I wouldn’t worry about performance with that setup. I just checked on a production system with 13 million docs in four shards, so 3+ million per shard. I searched on the most common term in the title field and got a response in 31 milliseconds. This was probably not cached, because the collection gets frequent updates and is getting limited public traffic. That will change on Monday.
Make sure that you have more free RAM than the size of the index. Allow for the size of the JVM, OS, etc. Make sure you have plenty of CPU. After you have the RAM, CPU is the bottleneck. wunder Walter Underwood wun...@wunderwood.org http://observer.wunderwood.org/ (my blog) > On Oct 9, 2019, at 12:33 PM, David Hastings <hastings.recurs...@gmail.com> > wrote: > > yup. youre going to find solr is WAY more efficient than you think when it > comes to complex queries. > > On Wed, Oct 9, 2019 at 3:17 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com > <audrey.lorberf...@ibm.com> wrote: > >> True...I guess another rub here is that we're using the edismax parser, so >> all of our queries are inherently OR queries. So for a query like 'the ibm >> way', the search engine would have to: >> >> 1) retrieve a document list for: >> --> "ibm" (this list is probably 80% of the documents) >> --> "the" (this list is 100% of the english documents) >> -- >"way" >> 2) apply edismax parser >> --> foreach term >> --> --> foreach document in term >> --> --> --> score it >> >> So, it seems like it would take a toll on our system.... but maybe that's >> incorrect! (For reference, our corpus is ~5MM documents, multi-language, >> and we get ~80k-100k queries/day) >> >> Are you using edismax? >> >> -- >> Audrey Lorberfeld >> Data Scientist, w3 Search >> IBM >> audrey.lorberf...@ibm.com >> >> >> On 10/9/19, 3:11 PM, "David Hastings" <hastings.recurs...@gmail.com> >> wrote: >> >> if you have anything close to a decent server you wont notice it all. >> im >> at about 21 million documents, index varies between 450gb to 800gb >> depending on merges, and about 60k searches a day and stay sub second >> non >> stop, and this is on a single core/non cloud environment >> >> On Wed, Oct 9, 2019 at 2:55 PM Audrey Lorberfeld - >> audrey.lorberf...@ibm.com >> <audrey.lorberf...@ibm.com> wrote: >> >>> Also, in terms of computational cost, it would seem that including >> most >>> terms/not having a stop ilst would take a toll on the system. For >> instance, >>> right now we have "ibm" as a stop word because it appears everywhere >> in our >>> corpus. If we did not include it in the stop words file, we would >> have to >>> retrieve every single document in our corpus and rank them. That's a >> high >>> computational cost, no? >>> >>> -- >>> Audrey Lorberfeld >>> Data Scientist, w3 Search >>> IBM >>> audrey.lorberf...@ibm.com >>> >>> >>> On 10/9/19, 2:31 PM, "Audrey Lorberfeld - audrey.lorberf...@ibm.com" >> < >>> audrey.lorberf...@ibm.com> wrote: >>> >>> Wow, thank you so much, everyone. This is all incredibly helpful >>> insight. >>> >>> So, would it be fair to say that the majority of you all do NOT >> use >>> stop words? >>> >>> -- >>> Audrey Lorberfeld >>> Data Scientist, w3 Search >>> IBM >>> audrey.lorberf...@ibm.com >>> >>> >>> On 10/9/19, 11:14 AM, "David Hastings" < >> hastings.recurs...@gmail.com> >>> wrote: >>> >>> However, with all that said, stopwords CAN be useful in some >>> situations. I >>> combine stopwords with the shingle factory to create >> "interesting >>> phrases" >>> (not really) that i use in "my more like this" needs. for >> example, >>> europe for vacation >>> europe on vacation >>> will create the shingle >>> europe_vacation >>> which i can then use to relate other documents that would be >> much >>> more similar in such regard, rather than just using the >>> "interesting words" >>> europe, vacation >>> >>> with stop words, the shingles would be >>> europe_for >>> for_vacation >>> and >>> europe_on >>> on_vacation >>> >>> just something to keep in mind, theres a lot of creative >> ways to >>> use >>> stopwords depending on your needs. i use the above for a >> VERY >>> basic ML >>> teacher and it works way better than using stopwords, >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> On Wed, Oct 9, 2019 at 10:51 AM Erick Erickson < >>> erickerick...