bq: so I cannot copy this field to a text field with a
keywordtokenizer or strfield
1> There is no restriction on whether a field is analyzed or not as far as
faceting is concerned. You can freely facet on an analyzed field
or String field or KeywordTokenized field. As Binoy says, though,
faceting on large analyzed text fields is dangerous.
2> copyField directives are not chained. As soon as the
field is received, before _anything_ is done the raw contents are
pushed to the copyField destinations. So in your case the source
for both copyField directives should be "content". Otherwise you
get into interesting behavior if you, say, copyField from A to B and
have another copyField from B to A. I _suspect_ this is
why you have no term info available, but check....
3> This is not going to work as you're trying to implement it. If you
tokenize, the only available terms are "not" and "necessarily". There
is no "not necessarily" _token_ to facet on. If you use a String
or KeywordAnalylzed field, likewise there is no "not necessarily"
token, there will be a _single_ token that's the entire content of the field
(I'm leaving aside, for instance, WordDelimiterFilterFactory
modifications...).
One way to approach this would be to recognize and index synthetic
tokens representing the concepts. You'd pre-analyze the text, do your
entity recognition and add those entities to a special "entity" field or
some such. This would be an unanalyzed field that you facet on. Let's
say your entity was "colon cancer". Whenever you recognized that in
the text during indexing, you'd index "colon_cancer", or "disease_234"
in your special field.
Of course your app would then have to present this pleasingly, and
rather than the app needing access to your dictionary the "colon_cancer"
form would be easier to unpack.
The fragility here is that changing your text file of entities would require
you to re-index to re-inject them into documents.
You could also, assuming you know all the entities that should match
a given query form facet _queries_ on the phrases. This could get to be
quite a large query, but has the advantage of not requiring re-indexing.
So you'd have something like
facet.query=field:"not necessarily"&facet.query=field:certainly
etc.
Best,
Erick
On Mon, Dec 28, 2015 at 9:13 AM, Binoy Dalal <binoydala...@gmail.com> wrote:
> 1) When faceting use field of type string. That'll rid you of your
> tokenization problems.
> Alternatively do not use any tokenizers.
> Also turn doc values on for the field. It'll improve performance.
> 2) If however you do need to use a tokenized field for faceting, make sure
> that they're pretty short in terms of number of tokens or else your app
> will die real soon.
>
> On Mon, 28 Dec 2015, 22:24 Kevin Lopez <kevin.lopez...@gmail.com> wrote:
>
>> I am not sure I am following correctly. The field I upload the document to
>> would be "content" the analyzed field is "ColonCancerField". The "content"
>> field contains the entire text of the document, in my case a pubmed
>> abstract. This is a tokenized field. I made this field untokenized and I
>> still received the same results [the results for not instead of not
>> necessarily (in my current example I have 2 docs with not and 1 doc with
>> not necessarily {not is of course in the document that contains not
>> necessarily})]:
>>
>> http://imgur.com/a/1bfXT
>>
>> I also tried this:
>>
>> http://localhost:8983/solr/Cytokine/select?&q=ColonCancerField
>> :"not+necessarily"
>>
>> I still receive the two documents, which is the same as doing
>> ColonCancerField:"not"
>>
>> Just to clarify the structure looks like this: *content (untokenized,
>> unanalyzed)* [copied to]==> *ColonCancerField *(tokenized, analyzed) then I
>> browse the ColonCancerField and the facets state that there is 1 document
>> for not necessarily, but when selecting it, solr returns 2 results.
>>
>> -Kevin
>>
>> On Mon, Dec 28, 2015 at 10:22 AM, Jamie Johnson <jej2...@gmail.com> wrote:
>>
>> > Can you do the opposite? Index into an unanalyzed field and copy into
>> the
>> > analyzed?
>> >
>> > If I remember correctly facets are based off of indexed values so if you
>> > tokenize the field then the facets will be as you are seeing now.
>> > On Dec 28, 2015 9:45 AM, "Kevin Lopez" <kevin.lopez...@gmail.com> wrote:
>> >
>> > > *What I am trying to accomplish: *
>> > > Generate a facet based on the documents uploaded and a text file
>> > containing
>> > > terms from a domain/ontology such that a facet is shown if a term is in
>> > the
>> > > text file and in a document (key phrase extraction).
>> > >
>> > > *The problem:*
>> > > When I select the facet for the term "*not necessarily*" (we see there
>> > is a
>> > > space) and I get the results for the term "*not*". The field is
>> tokenized
>> > > and multivalued. This leads me to believe that I can not use a
>> tokenized
>> > > field as a facet field. I tried to copy the values of the field to a
>> text
>> > > field with a keywordtokenizer. I am told when checking the schema
>> > browser:
>> > > "Sorry, no Term Info available :(" This is after I delete the old index
>> > and
>> > > upload the documents again. The facet is coming from a field that is
>> > > already copied from another field, so I cannot copy this field to a
>> text
>> > > field with a keywordtokenizer or strfield. What can I do to fix this?
>> Is
>> > > there an alternate way to accomplish this?
>> > >
>> > > *Here is my configuration:*
>> > >
>> > > <copyField source="ColonCancerField" dest="cytokineField"/>
>> > >
>> > > <field name="cytokineField" indexed="true" stored="true"
>> > > multiValued="true" type="Cytokine_Pass"/>
>> > > <fieldType name="Cytokine_Pass" class="solr.TextField">
>> > > <analyzer>
>> > > <tokenizer class="solr.KeywordTokenizerFactory" />
>> > > </analyzer>
>> > > </fieldType>
>> > >
>> > > <field name="ColonCancerField" type="ColonCancer" indexed="true"
>> > > stored="true" multiValued="true"
>> > > termPositions="true"
>> > > termVectors="true"
>> > > termOffsets="true"/>
>> > > <fieldType name="ColonCancer" class="solr.TextField"
>> > > sortMissingLast="true" omitNorms="true">
>> > > <analyzer>
>> > > <filter class="solr.ShingleFilterFactory"
>> > > minShingleSize="2" maxShingleSize="5"
>> > > outputUnigramsIfNoShingles="true"
>> > > />
>> > > <tokenizer class="solr.WhitespaceTokenizerFactory"/>
>> > > <filter class="solr.LowerCaseFilterFactory"/>
>> > > <filter class="solr.SynonymFilterFactory"
>> > > synonyms="synonyms_ColonCancer.txt" ignoreCase="true" expand="true"
>> > > tokenizerFactory="solr.KeywordTokenizerFactory"/>
>> > > <filter class="solr.KeepWordFilterFactory"
>> > > words="prefLabels_ColonCancer.txt" ignoreCase="true"/>
>> > > </analyzer>
>> > > </fieldType>
>> > > <copyField source="content" dest="ColonCancerField"/>
>> > >
>> > > Regards,
>> > >
>> > > Kevin
>> > >
>> >
>>
> --
> Regards,
> Binoy Dalal
