Apache spark 卡夫卡的火花流有错误numRecords不能为负值

这是一种奇怪的错误，因为我仍然将数据推送到卡夫卡并使用来自卡夫卡的消息 线程“main”java.lang.IllegalArgumentException中的异常：要求失败：numRecords不能为负 这也有点奇怪。我搜索，但没有得到任何相关的资源

让我解释一下我的集群。 我有一台服务器是master，代理运行mesos，在这台服务器上我设置了3个类似于kafka的代理。 然后我在集群上运行spark作业。 我正在使用

spark 1.5.2

brokers:
  id: 0
  active: true
  state: running
  resources: cpus:1.00, mem:1024, heap:512, port:31000
  failover: delay:1m, max-delay:10m
  stickiness: period:10m, hostname:test-master
  task:
    id: broker-0-c32082d0-a544-4260-b7c4-0239d99f0972
    state: running
    endpoint: test-master:31000
  metrics:
    collected: 2016-01-25 17:46:47+08
    under-replicated-partitions: 0
    offline-partitions-count: 0
    is-active-controller: 1

  id: 1
  active: true
  state: running
  resources: cpus:1.00, mem:1024, heap:512, port:31001
  failover: delay:1m, max-delay:10m
  stickiness: period:10m, hostname:test-master
  task:
    id: broker-1-7b30d6ad-6b19-4420-b743-c6f7f1adfb07
    state: running
    endpoint: test-master:31001
  metrics:
    collected: 2016-01-25 17:46:31+08
    under-replicated-partitions: 0
    offline-partitions-count: 0
    is-active-controller: 0

  id: 2
  active: true
  state: running
  resources: cpus:1.00, mem:1024, heap:512, port:31002
  failover: delay:1m, max-delay:10m
  stickiness: period:10m, hostname:test-master
  task:
    id: broker-2-8ef6437b-79b2-4183-8653-17cf2fe4591f
    state: running
    endpoint: test-master:31002
  metrics:
    collected: 2016-01-25 17:46:38+08
    under-replicated-partitions: 0
    offline-partitions-count: 0
    is-active-controller: 0

