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https://github.com/ekzhu/datasketch
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
https://github.com/ekzhu/datasketch
data-sketches data-summary hnsw hyperloglog jaccard-similarity locality-sensitive-hashing lsh lsh-ensemble lsh-forest minhash python search top-k weighted-quantiles
Last synced: 10 days ago
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MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble and HNSW
- Host: GitHub
- URL: https://github.com/ekzhu/datasketch
- Owner: ekzhu
- License: mit
- Created: 2015-03-20T01:21:46.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2024-06-04T00:43:43.000Z (5 months ago)
- Last Synced: 2024-10-16T14:05:51.624Z (23 days ago)
- Topics: data-sketches, data-summary, hnsw, hyperloglog, jaccard-similarity, locality-sensitive-hashing, lsh, lsh-ensemble, lsh-forest, minhash, python, search, top-k, weighted-quantiles
- Language: Python
- Homepage: https://ekzhu.github.io/datasketch
- Size: 5.68 MB
- Stars: 2,539
- Watchers: 48
- Forks: 293
- Open Issues: 53
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
- best-of-python - GitHub - 30% open · ⏱️ 26.03.2024): (Data Containers & Dataframes)
- awesome-list - datasketch - Gives you probabilistic data structures that can process and search very large amount of data super fast, with little loss of accuracy. (Data Processing / Data Management)
- awesome-python-machine-learning-resources - GitHub - 25% open · ⏱️ 19.08.2022): (数据容器和结构)
README
datasketch: Big Data Looks Small
================================
.. image:: https://static.pepy.tech/badge/datasketch/month
:target: https://pepy.tech/project/datasketch
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.598238.svg
:target: https://zenodo.org/doi/10.5281/zenodo.598238
datasketch gives you probabilistic data structures that can process and
search very large amount of data super fast, with little loss of
accuracy.
This package contains the following data sketches:
+-------------------------+-----------------------------------------------+
| Data Sketch | Usage |
+=========================+===============================================+
| `MinHash`_ | estimate Jaccard similarity and cardinality |
+-------------------------+-----------------------------------------------+
| `Weighted MinHash`_ | estimate weighted Jaccard similarity |
+-------------------------+-----------------------------------------------+
| `HyperLogLog`_ | estimate cardinality |
+-------------------------+-----------------------------------------------+
| `HyperLogLog++`_ | estimate cardinality |
+-------------------------+-----------------------------------------------+
The following indexes for data sketches are provided to support
sub-linear query time:
+---------------------------+-----------------------------+------------------------+
| Index | For Data Sketch | Supported Query Type |
+===========================+=============================+========================+
| `MinHash LSH`_ | MinHash, Weighted MinHash | Jaccard Threshold |
+---------------------------+-----------------------------+------------------------+
| `MinHash LSH Forest`_ | MinHash, Weighted MinHash | Jaccard Top-K |
+---------------------------+-----------------------------+------------------------+
| `MinHash LSH Ensemble`_ | MinHash | Containment Threshold |
+---------------------------+-----------------------------+------------------------+
| `HNSW`_ | Any | Custom Metric Top-K |
+---------------------------+-----------------------------+------------------------+
datasketch must be used with Python 3.7 or above, NumPy 1.11 or above, and Scipy.
Note that `MinHash LSH`_ and `MinHash LSH Ensemble`_ also support Redis and Cassandra
storage layer (see `MinHash LSH at Scale`_).
Install
-------
To install datasketch using ``pip``:
::
pip install datasketch
This will also install NumPy as dependency.
To install with Redis dependency:
::
pip install datasketch[redis]
To install with Cassandra dependency:
::
pip install datasketch[cassandra]
.. _`MinHash`: https://ekzhu.github.io/datasketch/minhash.html
.. _`Weighted MinHash`: https://ekzhu.github.io/datasketch/weightedminhash.html
.. _`HyperLogLog`: https://ekzhu.github.io/datasketch/hyperloglog.html
.. _`HyperLogLog++`: https://ekzhu.github.io/datasketch/hyperloglog.html#hyperloglog-plusplus
.. _`MinHash LSH`: https://ekzhu.github.io/datasketch/lsh.html
.. _`MinHash LSH Forest`: https://ekzhu.github.io/datasketch/lshforest.html
.. _`MinHash LSH Ensemble`: https://ekzhu.github.io/datasketch/lshensemble.html
.. _`Minhash LSH at Scale`: http://ekzhu.github.io/datasketch/lsh.html#minhash-lsh-at-scale
.. _`HNSW`: https://ekzhu.github.io/datasketch/documentation.html#hnsw