分布式调度框架。
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
 
 
 
 
 
 

1004 lines
45 KiB

#
# 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.
# -- World time and date for cities in all time zones
timezone: "Asia/Shanghai"
# -- Used to detect whether dolphinscheduler dependent services such as database are ready
initImage:
# -- Image pull policy. Options: Always, Never, IfNotPresent
pullPolicy: "IfNotPresent"
# -- Specify initImage repository
busybox: "busybox:1.30.1"
image:
# -- Docker image repository for the DolphinScheduler
registry: apache
# -- Docker image version for the DolphinScheduler
tag: latest
# -- Image pull policy. Options: Always, Never, IfNotPresent
pullPolicy: "IfNotPresent"
# -- Specify a imagePullSecrets
pullSecret: ""
# -- master image
master: dolphinscheduler-master
# -- worker image
worker: dolphinscheduler-worker
# -- api-server image
api: dolphinscheduler-api
# -- alert-server image
alert: dolphinscheduler-alert-server
# -- tools image
tools: dolphinscheduler-tools
datasource:
# -- The profile of datasource
profile: postgresql
postgresql:
# -- If not exists external PostgreSQL, by default, the DolphinScheduler will use a internal PostgreSQL
enabled: true
# -- The username for internal PostgreSQL
postgresqlUsername: "root"
# -- The password for internal PostgreSQL
postgresqlPassword: "root"
# -- The database for internal PostgreSQL
postgresqlDatabase: "dolphinscheduler"
# -- The driverClassName for internal PostgreSQL
driverClassName: "org.postgresql.Driver"
# -- The params for internal PostgreSQL
params: "characterEncoding=utf8"
persistence:
# -- Set postgresql.persistence.enabled to true to mount a new volume for internal PostgreSQL
enabled: false
# -- `PersistentVolumeClaim` size
size: "20Gi"
# -- PostgreSQL data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClass: "-"
mysql:
# -- If not exists external MySQL, by default, the DolphinScheduler will use a internal MySQL
enabled: false
# -- mysql driverClassName
driverClassName: "com.mysql.cj.jdbc.Driver"
auth:
# -- mysql username
username: "ds"
# -- mysql password
password: "ds"
# -- mysql database
database: "dolphinscheduler"
# -- mysql params
params: "characterEncoding=utf8"
primary:
persistence:
# -- Set mysql.primary.persistence.enabled to true to mount a new volume for internal MySQL
enabled: false
# -- `PersistentVolumeClaim` size
size: "20Gi"
# -- MySQL data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClass: "-"
minio:
# -- Deploy minio and configure it as the default storage for DolphinScheduler, note this is for demo only, not for production.
enabled: true
auth:
# -- minio username
rootUser: minioadmin
# -- minio password
rootPassword: minioadmin
persistence:
# -- Set minio.persistence.enabled to true to mount a new volume for internal minio
enabled: false
# -- minio default buckets
defaultBuckets: "dolphinscheduler"
externalDatabase:
# -- If exists external database, and set postgresql.enable value to false.
# external database will be used, otherwise Dolphinscheduler's internal database will be used.
enabled: false
# -- The type of external database, supported types: postgresql, mysql
type: "postgresql"
# -- The host of external database
host: "localhost"
# -- The port of external database
port: "5432"
# -- The username of external database
username: "root"
# -- The password of external database
password: "root"
# -- The database of external database
database: "dolphinscheduler"
# -- The params of external database
params: "characterEncoding=utf8"
# -- The driverClassName of external database
driverClassName: "org.postgresql.Driver"
zookeeper:
# -- If not exists external registry, the zookeeper registry will be used by default.
enabled: true
service:
# -- The port of zookeeper
port: 2181
# -- A list of comma separated Four Letter Words commands to use
fourlwCommandsWhitelist: "srvr,ruok,wchs,cons"
persistence:
# -- Set `zookeeper.persistence.enabled` to true to mount a new volume for internal ZooKeeper
enabled: false
# -- PersistentVolumeClaim size
size: "20Gi"
# -- ZooKeeper data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClass: "-"
registryEtcd:
# -- If you want to use Etcd for your registry center, change this value to true. And set zookeeper.enabled to false
enabled: false
# -- Etcd endpoints
endpoints: ""
# -- Etcd namespace
namespace: "dolphinscheduler"
# -- Etcd user
user: ""
# -- Etcd passWord
passWord: ""
# -- Etcd authority
authority: ""
# Please create a new folder: deploy/kubernetes/dolphinscheduler/etcd-certs
ssl:
# -- If your Etcd server has configured with ssl, change this value to true. About certification files you can see [here](https://github.com/etcd-io/jetcd/blob/main/docs/SslConfig.md) for how to convert.
