853 lines
26 KiB
Plaintext
853 lines
26 KiB
Plaintext
[[pipeline]]
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== Pipeline Definition
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A pipeline is a definition of a series of <<ingest-processors, processors>> that are to be executed
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in the same order as they are declared. A pipeline consists of two main fields: a `description`
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and a list of `processors`:
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[source,js]
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--------------------------------------------------
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{
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"description" : "...",
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"processors" : [ ... ]
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}
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--------------------------------------------------
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// NOTCONSOLE
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The `description` is a special field to store a helpful description of
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what the pipeline does.
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The `processors` parameter defines a list of processors to be executed in
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order.
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[[accessing-data-in-pipelines]]
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== Accessing Data in Pipelines
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The processors in a pipeline have read and write access to documents that pass through the pipeline.
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The processors can access fields in the source of a document and the document's metadata fields.
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[float]
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[[accessing-source-fields]]
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=== Accessing Fields in the Source
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Accessing a field in the source is straightforward. You simply refer to fields by
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their name. For example:
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "my_field",
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"value": 582.1
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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On top of this, fields from the source are always accessible via the `_source` prefix:
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "_source.my_field",
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"value": 582.1
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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[float]
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[[accessing-metadata-fields]]
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=== Accessing Metadata Fields
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You can access metadata fields in the same way that you access fields in the source. This
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is possible because Elasticsearch doesn't allow fields in the source that have the
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same name as metadata fields.
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The following example sets the `_id` metadata field of a document to `1`:
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "_id",
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"value": "1"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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The following metadata fields are accessible by a processor: `_index`, `_type`, `_id`, `_routing`.
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[float]
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[[accessing-ingest-metadata]]
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=== Accessing Ingest Metadata Fields
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Beyond metadata fields and source fields, ingest also adds ingest metadata to the documents that it processes.
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These metadata properties are accessible under the `_ingest` key. Currently ingest adds the ingest timestamp
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under the `_ingest.timestamp` key of the ingest metadata. The ingest timestamp is the time when Elasticsearch
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received the index or bulk request to pre-process the document.
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Any processor can add ingest-related metadata during document processing. Ingest metadata is transient
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and is lost after a document has been processed by the pipeline. Therefore, ingest metadata won't be indexed.
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The following example adds a field with the name `received`. The value is the ingest timestamp:
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "received",
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"value": "{{_ingest.timestamp}}"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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Unlike Elasticsearch metadata fields, the ingest metadata field name `_ingest` can be used as a valid field name
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in the source of a document. Use `_source._ingest` to refer to the field in the source document. Otherwise, `_ingest`
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will be interpreted as an ingest metadata field.
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[float]
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[[accessing-template-fields]]
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=== Accessing Fields and Metafields in Templates
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A number of processor settings also support templating. Settings that support templating can have zero or more
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template snippets. A template snippet begins with `{{` and ends with `}}`.
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Accessing fields and metafields in templates is exactly the same as via regular processor field settings.
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The following example adds a field named `field_c`. Its value is a concatenation of
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the values of `field_a` and `field_b`.
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "field_c",
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"value": "{{field_a}} {{field_b}}"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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The following example uses the value of the `geoip.country_iso_code` field in the source
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to set the index that the document will be indexed into:
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "_index",
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"value": "{{geoip.country_iso_code}}"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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Dynamic field names are also supported. This example sets the field named after the
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value of `service` to the value of the field `code`:
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[source,js]
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--------------------------------------------------
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{
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"set": {
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"field": "{{service}}",
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"value": "{{code}}"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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[[ingest-conditionals]]
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== Conditional Execution in Pipelines
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Each processor allows for an optional `if` condition to determine if that
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processor should be executed or skipped. The value of the `if` is a
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<<modules-scripting-painless, Painless>> script that needs to evaluate
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to `true` or `false`.
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For example the following processor will <<drop-processor,drop>> the document
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(i.e. not index it) if the input document has a field named `network_name`
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and it is equal to `Guest`.
