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Possible issue with --packages argument for submit-args #90
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Using the --packages argument seems to actually populate the --jars argument with local paths to all .jar dependencies, and that won't work inside the cluster. What I ended up doing is a combination of the
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Hi, I had the same issue with packages. spark-submit \
--packages org.mongodb.spark:mongo-spark-connector_2.10:2.0.0 \
count_something.py But to be able run it with DC/OS Spark I have to do the follow: dcos spark run \
--submit-args=""`
`"--conf spark.mesos.uris=http://repo1.maven.org/maven2/org/mongodb/spark/mongo-spark-connector_2.10/2.0.0/mongo-spark-connector_2.10-2.0.0.jar,http://repo1.maven.org/maven2/
org/mongodb/mongo-java-driver/3.2.2/mongo-java-driver-3.2.2.jar "`
`"--conf spark.driver.extraClassPath=/mnt/mesos/sandbox/mongo-spark-connector_2.10-2.0.0.jar:/mnt/mesos/sandbox/mongo-java-driver-3.2.2.jar "`
`"--conf spark.executor.extraClassPath=/mnt/mesos/sandbox/mongo-spark-connector_2.10-2.0.0.jar:/mnt/mesos/sandbox/mongo-java-driver-3.2.2.jar "`
`"https://example.com/spark/do_something.py" \
--verbose As you can see it cannot resolve dependicies and this why I had to provide also jar for I think it is only because dcos spark bypasses |
@bogdangi |
@andreimarinescu there is a fix here for driver dependencies: apache/spark#18587. It will go in 2.3. Also planning to update the cli, --packages is currently unsupported along with some other flags. |
Hello everyone,
I'm trying to run a job using the following command:
The task fails immediately with the following output from dcos spark status <job_id>:
Looking at the mesos logs on that agent, I'm getting the following output. As far as I can see, all the jar dependencies are downloaded locally and they're only referenced from the mesos agent. Indeed, if I delete everything in /home/andrei/.ivy2, submitting the job takes substantially longer and the folder is then repopulated. Is this a bug, or am I doing anything wrong? I haven't found anything in the docs so far regarding the --packages parameter, running this on my local Spark cluster works.
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