Aggregate

• Plugin version: v2.6.0
• Released on: 2017-06-11
• Changelog

For other versions, see the overview list.

To learn more about Logstash, see the Logstash Reference.

For questions about the plugin, open a topic in the Discuss forums. For bugs or feature requests, open an issue in Github. For the list of Elastic supported plugins, please consult the Elastic Support Matrix.

Description
Example #1
Example #2 : no start event
Example #3 : no end event
Example #4 : no end event and tasks come one after the other
Example #5 : no end event and push events as soon as possible
How it works
Use Cases
Aggregate Filter Configuration Options

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 events may be processed out of sequence and unexpected results will occur.

• 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.get('duration')"
      map_action => "update"
    }
  }

  if [logger] == "TASK_END" {
    aggregate {
      task_id => "%{taskid}"
      code => "event.set('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 message",
  "sql_duration" => 46
}

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

• 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.get('duration')"
    }
  }

  if [logger] == "TASK_END" {
    aggregate {
      task_id => "%{taskid}"
      code => "event.set('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

Third use case: You have no specific end event.

A typical case is aggregating or tracking user behaviour. We can track a user by its ID through the events, however once the user stops interacting, the events stop coming in. There is no specific event indicating the end of the user’s interaction.

In this case, we can enable the option push_map_as_event_on_timeout to enable pushing the aggregation map as a new event when a timeout occurs. In addition, we can enable timeout_code to execute code on the populated timeout event. We can also add timeout_task_id_field so we can correlate the task_id, which in this case would be the user’s ID.

• Given these logs:

INFO - 12345 - Clicked One
INFO - 12345 - Clicked Two
INFO - 12345 - Clicked Three

• You can aggregate the amount of clicks the user did like this:

filter {
  grok {
    match => [ "message", "%{LOGLEVEL:loglevel} - %{NOTSPACE:user_id} - %{GREEDYDATA:msg_text}" ]
  }

  aggregate {
    task_id => "%{user_id}"
    code => "map['clicks'] ||= 0; map['clicks'] += 1;"
    push_map_as_event_on_timeout => true
    timeout_task_id_field => "user_id"
    timeout => 6001
    timeout_tags => ['_aggregatetimeout']
    timeout_code => "event.set('several_clicks', event.get('clicks') > 1)"
  }
}

1. 10 minutes timeout

• After ten minutes, this will yield an event like:

{
  "user_id": "12345",
  "clicks": 3,
  "several_clicks": true,
    "tags": [
       "_aggregatetimeout"
    ]
}

Fourth use case : like example #3, you have no specific end event, but also, tasks come one after the other.
That is to say : tasks are not interlaced. All task1 events come, then all task2 events come, …​
In that case, you don’t want to wait task timeout to flush aggregation map.

• A typical case is aggregating results from jdbc input plugin.
• Given that you have this SQL query : SELECT country_name, town_name FROM town
• Using jdbc input plugin, you get these 3 events from :

{ "country_name": "France", "town_name": "Paris" }
{ "country_name": "France", "town_name": "Marseille" }
{ "country_name": "USA", "town_name": "New-York" }

• And you would like these 2 result events to push them into elasticsearch :

{ "country_name": "France", "towns": [ {"town_name": "Paris"}, {"town_name": "Marseille"} ] }
{ "country_name": "USA", "towns": [ {"town_name": "New-York"} ] }

• You can do that using push_previous_map_as_event aggregate plugin option :

filter {
  aggregate {
    task_id => "%{country_name}"
    code => "
      map['country_name'] = event.get('country_name')
      map['towns'] ||= []
      map['towns'] << {'town_name' => event.get('town_name')}
      event.cancel()
    "
    push_previous_map_as_event => true
    timeout => 3
  }
}

• The key point is that each time aggregate plugin detects a new country_name, it pushes previous aggregate map as a new Logstash event, and then creates a new empty map for the next country
• When 5s timeout comes, the last aggregate map is pushed as a new event
• Finally, initial events (which are not aggregated) are dropped because useless (thanks to event.cancel())

Fifth use case: like example #3, there is no end event.
Events keep comming for an indefinite time and you want to push the aggregation map as soon as possible after the last user interaction without waiting for the timeout.
This allows to have the aggregated events pushed closer to real time.

