mirror of
https://gitee.com/dolphinscheduler/DolphinScheduler.git
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f5be784044
Signed-off-by: Gallardot <gallardot@apache.org> Co-authored-by: Eric Gao <ericgao.apache@gmail.com>
664 lines
26 KiB
YAML
664 lines
26 KiB
YAML
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# Default values for dolphinscheduler-chart.
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# This is a YAML-formatted file.
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# Declare variables to be passed into your templates.
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timezone: "Asia/Shanghai"
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# Used to detect whether dolphinscheduler dependent services such as database are ready
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initImage:
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pullPolicy: "IfNotPresent"
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busybox: "busybox:1.30.1"
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image:
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registry: "dolphinscheduler.docker.scarf.sh/apache"
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tag: "dev-SNAPSHOT"
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pullPolicy: "IfNotPresent"
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pullSecret: ""
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master: dolphinscheduler-master
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worker: dolphinscheduler-worker
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api: dolphinscheduler-api
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alert: dolphinscheduler-alert-server
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tools: dolphinscheduler-tools
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## If not exists external database, by default, Dolphinscheduler's database will use it.
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postgresql:
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enabled: true
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postgresqlUsername: "root"
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postgresqlPassword: "root"
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postgresqlDatabase: "dolphinscheduler"
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params: "characterEncoding=utf8"
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persistence:
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enabled: false
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size: "20Gi"
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storageClass: "-"
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mysql:
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enabled: false
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auth:
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username: "ds"
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password: "ds"
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database: "dolphinscheduler"
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params: "characterEncoding=utf8"
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primary:
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persistence:
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enabled: false
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size: "20Gi"
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storageClass: "-"
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minio:
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enabled: true
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auth:
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rootUser: minioadmin
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rootPassword: minioadmin
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persistence:
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enabled: false
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defaultBuckets: "dolphinscheduler"
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## If exists external database, and set postgresql.enable value to false.
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## external database will be used, otherwise Dolphinscheduler's database will be used.
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externalDatabase:
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enabled: false
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type: "postgresql"
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host: "localhost"
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port: "5432"
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username: "root"
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password: "root"
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database: "dolphinscheduler"
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params: "characterEncoding=utf8"
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## If not exists external registry, the zookeeper registry will be used by default.
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zookeeper:
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enabled: true
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service:
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port: 2181
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fourlwCommandsWhitelist: "srvr,ruok,wchs,cons"
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persistence:
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enabled: false
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size: "20Gi"
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storageClass: "-"
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etcd:
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enabled: false
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endpoints: ""
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namespace: "dolphinscheduler"
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user: ""
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passWord: ""
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authority: ""
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# Please create a new folder: deploy/kubernetes/dolphinscheduler/etcd-certs
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ssl:
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enabled: false
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certFile: "etcd-certs/ca.crt"
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keyCertChainFile: "etcd-certs/client.crt"
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keyFile: "etcd-certs/client.pem"
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## If exists external registry and set zookeeper.enable value to false, the external registry will be used.
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externalRegistry:
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registryPluginName: "zookeeper"
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registryServers: "127.0.0.1:2181"
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security:
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authentication:
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type: PASSWORD
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ldap:
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urls: ldap://ldap.forumsys.com:389/
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basedn: dc=example,dc=com
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username: cn=read-only-admin,dc=example,dc=com
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password: password
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user:
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admin: read-only-admin
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identityattribute: uid
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emailattribute: mail
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notexistaction: CREATE
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ssl:
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enable: false
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# do not change this value
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truststore: "/opt/ldapkeystore.jks"
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# if you use macOS, please run `base64 -b 0 -i /path/to/your.jks`
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# if you use Linux, please run `base64 -w 0 /path/to/your.jks`
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# if you use Windows, please run `certutil -f -encode /path/to/your.jks`
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# Then copy the base64 content to below field in one line
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jksbase64content: ""
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truststorepassword: ""
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conf:
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common:
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# user data local directory path, please make sure the directory exists and have read write permissions
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data.basedir.path: /tmp/dolphinscheduler
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# resource storage type: HDFS, S3, OSS, GCS, ABS, NONE
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resource.storage.type: S3
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# 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
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resource.storage.upload.base.path: /dolphinscheduler
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# The AWS access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
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resource.aws.access.key.id: minioadmin
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# The AWS secret access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
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resource.aws.secret.access.key: minioadmin
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# The AWS Region to use. if resource.storage.type=S3 or use EMR-Task, This configuration is required
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resource.aws.region: ca-central-1
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# 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.