然后我运行spark streaming作业从kafka获取数据，然后进行解析

我查过经纪人正在使用

kafkacat -b test-master:31001,test-master:31000,test-master:31002 -t bid_event

它得到了数据，但当我运行spark作业时，我得到了错误

6/01/25 17:44:52 INFO SparkContext: Running Spark version 1.5.2
16/01/25 17:44:52 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/01/25 17:44:52 INFO SecurityManager: Changing view acls to: ubuntu
16/01/25 17:44:52 INFO SecurityManager: Changing modify acls to: ubuntu
16/01/25 17:44:52 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(ubuntu); users with modify permissions: Set(ubuntu)
16/01/25 17:44:53 INFO Slf4jLogger: Slf4jLogger started
16/01/25 17:44:53 INFO Remoting: Starting remoting
16/01/25 17:44:53 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriver@10.xxx.xxx.25:51816]
16/01/25 17:44:53 INFO Utils: Successfully started service 'sparkDriver' on port 51816.
16/01/25 17:44:53 INFO SparkEnv: Registering MapOutputTracker
16/01/25 17:44:53 INFO SparkEnv: Registering BlockManagerMaster
16/01/25 17:44:53 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-97e9787b-3a67-4d00-aff6-a5e02b271a74
16/01/25 17:44:53 INFO MemoryStore: MemoryStore started with capacity 441.9 MB
16/01/25 17:44:53 INFO HttpFileServer: HTTP File server directory is /tmp/spark-442ac339-2ac7-427f-9e6b-5b5cb18a54dd/httpd-4724a937-4d03-4bd0-99f1-7b9f1129291e
16/01/25 17:44:53 INFO HttpServer: Starting HTTP Server
16/01/25 17:44:53 INFO Utils: Successfully started service 'HTTP file server' on port 51817.
16/01/25 17:44:53 INFO SparkEnv: Registering OutputCommitCoordinator
16/01/25 17:44:53 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/01/25 17:44:53 INFO SparkUI: Started SparkUI at http://10.xxx.xxx.25:4040
16/01/25 17:44:54 INFO SparkContext: Added JAR file:/home/ubuntu/spark-jobs/./rtb_spark-assembly-1.0-deps.jar at http://10.xxx.xxx.25:51817/jars/rtb_spark-assembly-1.0-deps.jar with timestamp 1453715094219
16/01/25 17:44:54 INFO SparkContext: Added JAR file:/home/ubuntu/spark-jobs/./rtb-spark.jar at http://10.xxx.xxx.25:51817/jars/rtb-spark.jar with timestamp 1453715094222
16/01/25 17:44:54 INFO Utils: Copying /home/ubuntu/spark-jobs/./test.conf to /tmp/spark-442ac339-2ac7-427f-9e6b-5b5cb18a54dd/userFiles-cdef27e0-c357-4ebb-adcf-ccf963ff9d60/test.conf
16/01/25 17:44:54 INFO SparkContext: Added file file:/home/ubuntu/spark-jobs/./test.conf at http://10.xxx.xxx.25:51817/files/test.conf with timestamp 1453715094309
16/01/25 17:44:54 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@712: Client environment:zookeeper.version=zookeeper C client 3.4.5
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@716: Client environment:host.name=knx-rtb-server-google-test
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@723: Client environment:os.name=Linux
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@724: Client environment:os.arch=3.13.0-76-generic
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@725: Client environment:os.version=#120~precise1-Ubuntu SMP Tue Jan 19 11:09:43 UTC 2016
I0125 17:44:54.444169  5444 sched.cpp:166] Version: 0.26.0
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@733: Client environment:user.name=ubuntu
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@741: Client environment:user.home=/home/ubuntu
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@log_env@753: Client environment:user.dir=/home/ubuntu/spark-jobs
2016-01-25 17:44:54,444:5202(0x7f2d7604f700):ZOO_INFO@zookeeper_init@786: Initiating client connection, host=test-master:2181 sessionTimeout=10000 watcher=0x7f2ded821210 sessionId=0 sessionPasswd=<null> context=0x7f2d54001470 flags=0
2016-01-25 17:44:54,444:5202(0x7f2d6e6fb700):ZOO_INFO@check_events@1703: initiated connection to server [10.xxx.xxx.25:2181]
2016-01-25 17:44:54,446:5202(0x7f2d6e6fb700):ZOO_INFO@check_events@1750: session establishment complete on server [10.xxx.xxx.25:2181], sessionId=0x15278112832012c, negotiated timeout=10000
I0125 17:44:54.447082  5439 group.cpp:331] Group process (group(1)@10.xxx.xxx.25:28249) connected to ZooKeeper
I0125 17:44:54.447120  5439 group.cpp:805] Syncing group operations: queue size (joins, cancels, datas) = (0, 0, 0)
