Gandhi, Is that code public at all? I made a docker container for the REST server that uses the hsql, but if mysql is even faster and the dictionary building can be containerized that might be a nice next step for better performance of the container. Tim
On Thu, 2021-02-25 at 20:33 +0530, gandhi rajan wrote: > * External Email - Caution * > > > Hi Peter, > > Noticed a similar behavior while working on cTAKES REST module. The > in-memory HSQL in my case was stressing the application server memory > and > ended up slowing down the process whereas mysql performed better. > Also > the engine you use in MySQL matters as well. > > We did a testing on MySQL based UMLS dictionary using multiple pods > running > ctakes rest and it was scaling fairly well. But havent explored with > 100+ > connections. But i guess with connection pool configurations in MySQL > DB it > should be manageable. Hope it helps. > > On Thu, Feb 25, 2021 at 7:37 PM Peter Abramowitsch < > pabramowit...@gmail.com> > wrote: > > > Hi all, > > > > As an experiment I extracted my rather large HSQL UMLS dictionary > > into a > > local MYSQL instance and ran the equivalent of 3 simultaneous > > ctakes > > pipelines with the overlap lookup annotator against it with a set > > of 1000 > > notes. > > > > Comparing that with the same setup running against the traditional > > in-memory HSQL database (three separate instances), I was surprised > > to find > > that the Mysql implementation it was 30% faster even though it is > > an out of > > process DB > > > > Has that been anyone else's experience as well? And if so, do you > > have any > > experience with a MYSQL based UMLS dictionary with 100+ pipeline > > connections? > > > > Peter > > > >
