| Quantiles Sketches |
| ================== |
| |
| Quantile estimation is useful for understanding the distribution of data values in a stream. The sketches currently |
| in the library are designed to answer queries about the `rank` of an item in the stream of items. That is, when |
| applying a global ordering on all the items, what is the portion of items seen so far that are less than (alternatively, |
| less-than-or-equal-to) the given item. Using straightforward logic, they can also estimate the item at a given rank |
| in the stream. |
| |
| These sketches may be used to compute approximate histograms, Probability Mass Functions (PMFs), or |
| Cumulative Distribution Functions (CDFs). |
| |
| The library provides three types of quantiles sketches, each of which has generic items as well as versions |
| specific to a given numeric type (e.g. integer or floating point values). All three types provide error |
| bounds on rank estimation with proven probabilistic error distributions. |
| |
| * KLL: Provides uniform rank estimation error over the entire range |
| * REQ: Provides relative rank error estimates, which decreases approaching either the high or low end values. |
| * Classic quantiles: Largely deprecated in favor of KLL, also provides uniform rank estimation error. Included largely for backwards compatibility with historic data. |
| |
| .. toctree:: |
| :maxdepth: 1 |
| |
| kll |
| req |
| quantiles_depr |