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resource.aws.s3.bucket.name: dolphinscheduler
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# 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
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resource.aws.s3.endpoint: http://minio:9000
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# alibaba cloud access key id, required if you set resource.storage.type=OSS
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resource.alibaba.cloud.access.key.id: <your-access-key-id>
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# alibaba cloud access key secret, required if you set resource.storage.type=OSS
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resource.alibaba.cloud.access.key.secret: <your-access-key-secret>
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# alibaba cloud region, required if you set resource.storage.type=OSS
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resource.alibaba.cloud.region: cn-hangzhou
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# oss bucket name, required if you set resource.storage.type=OSS
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resource.alibaba.cloud.oss.bucket.name: dolphinscheduler
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# oss bucket endpoint, required if you set resource.storage.type=OSS
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resource.alibaba.cloud.oss.endpoint: https://oss-cn-hangzhou.aliyuncs.com
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# if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path
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resource.hdfs.root.user: hdfs
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# 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
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resource.hdfs.fs.defaultFS: hdfs://mycluster:8020
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# whether to startup kerberos
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hadoop.security.authentication.startup.state: false
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# java.security.krb5.conf path
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java.security.krb5.conf.path: /opt/krb5.conf
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# login user from keytab username
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login.user.keytab.username: hdfs-mycluster@ESZ.COM
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# login user from keytab path
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login.user.keytab.path: /opt/hdfs.headless.keytab
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# kerberos expire time, the unit is hour
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kerberos.expire.time: 2
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# resourcemanager port, the default value is 8088 if not specified
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resource.manager.httpaddress.port: 8088
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# if resourcemanager HA is enabled, please set the HA IPs; if resourcemanager is single, keep this value empty
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yarn.resourcemanager.ha.rm.ids: 192.168.xx.xx,192.168.xx.xx
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# 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
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yarn.application.status.address: http://ds1:%s/ws/v1/cluster/apps/%s
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# job history status url when application number threshold is reached(default 10000, maybe it was set to 1000)
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yarn.job.history.status.address: http://ds1:19888/ws/v1/history/mapreduce/jobs/%s
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# datasource encryption enable
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datasource.encryption.enable: false
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# datasource encryption salt
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datasource.encryption.salt: '!@#$%^&*'
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# data quality option
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data-quality.jar.name: dolphinscheduler-data-quality-dev-SNAPSHOT.jar
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# Whether hive SQL is executed in the same session
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support.hive.oneSession: false
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# 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
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sudo.enable: true
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# development state
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development.state: false
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# rpc port
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alert.rpc.port: 50052
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# set path of conda.sh
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conda.path: /opt/anaconda3/etc/profile.d/conda.sh
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# Task resource limit state
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task.resource.limit.state: false
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# mlflow task plugin preset repository
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ml.mlflow.preset_repository: https://github.com/apache/dolphinscheduler-mlflow
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# mlflow task plugin preset repository version
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ml.mlflow.preset_repository_version: "main"
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# way to collect applicationId: log, aop
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appId.collect: log
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common:
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## Configmap
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configmap:
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DOLPHINSCHEDULER_OPTS: ""
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DATA_BASEDIR_PATH: "/tmp/dolphinscheduler"
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RESOURCE_UPLOAD_PATH: "/dolphinscheduler"
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# dolphinscheduler env
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HADOOP_HOME: "/opt/soft/hadoop"
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HADOOP_CONF_DIR: "/opt/soft/hadoop/etc/hadoop"
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SPARK_HOME: "/opt/soft/spark"
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PYTHON_HOME: "/usr/bin/python"
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JAVA_HOME: "/opt/java/openjdk"
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HIVE_HOME: "/opt/soft/hive"
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FLINK_HOME: "/opt/soft/flink"
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DATAX_HOME: "/opt/soft/datax"
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## Shared storage persistence mounted into api, master and worker, such as Hadoop, Spark, Flink and DataX binary package
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sharedStoragePersistence:
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enabled: false
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mountPath: "/opt/soft"
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accessModes:
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- "ReadWriteMany"
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## storageClassName must support the access mode: ReadWriteMany
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storageClassName: "-"
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storage: "20Gi"
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## If RESOURCE_STORAGE_TYPE is HDFS and FS_DEFAULT_FS is file:///, fsFileResourcePersistence should be enabled for resource storage
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fsFileResourcePersistence:
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enabled: false
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accessModes:
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- "ReadWriteMany"
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## storageClassName must support the access mode: ReadWriteMany
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storageClassName: "-"
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storage: "20Gi"
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master:
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## PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
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podManagementPolicy: "Parallel"
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## Replicas is the desired number of replicas of the given Template.
