[
https://issues.apache.org/jira/browse/OPENNLP-776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15545212#comment-15545212
]
Joern Kottmann commented on OPENNLP-776:
----------------------------------------
Thanks, looks good, I think we can more or less merge it like that for the
1.6.1 release. One question, in which case can the else block of the if( in
instanceof InputStream ) be entered in the read and write methods ? As far as I
understand will this always be true, since the type is defined as part of the
Java API and won't change. I suggest we drop the else block.
I will test this on my cluster in the next days and then report back here.
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
