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Split the ingest processor docs into multiple files (#36887) 

This commit breaks the single ingest docs file into multiple files,
factoring out the processor docs into a documentation file per
processor. This will help make this content easier to maintain.
This commit is contained in:
Jason Tedor 2018-12-20 08:04:54 -05:00 committed by GitHub
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[[append-processor]]
=== Append Processor
Appends one or more values to an existing array if the field already exists and it is an array.
Converts a scalar to an array and appends one or more values to it if the field exists and it is a scalar.
Creates an array containing the provided values if the field doesn't exist.
Accepts a single value or an array of values.
[[append-options]]
.Append Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to be appended to. Supports <<accessing-template-fields,template snippets>>.
| `value` | yes | - | The value to be appended. Supports <<accessing-template-fields,template snippets>>.
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"append": {
"field": "tags",
"value": ["production", "{{app}}", "{{owner}}"]
}
}
--------------------------------------------------
// NOTCONSOLE

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[[bytes-processor]]
=== Bytes Processor
Converts a human readable byte value (e.g. 1kb) to its value in bytes (e.g. 1024).
Supported human readable units are "b", "kb", "mb", "gb", "tb", "pb" case insensitive. An error will occur if
the field is not a supported format or resultant value exceeds 2^63.
[[bytes-options]]
.Bytes Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to convert
| `target_field` | no | `field` | The field to assign the converted value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"bytes": {
"field": "file.size"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[convert-processor]]
=== Convert Processor
Converts a field in the currently ingested document to a different type, such as converting a string to an integer.
If the field value is an array, all members will be converted.
The supported types include: `integer`, `long`, `float`, `double`, `string`, `boolean`, and `auto`.
Specifying `boolean` will set the field to true if its string value is equal to `true` (ignore case), to
false if its string value is equal to `false` (ignore case), or it will throw an exception otherwise.
Specifying `auto` will attempt to convert the string-valued `field` into the closest non-string type.
For example, a field whose value is `"true"` will be converted to its respective boolean type: `true`. Do note
that float takes precedence of double in `auto`. A value of `"242.15"` will "automatically" be converted to
`242.15` of type `float`. If a provided field cannot be appropriately converted, the Convert Processor will
still process successfully and leave the field value as-is. In such a case, `target_field` will
still be updated with the unconverted field value.
[[convert-options]]
.Convert Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field whose value is to be converted
| `target_field` | no | `field` | The field to assign the converted value to, by default `field` is updated in-place
| `type` | yes | - | The type to convert the existing value to
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
PUT _ingest/pipeline/my-pipeline-id
{
"description": "converts the content of the id field to an integer",
"processors" : [
{
"convert" : {
"field" : "id",
"type": "integer"
}
}
]
}
--------------------------------------------------
// NOTCONSOLE

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[[date-index-name-processor]]
=== Date Index Name Processor
The purpose of this processor is to point documents to the right time based index based
on a date or timestamp field in a document by using the <<date-math-index-names, date math index name support>>.
The processor sets the `_index` meta field with a date math index name expression based on the provided index name
prefix, a date or timestamp field in the documents being processed and the provided date rounding.
First, this processor fetches the date or timestamp from a field in the document being processed. Optionally,
date formatting can be configured on how the field's value should be parsed into a date. Then this date,
the provided index name prefix and the provided date rounding get formatted into a date math index name expression.
Also here optionally date formatting can be specified on how the date should be formatted into a date math index name
expression.
An example pipeline that points documents to a monthly index that starts with a `myindex-` prefix based on a
date in the `date1` field:
[source,js]
--------------------------------------------------
PUT _ingest/pipeline/monthlyindex
{
"description": "monthly date-time index naming",
"processors" : [
{
"date_index_name" : {
"field" : "date1",
"index_name_prefix" : "myindex-",
"date_rounding" : "M"
}
}
]
}
--------------------------------------------------
// CONSOLE
Using that pipeline for an index request:
[source,js]
--------------------------------------------------
PUT /myindex/_doc/1?pipeline=monthlyindex
{
"date1" : "2016-04-25T12:02:01.789Z"
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
[source,js]
--------------------------------------------------
{
"_index" : "myindex-2016-04-01",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"result" : "created",
"_shards" : {
"total" : 2,
"successful" : 1,
"failed" : 0
},
"_seq_no" : 55,
"_primary_term" : 1
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no" : \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
The above request will not index this document into the `myindex` index, but into the `myindex-2016-04-01` index because
it was rounded by month. This is because the date-index-name-processor overrides the `_index` property of the document.
To see the date-math value of the index supplied in the actual index request which resulted in the above document being
indexed into `myindex-2016-04-01` we can inspect the effects of the processor using a simulate request.
[source,js]
--------------------------------------------------
POST _ingest/pipeline/_simulate
{
"pipeline" :
{
"description": "monthly date-time index naming",
"processors" : [
{
"date_index_name" : {
"field" : "date1",
"index_name_prefix" : "myindex-",
"date_rounding" : "M"
}
}
]
},
"docs": [
{
"_source": {
"date1": "2016-04-25T12:02:01.789Z"
}
}
]
}
--------------------------------------------------
// CONSOLE
and the result:
[source,js]
--------------------------------------------------
{
"docs" : [
{
"doc" : {
"_id" : "_id",
"_index" : "<myindex-{2016-04-25||/M{yyyy-MM-dd|UTC}}>",
"_type" : "_type",
"_source" : {
"date1" : "2016-04-25T12:02:01.789Z"
},
"_ingest" : {
"timestamp" : "2016-11-08T19:43:03.850+0000"
}
}
}
]
}
--------------------------------------------------
// TESTRESPONSE[s/2016-11-08T19:43:03.850\+0000/$body.docs.0.doc._ingest.timestamp/]
The above example shows that `_index` was set to `<myindex-{2016-04-25||/M{yyyy-MM-dd|UTC}}>`. Elasticsearch
understands this to mean `2016-04-01` as is explained in the <<date-math-index-names, date math index name documentation>>
[[date-index-name-options]]
.Date index name options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to get the date or timestamp from.
| `index_name_prefix` | no | - | A prefix of the index name to be prepended before the printed date. Supports <<accessing-template-fields,template snippets>>.
| `date_rounding` | yes | - | How to round the date when formatting the date into the index name. Valid values are: `y` (year), `M` (month), `w` (week), `d` (day), `h` (hour), `m` (minute) and `s` (second). Supports <<accessing-template-fields,template snippets>>.
| `date_formats` | no | yyyy-MM-dd'T'HH:mm:ss.SSSZ | An array of the expected date formats for parsing dates / timestamps in the document being preprocessed. Can be a Joda pattern or one of the following formats: ISO8601, UNIX, UNIX_MS, or TAI64N.
| `timezone` | no | UTC | The timezone to use when parsing the date and when date math index supports resolves expressions into concrete index names.
| `locale` | no | ENGLISH | The locale to use when parsing the date from the document being preprocessed, relevant when parsing month names or week days.
| `index_name_format` | no | yyyy-MM-dd | The format to be used when printing the parsed date into the index name. An valid Joda pattern is expected here. Supports <<accessing-template-fields,template snippets>>.
include::common-options.asciidoc[]
|======