enabled: false
# -- CertFile file path
certFile: "etcd-certs/ca.crt"
# -- keyCertChainFile file path
keyCertChainFile: "etcd-certs/client.crt"
# -- keyFile file path
keyFile: "etcd-certs/client.pem"
registryJdbc:
# -- If you want to use JDbc for your registry center, change this value to true. And set zookeeper.enabled and registryEtcd.enabled to false
enabled: false
# -- Used to schedule refresh the ephemeral data/ lock
termRefreshInterval: 2s
# -- Used to calculate the expire time
termExpireTimes: 3
hikariConfig:
# -- Default use same Dolphinscheduler's database, if you want to use other database please change `enabled` to `true` and change other configs
enabled: false
# -- Default use same Dolphinscheduler's database if you don't change this value. If you set this value, Registry jdbc's database type will use it
driverClassName: com.mysql.cj.jdbc.Driver
# -- Default use same Dolphinscheduler's database if you don't change this value. If you set this value, Registry jdbc's database type will use it
jdbcurl: jdbc:mysql://
# -- Default use same Dolphinscheduler's database if you don't change this value. If you set this value, Registry jdbc's database type will use it
username: ""
# -- Default use same Dolphinscheduler's database if you don't change this value. If you set this value, Registry jdbc's database type will use it
password: ""
## If exists external registry and set zookeeper.enable value to false, the external registry will be used.
externalRegistry:
# -- If exists external registry and set `zookeeper.enable` && `registryEtcd.enabled` && `registryJdbc.enabled` to false, specify the external registry plugin name
registryPluginName: "zookeeper"
# -- If exists external registry and set `zookeeper.enable` && `registryEtcd.enabled` && `registryJdbc.enabled` to false, specify the external registry servers
registryServers: "127.0.0.1:2181"
security:
authentication:
# -- Authentication types (supported types: PASSWORD,LDAP,CASDOOR_SSO)
type: PASSWORD
# IF you set type `LDAP`, below config will be effective
ldap:
# -- LDAP urls
urls: ldap://ldap.forumsys.com:389/
# -- LDAP base dn
basedn: dc=example,dc=com
# -- LDAP username
username: cn=read-only-admin,dc=example,dc=com
# -- LDAP password
password: password
user:
# -- Admin user account when you log-in with LDAP
admin: read-only-admin
# -- LDAP user identity attribute
identityattribute: uid
# -- LDAP user email attribute
emailattribute: mail
# -- action when ldap user is not exist,default value: CREATE. Optional values include(CREATE,DENY)
notexistaction: CREATE
ssl:
# -- LDAP ssl switch
enable: false
# -- LDAP jks file absolute path, do not change this value
truststore: "/opt/ldapkeystore.jks"
