docs/reference/query-languages/esql/_snippets/commands/layout/lookup-join.md
stack: preview =9.0, ga 9.1+
serverless: ga
LOOKUP JOIN enables you to add data from another index, AKA a 'lookup'
index, to your {{esql}} query results, simplifying data enrichment
and analysis workflows.
Refer to the high-level landing page for an overview of the LOOKUP JOIN command, including use cases, prerequisites, and current limitations.
FROM <source_index>
| LOOKUP JOIN <lookup_index> ON <join_condition>
<lookup_index>
: The name of the lookup index. This must be a specific index name or alias. Wildcards and remote cluster prefixes are not supported. If the query source includes remote indices, the lookup index must exist on all involved clusters. Indices used for lookups must be configured with the lookup index mode.
<join_condition>
: Can be one of the following:
<field1>, <field2>, <field3> {applies_to}stack: ga 9.2AND, for example <left_field1> >= <lookup_field1> AND <left_field2> == <lookup_field2>. Each predicate compares a field from the left index with a field from the lookup index using binary operators (==, >=, <=, >, <, !=). Each field name in the join condition must exist in only one of the indexes. Use RENAME to resolve naming conflicts. {applies_to}stack: preview 9.2 {applies_to}serverless: previewMATCH(<lookup_field>, "search term") AND <left_field> == <lookup_field>. These functions can be combined with binary operators and logical operators (AND, OR, NOT) to create complex join conditions. At least one condition that relates the lookup index fields to the left side of the join fields is still required. {applies_to}stack: preview 9.3 {applies_to}serverless: preview
: If using join on a single field or a field list, the fields used must exist in both your current query results and in the lookup index. If the fields contains multi-valued entries, those entries will not match anything (the added fields will contain null for those rows).The LOOKUP JOIN command adds new columns to your {{esql}} query
results table by finding documents in a lookup index that share the same
join field value as your result rows.
For each row in your results table that matches a document in the lookup index based on the join fields, all fields from the matching document are added as new columns to that row.
If multiple documents in the lookup index match a single row in your results, the output will contain one row for each matching combination.
::::{tip}
For important information about using LOOKUP JOIN, refer to Usage notes.
::::
:::{include} ../types/lookup-join.md :::
The following examples show common LOOKUP JOIN use cases.
Check whether source IPs match known malicious addresses:
:::{include} ../examples/docs-lookup-join.csv-spec/lookupJoinSourceIp.md :::
To filter only for those rows that have a matching threat_list entry, use WHERE ... IS NOT NULL with a field from the lookup index:
:::{include} ../examples/docs-lookup-join.csv-spec/lookupJoinSourceIpWhere.md :::
Pull in environment or ownership details for each host to correlate with metrics data:
:::{include} ../examples/docs-lookup-join.csv-spec/lookupJoinHostNameTwice.md :::
Show logs alongside the owning team or escalation information for faster triage:
:::{include} ../examples/docs-lookup-join.csv-spec/lookupJoinServiceId.md :::
LOOKUP JOIN is generally faster when there are fewer rows to join with. {{esql}} will try to perform any WHERE clause before the LOOKUP JOIN where possible. The following two queries produce the same results. One filters before the join, the other after. The optimizer will push the filter before the lookup when possible:
:::{include} ../examples/lookup-join.csv-spec/filterOnLeftSide.md :::
:::{include} ../examples/lookup-join.csv-spec/filterOnRightSide.md :::