Hi Quick question. How to pass constraint [["hostname", "CLUSTER", " specific.node.com"]] to mesos?
I was trying --conf spark.mesos.constraints=hostname:specific.node.com. But it didn't seems working Please help Thanks Sathish On Thu, Jan 28, 2016 at 6:52 PM Mao Geng <m...@sumologic.com> wrote: > From my limited knowledge, only limited options such as network mode, > volumes, portmaps can be passed through. See > https://github.com/apache/spark/pull/3074/files. > > https://issues.apache.org/jira/browse/SPARK-8734 is open for exposing all > docker options to spark. > > -Mao > > On Thu, Jan 28, 2016 at 1:55 PM, Sathish Kumaran Vairavelu < > vsathishkuma...@gmail.com> wrote: > >> Thank you., I figured it out. I have set executor memory to minimal and >> it works., >> >> Another issue has come.. I have to pass --add-host option while running >> containers in slave nodes.. Is there any option to pass docker run >> parameters from spark? >> On Thu, Jan 28, 2016 at 12:26 PM Mao Geng <m...@sumologic.com> wrote: >> >>> Sathish, >>> >>> I guess the mesos resources are not enough to run your job. You might >>> want to check the mesos log to figure out why. >>> >>> I tried to run the docker image with "--conf spark.mesos.coarse=false" >>> and "true". Both are fine. >>> >>> Best, >>> Mao >>> >>> On Wed, Jan 27, 2016 at 5:00 PM, Sathish Kumaran Vairavelu < >>> vsathishkuma...@gmail.com> wrote: >>> >>>> Hi, >>>> >>>> On the same Spark/Mesos/Docker setup, I am getting warning "Initial Job >>>> has not accepted any resources; check your cluster UI to ensure that >>>> workers are registered and have sufficient resources". I am running in >>>> coarse grained mode. Any pointers on how to fix this issue? Please help. I >>>> have updated both docker.properties and spark-default.conf with >>>> spark.mesos.executor.docker.image >>>> and other properties. >>>> >>>> >>>> Thanks >>>> >>>> Sathish >>>> >>>> On Wed, Jan 27, 2016 at 9:58 AM Sathish Kumaran Vairavelu < >>>> vsathishkuma...@gmail.com> wrote: >>>> >>>>> Thanks a lot for your info! I will try this today. >>>>> On Wed, Jan 27, 2016 at 9:29 AM Mao Geng <m...@sumologic.com> wrote: >>>>> >>>>>> Hi Sathish, >>>>>> >>>>>> The docker image is normal, no AWS profile included. >>>>>> >>>>>> When the driver container runs with --net=host, the driver host's AWS >>>>>> profile will take effect so that the driver can access the protected s3 >>>>>> files. >>>>>> >>>>>> Similarly, Mesos slaves also run Spark executor docker container in >>>>>> --net=host mode, so that the AWS profile of Mesos slaves will take >>>>>> effect. >>>>>> >>>>>> Hope it helps, >>>>>> Mao >>>>>> >>>>>> On Jan 26, 2016, at 9:15 PM, Sathish Kumaran Vairavelu < >>>>>> vsathishkuma...@gmail.com> wrote: >>>>>> >>>>>> Hi Mao, >>>>>> >>>>>> I want to check on accessing the S3 from Spark docker in Mesos. The >>>>>> EC2 instance that I am using has the AWS profile/IAM included. Should we >>>>>> build the docker image with any AWS profile settings or --net=host docker >>>>>> option takes care of it? >>>>>> >>>>>> Please help >>>>>> >>>>>> >>>>>> Thanks >>>>>> >>>>>> Sathish >>>>>> >>>>>> On Tue, Jan 26, 2016 at 9:04 PM Mao Geng <m...@sumologic.com> wrote: >>>>>> >>>>>>> Thank you very much, Jerry! >>>>>>> >>>>>>> I changed to "--jars >>>>>>> /opt/spark/lib/hadoop-aws-2.7.1.jar,/opt/spark/lib/aws-java-sdk-1.7.4.jar" >>>>>>> then it worked like a charm! >>>>>>> >>>>>>> From Mesos task logs below, I saw Mesos executor downloaded the jars >>>>>>> from the driver, which is a bit unnecessary (as the docker image already >>>>>>> has them), but that's ok - I am happy seeing Spark + Mesos + Docker + S3 >>>>>>> worked together! >>>>>>> >>>>>>> Thanks, >>>>>>> Mao >>>>>>> >>>>>>> 16/01/27 02:54:45 INFO Executor: Using REPL class URI: >>>>>>> http://172.16.3.98:33771 >>>>>>> 16/01/27 02:55:12 INFO CoarseGrainedExecutorBackend: Got assigned task 0 >>>>>>> 16/01/27 02:55:12 INFO Executor: Running task 0.0 in stage 0.0 (TID 0) >>>>>>> 16/01/27 02:55:12 INFO Executor: Fetching >>>>>>> http://172.16.3.98:3850/jars/hadoop-aws-2.7.1.jar with timestamp >>>>>>> 1453863280432 >>>>>>> 16/01/27 02:55:12 INFO Utils: Fetching >>>>>>> http://172.16.3.98:3850/jars/hadoop-aws-2.7.1.jar to >>>>>>> /tmp/spark-7b8e1681-8a62-4f1d-9e11-fdf8062b1b08/fetchFileTemp1518118694295619525.tmp >>>>>>> 16/01/27 02:55:12 INFO Utils: Copying >>>>>>> /tmp/spark-7b8e1681-8a62-4f1d-9e11-fdf8062b1b08/-19880839621453863280432_cache >>>>>>> to /./hadoop-aws-2.7.1.jar >>>>>>> 16/01/27 02:55:12 INFO Executor: Adding file:/./hadoop-aws-2.7.1.jar to >>>>>>> class loader >>>>>>> 16/01/27 02:55:12 INFO Executor: Fetching >>>>>>> http://172.16.3.98:3850/jars/aws-java-sdk-1.7.4.jar with timestamp >>>>>>> 1453863280472 >>>>>>> 16/01/27 02:55:12 INFO Utils: Fetching >>>>>>> http://172.16.3.98:3850/jars/aws-java-sdk-1.7.4.jar to >>>>>>> /tmp/spark-7b8e1681-8a62-4f1d-9e11-fdf8062b1b08/fetchFileTemp8868621397726761921.tmp >>>>>>> 16/01/27 02:55:12 INFO Utils: Copying >>>>>>> /tmp/spark-7b8e1681-8a62-4f1d-9e11-fdf8062b1b08/8167072821453863280472_cache >>>>>>> to /./aws-java-sdk-1.7.4.jar >>>>>>> 16/01/27 02:55:12 INFO Executor: Adding file:/./aws-java-sdk-1.7.4.jar >>>>>>> to class loader >>>>>>> >>>>>>> On Tue, Jan 26, 2016 at 5:40 PM, Jerry Lam <chiling...@gmail.com> >>>>>>> wrote: >>>>>>> >>>>>>>> Hi Mao, >>>>>>>> >>>>>>>> Can you try --jars to include those jars? >>>>>>>> >>>>>>>> Best Regards, >>>>>>>> >>>>>>>> Jerry >>>>>>>> >>>>>>>> Sent from my iPhone >>>>>>>> >>>>>>>> On 26 Jan, 2016, at 7:02 pm, Mao Geng <m...@sumologic.com> wrote: >>>>>>>> >>>>>>>> Hi there, >>>>>>>> >>>>>>>> I am trying to run Spark on Mesos using a Docker image as executor, >>>>>>>> as mentioned >>>>>>>> http://spark.apache.org/docs/latest/running-on-mesos.html#mesos-docker-support >>>>>>>> . >>>>>>>> >>>>>>>> I built a docker image using the following Dockerfile (which is >>>>>>>> based on >>>>>>>> https://github.com/apache/spark/blob/master/docker/spark-mesos/Dockerfile >>>>>>>> ): >>>>>>>> >>>>>>>> FROM mesosphere/mesos:0.25.0-0.2.70.ubuntu1404 >>>>>>>> >>>>>>>> # Update the base ubuntu image with dependencies needed for Spark >>>>>>>> RUN apt-get update && \ >>>>>>>> apt-get install -y python libnss3 openjdk-7-jre-headless curl >>>>>>>> >>>>>>>> RUN curl >>>>>>>> http://www.carfab.com/apachesoftware/spark/spark-1.6.0/spark-1.6.0-bin-hadoop2.6.tgz >>>>>>>> | tar -xzC /opt && \ >>>>>>>> ln -s /opt/spark-1.6.0-bin-hadoop2.6 /opt/spark >>>>>>>> ENV SPARK_HOME /opt/spark >>>>>>>> ENV MESOS_NATIVE_JAVA_LIBRARY /usr/local/lib/libmesos.so >>>>>>>> >>>>>>>> Then I successfully ran spark-shell via this docker command: >>>>>>>> docker run --rm -it --net=host <registry>/<image>:<tag> >>>>>>>> /opt/spark/bin/spark-shell --master mesos://<master_host>:5050 --conf >>>>>>>> <registry>/<image>:<tag> >>>>>>>> >>>>>>>> So far so good. Then I wanted to call sc.textFile to load a file >>>>>>>> from S3, but I was blocked by some issues which I couldn't figure out. >>>>>>>> I've >>>>>>>> read >>>>>>>> https://dzone.com/articles/uniting-spark-parquet-and-s3-as-an-alternative-to >>>>>>>> and >>>>>>>> http://blog.encomiabile.it/2015/10/29/apache-spark-amazon-s3-and-apache-mesos, >>>>>>>> learned that I need to add hadood-aws-2.7.1 and aws-java-sdk-2.7.4 >>>>>>>> into the >>>>>>>> executor and driver's classpaths, in order to access s3 files. >>>>>>>> >>>>>>>> So, I added following lines into Dockerfile and build a new image. >>>>>>>> RUN curl >>>>>>>> https://repo1.maven.org/maven2/com/amazonaws/aws-java-sdk/1.7.4/aws-java-sdk-1.7.4.jar >>>>>>>> -o /opt/spark/lib/aws-java-sdk-1.7.4.jar >>>>>>>> RUN curl >>>>>>>> http://central.maven.org/maven2/org/apache/hadoop/hadoop-aws/2.7.1/hadoop-aws-2.7.1.jar >>>>>>>> -o /opt/spark/lib/hadoop-aws-2.7.1.jar >>>>>>>> >>>>>>>> Then I started spark-shell again with below command: >>>>>>>> docker run --rm -it --net=host <registry>/<image>:<tag> >>>>>>>> /opt/spark/bin/spark-shell --master mesos://<master_host>:5050 --conf >>>>>>>> <registry>/<image>:<tag> --conf >>>>>>>> spark.executor.extraClassPath=/opt/spark/lib/hadoop-aws-2.7.1.jar:/opt/spark/lib/aws-java-sdk-1.7.4.jar >>>>>>>> --conf >>>>>>>> spark.driver.extraClassPath=/opt/spark/lib/hadoop-aws-2.7.1.jar:/opt/spark/lib/aws-java-sdk-1.7.4.jar >>>>>>>> >>>>>>>> But below command failed when I ran it in spark-shell: >>>>>>>> scala> sc.textFile("s3a://<bucket_name>/<file_name>").count() >>>>>>>> [Stage 0:> >>>>>>>> (0 + 2) / 2]16/01/26 23:05:23 WARN TaskSetManager: Lost task 0.0 in >>>>>>>> stage >>>>>>>> 0.0 (TID 0, ip-172-16-14-203.us-west-2.compute.internal): >>>>>>>> java.lang.RuntimeException: java.lang.ClassNotFoundException: Class >>>>>>>> org.apache.hadoop.fs.s3a.S3AFileSystem not found >>>>>>>> at >>>>>>>> org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2074) >>>>>>>> at >>>>>>>> org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2578) >>>>>>>> at >>>>>>>> org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2591) >>>>>>>> at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91) >>>>>>>> at >>>>>>>> org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630) >>>>>>>> at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612) >>>>>>>> at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370) >>>>>>>> at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296) >>>>>>>> at >>>>>>>> org.apache.hadoop.mapred.LineRecordReader.<init>(LineRecordReader.java:107) >>>>>>>> at >>>>>>>> org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67) >>>>>>>> at >>>>>>>> org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:237) >>>>>>>> at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:208) >>>>>>>> at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:101) >>>>>>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) >>>>>>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) >>>>>>>> at >>>>>>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >>>>>>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306) >>>>>>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:270) >>>>>>>> at >>>>>>>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66) >>>>>>>> at org.apache.spark.scheduler.Task.run(Task.scala:89) >>>>>>>> at >>>>>>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) >>>>>>>> at >>>>>>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) >>>>>>>> at >>>>>>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) >>>>>>>> at java.lang.Thread.run(Thread.java:745) >>>>>>>> Caused by: java.lang.ClassNotFoundException: Class >>>>>>>> org.apache.hadoop.fs.s3a.S3AFileSystem not found >>>>>>>> at >>>>>>>> org.apache.hadoop.conf.Configuration.getClassByName(Configuration.java:1980) >>>>>>>> at >>>>>>>> org.apache.hadoop.conf.Configuration.getClass(Configuration.java:2072) >>>>>>>> ... 23 more >>>>>>>> >>>>>>>> I checked hadoop-aws-2.7.1.jar, >>>>>>>> the org.apache.hadoop.fs.s3a.S3AFileSystem class file is in it. I also >>>>>>>> checked the Environment page of driver's Web UI at 4040 port, both >>>>>>>> hadoop-aws-2.7.1.jar and aws-java-sdk-1.7.4.jar are in the >>>>>>>> Classpath Entries (system path). And following code ran fine in >>>>>>>> spark-shell: >>>>>>>> scala> val clazz = >>>>>>>> Class.forName("org.apache.hadoop.fs.s3a.S3AFileSystem") >>>>>>>> clazz: Class[_] = class org.apache.hadoop.fs.s3a.S3AFileSystem >>>>>>>> >>>>>>>> scala> clazz.getClassLoader() >>>>>>>> res2: ClassLoader = sun.misc.Launcher$AppClassLoader@770848b9 >>>>>>>> >>>>>>>> So, I am confused why the task failed with >>>>>>>> "java.lang.ClassNotFoundException" >>>>>>>> Exception? Is there something wrong in the command line options I >>>>>>>> used to start spark-shell, or in the docker image, or in the "s3a://" >>>>>>>> url? >>>>>>>> Or is something related to the Docker executor of Mesos? I studied a >>>>>>>> bit >>>>>>>> https://github.com/apache/spark/blob/branch-1.6/core/src/main/scala/org/apache/spark/scheduler/cluster/mesos/MesosSchedulerBackend.scala >>>>>>>> but didn't understand it well... >>>>>>>> >>>>>>>> Appreciate if anyone will shed some lights on me. >>>>>>>> >>>>>>>> Thanks, >>>>>>>> Mao Geng >>>>>>>> >>>>>>>> >>>>>>> >>> >
