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https://issues.apache.org/jira/browse/SPARK-5992?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15159679#comment-15159679
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Karl Higley commented on SPARK-5992:
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I've been working on [a Spark package for approximate nearest
neighbors|https://github.com/karlhigley/spark-neighbors] that implements
several LSH flavors for different distance measures behind a unified interface.
Currently, the package supports Hamming, Jaccard, Euclidean, and cosine
distance. It's still a work in progress, but maybe it will provide some food
for thought on how to proceed with the implementation for MLlib.
> Locality Sensitive Hashing (LSH) for MLlib
> ------------------------------------------
>
> Key: SPARK-5992
> URL: https://issues.apache.org/jira/browse/SPARK-5992
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Reporter: Joseph K. Bradley
>
> Locality Sensitive Hashing (LSH) would be very useful for ML. It would be
> great to discuss some possible algorithms here, choose an API, and make a PR
> for an initial algorithm.
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