I am not sure I have the proper vocabulary to describe the error that I am having so bear with me.
Here is the general schema for the documents in my collection
{
_id: ObjectId(),
name: String,
business: String,
address: {
search_type: Character,
address: String,
city: String,
state: String,
zip: Number
}
}
I wanted to search based on the address.search_type
so I created a text index for that fields in my collection.
{
v: 1,
key: { _fts: 'text', _ftsx: 1 },
name: 'address.search_type_text',
ns: 'admin.customer',
default_language: 'none',
weights: { 'address.search_type': 1 },
language_override: 'language',
textIndexVersion: 3
}
Now I know that my data should really only have C, G, or T as a search type and when I run a find query on this collection with one of the supported search_types the query runs just fine.
db.collection('blah').find({'address.search_type':'C'}).limit(10).toArray(function(err, result){
if(err) console.log(err);
else console.log(result[0]);
db.close();
});
But when I run this query with a address.search_type
that should return 0 documents my query either never finishes or times out.
db.collection('blah').find({'address.search_type':'Z'}).limit(10).toArray(function(err, result){
if(err) console.log(err);
else console.log(result[0]);
db.close();
});
Why would my query not finish running / timeout when there are supposed to be 0 documents but works just fine when it can find documents?
After playing around with different types of indexes I realized that I did not need a text index at all.
This is probably an embarrassing mistake but hey I just started learning mongodb
so whatever.
Anyway, I realized that all I needed to do was the create a single field index on address.search_type
.
{ v: 1,
key: { 'address.Search_Type': 1 },
name: 'address.Search_Type_1',
ns: 'admin.customer'
}
I am not still totally sure why the text index was not working since I had set the language to none, but it makes sense that all I would need is a single index.
I think text index is mostly used for searching phrases or keywords in largeish blocks of text. So the fact that my search was looking for a single character might have been causing problems since that is not what the text index was intended to be used for.