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[[date-processor]]
=== Date Processor
Parses dates from fields, and then uses the date or timestamp as the timestamp for the document.
By default, the date processor adds the parsed date as a new field called `@timestamp`. You can specify a
different field by setting the `target_field` configuration parameter. Multiple date formats are supported
as part of the same date processor definition. They will be used sequentially to attempt parsing the date field,
in the same order they were defined as part of the processor definition.
[[date-options]]
.Date options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to get the date from.
| `target_field` | no | @timestamp | The field that will hold the parsed date.
| `formats` | yes | - | An array of the expected date formats. Can be a Joda pattern or one of the following formats: ISO8601, UNIX, UNIX_MS, or TAI64N.
| `timezone` | no | UTC | The timezone to use when parsing the date. Supports <<accessing-template-fields,template snippets>>.
| `locale` | no | ENGLISH | The locale to use when parsing the date, relevant when parsing month names or week days. Supports <<accessing-template-fields,template snippets>>.
include::common-options.asciidoc[]
|======
Here is an example that adds the parsed date to the `timestamp` field based on the `initial_date` field:
[source,js]
--------------------------------------------------
{
"description" : "...",
"processors" : [
{
"date" : {
"field" : "initial_date",
"target_field" : "timestamp",
"formats" : ["dd/MM/yyyy hh:mm:ss"],
"timezone" : "Europe/Amsterdam"
}
}
]
}
--------------------------------------------------
// NOTCONSOLE
The `timezone` and `locale` processor parameters are templated. This means that their values can be
extracted from fields within documents. The example below shows how to extract the locale/timezone
details from existing fields, `my_timezone` and `my_locale`, in the ingested document that contain
the timezone and locale values.
[source,js]
--------------------------------------------------
{
"description" : "...",
"processors" : [
{
"date" : {
"field" : "initial_date",
"target_field" : "timestamp",
"formats" : ["ISO8601"],
"timezone" : "{{my_timezone}}",
"locale" : "{{my_locale}}"
}
}
]
}
--------------------------------------------------
// NOTCONSOLE

