- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.7
- Getting started with Elasticsearch
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
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- Indexing aggregation results with transforms
- Metrics Aggregations
- Scripting
- Mapping
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Char Group Tokenizer
- Classic Tokenizer
- Edge n-gram tokenizer
- Keyword Tokenizer
- Letter Tokenizer
- Lowercase Tokenizer
- N-gram tokenizer
- Path Hierarchy Tokenizer
- Path Hierarchy Tokenizer Examples
- Pattern Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
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- Thai Tokenizer
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- Token filter reference
- Apostrophe
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- Length
- Limit token count
- Lowercase
- MinHash
- Multiplexer
- N-gram
- Normalization
- Pattern capture
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- Remove duplicates
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- Stemmer override
- Stop
- Synonym
- Synonym graph
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- Unique
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- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Index modules
- Ingest node
- Pipeline Definition
- Accessing Data in Pipelines
- Conditional Execution in Pipelines
- Handling Failures in Pipelines
- Enrich your data
- Processors
- Append Processor
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- User Agent processor
- ILM: Manage the index lifecycle
- Monitor a cluster
- Frozen indices
- Roll up or transform your data
- Set up a cluster for high availability
- Snapshot and restore
- Secure a cluster
- Overview
- Configuring security
- User authentication
- Built-in users
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- Token-based authentication services
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
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- Kerberos authentication
- Integrating with other authentication systems
- Enabling anonymous access
- Controlling the user cache
- Configuring SAML single-sign-on on the Elastic Stack
- Configuring single sign-on to the Elastic Stack using OpenID Connect
- User authorization
- Built-in roles
- Defining roles
- Security privileges
- Document level security
- Field level security
- Granting privileges for indices and aliases
- Mapping users and groups to roles
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- Submitting requests on behalf of other users
- Configuring authorization delegation
- Customizing roles and authorization
- Enabling audit logging
- Encrypting communications
- Restricting connections with IP filtering
- Cross cluster search, clients, and integrations
- Tutorial: Getting started with security
- Tutorial: Encrypting communications
- Troubleshooting
- Some settings are not returned via the nodes settings API
- Authorization exceptions
- Users command fails due to extra arguments
- Users are frequently locked out of Active Directory
- Certificate verification fails for curl on Mac
- SSLHandshakeException causes connections to fail
- Common SSL/TLS exceptions
- Common Kerberos exceptions
- Common SAML issues
- Internal Server Error in Kibana
- Setup-passwords command fails due to connection failure
- Failures due to relocation of the configuration files
- Limitations
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- Command line tools
- How To
- Glossary of terms
- REST APIs
- API conventions
- cat APIs
- cat aliases
- cat allocation
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- Cluster APIs
- Cluster allocation explain
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- Add index alias
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- OpenID Connect Prepare Authentication API
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- Transform APIs
- Usage API
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- Definitions
- Breaking changes
- Release notes
- Elasticsearch version 7.7.1
- Elasticsearch version 7.7.0
- Elasticsearch version 7.6.2
- Elasticsearch version 7.6.1
- Elasticsearch version 7.6.0
- Elasticsearch version 7.5.2
- Elasticsearch version 7.5.1
- Elasticsearch version 7.5.0
- Elasticsearch version 7.4.2
- Elasticsearch version 7.4.1
- Elasticsearch version 7.4.0
- Elasticsearch version 7.3.2
- Elasticsearch version 7.3.1
- Elasticsearch version 7.3.0
- Elasticsearch version 7.2.1
- Elasticsearch version 7.2.0
- Elasticsearch version 7.1.1
- Elasticsearch version 7.1.0
- Elasticsearch version 7.0.0
- Elasticsearch version 7.0.0-rc2
- Elasticsearch version 7.0.0-rc1
- Elasticsearch version 7.0.0-beta1
- Elasticsearch version 7.0.0-alpha2
- Elasticsearch version 7.0.0-alpha1
Analyze API
editAnalyze API
editPerforms analysis on a text string and returns the resulting tokens.
GET /_analyze { "analyzer" : "standard", "text" : "Quick Brown Foxes!" }
Path parameters
edit-
<index>
-
(Optional, string) Index used to derive the analyzer.
If specified, the
analyzer
or<field>
parameter overrides this value.If no analyzer or field are specified, the analyze API uses the default analyzer for the index.
If no index is specified or the index does not have a default analyzer, the analyze API uses the standard analyzer.
Query parameters
edit-
analyzer
-
(Optional, string) The name of the analyzer that should be applied to the provided
text
. This could be a built-in analyzer, or an analyzer that’s been configured in the index.If this parameter is not specified, the analyze API uses the analyzer defined in the field’s mapping.
If no field is specified, the analyze API uses the default analyzer for the index.
If no index is specified, or the index does not have a default analyzer, the analyze API uses the standard analyzer.
-
attributes
-
(Optional, array of strings)
Array of token attributes used to filter the output of the
explain
parameter. -
char_filter
- (Optional, array of strings) Array of character filters used to preprocess characters before the tokenizer. See Character filters reference for a list of character filters.