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replicas: "3"
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## You can use annotations to attach arbitrary non-identifying metadata to objects.
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## Clients such as tools and libraries can retrieve this metadata.
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annotations: {}
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## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
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## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
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affinity: {}
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## NodeSelector is a selector which must be true for the pod to fit on a node.
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## Selector which must match a node's labels for the pod to be scheduled on that node.
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## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
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nodeSelector: {}
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## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
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## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
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tolerations: []
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## Compute Resources required by this container. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
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resources: {}
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# resources:
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# limits:
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# memory: "8Gi"
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# cpu: "4"
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# requests:
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# memory: "2Gi"
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# cpu: "500m"
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## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
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livenessProbe:
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enabled: true
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initialDelaySeconds: "30"
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periodSeconds: "30"
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timeoutSeconds: "5"
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failureThreshold: "3"
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successThreshold: "1"
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## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
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readinessProbe:
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enabled: true
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initialDelaySeconds: "30"
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periodSeconds: "30"
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timeoutSeconds: "5"
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failureThreshold: "3"
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successThreshold: "1"
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## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
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## The StatefulSet controller is responsible for mapping network identities to claims in a way that maintains the identity of a pod.
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## Every claim in this list must have at least one matching (by name) volumeMount in one container in the template.
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## A claim in this list takes precedence over any volumes in the template, with the same name.
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persistentVolumeClaim:
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enabled: false
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accessModes:
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- "ReadWriteOnce"
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storageClassName: "-"
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storage: "20Gi"
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env:
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JAVA_OPTS: "-Xms1g -Xmx1g -Xmn512m"
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MASTER_EXEC_THREADS: "100"
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MASTER_EXEC_TASK_NUM: "20"
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MASTER_DISPATCH_TASK_NUM: "3"
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MASTER_HOST_SELECTOR: "LowerWeight"
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MASTER_HEARTBEAT_INTERVAL: "10s"
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MASTER_HEARTBEAT_ERROR_THRESHOLD: "5"
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MASTER_TASK_COMMIT_RETRYTIMES: "5"
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MASTER_TASK_COMMIT_INTERVAL: "1s"
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MASTER_STATE_WHEEL_INTERVAL: "5s"
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MASTER_MAX_CPU_LOAD_AVG: "1"
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MASTER_RESERVED_MEMORY: "0.3"
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MASTER_FAILOVER_INTERVAL: "10m"
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MASTER_KILL_APPLICATION_WHEN_HANDLE_FAILOVER: "true"
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service:
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# annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
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annotations: {}
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# serviceMonitor for prometheus operator
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serviceMonitor:
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# -- Enable or disable master serviceMonitor
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enabled: false
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# -- @param serviceMonitor.interval interval at which metrics should be scraped
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interval: 15s
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# -- @param serviceMonitor.path path of the metrics endpoint
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path: /actuator/prometheus
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# -- @param serviceMonitor.labels ServiceMonitor extra labels
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labels: {}
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# -- @param serviceMonitor.annotations ServiceMonitor annotations
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annotations: {}
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worker:
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## PodManagementPolicy controls how pods are created during initial scale up, when replacing pods on nodes, or when scaling down.
