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69 lines
1.6 KiB
69 lines
1.6 KiB
image:
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registry: docker.io
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repository: kubeflow/spark-operator
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# version 목록
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## spark : 3.5.2
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## java : 11
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## python : 3.8.10
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tag: "2.0.2"
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controller:
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# spark contoller의 thread 설정
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# SparkApplication 객체를 동시에 처리할 수 있는 수
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workers: 10
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# controller log level 설정
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logLevel: info
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# spark application 실행 시 접근 가능한 UI Ingress 활성화
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## spark 동작 중에만 접근 가능한 UI
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uiService:
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enable: true
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uiIngress:
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enable: true
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urlFormat: "spark.example.org/{{$appNamespace}}/{{$appName}}"
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# controller resource 설정
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resources:
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limits:
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cpu: 100m
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memory: 300Mi
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requests:
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cpu: 100m
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memory: 300Mi
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# Workqueue rate limiter configuration forwarded to the controller-runtime Reconciler.
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workqueueRateLimiter:
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# -- Specifies the average rate of items process by the workqueue rate limiter.
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bucketQPS: 50
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# -- Specifies the maximum number of items that can be in the workqueue at any given time.
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bucketSize: 500
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maxDelay:
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# -- Specifies whether to enable max delay for the workqueue rate limiter.
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# This is useful to avoid losing events when the workqueue is full.
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enable: true
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# -- Specifies the maximum delay duration for the workqueue rate limiter.
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duration: 6h
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webhook:
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resources:
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limits:
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cpu: 100m
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memory: 300Mi
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requests:
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cpu: 100m
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memory: 300Mi
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spark:
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jobNamespaces: []
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# prometheus:
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# metrics:
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# enable: false
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# podMonitor:
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# create: false
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# labels: {}
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