DolphinScheduler/deploy/kubernetes/dolphinscheduler/values.yaml

504 lines
21 KiB
YAML

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# Default values for dolphinscheduler-chart.
# This is a YAML-formatted file.
# Declare variables to be passed into your templates.
timezone: "Asia/Shanghai"
image:
registry: "dolphinscheduler.docker.scarf.sh/apache"
tag: "dev-SNAPSHOT"
pullPolicy: "IfNotPresent"
pullSecret: ""
## If not exists external database, by default, Dolphinscheduler's database will use it.
postgresql:
enabled: true
postgresqlUsername: "root"
postgresqlPassword: "root"
postgresqlDatabase: "dolphinscheduler"
persistence:
enabled: false
size: "20Gi"
storageClass: "-"
## If exists external database, and set postgresql.enable value to false.
## external database will be used, otherwise Dolphinscheduler's database will be used.
externalDatabase:
type: "postgresql"
host: "localhost"
port: "5432"
username: "root"
password: "root"
database: "dolphinscheduler"
params: "characterEncoding=utf8"
## If not exists external registry, the zookeeper registry will be used by default.
zookeeper:
enabled: true
service:
port: 2181
fourlwCommandsWhitelist: "srvr,ruok,wchs,cons"
persistence:
enabled: false
size: "20Gi"
storageClass: "-"
## If exists external registry and set zookeeper.enable value to false, the external registry will be used.
externalRegistry:
registryPluginDir: "lib/plugin/registry"
registryPluginName: "zookeeper"
registryServers: "127.0.0.1:2181"
conf:
common:
# user data local directory path, please make sure the directory exists and have read write permissions
data.basedir.path: /tmp/dolphinscheduler
# resource storage type: HDFS, S3, NONE
resource.storage.type: HDFS
# resource store on HDFS/S3 path, resource file will store to this base path, self configuration, please make sure the directory exists on hdfs and have read write permissions. "/dolphinscheduler" is recommended
resource.storage.upload.base.path: /dolphinscheduler
# The AWS access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.access.key.id: minioadmin
# The AWS secret access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.secret.access.key: minioadmin
# The AWS Region to use. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.region: cn-north-1
# The name of the bucket. You need to create them by yourself. Otherwise, the system cannot start. All buckets in Amazon S3 share a single namespace; ensure the bucket is given a unique name.
resource.aws.s3.bucket.name: dolphinscheduler
# You need to set this parameter when private cloud s3. If S3 uses public cloud, you only need to set resource.aws.region or set to the endpoint of a public cloud such as S3.cn-north-1.amazonaws.com.cn
resource.aws.s3.endpoint: http://localhost:9000
# alibaba cloud access key id, required if you set resource.storage.type=OSS
resource.alibaba.cloud.access.key.id: <your-access-key-id>
# alibaba cloud access key secret, required if you set resource.storage.type=OSS
resource.alibaba.cloud.access.key.secret: <your-access-key-secret>
# alibaba cloud region, required if you set resource.storage.type=OSS
resource.alibaba.cloud.region: cn-hangzhou
# oss bucket name, required if you set resource.storage.type=OSS
resource.alibaba.cloud.oss.bucket.name: dolphinscheduler
# oss bucket endpoint, required if you set resource.storage.type=OSS
resource.alibaba.cloud.oss.endpoint: https://oss-cn-hangzhou.aliyuncs.com
# if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path
resource.hdfs.root.user: hdfs
# if resource.storage.type=S3, the value like: s3a://dolphinscheduler; if resource.storage.type=HDFS and namenode HA is enabled, you need to copy core-site.xml and hdfs-site.xml to conf dir
resource.hdfs.fs.defaultFS: hdfs://mycluster:8020
# whether to startup kerberos
hadoop.security.authentication.startup.state: false
# java.security.krb5.conf path
java.security.krb5.conf.path: /opt/krb5.conf
# login user from keytab username
login.user.keytab.username: hdfs-mycluster@ESZ.COM
# login user from keytab path
login.user.keytab.path: /opt/hdfs.headless.keytab
# kerberos expire time, the unit is hour
kerberos.expire.time: 2
# resourcemanager port, the default value is 8088 if not specified
resource.manager.httpaddress.port: 8088
# if resourcemanager HA is enabled, please set the HA IPs; if resourcemanager is single, keep this value empty
yarn.resourcemanager.ha.rm.ids: 192.168.xx.xx,192.168.xx.xx
# if resourcemanager HA is enabled or not use resourcemanager, please keep the default value; If resourcemanager is single, you only need to replace ds1 to actual resourcemanager hostname
yarn.application.status.address: http://ds1:%s/ws/v1/cluster/apps/%s
# job history status url when application number threshold is reached(default 10000, maybe it was set to 1000)
yarn.job.history.status.address: http://ds1:19888/ws/v1/history/mapreduce/jobs/%s
# datasource encryption enable
datasource.encryption.enable: false
# datasource encryption salt
datasource.encryption.salt: '!@#$%^&*'
# data quality option
data-quality.jar.name: dolphinscheduler-data-quality-dev-SNAPSHOT.jar