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podManagementPolicy: "Parallel"
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## Replicas is the desired number of replicas of the given Template.
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replicas: "3"
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## You can use annotations to attach arbitrary non-identifying metadata to objects.
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## Clients such as tools and libraries can retrieve this metadata.
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annotations: {}
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## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
|
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## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
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affinity: {}
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## NodeSelector is a selector which must be true for the pod to fit on a node.
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## 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/
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nodeSelector: {}
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## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
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## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
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tolerations: []
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## Compute Resources required by this container. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
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resources: {}
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# resources:
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# limits:
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# memory: "8Gi"
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# cpu: "4"
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# requests:
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# memory: "2Gi"
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# cpu: "500m"
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## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
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livenessProbe:
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enabled: true
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initialDelaySeconds: "30"
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periodSeconds: "30"
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timeoutSeconds: "5"
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failureThreshold: "3"
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successThreshold: "1"
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## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
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readinessProbe:
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enabled: true
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initialDelaySeconds: "30"
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periodSeconds: "30"
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timeoutSeconds: "5"
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failureThreshold: "3"
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successThreshold: "1"
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## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
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|
## The StatefulSet controller is responsible for mapping network identities to claims in a way that maintains the identity of a pod.
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|
## Every claim in this list must have at least one matching (by name) volumeMount in one container in the template.
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## A claim in this list takes precedence over any volumes in the template, with the same name.
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persistentVolumeClaim:
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enabled: false
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## dolphinscheduler data volume
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dataPersistentVolume:
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enabled: false
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accessModes:
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- "ReadWriteOnce"
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storageClassName: "-"
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storage: "20Gi"
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## dolphinscheduler logs volume
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logsPersistentVolume:
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enabled: false
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accessModes:
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- "ReadWriteOnce"
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storageClassName: "-"
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storage: "20Gi"
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env:
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WORKER_MAX_CPU_LOAD_AVG: "1"
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WORKER_RESERVED_MEMORY: "0.3"
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WORKER_EXEC_THREADS: "100"
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WORKER_HEARTBEAT_INTERVAL: "10s"
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WORKER_HEART_ERROR_THRESHOLD: "5"
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WORKER_HOST_WEIGHT: "100"
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keda:
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enabled: false
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namespaceLabels: { }
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# How often KEDA polls the DolphinScheduler DB to report new scale requests to the HPA
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pollingInterval: 5
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# How many seconds KEDA will wait before scaling to zero.
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# Note that HPA has a separate cooldown period for scale-downs
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cooldownPeriod: 30
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# Minimum number of workers created by keda
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minReplicaCount: 0
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# Maximum number of workers created by keda
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maxReplicaCount: 3
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|
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# Specify HPA related options
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advanced: { }
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# horizontalPodAutoscalerConfig:
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# behavior:
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# scaleDown:
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# stabilizationWindowSeconds: 300
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# policies:
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# - type: Percent
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# value: 100
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# periodSeconds: 15
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service:
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# annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
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annotations: {}
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# serviceMonitor for prometheus operator
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serviceMonitor:
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# -- Enable or disable worker serviceMonitor
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enabled: false
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# -- @param serviceMonitor.interval interval at which metrics should be scraped
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interval: 15s
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# -- @param serviceMonitor.path path of the metrics endpoint
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path: /actuator/prometheus
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# -- @param serviceMonitor.labels ServiceMonitor extra labels
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labels: {}
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# -- @param serviceMonitor.annotations ServiceMonitor annotations
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annotations: {}
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alert:
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## Number of desired pods. This is a pointer to distinguish between explicit zero and not specified. Defaults to 1.
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replicas: 1
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## The deployment strategy to use to replace existing pods with new ones.
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strategy:
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type: "RollingUpdate"
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rollingUpdate:
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maxSurge: "25%"
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maxUnavailable: "25%"
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## You can use annotations to attach arbitrary non-identifying metadata to objects.
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## Clients such as tools and libraries can retrieve this metadata.
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annotations: {}
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## Affinity is a group of affinity scheduling rules. If specified, the pod's scheduling constraints.