# -- LDAP jks file base64 content.
# If you use macOS, please run `base64 -b 0 -i /path/to/your.jks`.
# If you use Linux, please run `base64 -w 0 /path/to/your.jks`.
# If you use Windows, please run `certutil -f -encode /path/to/your.jks`.
# Then copy the base64 content to below field in one line
jksbase64content: ""
# -- LDAP jks password
truststorepassword: ""
conf:
# -- auto restart, if true, all components will be restarted automatically after the common configuration is updated. if false, you need to restart the components manually. default is false
auto: false
# common configuration
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, OSS, GCS, ABS, NONE
resource.storage.type: S3
# -- 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 credentials provider type. support: AWSStaticCredentialsProvider, InstanceProfileCredentialsProvider
# AWSStaticCredentialsProvider: use the access key and secret key to authenticate
# InstanceProfileCredentialsProvider: use the IAM role to authenticate
aws.credentials.provider.type: AWSStaticCredentialsProvider
# -- The AWS access key. if resource.storage.type=S3, and credentials.provider.type is AWSStaticCredentialsProvider. This configuration is required
aws.s3.access.key.id: minioadmin
# -- The AWS secret access key. if resource.storage.type=S3, and credentials.provider.type is AWSStaticCredentialsProvider. This configuration is required
aws.s3.access.key.secret: minioadmin
# -- The AWS Region to use. if resource.storage.type=S3, This configuration is required
aws.s3.region: ca-central-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.
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
aws.s3.endpoint: http://minio: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
# -- azure storage account name, required if you set resource.storage.type=ABS
resource.azure.client.id: minioadmin
# -- azure storage account key, required if you set resource.storage.type=ABS
resource.azure.client.secret: minioadmin
# -- azure storage subId, required if you set resource.storage.type=ABS
resource.azure.subId: minioadmin
# -- azure storage tenantId, required if you set resource.storage.type=ABS
resource.azure.tenant.id: minioadmin
# -- 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: '!@#$%^&*'
# -- 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"
# -- way to collect applicationId: log, aop
appId.collect: log
common:
## Configmap
configmap:
# -- The jvm options for dolphinscheduler, suitable for all servers
DOLPHINSCHEDULER_OPTS: ""
# -- User data directory path, self configuration, please make sure the directory exists and have read write permissions
DATA_BASEDIR_PATH: "/tmp/dolphinscheduler"
# -- Resource store on HDFS/S3 path, please make sure the directory exists on hdfs and have read write permissions
RESOURCE_UPLOAD_PATH: "/dolphinscheduler"
# dolphinscheduler env
# -- Set `HADOOP_HOME` for DolphinScheduler's task environment
HADOOP_HOME: "/opt/soft/hadoop"
# -- Set `HADOOP_CONF_DIR` for DolphinScheduler's task environment
HADOOP_CONF_DIR: "/opt/soft/hadoop/etc/hadoop"
# -- Set `SPARK_HOME` for DolphinScheduler's task environment
SPARK_HOME: "/opt/soft/spark"
# -- Set `PYTHON_LAUNCHER` for DolphinScheduler's task environment
PYTHON_LAUNCHER: "/usr/bin/python/bin/python3"
# -- Set `JAVA_HOME` for DolphinScheduler's task environment
JAVA_HOME: "/opt/java/openjdk"
# -- Set `HIVE_HOME` for DolphinScheduler's task environment
HIVE_HOME: "/opt/soft/hive"
# -- Set `FLINK_HOME` for DolphinScheduler's task environment
FLINK_HOME: "/opt/soft/flink"
# -- Set `DATAX_LAUNCHER` for DolphinScheduler's task environment
DATAX_LAUNCHER: "/opt/soft/datax/bin/datax.py"
## Shared storage persistence mounted into api, master and worker, such as Hadoop, Spark, Flink and DataX binary package
sharedStoragePersistence:
# -- Set `common.sharedStoragePersistence.enabled` to `true` to mount a shared storage volume for Hadoop, Spark binary and etc
enabled: false
# -- The mount path for the shared storage volume
mountPath: "/opt/soft"
# -- `PersistentVolumeClaim` access modes, must be `ReadWriteMany`
accessModes:
- "ReadWriteMany"
# -- Shared Storage persistent volume storage class, must support the access mode: ReadWriteMany
storageClassName: "-"
# -- `PersistentVolumeClaim` size
storage: "20Gi"
## If RESOURCE_STORAGE_TYPE is HDFS and FS_DEFAULT_FS is file:///, fsFileResourcePersistence should be enabled for resource storage
fsFileResourcePersistence:
# -- Set `common.fsFileResourcePersistence.enabled` to `true` to mount a new file resource volume for `api` and `worker`
enabled: false
# -- `PersistentVolumeClaim` access modes, must be `ReadWriteMany`
accessModes:
- "ReadWriteMany"
# -- Resource persistent volume storage class, must support the access mode: `ReadWriteMany`
storageClassName: "-"
# -- `PersistentVolumeClaim` size
storage: "20Gi"
master:
# -- Enable or disable the Master component
enabled: true
# -- PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
podManagementPolicy: "Parallel"
# -- Update strategy
# ref: https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/#update-strategies
#
updateStrategy:
type: RollingUpdate
# -- 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: [node-affinity](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#node-affinity)
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: [assign-pod-node](https://kubernetes.io/docs/concepts/scheduling-eviction/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.
