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https://issues.apache.org/jira/browse/OPENNLP-776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15545809#comment-15545809
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Joern Kottmann commented on OPENNLP-776:
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But it is not possible to pass on object which only implements ObjectOutput to
void writeObject(final ObjectOutputStream out) therefore the passed in object
must be of type OutputStream and the implementation in the patch will always
execute the first part of the if, and can't go into the else block.
Anyway, don't get me wrong, if we can make it work with Kyro serialization as
well, that would be great.
> Model Objects should be Serializable
> ------------------------------------
>
> Key: OPENNLP-776
> URL: https://issues.apache.org/jira/browse/OPENNLP-776
> Project: OpenNLP
> Issue Type: Improvement
> Affects Versions: tools-1.5.3
> Reporter: Tristan Nixon
> Assignee: Joern Kottmann
> Priority: Minor
> Labels: features, patch
> Fix For: 1.6.1
>
> Attachments: externalizable.patch, serializable-basemodel.patch,
> serialization_proxy.patch
>
>
> Marking model objects (ParserModel, SentenceModel, etc.) as Serializable can
> enable a number of features offered by other Java frameworks (my own use case
> is described below). You've already got a good mechanism for
> (de-)serialization, but it cannot be leveraged by other frameworks without
> implementing the Serializable interface. I'm attaching a patch to BaseModel
> that implements the methods in the java.io.Externalizable interface as
> wrappers to the existing (de-)serialization methods. This simple change can
> open up a number of useful opportunities for integrating OpenNLP with other
> frameworks.
> My use case is that I am incorporating OpenNLP into a Spark application. This
> requires that components of the system be distributed between the driver and
> worker nodes within the cluster. In order to do this, Spark uses Java
> serialization API to transmit objects between nodes. This is far more
> efficient than instantiating models on each node independently.
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