- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 8.2
- Quick start
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
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- Important system configuration
- Bootstrap Checks
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- Text analysis
- Overview
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- Configure text analysis
- Built-in analyzer reference
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- Token filter reference
- Apostrophe
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- Dictionary decompounder
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- Length
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- Synonym graph
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- Character filters reference
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- Example: Parse logs
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- Processor reference
- Append
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- Circle
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- Convert
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- Date index name
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- Parent
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- EQL
- SQL
- Overview
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- Security
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- Aggregate Functions
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- Date/Time and Interval Functions and Operators
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- Mathematical Functions
- String Functions
- Type Conversion Functions
- Geo Functions
- Conditional Functions And Expressions
- System Functions
- Reserved keywords
- SQL Limitations
- Scripting
- Data management
- ILM: Manage the index lifecycle
- Tutorial: Customize built-in policies
- Tutorial: Automate rollover
- Index management in Kibana
- Overview
- Concepts
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Troubleshooting index lifecycle management errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- Data tiers
- Autoscaling
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- Snapshot and restore
- Secure the Elastic Stack
- Elasticsearch security principles
- Start the Elastic Stack with security enabled automatically
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- Updating node security certificates
- User authentication
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- Realm chains
- Security domains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- Kerberos authentication
- JWT 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 data streams and aliases
- Mapping users and groups to roles
- Setting up field and document level security
- Submitting requests on behalf of other users
- Configuring authorization delegation
- Customizing roles and authorization
- Enable audit logging
- Restricting connections with IP filtering
- Securing clients and integrations
- Operator privileges
- 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
- Watcher
- Command line tools
- elasticsearch-certgen
- elasticsearch-certutil
- elasticsearch-create-enrollment-token
- elasticsearch-croneval
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- How to
- REST APIs
- API conventions
- Common options
- REST API compatibility
- Autoscaling APIs
- Compact and aligned text (CAT) APIs
- cat aliases
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- Cluster APIs
- Cluster allocation explain
- Cluster get settings
- Cluster health
- Cluster reroute
- Cluster state
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- Cluster update settings
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- Alias exists
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- Exists
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- Create or update lifecycle policy
- Get policy
- Delete policy
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- Remove policy
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- Get index lifecycle management status
- Explain lifecycle
- Start index lifecycle management
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- Migrate indices, ILM policies, and legacy, composable and component templates to data tiers routing
- Ingest APIs
- Info API
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- Logstash APIs
- Machine learning APIs
- Machine learning anomaly detection APIs
- Add events to calendar
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- Delete jobs from calendar
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- Delete expired data
- Estimate model memory
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
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- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
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- Get model snapshot upgrade statistics
- Get overall buckets
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- Open jobs
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- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Delete data frame analytics jobs
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Preview data frame analytics
- Start data frame analytics jobs
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- Update data frame analytics jobs
- Machine learning trained model APIs
- Create or update trained model aliases
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- Create trained model vocabulary
- Delete trained model aliases
- Delete trained models
- Get trained models
- Get trained models stats
- Infer trained model deployment
- Start trained model deployment
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- Migration APIs
- Node lifecycle APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Script APIs
- Search APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
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- Clear API key cache
- Clear service account token caches
- Create API keys
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- Create or update role mappings
- Create or update roles
- Create or update users
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- Delete roles
- Delete service account token
- Delete users
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- Enable users
- Enroll Kibana
- Enroll node
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Get service accounts
- Get service account credentials
- Get token
- Get user privileges
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- Query API key information
- SAML prepare authentication
- SAML authenticate
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- SAML complete logout
- SAML service provider metadata
- SSL certificate
- Activate user profile
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- Enable user profile
- Get user profile
- Suggest user profile
- Update user profile data
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- Elasticsearch version 8.2.3
- Elasticsearch version 8.2.2
- Elasticsearch version 8.2.1
- Elasticsearch version 8.2.0
- Elasticsearch version 8.1.3
- Elasticsearch version 8.1.2
- Elasticsearch version 8.1.1
- Elasticsearch version 8.1.0
- Elasticsearch version 8.0.1
- Elasticsearch version 8.0.0
- Elasticsearch version 8.0.0-rc2
- Elasticsearch version 8.0.0-rc1
- Elasticsearch version 8.0.0-beta1
- Elasticsearch version 8.0.0-alpha2
- Elasticsearch version 8.0.0-alpha1
- Dependencies and versions
Shape field type
editShape field type
editThe shape
data type facilitates the indexing of and searching
with arbitrary x, y
cartesian shapes such as rectangles and polygons. It can be
used to index and query geometries whose coordinates fall in a 2-dimensional planar
coordinate system.
You can query documents using this type using shape Query.
