[jira] [Assigned] (SPARK-18935) Use Mesos "Dynamic Reservation" resource for Spark
[
https://issues.apache.org/jira/browse/SPARK-18935?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-18935:
Assignee: (was: Apache Spark)
> Use Mesos "Dynamic Reservation" resource for Spark
> --
>
> Key: SPARK-18935
> URL: https://issues.apache.org/jira/browse/SPARK-18935
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0, 2.0.1, 2.0.2
>Reporter: jackyoh
>
> I'm running spark on Apache Mesos
> Please follow these steps to reproduce the issue:
> 1. First, run Mesos resource reserve:
> curl -i -d slaveId=c24d1cfb-79f3-4b07-9f8b-c7b19543a333-S0 -d
> resources='[{"name":"cpus","type":"SCALAR","scalar":{"value":20},"role":"spark","reservation":{"principal":""}},{"name":"mem","type":"SCALAR","scalar":{"value":4096},"role":"spark","reservation":{"principal":""}}]'
> -X POST http://192.168.1.118:5050/master/reserve
> 2. Then run spark-submit command:
> ./spark-submit --class org.apache.spark.examples.SparkPi --master
> mesos://192.168.1.118:5050 --conf spark.mesos.role=spark
> ../examples/jars/spark-examples_2.11-2.0.2.jar 1
> And the console will keep loging same warning message as shown below:
> 16/12/19 22:33:28 WARN TaskSchedulerImpl: Initial job has not accepted any
> resources; check your cluster UI to ensure that workers are registered and
> have sufficient resources
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[jira] [Assigned] (SPARK-18935) Use Mesos "Dynamic Reservation" resource for Spark
[
https://issues.apache.org/jira/browse/SPARK-18935?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-18935:
Assignee: Apache Spark
> Use Mesos "Dynamic Reservation" resource for Spark
> --
>
> Key: SPARK-18935
> URL: https://issues.apache.org/jira/browse/SPARK-18935
> Project: Spark
> Issue Type: Bug
>Affects Versions: 2.0.0, 2.0.1, 2.0.2
>Reporter: jackyoh
>Assignee: Apache Spark
>
> I'm running spark on Apache Mesos
> Please follow these steps to reproduce the issue:
> 1. First, run Mesos resource reserve:
> curl -i -d slaveId=c24d1cfb-79f3-4b07-9f8b-c7b19543a333-S0 -d
> resources='[{"name":"cpus","type":"SCALAR","scalar":{"value":20},"role":"spark","reservation":{"principal":""}},{"name":"mem","type":"SCALAR","scalar":{"value":4096},"role":"spark","reservation":{"principal":""}}]'
> -X POST http://192.168.1.118:5050/master/reserve
> 2. Then run spark-submit command:
> ./spark-submit --class org.apache.spark.examples.SparkPi --master
> mesos://192.168.1.118:5050 --conf spark.mesos.role=spark
> ../examples/jars/spark-examples_2.11-2.0.2.jar 1
> And the console will keep loging same warning message as shown below:
> 16/12/19 22:33:28 WARN TaskSchedulerImpl: Initial job has not accepted any
> resources; check your cluster UI to ensure that workers are registered and
> have sufficient resources
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