bq: FST-based vs AnalyzingInfix They are two totally different things. FST-based suggesters are very fast and compact. But they only match from the beginning of the input.
AnalyzingInfix creates a "sidecar" index that's searched like a normal index and the _field_ is returned. Thus analyzinginfix can suggest "my dog has fleas" when entering "fleas", but the FST-based suggesters cannot. Best, Erick On Thu, Apr 13, 2017 at 6:24 AM, OTH <omer.t....@gmail.com> wrote: > Thanks, that's very helpful! > The third link especially is quite helpful. > Is there any recommendation regarding using FST-based vs AnalyzingInfix > suggesters? > Thanks > > On Wed, Apr 12, 2017 at 6:23 PM, Andrea Gazzarini <gxs...@gmail.com> wrote: > >> Hi, >> I think you got an old post. I would have a look at the built-in feature, >> first. These posts can help you to get a quick overview: >> >> https://cwiki.apache.org/confluence/display/solr/Suggester >> http://alexbenedetti.blogspot.it/2015/07/solr-you-complete-me.html >> https://lucidworks.com/2015/03/04/solr-suggester/ >> >> HTH, >> Andrea >> >> >> On 12/04/17 14:43, OTH wrote: >> >>> Hello, >>> >>> Is there any recommended way to achieve auto-suggestion in textboxes using >>> Solr? >>> >>> I'm new to Solr, but right now I have achieved this functionality by using >>> an example I found online, doing this: >>> >>> I added a copy field, which is of the following type: >>> >>> <fieldType name="text_ngram" class="solr.TextField" >>> positionIncrementGap="100"> >>> <analyzer type="index"> >>> <tokenizer class="solr.NGramTokenizerFactory" minGramSize="2" >>> maxGramSize="10"/> >>> <filter class="solr.LowerCaseFilterFactory"/> >>> </analyzer> >>> <analyzer type="query"> >>> <tokenizer class="solr.EdgeNGramTokenizerFactory" minGramSize="2" >>> maxGramSize="10"/> >>> <filter class="solr.LowerCaseFilterFactory"/> >>> </analyzer> >>> </fieldType> >>> >>> In the search box, after each character is typed, the above field is >>> queried, and the results are shown in a drop-down list. >>> >>> However, this is performing quite slow. I'm not sure if that has to do >>> with the front-end code, or because I'm not using the recommended approach >>> in terms of how I'm using Solr. Is there any other recommended way to use >>> Solr to achieve this functionality? >>> >>> Thanks >>> >>> >>
