Logstash Filter Aggregate Documentation

The aim of this filter is to aggregate information available among several events (typically log lines) belonging to a same task, and finally push aggregated information into final task event.

You should be very careful to set logstash filter workers to 1 (-w 1 flag) for this filter to work correctly otherwise documents may be processed out of sequence and unexpected results will occur.

Example #1

• with these given logs :

     INFO - 12345 - TASK_START - start
     INFO - 12345 - SQL - sqlQuery1 - 12
     INFO - 12345 - SQL - sqlQuery2 - 34
     INFO - 12345 - TASK_END - end

• you can aggregate "sql duration" for the whole task with this configuration :

     filter {
         grok {
             match => [ "message", "%{LOGLEVEL:loglevel} - %{NOTSPACE:taskid} - %{NOTSPACE:logger} - %{WORD:label}( - %{INT:duration:int})?" ]
         }
     
         if [logger] == "TASK_START" {
             aggregate {
                 task_id => "%{taskid}"
                 code => "map['sql_duration'] = 0"
                 map_action => "create"
             }
         }
     
         if [logger] == "SQL" {
             aggregate {
                 task_id => "%{taskid}"
                 code => "map['sql_duration'] += event['duration']"
                 map_action => "update"
             }
         }
     
         if [logger] == "TASK_END" {
             aggregate {
                 task_id => "%{taskid}"
                 code => "event['sql_duration'] = map['sql_duration']"
                 map_action => "update"
                 end_of_task => true
                 timeout => 120
             }
         }
     }

• the final event then looks like :

{
         "message" => "INFO - 12345 - TASK_END - end",
    "sql_duration" => 46
}

the field sql_duration is added and contains the sum of all sql queries durations.

Example #2

• If you have the same logs than example #1, but without a start log :

     INFO - 12345 - SQL - sqlQuery1 - 12
     INFO - 12345 - SQL - sqlQuery2 - 34
     INFO - 12345 - TASK_END - end

• you can also aggregate "sql duration" with a slightly different configuration :

     filter {
         grok {
             match => [ "message", "%{LOGLEVEL:loglevel} - %{NOTSPACE:taskid} - %{NOTSPACE:logger} - %{WORD:label}( - %{INT:duration:int})?" ]
         }
     
         if [logger] == "SQL" {
             aggregate {
                 task_id => "%{taskid}"
                 code => "map['sql_duration'] ||= 0 ; map['sql_duration'] += event['duration']"
             }
         }
     
         if [logger] == "TASK_END" {
             aggregate {
                 task_id => "%{taskid}"
                 code => "event['sql_duration'] = map['sql_duration']"
                 end_of_task => true
                 timeout => 120
             }
         }
     }

• the final event is exactly the same than example #1
• the key point is the "||=" ruby operator.
  it allows to initialize 'sql_duration' map entry to 0 only if this map entry is not already initialized

How it works

• the filter needs a "task_id" to correlate events (log lines) of a same task
• at the task beggining, filter creates a map, attached to task_id
• for each event, you can execute code using 'event' and 'map' (for instance, copy an event field to map)
• in the final event, you can execute a last code (for instance, add map data to final event)
• after the final event, the map attached to task is deleted
• in one filter configuration, it is recommanded to define a timeout option to protect the filter against unterminated tasks. It tells the filter to delete expired maps
• if no timeout is defined, by default, all maps older than 1800 seconds are automatically deleted
• finally, if code execution raises an exception, the error is logged and event is tagged '_aggregateexception'

Use Cases

• extract some cool metrics from task logs and push them into task final log event (like in example #1 and #2)
• extract error information in any task log line, and push it in final task event (to get a final document with all error information if any)
• extract all back-end calls as a list, and push this list in final task event (to get a task profile)
• extract all http headers logged in several lines to push this list in final task event (complete http request info)
• for every back-end call, collect call details available on several lines, analyse it and finally tag final back-end call log line (error, timeout, business-warning, ...)
• Finally, task id can be any correlation id matching your need : it can be a session id, a file path, ...

Aggregate Plugin Options

• task_id :
  The expression defining task ID to correlate logs.
  This value must uniquely identify the task in the system.
  This option is required.
  Example value : "%{application}%{my_task_id}"

• code:
  The code to execute to update map, using current event.
  Or on the contrary, the code to execute to update event, using current map.
  You will have a 'map' variable and an 'event' variable available (that is the event itself).
  This option is required.
  Example value : "map['sql_duration'] += event['duration']"

• map_action:
  Tell the filter what to do with aggregate map (default : "create_or_update").
  create: create the map, and execute the code only if map wasn't created before
  update: doesn't create the map, and execute the code only if map was created before
  create_or_update: create the map if it wasn't created before, execute the code in all cases
  Default value: create_or_update

• end_of_task:
  Tell the filter that task is ended, and therefore, to delete map after code execution.
  Default value: false

• timeout:
  The amount of seconds after a task "end event" can be considered lost.
  The task "map" is then evicted.
  The default value is 0, which means no timeout so no auto eviction.

Need Help?

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