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## More info: https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.17/#affinity-v1-core
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affinity: {}
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## NodeSelector is a selector which must be true for the pod to fit on a node.
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## Selector which must match a node's labels for the pod to be scheduled on that node.
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## More info: https://kubernetes.io/docs/concepts/configuration/assign-pod-node/
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nodeSelector: {}
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## Tolerations are appended (excluding duplicates) to pods running with this RuntimeClass during admission,
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## effectively unioning the set of nodes tolerated by the pod and the RuntimeClass.
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tolerations: []
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## Compute Resources required by this container. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/configuration/manage-compute-resources-container
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resources: {}
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# resources:
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# limits:
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# memory: "2Gi"
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# cpu: "1"
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# requests:
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# memory: "1Gi"
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# cpu: "500m"
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## Periodic probe of container liveness. Container will be restarted if the probe fails. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
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livenessProbe:
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enabled: true
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initialDelaySeconds: "30"
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periodSeconds: "30"
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timeoutSeconds: "5"
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failureThreshold: "3"
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successThreshold: "1"
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## Periodic probe of container service readiness. Container will be removed from service endpoints if the probe fails. Cannot be updated.
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## More info: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle#container-probes
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readinessProbe:
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enabled: true
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initialDelaySeconds: "30"
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periodSeconds: "30"
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timeoutSeconds: "5"
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failureThreshold: "3"
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successThreshold: "1"
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## PersistentVolumeClaim represents a reference to a PersistentVolumeClaim in the same namespace.
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## More info: https://kubernetes.io/docs/concepts/storage/persistent-volumes#persistentvolumeclaims
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persistentVolumeClaim:
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enabled: false
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accessModes:
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- "ReadWriteOnce"
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storageClassName: "-"
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storage: "20Gi"
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env:
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JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
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service:
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# annotations may need to be set when want to scrapy metrics by prometheus but not install prometheus operator
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annotations: {}
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# serviceMonitor for prometheus operator
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serviceMonitor:
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# -- Enable or disable alert-server serviceMonitor
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enabled: false
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# -- @param serviceMonitor.interval interval at which metrics should be scraped
|
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interval: 15s
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# -- @param serviceMonitor.path path of the metrics endpoint
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path: /actuator/prometheus
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# -- @param serviceMonitor.labels ServiceMonitor extra labels
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labels: {}
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# -- @param serviceMonitor.annotations ServiceMonitor annotations
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annotations: {}
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api:
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## Number of desired pods. This is a pointer to distinguish between explicit zero and not specified. Defaults to 1.
|
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replicas: "1"
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|
## The deployment strategy to use to replace existing pods with new ones.
|
|
strategy:
|
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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: {}
|
|
## 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: {}
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|
# 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
|
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type: "ClusterIP"
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|
## clusterIP is the IP address of the service and is usually assigned randomly by the master
|
|
clusterIP: ""
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|
## nodePort is the port on each node on which this api service is exposed when type=NodePort
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nodePort: ""
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## pythonNodePort is the port on each node on which this python api service is exposed when type=NodePort
|
|
pythonNodePort: ""
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|
## 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: ""
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## loadBalancerIP when service.type is LoadBalancer. LoadBalancer will get created with the IP specified in this field
|
|
loadBalancerIP: ""
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|
## 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
|
|
# -- @param serviceMonitor.interval interval at which metrics should be scraped
|
|
interval: 15s
|
|
# -- @param serviceMonitor.path path of the metrics endpoint
|
|
path: /dolphinscheduler/actuator/prometheus
|
|
# -- @param serviceMonitor.labels ServiceMonitor extra labels
|
|
labels: {}
|
|
# -- @param serviceMonitor.annotations ServiceMonitor annotations
|
|
annotations: {}
|
|
env:
|
|
JAVA_OPTS: "-Xms512m -Xmx512m -Xmn256m"
|
|
|
|
ingress:
|
|
enabled: false
|
|
host: "dolphinscheduler.org"
|
|
path: "/dolphinscheduler"
|
|
annotations: {}
|
|
tls:
|
|
enabled: false
|
|
secretName: "dolphinscheduler-tls"
|