Accessing COSMOS Data

The majority of data crawled by our team is stored on various MySQL databases on our servers. To access it from your home computer you will need to follow these steps:

1. (If outside campus) Setup UALR VPN
   1. Our servers are only accessible from within the UALR network. For this reason you must first setup a VPN connection to reach this network if you are connecting from home. Follow the official UALR instructions here: Application: Virtual private networking (VPN)
2. Install your preferred DB tool. We recommend MySQL Workbench, it is the standard in the lab and we will be able to help you better if you use it. Follow Oracle’s official installation instructions here (for Windows): MySQL :: MySQL Workbench Manual :: 2.3.1 Installing. See MySQL :: MySQL Workbench Manual :: 2 Installation for other operating systems.
3. Create a stored connection. From MySQL Workbench, you can store credential logins to access various databases.

Click on the “+” icon in the dashboard to open the new connection setup window:

This window will look like the following. “Connection Name” can be any recognizable name. I recommend calling it after the DB you are accessing. Fill the remaining two highlighted fields with the login credentials provided to you and leave the remaining fields as is. You should have been provided with a username. Once you try to access the database you will be prompted to enter your password.

For example, this is my connection for Cosmos-DB (note the hostname can be an IP address or an alias like below)

4. You are ready to access the schemas. You may see this sidebar upon first connecting.

You can click on “Users and Privileges” to enter your own password instead of the default.

Clicking on “Schemas” at the bottom will take you to the data. Simply double click on the desired database and start querying.

5. Exporting Here, I am using the “twitter” schema and selected some posts from the posts table. Click on the highlighted button to export the result set to a local file ready for analysis. Keep in mind that very large datasets (multiple gigabytes) will strain both MySQL Workbench and most likely your analysis tool (especially Excel). If you must select a large set, try selecting and exporting it in chunks.