It has been a while since I used a custom similarity, but what you have
looks right. Can you try a full class name instead?
Use org.elasticsearch.index.similarity.tfCappedSimilarityProvider.
According to the error, it is looking for org.elasticsearch.index.
similarity.tfcappedsimilarity.tfCappedSimilaritySimilarityProvider.
--
Ivan
On Tue, Apr 1, 2014 at 7:00 AM, geantbrun <agin.patr...@gmail.com> wrote:
> Sure.
>
> {
> "settings" : {
> "index" : {
> "similarity" : {
> "my_similarity" : {
> "type" : "tfCappedSimilarity"
> }
> }
> }
> },
> "mappings" : {
> "post" : {
> "properties" : {
> "id" : { "type" : "long", "store" : "yes", "precision_step" : "0" },
> "name" : { "type" : "string", "store" : "yes", "index" : "analyzed"},
> "contents" : { "type" : "string", "store" : "no", "index" :
> "analyzed", "similarity" : "my_similarity"}
> }
> }
> }
> }
>
> If I substitute tfCappedSimilarity for tfCapped in the mapping, the error
> is the same except that provider is referred as tfCappedSimilarityProviderand
> not as
> tfCappedSimilaritySimilarityProvider.
> Cheers,
> Patrick
>
>
> Le lundi 31 mars 2014 17:13:24 UTC-4, Ivan Brusic a écrit :
>>
>> Can you also post your mapping where you defined the similarity?
>>
>> --
>> Ivan
>>
>>
>> On Mon, Mar 31, 2014 at 10:36 AM, geantbrun <agin.p...@gmail.com> wrote:
>>
>>> I realize that I probably have to define the similarity property of my
>>> field as "my_similarity" (and not as "tfCappedSimilarity") and define in
>>> the settings my_similarity as being of type tfCappedSimilarity.
>>> When I do that, I get the following error at the index/mapping creation:
>>>
>>> {"error":"IndexCreationException[[exbd] failed to create index];
>>> nested: NoClassSettingsException[Failed to load class setting [type]
>>> with value [tfCappedSimilarity]]; nested: ClassNotFoundException[org.
>>> elasticsearch.index.similarity.tfcappedsimilarity.
>>> tfCappedSimilaritySimilarityProvider]; ","status":500}]
>>>
>>> Note that the provider is referred in the error as
>>> tfCappedSimilaritySimilarityProvider (similarity repeated 2 times). Is
>>> it normal?
>>> Patrick
>>>
>>> Le lundi 31 mars 2014 13:06:00 UTC-4, geantbrun a écrit :
>>>
>>>> Hi Ivan,
>>>> I followed your instructions but it does not seem to work, I must be
>>>> wrong somewhere. I created the jar file from the following two java files,
>>>> could you tell me if they are ok?
>>>>
>>>> tfCappedSimilarity.java
>>>> ***************************
>>>> package org.elasticsearch.index.similarity;
>>>>
>>>> import org.apache.lucene.search.similarities.DefaultSimilarity;
>>>> import org.elasticsearch.common.logging.ESLogger;
>>>> import org.elasticsearch.common.logging.Loggers;
>>>>
>>>> public class tfCappedSimilarity extends DefaultSimilarity {
>>>>
>>>> private ESLogger logger;
>>>>
>>>> public tfCappedSimilarity() {
>>>> logger = Loggers.getLogger(getClass());
>>>> }
>>>>
>>>> /**
>>>> * Capped tf value
>>>> */
>>>> @Override
>>>> public float tf(float freq) {
>>>> return (float)Math.sqrt(Math.min(9, freq));
>>>> }
>>>> }
>>>>
>>>> tfCappedSimilarityProvider.java
>>>> *************************************
>>>> package org.elasticsearch.index.similarity;
>>>>
>>>> import org.elasticsearch.common.inject.Inject;
>>>> import org.elasticsearch.common.inject.assistedinject.Assisted;
>>>> import org.elasticsearch.common.settings.Settings;
>>>>
>>>> public class tfCappedSimilarityProvider extends
>>>> AbstractSimilarityProvider {
>>>>
>>>> private tfCappedSimilarity similarity;
>>>>
>>>> @Inject
>>>> public tfCappedSimilarityProvider(@Assisted String name,
>>>> @Assisted Settings settings) {
>>>> super(name);
>>>> this.similarity = new tfCappedSimilarity();
>>>> }
>>>>
>>>> /**
>>>> * {@inheritDoc}
>>>> */
>>>> @Override
>>>> public tfCappedSimilarity get() {
>>>> return similarity;
>>>> }
>>>> }
>>>>
>>>>
>>>> In my mapping, I define the similarity property of my field as
>>>> tfCappedSimilarity, is it ok?
