PBSControllerLauncher: Unable to connect_client_sync()
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Descrição
I have been using ipyparallel 6 for a while and would like to migrate to ipyparallel 7 mainly due to fact that the new Cluster API enables you to manage the entire process through a Jupyter Notebook. Unfortunatelly, I am having difficulties to connect a client to my cluster.
I have created a new IPython profile adding a custom `ipcluster_config.py`, which is a modified version of my existing/working config for ipp 6 (see below).
I can successfully start a cluster spawning two PBS jobs (controller and engine).
```python
import ipyparallel as ipp
cluster=ipp.Cluster(
n=128,
controller_ip='*',
profile='pbs'
)
```
```
# Using existing profile dir: '/network/datamic/home/lukask/.aixvipmap/.ipython/profile_pbs'
```
```python
await cluster.start_cluster()
```
```
# Job submitted with job id: '23777'
# Starting 4 engines with
# Job submitted with job id: '23778'
# , engine_sets=['1635407070'])>
```
But if I run the following line, the notebook will only show that the kernel is busy and it will never actually finish.
```python
rc = cluster.connect_client_sync()
```
Am I using the API incorrectly? What might be the problem?
### ipcluster_config.py
```python
c.Cluster.engine_launcher_class = 'ipyparallel.cluster.launcher.PBSEngineSetLauncher'
c.Cluster.controller_launcher_class = 'ipyparallel.cluster.launcher.PBSControllerLauncher'
c.PBSControllerLauncher.batch_template = '''
#PBS -N ipcontroller
#PBS -j oe
#PBS -l walltime=01:00:00
#PBS -l nodes=1:ppn=1
cd $PBS_O_WORKDIR
conda activate ipp7
ipcontroller --profile-dir={profile_dir}
'''
c.PBSEngineSetLauncher.batch_template = '''
#PBS -N ipengine
#PBS -j oe
#PBS -l walltime=01:00:00
#PBS -l nodes={n//4}:ppn=4
cd $PBS_O_WORKDIR
conda activate ipp7
module load intel
mpiexec -n {n} ipengine --profile-dir={profile_dir}
'''
```
Guia de contribuição
Direção de pesquisa
Start with PBSControllerLauncher and the Cluster.connect_client_sync() path, using the ipcluster_config.py templates and the reported cluster-start sequence as the reproduction. Inspect the controller job output and connection wait behavior; done means the synchronous call returns a usable client for the started PBS cluster.
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Avaliação
- Stack de tecnologia
- jupyter, python
- Domínio
- devops, distributed-systems
- Tipo de issue
- Bug
- Dificuldade
- 4/5
- Tempo estimado
- 3-5 dias
- Status de atividade
- Estagnada
- Clareza
- Razoavelmente clara
- Facilidade para iniciantes
- 35/100