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https://issues.apache.org/jira/browse/OPENNLP-776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15549163#comment-15549163
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Joern Kottmann commented on OPENNLP-776:
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Now speaking here about the serialization_proxy.patch approach. I try to
understand what is necessary to make this work with Kyro serialization.
Do you use the ExternalizableSerializer as described here [1]?
If not, which mechanism inside Kyro is used in your application to
serialize/deserialize the models?
[1] https://github.com/EsotericSoftware/kryo#using-standard-java-serialization
> 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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