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https://issues.apache.org/jira/browse/SPARK-11327?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15009189#comment-15009189
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Jo Voordeckers commented on SPARK-11327:
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I've seen similar issues, when running on mesos (no docker tho).
The Mesos Dispatcher only sets the class, jar and cpu/mem resources when
spinning up a new executor, all the spark properties (UI port, classpath order,
system properties, jvm opts, etc...) passed to the dispatcher via spark-submit
are not passed along in the commandline.
I've made a quick patch that solves this for me:
https://github.com/apache/spark/pull/9752/
I need to debug some more, because [~dragos] found this, which suggests it does
"something" with those args:
https://github.com/jayv/spark/blob/mesos_cluster_params/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosClusterScheduler.scala#L375-L377
> spark-dispatcher doesn't pass along some spark properties
> ---------------------------------------------------------
>
> Key: SPARK-11327
> URL: https://issues.apache.org/jira/browse/SPARK-11327
> Project: Spark
> Issue Type: Bug
> Components: Mesos
> Reporter: Alan Braithwaite
>
> I haven't figured out exactly what's going on yet, but there's something in
> the spark-dispatcher which is failing to pass along properties to the
> spark-driver when using spark-submit in a clustered mesos docker environment.
> Most importantly, it's not passing along spark.mesos.executor.docker.image...
> cli:
> {code}
> docker run -t -i --rm --net=host
> --entrypoint=/usr/local/spark/bin/spark-submit
> docker.example.com/spark:2015.10.2 --conf spark.driver.memory=8G --conf
> spark.mesos.executor.docker.image=docker.example.com/spark:2015.10.2 --master
> mesos://spark-dispatcher.example.com:31262 --deploy-mode cluster
> --properties-file /usr/local/spark/conf/spark-defaults.conf --class
> com.example.spark.streaming.MyApp
> http://jarserver.example.com:8000/sparkapp.jar zk1.example.com:2181
> spark-testing my-stream 40
> {code}
> submit output:
> {code}
> 15/10/26 22:03:53 INFO RestSubmissionClient: Submitting a request to launch
> an application in mesos://compute1.example.com:31262.
> 15/10/26 22:03:53 DEBUG RestSubmissionClient: Sending POST request to server
> at http://compute1.example.com:31262/v1/submissions/create:
> {
> "action" : "CreateSubmissionRequest",
> "appArgs" : [ "zk1.example.com:2181", "spark-testing", "requests", "40" ],
> "appResource" : "http://jarserver.example.com:8000/sparkapp.jar";,
> "clientSparkVersion" : "1.5.0",
> "environmentVariables" : {
> "SPARK_SCALA_VERSION" : "2.10",
> "SPARK_CONF_DIR" : "/usr/local/spark/conf",
> "SPARK_HOME" : "/usr/local/spark",
> "SPARK_ENV_LOADED" : "1"
> },
> "mainClass" : "com.example.spark.streaming.MyApp",
> "sparkProperties" : {
> "spark.serializer" : "org.apache.spark.serializer.KryoSerializer",
> "spark.executorEnv.MESOS_NATIVE_JAVA_LIBRARY" :
> "/usr/local/lib/libmesos.so",
> "spark.history.fs.logDirectory" : "hdfs://hdfsha.example.com/spark/logs",
> "spark.eventLog.enabled" : "true",
> "spark.driver.maxResultSize" : "0",
> "spark.mesos.deploy.recoveryMode" : "ZOOKEEPER",
> "spark.mesos.deploy.zookeeper.url" :
> "zk1.example.com:2181,zk2.example.com:2181,zk3.example.com:2181,zk4.example.com:2181,zk5.example.com:2181",
> "spark.jars" : "http://jarserver.example.com:8000/sparkapp.jar";,
> "spark.driver.supervise" : "false",
> "spark.app.name" : "com.example.spark.streaming.MyApp",
> "spark.driver.memory" : "8G",
> "spark.logConf" : "true",
> "spark.deploy.zookeeper.dir" : "/spark_mesos_dispatcher",
> "spark.mesos.executor.docker.image" :
> "docker.example.com/spark-prod:2015.10.2",
> "spark.submit.deployMode" : "cluster",
> "spark.master" : "mesos://compute1.example.com:31262",
> "spark.executor.memory" : "8G",
> "spark.eventLog.dir" : "hdfs://hdfsha.example.com/spark/logs",
> "spark.mesos.docker.executor.network" : "HOST",
> "spark.mesos.executor.home" : "/usr/local/spark"
> }
> }
> 15/10/26 22:03:53 DEBUG RestSubmissionClient: Response from the server:
> {
> "action" : "CreateSubmissionResponse",
> "serverSparkVersion" : "1.5.0",
> "submissionId" : "driver-20151026220353-0011",
> "success" : true
> }
> 15/10/26 22:03:53 INFO RestSubmissionClient: Submission successfully created
> as driver-20151026220353-0011. Polling submission state...
