# Indexes

An index is an entity that gathers a set of documents with its own settings.

It can be comparable to a table in SQL, or a collection in MongoDB.

An index is defined by an uid and contains the following information:

  • One
  • Default settings that can be configured as needed: relevancy rules, synonyms, stop words, and field properties.

# Example

Suppose you manage a database that contains information about movies. You would probably want to have multiple categories: one for movie descriptions, one for actors, one for costumes and one for reviews. Each of these categories would be represented by an index in MeiliSearch.

Each index holds information about the fields found in the documents, how they get handled by MeiliSearch, and their order of importance. Besides, an index defines its own synonyms, relevancy rules, and stop words. The settings of one index don't impact other indexes.

For example, it means you could create on the same server synonyms for a movie index and different synonyms for a costumes index.

# Index Creation

An index is created the first time documents are added to it or manually using the create index endpoint.

# Example

Working on a fresh MeiliSearch instance with no indexes, let's add documents using the add or replace documents endpoint.
We provide movie as our index name. Because there's currently no index of that name in our MeiliSearch instance, using the following code will:

  1. Create the movie index.
  2. Add the documents to it.

# Index UID

The uid is the unique identifier of a given index. It is used on every indexes/:index_uid route as the :index_uid parameter.

The uid is set at index creation time. Once a uid has been defined for an index, you cannot create another index with the same uid and the identifier cannot be changed anymore.

{
  "uid": "movie",
  "createdAt": "2019-11-20T09:40:33.711324Z",
  "updatedAt": "2019-11-20T10:16:42.761858Z"
}

# Primary key

An index is a collection of documents. All documents have a primary key, which is a mandatory . This field is composed of a primary key name and a unique value. All documents in a given index share the same primary key attribute but a different unique value.

The primary key's attribute name must be known by the index. You can set a primary key for an index or let it be inferred by MeiliSearch.

Learn more about document primary key

# Relevancy rules

Each index applies its own relevancy rules. All indexes are created with the same built-in executed in a default order. Once your first document has been added, the index will record how the attributes must be sorted. Their order of importance will be deduced from their order of appearance in the document.

For example, if in your first document attributes are listed as follows: id, title, description, release_date, any document containing the matching query in title will be considered more relevant than a document containing it in description.

On top of that, you can add your custom rules to the ranking rules. For example, you may want to rank your movies either by release date or popularity, or both and so on. Rules are customizable so the results meet your user's needs as close as possible.

Learn more about ranking rules

# Synonyms

In your dataset, you may decide to create synonyms for words which have the same meaning. To do so, a set of synonyms can be defined for an index. Even though they are different, they should be treated similarly. If either of the associated words is searched, the same results shall be displayed.

Since synonyms are linked to a given index, they won't apply to any other index on the same MeiliSearch instance.

Learn more about synonyms

# Stop words

Sometimes you may want to ignore certain words in documents and search queries. To do so, a set of stop words can be defined for an index. Unless you actually need them, some words neither add semantic value nor context. Besides, they are often too frequent (i.e., the or of in English).

By adding words to a stop words list, these specific terms will be ignored during search. It will avoid documents being considered highly relevant because of the presence of some words in an important attribute or in a good position. This will also greatly improve the response time because all the documents that contain only those words will not be used for documents sorting.

For example, suppose you would perform the following search query: the great gatsby. Having the word the in a film review wouldn't make the review more relevant. By adding the to the stop word list, performance would be increased and search results more relevant.

Learn more about stop words

# Field properties

By default, every document field is searchable and returned on search queries.

Fields can have either or both or none of the following properties that can be modified in the settings:

  • Searchable: The content of searchable fields is used by MeiliSearch to assess the relevancy of a document.
  • Displayed: Documents returned upon search contain only displayed fields.

By default, each field is stored and this behavior cannot be changed.

Learn more about field properties

Last Updated: 11/10/2020, 3:09:11 PM