5.4. Incorporating the Cascade DataHub

Start the Cascade DataHub by typing the following command at the command prompt:

    [sh]$ datahub

For a basic view of the data, you can use the waiter command from a terminal on the data server, or from a telnet session in Windows. We will use it on the data server for now:

    [sh]$ waiter

The waiter registers for points on the database, and then blocks waiting for points to be written to the Cascade DataHub. When the Cascade DataHub receives a new value for a point, the waiter prints the data to the screen in this format:

    Point: output1
    Value: 55
    Conf:  100, Lock: no, Time: Thu Nov  1 2001 18:10:48.000, Security: 0

The waiter is useful for simple tests, but you can get a more sophisticated, easier-to-read view of the data by using the Cascade DataHub Viewer, which is called using dhview (for console mode), phdhview (for Photon), or xdhview (for X Windows). The Cascade DataHub Viewer is only available on the data server, though, whereas the waiter can be accessed from Windows. In this tutorial we run the waiter and the Cascade DataHub Viewer simultaneously on the data server.

Open a new terminal and start dhview by typing its name at the prompt:

    [sh]$ dhview

The terminal screen will change to look like this (except with your data):

Please refer to the Using the Cascade DataHub Viewer section of the Cascade DataHub manual for details on how to use the viewer.

Shut down Cascade Connect if it is running. (It has to be restarted so it can find the Cascade DataHub.)

Start Cascade Connect by double clicking on the Excel Test icon.

In Excel, type a number in the output1 cell, press Enter, and click the Send button.

On the data server, you should see the new point value and other information displayed by waiter and in the Cascade DataHub Viewer.

From a terminal on the data server, enter the following command:

    [sh]$ writept input1 99

The writept command writes values to points in the Cascade DataHub. In Excel, you should see the new value appear in the input1 cell.

Also from the data server, try entering:

    [sh]$ demowrite 500

If you watch both the text.xls spreadsheet and the Cascade DataHub Viewer simultaneously, you will notice that the information updates much faster in the Cascade DataHub than in Excel. Again, this is due to the inability of Excel to handle large volumes of incoming data quickly. Cascade Connect transmits the data at just about the same rate as it gets written to the Cascade DataHub.