RuleFor(p => p.Store, f => f.PickRandom(stores)) RuleFor(p => p.Category, f => f.PickRandom(categories)) RuleFor(p => p.Brand, f => f.PickRandom(brands)) RuleFor(p => p.Description, f => f.Lorem.Sentence(f.Random.Int(5, 20))) RuleFor(p => p.Name, f => f.Commerce.ProductName()) There are some default analyzers ready to use but, to improve the accuracy of our searches based on our requirements, we created a custom analyzer.Ī custom analyzer allows us to take control, during the analysis process, of any change to document before tokenizing, of how it’s been converted to a token, and how it’s normalized. An analyzer performs this process.Īn analyzer is build up by three main components: That is a process with the first phase of tokenization (splitting text into small chunks, called token) and another one of normalization (it allows you to find matches to tokens that are not equal to searched words, but similar enough to be relevant) of text indexed for search. Searching process, as described in the last article, is based on document analysis. In this way, we defined the indexing process so that we get a document list indexed as we want.Īfter indexing documents with the created pipeline, we can check them by visiting with a browser We obtain a result similar to this:
CONTEXT SUGGESTER ELASTICSEARCH CODE
In our example, we used the same node both for searching and for ingesting, we don’t need to write code for managing the ingest node, but, if we want to have a set of dedicated ingest nodes, we have to configure the ElasticSearch client as follows: The ingest has to be enabled in the configuration file elasticsearch.yml, by this parameter: The ingest node intercepts all indexing requests, even the bulk ones, and applies all defined transformations on its content, then it gives back the documents to indexing API. In order to make possible the processing of our products before indexing, a useful way is the ingest node, that is a node where the document pre-processing takes place. We create, specifically for the ElasticSearch index, a new property named fullname for User class named fullname, and we defined which are the geographic info that will be processed.
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