Hello, >From what I understand, the AnalyzingInfixSuggester is using a simple Lucene query; so I was wondering, how then would this suggester have better performance than using a simple Solr 'select' query on a regular Solr index (with an asterisk placed at the start and end of the query string). I could understand why say an FST based suggester would be faster, but I wanted to confirm if that indeed is the case with AnalyzingInfixSuggester.
One reason I ask is: I needed the results to be boosted based on the value of another field; e.g., if a user in the UK is searching for cities, then I'd need the cities which are in the UK to be boosted. I was able to do this with a regular Solr index by adding something like these parameters: defType=edismax&bq=country:UK^2.0 However, I'm not sure if this is possible with the Suggester. Moreover - other than the 'country' field above, there are other fields as well which I need to be returned with the results. Since the Suggester seems to only allow one additional field, called 'payload', I'm able to do this by putting the values of all the other fields into a JSON and then placing that into the 'payload' field - however, I don't know if it would be possible then to incorporate the boosting mechanism I showed above. So I was thinking of just using a regular Solr index instead of the Suggester; I wanted to confirm, what if any is the performance improvement in using the AnalyzingInfixSuggester over using a regular index? Much thanks
