QuickStart in Docker

Prerequisites

• Docker 1.13.1+
• Docker Compose 1.11.0+

How to use this Docker image

Here’re 3 ways to quickly install DolphinScheduler

The First Way: Start a DolphinScheduler by docker-compose (recommended)

In this way, you need to install docker-compose as a prerequisite, please install it yourself according to the rich docker-compose installation guidance on the Internet

For Windows 7-10, you can install Docker Toolbox. For Windows 10 64-bit, you can install Docker Desktop, and pay attention to the system requirements

0. Configure memory not less than 4GB

For Mac user, click Docker Desktop -> Preferences -> Resources -> Memory

For Windows Docker Toolbox user, two items need to be configured:

• Memory: Open Oracle VirtualBox Manager, if you double-click Docker Quickstart Terminal and successfully run Docker Toolbox, you will see a Virtual Machine named default. And click Settings -> System -> Motherboard -> Base Memory
• Port Forwarding: Click Settings -> Network -> Advanced -> Port forwarding -> Add. Name, Host Port and Guest Port all fill in 12345, regardless of Host IP and Guest IP

For Windows Docker Desktop user

• Hyper-V mode: Click Docker Desktop -> Settings -> Resources -> Memory
• WSL 2 mode: Refer to WSL 2 utility VM

1. Download the Source Code Package

Please download the source code package apache-dolphinscheduler-2.0.6-src.tar.gz, download address: download

2. Pull Image and Start the Service

For Mac and Linux user, open Terminal For Windows Docker Toolbox user, open Docker Quickstart Terminal For Windows Docker Desktop user, open Windows PowerShell

$ tar -zxvf apache-dolphinscheduler-2.0.6-src.tar.gz
$ cd apache-dolphinscheduler-2.0.6-src/docker/docker-swarm
$ docker pull dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6
$ docker tag apache/dolphinscheduler:2.0.6 apache/dolphinscheduler:latest
$ docker-compose up -d

PowerShell should use cd apache-dolphinscheduler-2.0.6-src\docker\docker-swarm

The PostgreSQL (with username root, password root and database dolphinscheduler) and ZooKeeper services will start by default

3. Login

Visit the Web UI: http://localhost:12345/dolphinscheduler (The local address is http://localhost:12345/dolphinscheduler)

The default username is admin and the default password is dolphinscheduler123

Please refer to the Quick Start in the chapter Quick Start to explore how to use DolphinScheduler

The Second Way: Start via specifying the existing PostgreSQL and ZooKeeper service

In this way, you need to install docker as a prerequisite, please install it yourself according to the rich docker installation guidance on the Internet

1. Basic Required Software (please install by yourself)

• PostgreSQL (8.2.15+)
• ZooKeeper (3.4.6+)
• Docker (1.13.1+)

2. Please login to the PostgreSQL database and create a database named dolphinscheduler

3. Initialize the database, import sql/dolphinscheduler_postgre.sql to create tables and initial data

4. Download the DolphinScheduler Image

We have already uploaded user-oriented DolphinScheduler image to the Docker repository so that you can pull the image from the docker repository:

docker pull dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6

5. Run a DolphinScheduler Instance

$ docker run -d --name dolphinscheduler \
-e DATABASE_HOST="192.168.x.x" -e DATABASE_PORT="5432" -e DATABASE_DATABASE="dolphinscheduler" \
-e DATABASE_USERNAME="test" -e DATABASE_PASSWORD="test" \
-e ZOOKEEPER_QUORUM="192.168.x.x:2181" \
-p 12345:12345 \
apache/dolphinscheduler:2.0.6 all

Note: database username test and password test need to be replaced with your actual PostgreSQL username and password, 192.168.x.x need to be replaced with your relate PostgreSQL and ZooKeeper host IP

6. Login

Same as above

The Third Way: Start a standalone DolphinScheduler server

The following services are automatically started when the container starts:

     MasterServer         ----- master service
     WorkerServer         ----- worker service
     LoggerServer         ----- logger service
     ApiApplicationServer ----- api service
     AlertServer          ----- alert service
     PythonGatewayServer  ----- python gateway service

If you just want to run part of the services in the DolphinScheduler

You can start some services in DolphinScheduler by running the following commands.

