Dedupe events

Deduplicate logs passing through a topology

status: stable egress: stream state: stateful
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Deduplicates events to reduce data volume by eliminating copies of data.

Configuration

Example configurations 

{
  "transforms": {
    "my_transform_id": {
      "type": "dedupe",
      "inputs": [
        "my-source-or-transform-id"
      ]
    }
  }
}
[transforms.my_transform_id]
type = "dedupe"
inputs = [ "my-source-or-transform-id" ]

transforms:
  my_transform_id:
    type: dedupe
    inputs:
      - my-source-or-transform-id

{
  "transforms": {
    "my_transform_id": {
      "type": "dedupe",
      "inputs": [
        "my-source-or-transform-id"
      ]
    }
  }
}
[transforms.my_transform_id]
type = "dedupe"
inputs = [ "my-source-or-transform-id" ]

transforms:
  my_transform_id:
    type: dedupe
    inputs:
      - my-source-or-transform-id

cache

optional object
Caching configuration for deduplication.

cache.num_events

optional uint
Number of events to cache and use for comparing incoming events to previously seen events.
default: 5000

fields

optional object

Options to control what fields to match against.

When no field matching configuration is specified, events are matched using the timestamp, host, and message fields from an event. The specific field names used are those set in the global log schema configuration.

fields.ignore

required [string]
Matches events using all fields except for the ignored ones.

fields.match

required [string]
Matches events using only the specified fields.

graph

optional object

Extra graph configuration

Configure output for component when generated with graph command

graph.node_attributes

optional object

Node attributes to add to this component’s node in resulting graph

They are added to the node as provided

graph.node_attributes.*
required string literal
A single graph node attribute in graphviz DOT language.
Examples 
{
  "color": "red",
  "name": "Example Node",
  "width": "5.0"
}

inputs

required [string]

A list of upstream source or transform IDs.

Wildcards (*) are supported.

See configuration for more info.

Array string literal
Examples 
[
  "my-source-or-transform-id",
  "prefix-*"
]

Outputs

<component_id>

Default output stream of the component. Use this component’s ID as an input to downstream transforms and sinks.

Telemetry

Metrics

link

component_discarded_events_total

counter
The number of events dropped by this component.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
host optional
The hostname of the system Vector is running on.
intentional
True if the events were discarded intentionally, like a filter transform, or false if due to an error.
pid optional
The process ID of the Vector instance.

component_errors_total

counter
The total number of errors encountered by this component.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
error_type
The type of the error
host optional
The hostname of the system Vector is running on.
pid optional
The process ID of the Vector instance.
stage
The stage within the component at which the error occurred.

component_received_event_bytes_total

counter
The number of event bytes accepted by this component either from tagged origins like file and uri, or cumulatively from other origins.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
container_name optional
The name of the container from which the data originated.
file optional
The file from which the data originated.
host optional
The hostname of the system Vector is running on.
mode optional
The connection mode used by the component.
peer_addr optional
The IP from which the data originated.
peer_path optional
The pathname from which the data originated.
pid optional
The process ID of the Vector instance.
pod_name optional
The name of the pod from which the data originated.
uri optional
The sanitized URI from which the data originated.

component_received_events_count

histogram

A histogram of the number of events passed in each internal batch in Vector’s internal topology.

Note that this is separate than sink-level batching. It is mostly useful for low level debugging performance issues in Vector due to small internal batches.

component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
container_name optional
The name of the container from which the data originated.
file optional
The file from which the data originated.
host optional
The hostname of the system Vector is running on.
mode optional
The connection mode used by the component.
peer_addr optional
The IP from which the data originated.
peer_path optional
The pathname from which the data originated.
pid optional
The process ID of the Vector instance.
pod_name optional
The name of the pod from which the data originated.
uri optional
The sanitized URI from which the data originated.

component_received_events_total

counter
The number of events accepted by this component either from tagged origins like file and uri, or cumulatively from other origins.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
container_name optional
The name of the container from which the data originated.
file optional
The file from which the data originated.
host optional
The hostname of the system Vector is running on.
mode optional
The connection mode used by the component.
peer_addr optional
The IP from which the data originated.
peer_path optional
The pathname from which the data originated.
pid optional
The process ID of the Vector instance.
pod_name optional
The name of the pod from which the data originated.
uri optional
The sanitized URI from which the data originated.

component_sent_event_bytes_total

counter
The total number of event bytes emitted by this component.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
host optional
The hostname of the system Vector is running on.
output optional
The specific output of the component.
pid optional
The process ID of the Vector instance.

component_sent_events_total

counter
The total number of events emitted by this component.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
host optional
The hostname of the system Vector is running on.
output optional
The specific output of the component.
pid optional
The process ID of the Vector instance.

utilization

gauge
A ratio from 0 to 1 of the load on a component. A value of 0 would indicate a completely idle component that is simply waiting for input. A value of 1 would indicate a that is never idle. This value is updated every 5 seconds.
component_id
The Vector component ID.
component_kind
The Vector component kind.
component_type
The Vector component type.
host optional
The hostname of the system Vector is running on.
pid optional
The process ID of the Vector instance.

How it works

Cache Behavior

This transform is backed by an LRU cache of size cache.num_events. That means that this transform will cache information in memory for the last cache.num_events Events that it has processed. Entries will be removed from the cache in the order they were inserted. If an Event is received that is considered a duplicate of an Event already in the cache that will put that event back to the head of the cache and reset its place in line, making it once again last entry in line to be evicted.

Memory Usage Details

Each entry in the cache corresponds to an incoming Event and contains a copy of the ‘value’ data for all fields in the Event being considered for matching. When using fields.match this will be the list of fields specified in that configuration option. When using fields.ignore that will include all fields present in the incoming event except those specified in fields.ignore. Each entry also uses a single byte per field to store the type information of that field. When using fields.ignore each cache entry additionally stores a copy of each field name being considered for matching. When using fields.match storing the field names is not necessary.

Memory Utilization Estimation

If you want to estimate the memory requirements of this transform for your dataset, you can do so with these formulas:

When using fields.match:

Sum(the average size of the *data* (but not including the field name) for each field in `fields.match`) * `cache.num_events`

When using fields.ignore:

(Sum(the average size of each incoming Event) - (the average size of the field name *and* value for each field in `fields.ignore`)) * `cache.num_events`

Missing Fields

Fields with explicit null values will always be considered different than if that field was omitted entirely. For example, if you run this transform with fields.match = ["a"], the event “{a: null, b:5}” will be considered different to the event “{b:5}”.

State

This component is stateful, meaning its behavior changes based on previous inputs (events). State is not preserved across restarts, therefore state-dependent behavior will reset between restarts and depend on the inputs (events) received since the most recent restart.
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