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 >>>> >>>> >>>