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[[dissect-processor]]
=== Dissect Processor
Similar to the <<grok-processor,Grok Processor>>, dissect also extracts structured fields out of a single text field
within a document. However unlike the <<grok-processor,Grok Processor>>, dissect does not use
https://en.wikipedia.org/wiki/Regular_expression[Regular Expressions]. This allows dissect's syntax to be simple and for
some cases faster than the <<grok-processor,Grok Processor>>.
Dissect matches a single text field against a defined pattern.
For example the following pattern:
[source,txt]
--------------------------------------------------
%{clientip} %{ident} %{auth} [%{@timestamp}] \"%{verb} %{request} HTTP/%{httpversion}\" %{status} %{size}
--------------------------------------------------
will match a log line of this format:
[source,txt]
--------------------------------------------------
1.2.3.4 - - [30/Apr/1998:22:00:52 +0000] \"GET /english/venues/cities/images/montpellier/18.gif HTTP/1.0\" 200 3171
--------------------------------------------------
and result in a document with the following fields:
[source,js]
--------------------------------------------------
"doc": {
"_index": "_index",
"_type": "_type",
"_id": "_id",
"_source": {
"request": "/english/venues/cities/images/montpellier/18.gif",
"auth": "-",
"ident": "-",
"verb": "GET",
"@timestamp": "30/Apr/1998:22:00:52 +0000",
"size": "3171",
"clientip": "1.2.3.4",
"httpversion": "1.0",
"status": "200"
}
}
--------------------------------------------------
// NOTCONSOLE
A dissect pattern is defined by the parts of the string that will be discarded. In the example above the first part
to be discarded is a single space. Dissect finds this space, then assigns the value of `clientip` is everything up
until that space.
Later dissect matches the `[` and then `]` and then assigns `@timestamp` to everything in-between `[` and `]`.
Paying special attention the parts of the string to discard will help build successful dissect patterns.
Successful matches require all keys in a pattern to have a value. If any of the `%{keyname}` defined in the pattern do
not have a value, then an exception is thrown and may be handled by the <<handling-failure-in-pipelines,on_falure>> directive.
An empty key `%{}` or a <<dissect-modifier-named-skip-key, named skip key>> can be used to match values, but exclude the value from
the final document. All matched values are represented as string data types. The <<convert-processor, convert processor>>
may be used to convert to expected data type.
Dissect also supports <<dissect-key-modifiers,key modifiers>> that can change dissect's default
behavior. For example you can instruct dissect to ignore certain fields, append fields, skip over padding, etc.
See <<dissect-key-modifiers, below>> for more information.
[[dissect-options]]
.Dissect Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to dissect
| `pattern` | yes | - | The pattern to apply to the field
| `append_separator`| no | "" (empty string) | The character(s) that separate the appended fields.
| `ignore_missing` | no | false | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"dissect": {
"field": "message",
"pattern" : "%{clientip} %{ident} %{auth} [%{@timestamp}] \"%{verb} %{request} HTTP/%{httpversion}\" %{status} %{size}"
}
}
--------------------------------------------------
// NOTCONSOLE
[[dissect-key-modifiers]]
==== Dissect key modifiers
Key modifiers can change the default behavior for dissection. Key modifiers may be found on the left or right
of the `%{keyname}` always inside the `%{` and `}`. For example `%{+keyname ->}` has the append and right padding
modifiers.
.Dissect Key Modifiers
[options="header"]
|======
| Modifier | Name | Position | Example | Description | Details
| `->` | Skip right padding | (far) right | `%{keyname1->}` | Skips any repeated characters to the right | <<dissect-modifier-skip-right-padding,link>>
| `+` | Append | left | `%{+keyname} %{+keyname}` | Appends two or more fields together | <<dissect-modifier-append-key,link>>
| `+` with `/n` | Append with order | left and right | `%{+keyname/2} %{+keyname/1}` | Appends two or more fields together in the order specified | <<dissect-modifier-append-key-with-order,link>>
| `?` | Named skip key | left | `%{?ignoreme}` | Skips the matched value in the output. Same behavior as `%{}`| <<dissect-modifier-named-skip-key,link>>
| `*` and `&` | Reference keys | left | `%{*r1} %{&r1}` | Sets the output key as value of `*` and output value of `&` | <<dissect-modifier-reference-keys,link>>
|======
[[dissect-modifier-skip-right-padding]]
===== Right padding modifier (`->`)
The algorithm that performs the dissection is very strict in that it requires all characters in the pattern to match
the source string. For example, the pattern `%{fookey} %{barkey}` (1 space), will match the string "foo{nbsp}bar"
(1 space), but will not match the string "foo{nbsp}{nbsp}bar" (2 spaces) since the pattern has only 1 space and the
source string has 2 spaces.
The right padding modifier helps with this case. Adding the right padding modifier to the pattern `%{fookey->} %{barkey}`,
It will now will match "foo{nbsp}bar" (1 space) and "foo{nbsp}{nbsp}bar" (2 spaces)
and even "foo{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}bar" (10 spaces).
Use the right padding modifier to allow for repetition of the characters after a `%{keyname->}`.
The right padding modifier may be placed on any key with any other modifiers. It should always be the furthest right
modifier. For example: `%{+keyname/1->}` and `%{->}`
Right padding modifier example
|======
| *Pattern* | `%{ts->} %{level}`
| *Input* | 1998-08-10T17:15:42,466{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}WARN
| *Result* a|
* ts = 1998-08-10T17:15:42,466
* level = WARN
|======
The right padding modifier may be used with an empty key to help skip unwanted data. For example, the same input string, but wrapped with brackets requires the use of an empty right padded key to achieve the same result.
Right padding modifier with empty key example
|======
| *Pattern* | `[%{ts}]%{->}[%{level}]`
| *Input* | [1998-08-10T17:15:42,466]{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}{nbsp}[WARN]
| *Result* a|
* ts = 1998-08-10T17:15:42,466
* level = WARN
|======
===== Append modifier (`+`)
[[dissect-modifier-append-key]]
Dissect supports appending two or more results together for the output.
Values are appended left to right. An append separator can be specified.
In this example the append_separator is defined as a space.
Append modifier example
|======
| *Pattern* | `%{+name} %{+name} %{+name} %{+name}`
| *Input* | john jacob jingleheimer schmidt
| *Result* a|
* name = john jacob jingleheimer schmidt
|======
===== Append with order modifier (`+` and `/n`)
[[dissect-modifier-append-key-with-order]]
Dissect supports appending two or more results together for the output.
Values are appended based on the order defined (`/n`). An append separator can be specified.
In this example the append_separator is defined as a comma.
Append with order modifier example
|======
| *Pattern* | `%{+name/2} %{+name/4} %{+name/3} %{+name/1}`
| *Input* | john jacob jingleheimer schmidt
| *Result* a|
* name = schmidt,john,jingleheimer,jacob
|======
===== Named skip key (`?`)
[[dissect-modifier-named-skip-key]]
Dissect supports ignoring matches in the final result. This can be done with an empty key `%{}`, but for readability
it may be desired to give that empty key a name.
Named skip key modifier example
|======
| *Pattern* | `%{clientip} %{?ident} %{?auth} [%{@timestamp}]`
| *Input* | 1.2.3.4 - - [30/Apr/1998:22:00:52 +0000]
| *Result* a|
* ip = 1.2.3.4
* @timestamp = 30/Apr/1998:22:00:52 +0000
|======
===== Reference keys (`*` and `&`)
[[dissect-modifier-reference-keys]]
Dissect support using parsed values as the key/value pairings for the structured content. Imagine a system that
partially logs in key/value pairs. Reference keys allow you to maintain that key/value relationship.
Reference key modifier example
|======
| *Pattern* | `[%{ts}] [%{level}] %{*p1}:%{&p1} %{*p2}:%{&p2}`
| *Input* | [2018-08-10T17:15:42,466] [ERR] ip:1.2.3.4 error:REFUSED
| *Result* a|
* ts = 1998-08-10T17:15:42,466
* level = ERR
* ip = 1.2.3.4
* error = REFUSED
|======

