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https://issues.apache.org/jira/browse/SYNAPSE-408?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12617702#action_12617702
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Saliya Ekanayake commented on SYNAPSE-408:
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The alternative approach you are suggesting was in fact there in Synapse before
https://issues.apache.org/jira/browse/SYNAPSE-392. We have used the serialize()
and serializeAndConsume() methods to find the content length and then to send
it out respectively. This, however, resulted in different outputs as the latter
method adds an empty SOAP header element where as the former does not add such
if it's not available in the original XML. However, IMHO serializing twice will
affect the performance with respect to time as well (pls. correct me here if I
am wrong).
Thanks,
Saliya
> Improve Synapse Memory Footprint under HTTP 1.0
> -----------------------------------------------
>
> Key: SYNAPSE-408
> URL: https://issues.apache.org/jira/browse/SYNAPSE-408
> Project: Synapse
> Issue Type: Improvement
> Reporter: Saliya Ekanayake
> Priority: Minor
>
> Synapse serializes the SOAP envelope in order to calculate the content length
> of the message under HTTP 1.0. This serialization is done inside the class
> Axis2HttpRequest which is inside the transports module. The serialized bytes
> are then stored in the message context for future use by the
> streamMessageContents() method inside the same class.
> Thus, the entire content of the SOAP envelope is stored inside the memory
> leading to a possible out of memory situation when the XML data is large. A
> solution to this would be to write some of the data to a permanent storage
> (like hard disk) based on a threshold value. The TemporaryData class inside
> the core module is a good solution to this kind of work. It would, however,
> incur a cyclic dependency if used inside the Axis2HttpRequest class.
> If we can resolve this issue (probably by moving the TemporaryData class to a
> utility module and then making the core too depend on that) it will of great
> use in improving the memory footprint of Synapse.
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