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https://issues.apache.org/jira/browse/JENA-576?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15568928#comment-15568928
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ASF GitHub Bot commented on JENA-576:
-------------------------------------
Github user afs commented on the issue:
https://github.com/apache/jena/pull/151
I've cleaned up allocating/deallocing the Fuseki server in case it hides
some timing issues.
Commit AFS-Debug-3 which I have also tried with a multisecond wait after
the server is stopped and started as the first test suite ends and a second one
starts.
Also, the reset is done by clearing the datasets programmatically.
Hence, the problem is not `UpdateExecutionFactory.createRemote` itself.
I now get (+ messages about server start/stop) 2 low level messages from
the commons HTTP code but a green line.
Could some connection state be carried across the server restart? Or is
this reason across server restart?
```
*** connection_statement_query_select_max_rows_01
*** connection_prepared_statement_select_01
*** connection_statement_query_select_max_rows_01
15:08:29 INFO RetryExec :: I/O exception
(java.net.SocketException) caught when processing request to
{}->http://localhost:42668: Broken pipe
15:08:29 INFO RetryExec :: Retrying request to
{}->http://localhost:42668
*** connection_prepared_statement_select_01
```
Those "RetryExec" appeared. If, however, there is one server across the run
of both test classes, these do not occur.
Not using a pooling client also fixes them. AFS_TS_Debug : set the used
HttpClient to null.
> Upgrade Apache HTTP Client to 4.3
> ---------------------------------
>
> Key: JENA-576
> URL: https://issues.apache.org/jira/browse/JENA-576
> Project: Apache Jena
> Issue Type: Dependency upgrade
> Components: ARQ
> Affects Versions: Jena 2.11.0
> Reporter: Rob Vesse
> Assignee: Rob Vesse
> Priority: Minor
> Original Estimate: 72h
> Remaining Estimate: 72h
>
> As of 2.11.0 ARQ centralizes all HTTP operations through HttpOp which relies
> on Apache HTTP Client. Currently we are using 4.2.3 while the latest stable
> release is actually 4.3.1
> Therefore we should look at upgrading our code to use the latest version
> which may entail some refactoring since there appears to have been some
> breaking changes across the minor version bump which users have seen in usage
> - e.g.
> https://github.com/pyvandenbussche/sparqles/issues/9#issuecomment-27220738
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