It's easy to realize data visualization without writing code. This artifact based on SpringBoot is amazing!

Posted by desmond_ckl on Mon, 03 Jan 2022 03:20:30 +0100

Before, a reader asked me if I have any useful BI (Business Intelligence) tools? BI tools are simply a data visualization tool. Today, I recommend an open-source data visualization tool DataEase, which is implemented based on SpringBoot and integrated with Apache Doris + Kettle. It can support second level queries with large data volume. I hope it will be helpful to you!

brief introduction

DataEase is an open source data visualization and analysis tool known to be available to everyone. There is already 4.1K+Star on Github. Committed to helping users quickly analyze data and insight into business trends, so as to achieve business improvement and optimization. DataEase supports rich data source connections, and can quickly make charts by dragging and dropping, and share them with others.

The following is a large visual screen generated by DataEase, which is still very cool.


As a data visualization tool, DataEase uses the popular big data technologies Apache Doris and Kettle. If you want to learn these two technologies, this project is a good choice.

system architecture

The technology stack used by DataEase is as follows:




Back end infrastructure


data storage

Apache Doris

A modern MPP analytical database product. Query results can be obtained with sub second response time, which effectively supports real-time data analysis.


An open source ETL (i.e. the process of data extraction, conversion and loading) tool, written in pure Java, can achieve efficient and stable data extraction.


Container deployment


Front end foundation frame


Front end UI framework

The usage scenarios of various technologies in DataEase are as follows:

Functional architecture

The following is the functional architecture diagram of DataEase, from which we can easily see what we can do with DataEase.


DataEase provides the installation package. Download the installation package and use the installation script install SH to complete the installation. If your server has MySQL installed, you need some additional configuration.

  • First of all, we need to download the installation package. V1.0 is used here Version 5.2, download address:
  • After downloading, upload it to the Linux server and unzip it to the specified directory with the following command;
tar -zxvf dataease-v1.5.2-online.tar.gz
  • After decompression, the directory structure is as follows. Note that there is docker compose deployment script under the dataease folder;
  • Next, modify the installation configuration install Conf, which mainly modifies the service running port DE_PORT and MySQL configuration;
# Basic configuration
## Installation directory
## Service port (default 80, probable conflict rate)

# Database configuration
## Use external database
## Database address (the default is mysql. If you have installed MySQL with docker before, it is recommended to modify it)
## Database port (3306 by default. If you have installed mysql with docker before, it is recommended to modify it)
## DataEase database library name
## Database user name
## Database password
  • Modify the docker compose file of DataEase to DataEase / docker compose YML, modify the MySQL dependency name and network configuration. The default network configuration may cause conflicts;

    container_name: dataease
      - ${DE_PORT}:8081
    mem_limit: 4096m
      - ${DE_BASE}/dataease/conf:/opt/dataease/conf
      - ${DE_BASE}/dataease/logs:/opt/dataease/logs
      - ${DE_BASE}/dataease/plugins/thirdpart:/opt/dataease/plugins/thirdpart
      - ${DE_BASE}/dataease/data/kettle:/opt/dataease/data/kettle
      # If you have previously installed mysql using Docker, modify the name
        condition: service_healthy
      - dataease-network

    driver: bridge
      driver: default
      # The default network segment configuration may conflict. It is recommended to modify it
        - subnet:
  • Modify Doris's docker compose file to dataease / docker compose kettle Doris YML, which mainly modifies the network configuration;
version: '2.1'

    container_name: doris-fe
      # Change to 33 network segments to prevent conflicts
      dataease-network :
    restart: always

      # Change to 33 network segments to prevent conflicts
      dataease-network :
    restart: always
  • Modify the docker compose file of MySQL to dataease / docker compose MySQL YML, just modify the container name;
version: '2.1'

    # You have previously installed mysql using Docker, and you need to modify the container name
    container_name: mysql-de
      - ${DE_BASE}/dataease/conf/mysql.env
      - ${DE_MYSQL_PORT}:3306
      - ${DE_BASE}/dataease/conf/my.cnf:/etc/mysql/conf.d/my.cnf
      - ${DE_BASE}/dataease/bin/mysql:/docker-entrypoint-initdb.d/
      - ${DE_BASE}/dataease/data/mysql:/var/lib/mysql
      - dataease-network
  • If you enable firewall, you should also open port 8010;
firewall-cmd --zone=public --add-port=8010/tcp --permanent
firewall-cmd --reload
  • When everything is ready, run install. In the installation directory directly SH file for installation;
  • The installation process involves downloading the image, which takes a long time and needs to wait patiently. After the final installation is successful, it is displayed as follows;
➜  dataease-v1.5.2-online ./ 

