Ingest processor referenceedit

An ingest pipeline is made up of a sequence of processors that are applied to documents as they are ingested into an index. Each processor performs a specific task, such as filtering, transforming, or enriching data.

Each successive processor depends on the output of the previous processor, so the order of processors is important. The modified documents are indexed into Elasticsearch after all processors are applied.

Elasticsearch includes over 40 configurable processors. The subpages in this section contain reference documentation for each processor. To get a list of available processors, use the nodes info API.

response =
  node_id: 'ingest',
  filter_path: 'nodes.*.ingest.processors'
puts response
GET _nodes/ingest?filter_path=nodes.*.ingest.processors

Ingest processors by categoryedit

We’ve categorized the available processors on this page and summarized their functions. This will help you find the right processor for your use case.

Data enrichment processorsedit

General outcomesedit

append processor
Appends a value to a field.
date_index_name processor
Points documents to the right time-based index based on a date or timestamp field.
enrich processor
Enriches documents with data from another index.

Refer to Enrich your data for detailed examples of how to use the enrich processor to add data from your existing indices to incoming documents during ingest.

inference processor
Uses machine learning to classify and tag text fields.

Specific outcomesedit

attachment processor
Parses and indexes binary data, such as PDFs and Word documents.
circle processor
Converts a location field to a Geo-Point field.
community_id processor
Computes the Community ID for network flow data.
fingerprint processor
Computes a hash of the document’s content.
geo_grid processor
Converts geo-grid definitions of grid tiles or cells to regular bounding boxes or polygons which describe their shape.
geoip processor
Adds information about the geographical location of an IPv4 or IPv6 address.
network_direction processor
Calculates the network direction given a source IP address, destination IP address, and a list of internal networks.
registered_domain processor
Extracts the registered domain (also known as the effective top-level domain or eTLD), sub-domain, and top-level domain from a fully qualified domain name (FQDN).
set_security_user processor
Sets user-related details (such as username, roles, email, full_name,metadata, api_key, realm and authentication_type) from the current authenticated user to the current document by pre-processing the ingest.
uri_parts processor
Parses a Uniform Resource Identifier (URI) string and extracts its components as an object.
urldecode processor
URL-decodes a string.
user_agent processor
Parses user-agent strings to extract information about web clients.

Data transformation processorsedit

General outcomesedit

convert processor
Converts a field in the currently ingested document to a different type, such as converting a string to an integer.
dissect processor
Extracts structured fields out of a single text field within a document. Unlike the grok processor, dissect does not use regular expressions. This makes the dissect’s a simpler and often faster alternative.
grok processor
Extracts structured fields out of a single text field within a document, using the Grok regular expression dialect that supports reusable aliased expressions.
gsub processor
Converts a string field by applying a regular expression and a replacement.
redact processor
Uses the Grok rules engine to obscure text in the input document matching the given Grok patterns.
rename processor
Renames an existing field.
set processor
Sets a value on a field.

Specific outcomesedit

bytes processor
Converts a human-readable byte value to its value in bytes (for example 1kb becomes 1024).
csv processor
Extracts a single line of CSV data from a text field.
date processor
Extracts and converts date fields.
dot_expand processor
Expands a field with dots into an object field.
html_strip processor
Removes HTML tags from a field.
join processor
Joins each element of an array into a single string using a separator character between each element.
kv processor
Parse messages (or specific event fields) containing key-value pairs.
lowercase processor and uppercase processor
Converts a string field to lowercase or uppercase.
split processor
Splits a field into an array of values.
trim processor
Trims whitespace from field.

Data filtering processorsedit

drop processor
Drops the document without raising any errors.
remove processor
Removes fields from documents.

Pipeline handling processorsedit

fail processor
Raises an exception. Useful for when you expect a pipeline to fail and want to relay a specific message to the requester.
pipeline processor
Executes another pipeline.
reroute processor
Reroutes documents to another target index or data stream.

Array/JSON handling processorsedit

for_each processor
Runs an ingest processor on each element of an array or object.
json processor
Converts a JSON string into a structured JSON object.
script processor
Runs an inline or stored script on incoming documents. The script runs in the painless ingest context.
sort processor
Sorts the elements of an array in ascending or descending order.

Add additional processorsedit

You can install additional processors as plugins.

You must install any plugin processors on all nodes in your cluster. Otherwise, Elasticsearch will fail to create pipelines containing the processor.

Mark a plugin as mandatory by setting plugin.mandatory in elasticsearch.yml. A node will fail to start if a mandatory plugin is not installed.

plugin.mandatory: my-ingest-plugin