Skip to content

Commit

Permalink
document quotient filter
Browse files Browse the repository at this point in the history
  • Loading branch information
barrust committed Jan 4, 2024
1 parent 581d8f3 commit ac627c7
Showing 1 changed file with 35 additions and 0 deletions.
35 changes: 35 additions & 0 deletions docs/source/code.rst
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@ operations. Bloom Filters guarantee a zero percent false negative rate
and a predetermined false positive rate. Once the number of elements inserted
exceeds the estimated elements, the false positive rate will increase over the
desired amount.

`Further Reading <https://en.wikipedia.org/wiki/Bloom_filter>`__


Expand Down Expand Up @@ -69,6 +70,7 @@ membership testing. Cuckoo filters support insertion, deletion, and lookup of
elements with low overhead and few false positive results. The name is derived
from the `cuckoo hashing <https://en.wikipedia.org/wiki/Cuckoo_hashing>`__
strategy used to resolve conflicts.

`Further Reading <https://www.cs.cmu.edu/~dga/papers/cuckoo-conext2014.pdf>`__

CuckooFilter
Expand All @@ -92,6 +94,7 @@ data elements. The result is a probabilistic count of elements inserted into
the data structure. It will always provide the **maximum** number of times a
data element was encountered. Notice that the result may be **more** than the
true number of times it was inserted, but never fewer.

`Further Reading <https://en.wikipedia.org/wiki/Count%E2%80%93min_sketch>`__


Expand Down Expand Up @@ -137,6 +140,38 @@ StreamThreshold

For more information of all methods and properties, see `CountMinSketch`_.

QuotientFilter
------------------

Quotient filters are an aproximate membership query filter (AMQ) that is both
space efficient and returns a zero false negative rate and a probablistic false
positive rate. Unlike Bloom filters, the quotient filter only requires a single
hash of the element to insert. The upper **q** bits denote the location within the
filter while the lower **r** bits are stored in the filter.

Quotient filters provide some useful benifits over Bloom filters including:

* Merging of two filters (not union)
* Resizing of the filter
* Ability to remove elements

`Further Reading <https://en.wikipedia.org/wiki/Quotient_filter>`__

QuotientFilter
+++++++++++++++++++++++++++++++

.. autoclass:: probables.QuotientFilter
:members:


Utilities
------------------

Bitarray
+++++++++++++++++++++++++++++++

.. autoclass:: probables.utilities.Bitarray
:members:

Exceptions
============================
Expand Down

0 comments on commit ac627c7

Please sign in to comment.