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# Contains a basic spark-application to trigger a one-time execution of the referenced [py-]spark pipeline.
#
# GENERATED STUB CODE - PLEASE ***DO*** MODIFY
#
# Generated from: ${templateName}

# Default values for spark-operator.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.

# replicaCount -- Desired number of pods, leaderElection will be enabled
# if this is greater than 1
replicaCount: 1

image:
  # -- Image repository
  repository: "ghcr.io/boozallen/aissemble-spark-operator"
  # -- Image pull policy
  pullPolicy: IfNotPresent
  # -- if set, override the image tag whose default is the chart appVersion.
  tag: "${versionTag}"

# -- Image pull secrets
imagePullSecrets: []

# -- String to partially override `spark-operator.fullname` template (will maintain the release name)
nameOverride: ""

# -- String to override release name
fullnameOverride: "spark-operator"

rbac:
  # -- Create and use RBAC `Role` resources
  createRole: true
  # -- Create and use RBAC `ClusterRole` resources
  createClusterRole: true

serviceAccounts:
  spark:
    # -- Create a service account for spark apps
    create: true
    # -- Optional name for the spark service account
    name: "spark"
    # -- Optional annotations for the spark service account
    annotations: {}
  sparkoperator:
    # -- Create a service account for the operator
    create: true
    # -- Optional name for the operator service account
    name: "sparkoperator"
    # -- Optional annotations for the operator service account
    annotations: {}

# -- Set this if running spark jobs in a different namespace than the operator
sparkJobNamespace: ""

# -- Operator concurrency, higher values might increase memory usage
controllerThreads: 10

# -- Operator resync interval. Note that the operator will respond to events (e.g. create, update)
# unrelated to this setting
resyncInterval: 30

uiService:
  # -- Enable UI service creation for Spark application
  enable: true

# -- Ingress URL format.
# Requires the UI service to be enabled by setting `uiService.enable` to true.
ingressUrlFormat: ""

# -- Set higher levels for more verbose logging
logLevel: 2

# podSecurityContext -- Pod security context
podSecurityContext: {}

# securityContext -- Operator container security context
securityContext: {}

# volumes - Operator volumes
volumes:
  - name: spark-logging

# volumeMounts - Operator volumeMounts
volumeMounts:
  - name: spark-logging
    mountPath: "/tmp/spark-events"
webhook:
  # -- Enable webhook server
  enable: true
  # -- Webhook service port
  port: 8080
  # -- The webhook server will only operate on namespaces with this label, specified in the form key1=value1,key2=value2.
  # Empty string (default) will operate on all namespaces
  namespaceSelector: ""
  # -- The annotations applied to init job, required to restore certs deleted by the cleanup job during upgrade
  initAnnotations:
    "helm.sh/hook": pre-install, pre-upgrade
    "helm.sh/hook-weight": "50"
  # -- The annotations applied to the cleanup job, required for helm lifecycle hooks
  cleanupAnnotations:
    "helm.sh/hook": pre-delete, pre-upgrade
    "helm.sh/hook-delete-policy": hook-succeeded
    # -- Webhook Timeout in seconds
  timeout: 30

metrics:
  # -- Enable prometheus metric scraping
  enable: true
  # -- Metrics port
  port: 10254
  # -- Metrics port name
  portName: metrics
  # -- Metrics serving endpoint
  endpoint: /metrics
  # -- Metric prefix, will be added to all exported metrics
  prefix: ""

# -- Prometheus pod monitor for operator's pod.
podMonitor:
  # -- If enabled, a pod monitor for operator's pod will be submitted. Note that prometheus metrics should be enabled as well.
  enable: false
  # -- Pod monitor labels
  labels: {}
  # -- The label to use to retrieve the job name from
  jobLabel: spark-operator-podmonitor
  # -- Prometheus metrics endpoint properties. `metrics.portName` will be used as a port
  podMetricsEndpoint:
    scheme: http
    interval: 5s

# nodeSelector -- Node labels for pod assignment
nodeSelector: {}

# tolerations -- List of node taints to tolerate
tolerations: []

# affinity -- Affinity for pod assignment
affinity: {}

# podAnnotations -- Additional annotations to add to the pod
podAnnotations: {}

# podLabels -- Additional labels to add to the pod
podLabels: {}

# resources -- Pod resource requests and limits
# Note, that each job submission will spawn a JVM within the Spark Operator Pod using "/usr/local/openjdk-11/bin/java -Xmx128m".
# Kubernetes may kill these Java processes at will to enforce resource limits. When that happens, you will see the following error:
# 'failed to run spark-submit for SparkApplication [...]: signal: killed' - when this happens, you may want to increase memory limits.
resources: {}
  # limits:
  #   cpu: 100m
  #   memory: 300Mi
  # requests:
  #   cpu: 100m
  #   memory: 300Mi

batchScheduler:
  # -- Enable batch scheduler for spark jobs scheduling. If enabled, users can specify batch scheduler name in spark application
  enable: false

resourceQuotaEnforcement:
  # -- Whether to enable the ResourceQuota enforcement for SparkApplication resources.
  # Requires the webhook to be enabled by setting `webhook.enable` to true.
  # Ref: https://github.com/kubeflow/spark-operator/blob/master/docs/user-guide.md#enabling-resource-quota-enforcement.
  enable: false

leaderElection:
  # -- Leader election lock name.
  # Ref: https://github.com/kubeflow/spark-operator/blob/master/docs/user-guide.md#enabling-leader-election-for-high-availability.
  lockName: "spark-operator-lock"
  # -- Optionally store the lock in another namespace. Defaults to operator's namespace
  lockNamespace: ""

istio:
  # -- When using `istio`, spark jobs need to run without a sidecar to properly terminate
  enabled: false

# labelSelectorFilter -- A comma-separated list of key=value, or key labels to filter resources during watch and list based on the specified labels.
labelSelectorFilter: ""