223
21/08/18 14:44:46 INFO BlockManager: Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
21/08/18 14:44:46 INFO BlockManagerMaster: Registering BlockManager BlockManagerId(driver, ZXLT, 56223, None)
21/08/18 14:44:46 INFO BlockManagerMasterEndpoint: Registering block manager ZXLT:56223 with 1987.5 MiB RAM, BlockManagerId(driver, ZXLT, 56223, None)
21/08/18 14:44:46 INFO BlockManagerMaster: Registered BlockManager BlockManagerId(driver, ZXLT, 56223, None)
21/08/18 14:44:46 INFO BlockManager: Initialized BlockManager: BlockManagerId(driver, ZXLT, 56223, None)
21/08/18 14:44:46 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 488.0 B, free 1987.5 MiB)
21/08/18 14:44:46 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 326.0 B, free 1987.5 MiB)
21/08/18 14:44:46 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on ZXLT:56223 (size: 326.0 B, free: 1987.5 MiB)
21/08/18 14:44:46 INFO SparkContext: Created broadcast 0 from broadcast at BroadcastDemo.scala:13
21/08/18 14:44:46 INFO SparkContext: Starting job: collect at BroadcastDemo.scala:14
21/08/18 14:44:46 INFO DAGScheduler: Got job 0 (collect at BroadcastDemo.scala:14) with 4 output partitions
21/08/18 14:44:46 INFO DAGScheduler: Final stage: ResultStage 0 (collect at BroadcastDemo.scala:14)
21/08/18 14:44:46 INFO DAGScheduler: Parents of final stage: List()
21/08/18 14:44:46 INFO DAGScheduler: Missing parents: List()
21/08/18 14:44:46 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at map at BroadcastDemo.scala:14), which has no missing parents
21/08/18 14:44:46 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 3.5 KiB, free 1987.5 MiB)
21/08/18 14:44:46 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2013.0 B, free 1987.5 MiB)
21/08/18 14:44:46 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on ZXLT:56223 (size: 2013.0 B, free: 1987.5 MiB)
21/08/18 14:44:46 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:1383
21/08/18 14:44:46 INFO DAGScheduler: Submitting 4 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at BroadcastDemo.scala:14) (first 15 tasks are for partitions Vector(0, 1, 2, 3))
21/08/18 14:44:46 INFO TaskSchedulerImpl: Adding task set 0.0 with 4 tasks resource profile 0
21/08/18 14:44:46 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0) (ZXLT, executor driver, partition 0, PROCESS_LOCAL, 4508 bytes) taskResourceAssignments Map()
21/08/18 14:44:46 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1) (ZXLT, executor driver, partition 1, PROCESS_LOCAL, 4508 bytes) taskResourceAssignments Map()
21/08/18 14:44:46 INFO TaskSetManager: Starting task 2.0 in stage 0.0 (TID 2) (ZXLT, executor driver, partition 2, PROCESS_LOCAL, 4508 bytes) taskResourceAssignments Map()
21/08/18 14:44:46 INFO TaskSetManager: Starting task 3.0 in stage 0.0 (TID 3) (ZXLT, executor driver, partition 3, PROCESS_LOCAL, 4508 bytes) taskResourceAssignments Map()
21/08/18 14:44:46 INFO Executor: Running task 1.0 in stage 0.0 (TID 1)
21/08/18 14:44:46 INFO Executor: Running task 3.0 in stage 0.0 (TID 3)
21/08/18 14:44:46 INFO Executor: Running task 2.0 in stage 0.0 (TID 2)
21/08/18 14:44:46 INFO Executor: Running task 0.0 in stage 0.0 (TID 0)
21/08/18 14:44:46 INFO Executor: Finished task 0.0 in stage 0.0 (TID 0). 1063 bytes result sent to driver
21/08/18 14:44:46 INFO Executor: Finished task 2.0 in stage 0.0 (TID 2). 1063 bytes result sent to driver
21/08/18 14:44:46 INFO Executor: Finished task 1.0 in stage 0.0 (TID 1). 1063 bytes result sent to driver
21/08/18 14:44:46 INFO Executor: Finished task 3.0 in stage 0.0 (TID 3). 1063 bytes result sent to driver
21/08/18 14:44:46 INFO TaskSetManager: Finished task 2.0 in stage 0.0 (TID 2) in 265 ms on ZXLT (executor driver) (1/4)
21/08/18 14:44:46 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 288 ms on ZXLT (executor driver) (2/4)
21/08/18 14:44:46 INFO TaskSetManager: Finished task 3.0 in stage 0.0 (TID 3) in 267 ms on ZXLT (executor driver) (3/4)
21/08/18 14:44:46 INFO TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 268 ms on ZXLT (executor driver) (4/4)
21/08/18 14:44:46 INFO TaskSchedulerImpl: Removed TaskSet 0.0, whose tasks have all completed, from pool 
21/08/18 14:44:46 INFO DAGScheduler: ResultStage 0 (collect at BroadcastDemo.scala:14) finished in 0.339 s
21/08/18 14:44:46 INFO DAGScheduler: Job 0 is finished. Cancelling potential speculative or zombie tasks for this job
21/08/18 14:44:46 INFO TaskSchedulerImpl: Killing all running tasks in stage 0: Stage finished
21/08/18 14:44:46 INFO DAGScheduler: Job 0 finished: collect at BroadcastDemo.scala:14, took 0.387019 s
(a,(1,4))
(b,(2,5))
(c,(3,6))
(d,(4,7))
21/08/18 14:44:47 INFO SparkContext: Invoking stop() from shutdown hook
21/08/18 14:44:47 INFO SparkUI: Stopped Spark web UI at http://ZXLT:4040
21/08/18 14:44:47 INFO BlockManagerInfo: Removed broadcast_1_piece0 on ZXLT:56223 in memory (size: 2013.0 B, free: 1987.5 MiB)
21/08/18 14:44:47 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
21/08/18 14:44:47 INFO MemoryStore: MemoryStore cleared
21/08/18 14:44:47 INFO BlockManager: BlockManager stopped
21/08/18 14:44:47 INFO BlockManagerMaster: BlockManagerMaster stopped
21/08/18 14:44:47 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
21/08/18 14:44:47 INFO SparkContext: Successfully stopped SparkContext
21/08/18 14:44:47 INFO ShutdownHookManager: Shutdown hook called
21/08/18 14:44:47 INFO ShutdownHookManager: Deleting directory C:\Users\zhang\AppData\Local\Temp\spark-5620def7-287d-406e-8806-49265b19bf44

Process finished with exit code 0