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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 | ||
--- | ||
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# LOOKUP JOIN [esql-lookup-join-reference] | ||
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The {{esql}} [`LOOKUP JOIN`](/reference/query-languages/esql/esql-commands.md#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. | ||
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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. | ||
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For example, you can use `LOOKUP JOIN` to: | ||
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* 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. | ||
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[`LOOKUP join`](/reference/query-languages/esql/esql-commands.md#esql-lookup-join) is similar to [`ENRICH`](/reference/query-languages/esql/esql-commands.md#esql-enrich) in the fact that they both help you join data together. You should use `LOOKUP JOIN` when: | ||
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* Your enrichment data changes frequently | ||
* You want to avoid index-time processing | ||
* You're working with regular indices | ||
* You need to preserve distinct matches | ||
* You need to match on any field in a lookup index | ||
* You use document or field level security | ||
* You want to restrict users to a specific lookup indices that they can you | ||
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## How the `LOOKUP JOIN` command works [esql-how-lookup-join-works] | ||
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The `LOOKUP JOIN` command adds new columns to a table, with data from {{es}} indices. | ||
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:::{image} ../../../images/esql-lookup-join.png | ||
:alt: esql lookup join | ||
::: | ||
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`<lookup_index>` | ||
: The name of the lookup index. This must be a specific index name - wildcards, aliases, and remote cluster references are not supported. | ||
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`<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). | ||
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## Example | ||
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`LOOKUP JOIN` has left-join behavior. If no rows match in the looked index, `LOOKUP JOIN` retains the incoming row and adds `null`s. If many rows in the lookedup index match, `LOOKUP JOIN` adds one row per match. | ||
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In this example, we have two sample tables: | ||
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**employees** | ||
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| 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| | ||
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**languages_non_unique_key** | ||
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|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| | ||
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Running the following query would provide the results shown below. | ||
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```esql | ||
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; | ||
``` | ||
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|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| | ||
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::::{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`](/reference/query-languages/esql/esql-commands.md#esql-sort) somewhere after the `LOOKUP JOIN`. | ||
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:::: | ||
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## Prerequisites [esql-lookup-join-prereqs] | ||
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To use `LOOKUP JOIN`, the following requirements must be met: | ||
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* **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 Elasticsearch's type system | ||
* 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 use text fields on the left-hand side of the join only if they have a `.keyword` subfield | ||
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For a complete list of supported data types and their internal representations, see the [Supported Field Types documentation](/reference/query-languages/esql/limitations.md#_supported_types). | ||
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## Limitations | ||
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The following are the current limitations with `LOOKUP JOIN` | ||
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* `LOOKUP JOIN` will be successful if the join field in the lookup index is a `KEYWORD` type. If the main index's join field is `TEXT` type, it must have an exact `.keyword` subfield that can be matched with the lookup index's `KEYWORD` field. | ||
* Indices in [lookup](/reference/elasticsearch/index-settings/index-modules.md#index-mode-setting) mode are always single-sharded. | ||
* Cross cluster search is unsupported. Both source and lookup indices must be local. | ||
* `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`. |
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