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https://issues.apache.org/jira/browse/SPARK-4823?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Debasish Das updated SPARK-4823:
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Attachment: MovieLensSimilarity Comparisons.pdf
The attached file shows the runtime comparison of row and column based flow on
all items from MovieLens dataset on my local Macbook with 8 cores, 1 GB driver,
4 GB executor memory.
1e-2 is the threshold that's being set to both row based kernel flow and column
based dimsum flow.
Stage 24 - 35 is the row similarity flow. Total runtime ~ 20 s
Stage 64 is col similarity mapPartitions. Total runtime ~ 4.6 mins
This shows the power of blocking in Spark and I have not yet gone to gemv which
will decrease the runtime further.
I updated the driver code in examples.mllib.MovieLensSimilarity
> rowSimilarities
> ---------------
>
> Key: SPARK-4823
> URL: https://issues.apache.org/jira/browse/SPARK-4823
> Project: Spark
> Issue Type: Improvement
> Components: MLlib
> Reporter: Reza Zadeh
> Attachments: MovieLensSimilarity Comparisons.pdf
>
>
> RowMatrix has a columnSimilarities method to find cosine similarities between
> columns.
> A rowSimilarities method would be useful to find similarities between rows.
> This is JIRA is to investigate which algorithms are suitable for such a
> method, better than brute-forcing it. Note that when there are many rows (>
> 10^6), it is unlikely that brute-force will be feasible, since the output
> will be of order 10^12.
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