Split an event structure that includes an array into multiple distinct events with each array element.

ParameterTypeRequiredDefault ValueDescription
field[a]stringoptional[b] _events Field to split by.
stripbooleanoptional[b] false Strip the field prefix when splitting (default is false).

[a] The parameter name field can be omitted.

[b] Optional parameters use their default value unless explicitly set.

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When LogScale ingests data into arrays, each array entry is turned into separate attributes named [0], [1], ... This function takes such an event and splits it into multiple events based on the prefix of such [N] attributes, allowing for aggregate functions across array values.

When the function is called, each split event generated is given a unique index ID in the _index field. This can be used to identify the individual event.

If the event data includes an @id field, then the @id field is split into multiple fields to identify each array element, with the string __ and the index number appended. For example, given the input record:

Raw Events
"@id=1", "a=[1,2,3]"

When executing:

logscale
split(a)

Generates the following events:

@id_indexa
1__001
1__112
1__223

Note

The split() function is not very efficient, so it should only be used after some aggressive filtering.

split() Syntax Examples

In GitHub events, a PushEvent contains an array of commits, and each commit gets expanded into subattributes of payload.commit_0, payload.commit_1, .... LogScale cannot sum/count, etc. across such attributes. split() expands each PushEvent into one PushEvent for each commit so they can be counted.

logscale
type=PushEvent
| split(payload.commits)
| groupBy(payload.commits.author.email)
| sort()

There might be a case where your parser is receiving JSON events in a JSON array, as in:

JSON
[
  {"exampleField": "value"},
  {"exampleField": "value2"}
]

In this case, your @rawstring text contains this full array, but each record in the array is actually an event in itself, and you would like to split them out.

First you need to call parseJson(), but when @rawstring contains an array, the parseJson() function doesn't assign names to the fields automatically, it only assigns indexes. In other words, calling parseJson() adds fields named something like [0].exampleField, [1].exampleField, etc. to the current event.

Since split() needs a field name to operate on before it reads indexes, it seems like we can't pass it anything here. But we can tell split() to look for the empty field name by calling split(field="").

This means that parsing the above with:

logscale
parseJson()
| split(field="")

will produce two events, each with a field named exampleField, and with an additional field, _index containing the index (count) of the original data so that each individual split() event can be identified:

Alternatively, we can tell parseJson() to add a prefix to all the fields, which can then use as the field name to split on:

logscale
parseJson(prefix="example")
| split(field="example")

Unfortunately this adds the example prefix to all fields on the new event we've split out, so you may prefer splitting on the empty field name to avoid that.

split()Examples

Click + next to an example below to get the full details.

Deduplicate Compound Field Data With array:union() and split()

Query
logscale
splitString(field=userAgent,by=" ",as=agents)
|array:filter(array="agents[]", function={bname=/\//}, var="bname")
|array:union(array=agents,as=browsers)
| split(browsers)
Introduction

Deduplicating fields of information where there are multiple occurrences of a value in a single field, maybe separated by a single character can be achieved in a variety of ways. This solution uses array:union() and split create a unique array and then split the content out to a unique list.

For example, when examining the humio and looking for the browsers or user agents that have used your instance, the UserAgent data will contain the browser and toolkits used to support them, for example:

Raw Events
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36

The actual names are the Name/Version pairs showing compatibility with different browser standards. Resolving this into a simplified list requires splitting up the list, simplifying (to remove duplicates), filtering, and then summarizing the final list.

Step-by-Step
  1. Starting with the source repository events.

  2. logscale
    splitString(field=userAgent,by=" ",as=agents)

    First we split up the userAgent field using a call to splitString() and place the output into the array field agents

    This will create individual array entries into the agents array for each event:

    agents[0]agents[1]agents[2]agents[3]agents[4]agents[5]agents[6]agents[7]agents[8]agents[9]agents[10]agents[11]agents[12]
    Mozilla/5.0(Macintosh;IntelMacOSX10_15_7)AppleWebKit/537.36(KHTML,likeGecko)Chrome/116.0.0.0Safari/537.36
  3. logscale
    |array:filter(array="agents[]", function={bname=/\//}, var="bname")

  4. logscale
    |array:union(array=agents,as=browsers)

    Using array:union() we aggregate the list of user agents across all the events to create a list of unique entries. This will eliminate duplicates where the value of the user agent is the same value.

    The event data now looks like this:

    browsers[0]browsers[1]browsers[2]
    Gecko/20100101Safari/537.36AppleWebKit/605.1.15

    An array of the individual values.

  5. logscale
    | split(browsers)

    Using the split() will split the array into individual events, turning:

    browsers[0]browsers[1]browsers[2]
    Gecko/20100101Safari/537.36AppleWebKit/605.1.15

    into:

    _indexrow[1]
    0Gecko/20100101
    1Safari/537.36
    2AppleWebKit/605.1.15
  6. Event Result set.

Summary and Results

The resulting output from the query is a list of events with each event containing a matching _index and browser. This can be useful if you want to perform further processing on a list of events rather than an array of values.