- Elasticsearch Guide: other versions:
- Getting Started
- Setup Elasticsearch
- Breaking changes
- Breaking changes in 5.1
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- Search and Query DSL changes
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- Analysis
- Anatomy of an analyzer
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- Modules
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- Ingest Node
- Pipeline Definition
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- Accessing Data in Pipelines
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- Processors
- Append Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Fail Processor
- Foreach Processor
- Grok Processor
- Gsub Processor
- Join Processor
- JSON Processor
- Lowercase Processor
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- Dot Expander Processor
- How To
- Testing
- Glossary of terms
- Release Notes
- 5.1.2 Release Notes
- 5.1.1 Release Notes
- 5.1.0 Release Notes
- 5.0.2 Release Notes
- 5.0.1 Release Notes
- 5.0.0 Combined Release Notes
- 5.0.0 GA Release Notes
- 5.0.0-rc1 Release Notes
- 5.0.0-beta1 Release Notes
- 5.0.0-alpha5 Release Notes
- 5.0.0-alpha4 Release Notes
- 5.0.0-alpha3 Release Notes
- 5.0.0-alpha2 Release Notes
- 5.0.0-alpha1 Release Notes
- 5.0.0-alpha1 Release Notes (Changes previously released in 2.x)
WARNING: Version 5.1 of Elasticsearch has passed its EOL date.
This documentation is no longer being maintained and may be removed. If you are running this version, we strongly advise you to upgrade. For the latest information, see the current release documentation.
Foreach Processor
editForeach Processor
edit[preview] This processor may change or be replaced by something else that provides similar functionality. This processor executes in its own context, which makes it different compared to all other processors and for features like verbose simulation the subprocessor isn’t visible. The reason we still expose this processor, is that it is the only processor that can operate on an array
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.
Table 19. Foreach Options
Name | Required | Default | Description |
---|---|---|---|
|
yes |
- |
The array field |
|
yes |
- |
The processor to execute against each field |
Assume the following document:
{ "values" : ["foo", "bar", "baz"] }
When this foreach
processor operates on this sample document:
{ "foreach" : { "field" : "values", "processor" : { "uppercase" : { "field" : "_ingest._value" } } } }
Then the document will look like this after preprocessing:
{ "values" : ["FOO", "BAR", "BAZ"] }
Let’s take a look at another example:
{ "persons" : [ { "id" : "1", "name" : "John Doe" }, { "id" : "2", "name" : "Jane Doe" } ] }
In this case, the id
field needs to be removed,
so the following foreach
processor is used:
{ "foreach" : { "field" : "persons", "processor" : { "remove" : { "field" : "_ingest._value.id" } } } }
After preprocessing the result is:
{ "persons" : [ { "name" : "John Doe" }, { "name" : "Jane Doe" } ] }
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:
{ "foreach" : { "field" : "persons", "processor" : { "remove" : { "field" : "_value.id", "on_failure" : [ { "set" : { "field", "_index", "value", "failure_index" } } ] } } } }
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 attachment processor documentation.