-
explain
-
(Optional, boolean)
If
true
, the response includes token attributes and additional details. Defaults tofalse
. [preview] The format of the additional detail information is labelled as experimental in Lucene and it may change in the future. -
field
-
(Optional, string) Field used to derive the analyzer. To use this parameter, you must specify an index.
If specified, the
analyzer
parameter overrides this value.If no field is specified, the analyze API uses the default analyzer for the index.
If no index is specified or the index does not have a default analyzer, the analyze API uses the standard analyzer.
-
filter
- (Optional, Array of strings) Array of token filters used to apply after the tokenizer. See Token filter reference for a list of token filters.
-
normalizer
- (Optional, string) Normalizer to use to convert text into a single token. See Normalizers for a list of normalizers.
-
text
- (Required, string or array of strings) Text to analyze. If an array of strings is provided, it is analyzed as a multi-value field.
-
tokenizer
- (Optional, string) Tokenizer to use to convert text into tokens. See Tokenizer reference for a list of tokenizers.
Examples
editNo index specified
editYou can apply any of the built-in analyzers to the text string without specifying an index.
GET /_analyze { "analyzer" : "standard", "text" : "this is a test" }
Array of text strings
editIf the text
parameter is provided as array of strings, it is analyzed as a multi-value field.
GET /_analyze { "analyzer" : "standard", "text" : ["this is a test", "the second text"] }
Custom analyzer
editYou can use the analyze API to test a custom transient analyzer built from
tokenizers, token filters, and char filters. Token filters use the filter
parameter:
GET /_analyze { "tokenizer" : "keyword", "filter" : ["lowercase"], "text" : "this is a test" }
GET /_analyze { "tokenizer" : "keyword", "filter" : ["lowercase"], "char_filter" : ["html_strip"], "text" : "this is a <b>test</b>" }
Custom tokenizers, token filters, and character filters can be specified in the request body as follows:
GET /_analyze { "tokenizer" : "whitespace", "filter" : ["lowercase", {"type": "stop", "stopwords": ["a", "is", "this"]}], "text" : "this is a test" }
Specific index
editYou can also run the analyze API against a specific index:
GET /analyze_sample/_analyze { "text" : "this is a test" }
The above will run an analysis on the "this is a test" text, using the
default index analyzer associated with the analyze_sample
index. An analyzer
can also be provided to use a different analyzer:
GET /analyze_sample/_analyze { "analyzer" : "whitespace", "text" : "this is a test" }
Derive analyzer from a field mapping
editThe analyzer can be derived based on a field mapping, for example:
GET /analyze_sample/_analyze { "field" : "obj1.field1", "text" : "this is a test" }
Will cause the analysis to happen based on the analyzer configured in the
mapping for obj1.field1
(and if not, the default index analyzer).
Normalizer
editA normalizer
can be provided for keyword field with normalizer associated with the analyze_sample
index.
GET /analyze_sample/_analyze { "normalizer" : "my_normalizer", "text" : "BaR" }
Or by building a custom transient normalizer out of token filters and char filters.
GET /_analyze { "filter" : ["lowercase"], "text" : "BaR" }
Explain analyze
editIf you want to get more advanced details, set explain
to true
(defaults to false
). It will output all token attributes for each token.
You can filter token attributes you want to output by setting attributes
option.
The format of the additional detail information is labelled as experimental in Lucene and it may change in the future.
GET /_analyze { "tokenizer" : "standard", "filter" : ["snowball"], "text" : "detailed output", "explain" : true, "attributes" : ["keyword"] }
The request returns the following result:
{ "detail" : { "custom_analyzer" : true, "charfilters" : [ ], "tokenizer" : { "name" : "standard", "tokens" : [ { "token" : "detailed", "start_offset" : 0, "end_offset" : 8, "type" : "<ALPHANUM>", "position" : 0 }, { "token" : "output", "start_offset" : 9, "end_offset" : 15, "type" : "<ALPHANUM>", "position" : 1 } ] }, "tokenfilters" : [ { "name" : "snowball", "tokens" : [ { "token" : "detail", "start_offset" : 0, "end_offset" : 8, "type" : "<ALPHANUM>", "position" : 0, "keyword" : false }, { "token" : "output", "start_offset" : 9, "end_offset" : 15, "type" : "<ALPHANUM>", "position" : 1, "keyword" : false } ] } ] } }
Setting a token limit
editGenerating excessive amount of tokens may cause a node to run out of memory. The following setting allows to limit the number of tokens that can be produced:
-
index.analyze.max_token_count
-
The maximum number of tokens that can be produced using
_analyze
API. The default value is10000
. If more than this limit of tokens gets generated, an error will be thrown. The_analyze
endpoint without a specified index will always use10000
value as a limit. This setting allows you to control the limit for a specific index:
PUT /analyze_sample { "settings" : { "index.analyze.max_token_count" : 20000 } }
GET /analyze_sample/_analyze { "text" : "this is a test" }
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