Rustics

A minimal statistics library for performance monitoring

Rustics implements a simple set of statistics objects intended primarily for measuring performance parameters. It provides statistics objects that collect data and compute various statistical characterizations of the data, such as the mean and variance.

The testing modules for arc_sets.rs and rc_sets.rs contain very simple example routines called "sample_usage".

At this time, statistics can be gathered for i64 values and for time values. They can be collected as a running total of all samples recorded, or as a window covering the last N events, for a programmable N. The interface does support a "clear" function to discard all gather statistics. See the time.rs file for information on timers and to see some sample implementations.

In addition to the more detailed, the library supports a simple counter for which no other statistics are generated. This can be useful for counting events.

This library also implements a form of hierarchical statistics. Such structures can provide multiple levels of statistics to help reduce loss of information for long-running programs. See the hier.rs file and documentation for more information.

This library also implements sets, which contain statistics that are printed and manipulated together. It provides sets contained in Arc structures and Rc structures. The two set modules are otherwise identical. The implementations are simple and will not scale to handle a single set with a very large number of elements.

Sets are recursive: a set can have a set as a member. A set hierarchy can be printed with a single procedure call, and the contained statistics object can be cleared in the same way. The set implementation automatically creates hierarchical names for objects. Each set or statistic typically will have a single element name given by the user, and the string "==>" will be used to create a hierarchical name in the manner of a Unix filesystem by concatenating the names as the print process descends the tree. For example, if a tree has one set named "Everything" and that set contains one statistics object named "Lonely", the title printed will be "Everything ==> Lonely".

Statistics and sets can be deleted, but the code uses simple algorithms that are linear in the number of elements of the parent set, so sets with a very high number of subsets or statistics can require a long time to process a deletion.