A typical case is aggregating or tracking user behaviour.
We can track a user by its ID through the events, however once the user stops interacting, the events stop coming in.
There is no specific event indicating the end of the user’s interaction.
The user ineraction will be considered as ended when no events for the specified user (task_id) arrive after the specified inactivity_timeout.<br> If the user continues interacting for longer than timeoutseconds (since first event), the aggregation map will still be deleted and pushed as a new event when timeout occurs.<br> The difference with example #3 is that the events will be pushed as soon as the user stops interacting forinactivity_timeoutseconds instead of waiting for the end oftimeout` seconds since first event.

In this case, we can enable the option push_map_as_event_on_timeout to enable pushing the aggregation map as a new event when inactivity timeout occurs.
In addition, we can enable timeout_code to execute code on the populated timeout event.
We can also add timeout_task_id_field so we can correlate the task_id, which in this case would be the user’s ID.

• Given these logs:

INFO - 12345 - Clicked One
INFO - 12345 - Clicked Two
INFO - 12345 - Clicked Three

• You can aggregate the amount of clicks the user did like this:

filter {
 grok {
   match => [ "message", "%{LOGLEVEL:loglevel} - %{NOTSPACE:user_id} - %{GREEDYDATA:msg_text}" ]
 }
 aggregate {
   task_id => "%{user_id}"
   code => "map['clicks'] ||= 0; map['clicks'] += 1;"
   push_map_as_event_on_timeout => true
   timeout_task_id_field => "user_id"
   timeout => 36001
   inactivity_timeout => 3002
   timeout_tags => ['_aggregatetimeout']
   timeout_code => "event.set('several_clicks', event.get('clicks') > 1)"
 }
}

1. 1 hour timeout, user activity will be considered finished one hour after the first event, even if events keep comming
2. 5 minutes timeout, user activity will be considered finished if no new events arrive 5 minutes after the last event

• After five minutes of inactivity or one hour since first event, this will yield an event like:

{
 "user_id": "12345",
 "clicks": 3,
 "several_clicks": true,
   "tags": [
      "_aggregatetimeout"
   ]
}

• 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 (thanks to end_of_task => true)
• an aggregate map is tied to one task_id value which is tied to one task_id pattern. So if you have 2 filters with different task_id patterns, even if you have same task_id value, they won’t share the same aggregate map.
• in one filter configuration, it is recommanded to define a timeout option to protect the feature 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
• all timeout options have to be defined in only one aggregate filter per task_id pattern. Timeout options are : timeout, inactivity_timeout, timeout_code, push_map_as_event_on_timeout, push_previous_map_as_event, timeout_task_id_field, timeout_tags
• if code execution raises an exception, the error is logged and event is tagged _aggregateexception

• 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 event 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, …​

This plugin supports the following configuration options plus the Common options described later.

Also see Common options for a list of options supported by all filter plugins.

• Value type is string
• There is no default value for this setting.

The path to file where aggregate maps are stored when Logstash stops and are loaded from when Logstash starts.

If not defined, aggregate maps will not be stored at Logstash stop and will be lost. Must be defined in only one aggregate filter (as aggregate maps are global).

Example:

filter {
  aggregate {
    aggregate_maps_path => "/path/to/.aggregate_maps"
  }
}

• This is a required setting.
• Value type is string
• There is no default value for this setting.

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).

Example:

filter {
  aggregate {
    code => "map['sql_duration'] += event.get('duration')"
  }
}

• Value type is boolean
• Default value is false

Tell the filter that task is ended, and therefore, to delete aggregate map after code execution.

• Value type is number
• There is no default value for this setting.

The amount of seconds (since the last event) after which a task is considered as expired.

When timeout occurs for a task, its aggregate map is evicted.

If push_map_as_event_on_timeout or push_previous_map_as_event is set to true, the task aggregation map is pushed as a new Logstash event.

inactivity_timeout can be defined for each "task_id" pattern.

inactivity_timeout must be lower than timeout.

• Value type is string
• Default value is "create_or_update"

Tell the filter what to do with aggregate map.

"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

• Value type is boolean
• Default value is false

When this option is enabled, each time a task timeout is detected, it pushes task aggregation map as a new Logstash event. This enables to detect and process task timeouts in Logstash, but also to manage tasks that have no explicit end event.

• Value type is boolean
• Default value is false

When this option is enabled, each time aggregate plugin detects a new task id, it pushes previous aggregate map as a new Logstash event, and then creates a new empty map for the next task.

• This is a required setting.
• Value type is string
• There is no default value for this setting.

The expression defining task ID to correlate logs.

This value must uniquely identify the task.