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[[dot-expand-processor]]
=== Dot Expander Processor
Expands a field with dots into an object field. This processor allows fields
with dots in the name to be accessible by other processors in the pipeline.
Otherwise these <<accessing-data-in-pipelines,fields>> can't be accessed by any processor.
[[dot-expender-options]]
.Dot Expand Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to expand into an object field
| `path` | no | - | The field that contains the field to expand. Only required if the field to expand is part another object field, because the `field` option can only understand leaf fields.
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"dot_expander": {
"field": "foo.bar"
}
}
--------------------------------------------------
// NOTCONSOLE
For example the dot expand processor would turn this document:
[source,js]
--------------------------------------------------
{
"foo.bar" : "value"
}
--------------------------------------------------
// NOTCONSOLE
into:
[source,js]
--------------------------------------------------
{
"foo" : {
"bar" : "value"
}
}
--------------------------------------------------
// NOTCONSOLE
If there is already a `bar` field nested under `foo` then
this processor merges the `foo.bar` field into it. If the field is
a scalar value then it will turn that field into an array field.
For example, the following document:
[source,js]
--------------------------------------------------
{
"foo.bar" : "value2",
"foo" : {
"bar" : "value1"
}
}
--------------------------------------------------
// NOTCONSOLE
is transformed by the `dot_expander` processor into:
[source,js]
--------------------------------------------------
{
"foo" : {
"bar" : ["value1", "value2"]
}
}
--------------------------------------------------
// NOTCONSOLE
If any field outside of the leaf field conflicts with a pre-existing field of the same name,
then that field needs to be renamed first.
Consider the following document:
[source,js]
--------------------------------------------------
{
"foo": "value1",
"foo.bar": "value2"
}
--------------------------------------------------
// NOTCONSOLE
Then the `foo` needs to be renamed first before the `dot_expander`
processor is applied. So in order for the `foo.bar` field to properly
be expanded into the `bar` field under the `foo` field the following
pipeline should be used:
[source,js]
--------------------------------------------------
{
"processors" : [
{
"rename" : {
"field" : "foo",
"target_field" : "foo.bar""
}
},
{
"dot_expander": {
"field": "foo.bar"
}
}
]
}
--------------------------------------------------
// NOTCONSOLE
The reason for this is that Ingest doesn't know how to automatically cast
a scalar field to an object field.

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[[drop-processor]]
=== Drop Processor
Drops the document without raising any errors. This is useful to prevent the document from
getting indexed based on some condition.
[[drop-options]]
.Drop Options
[options="header"]
|======
| Name | Required | Default | Description
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"drop": {
"if" : "ctx.network_name == 'Guest'"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[fail-processor]]
=== Fail Processor
Raises an exception. This is useful for when
you expect a pipeline to fail and want to relay a specific message
to the requester.
[[fail-options]]
.Fail Options
[options="header"]
|======
| Name | Required | Default | Description
| `message` | yes | - | The error message thrown by the processor. Supports <<accessing-template-fields,template snippets>>.
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"fail": {
"if" : "ctx.tags.contains('production') != true",
"message": "The production tag is not present, found tags: {{tags}}"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[foreach-processor]]
=== Foreach Processor
Processes elements in an array of unknown length.
All processors can operate on elements inside an array, but if all elements of an array need to
be processed in the same way, defining a processor for each element becomes cumbersome and tricky
because it is likely that the number of elements in an array is unknown. For this reason the `foreach`
processor exists. By specifying the field holding array elements and a processor that
defines what should happen to each element, array fields can easily be preprocessed.
A processor inside the foreach processor works in the array element context and puts that in the ingest metadata
under the `_ingest._value` key. If the array element is a json object it holds all immediate fields of that json object.
and if the nested object is a value is `_ingest._value` just holds that value. Note that if a processor prior to the
`foreach` processor used `_ingest._value` key then the specified value will not be available to the processor inside
the `foreach` processor. The `foreach` processor does restore the original value, so that value is available to processors
after the `foreach` processor.
Note that any other field from the document are accessible and modifiable like with all other processors. This processor
just puts the current array element being read into `_ingest._value` ingest metadata attribute, so that it may be
pre-processed.
If the `foreach` processor fails to process an element inside the array, and no `on_failure` processor has been specified,
then it aborts the execution and leaves the array unmodified.
[[foreach-options]]
.Foreach Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The array field
| `processor` | yes | - | The processor to execute against each field
| `ignore_missing` | no | false | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
Assume the following document:
[source,js]
--------------------------------------------------
{
"values" : ["foo", "bar", "baz"]
}
--------------------------------------------------
// NOTCONSOLE
When this `foreach` processor operates on this sample document:
[source,js]
--------------------------------------------------
{
"foreach" : {
"field" : "values",
"processor" : {
"uppercase" : {
"field" : "_ingest._value"
}
}
}
}
--------------------------------------------------
// NOTCONSOLE
Then the document will look like this after preprocessing:
[source,js]
--------------------------------------------------
{
"values" : ["FOO", "BAR", "BAZ"]
}
--------------------------------------------------
// NOTCONSOLE
Let's take a look at another example:
[source,js]
--------------------------------------------------
{
"persons" : [
{
"id" : "1",
"name" : "John Doe"
},
{
"id" : "2",
"name" : "Jane Doe"
}
]
}
--------------------------------------------------
// NOTCONSOLE
In this case, the `id` field needs to be removed,
so the following `foreach` processor is used:
[source,js]
--------------------------------------------------
{
"foreach" : {
"field" : "persons",
"processor" : {
"remove" : {
"field" : "_ingest._value.id"
}
}
}
}
--------------------------------------------------
// NOTCONSOLE
After preprocessing the result is:
[source,js]
--------------------------------------------------
{
"persons" : [
{
"name" : "John Doe"
},
{
"name" : "Jane Doe"
}
]
}
--------------------------------------------------
// NOTCONSOLE
The wrapped processor can have a `on_failure` definition.
For example, the `id` field may not exist on all person objects.
Instead of failing the index request, you can use an `on_failure`
block to send the document to the 'failure_index' index for later inspection:
[source,js]
--------------------------------------------------
{
"foreach" : {
"field" : "persons",
"processor" : {
"remove" : {
"field" : "_value.id",
"on_failure" : [
{
"set" : {
"field", "_index",
"value", "failure_index"
}
}
]
}
}
}
}
--------------------------------------------------
// NOTCONSOLE
In this example, if the `remove` processor does fail, then
the array elements that have been processed thus far will
be updated.
Another advanced example can be found in the {plugins}/ingest-attachment-with-arrays.html[attachment processor documentation].