• Start a master server, For example:

$ docker run -d --name dolphinscheduler-master \
-e DATABASE_HOST="192.168.x.x" -e DATABASE_PORT="5432" -e DATABASE_DATABASE="dolphinscheduler" \
-e DATABASE_USERNAME="test" -e DATABASE_PASSWORD="test" \
-e ZOOKEEPER_QUORUM="192.168.x.x:2181" \
apache/dolphinscheduler:2.0.6 master-server

• Start a worker server (including logger server), For example:

$ docker run -d --name dolphinscheduler-worker \
-e DATABASE_HOST="192.168.x.x" -e DATABASE_PORT="5432" -e DATABASE_DATABASE="dolphinscheduler" \
-e DATABASE_USERNAME="test" -e DATABASE_PASSWORD="test" \
-e ZOOKEEPER_QUORUM="192.168.x.x:2181" \
apache/dolphinscheduler:2.0.6 worker-server

• Start a api server, For example:

$ docker run -d --name dolphinscheduler-api \
-e DATABASE_HOST="192.168.x.x" -e DATABASE_PORT="5432" -e DATABASE_DATABASE="dolphinscheduler" \
-e DATABASE_USERNAME="test" -e DATABASE_PASSWORD="test" \
-e ZOOKEEPER_QUORUM="192.168.x.x:2181" \
-p 12345:12345 \
apache/dolphinscheduler:2.0.6 api-server

• Start a alert server, For example:

$ docker run -d --name dolphinscheduler-alert \
-e DATABASE_HOST="192.168.x.x" -e DATABASE_PORT="5432" -e DATABASE_DATABASE="dolphinscheduler" \
-e DATABASE_USERNAME="test" -e DATABASE_PASSWORD="test" \
apache/dolphinscheduler:2.0.6 alert-server

• Start a python gateway server, For example:

$ docker run -d --name dolphinscheduler-python-gateway \
-e DATABASE_HOST="192.168.x.x" -e DATABASE_PORT="5432" -e DATABASE_DATABASE="dolphinscheduler" \
-e DATABASE_USERNAME="test" -e DATABASE_PASSWORD="test" \
apache/dolphinscheduler:2.0.6 python-gateway

Note: You must be specify DATABASE_HOST, DATABASE_PORT, DATABASE_DATABASE, DATABASE_USERNAME, DATABASE_PASSWORD, ZOOKEEPER_QUORUM when start a standalone dolphinscheduler server.

Environment Variables

The Docker container is configured through environment variables, and the Appendix-Environment Variables lists the configurable environment variables of the DolphinScheduler and their default values

Especially, it can be configured through the environment variable configuration file config.env.sh in Docker Compose and Docker Swarm

Support Matrix

FAQ

How to manage DolphinScheduler by docker-compose?

Start, restart, stop or list containers:

docker-compose start
docker-compose restart
docker-compose stop
docker-compose ps

Stop containers and remove containers, networks:

docker-compose down

Stop containers and remove containers, networks and volumes:

docker-compose down -v

How to view the logs of a container?

List all running containers:

docker ps
docker ps --format "{{.Names}}" # only print names

View the logs of a container named docker-swarm_dolphinscheduler-api_1:

docker logs docker-swarm_dolphinscheduler-api_1
docker logs -f docker-swarm_dolphinscheduler-api_1 # follow log output
docker logs --tail 10 docker-swarm_dolphinscheduler-api_1 # show last 10 lines from the end of the logs

How to scale master and worker by docker-compose?

Scale master to 2 instances:

docker-compose up -d --scale dolphinscheduler-master=2 dolphinscheduler-master

Scale worker to 3 instances:

docker-compose up -d --scale dolphinscheduler-worker=3 dolphinscheduler-worker

How to deploy DolphinScheduler on Docker Swarm?