Example:

filter {
  aggregate {
    task_id => "%{type}%{my_task_id}"
  }
}

• Value type is number
• Default value is 1800

The amount of seconds (since the first event) after which a task is considered as expired.

When timeout occurs for a task, its aggregate map is evicted.

If push_map_as_event_on_timeout or push_previous_map_as_event is set to true, the task aggregation map is pushed as a new Logstash event.

Timeout can be defined for each "task_id" pattern.

• Value type is string
• There is no default value for this setting.

The code to execute to complete timeout generated event, when 'push_map_as_event_on_timeout' or 'push_previous_map_as_event' is set to true. The code block will have access to the newly generated timeout event that is pre-populated with the aggregation map.

If 'timeout_task_id_field' is set, the event is also populated with the task_id value

Example:

filter {
  aggregate {
    timeout_code => "event.set('state', 'timeout')"
  }
}

• Value type is array
• Default value is []

Defines tags to add when a timeout event is generated and yield

Example:

filter {
  aggregate {
    timeout_tags => ["aggregate_timeout']
  }
}

• Value type is string
• There is no default value for this setting.

This option indicates the timeout generated event’s field for the "task_id" value. The task id will then be set into the timeout event. This can help correlate which tasks have been timed out.

For example, with option timeout_task_id_field => "my_id" ,when timeout task id is "12345", the generated timeout event will contain 'my_id' => '12345'.

By default, if this option is not set, task id value won’t be set into timeout generated event.

These configuration options are supported by all filter plugins:

• Value type is hash
• Default value is {}

If this filter is successful, add any arbitrary fields to this event. Field names can be dynamic and include parts of the event using the %{{field}}.

Example:

filter {
  aggregate {
    add_field => { "foo_%{somefield}" => "Hello world, from %{host}" }
  }
}

# You can also add multiple fields at once:
filter {
  aggregate {
    add_field => {
      "foo_%{somefield}" => "Hello world, from %{host}"
      "new_field" => "new_static_value"
    }
  }
}

If the event has field "somefield" == "hello" this filter, on success, would add field foo_hello if it is present, with the value above and the %{{host}} piece replaced with that value from the event. The second example would also add a hardcoded field.

• Value type is array
• Default value is []

If this filter is successful, add arbitrary tags to the event. Tags can be dynamic and include parts of the event using the %{{field}} syntax.

Example:

filter {
  aggregate {
    add_tag => [ "foo_%{somefield}" ]
  }
}

# You can also add multiple tags at once:
filter {
  aggregate {
    add_tag => [ "foo_%{somefield}", "taggedy_tag"]
  }
}

If the event has field "somefield" == "hello" this filter, on success, would add a tag foo_hello (and the second example would of course add a taggedy_tag tag).

• Value type is boolean
• Default value is true

Disable or enable metric logging for this specific plugin instance by default we record all the metrics we can, but you can disable metrics collection for a specific plugin.

• Value type is string
• There is no default value for this setting.

Add a unique ID to the plugin configuration. If no ID is specified, Logstash will generate one. It is strongly recommended to set this ID in your configuration. This is particularly useful when you have two or more plugins of the same type, for example, if you have 2 aggregate filters. Adding a named ID in this case will help in monitoring Logstash when using the monitoring APIs.

filter {
  aggregate {
    id => "ABC"
  }
}

• Value type is boolean
• Default value is false

Call the filter flush method at regular interval. Optional.

• Value type is array
• Default value is []

If this filter is successful, remove arbitrary fields from this event. Fields names can be dynamic and include parts of the event using the %{{field}} Example:

filter {
  aggregate {
    remove_field => [ "foo_%{somefield}" ]
  }
}

# You can also remove multiple fields at once:
filter {
  aggregate {
    remove_field => [ "foo_%{somefield}", "my_extraneous_field" ]
  }
}

If the event has field "somefield" == "hello" this filter, on success, would remove the field with name foo_hello if it is present. The second example would remove an additional, non-dynamic field.

• Value type is array
• Default value is []

If this filter is successful, remove arbitrary tags from the event. Tags can be dynamic and include parts of the event using the %{{field}} syntax.

Example:

filter {
  aggregate {
    remove_tag => [ "foo_%{somefield}" ]
  }
}

# You can also remove multiple tags at once:
filter {
  aggregate {
    remove_tag => [ "foo_%{somefield}", "sad_unwanted_tag"]
  }
}

If the event has field "somefield" == "hello" this filter, on success, would remove the tag foo_hello if it is present. The second example would remove a sad, unwanted tag as well.