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[[grok-processor]]
=== Grok Processor
Extracts structured fields out of a single text field within a document. You choose which field to
extract matched fields from, as well as the grok pattern you expect will match. A grok pattern is like a regular
expression that supports aliased expressions that can be reused.
This tool is perfect for syslog logs, apache and other webserver logs, mysql logs, and in general, any log format
that is generally written for humans and not computer consumption.
This processor comes packaged with many
https://github.com/elastic/elasticsearch/blob/{branch}/libs/grok/src/main/resources/patterns[reusable patterns].
If you need help building patterns to match your logs, you will find the {kibana-ref}/xpack-grokdebugger.html[Grok Debugger] tool quite useful! The Grok Debugger is an {xpack} feature under the Basic License and is therefore *free to use*. The Grok Constructor at <http://grokconstructor.appspot.com/> is also a useful tool.
[[grok-basics]]
==== Grok Basics
Grok sits on top of regular expressions, so any regular expressions are valid in grok as well.
The regular expression library is Oniguruma, and you can see the full supported regexp syntax
https://github.com/kkos/oniguruma/blob/master/doc/RE[on the Onigiruma site].
Grok works by leveraging this regular expression language to allow naming existing patterns and combining them into more
complex patterns that match your fields.
The syntax for reusing a grok pattern comes in three forms: `%{SYNTAX:SEMANTIC}`, `%{SYNTAX}`, `%{SYNTAX:SEMANTIC:TYPE}`.
The `SYNTAX` is the name of the pattern that will match your text. For example, `3.44` will be matched by the `NUMBER`
pattern and `55.3.244.1` will be matched by the `IP` pattern. The syntax is how you match. `NUMBER` and `IP` are both
patterns that are provided within the default patterns set.
The `SEMANTIC` is the identifier you give to the piece of text being matched. For example, `3.44` could be the
duration of an event, so you could call it simply `duration`. Further, a string `55.3.244.1` might identify
the `client` making a request.
The `TYPE` is the type you wish to cast your named field. `int`, `long`, `double`, `float` and `boolean` are supported types for coercion.
For example, you might want to match the following text:
[source,txt]
--------------------------------------------------
3.44 55.3.244.1
--------------------------------------------------
You may know that the message in the example is a number followed by an IP address. You can match this text by using the following
Grok expression.
[source,txt]
--------------------------------------------------
%{NUMBER:duration} %{IP:client}
--------------------------------------------------
[[using-grok]]
==== Using the Grok Processor in a Pipeline
[[grok-options]]
.Grok Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to use for grok expression parsing
| `patterns` | yes | - | An ordered list of grok expression to match and extract named captures with. Returns on the first expression in the list that matches.
| `pattern_definitions` | no | - | A map of pattern-name and pattern tuples defining custom patterns to be used by the current processor. Patterns matching existing names will override the pre-existing definition.
| `trace_match` | no | false | when true, `_ingest._grok_match_index` will be inserted into your matched document's metadata with the index into the pattern found in `patterns` that matched.
| `ignore_missing` | no | false | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
Here is an example of using the provided patterns to extract out and name structured fields from a string field in
a document.
[source,js]
--------------------------------------------------
{
"message": "55.3.244.1 GET /index.html 15824 0.043"
}
--------------------------------------------------
// NOTCONSOLE
The pattern for this could be:
[source,txt]
--------------------------------------------------
%{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}
--------------------------------------------------
Here is an example pipeline for processing the above document by using Grok:
[source,js]
--------------------------------------------------
{
"description" : "...",
"processors": [
{
"grok": {
"field": "message",
"patterns": ["%{IP:client} %{WORD:method} %{URIPATHPARAM:request} %{NUMBER:bytes} %{NUMBER:duration}"]
}
}
]
}
--------------------------------------------------
// NOTCONSOLE
This pipeline will insert these named captures as new fields within the document, like so:
[source,js]
--------------------------------------------------
{
"message": "55.3.244.1 GET /index.html 15824 0.043",
"client": "55.3.244.1",
"method": "GET",
"request": "/index.html",
"bytes": 15824,
"duration": "0.043"
}
--------------------------------------------------
// NOTCONSOLE
[[custom-patterns]]
==== Custom Patterns
The Grok processor comes pre-packaged with a base set of pattern. These patterns may not always have
what you are looking for. Pattern have a very basic format. Each entry describes has a name and the pattern itself.
You can add your own patterns to a processor definition under the `pattern_definitions` option.
Here is an example of a pipeline specifying custom pattern definitions:
[source,js]
--------------------------------------------------
{
"description" : "...",
"processors": [
{
"grok": {
"field": "message",
"patterns": ["my %{FAVORITE_DOG:dog} is colored %{RGB:color}"],
"pattern_definitions" : {
"FAVORITE_DOG" : "beagle",
"RGB" : "RED|GREEN|BLUE"
}
}
}
]
}
--------------------------------------------------
// NOTCONSOLE
[[trace-match]]
==== Providing Multiple Match Patterns
Sometimes one pattern is not enough to capture the potential structure of a field. Let's assume we
want to match all messages that contain your favorite pet breeds of either cats or dogs. One way to accomplish
this is to provide two distinct patterns that can be matched, instead of one really complicated expression capturing
the same `or` behavior.
Here is an example of such a configuration executed against the simulate API:
[source,js]
--------------------------------------------------
POST _ingest/pipeline/_simulate
{
"pipeline": {
"description" : "parse multiple patterns",
"processors": [
{
"grok": {
"field": "message",
"patterns": ["%{FAVORITE_DOG:pet}", "%{FAVORITE_CAT:pet}"],
"pattern_definitions" : {
"FAVORITE_DOG" : "beagle",
"FAVORITE_CAT" : "burmese"
}
}
}
]
},
"docs":[
{
"_source": {
"message": "I love burmese cats!"
}
}
]
}
--------------------------------------------------
// CONSOLE
response:
[source,js]
--------------------------------------------------
{
"docs": [
{
"doc": {
"_type": "_type",
"_index": "_index",
"_id": "_id",
"_source": {
"message": "I love burmese cats!",
"pet": "burmese"
},
"_ingest": {
"timestamp": "2016-11-08T19:43:03.850+0000"
}
}
}
]
}
--------------------------------------------------
// TESTRESPONSE[s/2016-11-08T19:43:03.850\+0000/$body.docs.0.doc._ingest.timestamp/]
Both patterns will set the field `pet` with the appropriate match, but what if we want to trace which of our
patterns matched and populated our fields? We can do this with the `trace_match` parameter. Here is the output of
that same pipeline, but with `"trace_match": true` configured:
////
Hidden setup for example:
[source,js]
--------------------------------------------------
POST _ingest/pipeline/_simulate
{
"pipeline": {
"description" : "parse multiple patterns",
"processors": [
{
"grok": {
"field": "message",
"patterns": ["%{FAVORITE_DOG:pet}", "%{FAVORITE_CAT:pet}"],
"trace_match": true,
"pattern_definitions" : {
"FAVORITE_DOG" : "beagle",
"FAVORITE_CAT" : "burmese"
}
}
}
]
},
"docs":[
{
"_source": {
"message": "I love burmese cats!"
}
}
]
}
--------------------------------------------------
// CONSOLE
////
[source,js]
--------------------------------------------------
{
"docs": [
{
"doc": {
"_type": "_type",
"_index": "_index",
"_id": "_id",
"_source": {
"message": "I love burmese cats!",
"pet": "burmese"
},
"_ingest": {
"_grok_match_index": "1",
"timestamp": "2016-11-08T19:43:03.850+0000"
}
}
}
]
}
--------------------------------------------------
// TESTRESPONSE[s/2016-11-08T19:43:03.850\+0000/$body.docs.0.doc._ingest.timestamp/]
In the above response, you can see that the index of the pattern that matched was `"1"`. This is to say that it was the
second (index starts at zero) pattern in `patterns` to match.
This trace metadata enables debugging which of the patterns matched. This information is stored in the ingest
metadata and will not be indexed.
[[grok-processor-rest-get]]
==== Retrieving patterns from REST endpoint
The Grok Processor comes packaged with its own REST endpoint for retrieving which patterns the processor is packaged with.
[source,js]
--------------------------------------------------
GET _ingest/processor/grok
--------------------------------------------------
// CONSOLE
The above request will return a response body containing a key-value representation of the built-in patterns dictionary.
[source,js]
--------------------------------------------------
{
"patterns" : {
"BACULA_CAPACITY" : "%{INT}{1,3}(,%{INT}{3})*",
"PATH" : "(?:%{UNIXPATH}|%{WINPATH})",
...
}
--------------------------------------------------
// NOTCONSOLE
This can be useful to reference as the built-in patterns change across versions.
[[grok-watchdog]]
==== Grok watchdog
Grok expressions that take too long to execute are interrupted and
the grok processor then fails with an exception. The grok
processor has a watchdog thread that determines when evaluation of
a grok expression takes too long and is controlled by the following
settings:
[[grok-watchdog-options]]
.Grok watchdog settings
[options="header"]
|======
| Name | Default | Description
| `ingest.grok.watchdog.interval` | 1s | How often to check whether there are grok evaluations that take longer than the maximum allowed execution time.
| `ingest.grok.watchdog.max_execution_time` | 1s | The maximum allowed execution of a grok expression evaluation.
|======

