...where, just to be clear, VECTOR<type, dimension> means a frozen fixed size array w/ no null values?
On Fri, May 5, 2023 at 11:23 AM Jonathan Ellis <jbel...@gmail.com> wrote: > +10 for not inflicting unwieldy keywords on ML users. > > Re Josh's summary, mostly agreed, my only objection to adding the DENSE > keyword is that I don't see a foreseeable future where we also support > sparse vectors, so it would end up being unnecessary extra verbosity. So > my preference would be > > 1. VECTOR<type, dimension> > 2. DENSE VECTOR<type, dimension> (space instead of underscore, SQL isn't > afraid of spaces) > 3. type[dimension] > > On Fri, May 5, 2023 at 10:54 AM Patrick McFadin <pmcfa...@gmail.com> > wrote: > >> I hope we are willing to consider developers that use our system because >> if I had to teach people to use "NON-NULL FROZEN<TYPE[n]>" I'm pretty sure >> the response would be: >> >> Did you tell me to go write a distributed map-reduce job in Erlang? I >> beleive I did, Bob. >> >> On Fri, May 5, 2023 at 8:05 AM Josh McKenzie <jmcken...@apache.org> >> wrote: >> >>> Idiomatically, to my mind, there's a question of "what space are we >>> thinking about this datatype in"? >>> >>> - In the context of mathematics, nullability in a vector would be 0 >>> - In the context of Cassandra, nullability tends to mean a tombstone (or >>> nothing) >>> - In the context of programming languages, it's all over the place >>> >>> Given many models are exploring quantizing to int8 and other data types, >>> there's definitely the "support other data types easily in the future" >>> piece to me we need to keep in mind. >>> >>> So with the above and the "meet the user where they are and don't make >>> them understand more of Cassandra than absolutely critical to use it", I >>> lean: >>> >>> 1. DENSE_VECTOR<type, dimension> >>> 2. VECTOR<type, dimension> >>> 3. type[dimension] >>> >>> This leaves the path open for us to expand on it in the future with >>> sparse support and allows us to introduce some semantics that indicate >>> idioms around nullability for the users coming from a different space. >>> >>> "NON-NULL FROZEN<TYPE[n]>" is strictly correct, however it requires >>> understanding idioms of how Cassandra thinks about data (nulls mean >>> different things to us, we have differences between frozen and non-frozen >>> due to constraints in our storage engine and materialization of data, etc) >>> that get in the way of users doing things in the pattern they're familiar >>> with without learning more about the DB than they're probably looking to >>> learn. Historically this has been a challenge for us in adoption; the >>> classic "Why can't I just write and delete and write as much as I want? Why >>> are deletes filling up my disk?" problem comes to mind. >>> >>> I'd also be happy with us supporting: >>> * NON-NULL FROZEN<TYPE[n]> >>> * DENSE_VECTOR<type, dimension> as syntactic sugar for the above >>> >>> If getting into the "built-in syntactic sugar mapping for communities >>> and specific use-cases" is something we're willing to consider. >>> >>> On Fri, May 5, 2023, at 7:26 AM, Patrick McFadin wrote: >>> >>> 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> >>> >>> >>> > > -- > Jonathan Ellis > co-founder, http://www.datastax.com > @spyced >
