You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, thanks for this very useful rdflib plugin! I am running some tests and comparisons and am noticing that using sqlite results in very large db sizes. I have a graph of ~10k triples and it serializes on disk to ~2MB using rdf-xml and a sqlite db of almost 14MB - is this expected? Or is there some setup step I'm missing that would make the db more reasonable? Thanks!
The text was updated successfully, but these errors were encountered:
Hard to say for sure without your source data why your database file is as large as it is. I did a test of adding exactly 10,000 triples with 10,000 distinct subjects, 100 distinct predicates, and 1000 distinct objects and got a DB file size of 4.7MB. Repeated with all distinct sub, pred, obj and that only increased to 4.8 MB. I'm able to increase that to 19MB+ just by using longer URIs.
sqlite3 version: 3.32.2
Python version: 3.7.4
rdflib-sqlalchemy version: 0.4.0
Thanks for the quick response @mwatts15 - there certainly might be some long(ish) URIs in my data. I'm wondering if there are any indexing options available to mitigate this problem?
If by options you mean a flag you can specify that will create a table mapping strings to more compact identifiers, there is no such thing in rdflib-sqlalchemy, nor, as far as I have seen, is there any sqlite extension that does something similar. If you would like to implement such a feature, I would certainly be open to merging it.
Hi, thanks for this very useful rdflib plugin! I am running some tests and comparisons and am noticing that using sqlite results in very large db sizes. I have a graph of ~10k triples and it serializes on disk to ~2MB using rdf-xml and a sqlite db of almost 14MB - is this expected? Or is there some setup step I'm missing that would make the db more reasonable? Thanks!
The text was updated successfully, but these errors were encountered: