| Exact and Bounded, Probabilitiy Proportional to Size (EBPPS) Sampling |
| --------------------------------------------------------------------- |
| |
| .. currentmodule:: datasketches |
| |
| An EBPPS sketch produces a randome sample of data from a stream of items, ensuring that the probability |
| of including an item is always exactly equal to the item's size. The size of an item is defined as its |
| weight relative to the total weight of all items seen so far by the sketch. In contrast to VarOpt sampling, |
| this sketch may return fewer than `k` items in order to keep the probability of including an item strictly |
| proportional to its size. |
| |
| This sketch is based on: B. Hentschel, P. J. Haas, Y. Tian |
| "Exact PPS Sampling with Bounded Sample Size", |
| Information Processing Letters, 2023. |
| |
| EBPPS sampling is related to reservoir sampling, but handles unequal item weights. |
| Feeding the sketch items with a uniform weight value will produce a sample equivalent to reservoir sampling. |
| |
| .. note:: |
| Serializing and deserializing this sketch requires the use of a :class:`PyObjectSerDe`. |
| |
| .. autoclass:: ebpps_sketch |
| :members: |
| :undoc-members: |
| :exclude-members: deserialize |
| |
| .. rubric:: Static Methods: |
| |
| .. automethod:: deserialize |
| |
| .. rubric:: Non-static Methods: |
| |
| .. automethod:: __init__ |
