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Resource Center Configuration

  • You could use Resource Center to upload text files, UDFs and other task-related files.
  • You could configure Resource Center to use distributed file system like Hadoop (2.6+), MinIO cluster or remote storage products like AWS S3, Alibaba Cloud OSS, etc.
  • You could configure Resource Center to use local file system. If you deploy DolphinScheduler in Standalone mode, you could configure it to use local file system for Resouce Center without the need of an external HDFS system or S3.
  • Furthermore, if you deploy DolphinScheduler in Cluster mode, you could use S3FS-FUSE to mount S3 or JINDO-FUSE to mount OSS to your machines and use the local file system for Resouce Center. In this way, you could operate remote files as if on your local machines.

Use Local File System

Configure common.properties

If you deploy DolphinScheduler in Cluster or Pseudo-Cluster mode, you need to configure api-server/conf/common.properties and worker-server/conf/common.properties. If you deploy DolphinScheduler in Standalone mode, you only need to configure standalone-server/conf/common.properties as follows:

  • Change resource.storage.upload.base.path to your local directory path. Please make sure the tenant resource.hdfs.root.user has read and write permissions for resource.storage.upload.base.path, e,g. /tmp/dolphinscheduler. DolphinScheduler will create the directory you configure if it does not exist.
  • Modify resource.storage.type=HDFS and resource.hdfs.fs.defaultFS=file:///.

NOTE: Please modify the value of resource.storage.upload.base.path if you do not want to use the default value as the base path.

Use HDFS or Remote Object Storage

After version 3.0.0-alpha, if you want to upload resources to Resource Center connected to HDFS or S3, you need to configure api-server/conf/common.properties and worker-server/conf/common.properties.

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# 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, NONE
resource.storage.type=NONE
# resource store on HDFS/S3/OSS 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=/tmp/dolphinscheduler

# The AWS access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.access.key.id=minioadmin
# The AWS secret access key. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.secret.access.key=minioadmin
# The AWS Region to use. if resource.storage.type=S3 or use EMR-Task, This configuration is required
resource.aws.region=cn-north-1
# The name of the bucket. You need to create them by yourself. Otherwise, the system cannot start. All buckets in Amazon S3 share a single namespace; ensure the bucket is given a unique name.
resource.aws.s3.bucket.name=dolphinscheduler
# You need to set this parameter when private cloud s3. If S3 uses public cloud, you only need to set resource.aws.region or set to the endpoint of a public cloud such as S3.cn-north-1.amazonaws.com.cn
resource.aws.s3.endpoint=http://localhost:9000

# alibaba cloud access key id, required if you set resource.storage.type=OSS 
resource.alibaba.cloud.access.key.id=<your-access-key-id>
# alibaba cloud access key secret, required if you set resource.storage.type=OSS
resource.alibaba.cloud.access.key.secret=<your-access-key-secret>
# alibaba cloud region, required if you set resource.storage.type=OSS
resource.alibaba.cloud.region=cn-hangzhou
# oss bucket name, required if you set resource.storage.type=OSS
resource.alibaba.cloud.oss.bucket.name=dolphinscheduler
# oss bucket endpoint, required if you set resource.storage.type=OSS
resource.alibaba.cloud.oss.endpoint=https://oss-cn-hangzhou.aliyuncs.com

# if resource.storage.type=HDFS, the user must have the permission to create directories under the HDFS root path
resource.hdfs.root.user=hdfs
# if resource.storage.type=S3, the value like: s3a://dolphinscheduler; if resource.storage.type=HDFS and namenode HA is enabled, you need to copy core-site.xml and hdfs-site.xml to conf dir
resource.hdfs.fs.defaultFS=hdfs://mycluster:8020

# whether to startup kerberos
hadoop.security.authentication.startup.state=false

# java.security.krb5.conf path
java.security.krb5.conf.path=/opt/krb5.conf

# login user from keytab username
login.user.keytab.username=hdfs-mycluster@ESZ.COM

# login user from keytab path
login.user.keytab.path=/opt/hdfs.headless.keytab

# kerberos expire time, the unit is hour
kerberos.expire.time=2


# resourcemanager port, the default value is 8088 if not specified
resource.manager.httpaddress.port=8088
# if resourcemanager HA is enabled, please set the HA IPs; if resourcemanager is single, keep this value empty
yarn.resourcemanager.ha.rm.ids=192.168.xx.xx,192.168.xx.xx
# if resourcemanager HA is enabled or not use resourcemanager, please keep the default value; If resourcemanager is single, you only need to replace ds1 to actual resourcemanager hostname
yarn.application.status.address=http://ds1:%s/ws/v1/cluster/apps/%s
# job history status url when application number threshold is reached(default 10000, maybe it was set to 1000)
yarn.job.history.status.address=http://ds1:19888/ws/v1/history/mapreduce/jobs/%s

# datasource encryption enable
datasource.encryption.enable=false

# datasource encryption salt
datasource.encryption.salt=!@#$%^&*

# data quality option
data-quality.jar.name=dolphinscheduler-data-quality-dev-SNAPSHOT.jar

#data-quality.error.output.path=/tmp/data-quality-error-data

# Network IP gets priority, default inner outer

# 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

# system env path
#dolphinscheduler.env.path=dolphinscheduler_env.sh

# 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

Note:

  • If only the api-server/conf/common.properties file is configured, then resource uploading is enabled, but you can not use resources in task. If you want to use or execute the files in the workflow you need to configure worker-server/conf/common.properties too.
  • If you want to use the resource upload function, the deployment user in installation and deployment must have relevant operation authority.
  • If you using a Hadoop cluster with HA, you need to enable HDFS resource upload, and you need to copy the core-site.xml and hdfs-site.xml under the Hadoop cluster to worker-server/conf and api-server/conf, otherwise skip this copy step.