Chapter 5. Communicating with the Cascade DataHub

Table of Contents

5.1. Exceptions
5.2. Echoes
5.3. Non-Existent Cascade DataHub Points
5.4. Parsing Point Messages
5.5. Optimizing Throughput
5.6. Point Size Limit
5.7. Cascade DataHub API Code Examples
5.7.1. Reading from the Cascade DataHub
5.7.2. Writing data to the Cascade DataHub
5.7.3. Registering for exceptions from the Cascade DataHub
5.7.4. A sample makefile definition

The Cascade DataHub contains a snapshot of the current values of all of its points. A point is essentially a name and an associated value, along with auxiliary information such as time stamp, security and lock status. The following functions provide access to the Cascade DataHub through the Cascade DataHub IPC functions (IP_*).

The Cascade DataHub provides three basic data services:

5.1. Exceptions

The Cascade DataHub is designed using the exception paradigm of point value transmission. That is, a client task can tell the DataHub that it would like to be informed whenever a value changes on one or more points, and then it simply waits for the DataHub to transmit the changes. This mechanism generally results in less network traffic and substantially reduced delays compared with the more popular polling method of DataHub query. The Cascade DataHub automatically concatenates point messages to be sent to a client if more than one exception occurs before a message is sent out.