It seems that the problem is when I add the token created by
EdgeNGramTokenizer in in the index.
If the token contains a space (for example apple com) I have to add to
the index with Field.Index.TOKENIZED otherwise the search cannot find it.
If there is no space there is no problem even if I use
Field.Index.UN_TOKENIZED.
So I'd like to know if there is speed search difference insertinf a
field as TOKENIZED or UN_TOKENIZED.
Best regards
Marco ha scritto:
Hi all,
I'm following the suggestion of this forum on how create a suggestion
service like google suggest.
I'm parsing a words/rank file with my words.
For each word, I'm adding a document with content and rank in in
index: then I create a EdgeNGramTokenizer of the word. This gives me N
words and I add each one in a new field of the index.
So for each word in the index I have:
- content (for example apple)
- rank
- X initial letters of the word (for example app)
- X+1 initial letters of the word (for example appl)
- X+2 initial letters of the word (for example apple)
....
- Y initial letters of the word (for example app)
I add each additional field in the index as:
doc.add(new Field(name_gram, tn.termText(), Field.Store.NO,
Field.Index.UN_TOKENIZED));
When an user search a word, for example app, I have to query the index
the right field.
I calculate the length of the input and the I query the right field
and the I get the content of the docs.
Is it ok?
For search I use:
String field_ok = field + line.length(); QueryParser parser = new
QueryParser(field_ok, analyzer);
Query query = parser.parse(line);
System.out.println("Searching for: " + query.toString(field_ok));
Hits hits = searcher.search(query, new Sort("rank", true));
All is ok if the input of the user doesn't contain spaces...
Am I missing something?
Best regards
Marco
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