Assuming that the Docker Swarm cluster has been created (If there is no Docker Swarm cluster, please refer to create-swarm)

Start a stack named dolphinscheduler:

docker stack deploy -c docker-stack.yml dolphinscheduler

List the services in the stack named dolphinscheduler:

docker stack services dolphinscheduler

Stop and remove the stack named dolphinscheduler:

docker stack rm dolphinscheduler

Remove the volumes of the stack named dolphinscheduler:

docker volume rm -f $(docker volume ls --format "{{.Name}}" | grep -e "^dolphinscheduler")

How to scale master and worker on Docker Swarm?

Scale master of the stack named dolphinscheduler to 2 instances:

docker service scale dolphinscheduler_dolphinscheduler-master=2

Scale worker of the stack named dolphinscheduler to 3 instances:

docker service scale dolphinscheduler_dolphinscheduler-worker=3

How to build a Docker image?

Build from the source code (Require Maven 3.3+ & JDK 1.8+)

In Unix-Like, execute in Terminal:

$ bash ./docker/build/hooks/build

In Windows, execute in cmd or PowerShell:

C:\dolphinscheduler-src>.\docker\build\hooks\build.bat

Please read ./docker/build/hooks/build ./docker/build/hooks/build.bat script files if you don’t understand

Build from the binary distribution (Not require Maven 3.3+ & JDK 1.8+)

Please download the binary distribution package apache-dolphinscheduler-2.0.6-bin.tar.gz, download address: download. And put apache-dolphinscheduler-2.0.6-bin.tar.gz into the apache-dolphinscheduler-2.0.6-src/docker/build directory, execute in Terminal or PowerShell:

$ cd apache-dolphinscheduler-2.0.6-src/docker/build
$ docker build --build-arg VERSION=2.0.6 -t apache/dolphinscheduler:2.0.6 .

PowerShell should use cd apache-dolphinscheduler-2.0.6-src/docker/build

Build multi-platform images

Currently support to build images including linux/amd64 and linux/arm64 platform architecture, requirements:

1. Support docker buildx
2. Own the push permission of https://hub.docker.com/r/apache/dolphinscheduler (Be cautious: The build command will automatically push the multi-platform architecture images to the docker hub of apache/dolphinscheduler by default)

Execute:

$ docker login # login to push apache/dolphinscheduler
$ bash ./docker/build/hooks/build

How to add an environment variable for Docker?

If you would like to do additional initialization in an image derived from this one, add one or more environment variables under /root/start-init-conf.sh, and modify template files in /opt/dolphinscheduler/conf/*.tpl.

For example, to add an environment variable SECURITY_AUTHENTICATION_TYPE in /root/start-init-conf.sh:

export SECURITY_AUTHENTICATION_TYPE=PASSWORD

and to modify application-api.properties.tpl template file, add the SECURITY_AUTHENTICATION_TYPE:

security.authentication.type=${SECURITY_AUTHENTICATION_TYPE}

/root/start-init-conf.sh will dynamically generate config file:

echo "generate dolphinscheduler config"
ls ${DOLPHINSCHEDULER_HOME}/conf/ | grep ".tpl" | while read line; do
eval "cat << EOF
$(cat ${DOLPHINSCHEDULER_HOME}/conf/${line})
EOF
" > ${DOLPHINSCHEDULER_HOME}/conf/${line%.*}
done

How to use MySQL as the DolphinScheduler’s database instead of PostgreSQL?

Because of the commercial license, we cannot directly use the driver of MySQL.

If you want to use MySQL, you can build a new image based on the apache/dolphinscheduler image as follows.

1. Download the MySQL driver mysql-connector-java-8.0.16.jar

2. Create a new Dockerfile to add MySQL driver:

FROM dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6
COPY mysql-connector-java-8.0.16.jar /opt/dolphinscheduler/lib

1. Build a new docker image including MySQL driver:

docker build -t apache/dolphinscheduler:mysql-driver .