# More info: [manage-resources-containers](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/)
resources: {}
# resources:
# limits:
# memory: "8Gi"
# cpu: "4"
# requests:
# memory: "2Gi"
# cpu: "500m"
# -- enable configure custom config
enableCustomizedConfig: false
# -- configure aligned with https://github.com/apache/dolphinscheduler/blob/dev/dolphinscheduler-master/src/main/resources/application.yaml
customizedConfig: { }
# customizedConfig:
# application.yaml: |
# profiles:
# active: postgresql
# banner:
# charset: UTF-8
# jackson:
# time-zone: UTC
# date-format: "yyyy-MM-dd HH:mm:ss"
# -- Periodic probe of container liveness. Container will be restarted if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
livenessProbe:
# -- Turn on and off liveness probe
enabled: true
# -- Delay before liveness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
successThreshold: "1"
# -- Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
readinessProbe:
# -- Turn on and off readiness probe
enabled: true
# -- Delay before readiness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
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:
# -- Set `master.persistentVolumeClaim.enabled` to `true` to mount a new volume for `master`
enabled: false
# -- `PersistentVolumeClaim` access modes
accessModes:
- "ReadWriteOnce"
# -- `Master` logs data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClassName: "-"
# -- `PersistentVolumeClaim` size
storage: "20Gi"
env:
# -- The jvm options for master server
JAVA_OPTS: "-Xms1g -Xmx1g -Xmn512m"
# -- Master execute thread number to limit process instances
MASTER_EXEC_THREADS: "100"
# -- Master execute task number in parallel per process instance
MASTER_EXEC_TASK_NUM: "20"
# -- Master dispatch task number per batch
MASTER_DISPATCH_TASK_NUM: "3"
# -- Master host selector to select a suitable worker, optional values include Random, RoundRobin, LowerWeight
MASTER_HOST_SELECTOR: "LowerWeight"
# -- Master max heartbeat interval
MASTER_MAX_HEARTBEAT_INTERVAL: "10s"
# -- Master heartbeat error threshold
MASTER_HEARTBEAT_ERROR_THRESHOLD: "5"
# -- Master commit task retry times
MASTER_TASK_COMMIT_RETRYTIMES: "5"
# -- master commit task interval, the unit is second
MASTER_TASK_COMMIT_INTERVAL: "1s"
# -- master state wheel interval, the unit is second
MASTER_STATE_WHEEL_INTERVAL: "5s"
# -- If set true, will open master overload protection
MASTER_SERVER_LOAD_PROTECTION_ENABLED: false
# -- Master max system cpu usage, when the master's system cpu usage is smaller then this value, master server can execute workflow.
MASTER_SERVER_LOAD_PROTECTION_MAX_SYSTEM_CPU_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Master max jvm cpu usage, when the master's jvm cpu usage is smaller then this value, master server can execute workflow.
MASTER_SERVER_LOAD_PROTECTION_MAX_JVM_CPU_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Master max System memory usage , when the master's system memory usage is smaller then this value, master server can execute workflow.
MASTER_SERVER_LOAD_PROTECTION_MAX_SYSTEM_MEMORY_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Master max disk usage , when the master's disk usage is smaller then this value, master server can execute workflow.
