DolphinScheduler/deploy/kubernetes/dolphinscheduler/values.yaml

928 lines
41 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.
# -- 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/dolphinscheduler
# -- 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
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 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: 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.
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://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: '!@#$%^&*'
# -- 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"
# -- 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"
# -- 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)
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 heartbeat interval, the unit is second
MASTER_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"
# -- Master max cpuload avg, only higher than the system cpu load average, master server can schedule
MASTER_MAX_CPU_LOAD_AVG: "1"
# -- Master reserved memory, only lower than system available memory, master server can schedule, the unit is G
MASTER_RESERVED_MEMORY: "0.3"
# -- 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"
# -- 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)
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:
# -- Worker max cpu load avg, only higher than the system cpu load average, worker server can be dispatched tasks
WORKER_MAX_CPU_LOAD_AVG: "1"
# -- Worker reserved memory, only lower than system available memory, worker server can be dispatched tasks, the unit is G
WORKER_RESERVED_MEMORY: "0.3"
# -- Worker execute thread number to limit task instances
WORKER_EXEC_THREADS: "100"
# -- Worker heartbeat interval, the unit is second
WORKER_HEARTBEAT_INTERVAL: "10s"
# -- Worker heartbeat error threshold
WORKER_HEART_ERROR_THRESHOLD: "5"
# -- Worker host weight to dispatch tasks
WORKER_HOST_WEIGHT: "100"
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"
# -- 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"
# -- 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: []
# dataQuality: []
# 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"