Based on SimpleFacetedSearch. Uses DocID lists instead on bitmaps. Efficient memory usage for high cardinality sparsely populated facets.
Suitable for high cardinality, sparsely populated facets. i.e. There are a large number of facet values and each facet value is hit in a small percentage of documents. Especially if there are also a large number of documents. SimpleFacetedSearch holds a bitmap for each value representing whether that value is a hit is each document (approx 122KB per 1M documents per facet value). So this is an O(N*M) problem. The memory requirement can grow very quickly.
SparseFacetedSearcher records the DocID (Int32) for each value hit (memory cost = values * hits * 4). SimpleFacetedSearch record a bit for evey document per value (memory cost = values * documents / 8). So if the average number of hits for each value is less than 1/32 or 3.125% then Sparse is more memory efficient.
There are also some enumerable methods than mean there is much less pressure on the GC. Plus some bug fixes.