- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.10
- Getting started with Elasticsearch
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- Setting JVM options
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Field data cache settings
- HTTP
- Index lifecycle management settings
- Index management settings
- Index recovery settings
- Indexing buffer settings
- License settings
- Local gateway settings
- Logging
- Machine learning settings
- Monitoring settings
- Node
- Network settings
- Node query cache settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot lifecycle management settings
- Transforms settings
- Transport
- Thread pools
- Watcher settings
- Important Elasticsearch configuration
- Important System Configuration
- Bootstrap Checks
- Heap size check
- File descriptor check
- Memory lock check
- Maximum number of threads check
- Max file size check
- Maximum size virtual memory check
- Maximum map count check
- Client JVM check
- Use serial collector check
- System call filter check
- OnError and OnOutOfMemoryError checks
- Early-access check
- G1GC check
- All permission check
- Discovery configuration check
- Bootstrap Checks for X-Pack
- Starting Elasticsearch
- Stopping Elasticsearch
- Discovery and cluster formation
- Add and remove nodes in your cluster
- Full-cluster restart and rolling restart
- Remote clusters
- Set up X-Pack
- Configuring X-Pack Java Clients
- Plugins
- Upgrade Elasticsearch
- Index modules
- Mapping
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Token filter reference
- Apostrophe
- ASCII folding
- CJK bigram
- CJK width
- Classic
- Common grams
- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
- Flatten graph
- Hunspell
- Hyphenation decompounder
- Keep types
- Keep words
- Keyword marker
- Keyword repeat
- KStem
- Length
- Limit token count
- Lowercase
- MinHash
- Multiplexer
- N-gram
- Normalization
- Pattern capture
- Pattern replace
- Phonetic
- Porter stem
- Predicate script
- Remove duplicates
- Reverse
- Shingle
- Snowball
- Stemmer
- Stemmer override
- Stop
- Synonym
- Synonym graph
- Trim
- Truncate
- Unique
- Uppercase
- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Index templates
- Data streams
- Ingest node
- Search your data
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Children
- Composite
- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Geo-distance
- Geohash grid
- Geotile grid
- Global
- Histogram
- IP range
- Missing
- Nested
- Parent
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Bucket aggregations
- EQL
- SQL access
- Overview
- Getting Started with SQL
- Conventions and Terminology
- Security
- SQL REST API
- SQL Translate API
- SQL CLI
- SQL JDBC
- SQL ODBC
- SQL Client Applications
- SQL Language
- Functions and Operators
- Comparison Operators
- Logical Operators
- Math Operators
- Cast Operators
- LIKE and RLIKE Operators
- Aggregate Functions
- Grouping Functions
- Date/Time and Interval Functions and Operators
- Full-Text Search Functions
- 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
- Overview
- Concepts
- Automate rollover
- Manage Filebeat time-based indices
- Index lifecycle actions
- Configure a lifecycle policy
- Migrate index allocation filters to node roles
- Resolve lifecycle policy execution errors
- Start and stop index lifecycle management
- Manage existing indices
- Skip rollover
- Restore a managed data stream or index
- 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
- Internal users
- Token-based authentication services
- Realms
- Realm chains
- Active Directory user authentication
- File-based user authentication
- LDAP user authentication
- Native user authentication
- OpenID Connect authentication
- PKI user authentication
- SAML authentication
- 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
- Granting access to Stack Management features
- Security privileges
- Document level security
- Field level security
- Granting privileges for data streams and index 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
- 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
- Watch for cluster and index events
- Command line tools
- How To
- Glossary of terms
- REST APIs
- API conventions
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat count
- cat data frame analytics
- cat datafeeds
- cat fielddata
- cat health
- cat indices
- cat master
- cat nodeattrs
- cat nodes
- cat pending tasks
- cat plugins
- cat recovery
- cat repositories
- cat segments
- cat shards
- cat snapshots
- cat task management
- cat templates
- cat thread pool
- cat trained model
- cat transforms
- Cluster APIs
- Cluster allocation explain
- Cluster get settings
- Cluster health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Nodes reload secure settings
- Nodes stats
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Cross-cluster replication APIs
- Data stream APIs
- Document APIs
- Enrich APIs
- Graph explore API
- Index APIs
- Add index alias
- Analyze
- Clear cache
- Clone index
- Close index
- Create index
- Delete index
- Delete index alias
- Delete component template
- Delete index template
- Delete index template (legacy)
- Flush
- Force merge
- Freeze index
- Get component template
- Get field mapping
- Get index
- Get index alias
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Index alias exists
- Index exists
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- Open index
- Put index template
- Put index template (legacy)
- Put component template
- Put mapping
- Refresh
- Rollover index
- Shrink index
- Simulate index
- Simulate template
- Split index
- Synced flush
- Type exists
- Unfreeze index
- Update index alias
- Update index settings
- Resolve index
- List dangling indices
- Import dangling index
- Delete dangling index
- Index lifecycle management APIs
- Ingest APIs
- Info API
- Licensing APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendars
- Create datafeeds
- Create filters
- Delete calendars
- Delete datafeeds
- Delete events from calendar
- Delete filters
- Delete forecasts
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- Estimate model memory
- Find file structure
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Revert model snapshots
- Set upgrade mode
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Create trained models
- Update data frame analytics jobs
- Delete data frame analytics jobs
- Delete trained models
- Evaluate data frame analytics
- Explain data frame analytics
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Get trained models
- Get trained models stats
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Migration APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Search APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete users
- Disable users
- Enable users
- Get API key information
- Get application privileges
- Get builtin privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Grant API keys
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect prepare authentication
- OpenID Connect authenticate
- OpenID Connect logout
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SSL certificate
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- Elasticsearch version 7.10.2
- Elasticsearch version 7.10.1
- Elasticsearch version 7.10.0
- Elasticsearch version 7.9.3
- Elasticsearch version 7.9.2
- Elasticsearch version 7.9.1
- Elasticsearch version 7.9.0
- Elasticsearch version 7.8.1
- Elasticsearch version 7.8.0
- 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
- Dependencies and versions
Flattened field type
editFlattened field type
editBy default, each subfield in an object is mapped and indexed separately. If the names or types of the subfields are not known in advance, then they are mapped dynamically.