> 15/10/26 22:03:53 INFO RestSubmissionClient: Submitting a request for the
> status of submission driver-20151026220353-0011 in
> mesos://compute1.example.com:31262.
> 15/10/26 22:03:53 DEBUG RestSubmissionClient: Sending GET request to server
> at
> http://compute1.example.com:31262/v1/submissions/status/driver-20151026220353-0011.
> 15/10/26 22:03:53 DEBUG RestSubmissionClient: Response from the server:
> {
> "action" : "SubmissionStatusResponse",
> "driverState" : "QUEUED",
> "serverSparkVersion" : "1.5.0",
> "submissionId" : "driver-20151026220353-0011",
> "success" : true
> }
> 15/10/26 22:03:53 INFO RestSubmissionClient: State of driver
> driver-20151026220353-0011 is now QUEUED.
> 15/10/26 22:03:53 INFO RestSubmissionClient: Server responded with
> CreateSubmissionResponse:
> {
> "action" : "CreateSubmissionResponse",
> "serverSparkVersion" : "1.5.0",
> "submissionId" : "driver-20151026220353-0011",
> "success" : true
> }
> {code}
> driver log:
> {code}
> 15/10/26 22:08:08 INFO SparkContext: Running Spark version 1.5.0
> 15/10/26 22:08:08 DEBUG MutableMetricsFactory: field
> org.apache.hadoop.metrics2.lib.MutableRate
> org.apache.hadoop.security.UserGroupInformation$UgiMetrics.loginSuccess with
> annotation @org.apache.hadoop.metrics2.annotation.Metric(about=,
> sampleName=Ops, always=false, type=DEFAULT, valueName=Time, value=[Rate of
> successful kerberos logins and latency (milliseconds)])
> 15/10/26 22:08:08 DEBUG MutableMetricsFactory: field
> org.apache.hadoop.metrics2.lib.MutableRate
> org.apache.hadoop.security.UserGroupInformation$UgiMetrics.loginFailure with
> annotation @org.apache.hadoop.metrics2.annotation.Metric(about=,
> sampleName=Ops, always=false, type=DEFAULT, valueName=Time, value=[Rate of
> failed kerberos logins and latency (milliseconds)])
> 15/10/26 22:08:08 DEBUG MutableMetricsFactory: field
> org.apache.hadoop.metrics2.lib.MutableRate
> org.apache.hadoop.security.UserGroupInformation$UgiMetrics.getGroups with
> annotation @org.apache.hadoop.metrics2.annotation.Metric(about=,
> sampleName=Ops, always=false, type=DEFAULT, valueName=Time, value=[GetGroups])
> 15/10/26 22:08:08 DEBUG MetricsSystemImpl: UgiMetrics, User and group related
> metrics
> 15/10/26 22:08:08 DEBUG KerberosName: Kerberos krb5 configuration not found,
> setting default realm to empty
> 15/10/26 22:08:08 DEBUG Groups: Creating new Groups object
> 15/10/26 22:08:08 DEBUG NativeCodeLoader: Trying to load the custom-built
> native-hadoop library...
> 15/10/26 22:08:08 DEBUG NativeCodeLoader: Failed to load native-hadoop with
> error: java.lang.UnsatisfiedLinkError: no hadoop in java.library.path
> 15/10/26 22:08:08 DEBUG NativeCodeLoader:
> java.library.path=/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib
> 15/10/26 22:08:08 WARN NativeCodeLoader: Unable to load native-hadoop library
> for your platform... using builtin-java classes where applicable
> 15/10/26 22:08:08 DEBUG PerformanceAdvisory: Falling back to shell based
> 15/10/26 22:08:08 DEBUG JniBasedUnixGroupsMappingWithFallback: Group mapping
> impl=org.apache.hadoop.security.ShellBasedUnixGroupsMapping
> 15/10/26 22:08:08 DEBUG Shell: Failed to detect a valid hadoop home directory
> java.io.IOException: HADOOP_HOME or hadoop.home.dir are not set.
