Python library implementing a subset of streaming algorithms. Includes variations of these algorithms (e.g. adversarially robust), as well as support for multiple data types.
pip install sublinear
Here is the list of the currently implemented streaming algorithms.
-
BJKST Sketch (basic, plus, adversarially robust) [1]
-
HyperLogLog [2]
- Morris (basic, plus, plus plus) [3][4]
- AMS Sketch (basic, plus, plus plus) [5]
- Count Min Sketch [6]
- Misra-Gries Sketch [7]
- K Independent Hash Function [8]
[1] Bar-Yossef, Ziv, et al. "Counting distinct elements in a data stream." Randomization and Approximation Techniques in Computer Science. Springer Berlin Heidelberg, 2002.
[2] Flajolet, Philippe, et al. "HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm." Conference on Analysis of Algorithms. Springer Berlin Heidelberg, 2007.
[3] Morris, R. "Counting large numbers of events in small registers". Communications of the ACM 21, 10, 1978.
[4] Flajolet, P. "Approximate Counting: A Detailed Analysis". BIT 25, 1985.
[5] Noga Alon, Yossi Matias, Mario Szegedy, "The Space Complexity of Approximating the Frequency Moments". Journal of Computer and System Sciences, Volume 58, Issue 1, 1999.
[6] Cormode, Graham; S. Muthukrishnan. "An Improved Data Stream Summary: The Count-Min Sketch and its Applications". 2005.
[7] Misra, J.; Gries, David. "Finding repeated elements". Science of Computer Programming. 1982
[8] Wegman, Mark N., et al. "New Hash Functions and Their Use in Authentication and Set Equality". Journal of Computer and System Sciences. 1981.