I0125 17:44:54.447140  5439 group.cpp:403] Trying to create path '/mesos' in ZooKeeper
I0125 17:44:54.448109  5439 detector.cpp:156] Detected a new leader: (id='28')
I0125 17:44:54.448246  5439 group.cpp:674] Trying to get '/mesos/json.info_0000000028' in ZooKeeper
I0125 17:44:54.448755  5440 detector.cpp:482] A new leading master (UPID=master@10.xxx.xxx.25:5050) is detected
I0125 17:44:54.448832  5440 sched.cpp:264] New master detected at master@10.xxx.xxx.25:5050
I0125 17:44:54.448977  5440 sched.cpp:274] No credentials provided. Attempting to register without authentication
I0125 17:44:54.449766  5440 sched.cpp:643] Framework registered with a636c17f-2b0d-46f7-9b15-5a3d6e9918a4-0003
16/01/25 17:44:54 INFO MesosSchedulerBackend: Registered as framework ID a636c17f-2b0d-46f7-9b15-5a3d6e9918a4-0003
16/01/25 17:44:54 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 51820.
16/01/25 17:44:54 INFO NettyBlockTransferService: Server created on 51820
16/01/25 17:44:54 INFO BlockManagerMaster: Trying to register BlockManager
16/01/25 17:44:54 INFO BlockManagerMasterEndpoint: Registering block manager 10.xxx.xxx.25:51820 with 441.9 MB RAM, BlockManagerId(driver, 10.xxx.xxx.25, 51820)
16/01/25 17:44:54 INFO BlockManagerMaster: Registered BlockManager
16/01/25 17:44:55 INFO ForEachDStream: metadataCleanupDelay = -1
16/01/25 17:44:55 INFO DirectKafkaInputDStream: metadataCleanupDelay = -1
16/01/25 17:44:55 INFO DirectKafkaInputDStream: Slide time = 30000 ms
16/01/25 17:44:55 INFO DirectKafkaInputDStream: Storage level = StorageLevel(false, false, false, false, 1)
16/01/25 17:44:55 INFO DirectKafkaInputDStream: Checkpoint interval = null
16/01/25 17:44:55 INFO DirectKafkaInputDStream: Remember duration = 30000 ms
16/01/25 17:44:55 INFO DirectKafkaInputDStream: Initialized and validated org.apache.spark.streaming.kafka.DirectKafkaInputDStream@270235cb
16/01/25 17:44:55 INFO ForEachDStream: Slide time = 30000 ms
16/01/25 17:44:55 INFO ForEachDStream: Storage level = StorageLevel(false, false, false, false, 1)
16/01/25 17:44:55 INFO ForEachDStream: Checkpoint interval = null
16/01/25 17:44:55 INFO ForEachDStream: Remember duration = 30000 ms
16/01/25 17:44:55 INFO ForEachDStream: Initialized and validated org.apache.spark.streaming.dstream.ForEachDStream@219b66f
16/01/25 17:44:55 INFO RecurringTimer: Started timer for JobGenerator at time 1453715100000
16/01/25 17:44:55 INFO JobGenerator: Started JobGenerator at 1453715100000 ms
16/01/25 17:44:55 INFO JobScheduler: Started JobScheduler
16/01/25 17:44:55 INFO StreamingContext: StreamingContext started
16/01/25 17:45:00 INFO VerifiableProperties: Verifying properties
16/01/25 17:45:00 INFO VerifiableProperties: Property auto.commit.interval.ms is overridden to 1000
16/01/25 17:45:00 INFO VerifiableProperties: Property auto.offset.reset is overridden to smallest
16/01/25 17:45:00 INFO VerifiableProperties: Property group.id is overridden to bid_event_consumer_group_zk
16/01/25 17:45:00 INFO VerifiableProperties: Property zookeeper.connect is overridden to test-master:2181
16/01/25 17:45:00 INFO VerifiableProperties: Property zookeeper.session.timeout.ms is overridden to 400
16/01/25 17:45:00 INFO VerifiableProperties: Property zookeeper.sync.time.ms is overridden to 200
16/01/25 17:45:00 ERROR JobScheduler: Error generating jobs for time 1453715100000 ms
java.lang.IllegalArgumentException: requirement failed: numRecords must not be negative
    at scala.Predef$.require(Predef.scala:233)
    at org.apache.spark.streaming.scheduler.StreamInputInfo.<init>(InputInfoTracker.scala:38)
    at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:165)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
    at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
    at scala.Option.orElse(Option.scala:257)
    at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
    at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38)
    at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)
    at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
