Janis Eccarius
710e2ec308
Scheduler uses requests (not limits) for placement. Previous 1Gi requests per pod caused Insufficient memory even with plenty of physical RAM. New requests: master 256Mi, workers 256Mi, history-server 128Mi. Limits unchanged. SPARK_WORKER_MEMORY reduced to 512m to match worker budget. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
63 lines
1.4 KiB
YAML
Executable File
63 lines
1.4 KiB
YAML
Executable File
apiVersion: apps/v1
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kind: Deployment
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metadata:
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name: spark-master
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labels:
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app.kubernetes.io/name: spark-master
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app.kubernetes.io/part-of: nowchess
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spec:
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replicas: 1
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selector:
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matchLabels:
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app.kubernetes.io/name: spark-master
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template:
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metadata:
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labels:
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app.kubernetes.io/name: spark-master
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app.kubernetes.io/part-of: nowchess
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spec:
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containers:
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- name: spark-master
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image: apache/spark:3.5.4-scala2.13-java17-ubuntu
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command:
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- /opt/spark/bin/spark-class
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- org.apache.spark.deploy.master.Master
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ports:
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- name: cluster
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containerPort: 7077
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- name: webui
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containerPort: 8080
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resources:
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requests:
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cpu: 200m
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memory: 256Mi
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limits:
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cpu: "1"
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memory: 2Gi
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volumeMounts:
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- name: spark-events
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mountPath: /spark-events
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volumes:
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- name: spark-events
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persistentVolumeClaim:
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claimName: spark-events
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---
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apiVersion: v1
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kind: Service
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metadata:
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name: spark-master
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labels:
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app.kubernetes.io/name: spark-master
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app.kubernetes.io/part-of: nowchess
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spec:
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selector:
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app.kubernetes.io/name: spark-master
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ports:
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- name: cluster
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port: 7077
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targetPort: cluster
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- name: webui
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port: 8080
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targetPort: webui
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type: ClusterIP
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