# Whether hive SQL is executed in the same session
support.hive.oneSession: false
# use sudo or not, if set true, executing user is tenant user and deploy user needs sudo permissions; if set false, executing user is the deploy user and doesn't need sudo permissions
sudo.enable: true
# development state
development.state: false
# rpc port
alert.rpc.port: 50052
# set path of conda.sh
conda.path: /opt/anaconda3/etc/profile.d/conda.sh
# Task resource limit state
task.resource.limit.state: false
# mlflow task plugin preset repository
ml.mlflow.preset_repository: https://github.com/apache/dolphinscheduler-mlflow
# mlflow task plugin preset repository version
ml.mlflow.preset_repository_version: "main"
common:
## Configmap
configmap:
DOLPHINSCHEDULER_OPTS: ""
DATA_BASEDIR_PATH: "/tmp/dolphinscheduler"
RESOURCE_UPLOAD_PATH: "/dolphinscheduler"
# dolphinscheduler env
HADOOP_HOME: "/opt/soft/hadoop"
HADOOP_CONF_DIR: "/opt/soft/hadoop/etc/hadoop"
SPARK_HOME: "/opt/soft/spark"
PYTHON_HOME: "/usr/bin/python"
JAVA_HOME: "/usr/local/openjdk-8"
HIVE_HOME: "/opt/soft/hive"
FLINK_HOME: "/opt/soft/flink"
DATAX_HOME: "/opt/soft/datax"
## Shared storage persistence mounted into api, master and worker, such as Hadoop, Spark, Flink and DataX binary package
sharedStoragePersistence:
enabled: false
mountPath: "/opt/soft"
accessModes:
- "ReadWriteMany"
## storageClassName must support the access mode: ReadWriteMany
storageClassName: "-"
storage: "20Gi"
## If RESOURCE_STORAGE_TYPE is HDFS and FS_DEFAULT_FS is file:///, fsFileResourcePersistence should be enabled for resource storage
fsFileResourcePersistence:
enabled: false
accessModes:
- "ReadWriteMany"
## storageClassName must support the access mode: ReadWriteMany
storageClassName: "-"
storage: "20Gi"
master:
## PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
podManagementPolicy: "Parallel"
## Replicas is the desired number of replicas of the given Template.
replicas: "3"
## You can use annotations to attach arbitrary non-identifying metadata to objects.
## Clients such as tools and libraries can retrieve this metadata.
annotations: {}
## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
affinity: {}
## NodeSelector is a selector which must be true for the pod to fit on a node.
## Selector which must match a node's labels for the pod to be scheduled on that node.
## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
nodeSelector: {}
## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
tolerations: []
## Compute Resources required by this container. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
resources: {}
# resources:
# limits:
# memory: "8Gi"
# cpu: "4"
# requests:
# memory: "2Gi"
# cpu: "500m"
## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
livenessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
readinessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
## The StatefulSet controller is responsible for mapping network identities to claims in a way that maintains the identity of a pod.
## Every claim in this list must have at least one matching (by name) volumeMount in one container in the template.
## A claim in this list takes precedence over any volumes in the template, with the same name.
persistentVolumeClaim:
enabled: false
accessModes:
- "ReadWriteOnce"
storageClassName: "-"
storage: "20Gi"
env:
JAVA_OPTS: "-Xms1g -Xmx1g -Xmn512m"
MASTER_EXEC_THREADS: "100"
MASTER_EXEC_TASK_NUM: "20"
MASTER_DISPATCH_TASK_NUM: "3"
MASTER_HOST_SELECTOR: "LowerWeight"
MASTER_HEARTBEAT_INTERVAL: "10s"
MASTER_HEARTBEAT_ERROR_THRESHOLD: "5"
MASTER_TASK_COMMIT_RETRYTIMES: "5"
MASTER_TASK_COMMIT_INTERVAL: "1s"
MASTER_STATE_WHEEL_INTERVAL: "5s"
MASTER_MAX_CPU_LOAD_AVG: "-1"
MASTER_RESERVED_MEMORY: "0.3"
MASTER_FAILOVER_INTERVAL: "10m"
MASTER_KILL_YARN_JOB_WHEN_HANDLE_FAILOVER: "true"
worker:
## PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
podManagementPolicy: "Parallel"
## Replicas is the desired number of replicas of the given Template.
replicas: "3"
## You can use annotations to attach arbitrary non-identifying metadata to objects.
## Clients such as tools and libraries can retrieve this metadata.
annotations: {}
## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
affinity: {}
## NodeSelector is a selector which must be true for the pod to fit on a node.
## Selector which must match a node's labels for the pod to be scheduled on that node.
## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
nodeSelector: {}
## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
tolerations: []
## Compute Resources required by this container. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
resources: {}
# resources:
# limits:
# memory: "8Gi"
# cpu: "4"
# requests:
# memory: "2Gi"
# cpu: "500m"
## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
livenessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
readinessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
## The StatefulSet controller is responsible for mapping network identities to claims in a way that maintains the identity of a pod.
