问题
I define a Document object for my product entity which has several fields: Title, Brand, Category, Size, Color, Material.
Now I want to support user to do an AND search on multiple fields. Any document that have one, two or more fields contain all the search words will be responded.
For example, when user enter "gucci shirt red" I want to return all documents that have fields matched with all 3 tokens "gucci", "shirt" AND "red". So all documents below will be responded:
1.Documents with title contains all the 3 words, for example Title = "Gucci Modern Shirt Red" or "Gucci blue shirt"...
2.Documents with Title = "Gucci classical shirt" AND Color = "red"
3.Documents with Category = "mens shirt" AND Brand = "gucci" AND Color = "red"
4.etc..
I know that Lucene support operator + that do a MUST for search query. For example I can translate the above keyword to query "+gucci +shirt +red" then I'm sure documents of example (1) above will definitely be responded. But does it work for cases (2) and (3) above ?
回答1:
No, when not given a a field to search explicitly in the query, it will go to the default field, which it would appear is the "title" in your case. You would need a query more like:
+shirt +color:red +brand:gucci
for instance.
Or, one common usage is to set up a catch all field, in which all (or a large subset) of searchable data is mashed together, allowing you to search everything in a very loose fashion, on that field, in which case you would just use something like:
all:(+shirt +gucci +red)
Or, if you made that field your default field instead:
+shirt +gucci +red
As you indicated.
回答2:
When doing these types of queries I like to: create a master BooleanQuery and add several sub-queries that work together to give the best result:
- TermQuery: (exact match), someone types in the exact match of the title
- PhraseQuery: (use slop), so if you have "Gucci Modern Shirt Red" and someone types in "Gucci Shirt" (notice one word gap) it would match
- FuzzyQuery: (slow on large(> 50 million records)/non-memory indexes) to account for potential misspellings
- Boolean SubQuery: with all of the terms seperated and OR'ed. Queries matching 1 our of 4 words will have low score however 3/4 words will have a higher score.
- Query Parse (as mentioned above with potential field boosts)
- Other: i.e. Synonym search on phrases etc.
I would OR all of these types and then filter them out using a Collector minimum score.
The reason I like the master BooleanQuery approach is that you can have a setting where a user chooses "the type" of query. Maybe as simple -> advanced and it is easy to add/remove query types rather quickly on the fly and the query can be built pretty easily giving predicitve results. Boosting records/similarity you are working within the internal Lucene algorithm and results are not sometimes clear.
Performance: I have done queries like this using Lucene 3.0.x on indexes with > 100M records NOT IN MEMORY and it works pretty quickly giving sub-second responses. Fuzzy Query does slow things down, but as stated before that can be made into an advanced search option (or "Search again with...")
回答3:
You could use MultiFieldQueryParser. Add Title, color, brand etc to this.
If you search for "gucci shirt red" then using above Parser would return query like
+((Title:gucci Color:gucci Brand:gucci) (Title:shirt Color:shirt Brand:shirt) (Title:red Color:red Brand:red)
This should solve the problem.
Also, if you want that lets say, for above query you want to show brand with gucci products to be shown 1st then you could apply boost to this field.
来源：https://stackoverflow.com/questions/19230403/lucene-net-do-an-and-search-multiple-words-on-multiple-fields