MASTER_SERVER_LOAD_PROTECTION_MAX_DISK_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Master failover interval, the unit is minute
MASTER_FAILOVER_INTERVAL: "10m"
# -- Master kill application when handle failover
MASTER_KILL_APPLICATION_WHEN_HANDLE_FAILOVER: "true"
service:
# -- annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
annotations: {}
# -- serviceMonitor for prometheus operator
serviceMonitor:
# -- Enable or disable master serviceMonitor
enabled: false
# -- serviceMonitor.interval interval at which metrics should be scraped
interval: 15s
# -- serviceMonitor.path path of the metrics endpoint
path: /actuator/prometheus
# -- serviceMonitor.labels ServiceMonitor extra labels
labels: {}
# -- serviceMonitor.annotations ServiceMonitor annotations
annotations: {}
worker:
# -- Enable or disable the Worker component
enabled: true
# -- PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
podManagementPolicy: "Parallel"
# -- Update strategy
# ref: https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/#update-strategies
#
updateStrategy:
type: RollingUpdate
# -- 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: [node-affinity](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#node-affinity)
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: [assign-pod-node](https://kubernetes.io/docs/concepts/scheduling-eviction/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.
# More info: [manage-resources-containers](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/)
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.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
# -- enable configure custom config
enableCustomizedConfig: false
# -- configure aligned with https://github.com/apache/dolphinscheduler/blob/dev/dolphinscheduler-worker/src/main/resources/application.yaml
customizedConfig: { }
# customizedConfig:
# application.yaml: |
# banner:
# charset: UTF-8
# jackson:
# time-zone: UTC
# date-format: "yyyy-MM-dd HH:mm:ss"
livenessProbe:
# -- Turn on and off liveness probe
enabled: true
# -- Delay before liveness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
successThreshold: "1"
# -- Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
readinessProbe:
# -- Turn on and off readiness probe
enabled: true
# -- Delay before readiness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
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:
# -- Set `worker.persistentVolumeClaim.enabled` to `true` to enable `persistentVolumeClaim` for `worker`
enabled: false
## dolphinscheduler data volume
dataPersistentVolume:
# -- Set `worker.persistentVolumeClaim.dataPersistentVolume.enabled` to `true` to mount a data volume for `worker`
enabled: false
# -- `PersistentVolumeClaim` access modes
accessModes:
- "ReadWriteOnce"
# -- `Worker` data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClassName: "-"
# -- `PersistentVolumeClaim` size
storage: "20Gi"
## dolphinscheduler logs volume
logsPersistentVolume:
# -- Set `worker.persistentVolumeClaim.logsPersistentVolume.enabled` to `true` to mount a logs volume for `worker`
enabled: false
# -- `PersistentVolumeClaim` access modes
accessModes:
- "ReadWriteOnce"
# -- `Worker` logs data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClassName: "-"
# -- `PersistentVolumeClaim` size
storage: "20Gi"
env:
# -- If set true, will open worker overload protection
WORKER_SERVER_LOAD_PROTECTION_ENABLED: false
# -- Worker max system cpu usage, when the worker's system cpu usage is smaller then this value, worker server can be dispatched tasks.
WORKER_SERVER_LOAD_PROTECTION_MAX_SYSTEM_CPU_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Worker max jvm cpu usage, when the worker's jvm cpu usage is smaller then this value, worker server can be dispatched tasks.
WORKER_SERVER_LOAD_PROTECTION_MAX_JVM_CPU_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Worker max memory usage , when the worker's memory usage is smaller then this value, worker server can be dispatched tasks.
WORKER_SERVER_LOAD_PROTECTION_MAX_SYSTEM_MEMORY_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Worker max disk usage , when the worker's disk usage is smaller then this value, worker server can be dispatched tasks.
WORKER_SERVER_LOAD_PROTECTION_MAX_DISK_USAGE_PERCENTAGE_THRESHOLDS: 0.7
# -- Worker execute thread number to limit task instances
WORKER_EXEC_THREADS: "100"
# -- Worker heartbeat interval
WORKER_MAX_HEARTBEAT_INTERVAL: "10s"
# -- Worker host weight to dispatch tasks
WORKER_HOST_WEIGHT: "100"
# -- tenant corresponds to the user of the system, which is used by the worker to submit the job. If system does not have this user, it will be automatically created after the parameter worker.tenant.auto.create is true.