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/drop_guests_network
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{
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"processors": [
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{
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"drop": {
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"if": "ctx.network_name == 'Guest'"
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}
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}
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]
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}
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--------------------------------------------------
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Using that pipeline for an index request:
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[source,console]
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--------------------------------------------------
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POST test/_doc/1?pipeline=drop_guests_network
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{
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"network_name" : "Guest"
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}
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--------------------------------------------------
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// TEST[continued]
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Results in nothing indexed since the conditional evaluated to `true`.
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[source,console-result]
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--------------------------------------------------
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{
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"_index": "test",
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"_type": "_doc",
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"_id": "1",
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"_version": -3,
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"result": "noop",
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"_shards": {
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"total": 0,
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"successful": 0,
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"failed": 0
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}
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}
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--------------------------------------------------
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[[ingest-conditional-nullcheck]]
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=== Handling Nested Fields in Conditionals
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Source documents often contain nested fields. Care should be taken
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to avoid NullPointerExceptions if the parent object does not exist
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in the document. For example `ctx.a.b.c` can throw an NullPointerExceptions
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if the source document does not have top level `a` object, or a second
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level `b` object.
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To help protect against NullPointerExceptions, null safe operations should be used.
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Fortunately, Painless makes {painless}/painless-operators-reference.html#null-safe-operator[null safe]
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operations easy with the `?.` operator.
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/drop_guests_network
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{
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"processors": [
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{
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"drop": {
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"if": "ctx.network?.name == 'Guest'"
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}
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}
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]
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}
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--------------------------------------------------
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The following document will get <<drop-processor,dropped>> correctly:
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[source,console]
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--------------------------------------------------
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POST test/_doc/1?pipeline=drop_guests_network
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{
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"network": {
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"name": "Guest"
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}
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}
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--------------------------------------------------
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// TEST[continued]
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Thanks to the `?.` operator the following document will not throw an error.
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If the pipeline used a `.` the following document would throw a NullPointerException
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since the `network` object is not part of the source document.
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[source,console]
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--------------------------------------------------
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POST test/_doc/2?pipeline=drop_guests_network
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{
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"foo" : "bar"
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}
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--------------------------------------------------
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// TEST[continued]
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////
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Hidden example assertion:
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[source,console]
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--------------------------------------------------
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GET test/_doc/2
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--------------------------------------------------
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// TEST[continued]
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[source,console-result]
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--------------------------------------------------
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{
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"_index": "test",
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"_type": "_doc",
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"_id": "2",
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"_version": 1,
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"_seq_no": 22,
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"_primary_term": 1,
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"found": true,
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"_source": {
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"foo": "bar"
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term": 1/"_primary_term" : $body._primary_term/]
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////
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The source document can also use dot delimited fields to represent nested fields.
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For example instead the source document defining the fields nested:
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[source,js]
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--------------------------------------------------
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{
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"network": {
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"name": "Guest"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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The source document may have the nested fields flattened as such:
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[source,js]
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--------------------------------------------------
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{
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"network.name": "Guest"
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}
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--------------------------------------------------
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// NOTCONSOLE
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If this is the case, use the <<dot-expand-processor, Dot Expand Processor>>
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so that the nested fields may be used in a conditional.
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/drop_guests_network
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{
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"processors": [
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{
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"dot_expander": {
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"field": "network.name"
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}
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},
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{
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"drop": {
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"if": "ctx.network?.name == 'Guest'"
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}
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}
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]
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}
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--------------------------------------------------
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Now the following input document can be used with a conditional in the pipeline.
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[source,console]
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--------------------------------------------------
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POST test/_doc/3?pipeline=drop_guests_network
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{
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"network.name": "Guest"
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}
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--------------------------------------------------
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// TEST[continued]
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The `?.` operators works well for use in the `if` conditional
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because the {painless}/painless-operators-reference.html#null-safe-operator[null safe operator]
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returns null if the object is null and `==` is null safe (as well as many other
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{painless}/painless-operators.html[painless operators]).
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However, calling a method such as `.equalsIgnoreCase` is not null safe
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and can result in a NullPointerException.
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Some situations allow for the same functionality but done so in a null safe manner.
