AggreGate platform can store long-term time series data in a Round-Robin Database (RRD). The module responsible for collecting, storing and processing time-series data is called Statistical Process Control module, or simply Statistics.
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Round Robin Database (RRD) aims to handle time-series data like network bandwidth, temperatures, CPU load etc. The data are stored in an circular buffer, thus the system storage footprint remains constant over time. See RRD Technology article for more information. |
The RRD database has two important benefits for storing long term statistical data:
| • | Small and constant database size |
| • | Extremely fast access to the historical data for any time period |
Statistics Channels
In AggreGate, RRD-based statistical data is presented by named Statistics Channels. Each channel processes value of one context variable. However, since channel Primary Data Points are calculated by expressions, channel source values may be based upon any data flowing inside the system.
Each channel defines:
| • | Expression used to determine values of Primary Data Points |
| • | Storage type (file or memory) |
| • | Channel type (gauge, counter, etc.) |
| • | Active aggregation functions (average, minimum, etc.) |
| • | Storage periods for different aggregation intervals (hourly, daily, etc.) |
| • | And other options |
Use of Statistics
Currently, the following AggreGate data processing facilities allow to use statistics:
| • | Devices. One or more channels may be created to keep history of every device setting variable. |
| • | Trackers. Each tracker has a pre-created statistical channel to keep changes history. |
For more information see:
Channel Elements
Each statistical channel consists of the following elements:
| • | Datasets. Datasets allow to store multiple sets of statistics for one context variable. Simple variables match one dataset, while each row in a tabular variable may be identified by an unique key to form a named Dataset. See Working With Keys for details. |