WORKER_TENANT_CONFIG_AUTO_CREATE_TENANT_ENABLED: true
# -- If set true, will use worker bootstrap user as the tenant to execute task when the tenant is `default`;
WORKER_TENANT_CONFIG_DEFAULT_TENANT_ENABLED: false
keda:
# -- Enable or disable the Keda component
enabled: false
# -- Keda namespace labels
namespaceLabels: { }
# -- How often KEDA polls the DolphinScheduler DB to report new scale requests to the HPA
pollingInterval: 5
# -- How many seconds KEDA will wait before scaling to zero.
# Note that HPA has a separate cooldown period for scale-downs
cooldownPeriod: 30
# -- Minimum number of workers created by keda
minReplicaCount: 0
# -- Maximum number of workers created by keda
maxReplicaCount: 3
# -- Specify HPA related options
advanced: { }
# horizontalPodAutoscalerConfig:
# behavior:
# scaleDown:
# stabilizationWindowSeconds: 300
# policies:
# - type: Percent
# value: 100
# periodSeconds: 15
service:
# -- annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
annotations: {}
# -- serviceMonitor for prometheus operator
serviceMonitor:
# -- Enable or disable worker serviceMonitor
enabled: false
# -- serviceMonitor.interval interval at which metrics should be scraped
interval: 15s
# -- serviceMonitor.path path of the metrics endpoint
path: /actuator/prometheus
# -- serviceMonitor.labels ServiceMonitor extra labels
labels: {}
# -- serviceMonitor.annotations ServiceMonitor annotations
annotations: {}
alert:
# -- Enable or disable the Alert-Server component
enabled: true
# -- 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 of deployment. Can be "Recreate" or "RollingUpdate"
type: "RollingUpdate"
rollingUpdate:
# -- The maximum number of pods that can be scheduled above the desired number of pods
maxSurge: "25%"
# -- The maximum number of pods that can be unavailable during the update
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: {}
# -- Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
# More info: [node-affinity](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#node-affinity)
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: [assign-pod-node](https://kubernetes.io/docs/concepts/scheduling-eviction/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.
# More info: [manage-resources-containers](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/)
resources: {}
# resources:
# limits:
# memory: "2Gi"
# cpu: "1"
# requests:
# memory: "1Gi"
# cpu: "500m"
# -- enable configure custom config
enableCustomizedConfig: false
# -- configure aligned with https://github.com/apache/dolphinscheduler/blob/dev/dolphinscheduler-alert/dolphinscheduler-alert-server/src/main/resources/application.yaml
customizedConfig: { }
# customizedConfig:
# application.yaml: |
# profiles:
# active: postgresql
# banner:
# charset: UTF-8
# jackson:
# time-zone: UTC
# date-format: "yyyy-MM-dd HH:mm:ss"
# -- Periodic probe of container liveness. Container will be restarted if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
livenessProbe:
# -- Turn on and off liveness probe
enabled: true
# -- Delay before liveness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
successThreshold: "1"
# -- Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
readinessProbe:
# -- Turn on and off readiness probe
enabled: true
# -- Delay before readiness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
successThreshold: "1"
# -- PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
# More info: [persistentvolumeclaims](https://kubernetes.io/docs/concepts/storage/persistent-volumes/#persistentvolumeclaims)
persistentVolumeClaim:
# -- Set `alert.persistentVolumeClaim.enabled` to `true` to mount a new volume for `alert`
enabled: false
# -- `PersistentVolumeClaim` access modes
accessModes:
- "ReadWriteOnce"
# -- `Alert` logs data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClassName: "-"
# -- `PersistentVolumeClaim` size
storage: "20Gi"
env:
# -- The jvm options for alert server
JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
service:
# -- annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
annotations: {}
# -- serviceMonitor for prometheus operator
serviceMonitor:
# -- Enable or disable alert-server serviceMonitor
enabled: false
# -- serviceMonitor.interval interval at which metrics should be scraped
interval: 15s
# -- serviceMonitor.path path of the metrics endpoint
path: /actuator/prometheus
# -- serviceMonitor.labels ServiceMonitor extra labels
labels: {}
# -- serviceMonitor.annotations ServiceMonitor annotations
annotations: {}
api:
# -- Enable or disable the API-Server component
enabled: true
# -- 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 of deployment. Can be "Recreate" or "RollingUpdate"
type: "RollingUpdate"
rollingUpdate:
# -- The maximum number of pods that can be scheduled above the desired number of pods
maxSurge: "25%"
# -- The maximum number of pods that can be unavailable during the update
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: {}
# -- Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
# More info: [node-affinity](https://kubernetes.io/docs/concepts/scheduling-eviction/assign-pod-node/#node-affinity)
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: [assign-pod-node](https://kubernetes.io/docs/concepts/scheduling-eviction/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.
