- Elasticsearch Guide: other versions:
- What’s new in 8.17
- Elasticsearch basics
- Quick starts
- Set up Elasticsearch
- Run Elasticsearch locally
- Installing Elasticsearch
- Configuring Elasticsearch
- Important Elasticsearch configuration
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analyzer
coerce
copy_to
doc_values
dynamic
eager_global_ordinals
enabled
format
ignore_above
index.mapping.ignore_above
ignore_malformed
index
index_options
index_phrases
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meta
fields
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norms
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properties
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similarity
store
subobjects
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- Mapping limit settings
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- Text analysis
- Overview
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- Configure text analysis
- Built-in analyzer reference
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- Apostrophe
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- Connectors
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- Overview
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- Geo Functions
- Conditional Functions And Expressions
- System Functions
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- 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
- Monitor a cluster
- Roll up or transform your data
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- Secure the Elastic Stack
- Elasticsearch security principles
- Start the Elastic Stack with security enabled automatically
- Manually configure security
- Updating node security certificates
- User authentication
- Built-in users
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- Realms
- 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
- Looking up users without authentication
- 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
- Role restriction
- Security privileges
- Document level security
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- Granting privileges for data streams 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
- Enable audit logging
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- 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
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- Common SAML issues
- Internal Server Error in Kibana
- Setup-passwords command fails due to connection failure
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- Limitations
- Watcher
- Cross-cluster replication
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- REST APIs
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- REST API compatibility
- Autoscaling APIs
- Behavioral Analytics APIs
- Compact and aligned text (CAT) APIs
- cat aliases
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- cat count
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- Cluster APIs
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- Data stream APIs
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- Alias exists
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- Exists
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- Get index
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- Import dangling index
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- List dangling indices
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- Create or update lifecycle policy
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- Get index lifecycle management status
- Explain lifecycle
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- Migrate indices, ILM policies, and legacy, composable and component templates to data tiers routing
- Inference APIs
- Delete inference API
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- AlibabaCloud AI Search inference service
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- Info API
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- Add events to calendar
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- Get buckets
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- Get overall buckets
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- Machine learning data frame analytics APIs
- Create data frame analytics jobs
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- Machine learning trained model APIs
- Clear trained model deployment cache
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- Get user profiles
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- Has privileges user profile
- Create Cross-Cluster API key
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- Snapshot and restore APIs
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- SQL APIs
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- Definitions
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- elasticsearch-certgen
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- elasticsearch-reset-password
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- elasticsearch-shard
- elasticsearch-syskeygen
- elasticsearch-users
- Optimizations
- Troubleshooting
- Fix common cluster issues
- Diagnose unassigned shards
- Add a missing tier to the system
- Allow Elasticsearch to allocate the data in the system
- Allow Elasticsearch to allocate the index
- Indices mix index allocation filters with data tiers node roles to move through data tiers
- Not enough nodes to allocate all shard replicas
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- Troubleshooting corruption
- Fix data nodes out of disk
- Fix master nodes out of disk
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- Start index lifecycle management
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- Restore from snapshot
- Troubleshooting broken repositories
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- Troubleshooting an unstable cluster
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- Troubleshooting transforms
- Troubleshooting Watcher
- Troubleshooting searches
- Troubleshooting shards capacity health issues
- Troubleshooting an unbalanced cluster
- Capture diagnostics
- Migration guide
- Release notes
- Elasticsearch version 8.17.1
- Elasticsearch version 8.17.0
- Elasticsearch version 8.16.2
- Elasticsearch version 8.16.1
- Elasticsearch version 8.16.0
- Elasticsearch version 8.15.5
- Elasticsearch version 8.15.4
- Elasticsearch version 8.15.3
- Elasticsearch version 8.15.2
- Elasticsearch version 8.15.1
- Elasticsearch version 8.15.0
- Elasticsearch version 8.14.3
- Elasticsearch version 8.14.2
- Elasticsearch version 8.14.1
- Elasticsearch version 8.14.0
- Elasticsearch version 8.13.4
- Elasticsearch version 8.13.3
- Elasticsearch version 8.13.2
- Elasticsearch version 8.13.1
- Elasticsearch version 8.13.0
- Elasticsearch version 8.12.2
- Elasticsearch version 8.12.1
- Elasticsearch version 8.12.0
- Elasticsearch version 8.11.4
- Elasticsearch version 8.11.3
- Elasticsearch version 8.11.2
- Elasticsearch version 8.11.1
- Elasticsearch version 8.11.0
- Elasticsearch version 8.10.4
- Elasticsearch version 8.10.3
- Elasticsearch version 8.10.2
- Elasticsearch version 8.10.1
- Elasticsearch version 8.10.0
- Elasticsearch version 8.9.2
- Elasticsearch version 8.9.1
- Elasticsearch version 8.9.0
- Elasticsearch version 8.8.2
- Elasticsearch version 8.8.1
- Elasticsearch version 8.8.0
- Elasticsearch version 8.7.1
- Elasticsearch version 8.7.0
- Elasticsearch version 8.6.2
- Elasticsearch version 8.6.1
- Elasticsearch version 8.6.0
- Elasticsearch version 8.5.3
- Elasticsearch version 8.5.2
- Elasticsearch version 8.5.1
- Elasticsearch version 8.5.0
- Elasticsearch version 8.4.3
- Elasticsearch version 8.4.2
- Elasticsearch version 8.4.1
- Elasticsearch version 8.4.0
- Elasticsearch version 8.3.3
- Elasticsearch version 8.3.2
- Elasticsearch version 8.3.1
- Elasticsearch version 8.3.0
- 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
Geospatial analysis
editGeospatial analysis
editDid you know that Elasticsearch has geospatial capabilities? Elasticsearch and geo go way back, to 2010. A lot has happened since then and today Elasticsearch provides robust geospatial capabilities with speed, all with a stack that scales automatically.
