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MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++

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datasketch: Big Data Looks Small

https://travis-ci.org/ekzhu/datasketch.svg?branch=master

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 also supports a Redis storage layer as well as an experimental module with asynchronous interface to MongoDB.

Install

To install datasketch using pip:

pip install datasketch -U

This will also install NumPy as dependency.

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MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++

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