# More info: [manage-resources-containers](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/)
resources: {}
# resources:
# limits:
# memory: "2Gi"
# cpu: "1"
# requests:
# memory: "1Gi"
# cpu: "500m"
# -- enable configure custom config
enableCustomizedConfig: false
# -- configure aligned with https://github.com/apache/dolphinscheduler/blob/dev/dolphinscheduler-api/src/main/resources/application.yaml
customizedConfig: { }
# customizedConfig:
# application.yaml: |
# profiles:
# active: postgresql
# banner:
# charset: UTF-8
# jackson:
# time-zone: UTC
# date-format: "yyyy-MM-dd HH:mm:ss"
# -- Periodic probe of container liveness. Container will be restarted if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
livenessProbe:
# -- Turn on and off liveness probe
enabled: true
# -- Delay before liveness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
successThreshold: "1"
# -- Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails.
# More info: [container-probes](https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#container-probes)
readinessProbe:
# -- Turn on and off readiness probe
enabled: true
# -- Delay before readiness probe is initiated
initialDelaySeconds: "30"
# -- How often to perform the probe
periodSeconds: "30"
# -- When the probe times out
timeoutSeconds: "5"
# -- Minimum consecutive failures for the probe
failureThreshold: "3"
# -- Minimum consecutive successes for the probe
successThreshold: "1"
# -- PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
# More info: [persistentvolumeclaims](https://kubernetes.io/docs/concepts/storage/persistent-volumes/#persistentvolumeclaims)
persistentVolumeClaim:
# -- Set `api.persistentVolumeClaim.enabled` to `true` to mount a new volume for `api`
enabled: false
# -- `PersistentVolumeClaim` access modes
accessModes:
- "ReadWriteOnce"
# -- `api` logs data persistent volume storage class. If set to "-", storageClassName: "", which disables dynamic provisioning
storageClassName: "-"
# -- `PersistentVolumeClaim` size
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 api service is exposed when type=NodePort
nodePort: ""
# -- pythonNodePort is the port on each node on which this python api service is exposed when type=NodePort
pythonNodePort: ""
# -- 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: {}
# -- serviceMonitor for prometheus operator
serviceMonitor:
# -- Enable or disable api-server serviceMonitor
enabled: false
# -- serviceMonitor.interval interval at which metrics should be scraped
interval: 15s
# -- serviceMonitor.path path of the metrics endpoint
path: /dolphinscheduler/actuator/prometheus
# -- serviceMonitor.labels ServiceMonitor extra labels
labels: {}
# -- serviceMonitor.annotations ServiceMonitor annotations
annotations: {}
env:
# -- The jvm options for api server
JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
taskTypeFilter:
# -- Enable or disable the task type filter.
# If set to true, the API-Server will return tasks of a specific type set in api.taskTypeFilter.task
# Note: This feature only filters tasks to return a specific type on the WebUI. However, you can still create any task that DolphinScheduler supports via the API.
enabled: false
# -- taskTypeFilter.taskType task type
# -- ref: [task-type-config.yaml](https://github.com/apache/dolphinscheduler/blob/dev/dolphinscheduler-api/src/main/resources/task-type-config.yaml)
task: {}
# example task sets
# universal:
# - 'SQL'
# cloud: []
# logic: []
# dataIntegration: []
# machineLearning: []
# other: []
ingress:
# -- Enable ingress
enabled: false
# -- Ingress host
host: "dolphinscheduler.org"
# -- Ingress path
path: "/dolphinscheduler"
# -- Ingress annotations
annotations: {}
tls:
# -- Enable ingress tls
enabled: false
# -- Ingress tls secret name
secretName: "dolphinscheduler-tls"