@gmail.com> >>> wrote: >>> >>>> The theory behind stopwords is that they are “safe” to >> remove >>> when >>>> calculating relevance, so we can squeeze every last bit of >>> usefulness out >>>> of very constrained hardware (think 64K of memory. Yes >>> kilobytes). We’ve >>>> come a long way since then and the necessity of removing >>> stopwords from the >>>> indexed tokens to conserve RAM and disk is much less >> relevant >>> than it used >>>> to be in “the bad old days” when the idea of stopwords was >>> invented. >>>> >>>> I’m not quite so confident as Alex that there is “no >> benefit”, >>> but I’ll >>>> totally agree that you should remove stopwords only >> _after_ you >>> have some >>>> evidence that removing them is A Good Thing in your >> situation. >>>> >>>> And removing stopwords leads to some interesting corner >> cases. >>> Consider a >>>> search for “to be or not to be” if they’re all stopwords. >>>> >>>> Best, >>>> Erick >>>> >>>>> On Oct 9, 2019, at 9:38 AM, Audrey Lorberfeld - >>>> audrey.lorberf...@ibm.com <audrey.lorberf...@ibm.com> >> wrote: >>>>> >>>>> Hey Alex, >>>>> >>>>> Thank you! >>>>> >>>>> Re: stopwords being a thing of the past due to the >>> affordability of >>>> hardware...can you expand? I'm not sure I understand. >>>>> >>>>> -- >>>>> Audrey Lorberfeld >>>>> Data Scientist, w3 Search >>>>> IBM >>>>> audrey.lorberf...@ibm.com >>>>> >>>>> >>>>> On 10/8/19, 1:01 PM, "David Hastings" < >>> hastings.recurs...@gmail.com> >>>> wrote: >>>>> >>>>> Another thing to add to the above, >>>>>> >>>>>> IT:ibm. In this case, we would want to maintain the >> colon and >>> the >>>>>> capitalization (otherwise “it” would be taken out as a >>> stopword). >>>>>> >>>>> stopwords are a thing of the past at this point. >> there is >>> no benefit >>>> to >>>>> using them now with hardware being so cheap. >>>>> >>>>> On Tue, Oct 8, 2019 at 12:43 PM Alexandre Rafalovitch >> < >>>> arafa...@gmail.com> >>>>> wrote: >>>>> >>>>>> If you don't want it to be touched by a tokenizer, how >> would >>> the >>>>>> protection step know that the sequence of characters >> you want >>> to >>>>>> protect is "IT:ibm" and not "this is an IT:ibm term I >> want to >>>>>> protect"? >>>>>> >>>>>> What it sounds to me is that you may want to: >>>>>> 1) copyField to a second field >>>>>> 2) Apply a much lighter (whitespace?) tokenizer to that >>> second field >>>>>> 3) Run the results through something like >>> KeepWordFilterFactory >>>>>> 4) Search both fields with a boost on the second, >>> higher-signal field >>>>>> >>>>>> The other option is to run CharacterFilter, >>>>>> (PatternReplaceCharFilterFactory) which is >> pre-tokenizer to >>> map known >>>>>> complex acronyms to non-tokenizable substitutions. E.g. >>> "IT:ibm -> >>>>>> term365". As long as it is done on both indexing and >> query, >>> they will >>>>>> still match. You may have to have a bunch of them or >> write >>> some sort >>>>>> of lookup map. >>>>>> >>>>>> Regards, >>>>>> Alex. >>>>>> >>>>>> On Tue, 8 Oct 2019 at 12:10, Audrey Lorberfeld - >>>>>> audrey.lorberf...@ibm.com <audrey.lorberf...@ibm.com> >> wrote: >>>>>>> >>>>>>> Hi All, >>>>>>> >>>>>>> This is likely a rudimentary question, but I can’t >> seem to >>> find a >>>>>> straight-forward answer on forums or the >> documentation…is >>> there a way to >>>>>> protect tokens from ANY analysis? I know things like the >>>>>> KeywordMarkerFilterFactory protect tokens from >> stemming, but >>> we have >>>> some >>>>>> terms we don’t even want our tokenizer to touch. Mostly, >>> these are >>>>>> IBM-specific acronyms, such as IT:ibm. In this case, we >> would >>> want to >>>>>> maintain the colon and the capitalization (otherwise >> “it” >>> would be taken >>>>>> out as a stopword). >>>>>>> >>>>>>> Any advice is appreciated! >>>>>>> >>>>>>> Thank you, >>>>>>> Audrey >>>>>>> >>>>>>> -- >>>>>>> Audrey Lorberfeld >>>>>>> Data Scientist, w3 Search >>>>>>> IBM >>>>>>> audrey.lorberf...@ibm.com >>>>>>> >>>>>> >>>>> >>>>> >>>> >>>> >>> >>> >>> >>> >>> >> >> >>