Mapping Options
editLike the geo_shape
field type, the shape
field mapping maps
GeoJSON or Well-Known Text
(WKT) geometry objects to the shape type. To enable it, users must explicitly map
fields to the shape type.
Option | Description | Default |
---|---|---|
|
Optionally define how to interpret vertex order for
polygons / multipolygons. This parameter defines one of two coordinate
system rules (Right-hand or Left-hand) each of which can be specified in three
different ways. 1. Right-hand rule: |
|
|
If true, malformed GeoJSON or WKT shapes are ignored. If false (default), malformed GeoJSON and WKT shapes throw an exception and reject the entire document. |
|
|
If |
|
|
If |
|
Indexing approach
editLike geo_shape
, the shape
field type is indexed by decomposing geometries into
a triangular mesh and indexing each triangle as a 7 dimension point in a BKD tree.
The coordinates provided to the indexer are single precision floating point values so
the field guarantees the same accuracy provided by the java virtual machine (typically
1E-38
). For polygons/multi-polygons the performance of the tessellator primarily
depends on the number of vertices that define the geometry.
IMPORTANT NOTES
CONTAINS
relation query - shape
queries with relation
defined as contains
are supported
for indices created with ElasticSearch 7.5.0 or higher.
Example
editPUT /example { "mappings": { "properties": { "geometry": { "type": "shape" } } } }
This mapping definition maps the geometry field to the shape type. The indexer uses single
precision floats for the vertex values so accuracy is guaranteed to the same precision as
float
values provided by the java virtual machine approximately (typically 1E-38).
Input Structure
editShapes can be represented using either the GeoJSON or Well-Known Text (WKT) format. The following table provides a mapping of GeoJSON and WKT to Elasticsearch types:
GeoJSON Type | WKT Type | Elasticsearch Type | Description |
---|---|---|---|
|
|
|
A single |
|
|
|
An arbitrary line given two or more points. |
|
|
|
A closed polygon whose first and last point
must match, thus requiring |
|
|
|
An array of unconnected, but likely related points. |
|
|
|
An array of separate linestrings. |
|
|
|
An array of separate polygons. |
|
|
|
A shape collection similar to the
|
|
|
|
A bounding rectangle, or envelope, specified by specifying only the top left and bottom right points. |
For all types, both the inner type
and coordinates
fields are required.
In GeoJSON and WKT, and therefore Elasticsearch, the correct coordinate order is (X, Y)
within coordinate arrays. This differs from many Geospatial APIs (e.g., geo_shape
) that
typically use the colloquial latitude, longitude (Y, X) ordering.
A point is a single coordinate in cartesian x, y
space. It may represent the
location of an item of interest in a virtual world or projected space. The
following is an example of a point in GeoJSON.
POST /example/_doc { "location" : { "type" : "point", "coordinates" : [-377.03653, 389.897676] } }
The following is an example of a point in WKT:
POST /example/_doc { "location" : "POINT (-377.03653 389.897676)" }
A linestring
defined by an array of two or more positions. By
specifying only two points, the linestring
will represent a straight
line. Specifying more than two points creates an arbitrary path. The
following is an example of a LineString in GeoJSON.
POST /example/_doc { "location" : { "type" : "linestring", "coordinates" : [[-377.03653, 389.897676], [-377.009051, 389.889939]] } }
The following is an example of a LineString in WKT:
POST /example/_doc { "location" : "LINESTRING (-377.03653 389.897676, -377.009051 389.889939)" }
A polygon is defined by a list of a list of points. The first and last points in each (outer) list must be the same (the polygon must be closed). The following is an example of a Polygon in GeoJSON.
POST /example/_doc { "location" : { "type" : "polygon", "coordinates" : [ [ [1000.0, -1001.0], [1001.0, -1001.0], [1001.0, -1000.0], [1000.0, -1000.0], [1000.0, -1001.0] ] ] } }
The following is an example of a Polygon in WKT:
POST /example/_doc { "location" : "POLYGON ((1000.0 -1001.0, 1001.0 -1001.0, 1001.0 -1000.0, 1000.0 -1000.0, 1000.0 -1001.0))" }
The first array represents the outer boundary of the polygon, the other arrays represent the interior shapes ("holes"). The following is a GeoJSON example of a polygon with a hole:
POST /example/_doc { "location" : { "type" : "polygon", "coordinates" : [ [ [1000.0, -1001.0], [1001.0, -1001.0], [1001.0, -1000.0], [1000.0, -1000.0], [1000.0, -1001.0] ], [ [1000.2, -1001.2], [1000.8, -1001.2], [1000.8, -1001.8], [1000.2, -1001.8], [1000.2, -1001.2] ] ] } }
The following is an example of a Polygon with a hole in WKT:
POST /example/_doc { "location" : "POLYGON ((1000.0 1000.0, 1001.0 1000.0, 1001.0 1001.0, 1000.0 1001.0, 1000.0 1000.0), (1000.2 1000.2, 1000.8 1000.2, 1000.8 1000.8, 1000.2 1000.8, 1000.2 1000.2))" }
IMPORTANT NOTE: WKT does not enforce a specific order for vertices. GeoJSON mandates that the outer polygon must be counterclockwise and interior shapes must be clockwise, which agrees with the Open Geospatial Consortium (OGC) Simple Feature Access specification for vertex ordering.