    at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
    at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:120)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:247)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:245)
    at scala.util.Try$.apply(Try.scala:161)
    at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:245)
    at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:181)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:87)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:86)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
Exception in thread "main" java.lang.IllegalArgumentException: requirement failed: numRecords must not be negative
    at scala.Predef$.require(Predef.scala:233)
    at org.apache.spark.streaming.scheduler.StreamInputInfo.<init>(InputInfoTracker.scala:38)
    at org.apache.spark.streaming.kafka.DirectKafkaInputDStream.compute(DirectKafkaInputDStream.scala:165)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1$$anonfun$apply$7.apply(DStream.scala:350)
    at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1$$anonfun$1.apply(DStream.scala:349)
    at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:399)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:344)
    at org.apache.spark.streaming.dstream.DStream$$anonfun$getOrCompute$1.apply(DStream.scala:342)
    at scala.Option.orElse(Option.scala:257)
    at org.apache.spark.streaming.dstream.DStream.getOrCompute(DStream.scala:339)
    at org.apache.spark.streaming.dstream.ForEachDStream.generateJob(ForEachDStream.scala:38)
    at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)
    at org.apache.spark.streaming.DStreamGraph$$anonfun$1.apply(DStreamGraph.scala:120)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
    at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:251)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:251)
    at scala.collection.AbstractTraversable.flatMap(Traversable.scala:105)
    at org.apache.spark.streaming.DStreamGraph.generateJobs(DStreamGraph.scala:120)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:247)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$2.apply(JobGenerator.scala:245)
    at scala.util.Try$.apply(Try.scala:161)
    at org.apache.spark.streaming.scheduler.JobGenerator.generateJobs(JobGenerator.scala:245)
    at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:181)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:87)
    at org.apache.spark.streaming.scheduler.JobGenerator$$anon$1.onReceive(JobGenerator.scala:86)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
16/01/25 17:45:00 INFO StreamingContext: Invoking stop(stopGracefully=false) from shutdown hook
16/01/25 17:45:00 INFO JobGenerator: Stopping JobGenerator immediately
16/01/25 17:45:00 INFO RecurringTimer: Stopped timer for JobGenerator after time 1453715100000
16/01/25 17:45:00 INFO JobGenerator: Stopped JobGenerator
16/01/25 17:45:00 INFO JobScheduler: Stopped JobScheduler
16/01/25 17:45:00 INFO StreamingContext: StreamingContext stopped successfully
16/01/25 17:45:00 INFO SparkContext: Invoking stop() from shutdown hook
16/01/25 17:45:00 INFO SparkUI: Stopped Spark web UI at http://10.xxx.xxx.25:4040
16/01/25 17:45:00 INFO DAGScheduler: Stopping DAGScheduler
I0125 17:45:00.281819  5579 sched.cpp:1805] Asked to stop the driver
I0125 17:45:00.281951  5437 sched.cpp:1043] Stopping framework 'a636c17f-2b0d-46f7-9b15-5a3d6e9918a4-0003'
16/01/25 17:45:00 INFO MesosSchedulerBackend: driver.run() returned with code DRIVER_STOPPED
16/01/25 17:45:00 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
16/01/25 17:45:00 INFO MemoryStore: MemoryStore cleared
16/01/25 17:45:00 INFO BlockManager: BlockManager stopped
16/01/25 17:45:00 INFO BlockManagerMaster: BlockManagerMaster stopped
16/01/25 17:45:00 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
16/01/25 17:45:00 INFO SparkContext: Successfully stopped SparkContext
16/01/25 17:45:00 INFO ShutdownHookManager: Shutdown hook called
16/01/25 17:45:00 INFO ShutdownHookManager: Deleting directory /tmp/spark-442ac339-2ac7-427f-9e6b-5b5cb18a54dd