1. Modify all image fields to apache/dolphinscheduler:mysql-driver in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

1. Comment the dolphinscheduler-postgresql block in docker-compose.yml

2. Add dolphinscheduler-mysql service in docker-compose.yml (Optional, you can directly use an external MySQL database)

3. Modify DATABASE environment variables in config.env.sh

DATABASE_TYPE=mysql
DATABASE_DRIVER=com.mysql.jdbc.Driver
DATABASE_HOST=dolphinscheduler-mysql
DATABASE_PORT=3306
DATABASE_USERNAME=root
DATABASE_PASSWORD=root
DATABASE_DATABASE=dolphinscheduler
DATABASE_PARAMS=useUnicode=true&characterEncoding=UTF-8

If you have added dolphinscheduler-mysql service in docker-compose.yml, just set DATABASE_HOST to dolphinscheduler-mysql

1. Run a dolphinscheduler (See How to use this docker image)

How to support MySQL datasource in Datasource manage?

Because of the commercial license, we cannot directly use the driver of MySQL.

If you want to add MySQL datasource, you can build a new image based on the apache/dolphinscheduler image as follows.

1. Download the MySQL driver mysql-connector-java-8.0.16.jar

2. Create a new Dockerfile to add MySQL driver:

FROM dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6
COPY mysql-connector-java-8.0.16.jar /opt/dolphinscheduler/lib

1. Build a new docker image including MySQL driver:

docker build -t apache/dolphinscheduler:mysql-driver .

1. Modify all image fields to apache/dolphinscheduler:mysql-driver in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

1. Run a dolphinscheduler (See How to use this docker image)

2. Add a MySQL datasource in Datasource manage

How to support Oracle datasource in Datasource manage?

Because of the commercial license, we cannot directly use the driver of Oracle.

If you want to add Oracle datasource, you can build a new image based on the apache/dolphinscheduler image as follows.

1. Download the Oracle driver ojdbc8.jar (such as ojdbc8-19.9.0.0.jar)

2. Create a new Dockerfile to add Oracle driver:

FROM dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6
COPY ojdbc8-19.9.0.0.jar /opt/dolphinscheduler/lib

1. Build a new docker image including Oracle driver:

docker build -t apache/dolphinscheduler:oracle-driver .

1. Modify all image fields to apache/dolphinscheduler:oracle-driver in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

1. Run a dolphinscheduler (See How to use this docker image)

2. Add an Oracle datasource in Datasource manage

How to support Python 2 pip and custom requirements.txt?

1. Create a new Dockerfile to install pip:

FROM dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6
COPY requirements.txt /tmp
RUN apt-get update && \
    apt-get install -y --no-install-recommends python-pip && \
    pip install --no-cache-dir -r /tmp/requirements.txt && \
    rm -rf /var/lib/apt/lists/*

The command will install the default pip 18.1. If you upgrade the pip, just add one line

    pip install --no-cache-dir -U pip && \

1. Build a new docker image including pip:

docker build -t apache/dolphinscheduler:pip .

1. Modify all image fields to apache/dolphinscheduler:pip in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

1. Run a dolphinscheduler (See How to use this docker image)

2. Verify pip under a new Python task

How to support Python 3?

1. Create a new Dockerfile to install Python 3:

FROM dolphinscheduler.docker.scarf.sh/apache/dolphinscheduler:2.0.6
RUN apt-get update && \
    apt-get install -y --no-install-recommends python3 && \
    rm -rf /var/lib/apt/lists/*

The command will install the default Python 3.7.3. If you also want to install pip3, just replace python3 with python3-pip like

    apt-get install -y --no-install-recommends python3-pip && \

1. Build a new docker image including Python 3:

docker build -t apache/dolphinscheduler:python3 .

