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    <p>You can do the query, the question would be is it fast or not. ie something like: </p> <pre><code>find( { size:'S', color:'Blue', Brand:{$in:[...]} } ) </code></pre> <p>the question is then how is the performance. There isn't any special facility for faceted search in the product yet. Down the road there might be some set intersection-like query plans that are good but that is tbd/future.</p> <ul> <li><p>If your properties are a predefined set and you know what they are you could create an index on each of them. Only one of the indexes will be used in the current implementation so this will help but only get you so far: if the data set is medium plus in size it might be fine.</p></li> <li><p>You could use compound indexes which perhaps compound two or more of the properties. If you have a small # of properties this might work pretty well. The index need not use all the variables queries on but in the one above a compound index on any two of the three is likely to perform better than an index on a single item.</p></li> <li><p>If you dont have too many skus brute force would work; e.g. if you are 1MM skues a table scan in ram might be fast enough. in this case i would make a table with just the facet values and make it as small as possible and keep the full sku docs in a separate collection. e.g.:</p> <p>facets_collection: {sz:1,brand:123,clr:'b',_id:} ...</p></li> </ul> <p>if the # of facet dimensions isnt' too high you could instead make a highly compound index of the facit dimensions and you would get the equivalent to the above without the extra work. </p> <p>if you create quit a few indexes, it is probably best to not create so many that they no longer fit in ram.</p> <p>given the query runs and it is a performance question one might just with mongo and if it isn't fast enough then bolt on solr.</p>
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