I think we are still discussing implementation here when I'm talking about developer experience. I want developers to adopt this quickly, easily and be successful. Vector search is already a thing. People use it every day. A successful outcome, in my view, is developers picking up this feature without reading a manual. (Because they don't anyway and get in trouble) I did some more extensive research about what other DBs are using for syntax. The consensus is some variety of 'VECTOR', 'DENSE' and 'SPARSE'
Pinecone[1] - dense_vector, sparse_vector Elastic[2]: dense_vector Milvus[3]: float_vector, binary_vector pgvector[4]: vector Weaviate[5]: Different approach. All typed arrays can be indexed Based on that I'm advocating a similar syntax: - DENSE VECTOR or - VECTOR [1] https://docs.pinecone.io/docs/hybrid-search [2] https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html [3] https://milvus.io/docs/create_collection.md [4] https://github.com/pgvector/pgvector [5] https://weaviate.io/developers/weaviate/config-refs/datatypes On Fri, May 5, 2023 at 6:07 AM Mike Adamson <madam...@datastax.com> wrote: > Then we can have the indexing apparatus only accept *frozen<float[n]>* for >> the HSNW case. >> > I'm inclined to agree with Benedict that the index will need to be > specifically select by option rather than inferred based on type. As such > there is no real reason for the *frozen* requirement on the type. The > hnsw index can be built just as easily from a non-frozen array. > > I am in favour of enforcing non-null on the elements of an array by > default. I would prefer that allowing nulls in the array would be a later > addition if and when a use case arose for it. > > On Fri, 5 May 2023 at 03:02, Caleb Rackliffe <calebrackli...@gmail.com> > wrote: > >> Even in the ML case, sparse can just mean zeros rather than nulls, and >> they should compress similarly anyway. >> >> If we really want null values, I'd rather leave that in collections space. >> >> On Thu, May 4, 2023 at 8:59 PM Caleb Rackliffe <calebrackli...@gmail.com> >> wrote: >> >>> I actually still prefer *type[dimension]*, because I think I >>> intuitively read this as a primitive (meaning no null elements) array. Then >>> we can have the indexing apparatus only accept *frozen<float[n]>* for >>> the HSNW case. >>> >>> If that isn't intuitive to anyone else, I don't really have a strong >>> opinion...but...conflating "frozen" and "dense" seems like a bad idea. One >>> should indicate single vs. multi-cell, and the other the presence or >>> absence of nulls/zeros/whatever. >>> >>> On Thu, May 4, 2023 at 12:51 PM Patrick McFadin <pmcfa...@gmail.com> >>> wrote: >>> >>>> I agree with David's reasoning and the use of DENSE (and maybe >>>> eventually SPARSE). This is terminology well established in the data world, >>>> and it would lead to much easier adoption from users. VECTOR is close, but >>>> I can see having to create a lot of content around "How to use it and not >>>> get in trouble." (I have a lot of that content already) >>>> >>>> - We don't have to explain what it is. A lot of prior art out there >>>> already [1][2][3] >>>> - We're matching an established term with what users would expect. No >>>> surprises. >>>> - Shorter ramp-up time for users. Cassandra is being modernized. >>>> >>>> The implementation is flexible, but the interface should empower our >>>> users to be awesome. >>>> >>>> Patrick >>>> >>>> 1 - >>>> https://stats.stackexchange.com/questions/266996/what-do-the-terms-dense-and-sparse-mean-in-the-context-of-neural-networks >>>> <https://urldefense.com/v3/__https://stats.stackexchange.com/questions/266996/what-do-the-terms-dense-and-sparse-mean-in-the-context-of-neural-networks__;!!PbtH5S7Ebw!dpAaXazB6qZfr_FdkU9ThEq4X0DDTa-DlNvF5V4AvTiZSpHeYn6zqhFD4ZVaRLYoQBmNTn7n6jt5ymZs5Ud6ieKGQw$> >>>> 2 - >>>> https://induraj2020.medium.com/what-are-sparse-features-and-dense-features-8d1746a77035 >>>> <https://urldefense.com/v3/__https://induraj2020.medium.com/what-are-sparse-features-and-dense-features-8d1746a77035__;!!PbtH5S7Ebw!dpAaXazB6qZfr_FdkU9ThEq4X0DDTa-DlNvF5V4AvTiZSpHeYn6zqhFD4ZVaRLYoQBmNTn7n6jt5ymZs5Ue1o2CO2Q$> >>>> 3 - >>>> https://revware.net/sparse-vs-dense-data-the-power-of-points-and-clouds/ >>>> <https://urldefense.com/v3/__https://revware.net/sparse-vs-dense-data-the-power-of-points-and-clouds/__;!!PbtH5S7Ebw!dpAaXazB6qZfr_FdkU9ThEq4X0DDTa-DlNvF5V4AvTiZSpHeYn6zqhFD4ZVaRLYoQBmNTn7n6jt5ymZs5Ud3U6Hw5A$> >>>> >>>> On Thu, May 4, 2023 at 10:25 AM David Capwell <dcapw...