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Enrichment

match()

Enrich log events with data from a dictionary. Each matching log row gets additional columns from the dictionary lookup.

* | match(dict="threat_intel", field=src_ip, column=ip, include=[threat_score,category])

Parameters

Parameter Required Description
dict Yes Name of the dictionary (created in the Dictionaries page)
field Yes Log field to use as the lookup key
column Yes Dictionary column to match against
include Yes Dictionary columns to add to results: include=[col1,col2]
strict No When true, only return rows that have a match in the dictionary. Default: false

When strict=false (the default), non-matching rows are kept with empty strings for the included columns. When strict=true, non-matching rows are filtered out entirely.

Examples

Enrich logs with threat intelligence data:

* | match(dict="threat_intel", field=src_ip, column=ip, include=[threat_score,category])

Only keep logs that match the dictionary (strict mode):

* | match(dict="threat_intel", field=src_ip, column=ip, include=[threat_score,category], strict=true)

Combine with other pipeline stages:

* | match(dict="asset_inventory", field=hostname, column=name, include=[owner,department])
  | groupBy(department) | count()

comment()

Filter logs to only those that have comments. Optionally narrow by tag labels or keyword search in comment text.

* | comment()

Parameters

Parameter Required Description
tags No One or more tag labels (OR logic, case sensitive). Comma-separated.
keyword No Search term matched against comment text (case insensitive)

With no arguments, returns all logs that have at least one comment.

Tag Filtering

* | comment(tags=security)
* | comment(tags=security,critical)

Multiple tags use OR logic. This matches logs with comments tagged security OR critical.

Keyword Filtering

* | comment(keyword="timeout")

Matches logs with comments containing "timeout" (case insensitive).

Combined

* | comment(keyword="error", tags=security)

Keyword AND at least one matching tag.

Pipeline Usage

comment() can be combined with other pipeline commands:

* | comment(tags=incident) | groupby(src_ip) | count()
* | comment() | table(timestamp, raw_log, src_ip)