Splunk® Enterprise

Search Reference

tojson

Description

Converts events into JSON objects. You can specify which fields get converted by identifying them through exact match or through wildcard expressions. You can also apply specific JSON datatypes to field values using datatype functions. The tojson command converts multivalue fields into JSON arrays.

When fields are specifically named in a tojson search, the command generates JSON objects that are limited to the values of just those named fields. If no fields are specified for tojson, tojson generates JSON objects for all fields that would otherwise be returned by the search.

Syntax

Required syntax is in bold.

| tojson
[<tojson-function>]...
[default_type=<datatype>]
[fill_null=<boolean>]
[include_internal=<boolean>]
[output_field=<string>]

Optional arguments

tojson-function
Syntax: [auto | bool | json | none | num | str](<wc-field>)...
Description: Applies JSON datatype functions to values of named fields. See Usage for details about how tojson interprets these datatype functions, and how tojson applies datatypes to field values when it converts events into JSON objects.
If you provide no fields, the tojson processor creates JSON objects for each event that include all available fields. In other words, it applies none(*) to the search.
Default: none(*)
default_type
Syntax: default_type=<datatype>
Description: Specifies the datatype that the tojson processor should apply to fields that aren't specifically associated with a datatype function.
Default: none
fill_null
Syntax: fill_null=<boolean>
Description: When set to true, tojson outputs a literal null value when tojson skips a value. For example, normally, when tojson tries to apply the json datatype to a field that does not have proper JSON formatting, tojson skips the field. However, if fill_null=true, the tojson processor outputs a null value
Default: false
include_internal
Syntax: include_internal=<boolean>
Description: When set to true, tojson includes internal fields such as _time, _indextime, or _raw in its JSON object output.
Default: false
output_field
Syntax: output_field=<string>
Description: Specifies the name of the field to which the tojson search processor writes the output JSON objects.
Default: _raw

Usage

The tojson command is a streaming command, which means it operates on each event as it is returned by the search. See Types of commands.

Apply JSON datatypes to field values

The tojson command applies JSON datatypes to field values according to logic encoded in its datatype functions.

You can assign specific datatype functions to fields when you write a tojson search. Alternatively, you can name a set of fields without associating them with datatype functions, and then identify a default_type that tojson can apply to those unaffiliated fields.

If you do not specify any fields for the tojson command, the tojson returns JSON objects for each field that can possibly be returned by the search at that point, and applies the none datatype function to the values of those fields. The none datatype function applies the numeric datatype to field values that are purely numeric, and applies the string datatype to all other field values.

The following table explains the logic that the various datatype functions use to apply datatypes to the values of the fields with which they are associated.

Datatype function Conversion logic
auto Converts all values of the specified field into JSON-formatted output. Automatically determines the field datatypes.
  • If the value is numeric, the JSON output has a numeric output and includes a literal numeric.
  • If the value is the string true or false the JSON output has a Boolean type.
  • If the value is a literal null the JSON output has a null type and includes a null value.
  • If the value is a string other than the previously mentioned strings, tojson examines the string. If it is proper JSON, tojson outputs a nested JSON object. If it is not proper JSON, tojson includes the string in the output.
bool Converts valid values of the specified field to the Boolean datatype, and skips invalid values, using string validation.
  • If the value is a number, tojson outputs false only if that value is 0. Otherwise tojson outputs false.
  • If the value is a string, tojson outputs false only if the value is false, f, or no.
  • The tojson processor outputs true only if the value is code true, t, or yes. If the value does not fit into those two sets of strings, it is skipped.
  • The validation for the bool datatype function is case insensitive. This means that it also interprets FALSE, False, F, and NO as false.
json Converts all values of the specified field to the JSON type, using string validation. Skips values with invalid JSON.
  • If the value is a number, tojson outputs that number.
  • If the value is a string, tojson outputs the string as a JSON block.
  • If the value is invalid JSON, tojson skips it.
none Outputs all values for the specified field in the JSON type. Does not apply string validation.
  • If the value is a number, tojson outputs a numeric datatype in the JSON block.
  • If the value is a string, tojson outputs a string datatype.
num Converts all values of the specified field to the numeric type, using string validation.
  • If the value is a number, tojson outputs that value and gives it the numeric datatype.
  • If the value is a string, tojson attempts to parse the string as a number. If it cannot, it skips the value.
str Converts all values of the specified field into the string datatype, using string validation.
The tojson processor applies the string type to all values of the specified field, even if they are numbers, Boolean values, and so on.

