This guide describes two ways to deploy the Amoro demo environment: docker-compose or release packages. If you want to deploy by compiling the source code, please refer to Deployment.

Setup from Docker-Compose

The fastest way to deploy a Quick Demo environment is to use docker-compose.


Before starting to deploy Amoro based on Docker, please make sure that you have installed the docker-compose environment on your host. For information on installing Docker, please refer to Install Docker.

Linux or MacOS is recommended for use. If you are using a Windows system, consider using WSL2. For information on how to enable WSL2 and install Docker, please refer to Windows Installation.

After completing the Docker installation, please make sure that the docker-compose tool is installed Docker-Compose Installation.

Bring up demo cluster

Before starting, please prepare a clean directory as the workspace for Amoro Demo deployment, and obtain the Amoro demo deployment script:


Execute the following shell command to launch a demo cluster using docker-compose:

bash start

After executing the above command, there will be a data directory in the workspace directory for sharing files between different docker containers. You can use the following command to view all the running Docker containers:

$ docker ps --format "table {{.ID}}\t{{.Names}}\t{{.Status}}"

2a0d326c668f   datanode    Up 1 minutes
8e6b1c36e6ba   namenode    Up 1 minutes
1e11fb8187b3   quickdemo   Up 1 minutes

Setup from binary release

If installing Docker and related tools is not convenient, you can also deploy the Amoro demo cluster directly through the Amoro release package.


Before starting, please make sure that Java 8 is installed and the JAVA_HOME environment variable is set. Please make sure that HADOOP_HOME or HADOOP_CONF_DIR is not in the environment variables. If it is, please unset it first.

Setup AMS

Prepare a clean directory as the workspace for the Amoro demo cluster, and execute the following command to download Amoro and start AMS:


# Rplace version value with the latest Amoro version if needed
export AMORO_VERSION=0.6.0

# Download the binary package of AMS

# Unzip the package
unzip amoro-${AMORO_VERSION}

# Start AMS by script
cd amoro-${AMORO_VERSION} && ./bin/ start

Access with a browser and log in to the system with admin/admin. If you can log in successfully, the deployment of AMS is successful.

Before starting the Quick Demo, you must also deploy the Flink execution environment. Execute the following command to download the Flink binary distribution package:


# Rplace version value with the latest Amoro version if needed

# Download FLink binary package
wget ${APACHE_FLINK_URL}/flink-${FLINK_VERSION}/flink-${FLINK_VERSION}-bin-scala_2.12.tgz
# Unzip Flink binary package
tar -zxvf flink-${FLINK_VERSION}-bin-scala_2.12.tgz

cd flink-${FLINK_VERSION}
# Download Flink Hadoop dependency
wget ${FLINK_CONNECTOR_URL}/flink-shaded-hadoop-2-uber/${FLINK_HADOOP_SHADE_VERSION}-10.0/flink-shaded-hadoop-2-uber-${FLINK_HADOOP_SHADE_VERSION}-10.0.jar
# Download Flink Aoro Connector
wget ${AMORO_CONNECTOR_URL}/amoro-flink-runtime-${FLINK_MAJOR_VERSION}/${AMORO_VERSION}/amoro-flink-runtime-${FLINK_MAJOR_VERSION}-${AMORO_VERSION}.jar
# Download Flink Iceberg Connector

# Copy the necessary JAR files to the lib directory
mv flink-shaded-hadoop-2-uber-${FLINK_HADOOP_SHADE_VERSION}-10.0.jar lib
mv amoro-flink-runtime-${FLINK_MAJOR_VERSION}-${AMORO_VERSION}.jar lib
mv iceberg-flink-runtime-${FLINK_MAJOR_VERSION}-${ICEBERG_VERSION}.jar lib
cp examples/table/ChangelogSocketExample.jar lib

Finally, you must modify the flink-conf.yaml configuration file.

vim conf/flink-conf.yaml

# Increase the number of slots to run more streaming tasks
taskmanager.numberOfTaskSlots: 4

# Enable checkpointing and to see data changes more quickly, set the checkpoint interval to 5 seconds.
execution.checkpointing.interval: 5s