elasticsearch/docs/reference/query-languages/esql/esql-lookup-join.md

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navigation_title: "Correlate data with LOOKUP JOIN" mapped_pages:

• https://www.elastic.co/guide/en/elasticsearch/reference/current/esql-enrich-data.html ---

LOOKUP JOIN [esql-lookup-join-reference]

The {{esql}} LOOKUP JOIN processing command combines data from your {{esql}} query results table with matching records from a specified lookup index. It adds fields from the lookup index as new columns to your results table based on matching values in the join field.

Teams often have data scattered across multiple indices – like logs, IPs, user IDs, hosts, employees etc. Without a direct way to enrich or correlate each event with reference data, root-cause analysis, security checks, and operational insights become time-consuming.

For example, you can use LOOKUP JOIN to:

• Retrieve environment or ownership details for each host to correlate your metrics data.
• Quickly see if any source IPs match known malicious addresses.
• Tag logs with the owning team or escalation info for faster triage and incident response.

LOOKUP join is similar to ENRICH in the fact that they both help you join data together. You should use LOOKUP JOIN when:

• Your enrichment data changes frequently
• You want to avoid index-time processing
• You want SQL-like behavior, so that multiple matches result in multiple rows
• You need to match on any field in a lookup index
• You use document or field level security
• You want to restrict users to use only specific lookup indices
• You do not need to match using ranges or spatial relations

How the LOOKUP JOIN command works [esql-how-lookup-join-works]

The LOOKUP JOIN command adds new columns to a table, with data from {{es}} indices.

:::{image} ../images/esql-lookup-join.png :alt: esql lookup join :::

<lookup_index> : The name of the lookup index. This must be a specific index name - wildcards, aliases, and remote cluster references are not supported.

<field_name> : The field to join on. This field must exist in both your current query results and in the lookup index. If the field contains multi-valued entries, those entries will not match anything (the added fields will contain null for those rows).

Example

LOOKUP JOIN has left-join behavior. If no rows match in the lookup index, LOOKUP JOIN retains the incoming row and adds nulls. If many rows in the lookup index match, LOOKUP JOIN adds one row per match.

In this example, we have two sample tables:

employees

birth_date	emp_no	first_name	gender	hire_date	language
1955-10-04T00:00:00Z	10091	Amabile	M	1992-11-18T00:00:00Z	3
1964-10-18T00:00:00Z	10092	Valdiodio	F	1989-09-22T00:00:00Z	1
1964-06-11T00:00:00Z	10093	Sailaja	M	1996-11-05T00:00:00Z	3
1957-05-25T00:00:00Z	10094	Arumugam	F	1987-04-18T00:00:00Z	5
1965-01-03T00:00:00Z	10095	Hilari	M	1986-07-15T00:00:00Z	4

languages_non_unique_key

language_code	language_name	country
1	English	Canada
1	English
1		United Kingdom
1	English	United States of America
2	German	[Germany|Austria]
2	German	Switzerland
2	German
4	Spanish
5		France
[6|7]	Mv-Lang	Mv-Land
[7|8]	Mv-Lang2	Mv-Land2
	Null-Lang	Null-Land
	Null-Lang2	Null-Land2

Running the following query would provide the results shown below.

FROM employees
| EVAL language_code = emp_no % 10
| LOOKUP JOIN languages_lookup_non_unique_key ON language_code
| WHERE emp_no > 10090 AND emp_no < 10096
| SORT emp_no, country
| KEEP emp_no, language_code, language_name, country;

emp_no	language_code	language_name	country
10091	1	English	Canada
10091	1	null	United Kingdom
10091	1	English	United States of America
10091	1	English	null
10092	2	German	[Germany, Austria]
10092	2	German	Switzerland
10092	2	German	null
10093	3	null	null
10094	4	Spanish	null
10095	5	null	France

::::{important} LOOKUP JOIN does not guarantee the output to be in any particular order. If a certain order is required, users should use a SORT somewhere after the LOOKUP JOIN.

::::

Prerequisites [esql-lookup-join-prereqs]

To use LOOKUP JOIN, the following requirements must be met:

• Compatible data types: The join key and join field in the lookup index must have compatible data types. This means:
  • The data types must either be identical or be internally represented as the same type in {{esql}}
  • Numeric types follow these compatibility rules:
  • short and byte are compatible with integer (all represented as int)
  • float, half_float, and scaled_float are compatible with double (all represented as double)
  • For text fields: You can only use text fields as the join key on the left-hand side of the join and only if they have a .keyword subfield

To obtain a join key with a compatible type, use a conversion function if needed.

For a complete list of supported data types and their internal representations, see the Supported Field Types documentation.

Limitations

The following are the current limitations with LOOKUP JOIN

• Indices in lookup mode are always single-sharded.
• Cross cluster search is unsupported initially. Both source and lookup indices must be local.
• Currently, only matching on equality is supported.
• LOOKUP JOIN can only use a single match field and a single index. Wildcards, aliases, datemath, and datastreams are not supported.
• The name of the match field in LOOKUP JOIN lu_idx ON match_field must match an existing field in the query. This may require RENAMEs or EVALs to achieve.
• The query will circuit break if there are too many matching documents in the lookup index, or if the documents are too large. More precisely, LOOKUP JOIN works in batches of, normally, about 10,000 rows; a large amount of heap space is needed if the matching documents from the lookup index for a batch are multiple megabytes or larger. This is roughly the same as for ENRICH.