A {@link Filter} that only accepts documents whose single
term value in the specified field is contained in the
provided set of allowed terms.
This is the same functionality as TermsFilter (from
contrib/queries), except this filter requires that the
field contains only a single term for all documents.
Because of drastically different implementations, they
also have different performance characteristics, as
described below.
The first invocation of this filter on a given field will
be slower, since a {@link FieldCache.StringIndex} must be
created. Subsequent invocations using the same field
will re-use this cache. However, as with all
functionality based on {@link FieldCache}, persistent RAM
is consumed to hold the cache, and is not freed until the
{@link IndexReader} is closed. In contrast, TermsFilter
has no persistent RAM consumption.
With each search, this filter translates the specified
set of Terms into a private {@link OpenBitSet} keyed by
term number per unique {@link IndexReader} (normally one
reader per segment). Then, during matching, the term
number for each docID is retrieved from the cache and
then checked for inclusion using the {@link OpenBitSet}.
Since all testing is done using RAM resident data
structures, performance should be very fast, most likely
fast enough to not require further caching of the
DocIdSet for each possible combination of terms.
However, because docIDs are simply scanned linearly, an
index with a great many small documents may find this
linear scan too costly.
In contrast, TermsFilter builds up an {@link OpenBitSet},
keyed by docID, every time it's created, by enumerating
through all matching docs using {@link TermDocs} to seek
and scan through each term's docID list. While there is
no linear scan of all docIDs, besides the allocation of
the underlying array in the {@link OpenBitSet}, this
approach requires a number of "disk seeks" in proportion
to the number of terms, which can be exceptionally costly
when there are cache misses in the OS's IO cache.
Generally, this filter will be slower on the first
invocation for a given field, but subsequent invocations,
even if you change the allowed set of Terms, should be
faster than TermsFilter, especially as the number of
Terms being matched increases. If you are matching only
a very small number of terms, and those terms in turn
match a very small number of documents, TermsFilter may
perform faster.
Which filter is best is very application dependent.