| # |
| # 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. |
| # |
| |
| # user data local directory path, please make sure the directory exists and have read write permissions |
| data.basedir.path=/tmp/dolphinscheduler |
| |
| # resource view suffixs |
| #resource.view.suffixs=txt,log,sh,bat,conf,cfg,py,java,sql,xml,hql,properties,json,yml,yaml,ini,js |
| |
| # resource storage type: HDFS, S3, OSS, GCS, ABS, NONE |
| resource.storage.type=NONE |
| # 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 |
| |
| # alibaba cloud access key id, required if you set resource.storage.type=OSS |
| resource.alibaba.cloud.access.key.id=<your-access-key-id> |
| # alibaba cloud access key secret, required if you set resource.storage.type=OSS |
| resource.alibaba.cloud.access.key.secret=<your-access-key-secret> |
| # alibaba cloud region, required if you set resource.storage.type=OSS |
| resource.alibaba.cloud.region=cn-hangzhou |
| # oss bucket name, required if you set resource.storage.type=OSS |
| resource.alibaba.cloud.oss.bucket.name=dolphinscheduler |
| # oss bucket endpoint, required if you set resource.storage.type=OSS |
| resource.alibaba.cloud.oss.endpoint=https://oss-cn-hangzhou.aliyuncs.com |
| |
| # if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path |
| resource.hdfs.root.user=hdfs |
| # if resource.storage.type=S3, the value like: s3a://dolphinscheduler; if resource.storage.type=HDFS and namenode HA is enabled, you need to copy core-site.xml and hdfs-site.xml to conf dir |
| resource.hdfs.fs.defaultFS=hdfs://mycluster:8020 |
| |
| # whether to startup kerberos |
| hadoop.security.authentication.startup.state=false |
| |
| # java.security.krb5.conf path |
| java.security.krb5.conf.path=/opt/krb5.conf |
| |
| # login user from keytab username |
| login.user.keytab.username=hdfs-mycluster@ESZ.COM |
| |
| # login user from keytab path |
| login.user.keytab.path=/opt/hdfs.headless.keytab |
| |
| # kerberos expire time, the unit is hour |
| kerberos.expire.time=2 |
| |
| |
| # resourcemanager port, the default value is 8088 if not specified |
| resource.manager.httpaddress.port=8088 |
| # if resourcemanager HA is enabled, please set the HA IPs; if resourcemanager is single, keep this value empty |
| yarn.resourcemanager.ha.rm.ids=192.168.xx.xx,192.168.xx.xx |
| # if resourcemanager HA is enabled or not use resourcemanager, please keep the default value; If resourcemanager is single, you only need to replace ds1 to actual resourcemanager hostname |
| yarn.application.status.address=http://ds1:%s/ws/v1/cluster/apps/%s |
| # job history status url when application number threshold is reached(default 10000, maybe it was set to 1000) |
| yarn.job.history.status.address=http://ds1:19888/ws/v1/history/mapreduce/jobs/%s |
| |
| # datasource encryption enable |
| datasource.encryption.enable=false |
| |
| # datasource encryption salt |
| datasource.encryption.salt=!@#$%^&* |
| |
| # 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 |
| |
| # network interface preferred like eth0, default: empty |
| #dolphin.scheduler.network.interface.preferred= |
| |
| # network IP gets priority, default: inner outer |
| #dolphin.scheduler.network.priority.strategy=default |
| |
| # development state |
| development.state=false |
| |
| # If the shell process is still active after this timeout value (in seconds), then will use kill -9 to kill it |
| shell.kill.wait.timeout=10 |
| |
| # 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(original regex match), aop |
| appId.collect=log |
| |
| # The default env list will be load by Shell task, e.g. /etc/profile,~/.bash_profile |
| # shell.env_source_list=/etc/profile,~/.bash_profile |