I have a dataset of CrossRef works records stored in a collection called works in MongoDB and I am using a Python application to query this database.
I am trying to find documents based on one author's name. Removing extraneous details, a document might look like this:
{'DOI':'some-doi',
'author':[{'given': 'Albert','family':'Einstein',affiliation:[]},
{'given':'R.','family':'Feynman',affiliation:[]},
{'given':'Paul','family':'Dirac',affiliation:['University of Florida']}]
}
It isn't clear to me how to combine the queries to get just Albert Einstein's papers.
I have indexes on author.family and author.given, I've tried:
cur = works.find({'author.family':'Einstein','author.given':'Albert'})
This returns all of the documents by people called 'Albert' and all of those by people called 'Einstein'. I can filter this manually, but it's obviously less than ideal.
I also tried:
cur = works.find({'author':{'given':'Albert','family':'Einstein','affiliation':[]}})
But this returns nothing (after a very long delay). I've tried this with and without 'affiliation'. There are a few questions on SO about querying nested fields, but none seem to concern the case where we're looking for 2 specific things in 1 nested field.
Your issue is that author is a list.
You can use an aggregate query to unwind this list to objects, and then your query would work:
cur = works.aggregate([{'$unwind': '$author'},
{'$match': {'author.family':'Einstein', 'author.given':'Albert'}}])
Alternatively, use $elemMatch which matches on arrays that match all the elements specified.
cur = works.find({"author": {'$elemMatch': {'family': 'Einstein', 'given': 'Albert'}}})
Also consider using multikey indexes.