1. Modify all image fields to apache/dolphinscheduler:python3 in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

1. Modify PYTHON_HOME to /usr/bin/python3 in config.env.sh

2. Run a dolphinscheduler (See How to use this docker image)

3. Verify Python 3 under a new Python task

How to support Hadoop, Spark, Flink, Hive or DataX?

Take Spark 2.4.7 as an example:

1. Download the Spark 2.4.7 release binary spark-2.4.7-bin-hadoop2.7.tgz

2. Run a dolphinscheduler (See How to use this docker image)

3. Copy the Spark 2.4.7 release binary into Docker container

docker cp spark-2.4.7-bin-hadoop2.7.tgz docker-swarm_dolphinscheduler-worker_1:/opt/soft

Because the volume dolphinscheduler-shared-local is mounted on /opt/soft, all files in /opt/soft will not be lost

1. Attach the container and ensure that SPARK_HOME2 exists

docker exec -it docker-swarm_dolphinscheduler-worker_1 bash
cd /opt/soft
tar zxf spark-2.4.7-bin-hadoop2.7.tgz
rm -f spark-2.4.7-bin-hadoop2.7.tgz
ln -s spark-2.4.7-bin-hadoop2.7 spark2 # or just mv
$SPARK_HOME2/bin/spark-submit --version

The last command will print the Spark version if everything goes well

1. Verify Spark under a Shell task

$SPARK_HOME2/bin/spark-submit --class org.apache.spark.examples.SparkPi $SPARK_HOME2/examples/jars/spark-examples_2.11-2.4.7.jar

Check whether the task log contains the output like Pi is roughly 3.146015

1. Verify Spark under a Spark task

The file spark-examples_2.11-2.4.7.jar needs to be uploaded to the resources first, and then create a Spark task with:

• Spark Version: SPARK2
• Main Class: org.apache.spark.examples.SparkPi
• Main Package: spark-examples_2.11-2.4.7.jar
• Deploy Mode: local

Similarly, check whether the task log contains the output like Pi is roughly 3.146015

1. Verify Spark on YARN

Spark on YARN (Deploy Mode is cluster or client) requires Hadoop support. Similar to Spark support, the operation of supporting Hadoop is almost the same as the previous steps

Ensure that $HADOOP_HOME and $HADOOP_CONF_DIR exists

How to support Spark 3?

In fact, the way to submit applications with spark-submit is the same, regardless of Spark 1, 2 or 3. In other words, the semantics of SPARK_HOME2 is the second SPARK_HOME instead of SPARK2‘s HOME, so just set SPARK_HOME2=/path/to/spark3

Take Spark 3.1.1 as an example:

1. Download the Spark 3.1.1 release binary spark-3.1.1-bin-hadoop2.7.tgz

2. Run a dolphinscheduler (See How to use this docker image)

3. Copy the Spark 3.1.1 release binary into Docker container

docker cp spark-3.1.1-bin-hadoop2.7.tgz docker-swarm_dolphinscheduler-worker_1:/opt/soft

1. Attach the container and ensure that SPARK_HOME2 exists

docker exec -it docker-swarm_dolphinscheduler-worker_1 bash
cd /opt/soft
tar zxf spark-3.1.1-bin-hadoop2.7.tgz
rm -f spark-3.1.1-bin-hadoop2.7.tgz
ln -s spark-3.1.1-bin-hadoop2.7 spark2 # or just mv
$SPARK_HOME2/bin/spark-submit --version

The last command will print the Spark version if everything goes well

1. Verify Spark under a Shell task

$SPARK_HOME2/bin/spark-submit --class org.apache.spark.examples.SparkPi $SPARK_HOME2/examples/jars/spark-examples_2.12-3.1.1.jar

Check whether the task log contains the output like Pi is roughly 3.146015

How to support shared storage between Master, Worker and Api server?

