I am also in agreement with 'column : token' in that 'I don't hate it' but I'd like to offer an alternative to this in 'column HAS token'. HAS is currently not a keyword that we use so wouldn't cause any brain conflicts.
While I don't hate ':' I have a particular dislike of the lucene search syntax because of its terseness and lack of easy readability. Saying that, I'm happy to do with ':' if that is the decision. On Fri, 4 Aug 2023 at 00:23, Jon Haddad <rustyrazorbl...@apache.org> wrote: > Assuming SAI is a superset of SASI, and we were to set up something so > that SASI indexes auto convert to SAI, this gives even more weight to my > point regarding how differing behavior for the same syntax can lead to > issues. Imo the best case scenario results in the user not even noticing > their indexes have changed. > > An (maybe better?) alternative is to add a flag to the index configuration > for "compatibility mod", which might address the concerns around using an > equality operator when it actually is a partial match. > > For what it's worth, I'm in agreement that = should mean full equality and > not token match. > > On 2023/08/03 03:56:23 Caleb Rackliffe wrote: > > For what it's worth, I'd very much like to completely remove SASI from > the > > codebase for 6.0. The only remaining functionality gaps at the moment are > > LIKE (prefix/suffix) queries and its limited tokenization > > capabilities, both of which already have SAI Phase 2 Jiras. > > > > On Wed, Aug 2, 2023 at 7:20 PM Jeremiah Jordan <jerem...@datastax.com> > > wrote: > > > > > SASI just uses “=“ for the tokenized equality matching, which is the > exact > > > thing this discussion is about changing/not liking. > > > > > > > On Aug 2, 2023, at 7:18 PM, J. D. Jordan <jeremiah.jor...@gmail.com> > > > wrote: > > > > > > > > I do not think LIKE actually applies here. LIKE is used for prefix, > > > contains, or suffix searches in SASI depending on the index type. > > > > > > > > This is about exact matching of tokens. > > > > > > > >> On Aug 2, 2023, at 5:53 PM, Jon Haddad <rustyrazorbl...@apache.org> > > > wrote: > > > >> > > > >> Certain bits of functionality also already exist on the SASI side > of > > > things, but I'm not sure how much overlap there is. Currently, > there's a > > > LIKE keyword that handles token matching, although it seems to have > some > > > differences from the feature set in SAI. > > > >> > > > >> That said, there seems to be enough of an overlap that it would make > > > sense to consider using LIKE in the same manner, doesn't it? I think > it > > > would be a little odd if we have different syntax for different > indexes. > > > >> > > > >> https://github.com/apache/cassandra/blob/trunk/doc/SASI.md > > > >> > > > >> I think one complication here is that there seems to be a desire, > that > > > I very much agree with, to expose as much of the underlying > flexibility of > > > Lucene as much as possible. If it means we use Caleb's suggestion, > I'd ask > > > that the queries that SASI and SAI both support use the same syntax, > even > > > if it means there's two ways of writing the same query. To use Caleb's > > > example, this would mean supporting both LIKE and the `expr` column. > > > >> > > > >> Jon > > > >> > > > >>>> On 2023/08/01 19:17:11 Caleb Rackliffe wrote: > > > >>> Here are some additional bits of prior art, if anyone finds them > > > useful: > > > >>> > > > >>> > > > >>> The Stratio Lucene Index - > > > >>> https://github.com/Stratio/cassandra-lucene-index#examples > > > >>> > > > >>> Stratio was the reason C* added the "expr" functionality. They > embedded > > > >>> something similar to ElasticSearch JSON, which probably isn't my > > > favorite > > > >>> choice, but it's there. > > > >>> > > > >>> > > > >>> The ElasticSearch match query syntax - > > > >>> > > > > https://urldefense.com/v3/__https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-match-query.html__;!!PbtH5S7Ebw!ZHwYJ2xkivwTzYgjkp5QFAzALXCWPqkga6GBD-m2aK3j06ioSCRPsdZD0CIe50VpRrtW-1rY_m6lrSpp7zVlAf0MsxZ9$ > > > >>> > > > >>> Again, not my favorite. It's verbose, and probably too powerful > for us. > > > >>> > > > >>> > > > >>> ElasticSearch's documentation for the basic Lucene query syntax - > > > >>> > > > > https://urldefense.com/v3/__https://www.elastic.co/guide/en/elasticsearch/reference/8.9/query-dsl-query-string-query.html*query-string-syntax__;Iw!!PbtH5S7Ebw!ZHwYJ2xkivwTzYgjkp5QFAzALXCWPqkga6GBD-m2aK3j06ioSCRPsdZD0CIe50VpRrtW-1rY_m6lrSpp7zVlAXEPP1sK$ > > > >>> > > > >>> One idea is to take the basic Lucene index, which it seems we > already > > > have > > > >>> some support for, and feed it to "expr". This is nice for two > reasons: > > > >>> > > > >>> 1.) People can just write Lucene queries if they already know how. > > > >>> 2.) No changes to the grammar. > > > >>> > > > >>> Lucene has distinct concepts of filtering and querying, and this is > > > kind of > > > >>> the latter. I'm not sure how, for example, we would want "expr" to > > > interact > > > >>> w/ filters on other column indexes in vanilla CQL space... > > > >>> > > > >>> > > > >>>> On Mon, Jul 24, 2023 at 9:37 AM Josh McKenzie < > jmcken...@apache.org> > > > wrote: > > > >>>> > > > >>>> `column CONTAINS term`. Contains is used by both Java and Python > for > > > >>>> substring searches, so at least some users will be surprised by > > > term-based > > > >>>> behavior. > > > >>>> > > > >>>> I wonder whether users are in their "programming language" > headspace > > > or in > > > >>>> their "querying a database" headspace when interacting with CQL? > i.e. > > > this > > > >>>> would only present confusion if we expected users to be thinking > in > > > the > > > >>>> idioms of their respective programming languages. If they're > thinking > > > in > > > >>>> terms of SQL, MATCHES would probably end up confusing them a bit > > > since it > > > >>>> doesn't match the general structure of the MATCH operator. > > > >>>> > > > >>>> That said, I also think CONTAINS loses something important that > you > > > allude > > > >>>> to here Jonathan: > > > >>>> > > > >>>> with corresponding query-time tokenization and analysis. This > means > > > that > > > >>>> the query term is not always a substring of the original string! > > > Besides > > > >>>> obvious transformations like lowercasing, you have things like > > > >>>> PhoneticFilter available as well. > > > >>>> > > > >>>> So to me, neither MATCHES nor CONTAINS are particularly great > > > candidates. > > > >>>> > > > >>>> So +1 to the "I don't actually hate it" sentiment on: > > > >>>> > > > >>>> column : term`. Inspired by Lucene’s syntax > > > >>>> > > > >>>> > > > >>>>> On Mon, Jul 24, 2023, at 8:35 AM, Benedict wrote: > > > >>>> > > > >>>> > > > >>>> I have a strong preference not to use the name of an SQL operator, > > > since > > > >>>> it precludes us later providing the SQL standard operator to > users. > > > >>>> > > > >>>> What about CONTAINS TOKEN term? Or CONTAINS TERM term? > > > >>>> > > > >>>> > > > >>>>> On 24 Jul 2023, at 13:34, Andrés de la Peña < > adelap...@apache.org> > > > wrote: > > > >>>> > > > >>>> > > > >>>> `column = term` is definitively problematic because it creates an > > > >>>> ambiguity when the queried column belongs to the primary key. For > some > > > >>>> queries we wouldn't know whether the user wants a primary key > query > > > using > > > >>>> regular equality or an index query using the analyzer. > > > >>>> > > > >>>> `term_matches(column, term)` seems quite clear and hard to > > > misinterpret, > > > >>>> but it's quite long to write and its implementation will be > > > challenging > > > >>>> since we would need a bunch of special casing around > SelectStatement > > > and > > > >>>> functions. > > > >>>> > > > >>>> LIKE, MATCHES and CONTAINS could be a bit misleading since they > seem > > > to > > > >>>> evoke different behaviours to what they would have. > > > >>>> > > > >>>> `column LIKE :term:` seems a bit redundant compared to just using > > > `column > > > >>>> : term`, and we are still introducing a new symbol. > > > >>>> > > > >>>> I think I like `column : term` the most, because it's brief, it's > > > similar > > > >>>> to the equivalent Lucene's syntax, and it doesn't seem to clash > with > > > other > > > >>>> different meanings that I can think of. > > > >>>> > > > >>>>> On Mon, 24 Jul 2023 at 13:13, Jonathan Ellis <jbel...