image:
  registry: docker.io
  repository: kubeflow/spark-operator
  # version 목록
  ## spark : 3.5.2
  ## java : 11
  ## python : 3.8.10
  tag: "2.0.2"
  

controller:
  # spark contoller의 thread 설정
  # SparkApplication 객체를 동시에 처리할 수 있는 수
  workers: 10
  
  # controller log level 설정
  logLevel: info
  
  # spark application 실행 시 접근 가능한 UI Ingress 활성화
  ## spark 동작 중에만 접근 가능한 UI
  uiService:
    enable: true
  uiIngress:
    enable: true
    urlFormat: "spark.example.org/{{$appNamespace}}/{{$appName}}"

  # controller resource 설정
  resources:
    limits:
      cpu: 100m
      memory: 300Mi
    requests:
      cpu: 100m
      memory: 300Mi


  # Workqueue rate limiter configuration forwarded to the controller-runtime Reconciler.
  workqueueRateLimiter:
    # -- Specifies the average rate of items process by the workqueue rate limiter.
    bucketQPS: 50
    # -- Specifies the maximum number of items that can be in the workqueue at any given time.
    bucketSize: 500
    maxDelay:
      # -- Specifies whether to enable max delay for the workqueue rate limiter.
      # This is useful to avoid losing events when the workqueue is full.
      enable: true
      # -- Specifies the maximum delay duration for the workqueue rate limiter.
      duration: 6h

webhook:
  resources:
    limits:
      cpu: 100m
      memory: 300Mi
    requests:
      cpu: 100m
      memory: 300Mi

spark:
  jobNamespaces: []

# prometheus:
#   metrics:
#     enable: false
#   podMonitor:
#     create: false
#     labels: {}