andygrove opened a new issue, #44:
URL: https://github.com/apache/datafusion-ray/issues/44

   I cannot get benchmarks running in k8s. I suspect that too many tasks are 
being scheduled in parallel.
   
   I added resource constraints in the code:
   
   ```python
   @ray.remote(num_cpus=1)
   def execute_query_stage(
   
   ...
   
   @ray.remote(num_cpus=1)
   def execute_query_partition(
   ```
   
   I am running the benchmark with
   
   ```shell
   RAY_ADDRESS='http://localhost:8265' ray job submit --working-dir `pwd` -- 
python3 tpcbench.py --benchmark tpch --queries 
/home/ray/datafusion-benchmarks/tpch/queries/ --data /mnt/bigdata/tpch/sf100  
--concurrency 4
   ```
   
   My cluster definition is:
   
   ```yaml
   apiVersion: ray.io/v1alpha1
   kind: RayCluster
   metadata:
     name: datafusion-ray-cluster
   spec:
     headGroupSpec:
       rayStartParams:
         num-cpus: "0"
       template:
         spec:
           containers:
             - name: ray-head
               image: andygrove/datafusion-ray-tpch:latest
               imagePullPolicy: Always
               resources:
                 limits:
                   cpu: 2
                   memory: 8Gi
                 requests:
                   cpu: 2
                   memory: 8Gi
               volumeMounts:
                 - mountPath: /mnt/bigdata  # Mount path inside the container
                   name: ray-storage
           volumes:
             - name: ray-storage
               persistentVolumeClaim:
                 claimName: ray-pvc  # Reference the PVC name here
     workerGroupSpecs:
       - replicas: 2
         groupName: "datafusion-ray"
         rayStartParams:
           num-cpus: "4"
         template:
           spec:
             containers:
               - name: ray-worker
                 image: andygrove/datafusion-ray-tpch:latest
                 imagePullPolicy: Always
                 resources:
                   limits:
                     cpu: 5
                     memory: 64Gi
                   requests:
                     cpu: 5
                     memory: 64Gi
                 volumeMounts:
                   - mountPath: /mnt/bigdata
                     name: ray-storage
             volumes:
               - name: ray-storage
                 persistentVolumeClaim:
                   claimName: ray-pvc
   ```


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