Edge Delta Delete Empty Field Processor

The Edge Delta delete empty field processor removes fields with no value.

  6 minute read  

Overview

The delete empty field processor is used to clean up data items by removing extraneous fields. Typically empty fields are a result of upstream processing or the data source configuration. Removing these fields reduces traffic volume and makes the data items more readable.

Configuration

Consider the following log:

{
  "_type": "log",
  "timestamp": 1745463889804,
  "body": "{\"timestamp\": \"2025-04-24T00:59:56.527714Z\", \"level\": \"Emergency\", \"msg\": \"Critical error in processing\", \"user\": {\"email\": \"barbara.martinez@imaginarymail.com\", \"id\": \"8d25f352-dcde-4753-84a8-45960dc99f90\", \"name\": \"d6426c02-cd40-4278-90a4-c167d4e23370\"}, \"request\": {\"ip\": \"10.29.168.111\", \"method\": \"PUT\", \"path\": \"/json/submit\"}, \"status\": 503, \"response_time_ms\": 12521, \"api_token\": \"sk_live_51NWz4nEXAMPLExQbG7nB2t6h8EpF3Df7oMBez\", \"empty_string\": \"\", \"null_value\": null, \"empty_list\": [], \"empty_map\": {}}",
  "resource": {
...
  },
  "attributes": {
    "api_token": "sk_live_51NWz4nEXAMPLExQbG7nB2t6h8EpF3Df7oMBez",
    "empty_list": [],
    "empty_map": {},
    "empty_string": "",
    "level": "Emergency",
    "msg": "Critical error in processing",
    "null_value": null,
    "request": {
      "ip": "10.29.168.111",
      "method": "PUT",
      "path": "/json/submit"
    },
    "response_time_ms": 12521,
    "status": 503,
    "timestamp": "2025-04-24T00:59:56.527714Z",
    "user": {
      "email": "barbara.martinez@imaginarymail.com",
      "id": "8d25f352-dcde-4753-84a8-45960dc99f90",
      "name": "d6426c02-cd40-4278-90a4-c167d4e23370"
    }
  }
}

The body has been parsed which has resulted in an empty string field, a null value field, an empty list, and an empty map. Resources have been removed for brevity.

The following processor configuration is set to delete empty strings, nulls, empty lists, and empty maps:

This configuration generates the following YAML:

- name: Multi Processor_db04
  type: sequence
  processors:
  - type: delete_empty_values
    metadata: '{"id":"jrgX9yqsLSQJ7VqIO26xZ","type":"delete_empty_values","name":"Delete
      Empty Values"}'
    delete_empty_strings: true
    delete_empty_nulls: true
    delete_empty_lists: true
    delete_empty_maps: true

After being processed by the delete empty values processor:

{
  "_type": "log",
  "timestamp": 1745463889804,
  "body": "{\"timestamp\": \"2025-04-24T00:59:56.527714Z\", \"level\": \"Emergency\", \"msg\": \"Critical error in processing\", \"user\": {\"email\": \"barbara.martinez@imaginarymail.com\", \"id\": \"8d25f352-dcde-4753-84a8-45960dc99f90\", \"name\": \"d6426c02-cd40-4278-90a4-c167d4e23370\"}, \"request\": {\"ip\": \"10.29.168.111\", \"method\": \"PUT\", \"path\": \"/json/submit\"}, \"status\": 503, \"response_time_ms\": 12521, \"api_token\": \"sk_live_51NWz4nEXAMPLExQbG7nB2t6h8EpF3Df7oMBez\", \"empty_string\": \"\", \"null_value\": null, \"empty_list\": [], \"empty_map\": {}}",
  "resource": {
...
  },
  "attributes": {
    "api_token": "sk_live_51NWz4nEXAMPLExQbG7nB2t6h8EpF3Df7oMBez",
    "level": "Emergency",
    "msg": "Critical error in processing",
    "request": {
      "ip": "10.29.168.111",
      "method": "PUT",
      "path": "/json/submit"
    },
    "response_time_ms": 12521,
    "status": 503,
    "timestamp": "2025-04-24T00:59:56.527714Z",
    "user": {
      "email": "barbara.martinez@imaginarymail.com",
      "id": "8d25f352-dcde-4753-84a8-45960dc99f90",
      "name": "d6426c02-cd40-4278-90a4-c167d4e23370"
    }
  }
}

The empty_list, empty_map, empty_string and null_value fields have been deleted resulting in a 4% decrease in traffic volume.

Note: the original unparsed versions still exist in the body.

Options

Select a telemetry type

You can specify, log, metric, trace or all. It is specified using the interface, which generates a YAML list item for you under the data_types parameter. This defines the data item types against which the processor must operate. If data_types is not specified, the default value is all. It is optional.