Not sure where to get started with Elasticsearch and geo? Then, you have come to the right place.
Geospatial mapping
editElasticsearch supports two types of geo data: geo_point fields which support lat/lon pairs, and geo_shape fields, which support points, lines, circles, polygons, multi-polygons, and so on. Use explicit mapping to index geo data fields.
Have an index with lat/lon pairs but no geo_point mapping? Use runtime fields to make a geo_point field without reindexing.
Ingest
editData is often messy and incomplete. Ingest pipelines lets you clean, transform, and augment your data before indexing.
- Use CSV together with explicit mapping to index CSV files with geo data. Kibana’s Import CSV feature can help with this.
- Use GeoIP to add geographical location of an IPv4 or IPv6 address.
- Use geo-grid processor to convert grid tiles or hexagonal cell ids to bounding boxes or polygons which describe their shape.
- Use geo_match enrich policy for reverse geocoding. For example, use reverse geocoding to visualize metropolitan areas by web traffic.
Query
editGeo queries answer location-driven questions. Find documents that intersect with, are within, are contained by, or do not intersect your query geometry. Combine geospatial queries with full text search queries for unparalleled searching experience. For example, "Show me all subscribers that live within 5 miles of our new gym location, that joined in the last year and have running mentioned in their profile".
ES|QL
editES|QL has support for Geospatial Search functions, enabling efficient index searching for documents that intersect with, are within, are contained by, or are disjoint from a query geometry. In addition, the ST_DISTANCE
function calculates the distance between two points.
Aggregate
editAggregations summarizes your data as metrics, statistics, or other analytics. Use bucket aggregations to group documents into buckets, also called bins, based on field values, ranges, or other criteria. Then, use metric aggregations to calculate metrics, such as a sum or average, from field values in each bucket. Compare metrics across buckets to gain insights from your data.
Geospatial bucket aggregations:
- Geo-distance aggregation evaluates the distance of each geo_point location from an origin point and determines the buckets it belongs to based on the ranges (a document belongs to a bucket if the distance between the document and the origin falls within the distance range of the bucket).
- Geohash grid aggregation groups geo_point and geo_shape values into buckets that represent a grid.
- Geohex grid aggregation groups geo_point and geo_shape values into buckets that represent an H3 hexagonal cell.
- Geotile grid aggregation groups geo_point and geo_shape values into buckets that represent a grid. Each cell corresponds to a map tile as used by many online map sites.
Geospatial metric aggregations:
- Geo-bounds aggregation computes the geographic bounding box containing all values for a Geopoint or Geoshape field.
- Geo-centroid aggregation computes the weighted centroid from all coordinate values for geo fields.
- Geo-line aggregation aggregates all geo_point values within a bucket into a LineString ordered by the chosen sort field. Use geo_line aggregation to create vehicle tracks.
Combine aggregations to perform complex geospatial analysis. For example, to calculate the most recent GPS tracks per flight, use a terms aggregation to group documents into buckets per aircraft. Then use geo-line aggregation to compute a track for each aircraft. In another example, use geotile grid aggregation to group documents into a grid. Then use geo-centroid aggregation to find the weighted centroid of each grid cell.
Integrate
editUse vector tile search API to consume Elasticsearch geo data within existing GIS infrastructure.
Visualize
editVisualize geo data with Kibana. Add your map to a dashboard to view your data from all angles.
This dashboard shows the effects of the Cumbre Vieja eruption.
Machine learning
editPut machine learning to work for you and find the data that should stand out with anomaly detections. Find credit card transactions that occur in an unusual locations or a web request that has an unusual source location. Location-based anomaly detections make it easy to find and explore and compare anomalies with their typical locations.
Alerting
editLet your location data drive insights and action with geographic alerts. Commonly referred to as geo-fencing, track moving objects as they enter or exit a boundary to receive notifications through common business systems (email, Slack, Teams, PagerDuty, and more).
Interested in learning more? Follow step-by-step instructions for setting up tracking containment alerts to monitor moving vehicles.