Stopping doris-fe ... done
Stopping doris-be ... done
Stopping kettle   ... done
Removing doris-fe ... done
Removing doris-be ... done
Removing kettle   ... done
Removing network dataease_dataease-network
======================= Start installation =======================
[DATAEASE Log]: Copy profile template file  -> /opt/dataease/conf 
[DATAEASE Log]: Adjust the configuration file according to the installation configuration parameters 
time: Wed Dec 22 10:59:39 CST 2021
[DATAEASE Log]: Detected Docker Installed, skipping installation steps 
[DATAEASE Log]: start-up Docker  
Redirecting to /bin/systemctl start docker.service
[DATAEASE Log]: Detected Docker Compose Installed, skipping installation steps 
[DATAEASE Log]: Pull image 
Pulling doris-be ... done
Pulling kettle   ... done
Pulling mysql-de ... done
Pulling dataease ... done
Pulling doris-fe ... done
...Omit several logs
  Name                Command                       State                         Ports              
dataease   /deployments/         Up (health: starting)>8081/tcp           
doris-be   /                   Up (healthy)                                             
doris-fe   /                   Up (health: starting)                                    
kettle     /opt/kettle/ kettl ...   Up                                                       
mysql-de mysqld      Up (healthy)  >3306/tcp, 33060/tcp
[DATAEASE Log]: Please wait while the service starts ... 
[DATAEASE Log]: Please wait while the service starts ... 
[DATAEASE Log]: [Warning] the service is not fully started within the waiting time! Please use later dectl status Check service health. 
======================= installation is complete =======================

Please visit:
 URL: http://$LOCAL_IP:8010
 user name: admin
 Initial password: dataease
  • Since we have modified the MySQL configuration, we also need to modify the MySQL connection configuration under the installation directory / opt. The file path is / opt / dataease / conf / dataease Properties, changed to MySQL de;
# Database configuration
  • Then restart the dataease container;
docker restart dataease
  • When restarting, use docker logs -f dataease to view the log. The project is started successfully only after the database import is completed;
  • Since DateEase will automatically register the dataease service in the system after successful installation, we can use the following command to operate it.
# View service status
systemctl status dataease
# Start service
systemctl start dataease
# Out of Service
systemctl stop dataease


Data visualization can be easily realized by using DataEase. Next, let's take the data in Excel and MySQL as examples to experience its functions.

Basic concepts

Before using DataEase, we have to understand some of its basic concepts, which will be very helpful to use it.

  • Data source: it is the data source for subsequent data analysis. It refers to various database connection information and supports common data sources such as MySQL, Elasticsearch and MongoDB;
  • Dataset: a collection of data, including Excel data, database table data, and custom SQL query data. It is the data source of the view;
  • View: the smallest unit of visual display, which is the basic element of the dashboard. It can be line chart, bar chart, pie chart, etc;
  • Dashboard: large visual screen, view combination interface;
  • Template: data and style templates that can be used to quickly build dashboards.

Excel data analysis

Next, we will get data from Excel and implement the dashboard to experience the data visualization function of DataEase.

  • After DataEase is started successfully, you can log in with the account admin:dataease at:
  • Since we have previously modified the name of MySQL container, we also need to modify the data source here;
  • Next, we need to create a data set and use the official sample Excel. After downloading, you can open and have a look at a commodity sales report. The download address is:
  • Then select Add dataset;
  • Upload Excel when creating a new one, and finally select OK to import;
  • Due to the previous modification of Doris's network segment, the imported Excel data will not be displayed, and the following error prompt will pop up;
  • Enter the MySQL de container and enter the following command to solve the problem;
# Enter the built-in MySQL container
docker exec -it mysql-de sh
# After entering the MySQL container, connect Doris Fe
mysql -uroot -h doris-fe -P 9030
# Because the network segment of doris is modified, it should also be modified here
SET PASSWORD FOR 'root' = PASSWORD('Password123@doris');
  • After the data is imported successfully, you can start to create a view and select the dataset we just imported;
  • Then select the type of view. Here, select the pie chart representing the distribution;
  • Drag and select dimensions and indicators, then change the style, and finally save to complete a view;
  • Create a few more views, and then you can create a dashboard. By dragging and editing, the dashboard is completed. Isn't it very convenient!

Database data analysis

Of course, DataEase also supports importing data from the database and even customizing SQL queries. Let's experience these functions.

  • First, we have to create a new data source. You can select various types of data sources. There are many supports. Here, choose MySQL;
  • Then create a dataset and select Add dataset from database;
  • Then create a view and use the dataset created above;
  • Of course, you can also customize SQL queries to add data sets;
  • DataEase also has a powerful function. You can set each view to be linked directly according to a field. For example, in the official example, if we select a province, the data of other views will become the data of this province;
  • Another interesting function is drill down. For example, if we select a province to drill down, we can view the relevant data of cities in that province.


In general, DataEase is a very good data visualization tool. It allows us to easily realize some data visualization requirements without writing code, and supports the analysis of data from various data sources and Excel. And it uses the popular big data analysis technologies Apache Doris and Kettle. Friends interested in these technologies can also try it.

reference material

  • Project address:
  • Official documents: