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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-11994) Word2VecModel load and save cause SparkException when model is bigger than spark.kryoserializer.buffer.max
Date Sat, 28 Nov 2015 10:27:10 GMT

    [ https://issues.apache.org/jira/browse/SPARK-11994?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15030454#comment-15030454
] 

Apache Spark commented on SPARK-11994:
--------------------------------------

User 'tmnd1991' has created a pull request for this issue:
https://github.com/apache/spark/pull/9989

> Word2VecModel load and save cause SparkException when model is bigger than spark.kryoserializer.buffer.max
> ----------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-11994
>                 URL: https://issues.apache.org/jira/browse/SPARK-11994
>             Project: Spark
>          Issue Type: Bug
>          Components: MLlib
>    Affects Versions: 1.4.1, 1.5.1
>            Reporter: Antonio Murgia
>              Labels: kryo, mllib
>
> When loading a Word2VecModel of compressed size 58Mb using the Word2VecModel.load() method
introduced in Spark 1.4.0 I get a `org.apache.spark.SparkException: Kryo serialization failed:
Buffer overflow. Available: 0, required: 2` exception.
> This happens because the model is saved as a unique file with no partitioning and the
kryo buffer overflows when tries to serialize it all.
> Increasing `spark.kryoserializer.buffer.max` works as a temporary solution but needs
to increased again whenever we increase the model size. 



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