@gmail.com> > > > wrote: > > > >>>> > > > >>>> Hi all, > > > >>>> > > > >>>> With phase 1 of SAI wrapping up, I’d like to start the ball > rolling on > > > >>>> aligning around phase 2 features. > > > >>>> > > > >>>> In particular, we need to nail down the syntax for doing non-exact > > > string > > > >>>> matches. We have a proof of concept that includes full Lucene > > > analyzer and > > > >>>> filter functionality – just the text transformation pieces, none > of > > > the > > > >>>> storage parts – which is the gold standard in this space. For > > > example, the > > > >>>> StandardAnalyzer [1] lowercases all terms and removes stopwords > > > (common > > > >>>> words like “a”, “is”, “the” that are usually not useful to search > > > >>>> against). Lucene also has classes that offer stemming, special > case > > > >>>> handling for email, and many languages besides English [2]. > > > >>>> > > > >>>> What syntax should we use to express “rows whose analyzed tokens > match > > > >>>> this search term?” > > > >>>> > > > >>>> The syntax must be clear that we want to look for this term > within the > > > >>>> column data using the configured index with corresponding > query-time > > > >>>> tokenization and analysis. This means that the query term is not > > > always a > > > >>>> substring of the original string! Besides obvious transformations > > > like > > > >>>> lowercasing, you have things like PhoneticFilter available as > well. > > > >>>> > > > >>>> Here are my thoughts on some of the options: > > > >>>> > > > >>>> `column = term`. This is what the POC does today and it’s super > > > confusing > > > >>>> to overload = to mean something other than exact equality. I am > not > > > a fan. > > > >>>> > > > >>>> `column LIKE term` or `column LIKE %term%`. The closest SQL > operator, > > > but > > > >>>> neither the wildcarded nor unwildcarded syntax matches the > semantics > > > of > > > >>>> term-based search. > > > >>>> > > > >>>> `column MATCHES term`. I rather like this one, although Mike > points > > > out > > > >>>> that “match” has a meaning in the context of regular expressions > that > > > could > > > >>>> cause confusion here. > > > >>>> > > > >>>> `column CONTAINS term`. Contains is used by both Java and Python > for > > > >>>> substring searches, so at least some users will be surprised by > > > term-based > > > >>>> behavior. > > > >>>> > > > >>>> `term_matches(column, term)`. Postgresql FTS makes you use > functions > > > like > > > >>>> this for everything. It’s pretty clunky, and we would need to > make > > > the > > > >>>> amazingly hairy SelectStatement even hairier to handle “use a > function > > > >>>> result in a predicate” like this. > > > >>>> > > > >>>> `column : term`. Inspired by Lucene’s syntax. I don’t actually > hate > > > it. > > > >>>> > > > >>>> `column LIKE :term:`. Stick with the LIKE operator but add a new > > > symbol to > > > >>>> indicate term matching. Arguably more SQL-ish than a new bare > symbol > > > >>>> operator. > > > >>>> > > > >>>> [1] > > > >>>> > > > > https://lucene.apache.org/core/9_7_0/core/org/apache/lucene/analysis/standard/StandardAnalyzer.html > > > >>>> [2] > https://lucene.apache.org/core/9_7_0/analysis/common/index.html > > > >>>> > > > >>>> -- > > > >>>> Jonathan Ellis > > > >>>> co-founder, http://www.datastax.com > > > >>>> @spyced > > > >>>> > > > >>>> > > > >>>> > > > >>> > > > > > > -- [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>
