aggregate

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This is a community-maintained plugin! It does not ship with Logstash by default, but it is easy to install by running bin/logstash-plugin install logstash-filter-aggregate.

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.

Example #1

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  • 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.

Example #2 : no start event

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  • 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

Example #3 : no end event

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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 => 600 # 10 minutes timeout
    timeout_tags => ['_aggregatetimeout']
    timeout_code => "event.set('several_clicks', event.get('clicks') > 1)"
  }
}
  • After ten minutes, this will yield an event like:
{
  "user_id": "12345",
  "clicks": 3,
  "several_clicks": true,
    "tags": [
       "_aggregatetimeout"
    ]
}

Example #4 : no end event and tasks come one after the other

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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", "town_name": [ "Paris", "Marseille" ] }
  { "country_name": "USA", "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['town_name'] ||= []
          event.to_hash.each do |key,value|
            map[key] = value unless map.has_key?(key)
            map[key] << value if map[key].is_a?(Array)
          end
         "
         push_previous_map_as_event => true
         timeout => 5
         timeout_tags => ['aggregated']
     }

     if "aggregated" not in [tags] {
      drop {}
     }
   }
  • The key point is that each time aggregate plugin detects a new country_name, it pushes previous aggregate map as a new logstash event (with aggregated tag), 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

How it works

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  • 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 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, 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

Use Cases

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  • 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, …​

 

Synopsis

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This plugin supports the following configuration options:

Required configuration options:

aggregate {
    code => ...
    task_id => ...
}

Available configuration options:

Details

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add_field

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  • 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}" }
      }
    }
[source,ruby]
    # 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.

add_tag

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  • 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}" ]
      }
    }
[source,ruby]
    # 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).

aggregate_maps_path

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  • 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 value : "/path/to/.aggregate_maps"

code

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  • 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 value : "map['sql_duration'] += event.get('duration')"

enable_metric

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  • 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.

end_of_task

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

Add a unique ID to the plugin instance, this ID is used for tracking information for a specific configuration of the plugin.

output {
 stdout {
   id => "ABC"
 }
}

If you don’t explicitely set this variable Logstash will generate a unique name.

map_action

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  • 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

periodic_flush

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  • Value type is boolean
  • Default value is false

Call the filter flush method at regular interval. Optional.

push_map_as_event_on_timeout

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  • 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.

push_previous_map_as_event

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  • 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 option works fine only if tasks come one after the other. It means : all task1 events, then all task2 events, etc…​

remove_field

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  • 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}" ]
      }
    }
[source,ruby]
    # 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.

remove_tag

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  • 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}" ]
      }
    }
[source,ruby]
    # 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.

task_id

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  • 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 in the system.

Example value : "%{application}%{my_task_id}"

timeout

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

The amount of seconds after a task "end event" can be considered lost.

When timeout occurs for a task, The task "map" is evicted.

Timeout can be defined for each "task_id" pattern.

If no timeout is defined, default timeout will be applied : 1800 seconds.

timeout_code

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  • 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 value: "event.set('state', 'timeout')"

timeout_tags

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  • Value type is array
  • Default value is []

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

timeout_task_id_field

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  • 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.

This field has no default value and will not be set on the event if not configured.

Example:

If the task_id is "12345" and this field is set to "my_id", the generated timeout event will contain 'my_id' key with '12345' value.