Hi, Thanks for the reply. I haven't tried to do that. However, I do not fully understand how in this case an inverted index will be constructed for an efficient search by terms (O(1) for each term as a key )?
пн, 2 дек. 2024 г. в 21:55, Patrick Zhai <zhai7...@gmail.com>: > Hi, have you tried to encode the sparse vector yourself using the > BinaryDocValueField? One way I can think of is to encode it as (size, > index_array, value_array) per doc > Intuitively I feel like this should be more efficient than one dimension > per field if your dimension is high enough > > Patrick > > On Mon, Dec 2, 2024, 09:03 Viacheslav Dobrynin <w.v.d...@gmail.com> wrote: > > > Hi! > > > > I need to index sparse vectors, whereas as I understand it, > > KnnFloatVectorField is designed for dense vectors. > > Therefore, it seems that this approach will not work. > > > > вс, 1 дек. 2024 г. в 18:36, Mikhail Khludnev <m...@apache.org>: > > > > > Hi, > > > May it look like KnnFloatVectorField(... DOT_PRODUCT) > > > and KnnFloatVectorQuery? > > > > > >