> at org.apache.hadoop.util.Shell.checkHadoopHome(Shell.java:302)
> at org.apache.hadoop.util.Shell.<clinit>(Shell.java:327)
> at org.apache.hadoop.util.StringUtils.<clinit>(StringUtils.java:79)
> at org.apache.hadoop.security.Groups.parseStaticMapping(Groups.java:130)
> at org.apache.hadoop.security.Groups.<init>(Groups.java:94)
> at org.apache.hadoop.security.Groups.<init>(Groups.java:74)
> at
> org.apache.hadoop.security.Groups.getUserToGroupsMappingService(Groups.java:303)
> at
> org.apache.hadoop.security.UserGroupInformation.initialize(UserGroupInformation.java:283)
> at
> org.apache.hadoop.security.UserGroupInformation.ensureInitialized(UserGroupInformation.java:260)
> at
> org.apache.hadoop.security.UserGroupInformation.loginUserFromSubject(UserGroupInformation.java:804)
> at
> org.apache.hadoop.security.UserGroupInformation.getLoginUser(UserGroupInformation.java:774)
> at
> org.apache.hadoop.security.UserGroupInformation.getCurrentUser(UserGroupInformation.java:647)
> at
> org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2084)
> at
> org.apache.spark.util.Utils$$anonfun$getCurrentUserName$1.apply(Utils.scala:2084)
> at scala.Option.getOrElse(Option.scala:120)
> at org.apache.spark.util.Utils$.getCurrentUserName(Utils.scala:2084)
> at org.apache.spark.SparkContext.<init>(SparkContext.scala:310)
> at
> org.apache.spark.streaming.StreamingContext$.createNewSparkContext(StreamingContext.scala:847)
> at
> org.apache.spark.streaming.StreamingContext.<init>(StreamingContext.scala:81)
> at
> org.apache.spark.streaming.api.java.JavaStreamingContext.<init>(JavaStreamingContext.scala:134)
> at com.example.spark.streaming.MyApp.main(MyApp.java:63)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:497)
> at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
> at
> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
> at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
> at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
> at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> 15/10/26 22:08:08 DEBUG Shell: setsid exited with exit code 0
> 15/10/26 22:08:08 DEBUG Groups: Group mapping
> impl=org.apache.hadoop.security.JniBasedUnixGroupsMappingWithFallback;
> cacheTimeout=300000; warningDeltaMs=5000
> 15/10/26 22:08:08 DEBUG UserGroupInformation: hadoop login
> 15/10/26 22:08:08 DEBUG UserGroupInformation: hadoop login commit
> 15/10/26 22:08:08 DEBUG UserGroupInformation: using local user:UnixPrincipal:
> root
> 15/10/26 22:08:08 DEBUG UserGroupInformation: Using user: "UnixPrincipal:
> root" with name root
> 15/10/26 22:08:08 DEBUG UserGroupInformation: User entry: "root"
> 15/10/26 22:08:08 DEBUG UserGroupInformation: UGI loginUser:root (auth:SIMPLE)
> 15/10/26 22:08:08 INFO SparkContext: Spark configuration:
> spark.app.name=MyApp
> spark.deploy.zookeeper.dir=/spark_mesos_dispatcher
> spark.driver.maxResultSize=0
> spark.driver.memory=8192M
> spark.eventLog.dir=hdfs://hdfsha.example.com/spark/logs
> spark.eventLog.enabled=true
> spark.executor.memory=8G
> spark.executorEnv.MESOS_NATIVE_JAVA_LIBRARY=/usr/local/lib/libmesos.so
> spark.history.fs.logDirectory=hdfs://hdfsha.example.com/spark/logs
> spark.jars=file:/var/lib/mesos/sandbox/sparkapp.jar
> spark.logConf=true
> spark.master=mesos://zk://zk1.example.com:2181/mesos
> spark.mesos.deploy.recoveryMode=ZOOKEEPER
> spark.mesos.deploy.zookeeper.url=zk1.example.com:2181,zk2.example.com:2181,zk3.example.com:2181,zk4.example.com:2181,zk5.example.com:2181
> spark.mesos.docker.executor.network=HOST
> spark.mesos.executor.home=/usr/local/spark
> spark.serializer=org.apache.spark.serializer.KryoSerializer
> spark.submit.deployMode=client
> 15/10/26 22:08:08 INFO SecurityManager: Changing view acls to: root
> 15/10/26 22:08:08 INFO SecurityManager: Changing modify acls to: root
> 15/10/26 22:08:08 INFO SecurityManager: SecurityManager: authentication
> disabled; ui acls disabled; users with view permissions: Set(root); users
> with modify permissions: Set(root)
> 15/10/26 22:08:08 DEBUG SSLOptions: No SSL protocol specified
> 15/10/26 22:08:08 DEBUG SSLOptions: No SSL protocol specified
> 15/10/26 22:08:08 DEBUG SSLOptions: No SSL protocol specified
> {code}
> The timestamps are different because I don't know which machine the driver is
> going to be scheduled on, so after I know I did a docker start -ai <id> and
> got the logs that way.
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