search for: topdocs

...er understanding of how Java Lucene implements its search methods, I realized that one level of abstraction is not present in the Ferret classes/methods. Here are the relevant method signatures: Ferret''s search methods: in Ferret::Index::Index: search(query, options = {}) -> returns a TopDocs search_each(query, options = {}) {|doc, score| ...} -> yields to context w/ doc and score for each hit in Ferret::Search::IndexSearcher: search(query, options = {}) -> returns a TopDocs search_each(query, filter = nil) {|doc, score| ...} -> yields to context w/ doc and score for each hit...

...walker", "Top daw g dog walker"].each {|text| i << text } => ["While you were out pet care", "Eastside dog walker", "Top dawg dog walker"] *** Now let''s do some searches *** irb(main):006:0> puts i.search(''pet'') TopDocs: total_hits = 1, max_score = 0.878416 [ 0 "While you were out pet care": 0.878416 ] => nil irb(main):007:0> puts i.search(''dog'') TopDocs: total_hits = 2, max_score = 0.500000 [ 1 "Eastside dog walker": 0.500000 2 "Top dawg dog walker": 0.500...

...uot;}, {:num => 1000, :data => "yes"}, {:num => 1000, :data => "no"} ] ?> puts index.process_query(''data:yes AND num:[10 100]'') +data:yes +num:[10 100] => nil >> puts index.search(''d:data:yes AND num:[10 100]'') TopDocs: total_hits = 2, max_score = 1.777895 [ 2 "": 1.777895 4 "": 1.777895 ] => nil >> puts index.process_query(''data:yes AND num:[2 100]'') num:"data yes <> num 2 100"~4 => nil >> puts index.process_query(...

Hi, i''m working on a project using Ferret for indexing it''s datas. I''m very happy with it but i need to code an extension to implement a .to_json method to TopDocs class, because ruby''s json implementation is really really slow... It''s my second (the first was the tutorial :/ ) ruby C extension, so i''m not really at ease with ruby C bindings, even with the C experience... Here is my problem : I would like to load each document...

...ng a search string seems to always work whereas using a TermQuery often doesn''t return any entries. For example: > x=@i[450][:message_id] => "9e7db9110509070759732b21c4 at mail.gmail.com" > @i.search("message_id:#{x}") => #<struct Ferret::Search::TopDocs total_hits=1, hits=[#<struct Ferret::Search::Hit doc=450, score=6.51688194274902>], max_score=6.51688194274902> > @i.search(Ferret::Search::TermQuery.new(:message_id, x)) => #<struct Ferret::Search::TopDocs total_hits=0, hits=[], max_score=0.0> But sometimes it works fine:...

Is there a fast way to determine how many documents a term occurs in, besides iterating through every document with TermDocEnum? -- Best regards, Stian Gryt?yr

I''m trying to generate a rails pagination helper for some ferret search results, and I need to know how many total matches there are to my search query. I don''t see an obvious way of finding this. Any help would be appreciated. Thanks, Carl Youngblood

Hi James, > ID: some identifier for each query > QUERY: text of the query (when the query is run) > URLs: every URL displayed (or alternatively, the Xapian docid — this > might be easier) > OFFSET: otherwise you'll have difficulty coping with result pages other > than the first page (when this happens, the query ID should probably > remain the same, and when you aggregate

I can consistently segfault the 0.10.4 gem, so I''m trying to get the subversion version working with hopes towards tracking the problem down. I have a fresh SVN checkout but: a) the version (in ferret.rb) claims to be 0.9.6; and b) Ferret::Index::FieldInfos and a couple other classes are missing at run time. It looks like this is because they''re not exported in the C

> In case I wasn't clear: I don't think you have to modify the command > at all. Just create a template that uses the command as it currently > works. I thought we needed a new template only for the second log file? To generate the first log file using the existing $log command, I have introduced another $log command in query template that looks like:

Here''s the deal: static TopDocs *isea_search_w(Searcher *self, Weight *weight, int first_doc, // OFFSET int num_docs, // LIMIT Filter *filter, Sort *sort,...

...Writer.new(:path => "/tmp/test") index_writer.add_readers(readers) index_writer.close() readers.each {|reader| reader.close()} i = Ferret::I.new(:path => ''/tmp/test'') res = i.search(''name*'') puts res.inspect # gives me: #<struct Ferret::Search::TopDocs total_hits=0, hits=[], max_score=0.0, searcher=#<Ferret::Search::Searcher:0x58a6ec>> puts res.hits.size # gives me: 0

I've just noticed the Omega "opensearch" template seems to lack escaping for URLs in <link> tags: $httpheader{Content-Type,application/xml}<?xml version="1.0"?> <rss version="2.0" xmlns:openSearch="http://a9.com/-/spec/opensearchrss/1.0/"> <channel> <title>Xapian search results</title>

Folks, Having trouble getting this to work. OMEGA cgi is not reading my stub file properly because it is trying to read it as a directory instead of a file. Is there an easy fix? Here is a transcript. Thanks, OSC oscar@epsilon:/svr/xapian/beta$ ls -aFl total 21335200 drwxr-xr-x 2 oscar oscar 4096 Aug 6 10:15 ./ drwxr-xr-x 5 oscar oscar 4096 Aug 6 12:59 ../ lrwxrwxrwx 1 oscar

> > I'm not clear on what the OFFSET really represents. Could you > > please explain a bit? > > Omega paginates results (as does Xapian's MSet, internally). So if > you're displaying the second page of results, you'll need to know > that when building training data. It's affected by TOPDOC and also > by the <>[# CGI variables, but internally to

> There's a lot of flexibility already, because the log format is just > omegascript. So I don't think you need to implement a new command to > achieve this. (Although you might need a command to generate the query > id. It depends on how you're going to do that.) Ok, I'll try adapting the existing log command to achieve the kind of logging we want. And, about the

hi, ive been reading up on ferret, acts_as_ferret, and other search plugins for rails. after reading about ferret, i found out about the acts_as_ferrt plugin. my first question about acts_as_ferret: 1. from reading about ferret, do i still need to manually save the IDX and add a IDX column field to my model table for acts_as_ferret to work? they say that acts_as_ferret handles everything,

...erialized, such that a long search would cause others to wait noticeably. Anyhow, after coding both :limit and applying homegrown thread time limit monitoring, I discovered that Searcher#search_each uses rb_thread_critical = Qtrue whereas Searcher#search doesn''t. I changed my code to use TopDocs and Searcher#search and viola, concurrent searches! Cheers, Nevill

Sorry if this has been beaten to death here but I couldn''t find the exact answer I was looking for. In the app I''m writing, we convert the score to a percentage and display it with the search results. The problem is when you search for an exact phrase (for example) and it matches the title of a document exactly, you only get a 17% match. Has anyone seen a way to either curve

...type => hardware or mixed datas. We''ve got around 12400 docs with this type, here are the queries (THEY ARE ALL LAUNCHED IN A _NEW_ INSTANCE OF FERRET ! (with the same index of course)): this one works fine : >> INDEX.search(''type:hardware'').to_s => "TopDocs: total_hits = 12490, max_score = 1.751220 [\n\t13997 \"61426\": 1.751220\n\t13998 \"61427\": 1.751220\n\t13999 \"61428\": 1.751220\n\t14000 \"61429\": 1.751220\n\t14001 \"61430\": 1.751220\n\t14002 \"61431\": 1.751220\n\t14003 \"61...