Multivalue and array functions

For an overview about the stats and charting functions, see Overview of SPL2 stats and chart functions.

dataset() or dataset(<fields>)

The dataset function aggregates events into arrays of SPL2 field-value objects. See object in Built-in data types.

Usage

You can use this function in the SELECT clause in the from command and with the stats command.

• If you specify dataset(), the function returns all of the fields in the events that match your search criteria.

• If you specify dataset<fields>, the function returns only the specified fields in each event that match your search criteria. The list of fields must be comma separated.

Examples

Return all fields and values in an array

You can create a dataset array from all of the fields and values in the search results.

Consider this set of data:

_time	department	username
13 Apr 2022 13:02:45.000 PM	Engineering	Claudia Garcia
13 Apr 2022 10:52:41.000 AM	IT	Vanya Patel
13 Apr 2022 06:23:48.000 AM	Personnel	Alex Martin

Use the dataset function to create an array from all of the fields and values using the following search:

...| stats dataset()

The results look something like this:

[{_time: 13 Apr 2022 13:02:45.000 PM, department: Engineering, username: "Claudia Garcia"}, {_time: 13 Apr 2022 10:52:41.000 AM, department: IT, username: "Vanya Patel"}, {_time: 13 Apr 2022 06:23:48.000 AM, department: Personnel, username: "Alex Martin"}]

If you don't specify any fields with the dataset function, all of the fields are included in a single dataset array. A single dataset array is also returned if you specify a wildcard with the dataset function, for example: dataset(*).

Return specific fields in an array

You can specify multiple fields to populate the dataset arrays.

Consider this set of data:

_time	host	action	department	uid	username
13 Apr 2022 13:02:45.000 PM	mailsv2	Failed password	Engineering	1066	Claudia Garcia
13 Apr 2022 10:52:41.000 AM	mailsv1	Failed password	IT	1815	Vanya Patel
13 Apr 2022 06:23:48.000 AM	mailsv3	Session closed	Personnel	1916	Alex Martin
13 Apr 2022 06:23:48.000 AM	mailsv3	Failed password	Engineering	1862	Wei Zhang
12 Apr 2022 20:18:36.000 PM	mailsv1	Session closed	Engineering	1690	Rutherford Sullivan

The following search creates a dataset array with only the department and username field values.

| FROM main SELECT dataset(department, username)

The results look something like this:

dataset(department, username)
[{department: Engineering, username: "Claudia Garcia"}, {department: IT, username: "Vanya Patel"}, {department: Personnel, username: "Alex Martin"}, {department: Engineering, username: "Wei Zhang"},{department: Engineering, username: "Rutherford Sullivan"}]

Use a BY clause to create separate arrays

You can use a BY clause to organize the search results into separate dataset arrays.

Consider this set of data.

_time	host	action	department	uid	username
13 Apr 2022 13:02:45.000 PM	mailsv2	Failed password	Engineering	1066	Claudia Garcia
13 Apr 2022 10:52:41.000 AM	mailsv1	Failed password	IT	1815	Vanya Patel
13 Apr 2022 06:23:48.000 AM	mailsv3	Session closed	Personnel	1916	Alex Martin
13 Apr 2022 06:23:48.000 AM	mailsv3	Failed password	Engineering	1862	Wei Zhang
12 Apr 2022 20:18:36.000 PM	mailsv1	Session closed	Engineering	1690	Rutherford Sullivan

The following search organizes the dataset arrays by department. Each dataset array contains the user ID and username.

| FROM main SELECT dataset(uid, username) GROUP BY department

Because this search uses the from command, the GROUP BY clause is used. If you use this function with the stats command, you would specify the BY clause.

The results look something like this:

department	dataset(uid, username)
Engineering	[{uid: 1066, username: "Claudia Garcia"}, {uid: 1690, username: "Rutherford Sullivan"}, {uid: 1862, username: "Wei Zhang"}]
IT	[{uid: 1815 , username: "Vanya Patel"}]
Personnel	[{uid: 1916, username: "Alex Martin"}]

Rename the dataset field

By default the field name created by the dataset function is the name of the function and the fields specified. You can rename the field that appears in the search results by using the AS keyword. For example:

| FROM main | stats dataset(department, username) AS employees

The results look something like this:

employees
[{department: Engineering, username: "Claudia Garcia"}, {department: IT, username: "Vanya Patel"}, {department: Personnel, username: "Alex Martin"}]

Start the search with the SELECT clause

This example shows how to use the dataset function with the SELECT clause in the from command.

| SELECT dataset(department, username) FROM main

The results look something like this:

dataset(department, name)
[{department: Engineering, username: "Claudia Garcia"}, {department: IT, username: "Vanya Patel"}, {department: Personnel, username: "Alex Martin"}, {department: Engineering, username: "Wei Zhang"},{department: Engineering, username: "Rutherford Sullivan"}]

list(<value>)

The list function returns a multivalue entry from the values in a field. The order of the values reflects the order of the events.

Usage

You can use this function with the stats, streamstats, and timechart commands.

• If more than 100 values are in the field, only the first 100 are returned.
• This function processes field values as strings.

Example

To illustrate what the list function does, let's start by generating a few simple results.

1. Use the from and streamstats commands to generate a set of 11 results that are simply timestamps and a count of the results, which are used as row numbers. Empty arrays with the from command generate the timestamps.

   | from [{},{},{},{},{},{},{},{},{},{},{}] | streamstats count AS rowNumber

   There are 11 results. Th first few results look something like this:

   _time	rowNumber
   2019-10-10T07:19:02.000-07:00	1
   2019-10-10T07:19:02.000-07:00	2
   2019-10-10T07:19:02.000-07:00	3
   2019-10-10T07:19:02.000-07:00	4
   2019-10-10T07:19:02.000-07:00	5

   Notice that each result appears on a separate row, with a line between each row.