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[[gsub-processor]]
=== Gsub Processor
Converts a string field by applying a regular expression and a replacement.
If the field is not a string, the processor will throw an exception.
[[gsub-options]]
.Gsub Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to apply the replacement to
| `pattern` | yes | - | The pattern to be replaced
| `replacement` | yes | - | The string to replace the matching patterns with
| `target_field` | no | `field` | The field to assign the converted value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"gsub": {
"field": "field1",
"pattern": "\.",
"replacement": "-"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[join-processor]]
=== Join Processor
Joins each element of an array into a single string using a separator character between each element.
Throws an error when the field is not an array.
[[join-options]]
.Join Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to be separated
| `separator` | yes | - | The separator character
| `target_field` | no | `field` | The field to assign the joined value to, by default `field` is updated in-place
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"join": {
"field": "joined_array_field",
"separator": "-"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[json-processor]]
=== JSON Processor
Converts a JSON string into a structured JSON object.
[[json-options]]
.Json Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to be parsed
| `target_field` | no | `field` | The field to insert the converted structured object into
| `add_to_root` | no | false | Flag that forces the serialized json to be injected into the top level of the document. `target_field` must not be set when this option is chosen.
include::common-options.asciidoc[]
|======
All JSON-supported types will be parsed (null, boolean, number, array, object, string).
Suppose you provide this configuration of the `json` processor:
[source,js]
--------------------------------------------------
{
"json" : {
"field" : "string_source",
"target_field" : "json_target"
}
}
--------------------------------------------------
// NOTCONSOLE
If the following document is processed:
[source,js]
--------------------------------------------------
{
"string_source": "{\"foo\": 2000}"
}
--------------------------------------------------
// NOTCONSOLE
after the `json` processor operates on it, it will look like:
[source,js]
--------------------------------------------------
{
"string_source": "{\"foo\": 2000}",
"json_target": {
"foo": 2000
}
}
--------------------------------------------------
// NOTCONSOLE
If the following configuration is provided, omitting the optional `target_field` setting:
[source,js]
--------------------------------------------------
{
"json" : {
"field" : "source_and_target"
}
}
--------------------------------------------------
// NOTCONSOLE
then after the `json` processor operates on this document:
[source,js]
--------------------------------------------------
{
"source_and_target": "{\"foo\": 2000}"
}
--------------------------------------------------
// NOTCONSOLE
it will look like:
[source,js]
--------------------------------------------------
{
"source_and_target": {
"foo": 2000
}
}
--------------------------------------------------
// NOTCONSOLE
This illustrates that, unless it is explicitly named in the processor configuration, the `target_field`
is the same field provided in the required `field` configuration.

