Elasticsearch has a builtin scoring algorithm which works quite well in practice, but sometimes you want to roll your own scoring algorithm. Let's examine how to create a custom scoring algorithm using the function score query.
Let's assume we want to search and score Perl job offers based on a set of weighted keyw…
We recently saw an example of an elasticsearch token filter called the catalan_stemmer. The Catalan language has other token filters available:
Let's see what they do.
The catalan_stop filter removes a list (common) of words. Given the example search:
porros amb balsàmic
applying the catalan_stop filter will remove the word amb/var/www/users/mateu/index.html
When dealing with elasticearch, one has to consider how they want to manage the analysis of the content that is ingested. The use of templates is a way to ease this burden of managing analyzer settings. Let's learn by example...
Here's a template that defines an analyzer, cat_stems, which utilizes the built-in catalan stemmer. For example, both singular: porro and plural: porros will be reduced to porr when analyzed by the stemmer. Moreover, this template will be applied to any index created with a name that starts with…
Yesterday we looked at an example of how to both index and search using elasticsearch. Today, we'll talk a little about what takes place during indexing, particularly tokenization. For example, what happens when we tokenize the phrase:
porros amb basàlmic
To find out we can pass the phrase to the elasticsearch analyzer API like so:
curl -XGET 'localhost:9200/_analyze?tokenizer=standard' -d 'porros amb balsàmic'
Elasticsearch és un motor de cerca. Fem un petit exemple com es pot utilitzar-ho. Necessitem unes dades per cercar, per tant agafem unes receptes d'internet, gràcies a http://receptes.cat. Un cop tenim les receptes, llavors les podem indexar en elasticsearch, després del qual podem cercar-les.
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