spark-standalone-cluster-on-docker
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[BUG] Cannot submit tasks to master
Hi, I met an issue. Anyone can help? Thanks in advance.
After deploy spark-standalone-cluster-on-docker (images: andreper/spark-master:3.0.0) on a server (192.XX.X.X), I try to test by another PC (192.XX.X.Y). cmd steps: $ spark-shell --master spark://192.XX.X.X:7077
val count = sc.parallelize(1 to 1000).filter { _ =>
val x = math.random
val y = math.random
x*x + y*y < 1
}.count()
I got below error.(infinite loop messages)
WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
Build Env.
- Images: andreper/spark-master:3.0.0
- Docker Engine version: 20.10.14
- Docker Compose version: Docker Compose version v2.2.3
@rilakgg I am facing the same issue. Did you find a solution for that problem?
@Estreuselito @rilakgg
This is not a bug.
You have another Spark Application running on this cluster already (e.g. a Spark Session created in Jupyter Lab). Close this Session/Spark Application.
In a Standalone Cluster default behavior for a Spark Application is to "grav" all ressources. If this is a permanent Session, it will block any other application from correctly getting any ressource.
@ThomasMannKenbun is there a way around this?
@ThomasMannKenbun I think it would work if jupyter was run on the same container as spark master and starting pyspark with the --master local[*] option. Tested on Iceberg image. The app isn't listed on localhost:7077.