mv-expand

You use mv-expand when you want to analyze or filter individual values inside arrays or objects. This is especially useful when working with logs that include lists of values, OpenTelemetry traces that contain arrays of spans, or security events that group multiple attributes into one field.

Usage#

Syntax#

mv-expand [kind=(bag|array)] [with_itemindex=IndexFieldName] FieldName [to typeof(Typename)] [limit Rowlimit]

Parameters#

Parameter	Description
`kind`	Optional. Specifies whether the column is a bag (object) or an array. Defaults to `array`.
`with_itemindex=IndexFieldName`	Optional. Outputs an additional column with the zero-based index of the expanded item.
`FieldName`	Required. The name of the column that contains an array or object to expand.
`to typeof(Typename)`	Optional. Converts each expanded element to the specified type.
`limit Rowlimit`	Optional. Limits the number of expanded rows per record.

Returns#

The operator returns a table where each element of the expanded array or each property of the expanded object is placed in its own row. Other columns are duplicated for each expanded row.

Use case example#

When analyzing logs, some values can be stored as arrays. You can use mv-expand to expand them into individual rows for easier filtering.

Query

['sample-http-logs']
| limit 100
| mv-expand territories
| summarize count = count() by territory_name = tostring(territories)

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Output

territory_name	count
United States	67
India	22
Japan	12

This query expands the territories array into rows and counts the most frequent territories.

project: Selects or computes columns. Use it when you want to reshape data, not expand arrays.
summarize: Aggregates data across rows. Use it after expanding arrays to compute statistics.
top: Returns the top N rows by expression. Use it after expansion to find the most frequent values.

Other query languages#

Splunk SPL users

In Splunk SPL, the mvexpand command expands multi-value fields into separate events. The APL mv-expand operator works in a very similar way, splitting array values into individual rows. The main difference is that APL explicitly works with dynamic arrays or property bags, while Splunk handles multi-value fields implicitly.

Splunk example

... | mvexpand request_uri

APL equivalent

['sample-http-logs']
| mv-expand uri

ANSI SQL users

In ANSI SQL, you use CROSS JOIN UNNEST or CROSS APPLY to flatten arrays into rows. In APL, mv-expand provides a simpler and more direct way to achieve the same result.

SQL example

SELECT id, value
FROM logs
CROSS JOIN UNNEST(request_uris) AS t(value)