Frederik Petersen created NIFI-5858:
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Summary: Existing unpacked custom processors fail to deploy after
upgrade from 1.7.0 to 1.8.0
Key: NIFI-5858
URL: https://issues.apache.org/jira/browse/NIFI-5858
Project: Apache NiFi
Issue Type: Bug
Components: Core Framework
Affects Versions: 1.8.0
Environment: HDF 3.2.1 -> HDF 3.3.0
Reporter: Frederik Petersen
Hi,
after upgrading our HDF cluster from 3.2.0.0 to 3.3.0.0 our custom processors
didn't work anymore and were replaced by "ghost" processors. We had to roll
back and it was kind of hard to find out what went wrong.
I think I figured it out now and I'm confused that there are no measures taken
or at least documented to avoid this issue. Maybe I didn't find them though, so
if that's the case please point them out to me, thanks.
So the root of the problem seems to be this change in nifi:
[https://github.com/apache/nifi/commit/a27ccd8a56fb52a61d79f87711324142a5b4a141]
The corresponding Jira ticket is: https://jira.apache.org/jira/browse/NIFI-5479
What I think happened:
We have our custom processors in a custom library folder configured with
"nifi.nar.library.directory.custom=/custom/folder". The last release of our
processors happened during 1.7.0 so the NarUnpacker unpacked them into nifis
work directory.
Before upgrading to nifi 1.8.0 we went through the changelog and checked
whether there were any api incompatibilities, but it didn't seem like it so we
thought we would be fine with our current nar.
During the upgrade we saw this log line:
2018-11-30 11:49:52,920 WARN [main] org.apache.nifi.nar.NarClassLoader
/var/lib/nifi/work/nar/extensions/custom-nar-1.14.2.nar-unpacked does not
contain NAR-INF/bundled-dependencies!
So I guess, the new NarUnpacker didn't re-unpack the .nar file (and thus there
was no renaming from META-INF to NAR-INF. Thus the NarClassLoader cannot
resolve everything properly.
So a new .nar release/deleting the work directory at this point should allow us
to upgrade. But maybe it would be a good idea to make sure this is documented
somewhere to save others from some of the frustration and investigation. Maybe
it can even be handled (at least for HDF upgrades, but I know that this Jira is
the wrong place for that) automatically.
Let me know if you have any questions.
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