The flattened
type provides an alternative approach, where the entire
object is mapped as a single field. Given an object, the flattened
mapping will parse out its leaf values and index them into one field as
keywords. The object’s contents can then be searched through simple queries
and aggregations.
This data type can be useful for indexing objects with a large or unknown number of unique keys. Only one field mapping is created for the whole JSON object, which can help prevent a mappings explosion from having too many distinct field mappings.
On the other hand, flattened object fields present a trade-off in terms of search functionality. Only basic queries are allowed, with no support for numeric range queries or highlighting. Further information on the limitations can be found in the Supported operations section.
The flattened
mapping type should not be used for indexing all
document content, as it treats all values as keywords and does not provide full
search functionality. The default approach, where each subfield has its own
entry in the mappings, works well in the majority of cases.
An flattened object field can be created as follows:
PUT bug_reports { "mappings": { "properties": { "title": { "type": "text" }, "labels": { "type": "flattened" } } } } POST bug_reports/_doc/1 { "title": "Results are not sorted correctly.", "labels": { "priority": "urgent", "release": ["v1.2.5", "v1.3.0"], "timestamp": { "created": 1541458026, "closed": 1541457010 } } }
During indexing, tokens are created for each leaf value in the JSON object. The values are indexed as string keywords, without analysis or special handling for numbers or dates.
Querying the top-level flattened
field searches all leaf values in the
object:
POST bug_reports/_search { "query": { "term": {"labels": "urgent"} } }
To query on a specific key in the flattened object, object dot notation is used:
POST bug_reports/_search { "query": { "term": {"labels.release": "v1.3.0"} } }
Supported operations
editBecause of the similarities in the way values are indexed, flattened
fields share much of the same mapping and search functionality as
keyword
fields.
Currently, flattened object fields can be used with the following query types:
-
term
,terms
, andterms_set
-
prefix
-
range
-
match
andmulti_match
-
query_string
andsimple_query_string
-
exists
When querying, it is not possible to refer to field keys using wildcards, as in
{ "term": {"labels.time*": 1541457010}}
. Note that all queries, including
range
, treat the values as string keywords. Highlighting is not supported on
flattened
fields.
It is possible to sort on an flattened object field, as well as perform simple
keyword-style aggregations such as terms
. As with queries, there is no
special support for numerics — all values in the JSON object are treated as
keywords. When sorting, this implies that values are compared
lexicographically.
Flattened object fields currently cannot be stored. It is not possible to
specify the store
parameter in the mapping.
Parameters for flattened object fields
editThe following mapping parameters are accepted:
Mapping field-level query time boosting. Accepts a floating point number,
defaults to |
|
|
The maximum allowed depth of the flattened object field, in terms of nested
inner objects. If a flattened object field exceeds this limit, then an
error will be thrown. Defaults to |
Should the field be stored on disk in a column-stride fashion, so that it
can later be used for sorting, aggregations, or scripting? Accepts |
|
Should global ordinals be loaded eagerly on refresh? Accepts |
|
Leaf values longer than this limit will not be indexed. By default, there is no limit and all values will be indexed. Note that this limit applies to the leaf values within the flattened object field, and not the length of the entire field. |
|
Determines if the field should be searchable. Accepts |
|
What information should be stored in the index for scoring purposes.
Defaults to |
|
A string value which is substituted for any explicit |
|
Which scoring algorithm or similarity should be used. Defaults
to |
|
|
Whether full text queries should split the input on
whitespace when building a query for this field. Accepts |