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[[kv-processor]]
=== KV Processor
This processor helps automatically parse messages (or specific event fields) which are of the foo=bar variety.
For example, if you have a log message which contains `ip=1.2.3.4 error=REFUSED`, you can parse those automatically by configuring:
[source,js]
--------------------------------------------------
{
"kv": {
"field": "message",
"field_split": " ",
"value_split": "="
}
}
--------------------------------------------------
// NOTCONSOLE
[[kv-options]]
.Kv Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to be parsed
| `field_split` | yes | - | Regex pattern to use for splitting key-value pairs
| `value_split` | yes | - | Regex pattern to use for splitting the key from the value within a key-value pair
| `target_field` | no | `null` | The field to insert the extracted keys into. Defaults to the root of the document
| `include_keys` | no | `null` | List of keys to filter and insert into document. Defaults to including all keys
| `exclude_keys` | no | `null` | List of keys to exclude from document
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
| `prefix` | no | `null` | Prefix to be added to extracted keys
| `trim_key` | no | `null` | String of characters to trim from extracted keys
| `trim_value` | no | `null` | String of characters to trim from extracted values
| `strip_brackets` | no | `false` | If `true` strip brackets `()`, `<>`, `[]` as well as quotes `'` and `"` from extracted values
include::common-options.asciidoc[]
|======

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[[lowercase-processor]]
=== Lowercase Processor
Converts a string to its lowercase equivalent.
[[lowercase-options]]
.Lowercase Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to make lowercase
| `target_field` | no | `field` | The field to assign the converted value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"lowercase": {
"field": "foo"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[pipeline-processor]]
=== Pipeline Processor
Executes another pipeline.
[[pipeline-options]]
.Pipeline Options
[options="header"]
|======
| Name | Required | Default | Description
| `name` | yes | - | The name of the pipeline to execute
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"pipeline": {
"name": "inner-pipeline"
}
}
--------------------------------------------------
// NOTCONSOLE
An example of using this processor for nesting pipelines would be:
Define an inner pipeline:
[source,js]
--------------------------------------------------
PUT _ingest/pipeline/pipelineA
{
"description" : "inner pipeline",
"processors" : [
{
"set" : {
"field": "inner_pipeline_set",
"value": "inner"
}
}
]
}
--------------------------------------------------
// CONSOLE
Define another pipeline that uses the previously defined inner pipeline:
[source,js]
--------------------------------------------------
PUT _ingest/pipeline/pipelineB
{
"description" : "outer pipeline",
"processors" : [
{
"pipeline" : {
"name": "pipelineA"
}
},
{
"set" : {
"field": "outer_pipeline_set",
"value": "outer"
}
}
]
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
Now indexing a document while applying the outer pipeline will see the inner pipeline executed
from the outer pipeline:
[source,js]
--------------------------------------------------
PUT /myindex/_doc/1?pipeline=pipelineB
{
"field": "value"
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
Response from the index request:
[source,js]
--------------------------------------------------
{
"_index": "myindex",
"_type": "_doc",
"_id": "1",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 66,
"_primary_term": 1,
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
Indexed document:
[source,js]
--------------------------------------------------
{
"field": "value",
"inner_pipeline_set": "inner",
"outer_pipeline_set": "outer"
}
--------------------------------------------------
// NOTCONSOLE

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[[remove-processor]]
=== Remove Processor
Removes existing fields. If one field doesn't exist, an exception will be thrown.
[[remove-options]]
.Remove Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | Fields to be removed. Supports <<accessing-template-fields,template snippets>>.
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
Here is an example to remove a single field:
[source,js]
--------------------------------------------------
{
"remove": {
"field": "user_agent"
}
}
--------------------------------------------------
// NOTCONSOLE
To remove multiple fields, you can use the following query:
[source,js]
--------------------------------------------------
{
"remove": {
"field": ["user_agent", "url"]
}
}
--------------------------------------------------
// NOTCONSOLE