## Every claim in this list must have at least one matching (by name) volumeMount in one container in the template.
## A claim in this list takes precedence over any volumes in the template, with the same name.
persistentVolumeClaim:
enabled: false
## dolphinscheduler data volume
dataPersistentVolume:
enabled: false
accessModes:
- "ReadWriteOnce"
storageClassName: "-"
storage: "20Gi"
## dolphinscheduler logs volume
logsPersistentVolume:
enabled: false
accessModes:
- "ReadWriteOnce"
storageClassName: "-"
storage: "20Gi"
env:
WORKER_GROUPS_0: default
WORKER_MAX_CPU_LOAD_AVG: "-1"
WORKER_RESERVED_MEMORY: "0.3"
WORKER_EXEC_THREADS: "100"
WORKER_HEARTBEAT_INTERVAL: "10s"
WORKER_HEART_ERROR_THRESHOLD: "5"
WORKER_HOST_WEIGHT: "100"
WORKER_GROUPS: "default"
alert:
## Number of desired pods. This is a pointer to distinguish between explicit zero and not specified. Defaults to 1.
replicas: 1
## The deployment strategy to use to replace existing pods with new ones.
strategy:
type: "RollingUpdate"
rollingUpdate:
maxSurge: "25%"
maxUnavailable: "25%"
## You can use annotations to attach arbitrary non-identifying metadata to objects.
## Clients such as tools and libraries can retrieve this metadata.
annotations: {}
## NodeSelector is a selector which must be true for the pod to fit on a node.
## Selector which must match a node's labels for the pod to be scheduled on that node.
## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
affinity: {}
## Compute Resources required by this container. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
nodeSelector: {}
## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
tolerations: []
## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
resources: {}
# resources:
# limits:
# memory: "2Gi"
# cpu: "1"
# requests:
# memory: "1Gi"
# cpu: "500m"
## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
livenessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
readinessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
## More info: https://kubernetes.io/docs/concepts/storage/persistent-volumes#persistentvolumeclaims
persistentVolumeClaim:
enabled: false
accessModes:
- "ReadWriteOnce"
storageClassName: "-"
storage: "20Gi"
env:
JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
api:
## Number of desired pods. This is a pointer to distinguish between explicit zero and not specified. Defaults to 1.
replicas: "1"
## The deployment strategy to use to replace existing pods with new ones.
strategy:
type: "RollingUpdate"
rollingUpdate:
maxSurge: "25%"
maxUnavailable: "25%"
## You can use annotations to attach arbitrary non-identifying metadata to objects.
## Clients such as tools and libraries can retrieve this metadata.
annotations: {}
## NodeSelector is a selector which must be true for the pod to fit on a node.
## Selector which must match a node's labels for the pod to be scheduled on that node.
## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
affinity: {}
## Compute Resources required by this container. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
nodeSelector: {}
## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
tolerations: []
## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
resources: {}
# resources:
# limits:
# memory: "2Gi"
# cpu: "1"
# requests:
# memory: "1Gi"
# cpu: "500m"
## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
livenessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
readinessProbe:
enabled: true
initialDelaySeconds: "30"
periodSeconds: "30"
timeoutSeconds: "5"
failureThreshold: "3"
successThreshold: "1"
## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
## More info: https://kubernetes.io/docs/concepts/storage/persistent-volumes#persistentvolumeclaims
persistentVolumeClaim:
enabled: false
accessModes:
- "ReadWriteOnce"
storageClassName: "-"
storage: "20Gi"
service:
## type determines how the Service is exposed. Defaults to ClusterIP. Valid options are ExternalName, ClusterIP, NodePort, and LoadBalancer
type: "ClusterIP"
## clusterIP is the IP address of the service and is usually assigned randomly by the master
clusterIP: ""
## nodePort is the port on each node on which this service is exposed when type=NodePort
nodePort: ""
## externalIPs is a list of IP addresses for which nodes in the cluster will also accept traffic for this service
externalIPs: []
## externalName is the external reference that kubedns or equivalent will return as a CNAME record for this service, requires Type to be ExternalName
externalName: ""
## loadBalancerIP when service.type is LoadBalancer. LoadBalancer will get created with the IP specified in this field
loadBalancerIP: ""
## annotations may need to be set when service.type is LoadBalancer
## service.beta.kubernetes.io/aws-load-balancer-ssl-cert: arn:aws:acm:us-east-1:EXAMPLE_CERT
annotations: {}
env:
JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
ingress:
enabled: false
host: "dolphinscheduler.org"
path: "/dolphinscheduler"
annotations: {}
tls:
enabled: false
secretName: "dolphinscheduler-tls"