[jira] [Comment Edited] (SPARK-10643) Support HDFS application download in client mode spark submit
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https://issues.apache.org/jira/browse/SPARK-10643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15176150#comment-15176150
]
Enrique edited comment on SPARK-10643 at 3/2/16 6:22 PM:
-
[~abraithwaite] you are wrong, It's a bug, because on official docs was
references that you can use hdfs on spark-submit in client mode.
was (Author: kkcarb):
[~abraithwaite] you are wrong, this is a bug, because on official docs was
references that you can use hdfs on spark-submit in client mode.
> Support HDFS application download in client mode spark submit
> -
>
> Key: SPARK-10643
> URL: https://issues.apache.org/jira/browse/SPARK-10643
> Project: Spark
> Issue Type: New Feature
> Components: Spark Submit
>Reporter: Alan Braithwaite
>Priority: Minor
>
> When using mesos with docker and marathon, it would be nice to be able to
> make spark-submit deployable on marathon and have that download a jar from
> HDFS instead of having to package the jar with the docker.
> {code}
> $ docker run -it docker.example.com/spark:latest
> /usr/local/spark/bin/spark-submit --class
> com.example.spark.streaming.EventHandler hdfs://hdfs/tmp/application.jar
> Warning: Skip remote jar hdfs://hdfs/tmp/application.jar.
> java.lang.ClassNotFoundException: com.example.spark.streaming.EventHandler
> at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at org.apache.spark.util.Utils$.classForName(Utils.scala:173)
> at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:639)
> 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)
> {code}
> Although I'm aware that we can run in cluster mode with mesos, we've already
> built some nice tools surrounding marathon for logging and monitoring.
> Code in question:
> https://github.com/apache/spark/blob/132718ad7f387e1002b708b19e471d9cd907e105/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L723-L736
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[jira] [Comment Edited] (SPARK-10643) Support HDFS application download in client mode spark submit
[
https://issues.apache.org/jira/browse/SPARK-10643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15176150#comment-15176150
]
Enrique edited comment on SPARK-10643 at 3/2/16 6:22 PM:
-
[~abraithwaite] you are wrong, this is a bug, because on official docs was
references that you can use hdfs on spark-submit in client mode.
was (Author: kkcarb):
[~abraithwaite] you are wrong, this is a bug, because on official docs was
references that you can use hdfs on spark-submit con client mode.
> Support HDFS application download in client mode spark submit
> -
>
> Key: SPARK-10643
> URL: https://issues.apache.org/jira/browse/SPARK-10643
> Project: Spark
> Issue Type: New Feature
> Components: Spark Submit
>Reporter: Alan Braithwaite
>Priority: Minor
>
> When using mesos with docker and marathon, it would be nice to be able to
> make spark-submit deployable on marathon and have that download a jar from
> HDFS instead of having to package the jar with the docker.
> {code}
> $ docker run -it docker.example.com/spark:latest
> /usr/local/spark/bin/spark-submit --class
> com.example.spark.streaming.EventHandler hdfs://hdfs/tmp/application.jar
> Warning: Skip remote jar hdfs://hdfs/tmp/application.jar.
> java.lang.ClassNotFoundException: com.example.spark.streaming.EventHandler
> at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at org.apache.spark.util.Utils$.classForName(Utils.scala:173)
> at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:639)
> 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)
> {code}
> Although I'm aware that we can run in cluster mode with mesos, we've already
> built some nice tools surrounding marathon for logging and monitoring.
> Code in question:
> https://github.com/apache/spark/blob/132718ad7f387e1002b708b19e471d9cd907e105/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L723-L736
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[jira] [Commented] (SPARK-10643) Support HDFS application download in client mode spark submit
[
https://issues.apache.org/jira/browse/SPARK-10643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15176150#comment-15176150
]
Enrique commented on SPARK-10643:
-
[~abraithwaite] you are wrong, this is a bug, because on official docs was
references that you can use hdfs on spark-submit con client mode.
> Support HDFS application download in client mode spark submit
> -
>
> Key: SPARK-10643
> URL: https://issues.apache.org/jira/browse/SPARK-10643
> Project: Spark
> Issue Type: New Feature
> Components: Spark Submit
>Reporter: Alan Braithwaite
>Priority: Minor
>
> When using mesos with docker and marathon, it would be nice to be able to
> make spark-submit deployable on marathon and have that download a jar from
> HDFS instead of having to package the jar with the docker.
> {code}
> $ docker run -it docker.example.com/spark:latest
> /usr/local/spark/bin/spark-submit --class
> com.example.spark.streaming.EventHandler hdfs://hdfs/tmp/application.jar
> Warning: Skip remote jar hdfs://hdfs/tmp/application.jar.
> java.lang.ClassNotFoundException: com.example.spark.streaming.EventHandler
> at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
> at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
> at java.lang.Class.forName0(Native Method)
> at java.lang.Class.forName(Class.java:348)
> at org.apache.spark.util.Utils$.classForName(Utils.scala:173)
> at
> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:639)
> 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)
> {code}
> Although I'm aware that we can run in cluster mode with mesos, we've already
> built some nice tools surrounding marathon for logging and monitoring.
> Code in question:
> https://github.com/apache/spark/blob/132718ad7f387e1002b708b19e471d9cd907e105/core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala#L723-L736
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