> For the complete documentation index, see [llms.txt](https://docs.bdb.ai/7.6/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bdb.ai/7.6/core-platform/platform-administration/admin-panel-options/configurations/data-science-servers.md).
# Data Science Servers
This section explains server settings for various data science workspaces for the Data Science Workbench plugin of the platform.
* Click the ***Data Science Servers*** option from the list of ***Configurations*** admin options.
* Various Data Science Servers get listed.
## **Steps to Create a New R-Server**
* Navigate to the ***Data Science Servers*** admin option.
* Click the ***R Server*** option.
* The ***R Server*** page opens.
* Click the ***Add new server*** 
icon.
* The ***Create R Server*** scrollable window opens asking basic Information for a new R Server.
* Provide the following information to configure a new R server:
* IP Address: IP address of the R-server
* Port: R-Server’s port number
* Username: Enter a username to log in to the R- server
* Password: Enter the password for the above username
* R Server Name: Provide the R- Server address
* Provide HTTP URL for R-Bokeh: Provide R Visualization URL
* Elastic Search Port: Provide an elastic search port number
* R Visualization URL: Provide HTTP URL for R-Bokeh
* Enable Parallel Processing: Avail this option by using the enable/disable button
* Set as Default: Select this option by using a checkmark in the box
* Click the ***Test*** option to verify the R-Server connection.
* A message appears to assure the connection.
* The ***Save*** option gets enabled
* Click the ***Save*** option to save the verified R-server configuration details.
* A message appears to ensure the successful updates in Data Science Settings.
* The newly created R-Server gets added to the R-Server list displayed under the ***R-Server*** window.
Note:
* The user can click the ***Edit*** 
icon from the R Servers window to modify the R Server settings.
* The user can click the ***Save*** from the R Servers window to save the edited R Server settings.
* The Administrator can configure multiple R-Servers, but the process execution happens on a single server at a time. Click the ***Delete*** 
icon to remove the selected server configuration details from the list.
## **Spark Server Settings**
Users can configure a new Spark Server or edit the existing server via the Spark Server Settings.
* Navigate to the ***Data Science Servers*** admin option.
* Click the ***Spark Server*** option.
* The ***Spark Server*** page opens.
* Click the ***Add New Server*** 
icon.
* The ***Create Spark Server*** configuration window opens.
* Provide the following information:
* ***Host***: Host address of the Spark server
* ***Port:*** Spark server’s port number
* ***Username***: Enter a username to log in to the Spark server
* ***Password***: Enter the password for the above username
* ***Spark Server Name***: Provide Spark Server Address
* ***Jetty Confirmation URL***: Provide Jetty confirmation URL link
* ***Application***: Provide the application name
* ***Spark Server Protocol***: Select a protocol option by using the radio option
* Click the ***Test*** option to verify the connection.
* A message appears to assure the connection.
* The ***Save*** option gets enabled.
* Click the ***Save*** option to save the verified Spark server configuration details.
* A confirmation message appears to ensure successful updates in the data science server settings.
* The newly configured Spark server gets added to the ***Spark Server*** page.
## **Python Server**
Users can configure the Python Application settings for the Data Science Workbench via the ***Python Server*** configuration fields.
* Navigate to the ***Data Science Servers*** admin option.
* Click the ‘**Python Server**’ option.
* The Python Server page opens.
* Click the ***Add new server***  icon to add a new Python server configuration.
* The ***Create Python Server*** configuration window opens.
* Provide the following information:
* ***Host***: Host address of the Spark server
* ***Port:*** Spark server’s port number
* ***Username***: Enter a username to log in to the Spark server
* ***Password:*** Enter the password for the above username
* ***Python Server Name:*** Provide Python Server Address
* ***Elastic Search Port:*** Provide the elastic search port number
* ***Web Socket URL***: Provide the web socket URL link
* ***Visualization URL***: Provide the Visualization URL link
* ***Python Server Protocol***: Select a protocol option by using the radio option.
* Click the ***Test*** option to verify the connection.
* A message appears to assure the connection.
* The ***Save*** option gets enabled.
* Click the ***Save*** option to save the verified Python server information.
* A success message appears to ensure that the data science settings got updated.
* The newly configured Python Server gets added to the ***Python Servers*** window.
**Note:**
* Click the ***Edit*** 
icon to modify an existing Python server configuration.
* Click the ***Delete*** 
icon to remove the selected Python server details from the list.
## **Process Queue**
Users can reset the Predictive process queue through this Predictive Settings option.
* Click the ***Process Queue*** option from the Data Science servers.
* The Process Queue page opens.
* Click the ***Reset Queue*** option.
* A warning message appears, asking whether the user wants to flush the queue.
* Click the ***YES*** option to set the count of currently running processes to Zero for the Data Science Workbench.