Note: If it is deployed on a single machine by docker-compose, step 1 and 2 can be skipped directly, and execute the command like docker cp hadoop-3.2.2.tar.gz docker-swarm_dolphinscheduler-worker_1:/opt/soft to put Hadoop into the shared directory /opt/soft in the container

For example, Master, Worker and Api server may use Hadoop at the same time

1. Modify the volume dolphinscheduler-shared-local to support NFS in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

volumes:
  dolphinscheduler-shared-local:
    driver_opts:
      type: "nfs"
      o: "addr=10.40.0.199,nolock,soft,rw"
      device: ":/path/to/shared/dir"

1. Put the Hadoop into the NFS

2. Ensure that $HADOOP_HOME and $HADOOP_CONF_DIR are correct

How to support local file resource storage instead of HDFS and S3?

Note: If it is deployed on a single machine by docker-compose, step 2 can be skipped directly

1. Modify the following environment variables in config.env.sh:

RESOURCE_STORAGE_TYPE=HDFS
FS_DEFAULT_FS=file:///

1. Modify the volume dolphinscheduler-resource-local to support NFS in docker-compose.yml

If you want to deploy dolphinscheduler on Docker Swarm, you need to modify docker-stack.yml

volumes:
  dolphinscheduler-resource-local:
    driver_opts:
      type: "nfs"
      o: "addr=10.40.0.199,nolock,soft,rw"
      device: ":/path/to/resource/dir"

How to support S3 resource storage like MinIO?

Take MinIO as an example: Modify the following environment variables in config.env.sh

RESOURCE_STORAGE_TYPE=S3
RESOURCE_UPLOAD_PATH=/dolphinscheduler
FS_DEFAULT_FS=s3a://BUCKET_NAME
FS_S3A_ENDPOINT=http://MINIO_IP:9000
FS_S3A_ACCESS_KEY=MINIO_ACCESS_KEY
FS_S3A_SECRET_KEY=MINIO_SECRET_KEY

BUCKET_NAME, MINIO_IP, MINIO_ACCESS_KEY and MINIO_SECRET_KEY need to be modified to actual values

Note: MINIO_IP can only use IP instead of the domain name, because DolphinScheduler currently doesn’t support S3 path style access

How to configure SkyWalking?

Modify SkyWalking environment variables in config.env.sh:

SKYWALKING_ENABLE=true
SW_AGENT_COLLECTOR_BACKEND_SERVICES=127.0.0.1:11800
SW_GRPC_LOG_SERVER_HOST=127.0.0.1
SW_GRPC_LOG_SERVER_PORT=11800

Appendix-Environment Variables

Database

DATABASE_TYPE

This environment variable sets the type for the database. The default value is postgresql.

Note: You must be specify it when start a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_DRIVER

This environment variable sets the type for the database. The default value is org.postgresql.Driver.

Note: You must specify it when starting a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_HOST

This environment variable sets the host for the database. The default value is 127.0.0.1.

Note: You must specify it when start a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_PORT

This environment variable sets the port for the database. The default value is 5432.

Note: You must specify it when start a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_USERNAME

This environment variable sets the username for the database. The default value is root.

Note: You must specify it when start a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_PASSWORD

This environment variable sets the password for the database. The default value is root.

Note: You must specify it when start a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_DATABASE

This environment variable sets the database for the database. The default value is dolphinscheduler.

Note: You must specify it when start a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

DATABASE_PARAMS

This environment variable sets the database for the database. The default value is characterEncoding=utf8.

Note: You must specify it when starting a standalone dolphinscheduler server. Like master-server, worker-server, api-server, alert-server.

ZooKeeper

ZOOKEEPER_QUORUM

This environment variable sets zookeeper quorum. The default value is 127.0.0.1:2181.

Note: You must specify it when starting a standalone dolphinscheduler server. Like master-server, worker-server, api-server.

ZOOKEEPER_ROOT

This environment variable sets zookeeper root directory for dolphinscheduler. The default value is /dolphinscheduler.

Common

DOLPHINSCHEDULER_OPTS

This environment variable sets JVM options for dolphinscheduler, suitable for master-server, worker-server, api-server, alert-server, logger-server. The default value is empty.

