8 May
2015
8 May
'15
8:10 p.m.
On 05/08/2015 05:22 AM, Marius Dumitru Florea wrote:
On Fri, May 8, 2015 at 10:39 AM, Sergiu Dumitriu
<sergiu(a)xwiki.org> wrote:
At the moment only English.
Well, my usecase is not the same, since I'm
indexing ontologies and the
end purpose is to find the best matching terms. A few numbers though:
- 4MB ontology with 11k terms ends up as 16M index (including
spellcheck, and most fields are also stored), searches take ~40ms
including the XWiki overhead, ~10ms just in Solr
- 180MB ontology with 24k terms -> 100M index, ~15ms Solr search time
For smaller indexes, it does seem to use more disk space than the
source, but Lucene is good at indexing larger data sets, and after a
while the index grows slower than the data.
For me it is worth the extra disk space, since
every user is amazed by
how good the search is at finding the relevant terms, overcoming typos,
synonyms, and abbreviations, plus autocomplete while typing.
You do this for multiple languages or just for English? In other
words, do you have text_fr_splitting, text_es_splitting etc.? Thanks Sergiu, I'll definitely take this into
account.
Marius
>
> In XWiki, not all fields should be indexed in all the ways, since it
> doesn't make sense to expect an exact match on a large textarea or the
> document content.
>
> On 05/07/2015 09:57 AM, Marius Dumitru Florea wrote:
>> Hi Sergiu,
>>
>> Can you tell us the effect on the index size (and speed in the end) if
>> each field (e.g. document title, a String or TextArea property) is
>> indexed in 5 different ways (5 separate fields in the index)? It is
>> worth having this configuration by default?
>>
>> Thanks,
>> Marius
>>
>> On Tue, May 5, 2015 at 4:57 PM, Sergiu Dumitriu <sergiu(a)xwiki.org> wrote:
>>> I agree with Paul.
>>>
>>> The way I usually do searches is:
>>>
>>> - each field gets indexed several times, including:
>>> -- exact matches ^5n (field == query)
>>> -- prefix matches ^1.5n (field ^= query)
>>> -- same spelling ^1.8n (query words in field)
>>> -- fuzzy matching ^n (aggressive tokenization and stemming)
>>> -- stub matching ^.5n (query tokens are prefixes of indexed tokens)
>>> -- and three catch-all fields where every other field gets copied, with
>>> spelling, fuzzy and stub variants
>>> - where n is a factor based on the field's importance: page title and
>>> name have the highest boost, a catch-all field has the lowest boost
>>> - search with edismax, pf with double the boost (2n) on
>>> exact,prefix,spelling,fuzzy and qf on spelling,fuzzy,stub
>>>
--
Sergiu Dumitriu
http://purl.org/net/sergiu