@apple.com> >>>> wrote: >>>> >>>>> My views have changed over time on syntax and I feel type[dimention] >>>>> may not be the best, so it has gone lower in my own personal ranking… this >>>>> is my current preference >>>>> >>>>> 1) DENSE <type>[dimention] | NON NULL <type>[dimention] >>>>> 2) VECTOR<type, dimention> >>>>> 3) type[dimention] >>>>> >>>>> My reasoning for this order >>>>> >>>>> * type[dimention] looks like syntax sugar for array<type, dimention>, >>>>> so users may assume list/array semantics, but we limit to non-null >>>>> elements >>>>> in a frozen array >>>>> * feel VECTOR as a prefix feels out of place, but VECTOR as a direct >>>>> type makes more sense… this also leads to a possible future of >>>>> VECTOR<type> >>>>> which is the non-fixed length version of this type. What makes VECTOR >>>>> different from list/array? non-null elements and is frozen. I don’t feel >>>>> that VECTOR really tells users to expect non-null or frozen semantics, as >>>>> there exists different VECTOR types for those reasons (sparse vs dense)… >>>>> * DENSE may be confusing for people coming from languages where this >>>>> just means “sequential layout”, which is what our frozen array/list >>>>> already >>>>> are… but since the target user is coming from a ML background, this >>>>> shouldn’t offer much confusion. DENSE just means FROZEN in Cassandra, >>>>> with >>>>> NON NULL elements (SPARSE allows for NULL and isn’t frozen)… So DENSE just >>>>> acts as syntax sugar for frozen<non null type[dimention]> >>>>> >>>>> >>>>> On May 4, 2023, at 4:13 AM, Brandon Williams <dri...@gmail.com> wrote: >>>>> >>>>> 1. VECTOR<FLOAT,n> >>>>> 2. VECTOR FLOAT[n] >>>>> 3. FLOAT[N] (Non null by default) >>>>> >>>>> Redundant or not, I think having the VECTOR keyword helps signify what >>>>> the app is generally about and helps get buy-in from ML stakeholders. >>>>> >>>>> On Thu, May 4, 2023 at 3:45 AM Benedict <bened...@apache.org> wrote: >>>>> >>>>> >>>>> Hurrah for initial agreement. >>>>> >>>>> For syntax, I think one option was just FLOAT[N]. In VECTOR FLOAT[N], >>>>> VECTOR is redundant - FLOAT[N] is fully descriptive by itself. I don’t >>>>> think VECTOR should be used to simply imply non-null, as this would be >>>>> very >>>>> unintuitive. More logical would be NONNULL, if this is the only condition >>>>> being applied. Alternatively for arrays we could default to NONNULL and >>>>> later introduce NULLABLE if we want to permit nulls. >>>>> >>>>> If the word vector is to be used it makes more sense to make it look >>>>> like a list, so VECTOR<FLOAT, N> as here the word VECTOR is clearly not >>>>> redundant. >>>>> >>>>> So, I vote: >>>>> >>>>> 1) (NON NULL) FLOAT[N] >>>>> 2) FLOAT[N] (Non null by default) >>>>> 3) VECTOR<FLOAT, N> >>>>> >>>>> >>>>> >>>>> On 4 May 2023, at 08:52, Mick Semb Wever <m...@apache.org> wrote: >>>>> >>>>> >>>>> >>>>> >>>>> Did we agree on a CQL syntax? >>>>> >>>>> I don’t believe there has been a pool on CQL syntax… my understanding >>>>> reading all the threads is that there are ~4-5 options and non are -1ed, >>>>> so >>>>> believe we are waiting for majority rule on this? >>>>> >>>>> >>>>> >>>>> >>>>> Re-reading that thread, IIUC the valid choices remaining are… >>>>> >>>>> 1. VECTOR FLOAT[n] >>>>> 2. FLOAT VECTOR[n] >>>>> 3. VECTOR<FLOAT,n> >>>>> 4. VECTOR[n]<FLOAT> >>>>> 5. ARRAY<FLOAT, n> >>>>> 6. NON-NULL FROZEN<FLOAT[n]> >>>>> >>>>> >>>>> Yes I'm putting my preference (1) first ;) because (banging on) if the >>>>> future of CQL will have FLOAT[n] and FROZEN<FLOAT[n]>, where the VECTOR >>>>> keyword is: for general cql users; just meaning "non-null and frozen", >>>>> these gel best together. >>>>> >>>>> Options (5) and (6) are for those that feel we can and should provide >>>>> this type without introducing the vector keyword. >>>>> >>>>> >>>>> >>>>> > > -- > [image: DataStax Logo Square] <https://www.datastax.com/> *Mike Adamson* > Engineering > > +1 650 389 6000 <16503896000> | datastax.com <https://www.datastax.com/> > Find DataStax Online: [image: LinkedIn Logo] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.linkedin.com_company_datastax&d=DwMFaQ&c=adz96Xi0w1RHqtPMowiL2g&r=IFj3MdIKYLLXIUhYdUGB0cTzTlxyCb7_VUmICBaYilU&m=uHzE4WhPViSF0rsjSxKhfwGDU1Bo7USObSc_aIcgelo&s=akx0E6l2bnTjOvA-YxtonbW0M4b6bNg4nRwmcHNDo4Q&e=> > [image: Facebook Logo] > <https://urldefense.proofpoint.com/v2/url?u=https-3A__www.facebook.com_datastax&d=DwMFaQ&c=adz96Xi0w1RHqtPMowiL2g&r=IFj3MdIKYLLXIUhYdUGB0cTzTlxyCb7_VUmICBaYilU&m=uHzE4WhPViSF0rsjSxKhfwGDU1Bo7USObSc_aIcgelo&s=ncMlB41-6hHuqx-EhnM83-KVtjMegQ9c2l2zDzHAxiU&e=> > [image: Twitter Logo] <https://twitter.com/DataStax> [image: RSS > Feed] <https://www.datastax.com/blog/rss.xml> [image: Github Logo] > <https://github.com/datastax> > >
