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From Ian Lea <ian....@gmail.com>
Subject Re: Spell check on a subset of an index ( 'namespace' aware spell checker)
Date Tue, 06 Dec 2011 14:40:30 GMT
There are utilities floating around for getting output from analyzers
- would that help?  I think there are some in LIA, probably others
elsewhere.  The idea being that you grab the stored fields from the
index, pass them through your analyzer, grab the output and use that.

Or can you do something with TermEnum and/or TermDocs.  Not sure
exactly what or how though ...


--
Ian.

On Tue, Dec 6, 2011 at 2:20 PM, E. van Chastelet
<evanchastelet@gmail.com> wrote:
> I'm still struggling with this.
>
> I've tried to implement the solution mentioned in previous reply, but
> unfortunately there is a blocking issue with this:
> I cannot find a way to create another index from the source index in a way
> that the new index has the field values in it. The only way to copy
> document's field values from one to another index is to have stored fields.
> But stored fields hold "the original String in its entirety", and not the
> analyzed String, which I need. Is there another way to copy documents with
> (at least the spellcheck field) from the one to another index?
>
> Recap:
> I have a source index holding documents for different namespaces. These
> documents hold one field (analyzed) that should be used for spell checking.
> I want to construct an spellchecker index for each namespace separately. To
> accomplish this, I first get the list of namespaces (each document has a
> namespace field in the original index). Then, for each namespace, I get the
> list of documents that match this namespace. Then I'd like to use this
> subset to construct a spellchecker index.
>
> Regards,
> Elmer
>
>
> On 11/23/2011 03:28 PM, E. van Chastelet wrote:
>>
>> I currently have an idea to get it done, but it's not a nice solution.
>>
>> If we have an index Q with all documents for all namespaces, we first
>> extract the list of all terms that appear for the field namespace in Q (this
>> field indicates the namespace of the document).
>>
>> Then, for each namespace n in the terms list:
>>  - Get all docs from Q that match +namespace:n
>>  - Construct a temporary index from these docs
>>  - Use this temporary index to construct the dictionary, which the
>> SpellChecker can use as input.
>>  - Call indexDictionary on SpellChecker to create spellcheck index for
>> current namespace.
>>  - Delete temporary index
>>
>> We now have separate spell check indexes for each namespace.
>>
>> Any suggestions for a cleaner solution?
>>
>> Regards,
>> Elmer van Chastelet
>>
>>
>>
>> On 11/10/2011 01:16 PM, E. van Chastelet wrote:
>>>
>>> Hi all,
>>>
>>> In our project we like to have the ability to get search results scoped
>>> to one 'namespace' (as we call it). This can easily be achieved by using a
>>> filter or just an additional must-clause.
>>> For the spellchecker (and our autocompletion, which is a modified
>>> spellchecker), the story seems different. The spell checker index is created
>>> using a LuceneDictionary, which has a IndexReader as source. We would like
>>> to get (spellcheck/autocomplete) suggestions that are scoped to one
>>> namespace (i.e. field 'namespace' should have a particular value).
>>> With a single source index containing docs for all namespaces, it seems
>>> not possible to create a spellcheck index for each namespace the ordinary
>>> way.
>>> Q1: Is there a way to construct a LuceneDictionary from a subset of a
>>> single source index (all terms where namespace = %value%) ?
>>>
>>> Another, maybe better solution is to customize the spellchecker by adding
>>> an additional namespace field to the spellchecker index. At query-time, an
>>> additional must-clause is added, scoping the suggestions to one (or more)
>>> namespace(s). The advantage of this is to have a singleton spellchecker (or
>>> at least the index reader) for all namespaces. This also means less open
>>> files by our application (imagine if there are over 1000 namespaces).
>>> Q2: Will there be a significant penalty (say more than 50% slower) for
>>> the additional must-clause at query time?
>>>
>>> Q3: Or can you think of a better solution for this problem? :)
>>>
>>> How we currently do it: we currently use Lucene 3.1 with Hibernate Search
>>> and we actually already have auto completion and spell checking scoped to
>>> one namespace. This is currently achieved by using index sharding, so each
>>> namespace has its own index and reader, and another for spell check and auto
>>> completion. Unfortunately there are some downsides to this:
>>> - Our faceting engine has no good support for multiple indexes, so
>>> faceting only works on a single namespace
>>> - Needs administration for mapping namespace identifier (String) to index
>>> number (integer)
>>> - The number of shards (and thus name spaces) is currently hardcoded. At
>>> this moment it is set to 100, and this means Hibernate Search opens up 100
>>> index readers/writers, while only n<100 are in use. and therfore:
>>> - Much open file descriptors
>>> - Hard limit on number of namespaces
>>>
>>> Therefore it seems better to switch back to having a single index for all
>>> namespaces.
>>>
>>> Thanks!
>>>
>>> Regards,
>>> Elmer van Chastelet
>>>
>>
>
>
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