6/01/25 17:44:52信息SparkContext:运行Spark版本1.5.2
16/01/25 17:44:52警告NativeCodeLoader:无法为您的平台加载本机hadoop库。。。在适用的情况下使用内置java类
16/01/25 17:44:52信息安全管理器：将视图ACL更改为：ubuntu
16/01/25 17:44:52信息安全管理器：将修改ACL更改为：ubuntu
16/01/25 17:44:52信息安全管理器：安全管理器：身份验证已禁用；ui ACL被禁用；具有查看权限的用户：Set（ubuntu）；具有修改权限的用户：Set（ubuntu）
16/01/25 17:44:53信息Slf4jLogger:Slf4jLogger已启动
16/01/25 17:44:53信息远程处理：开始远程处理
16/01/25 17:44:53信息远程处理：远程处理已开始；收听地址：[阿克卡。tcp://sparkDriver@10.xxx.xxx.25:51816]
16/01/25 17:44:53信息用途：已在端口51816上成功启动服务“sparkDriver”。
16/01/25 17:44:53信息SparkEnv:正在注册MapOutputTracker
16/01/25 17:44:53信息SparkEnv:正在注册BlockManagerMaster
16/01/25 17:44:53信息DiskBlockManager:已在/tmp/blockmgr-97e9787b-3a67-4d00-aff6-a5e02b271a74创建本地目录
16/01/25 17:44:53信息MemoryStore:MemoryStore以441.9 MB的容量启动
16/01/25 17:44:53信息HttpFileServer:HTTP文件服务器目录是/tmp/spark-442ac339-2ac7-427f-9e6b-5b5cb18a54dd/httpd-4724a937-4d03-4bd0-99f1-7b9f112921e
16/01/25 17:44:53信息HttpServer:正在启动HTTP服务器
16/01/25 17:44:53信息实用程序：已在端口51817上成功启动服务“HTTP文件服务器”。
16/01/25 17:44:53信息SparkEnv:正在注册OutputCommitCoordinator
16/01/25 17:44:53信息实用程序：已在端口4040上成功启动服务“SparkUI”。
16/01/25 17:44:53信息斯巴库伊：斯巴库伊于http://10.xxx.xxx.25:4040
16/01/25 17:44:54信息SparkContext：添加JAR文件：/home/ubuntu/spark jobs//rtb_spark-assembly-1.0-deps.JAR位于http://10.xxx.xxx.25:51817/jars/rtb_spark-assembly-1.0-deps.jar，时间戳为1453715094219
16/01/25 17:44:54信息SparkContext：添加JAR文件：/home/ubuntu/spark jobs//rtb-spark.JAR位于http://10.xxx.xxx.25:51817/jars/rtb-spark.jar，时间戳为1453715094222
16/01/25 17:44:54信息实用程序：将/home/ubuntu/spark jobs//test.conf复制到/tmp/spark-442ac339-2ac7-427f-9e6b-5b5cb18a54dd/userFiles-cdef27e0-c357-4ebb-adcf-ccf963ff9d60/test.conf
16/01/25 17:44:54信息SparkContext：添加文件：/home/ubuntu/spark jobs//test.confhttp://10.xxx.xxx.25:51817/files/test.conf 时间戳为1453715094309
16/01/25 17:44:54警告MetricsSystem:对源使用默认名称DAGScheduler，因为未设置spark.app.id。
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@712:客户端环境：zookeeper.version=zookeeper C客户端3.4.5
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@716:客户端环境：host.name=knx rtb服务器google测试
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@723:客户端环境：os.name=Linux
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@724:客户端环境：os.arch=3.13.0-76-generic
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@725：客户端环境：os.version=#120~precise1 Ubuntu SMP周二1月19日11:09:43 UTC 2016
I0125 17:44:54.444169 5444附表cpp:166]版本：0.26.0
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@733:客户端环境：user.name=ubuntu
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@741:客户端环境：user.home=/home/ubuntu
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@log_env@753:客户端环境：user.dir=/home/ubuntu/spark jobs
2016-01-25 17:44:54444:5202（0x7f2d7604f700）：动物园_INFO@zookeeper_init@786:启动客户端连接，主机=测试主机：2181 sessionTimeout=10000 watcher=0x7f2ded821210 sessionId=0 sessionPasswd=context=0x7f2d54001470标志=0
2016-01-25 17:44:54444:5202（0x7f2d6e6fb700）：动物园_INFO@check_events@1703:已启动与服务器的连接[10.xxx.xxx.25:2181]
2016-01-25 17:44:54446:5202（0x7f2d6e6fb700）：动物园_INFO@check_events@1750:在服务器[10.xxx.xxx.25:2181]上完成会话建立，会话ID=0x15278112832012c，协商超时=10000
I0125 17:44:54.447082 5439 group.cpp:331]组进程（组（1）@10.xxx.xxx.25:28249）已连接到ZooKeeper
I0125 17:44:54.447120 5439组。cpp:805]同步组操作：队列大小（加入、取消、数据）=（0,0,0）
I0125 17:44:54.447140 5439组。cpp:403]正在尝试在ZooKeeper中创建路径“/mesos”
I0125 17:44:54.448109 5439检测器。cpp:156]检测到新的前导：（id='28'）
I0125 17:44:54.448246 5439 group.cpp:674]正在尝试在ZooKeeper中获取“/mesos/json.info_0000000028”
I0125 17:44:54.448755 5440检测器。cpp:482]一个新的主引导（UPID=master@10.xxx.xxx.25：5050）被检测到
I0125 17:44:54.448832 5440 sched.cpp:264]在检测到新的主设备master@10.xxx.xxx.25:5050
I0125 17:44:54.448977 5440附表cpp:274]未提供凭据。正在尝试在没有身份验证的情况下注册
I0125 17:44:54.449766 5440 sched.cpp:643]使用a636c17f-2b0d-46f7-9b15-5a3d6e9918a4-0003注册的框架
16/01/25 17:44:54信息MesosSchedulerBackend:注册为框架ID a636c17f-2b0d-46f7-9b15-5a3d6e9918a4-0003
16/01/25 17:44:54信息实用程序：已成功启动服务“org.apache.spark.network.netty.NettyBlockTransferServi”