Searching with query rulesedit

This functionality is in technical preview and may be changed or removed in a future release. Elastic will apply best effort to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.

Query rules allow customization of search results for queries that match specified criteria metadata. This allows for more control over results, for example ensuring that promoted documents that match defined criteria are returned at the top of the result list. Metadata is defined in the query rule, and is matched against the query criteria. Query rules use metadata to match a query. Metadata is provided as part of the rule_query as an object and can be anything that helps differentiate the query, for example:

  • A user-entered query string
  • Personalized metadata about users (e.g. country, language, etc)
  • A particular topic
  • A referring site
  • etc.

Query rules define a metadata key that will be used to match the metadata provided in the rule_query with the criteria specified in the rule.

When a query rule matches the rule_query metadata according to its defined criteria, the query rule action is applied to the underlying organic_query.

For example, a query rule could be defined to match a user-entered query string of pugs and a country us and promote adoptable shelter dogs if the rule query met both criteria.

Rules are defined using the query rules API and searched using the rule query.

Rule definitionedit

When defining a rule, consider the following:

Rule typeedit

The type of rule we want to apply. For the moment there is a single rule type:

  • pinned will re-write the query into a pinned query, pinning specified results matching the query rule at the top of the returned result set.

Rule criteriaedit

The criteria for which this rule will match. Criteria is defined as type, metadata, and values. Allowed criteria types are:

Type Match Requirements

exact

Rule metadata matches the specified value exactly.

fuzzy

Rule metadata matches the specified value within an allowed Levenshtein edit distance.

prefix

Rule metadata starts with the specified value.

suffix

Rule metadata ends with the specified value.

contains

Rule metadata contains the specified value.

lt

Rule metadata is less than the specified value.

lte

Rule metadata is less than or equal to the specified value.

gt

Rule metadata is greater than the specified value.

gte

Rule metadata is greater than or equal to the specified value.

always

Always matches for all rule queries.

Rule actionsedit

The actions to take when the rule matches a query:

  • ids will pin the specified _ids.
  • docs will pin the specified documents in the specified indices.

Use ids when searching over a single index, and docs when searching over multiple indices. ids and docs cannot be combined in the same query. See pinned query for details.

Add query rulesedit

You can add query rules using the Create or update query ruleset call. This adds a ruleset containing one or more query rules that will be applied to queries that match their specified criteria.

The following command will create a query ruleset called my-ruleset with two pinned document rules:

  • The first rule will generate a Pinned Query pinning the _ids id1 and id2 when the query_string metadata value is a fuzzy match to either puggles or pugs and the user’s location is in the US.
  • The second rule will generate a Pinned Query pinning the _id of id3 specifically from the my-index-000001 index and id4 from the my-index-000002 index when the query_string metadata value contains beagles.
PUT /_query_rules/my-ruleset
{
  "rules": [
    {
      "rule_id": "rule1",
      "type": "pinned",
      "criteria": [
        {
          "type": "fuzzy",
          "metadata": "query_string",
          "values": [ "puggles", "pugs" ]
        },
        {
          "type": "exact",
          "metadata": "user_country",
          "values": [ "us" ]
        }
      ],
      "actions": {
        "ids": [
          "id1",
          "id2"
        ]
      }
    },
    {
      "rule_id": "rule2",
      "type": "pinned",
      "criteria": [
        {
          "type": "contains",
          "metadata": "query_string",
          "values": [ "beagles" ]
        }
      ],
      "actions": {
        "docs": [
          {
            "_index": "my-index-000001",
            "_id": "id3"
          },
          {
            "_index": "my-index-000002",
            "_id": "id4"
          }
        ]
      }
    }
  ]
}

The API response returns a results of created or updated depending on whether this was a new or edited ruleset.

{
  "result": "created"
}

You can use the Get query ruleset call to retrieve the ruleset you just created, the List query rulesets call to retrieve a summary of all query rulesets, and the Delete query ruleset call to delete a query ruleset.

Perform a rule queryedit

Once you have defined a query ruleset, you can search this ruleset using the Rule query. An example query for the my-ruleset defined above is:

GET /my-index-000001/_search
{
  "query": {
    "rule_query": {
      "organic": {
        "query_string": {
          "query": "puggles"
        }
      },
      "match_criteria": {
        "query_string": "puggles",
        "user_country": "us"
      },
      "ruleset_id": "my-ruleset"
    }
  }
}

This rule query will match against rule1 in the defined query ruleset, and will convert the organic query into a pinned query with id1 and id2 pinned as the top hits. Any other matches from the organic query will be returned below the pinned results.