Probabilistic data structures for processing and searching very large datasets
Project description
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 |
---|---|
estimate Jaccard similarity and cardinality |
|
estimate weighted Jaccard similarity |
|
estimate cardinality |
|
estimate cardinality |
The following indexes for data sketches are provided to support sub-linear query time:
Index |
For Data Sketch |
Supported Query Type |
---|---|---|
MinHash, Weighted MinHash |
Jaccard Threshold |
|
MinHash, Weighted MinHash |
Jaccard Top-K |
|
MinHash |
Containment Threshold |
|
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]
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