DATA_BASEDIR_PATH

User data directory path, self configuration, please make sure the directory exists and have read-write permissions. The default value is /tmp/dolphinscheduler

RESOURCE_STORAGE_TYPE

This environment variable sets resource storage types for dolphinscheduler like HDFS, S3, NONE. The default value is HDFS.

RESOURCE_UPLOAD_PATH

This environment variable sets resource store path on HDFS/S3 for resource storage. The default value is /dolphinscheduler.

FS_DEFAULT_FS

This environment variable sets fs.defaultFS for resource storage like file:///, hdfs://mycluster:8020 or s3a://dolphinscheduler. The default value is file:///.

FS_S3A_ENDPOINT

This environment variable sets s3 endpoint for resource storage. The default value is s3.xxx.amazonaws.com.

FS_S3A_ACCESS_KEY

This environment variable sets s3 access key for resource storage. The default value is xxxxxxx.

FS_S3A_SECRET_KEY

This environment variable sets s3 secret key for resource storage. The default value is xxxxxxx.

HADOOP_SECURITY_AUTHENTICATION_STARTUP_STATE

This environment variable sets whether to startup Kerberos. The default value is false.

JAVA_SECURITY_KRB5_CONF_PATH

This environment variable sets java.security.krb5.conf path. The default value is /opt/krb5.conf.

LOGIN_USER_KEYTAB_USERNAME

This environment variable sets login user from the keytab username. The default value is hdfs@HADOOP.COM.

LOGIN_USER_KEYTAB_PATH

This environment variable sets login user from the keytab path. The default value is /opt/hdfs.keytab.

KERBEROS_EXPIRE_TIME

This environment variable sets Kerberos expire time, the unit is hour. The default value is 2.

HDFS_ROOT_USER

This environment variable sets HDFS root user when resource.storage.type=HDFS. The default value is hdfs.

RESOURCE_MANAGER_HTTPADDRESS_PORT

This environment variable sets resource manager HTTP address port. The default value is 8088.

YARN_RESOURCEMANAGER_HA_RM_IDS

This environment variable sets yarn resourcemanager ha rm ids. The default value is empty.

YARN_APPLICATION_STATUS_ADDRESS

This environment variable sets yarn application status address. The default value is http://ds1:%s/ws/v1/cluster/apps/%s.

SKYWALKING_ENABLE

This environment variable sets whether to enable SkyWalking. The default value is false.

SW_AGENT_COLLECTOR_BACKEND_SERVICES

This environment variable sets agent collector backend services for SkyWalking. The default value is 127.0.0.1:11800.

SW_GRPC_LOG_SERVER_HOST

This environment variable sets gRPC log server host for SkyWalking. The default value is 127.0.0.1.

SW_GRPC_LOG_SERVER_PORT

This environment variable sets gRPC log server port for SkyWalking. The default value is 11800.

HADOOP_HOME

This environment variable sets HADOOP_HOME. The default value is /opt/soft/hadoop.

HADOOP_CONF_DIR

This environment variable sets HADOOP_CONF_DIR. The default value is /opt/soft/hadoop/etc/hadoop.

SPARK_HOME1

This environment variable sets SPARK_HOME1. The default value is /opt/soft/spark1.

SPARK_HOME2

This environment variable sets SPARK_HOME2. The default value is /opt/soft/spark2.

PYTHON_HOME

This environment variable sets PYTHON_HOME. The default value is /usr/bin/python.

JAVA_HOME

This environment variable sets JAVA_HOME. The default value is /usr/local/openjdk-8.

HIVE_HOME

This environment variable sets HIVE_HOME. The default value is /opt/soft/hive.

FLINK_HOME

This environment variable sets FLINK_HOME. The default value is /opt/soft/flink.

DATAX_HOME

This environment variable sets DATAX_HOME. The default value is /opt/soft/datax.

