Introduction to Search

Liferay DXP contains a search engine based on Elasticsearch. You can extend it, implement search for your own applications, and it’s highly configurable.

Basic Search Concepts

Indexing: During indexing, a document is sent to the search engine. This document contains fields of various types (string, etc.). The search engine processes each field and determines whether to store the field or analyze it. Index time analysis can be configured for each field (see Mapping Definitions).

For fields requiring analysis, the search engine first tokenizes the value to obtain individual words or tokens. Then it passes each token through a series of analyzers, which perform different functions. Some remove common words or stop words (e.g., “the”, “and”, “or”) while others perform operations like lowercasing all characters.

Searching: Searching involves sending a search query and obtaining results (a.k.a. hits) from the search engine. The search query might contain both queries and filters (more on this later). Queries and filters specify a field to search within and the value to match against. The search engine iterates through each field within the nested queries and filters and may perform special analysis prior to executing the query (search time analysis). Search time analysis can be configured for each field (see Mapping Definitions).

Mapping Definitions

Mappings control how a search engine processes a given field. For instance, if a field name ends in “es_ES”, it should be processed as Spanish, removing any common Spanish words like “si”.

In Elasticsearch and Solr, the two supported search engines for Liferay DXP, mappings are defined in liferay-type-mappings.json and schema.xml, respectively.

The Elasticsearch mapping JSON file is in the Liferay DXP source code, in the portal-search-elasticsearch6 module:


The Solr schema.xml is in the portal-search-solr7 module’s source code:


Access the Solr 7 module’s source code from the liferay-portal repository here.

You can customize these mappings to fit your needs. For example, you might want to use a special analyzer for a custom inventory number field.

Liferay Search Infrastructure

Search engines already provide native APIs, but Liferay wraps the engine with a search infrastructure that does several things:

  1. Index documents with the fields Liferay needs (entryClassName, entryClassPK, assetTagNames, assetCategories, companyId, groupId, staging status, etc.).

  2. Apply the right filters to search queries (e.g., for scoping results).

  3. Apply permission checking on the results.

  4. Summarize returned results.

That’s just a taste of Liferay’s Search Infrastructure. Continue reading to learn more.

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