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[[rename-processor]]
=== Rename Processor
Renames an existing field. If the field doesn't exist or the new name is already used, an exception will be thrown.
[[rename-options]]
.Rename Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to be renamed. Supports <<accessing-template-fields,template snippets>>.
| `target_field` | yes | - | The new name of the field. Supports <<accessing-template-fields,template snippets>>.
| `ignore_missing` | no | `false` | If `true` and `field` does not exist, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"rename": {
"field": "provider",
"target_field": "cloud.provider"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[script-processor]]
=== Script Processor
Allows inline and stored scripts to be executed within ingest pipelines.
See <<modules-scripting-using, How to use scripts>> to learn more about writing scripts. The Script Processor
leverages caching of compiled scripts for improved performance. Since the
script specified within the processor is potentially re-compiled per document, it is important
to understand how script caching works. To learn more about
caching see <<modules-scripting-using-caching, Script Caching>>.
[[script-options]]
.Script Options
[options="header"]
|======
| Name | Required | Default | Description
| `lang` | no | "painless" | The scripting language
| `id` | no | - | The stored script id to refer to
| `source` | no | - | An inline script to be executed
| `params` | no | - | Script Parameters
include::common-options.asciidoc[]
|======
One of `id` or `source` options must be provided in order to properly reference a script to execute.
You can access the current ingest document from within the script context by using the `ctx` variable.
The following example sets a new field called `field_a_plus_b_times_c` to be the sum of two existing
numeric fields `field_a` and `field_b` multiplied by the parameter param_c:
[source,js]
--------------------------------------------------
{
"script": {
"lang": "painless",
"source": "ctx.field_a_plus_b_times_c = (ctx.field_a + ctx.field_b) * params.param_c",
"params": {
"param_c": 10
}
}
}
--------------------------------------------------
// NOTCONSOLE
It is possible to use the Script Processor to manipulate document metadata like `_index` and `_type` during
ingestion. Here is an example of an Ingest Pipeline that renames the index and type to `my_index` no matter what
was provided in the original index request:
[source,js]
--------------------------------------------------
PUT _ingest/pipeline/my_index
{
"description": "use index:my_index and type:_doc",
"processors": [
{
"script": {
"source": """
ctx._index = 'my_index';
ctx._type = '_doc';
"""
}
}
]
}
--------------------------------------------------
// CONSOLE
Using the above pipeline, we can attempt to index a document into the `any_index` index.
[source,js]
--------------------------------------------------
PUT any_index/_doc/1?pipeline=my_index
{
"message": "text"
}
--------------------------------------------------
// CONSOLE
// TEST[continued]
The response from the above index request:
[source,js]
--------------------------------------------------
{
"_index": "my_index",
"_type": "_doc",
"_id": "1",
"_version": 1,
"result": "created",
"_shards": {
"total": 2,
"successful": 1,
"failed": 0
},
"_seq_no": 89,
"_primary_term": 1,
}
--------------------------------------------------
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
In the above response, you can see that our document was actually indexed into `my_index` instead of
`any_index`. This type of manipulation is often convenient in pipelines that have various branches of transformation,
and depending on the progress made, indexed into different indices.
[[set-processor]]
=== Set Processor
Sets one field and associates it with the specified value. If the field already exists,
its value will be replaced with the provided one.

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[[ingest-node-set-security-user-processor]]
=== Set Security User Processor
Sets user-related details (such as `username`, `roles`, `email`, `full_name`
and `metadata` ) from the current
authenticated user to the current document by pre-processing the ingest.
IMPORTANT: Requires an authenticated user for the index request.
[[set-security-user-options]]
.Set Security User Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to store the user information into.
| `properties` | no | [`username`, `roles`, `email`, `full_name`, `metadata`] | Controls what user related properties are added to the `field`.
include::common-options.asciidoc[]
|======
The following example adds all user details for the current authenticated user
to the `user` field for all documents that are processed by this pipeline:
[source,js]
--------------------------------------------------
{
"processors" : [
{
"set_security_user": {
"field": "user"
}
}
]
}
--------------------------------------------------
// NOTCONSOLE

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[[set-options]]
.Set Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to insert, upsert, or update. Supports <<accessing-template-fields,template snippets>>.
| `value` | yes | - | The value to be set for the field. Supports <<accessing-template-fields,template snippets>>.
| `override` | no | true | If processor will update fields with pre-existing non-null-valued field. When set to `false`, such fields will not be touched.
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"set": {
"field": "host.os.name",
"value": "{{os}}"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[sort-processor]]
=== Sort Processor
Sorts the elements of an array ascending or descending. Homogeneous arrays of numbers will be sorted
numerically, while arrays of strings or heterogeneous arrays of strings + numbers will be sorted lexicographically.
Throws an error when the field is not an array.
[[sort-options]]
.Sort Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to be sorted
| `order` | no | `"asc"` | The sort order to use. Accepts `"asc"` or `"desc"`.
| `target_field` | no | `field` | The field to assign the sorted value to, by default `field` is updated in-place
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"sort": {
"field": "array_field_to_sort",
"order": "desc"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[split-processor]]
=== Split Processor
Splits a field into an array using a separator character. Only works on string fields.
[[split-options]]
.Split Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to split
| `separator` | yes | - | A regex which matches the separator, eg `,` or `\s+`
| `target_field` | no | `field` | The field to assign the split value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"split": {
"field": "my_field",
"separator": "\\s+" <1>
}
}
--------------------------------------------------
// NOTCONSOLE
<1> Treat all consecutive whitespace characters as a single separator

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[[trim-processor]]
=== Trim Processor
Trims whitespace from field.
NOTE: This only works on leading and trailing whitespace.
[[trim-options]]
.Trim Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The string-valued field to trim whitespace from
| `target_field` | no | `field` | The field to assign the trimmed value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"trim": {
"field": "foo"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[uppercase-processor]]
=== Uppercase Processor
Converts a string to its uppercase equivalent.
[[uppercase-options]]
.Uppercase Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to make uppercase
| `target_field` | no | `field` | The field to assign the converted value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"uppercase": {
"field": "foo"
}
}
--------------------------------------------------
// NOTCONSOLE

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[[urldecode-processor]]
=== URL Decode Processor
URL-decodes a string
[[urldecode-options]]
.URL Decode Options
[options="header"]
|======
| Name | Required | Default | Description
| `field` | yes | - | The field to decode
| `target_field` | no | `field` | The field to assign the converted value to, by default `field` is updated in-place
| `ignore_missing` | no | `false` | If `true` and `field` does not exist or is `null`, the processor quietly exits without modifying the document
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"urldecode": {
"field": "my_url_to_decode"
}
}
--------------------------------------------------
// NOTCONSOLE