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https://issues.apache.org/jira/browse/SPARK-23266?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16389061#comment-16389061
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Chandan Misra commented on SPARK-23266:
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I have implemented matrix inversion using Spark version 2.2.0. Though the
implementation can be executed using Spark version 2.0.0 onwards. It would be
really helpful if the inversion is added in the next Spark version. As already
mentioned, I have the implementation of the inversion and happy to contribute.
> Matrix Inversion on BlockMatrix
> -------------------------------
>
> Key: SPARK-23266
> URL: https://issues.apache.org/jira/browse/SPARK-23266
> Project: Spark
> Issue Type: New Feature
> Components: MLlib
> Affects Versions: 2.2.1
> Reporter: Chandan Misra
> Priority: Minor
>
> Matrix inversion is the basic building block for many other algorithms like
> regression, classification, geostatistical analysis using ordinary kriging
> etc. A simple Spark BlockMatrix based efficient distributed
> divide-and-conquer algorithm can be implemented using only *6*
> multiplications in each recursion level of the algorithm. The reference paper
> can be found in
> [https://arxiv.org/abs/1801.04723]
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