BigObject uses docker as the primary delivery method. Docker allows BigOjbect applications to be shipped and updated in a standardized environment independent of the user's platform.
To download and install Docker, please visit https://docs.docker.com/engine/installation/
For non-Linux users, please visit following site to download and install Docker Toolbox.
Once docker is installed, the user can use following steps to setup BigObject:
Step 1: Pull BigObject demo version image for Docker.
docker pull bigobject/bigobject:demo
Step 2: Create and start a Docker container (with demo version or actual user data situation)
To run with demo version / pre-built-in data:
docker run -t -d --name bigobject -p 9090:9090 -p 9091:9091 -p 3306:3306 bigobject/bigobject:demo
Actual run with user's own data by mounting user data directory:
docker run -t -d --name bigobject -p 9090:9090 -p 9091:9091 -p 3306:3306 -v user_data_directory:/data bigobject/bigobject
Actual run with user's own data by mounting user data directory and input data directory:
docker run -t -d --name bigobject -p 9090:9090 -p 9091:9091 -p 3306:3306 -v user_data_directory:/data -v user_csv_directory:/bofile bigobject/bigobject
1. For the first time user, it is recommended to run the demo version first in order to gain better understanding from this tutorial. 2. user_data_directory refers to the data directory user placed his data. (example: /home/user/data) 3. user_csv_directory refers to the intended import data (i.e. csv files) user placed. (example: /home/user/csv) 4. For more on mounting, please refer to Mount User Directory section below.
Step 3: Open the browser and locate BigObject application
For Linux platform, the user can go to below address after opening up the browser:
For non-Linux / Docker Toolbox user, please find out the address to connect with following command in Docker shell:
docker-machine ip default (It's likely to be 192.168.99.100)
Then open the browser at
Step 4: Go to "BigObject shell" tab to start exploring the solution.