>>>>
>>>> What makes me say that it does not work: I insert a doc with a word
>>>> repeated 16 times in my field. When I do a search with that word, the
>>>> result shows a tf of 4 (square root of 16) and not 3 as I was expecting, Is
>>>> there a way to know if the similarity was loaded or not (maybe in a log
>>>> file?).
>>>>
>>>> Cheers,
>>>> Patrick
>>>>
>>>> Le mercredi 26 mars 2014 17:16:36 UTC-4, Ivan Brusic a écrit :
>>>>>
>>>>> I updated my gist to illustrate the SimilarityProvider that goes along
>>>>> with it. Similarities are easier to add to Elasticsearch than most
>>>>> plugins.
>>>>> You just need to compile the two files into a jar and then add that jar
>>>>> into Elasticsearch's classpath ($ES_HOME/lib most likely). The code will
>>>>> scan for every SimilarityProvider defined and load it.
>>>>>
>>>>> You then mapping the similarity to a field: http://www.elasticsearc
>>>>> h.org/guide/en/elasticsearch/reference/current/mapping-core-types.
>>>>> html#_configuring_similarity_per_field
>>>>>
>>>>> Note that you cannot change the similarity of a field dynamically.
>>>>>
>>>>> Ivan
>>>>>
>>>>>
>>>>> http://www.elasticsearch.org/guide/en/elasticsearch/referenc
>>>>> e/current/mapping-core-types.html#_configuring_similarity_per_field
>>>>>
>>>>>
>>>>> On Wed, Mar 26, 2014 at 12:49 PM, geantbrun <agin.p...@gmail.com>wrote:
>>>>>
>>>>>> Britta is looping over words that are passed as parameters. It's easy
>>>>>> to implement her script for a simple query but what about boolean querys?
>>>>>> In my understanding (but I could be wrong of course), I would have to
>>>>>> parse
>>>>>> the query to call the script with each sub-clause, am I wrong?
>>>>>>
>>>>>> I prefer your custom similarity alternative. Again, sorry for the
>>>>>> silly question (newbie!) but where do you put your java file? Is it the
>>>>>> only thing that is needed (except for the modification in the mapping)?
>>>>>> cheers,
>>>>>> Patrick
>>>>>>
>>>>>> Le mercredi 26 mars 2014 11:58:52 UTC-4, Ivan Brusic a écrit :
>>>>>>>
>>>>>>> I am still on a version of Elasticsearch that does not have access
>>>>>>> to the new scoring capabilities, so I cannot test out any scripts. The
>>>>>>> non
>>>>>>> normalized term frequency should be the line:
>>>>>>> tf = _index[field][word].tf()
>>>>>>>
>>>>>>> If that is the case, you could substitute that line with something
>>>>>>> like:
>>>>>>> tf = Math.min(10, _index[field][word].tf())
>>>>>>>
>>>>>>> As a stated before, I am used to using Similarities, so I find the
>>>>>>> example easier. Here is a custom similarity that I used in Elasticsearch
>>>>>>> (removes any norms that are indexed):
>>>>>>> https://gist.github.com/brusic/9786587
>>>>>>>
>>>>>>> The second part would be the tf() method you would need to implement
>>>>>>> instead of decodeNormValue I used.
>>>>>>>
>>>>>>> Cheers,
>>>>>>>
>>>>>>> Ivan
>>>>>>>
>>>>>>
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>>
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