Master Server

MASTER_SERVER_OPTS

This environment variable sets JVM options for master-server. The default value is -Xms1g -Xmx1g -Xmn512m.

MASTER_EXEC_THREADS

This environment variable sets exec thread number for master-server. The default value is 100.

MASTER_EXEC_TASK_NUM

This environment variable sets exec task number for master-server. The default value is 20.

MASTER_DISPATCH_TASK_NUM

This environment variable sets dispatch task number for master-server. The default value is 3.

MASTER_HOST_SELECTOR

This environment variable sets host selector for master-server. Optional values include Random, RoundRobin and LowerWeight. The default value is LowerWeight.

MASTER_HEARTBEAT_INTERVAL

This environment variable sets heartbeat interval for master-server. The default value is 10.

MASTER_TASK_COMMIT_RETRYTIMES

This environment variable sets task commit retry times for master-server. The default value is 5.

MASTER_TASK_COMMIT_INTERVAL

This environment variable sets task commit interval for master-server. The default value is 1.

MASTER_MAX_CPULOAD_AVG

This environment variable sets max CPU load avg for master-server. The default value is -1.

MASTER_RESERVED_MEMORY

This environment variable sets reserved memory for master-server, the unit is G. The default value is 0.3.

Worker Server

WORKER_SERVER_OPTS

This environment variable sets JVM options for worker-server. The default value is -Xms1g -Xmx1g -Xmn512m.

WORKER_EXEC_THREADS

This environment variable sets exec thread number for worker-server. The default value is 100.

WORKER_HEARTBEAT_INTERVAL

This environment variable sets heartbeat interval for worker-server. The default value is 10.

WORKER_MAX_CPULOAD_AVG

This environment variable sets max CPU load avg for worker-server. The default value is -1.

WORKER_RESERVED_MEMORY

This environment variable sets reserved memory for worker-server, the unit is G. The default value is 0.3.

WORKER_GROUPS

This environment variable sets groups for worker-server. The default value is default.

Alert Server

ALERT_SERVER_OPTS

This environment variable sets JVM options for alert-server. The default value is -Xms512m -Xmx512m -Xmn256m.

XLS_FILE_PATH

This environment variable sets xls file path for alert-server. The default value is /tmp/xls.

MAIL_SERVER_HOST

This environment variable sets mail server host for alert-server. The default value is empty.

MAIL_SERVER_PORT

This environment variable sets mail server port for alert-server. The default value is empty.

MAIL_SENDER

This environment variable sets mail sender for alert-server. The default value is empty.

MAIL_USER=

This environment variable sets mail user for alert-server. The default value is empty.

MAIL_PASSWD

This environment variable sets mail password for alert-server. The default value is empty.

MAIL_SMTP_STARTTLS_ENABLE

This environment variable sets SMTP tls for alert-server. The default value is true.

MAIL_SMTP_SSL_ENABLE

This environment variable sets SMTP ssl for alert-server. The default value is false.

MAIL_SMTP_SSL_TRUST

This environment variable sets SMTP ssl truest for alert-server. The default value is empty.

ENTERPRISE_WECHAT_ENABLE

This environment variable sets enterprise wechat enable for alert-server. The default value is false.

ENTERPRISE_WECHAT_CORP_ID

This environment variable sets enterprise wechat corp id for alert-server. The default value is empty.

ENTERPRISE_WECHAT_SECRET

This environment variable sets enterprise wechat secret for alert-server. The default value is empty.

ENTERPRISE_WECHAT_AGENT_ID

This environment variable sets enterprise wechat agent id for alert-server. The default value is empty.

ENTERPRISE_WECHAT_USERS

This environment variable sets enterprise wechat users for alert-server. The default value is empty.

Api Server

API_SERVER_OPTS

This environment variable sets JVM options for api-server. The default value is -Xms512m -Xmx512m -Xmn256m.

Logger Server

LOGGER_SERVER_OPTS

This environment variable sets JVM options for logger-server. The default value is -Xms512m -Xmx512m -Xmn256m.