Description of problem:
We have noticed in scale testing that was made that the amount of journal threads is unlimited, so for a service running on a node with a high amount of cores the API workers and RPC workers default to the amount of cores, so for a 50 core machine we will get 100 neutron server processes. In each such process there will be at least 1 journal thread, but at most there could be several depending on how much V2 drivers are used since each one instantiates a thread.

While this is already not optimal, the influx of journal threads causes the DB to misbehave due to multiple threads either querying the journal table all the time or exhausting all available DB connections (on the server side).

Each time an operation occurs it is written to the DB and the thread gets awoken to take care of it right after. In case there's a post commit hook the journal entry will be processed immediately. In case there's no such hook point, there might be a race where the journal will "miss" the entry.
Each 5 seconds (default config) a timer will awaken the thread to take care of any such missed entries, and also other entries that weren't handled due to conditions such as network connectivity loss (which halts the journal processing, to avoid a busy loop).

There's no need to have more than one thread per process as a single thread will either get awoken by the operation callback or by the timer, and process all journal entries it can process.
Also considering that python doesn't have true parallelism, it makes little sense to have virtual multi-threading in this context.

Version-Release number of selected component (if applicable):
python-networking-odl-4.0.0-1.el7ost.noarch

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