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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2017/01/28 00:21:24 UTC

[jira] [Updated] (SPARK-19247) Improve ml word2vec save/load scalability

     [ https://issues.apache.org/jira/browse/SPARK-19247?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joseph K. Bradley updated SPARK-19247:
--------------------------------------
    Issue Type: Improvement  (was: Bug)

> Improve ml word2vec save/load scalability
> -----------------------------------------
>
>                 Key: SPARK-19247
>                 URL: https://issues.apache.org/jira/browse/SPARK-19247
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>            Reporter: Asher Krim
>
> ml word2vec models can be somewhat large (~4gb is not uncommon). The current save implementation saves the model as a single large datum, which can cause rpc issues and fail to save the model.
> On the loading side, there are issues with loading this large datum as well. This was already solved for mllib word2vec in https://issues.apache.org/jira/browse/SPARK-11994, but the change was never ported to the ml word2vec implementation.



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