为什么lines.map不起作用,但spark.take.map在Spark中起作用?
问题描述:
我是Scala和Spark的新手。为什么lines.map不起作用,但spark.take.map在Spark中起作用?
但我跑进与这部分代码的一个问题:
60 val lines = sc.textFile(inputPath)
61 val points = lines.map(parsePoint _).cache()
62 val ITERATIONS = args(2).toInt
线61不起作用。之后我把它改成这样:
60 val lines = sc.textFile(inputPath)
61 val points = lines.take(149800).map(parsePoint _) //149800 is the total number of lines
62 val ITERATIONS = args(2).toInt
从SBT运行错误味精是:
[error] (run-main) org.apache.spark.SparkException: Job failed: Task 0.0:1 failed more than 4 times
org.apache.spark.SparkException: Job failed: Task 0.0:1 failed more than 4 times
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:760)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:758)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:60)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:758)
at org.apache.spark.scheduler.DAGScheduler.processEvent(DAGScheduler.scala:379)
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$run(DAGScheduler.scala:441)
at org.apache.spark.scheduler.DAGScheduler$$anon$1.run(DAGScheduler.scala:149)
java.lang.RuntimeException: Nonzero exit code: 1
at scala.sys.package$.error(package.scala:27)
[error] {file:/var/sdb/home/tim.tan/workspace/spark/}default-d3d73f/compile:run: Nonzero exit code: 1
[error] Total time: 52 s, completed Dec 20, 2013 5:42:18 PM
任务节点的性病的错误是:
13/12/20 17:42:16 INFO slf4j.Slf4jEventHandler: Slf4jEventHandler started
13/12/20 17:42:16 INFO executor.StandaloneExecutorBackend: Connecting to driver: akka://[email protected]:38975/user/StandaloneScheduler
13/12/20 17:42:17 INFO executor.StandaloneExecutorBackend: Successfully registered with driver
13/12/20 17:42:17 INFO slf4j.Slf4jEventHandler: Slf4jEventHandler started
13/12/20 17:42:17 INFO spark.SparkEnv: Connecting to BlockManagerMaster: akka://[email protected]:38975/user/BlockManagerMaster
13/12/20 17:42:17 INFO storage.MemoryStore: MemoryStore started with capacity 323.9 MB.
13/12/20 17:42:17 INFO storage.DiskStore: Created local directory at /tmp/spark-local-20131220174217-be8e
13/12/20 17:42:17 INFO network.ConnectionManager: Bound socket to port 52043 with id = ConnectionManagerId(TS-BH90,52043)
13/12/20 17:42:17 INFO storage.BlockManagerMaster: Trying to register BlockManager
13/12/20 17:42:17 INFO storage.BlockManagerMaster: Registered BlockManager
13/12/20 17:42:17 INFO spark.SparkEnv: Connecting to MapOutputTracker: akka://[email protected]:38975/user/MapOutputTracker
13/12/20 17:42:17 INFO spark.HttpFileServer: HTTP File server directory is /tmp/spark-1b1a6c0b-965e-4834-a3d3-554c95442041
13/12/20 17:42:17 INFO server.Server: jetty-7.x.y-SNAPSHOT
13/12/20 17:42:17 INFO server.AbstractConnector: Started [email protected]:41811
13/12/20 17:42:18 ERROR executor.StandaloneExecutorBackend: Driver terminated or disconnected! Shutting down.
日志中工人如下:
13/12/19 17:49:26 INFO worker.Worker: Asked to launch executor app-20131219174926-0001/2 for SparkHdfsLR
13/12/19 17:49:26 INFO worker.ExecutorRunner: Launch command: "java" "-cp" ":/var/bh/spark/conf:/var/bh/spark/assembly/target/scala-2.9.3/spark-assembly-0.8.0-incubating-hadoop1.0.3.jar:/var/bh/spark/core/target/scala-2.9.3/test-classes:/var/bh/spark/repl/target/scala-2.9.3/test-classes:/var/bh/spark/mllib/target/scala-2.9.3/test-classes:/var/bh/spark/bagel/target/scala-2.9.3/test-classes:/var/bh/spark/streaming/target/scala-2.9.3/test-classes" "-Djava.library.path=/var/bh/hadoop/lib/native/Linux-amd64-64/" "-Xms512M" "-Xmx512M" "org.apache.spark.executor.StandaloneExecutorBackend" "akka://[email protected]:56158/user/StandaloneScheduler" "2" "TS-BH87" "8"
13/12/19 17:49:30 INFO worker.Worker: Asked to kill executor app-20131219174926-0001/2
13/12/19 17:49:30 INFO worker.ExecutorRunner: Runner thread for executor app-20131219174926-0001/2 interrupted
13/12/19 17:49:30 INFO worker.ExecutorRunner: Killing process!
它看起来像e工人负载未成功启动。
我不知道为什么。有没有人可以给我一个建议?
答
我发现它为什么不起作用。
由于配置错误,spark只能在standalone模式下工作。更正配置,如果你想在分布式模式下运行的代码,最后两个参数必须是具体的功能SparkContext:
new SparkContext(master, jobName, [sparkHome], [jars])
如果最后两个参数是不特定,斯卡拉脚本只能工作在独立模式。
请指定'lines'的类型。 – senia
@senia它是[RDD](https://spark.incubator.apache.org/docs/0.6.0/api/core/spark/RDD.html) –
你是什么意思的“不工作”? –