2. Add the stats command with the list function to the search. The numbers are returned in ascending order in a single, multivalue result.

   | from [{},{},{},{},{},{},{},{},{},{},{}] | streamstats count AS rowNumber | stats list(rowNumber) AS numbers

   The results look something like this:

   numbers
   1 2 3 4 5 6 7 8 9 10 11

   Notice that this is a single result with multiple values. There are no lines between each value.

3. Compare this result with the results returned by the values function.

pivot(<key>,<value>)

The pivot function aggregates the values in a field and returns the results as an object. See object in the list of built-in data types.

Usage

The <key> argument can be a single field or a string template, which can reference multiple fields.

The <value> argument must be an aggregate, such as count() or sum().

You can use this function with the SELECT clause in the from command, or with the stats command.

Examples

Using the pivot function

Consider the following data that's in the main dataset:

status	host
200	www1
200	www2
200	www1
400	www2
400	www1
400	www3
403	www2
404	www2

Use the pivot function to create an object that summarizes the HTTP status values for each separate host. The search looks like this:

FROM main GROUP BY host SELECT host, pivot(status, count())

The results look something like this:

host	pivot(status,count())
www1	{"200":2,"400":1}
www2	{"200":1,"400":1,"403":1,"404":1}
www3	{"400":1}

You can use the pivot function with the stats command to accomplish the same results:

FROM main | stats pivot(status,count()) as pivotStatus by host

In this search the output field, pivot(status,count()), is renamed using the AS clause.

This search returns the same results as the previous search and looks something like this:

host	pivotStatus
www1	{"200":2,"400":1}
www2	{"200":1,"400":1,"403":1,"404":1}
www3	{"400":1}

Creating nested objects with the pivot function

You can use nested pivot functions to create nested objects.

Consider the following data:

status	host	action
200	www1	purchase
200	www2	purchase
200	www1	addtocart
200	www2	purchase
400	www1	addtocart
400	www1	purchase
403	www2	changequantity
404	www1	view
404	www3	purchase
404	www2	changequantity
404	www1	purchase

You can use one pivot function as the <value> argument in another pivot function to create nested objects:

FROM main GROUP BY status SELECT status, pivot(host, pivot(action, count())) AS nestedPivot

The results look something like this:

status	nestedPivot
200	{"www1":{"addtocart":1,"purchase":1},"www2":{"purchase":2}}
400	{"www1":{"addtocart":1,"purchase":1}}
403	{"www2":{"changequantity":1}}
404	{"www1":{"purchase":1,"view":1},"www2":{"changequantity":1},"www3":{"purchase":1}}

Using a string template with the pivot function

You can use a string template in the <value> argument of the pivot function.

In this example, the string template contains two template expressions, ${name} and ${city}, which are field names. The entire string template is enclosed in double quotation marks:

SELECT pivot("${name} in ${city}", count()) AS mylist FROM main

Suppose these are the values in the name and city fields:

name	city	date
Claudia	London	2020-04-13
Alex	Berlin	2020-04-19
Wei	Sydney	2020-04-21
Claudia	London	2020-04-30

The results look something like this:

mylist
{"Alex in Berlin":1,"Claudia in London":2,"Wei in Sydney":1}

You can add the flatten command to the search:

SELECT pivot("${name} in ${city}", count()) AS mylist FROM main | flatten mylist

The results look something like this:

Alex in Berlin	Claudia in London	Wei in Sydney	mylist
1	2	1	{"Alex in Berlin":1,"Claudia in London":2,"Wei in Sydney":1}

values(<value>)

The values function returns a list of the distinct values in a field as a multivalue entry.

Usage

You can use this function with the stats, streamstats, and timechart commands.

• By default there is no limit to the number of values returned.
• This function processes field values as strings.

The order of the values is lexicographical.

Lexicographical order sorts items based on the values used to encode the items in computer memory. In Splunk software, this is almost always UTF-8 encoding, which is a superset of ASCII.

• Numbers are sorted before letters. Numbers are sorted based on the first digit. For example, the numbers 10, 9, 70, 100 are sorted lexicographically as 10, 100, 70, 9.
• Uppercase letters are sorted before lowercase letters.
• Symbols are not standard. Some symbols are sorted before numeric values. Other symbols are sorted before or after letters.

Example

To illustrate what the values function does, let's start by generating a few simple results.

1. Use the from and streamstats commands to generate a set of 11 results that are simply timestamps and a count of the results, which are used as row numbers. Empty arrays with the from command generate the timestamps.

   | from [{},{},{},{},{},{},{},{},{},{},{}] | streamstats count AS rowNumber

   There are 11 results. Th first few results look something like this:

   _time	rowNumber
   2019-10-10T07:19:02.000-07:00	1
   2019-10-10T07:19:02.000-07:00	2
   2019-10-10T07:19:02.000-07:00	3
   2019-10-10T07:19:02.000-07:00	4
   2019-10-10T07:19:02.000-07:00	5

   Notice that each result appears on a separate row, with a line between each row.

2. Add the stats command with thevalues function the the search. The results are returned in lexicographical order.

   | from [{},{},{},{},{},{},{},{},{},{},{}] | streamstats count AS rowNumber | stats values(rowNumber) AS numbers

   The results look something like this:

   numbers
   1 10 11 2 3 4 5 6 7 8 9

   Notice that this is a single result with multiple values. There are no lines between each value.

3. Compare these results with the results returned by the list function.

See also

Function information

Overview of SPL2 stats and chart functions

SPL2 Stats and Charting Functions Quick Reference

Naming function arguments in the SPL2 Search Manual

Evaluation functions for JSON and multivalue data

JSON functions

Multivalue eval functions