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(datasketch: Big Data Looks Small
.. image:: https://travis-ci.org/ekzhu/datasketch.svg?branch=master
:target: https://travis-ci.org/ekzhu/datasketch
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.290602.svg
:target: https://doi.org/10.5281/zenodo.290602
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, +---------------------------+-----------------------------+------------------------+
datasketch must be used with Python 2.7 or above and NumPy 1.11 or
above. Scipy is optional, but with it the LSH initialization can be much
faster.
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]
To install with Scipy for faster MinHashLSH initialization:
::
pip install datasketch[scipy]
.. _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