By default Elasticsearch expects vertices in counterclockwise (right hand rule)
order. If data is provided in clockwise order (left hand rule) the user can change
the orientation
parameter either in the field mapping, or as a parameter provided
with the document.
The following is an example of overriding the orientation
parameters on a document:
POST /example/_doc { "location" : { "type" : "polygon", "orientation" : "clockwise", "coordinates" : [ [ [1000.0, 1000.0], [1000.0, 1001.0], [1001.0, 1001.0], [1001.0, 1000.0], [1000.0, 1000.0] ] ] } }
The following is an example of a list of GeoJSON points:
POST /example/_doc { "location" : { "type" : "multipoint", "coordinates" : [ [1002.0, 1002.0], [1003.0, 2000.0] ] } }
The following is an example of a list of WKT points:
POST /example/_doc { "location" : "MULTIPOINT (1002.0 2000.0, 1003.0 2000.0)" }
The following is an example of a list of GeoJSON linestrings:
POST /example/_doc { "location" : { "type" : "multilinestring", "coordinates" : [ [ [1002.0, 200.0], [1003.0, 200.0], [1003.0, 300.0], [1002.0, 300.0] ], [ [1000.0, 100.0], [1001.0, 100.0], [1001.0, 100.0], [1000.0, 100.0] ], [ [1000.2, 100.2], [1000.8, 100.2], [1000.8, 100.8], [1000.2, 100.8] ] ] } }
The following is an example of a list of WKT linestrings:
POST /example/_doc { "location" : "MULTILINESTRING ((1002.0 200.0, 1003.0 200.0, 1003.0 300.0, 1002.0 300.0), (1000.0 100.0, 1001.0 100.0, 1001.0 100.0, 1000.0 100.0), (1000.2 0.2, 1000.8 100.2, 1000.8 100.8, 1000.2 100.8))" }
The following is an example of a list of GeoJSON polygons (second polygon contains a hole):
POST /example/_doc { "location" : { "type" : "multipolygon", "coordinates" : [ [ [[1002.0, 200.0], [1003.0, 200.0], [1003.0, 300.0], [1002.0, 300.0], [1002.0, 200.0]] ], [ [[1000.0, 200.0], [1001.0, 100.0], [1001.0, 100.0], [1000.0, 100.0], [1000.0, 100.0]], [[1000.2, 200.2], [1000.8, 100.2], [1000.8, 100.8], [1000.2, 100.8], [1000.2, 100.2]] ] ] } }
The following is an example of a list of WKT polygons (second polygon contains a hole):
POST /example/_doc { "location" : "MULTIPOLYGON (((1002.0 200.0, 1003.0 200.0, 1003.0 300.0, 1002.0 300.0, 102.0 200.0)), ((1000.0 100.0, 1001.0 100.0, 1001.0 100.0, 1000.0 100.0, 1000.0 100.0), (1000.2 100.2, 1000.8 100.2, 1000.8 100.8, 1000.2 100.8, 1000.2 100.2)))" }
The following is an example of a collection of GeoJSON geometry objects:
POST /example/_doc { "location" : { "type": "geometrycollection", "geometries": [ { "type": "point", "coordinates": [1000.0, 100.0] }, { "type": "linestring", "coordinates": [ [1001.0, 100.0], [1002.0, 100.0] ] } ] } }
The following is an example of a collection of WKT geometry objects:
POST /example/_doc { "location" : "GEOMETRYCOLLECTION (POINT (1000.0 100.0), LINESTRING (1001.0 100.0, 1002.0 100.0))" }
Envelope
editElasticsearch supports an envelope
type, which consists of coordinates
for upper left and lower right points of the shape to represent a
bounding rectangle in the format [[minX, maxY], [maxX, minY]]
:
POST /example/_doc { "location" : { "type" : "envelope", "coordinates" : [ [1000.0, 100.0], [1001.0, 100.0] ] } }
The following is an example of an envelope using the WKT BBOX format:
NOTE: WKT specification expects the following order: minLon, maxLon, maxLat, minLat.
POST /example/_doc { "location" : "BBOX (1000.0, 1002.0, 2000.0, 1000.0)" }
Sorting and Retrieving index Shapes
editDue to the complex input structure and index representation of shapes,
it is not currently possible to sort shapes or retrieve their fields
directly. The shape
value is only retrievable through the _source
field.
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