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For example: `'Guest'.equalsIgnoreCase(ctx.network?.name)` is null safe because
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`Guest` is always non null, but `ctx.network?.name.equalsIgnoreCase('Guest')` is not null safe
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since `ctx.network?.name` can return null.
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Some situations require an explicit null check. In the following example there
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is not null safe alternative, so an explicit null check is needed.
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[source,js]
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--------------------------------------------------
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{
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"drop": {
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"if": "ctx.network?.name != null && ctx.network.name.contains('Guest')"
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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[[ingest-conditional-complex]]
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=== Complex Conditionals
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The `if` condition can be more then a simple equality check.
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The full power of the <<modules-scripting-painless, Painless Scripting Language>> is available and
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running in the {painless}/painless-ingest-processor-context.html[ingest processor context].
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IMPORTANT: The value of ctx is read-only in `if` conditions.
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A more complex `if` condition that drops the document (i.e. not index it)
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unless it has a multi-valued tag field with at least one value that contains the characters
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`prod` (case insensitive).
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/not_prod_dropper
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{
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"processors": [
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{
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"drop": {
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"if": "Collection tags = ctx.tags;if(tags != null){for (String tag : tags) {if (tag.toLowerCase().contains('prod')) { return false;}}} return true;"
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}
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}
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]
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}
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--------------------------------------------------
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The conditional needs to be all on one line since JSON does not
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support new line characters. However, Kibana's console supports
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a triple quote syntax to help with writing and debugging
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scripts like these.
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[source,js]
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--------------------------------------------------
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PUT _ingest/pipeline/not_prod_dropper
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{
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"processors": [
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{
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"drop": {
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"if": """
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Collection tags = ctx.tags;
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if(tags != null){
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for (String tag : tags) {
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if (tag.toLowerCase().contains('prod')) {
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return false;
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}
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}
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}
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return true;
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"""
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}
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}
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]
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}
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--------------------------------------------------
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// NOTCONSOLE
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// TEST[continued]
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[source,console]
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--------------------------------------------------
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POST test/_doc/1?pipeline=not_prod_dropper
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{
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"tags": ["application:myapp", "env:Stage"]
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}
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--------------------------------------------------
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// TEST[continued]
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The document is <<drop-processor,dropped>> since `prod` (case insensitive)
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is not found in the tags.
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The following document is indexed (i.e. not dropped) since
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`prod` (case insensitive) is found in the tags.
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[source,console]
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--------------------------------------------------
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POST test/_doc/2?pipeline=not_prod_dropper
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{
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"tags": ["application:myapp", "env:Production"]
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}
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--------------------------------------------------
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// TEST[continued]
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////
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Hidden example assertion:
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[source,console]
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--------------------------------------------------
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GET test/_doc/2
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--------------------------------------------------
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// TEST[continued]
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[source,console-result]
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--------------------------------------------------
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{
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"_index": "test",
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"_type": "_doc",
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"_id": "2",
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"_version": 1,
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"_seq_no": 34,
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"_primary_term": 1,
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"found": true,
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"_source": {
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"tags": [
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"application:myapp",
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"env:Production"
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]
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}
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}
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--------------------------------------------------
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// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
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////
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The <<simulate-pipeline-api>> with verbose can be used to help build out
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complex conditionals. If the conditional evaluates to false it will be
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omitted from the verbose results of the simulation since the document will not change.
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Care should be taken to avoid overly complex or expensive conditional checks
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since the condition needs to be checked for each and every document.
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[[conditionals-with-multiple-pipelines]]
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=== Conditionals with the Pipeline Processor
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The combination of the `if` conditional and the <<pipeline-processor>> can result in a simple,
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yet powerful means to process heterogeneous input. For example, you can define a single pipeline
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that delegates to other pipelines based on some criteria.
