You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Stavros Kontopoulos (JIRA)" <ji...@apache.org> on 2017/09/28 11:23:00 UTC
[jira] [Commented] (SPARK-18935) Use Mesos "Dynamic Reservation"
resource for Spark
[ https://issues.apache.org/jira/browse/SPARK-18935?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16184025#comment-16184025 ]
Stavros Kontopoulos commented on SPARK-18935:
---------------------------------------------
I tested this a while ago and stuck here:
I0829 14:05:56.342872 21756 master.cpp:6532] Sending status update TASK_ERROR for task 1 of framework f0a1a46a-e404-4faa-87f7-29479f30b57e-0009 'Total resources cpus(spark-prive)(allocated: spark-prive):1; cpus(*)(allocated: spark-prive):1; mem(spark-prive)(allocated: spark-prive):1024; mem(*)(allocated: spark-prive):384 required by task and its executor is more than available disk(spark-prive, )(allocated: spark-prive):1000; ports(spark-prive, )(allocated: spark-prive):[31000-32000]; cpus(spark-prive, )(allocated: spark-prive):1; mem(spark-prive, )(allocated: spark-prive):1024; cpus(*)(allocated: spark-prive):1; mem(*)(allocated: spark-prive):976; disk(*)(allocated: spark-prive):9000'
To reserve resources I used:
curl -i -d slaveId=cf885682-8a28-4e82-b5db-a01277edfafc-S0 -d resources='[{"name":"disk","type":"SCALAR","scalar": {"value":1000} ,"role":"spark-prive","reservation":{"principal":""}},{"name":"ports","type":"RANGES","ranges": { "range": [{"begin": 31000, "end": 32000}] },"role":"spark-prive","reservation":{"principal":""}}, {"name":"cpus","type":"SCALAR","scalar": {"value":1} ,"role":"spark-prive","reservation":{"principal":""}},{"name":"mem","type":"SCALAR","scalar": {"value":1024},"role":"spark-prive","reservation":{"principal":""}}]' -X POST http://172.17.0.1:5050/master/reserve
The error comes from here: https://github.com/apache/mesos/blob/11ee081ee578ea12e85799e00c5fe8b89eb6ea5f/src/master/validation.cpp#L1339.
I havent check with a principal but I suspect its optional anyway.
> 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 10000
> 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
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org