When a field includes multivalues, tojson outputs a JSON array and applies the datatype function logic to each element of the array.

Examples

1. Convert all events returned by a search into JSON objects

This search of index=_internal converts all events it returns for its time range into JSON-formatted data. Because the search string does not assign datatype functions to specific fields, by default tojson applies the none datatype function to all fields returned by the search. This means all of their values get either the numeric or string datatypes.

index=_internal | tojson

For example, say you start with events that look like this:
12-18-2020 18:19:25.601 +0000 INFO  Metrics - group=thruput, name=thruput, instantaneous_kbps=5.821, instantaneous_eps=27.194, average_kbps=5.652, total_k_processed=444500.000, kb=180.443, ev=843, load_average=19.780
After being processed by tojson, such events have JSON formatting like this:
{ [-]
   component: Metrics
   date_hour: 18
   date_mday: 18
   date_minute: 22
   date_month: december
   date_second: 9
   date_wday: friday
   date_year: 2020
   date_zone: 0
   event_message: group=thruput, name=thruput, instantaneous_kbps=2.914, instantaneous_eps=13.903, average_kbps=5.062, total_k_processed=398412.000, kb=90.338, ev=431, load_average=14.690
   group: thruput
   host: sh1
   index: _internal
   linecount: 1
   log_level: INFO
   name: thruput
   punct: --_::._+____-_=,_=,_=.,_=.,_=.,_=.,_=.,_=,_=.
   source: /opt/splunk/var/log/splunk/metrics.log
   sourcetype: splunkd
   splunk_server: idx2
   timeendpos: 29
   timestartpos: 0
} 

2. Specify different datatypes for 'date' fields

The following search of the _internal index converts results into JSON objects that have only the date_* fields from each event. The numeric datatype is applied to all date_hour field values. The string datatype is applied to all other date field values.

index=_internal | tojson num(date_hour) str(date_*)

This search produces JSON objects like this:
{ [-]
   date_hour: 18
   date_mday: 18
   date_minute: 28
   date_month: december
   date_second: 45
   date_wday: friday
   date_year: 2020
   date_zone: 0
}
Note that all fields that do not start with date_ have been stripped from the output.

3. Limit JSON object output and apply datatypes to the field values

This search returns JSON objects only for the name, age, and isRegistered fields. It uses the auto datatype function to have tojson automatically apply appropriate JSON datatypes to the values of those fields.

... | tojson auto(name) auto(age) auto(isRegistered)

4. Convert all events into JSON objects and apply appropriate datatypes to all field values

This search converts all of the fields in each event returned by the search into JSON objects. It uses the auto datatype function in conjunction with a wildcard to apply appropriate datatypes to the values of all fields returned by the search.

... | tojson auto(*)

Notice that this search references the auto datatype function, which ensures that Boolean, JSON, and null field values are appropriately typed alongside numeric and string values.
Alternatively, you can use default_type to apply the auto datatype function to all fields returned by a search:

... | tojson default_type=auto

5. Apply the Boolean datatype to a specific field

This example generates JSON objects containing values of the isInternal field. It uses the bool datatype function to apply the Boolean datatype to those field values.

... | tojson bool(isInternal)

6. Include internal fields and assign a 'null' value to skipped fields

This example demonstrates usage of the include_internal and fill_null arguments.

... | tojson include_internal=true fill_null=true

7. Designate a default datatype for a set of fields and write the JSON objects to another field

This search generates JSON objects based on the values of four fields. It uses the default_type argument to convert the first three fields to the num datatype. It applies the string datatype to a fourth field. Finally, it writes the finished JSON objects to the field my_JSON_field.

... | tojson age height weight str(name) default_type=num output_field=my_JSON_field

See also

Commands
fromjson
Evaluation functions
JSON functions
Last modified on 11 February, 2023
timewrap   top

This documentation applies to the following versions of Splunk® Enterprise: 9.0.0, 9.0.1, 9.0.2, 9.0.3, 9.0.4, 9.0.5, 9.0.6, 9.0.7, 9.0.8, 9.0.9, 9.0.10, 9.1.0, 9.1.1, 9.1.2, 9.1.3, 9.1.4, 9.1.5, 9.1.6, 9.1.7, 9.2.0, 9.2.1, 9.2.2, 9.2.3, 9.2.4, 9.3.0, 9.3.1, 9.3.2, 9.4.0


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