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/logs_pipeline
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{
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"description": "A pipeline of pipelines for log files",
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"version": 1,
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"processors": [
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{
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"pipeline": {
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"if": "ctx.service?.name == 'apache_httpd'",
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"name": "httpd_pipeline"
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}
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},
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{
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"pipeline": {
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"if": "ctx.service?.name == 'syslog'",
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"name": "syslog_pipeline"
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}
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},
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{
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"fail": {
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"message": "This pipeline requires service.name to be either `syslog` or `apache_httpd`"
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}
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}
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]
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}
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--------------------------------------------------
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The above example allows consumers to point to a single pipeline for all log based index requests.
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Based on the conditional, the correct pipeline will be called to process that type of data.
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This pattern works well with a <<dynamic-index-settings, default pipeline>> defined in an index mapping
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template for all indexes that hold data that needs pre-index processing.
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[[conditionals-with-regex]]
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=== Conditionals with the Regular Expressions
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The `if` conditional is implemented as a Painless script, which requires
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{painless}//painless-regexes.html[explicit support for regular expressions].
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`script.painless.regex.enabled: true` must be set in `elasticsearch.yml` to use regular
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expressions in the `if` condition.
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If regular expressions are enabled, operators such as `=~` can be used against a `/pattern/` for conditions.
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For example:
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[source,console]
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--------------------------------------------------
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PUT _ingest/pipeline/check_url
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{
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"processors": [
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{
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"set": {
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"if": "ctx.href?.url =~ /^http[^s]/",
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"field": "href.insecure",
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"value": true
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}
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}
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]
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}
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--------------------------------------------------
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[source,console]
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--------------------------------------------------
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POST test/_doc/1?pipeline=check_url
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{
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"href": {
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"url": "http://www.elastic.co/"
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}
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}
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--------------------------------------------------
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// TEST[continued]
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Results in:
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////
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Hidden example assertion:
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[source,console]
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--------------------------------------------------
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GET test/_doc/1
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--------------------------------------------------
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// TEST[continued]
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////
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[source,console-result]
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--------------------------------------------------
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{
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"_index": "test",
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"_type": "_doc",
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"_id": "1",
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"_version": 1,
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"_seq_no": 60,
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"_primary_term": 1,
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"found": true,
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"_source": {
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"href": {
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"insecure": true,
|
|
"url": "http://www.elastic.co/"
|
|
}
|
|
}
|
|
}
|
|
--------------------------------------------------
|
|
// TESTRESPONSE[s/"_seq_no": \d+/"_seq_no" : $body._seq_no/ s/"_primary_term" : 1/"_primary_term" : $body._primary_term/]
|
|
|
|
|
|
Regular expressions can be expensive and should be avoided if viable
|
|
alternatives exist.
|
|
|
|
For example in this case `startsWith` can be used to get the same result
|
|
without using a regular expression:
|
|
|
|
[source,console]
|
|
--------------------------------------------------
|
|
PUT _ingest/pipeline/check_url
|
|
{
|
|
"processors": [
|
|
{
|
|
"set": {
|
|
"if": "ctx.href?.url != null && ctx.href.url.startsWith('http://')",
|
|
"field": "href.insecure",
|
|
"value": true
|
|
}
|
|
}
|
|
]
|
|
}
|
|
--------------------------------------------------
|
|
|
|
[[handling-failure-in-pipelines]]
|
|
== Handling Failures in Pipelines
|
|
|
|
In its simplest use case, a pipeline defines a list of processors that
|
|
are executed sequentially, and processing halts at the first exception. This
|
|
behavior may not be desirable when failures are expected. For example, you may have logs
|
|
that don't match the specified grok expression. Instead of halting execution, you may
|
|
want to index such documents into a separate index.
|
|
|
|
To enable this behavior, you can use the `on_failure` parameter. The `on_failure` parameter
|
|
defines a list of processors to be executed immediately following the failed processor.
|
|
You can specify this parameter at the pipeline level, as well as at the processor
|
|
level. If a processor specifies an `on_failure` configuration, whether
|
|
it is empty or not, any exceptions that are thrown by the processor are caught, and the
|
|
pipeline continues executing the remaining processors. Because you can define further processors
|
|
within the scope of an `on_failure` statement, you can nest failure handling.
