[jira] [Commented] (SPARK-18935) Use Mesos "Dynamic Reservation" resource for Spark

2017-09-28 Thread jackyoh (JIRA) 

[ 
https://issues.apache.org/jira/browse/SPARK-18935?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16185307#comment-16185307
 ] 

jackyoh commented on SPARK-18935:
-

It's clear to me now.

Thank you for your kind assistance.

> 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] [Updated] (SPARK-18935) Use Mesos "Dynamic Reservation" resource for Spark

2016-12-19 Thread jackyoh (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-18935?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

jackyoh updated SPARK-18935:

Affects Version/s: 2.0.1

> 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] [Created] (SPARK-18935) Use Mesos "Dynamic Reservation" resource for Spark

2016-12-19 Thread jackyoh (JIRA) 
jackyoh created SPARK-18935:
---

 Summary: 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: 2.0.2, 2.0.0
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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