It is defined in YAML as follows:

- name: multiprocessor
  type: sequence
  processors:
  - type: <processor type>
    data_types:
    - log

Condition

The condition parameter contains a conditional phrase of an OTTL statement. It restricts operation of the processor to only data items where the condition is met. Those data items that do not match the condition are passed without processing. You configure it in the interface and an OTTL condition is generated. It is optional.

Important: All conditions must be written on a single line in YAML. Multi-line conditions are not supported.

Comparison Operators

Operator Name Description Example
== Equal to Returns true if both values are exactly the same attributes["status"] == "OK"
!= Not equal to Returns true if the values are not the same attributes["level"] != "debug"
> Greater than Returns true if the left value is greater than the right attributes["duration_ms"] > 1000
>= Greater than or equal Returns true if the left value is greater than or equal to the right attributes["score"] >= 90
< Less than Returns true if the left value is less than the right attributes["load"] < 0.75
<= Less than or equal Returns true if the left value is less than or equal to the right attributes["retries"] <= 3
matches Regex match Returns true if the string matches a regular expression (generates IsMatch function) IsMatch(attributes["name"], ".*\\.log$")

Logical Operators

Important: Use lowercase and, or, not - uppercase operators will cause errors!

Operator Description Example
and Both conditions must be true attributes["level"] == "ERROR" and attributes["status"] >= 500
or At least one condition must be true attributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"
not Negates the condition not regex_match(attributes["path"], "^/health")

Functions

Function Description Example
regex_match Returns true if string matches the pattern regex_match(attributes["message"], "ERROR\|FATAL")
IsMatch Alternative regex function (UI generates this from “matches” operator) IsMatch(attributes["name"], ".*\\.log$")

Field Existence Checks

Check Description Example
!= nil Field exists (not null) attributes["user_id"] != nil
== nil Field doesn’t exist attributes["optional_field"] == nil
!= "" Field is not empty string attributes["message"] != ""

Common Examples

- name: _multiprocessor
  type: sequence
  processors:
  - type: <processor type>
    # Simple equality check
    condition: attributes["request"]["path"] == "/json/view"
    
  - type: <processor type>
    # Multiple values with OR
    condition: attributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"
    
  - type: <processor type>
    # Excluding multiple values (NOT equal to multiple values)
    condition: attributes["log_type"] != "TRAFFIC" and attributes["log_type"] != "THREAT"
    
  - type: <processor type>
    # Complex condition with AND/OR/NOT
    condition: (attributes["level"] == "ERROR" or attributes["level"] == "FATAL") and attributes["env"] != "test"
    
  - type: <processor type>
    # Field existence and value check
    condition: attributes["user_id"] != nil and attributes["user_id"] != ""
    
  - type: <processor type>
    # Regex matching using regex_match
    condition: regex_match(attributes["path"], "^/api/") and not regex_match(attributes["path"], "^/api/health")
    
  - type: <processor type>
    # Regex matching using IsMatch
    condition: IsMatch(attributes["message"], "ERROR|WARNING") and attributes["env"] == "production"

Common Mistakes to Avoid

# WRONG - Cannot use OR/AND with values directly
condition: attributes["log_type"] != "TRAFFIC" OR "THREAT"

# CORRECT - Must repeat the full comparison
condition: attributes["log_type"] != "TRAFFIC" and attributes["log_type"] != "THREAT"

# WRONG - Uppercase operators
condition: attributes["status"] == "error" AND attributes["level"] == "critical"

# CORRECT - Lowercase operators
condition: attributes["status"] == "error" and attributes["level"] == "critical"

# WRONG - Multi-line conditions
condition: |
  attributes["level"] == "ERROR" and 
  attributes["status"] >= 500  

# CORRECT - Single line (even if long)
condition: attributes["level"] == "ERROR" and attributes["status"] >= 500

Delete options

Toggle on or off the options to delete different types of empty values:

  • Delete empty strings
  • Delete nulls
  • Delete empty lists
  • Delete empty maps

Strings to delete

Use this option to delete fields that contain a particular static value. Such as an unwanted resource field.

Excluded Fields

Specify fields in with this option that should not be deleted even if they match the other conditions set in the processor, such as having an empty string.

Final

Determines whether successfully processed data items should continue through the remaining processors in the same processor stack. If final is set to true, data items output by this processor are not passed to subsequent processors within the node—they are instead emitted to downstream nodes in the pipeline (e.g., a destination). Failed items are always passed to the next processor, regardless of this setting.

The UI provides a slider to configure this setting. The default is false. It is defined in YAML as follows:

- name: multiprocessor
  type: sequence
  processors:
    - type: <processor type>
    final: true

See Also