|
|
|
|
The following example defines a pipeline that renames the `foo` field in
|
|
the processed document to `bar`. If the document does not contain the `foo` field, the processor
|
|
attaches an error message to the document for later analysis within
|
|
Elasticsearch.
|
|
|
|
[source,js]
|
|
--------------------------------------------------
|
|
{
|
|
"description" : "my first pipeline with handled exceptions",
|
|
"processors" : [
|
|
{
|
|
"rename" : {
|
|
"field" : "foo",
|
|
"target_field" : "bar",
|
|
"on_failure" : [
|
|
{
|
|
"set" : {
|
|
"field" : "error",
|
|
"value" : "field \"foo\" does not exist, cannot rename to \"bar\""
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
]
|
|
}
|
|
--------------------------------------------------
|
|
// NOTCONSOLE
|
|
|
|
The following example defines an `on_failure` block on a whole pipeline to change
|
|
the index to which failed documents get sent.
|
|
|
|
[source,js]
|
|
--------------------------------------------------
|
|
{
|
|
"description" : "my first pipeline with handled exceptions",
|
|
"processors" : [ ... ],
|
|
"on_failure" : [
|
|
{
|
|
"set" : {
|
|
"field" : "_index",
|
|
"value" : "failed-{{ _index }}"
|
|
}
|
|
}
|
|
]
|
|
}
|
|
--------------------------------------------------
|
|
// NOTCONSOLE
|
|
|
|
Alternatively instead of defining behaviour in case of processor failure, it is also possible
|
|
to ignore a failure and continue with the next processor by specifying the `ignore_failure` setting.
|
|
|
|
In case in the example below the field `foo` doesn't exist the failure will be caught and the pipeline
|
|
continues to execute, which in this case means that the pipeline does nothing.
|
|
|
|
[source,js]
|
|
--------------------------------------------------
|
|
{
|
|
"description" : "my first pipeline with handled exceptions",
|
|
"processors" : [
|
|
{
|
|
"rename" : {
|
|
"field" : "foo",
|
|
"target_field" : "bar",
|
|
"ignore_failure" : true
|
|
}
|
|
}
|
|
]
|
|
}
|
|
--------------------------------------------------
|
|
// NOTCONSOLE
|
|
|
|
The `ignore_failure` can be set on any processor and defaults to `false`.
|
|
|
|
[float]
|
|
[[accessing-error-metadata]]
|
|
=== Accessing Error Metadata From Processors Handling Exceptions
|
|
|
|
You may want to retrieve the actual error message that was thrown
|
|
by a failed processor. To do so you can access metadata fields called
|
|
`on_failure_message`, `on_failure_processor_type`, and `on_failure_processor_tag`. These fields are only accessible
|
|
from within the context of an `on_failure` block.
|
|
|
|
Here is an updated version of the example that you
|
|
saw earlier. But instead of setting the error message manually, the example leverages the `on_failure_message`
|
|
metadata field to provide the error message.
|
|
|
|
[source,js]
|
|
--------------------------------------------------
|
|
{
|
|
"description" : "my first pipeline with handled exceptions",
|
|
"processors" : [
|
|
{
|
|
"rename" : {
|
|
"field" : "foo",
|
|
"to" : "bar",
|
|
"on_failure" : [
|
|
{
|
|
"set" : {
|
|
"field" : "error",
|
|
"value" : "{{ _ingest.on_failure_message }}"
|
|
}
|
|
}
|
|
]
|
|
}
|
|
}
|
|
]
|
|
}
|
|
--------------------------------------------------
|
|
// NOTCONSOLE
|
|
|
|
[[ingest-processors]]
|
|
== Processors
|
|
|
|
All processors are defined in the following way within a pipeline definition:
|
|
|
|
[source,js]
|
|
--------------------------------------------------
|
|
{
|
|
"PROCESSOR_NAME" : {
|
|
... processor configuration options ...
|
|
}
|
|
}
|
|
--------------------------------------------------
|
|
// NOTCONSOLE
|
|
|
|
Each processor defines its own configuration parameters, but all processors have
|
|
the ability to declare `tag`, `on_failure` and `if` fields. These fields are optional.
