Since you know that it almost got inserted entirely, you could simply split your entries in 2 files of 125,000 entries each and insert these 2 files one after the other.
If your need a reliable way to do these kinds of insertions on a regular basis, then there is probably a way to adjust the timeout of the HTTP connection somewhere to extend it to more than 30 minutes. It depends on your real need. Google AI is talking nonsense. Erlang already uses one process for each CPU core and maxes out the usage of your CPU, so what Google AI told you is nothing here or there. Le jeu. 21 mai 2026 à 21:10, Momchil Bozhinov <[email protected]> a écrit : > > Hello, > > > > This is my first day of trying out CouchDb (1 node). Looking for a > > MongoDb alternative. > > > > First thing I noticed - no collections. That's fine though. > > > > I tried bulk inserting 110 Mb list of dictionaries (~250 000 entries) > > using pycouchdb and couchdb3 > > > Failed with timeout after 30 minutes and failed to insert the last ~10k > events. > > > > Tried disabling the compression - that did not help > > > > Looked for the option to enable Delayed commit but I could not find it. > > > > ref https://guide.couchdb.org/draft/performance.html > > > Google AI suggested I add some config options to use the kernel directly > and increase the number of processes. > > Upon checking those turned out old and obsolete. > > > Seems to be creating a bunch of stuff (keys, ids) for each entry. I > > guess that is taking a while. > > > My setup is a xen vm running on top of an old HP DL360 G8. Maybe I lack > CPU instructions ? > > > > Please help ? > > > > Momchil > > > > > >