|
|
|
|
A `tag` is simply a string identifier of the specific instantiation of a certain
|
|
processor in a pipeline. The `tag` field does not affect the processor's behavior,
|
|
but is very useful for bookkeeping and tracing errors to specific processors.
|
|
|
|
The `if` field must contain a script that returns a boolean value. If the script evaluates to `true`
|
|
then the processor will be executed for the given document otherwise it will be skipped.
|
|
The `if` field takes an object with the script fields defined in <<script-processor, script-options>>
|
|
and accesses a read only version of the document via the same `ctx` variable used by scripts in the
|
|
<<script-processor>>.
|
|
|
|
[source,js]
|
|
--------------------------------------------------
|
|
{
|
|
"set": {
|
|
"if": "ctx.foo == 'someValue'",
|
|
"field": "found",
|
|
"value": true
|
|
}
|
|
}
|
|
--------------------------------------------------
|
|
// NOTCONSOLE
|
|
|
|
See <<ingest-conditionals>> to learn more about the `if` field and conditional execution.
|
|
|
|
See <<handling-failure-in-pipelines>> to learn more about the `on_failure` field and error handling in pipelines.
|
|
|
|
The <<cluster-nodes-info,node info API>> can be used to figure out what processors are available in a cluster.
|
|
The <<cluster-nodes-info,node info API>> will provide a per node list of what processors are available.
|
|
|
|
Custom processors must be installed on all nodes. The put pipeline API will fail if a processor specified in a pipeline
|
|
doesn't exist on all nodes. If you rely on custom processor plugins make sure to mark these plugins as mandatory by adding
|
|
`plugin.mandatory` setting to the `config/elasticsearch.yml` file, for example:
|
|
|
|
[source,yaml]
|
|
--------------------------------------------------
|
|
plugin.mandatory: ingest-attachment
|
|
--------------------------------------------------
|
|
|
|
A node will not start if this plugin is not available.
|
|
|
|
The <<cluster-nodes-stats,node stats API>> can be used to fetch ingest usage statistics, globally and on a per
|
|
pipeline basis. Useful to find out which pipelines are used the most or spent the most time on preprocessing.
|
|
|
|
[float]
|
|
=== Ingest Processor Plugins
|
|
|
|
Additional ingest processors can be implemented and installed as Elasticsearch {plugins}/intro.html[plugins].
|
|
See {plugins}/ingest.html[Ingest plugins] for information about the available ingest plugins.
|
|
|
|
include::processors/append.asciidoc[]
|
|
include::processors/bytes.asciidoc[]
|
|
include::processors/circle.asciidoc[]
|
|
include::processors/convert.asciidoc[]
|
|
include::processors/date.asciidoc[]
|
|
include::processors/date-index-name.asciidoc[]
|
|
include::processors/dissect.asciidoc[]
|
|
include::processors/dot-expand.asciidoc[]
|
|
include::processors/drop.asciidoc[]
|
|
include::processors/fail.asciidoc[]
|
|
include::processors/foreach.asciidoc[]
|
|
include::processors/geoip.asciidoc[]
|
|
include::processors/grok.asciidoc[]
|
|
include::processors/gsub.asciidoc[]
|
|
include::processors/html_strip.asciidoc[]
|
|
include::processors/join.asciidoc[]
|
|
include::processors/json.asciidoc[]
|
|
include::processors/kv.asciidoc[]
|
|
include::processors/lowercase.asciidoc[]
|
|
include::processors/pipeline.asciidoc[]
|
|
include::processors/remove.asciidoc[]
|
|
include::processors/rename.asciidoc[]
|
|
include::processors/script.asciidoc[]
|
|
include::processors/set.asciidoc[]
|
|
include::processors/set-security-user.asciidoc[]
|
|
include::processors/split.asciidoc[]
|
|
include::processors/sort.asciidoc[]
|
|
include::processors/trim.asciidoc[]
|
|
include::processors/uppercase.asciidoc[]
|
|
include::processors/url-decode.asciidoc[]
|
|
include::processors/user-agent.asciidoc[]
|