- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 8.10
- Set up Elasticsearch
- Installing Elasticsearch
- Run Elasticsearch locally
- Configuring Elasticsearch
- Important Elasticsearch configuration
- Secure settings
- Auditing settings
- Circuit breaker settings
- Cluster-level shard allocation and routing settings
- Miscellaneous cluster settings
- Cross-cluster replication settings
- Discovery and cluster formation settings
- Field data cache settings
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- Index management settings
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- Indexing buffer settings
- License settings
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- Transforms settings
- Thread pools
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- Advanced configuration
- Important system configuration
- Bootstrap Checks
- Heap size check
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- Maximum number of threads check
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- 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
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- Discovery configuration check
- Bootstrap Checks for X-Pack
- Starting Elasticsearch
- Stopping Elasticsearch
- Discovery and cluster formation
- Add and remove nodes in your cluster
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- Remote clusters
- 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
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- Classic
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- Conditional
- Decimal digit
- Delimited payload
- Dictionary decompounder
- Edge n-gram
- Elision
- Fingerprint
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- Length
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- Lowercase
- MinHash
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- Phonetic
- Porter stem
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- Reverse
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- Stemmer override
- Stop
- Synonym
- Synonym graph
- Trim
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- Unique
- Uppercase
- Word delimiter
- Word delimiter graph
- Character filters reference
- Normalizers
- Index templates
- Data streams
- Ingest pipelines
- Example: Parse logs
- Enrich your data
- Processor reference
- Append
- Attachment
- Bytes
- Circle
- Community ID
- Convert
- CSV
- Date
- Date index name
- Dissect
- Dot expander
- Drop
- Enrich
- Fail
- Fingerprint
- Foreach
- Geo-grid
- GeoIP
- Grok
- Gsub
- HTML strip
- Inference
- Join
- JSON
- KV
- Lowercase
- Network direction
- Pipeline
- Redact
- Registered domain
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- Script
- Set
- Set security user
- Sort
- Split
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- Uppercase
- URL decode
- URI parts
- User agent
- Aliases
- Search your data
- Collapse search results
- Filter search results
- Highlighting
- Long-running searches
- Near real-time search
- Paginate search results
- Retrieve inner hits
- Retrieve selected fields
- Search across clusters
- Search multiple data streams and indices
- Search shard routing
- Search templates
- Search with synonyms
- Sort search results
- kNN search
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- Searching with query rules
- Query DSL
- Aggregations
- Bucket aggregations
- Adjacency matrix
- Auto-interval date histogram
- Categorize text
- Children
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- Date histogram
- Date range
- Diversified sampler
- Filter
- Filters
- Frequent item sets
- Geo-distance
- Geohash grid
- Geohex grid
- Geotile grid
- Global
- Histogram
- IP prefix
- IP range
- Missing
- Multi Terms
- Nested
- Parent
- Random sampler
- Range
- Rare terms
- Reverse nested
- Sampler
- Significant terms
- Significant text
- Terms
- Time series
- Variable width histogram
- Subtleties of bucketing range fields
- Metrics aggregations
- Pipeline aggregations
- Average bucket
- Bucket script
- Bucket count K-S test
- Bucket correlation
- Bucket selector
- Bucket sort
- Change point
- Cumulative cardinality
- Cumulative sum
- Derivative
- Extended stats bucket
- Inference bucket
- Max bucket
- Min bucket
- Moving function
- Moving percentiles
- Normalize
- Percentiles bucket
- Serial differencing
- Stats bucket
- Sum bucket
- Bucket aggregations
- Geospatial analysis
- EQL
- SQL
- 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
- 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
- Set up a cluster for high availability
- Snapshot and restore
- 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
- Service accounts
- Internal users
- Token-based authentication services
- User profiles
- 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
- 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
- elasticsearch-keystore
- elasticsearch-node
- elasticsearch-reconfigure-node
- elasticsearch-reset-password
- elasticsearch-saml-metadata
- elasticsearch-service-tokens
- elasticsearch-setup-passwords
- elasticsearch-shard
- elasticsearch-syskeygen
- elasticsearch-users
- How to
- 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
- Total number of shards for an index on a single node exceeded
- Total number of shards per node has been reached
- Troubleshooting corruption
- Fix data nodes out of disk
- Fix master nodes out of disk
- Fix other role nodes out of disk
- Start index lifecycle management
- Start Snapshot Lifecycle Management
- Restore from snapshot
- Multiple deployments writing to the same snapshot repository
- Addressing repeated snapshot policy failures
- Troubleshooting an unstable cluster
- Troubleshooting discovery
- Troubleshooting monitoring
- Troubleshooting transforms
- Troubleshooting Watcher
- Troubleshooting searches
- Troubleshooting shards capacity health issues
- REST APIs
- API conventions
- Common options
- REST API compatibility
- Autoscaling APIs
- Behavioral Analytics APIs
- Compact and aligned text (CAT) APIs
- cat aliases
- cat allocation
- cat anomaly detectors
- cat component templates
- 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
- Health
- Cluster reroute
- Cluster state
- Cluster stats
- Cluster update settings
- Nodes feature usage
- Nodes hot threads
- Nodes info
- Prevalidate node removal
- Nodes reload secure settings
- Nodes stats
- Cluster Info
- Pending cluster tasks
- Remote cluster info
- Task management
- Voting configuration exclusions
- Create or update desired nodes
- Get desired nodes
- Delete desired nodes
- Get desired balance
- Reset desired balance
- Cross-cluster replication APIs
- Data stream APIs
- Document APIs
- Enrich APIs
- EQL APIs
- Features APIs
- Fleet APIs
- Find structure API
- Graph explore API
- Index APIs
- Alias exists
- Aliases
- Analyze
- Analyze index disk usage
- Clear cache
- Clone index
- Close index
- Create index
- Create or update alias
- Create or update component template
- Create or update index template
- Create or update index template (legacy)
- Delete component template
- Delete dangling index
- Delete alias
- Delete index
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- Delete index template (legacy)
- Exists
- Field usage stats
- Flush
- Force merge
- Get alias
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- Get field mapping
- Get index
- Get index settings
- Get index template
- Get index template (legacy)
- Get mapping
- Import dangling index
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists (legacy)
- List dangling indices
- Open index
- Refresh
- Resolve index
- Rollover
- Shrink index
- Simulate index
- Simulate template
- Split index
- Unfreeze index
- Update index settings
- Update mapping
- Index lifecycle management APIs
- Create or update lifecycle policy
- Get policy
- Delete policy
- Move to step
- Remove policy
- Retry policy
- Get index lifecycle management status
- Explain lifecycle
- Start index lifecycle management
- Stop index lifecycle management
- Migrate indices, ILM policies, and legacy, composable and component templates to data tiers routing
- Ingest APIs
- Info API
- Licensing APIs
- Logstash APIs
- Machine learning APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
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- Create calendars
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- 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
- Flush jobs
- Forecast jobs
- Get buckets
- Get calendars
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get model snapshots
- Get model snapshot upgrade statistics
- Get overall buckets
- Get scheduled events
- Get filters
- Get records
- Open jobs
- Post data to jobs
- Preview datafeeds
- Reset jobs
- Revert model snapshots
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
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- Update model snapshots
- Upgrade model snapshots
- 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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- Machine learning trained model APIs
- Clear trained model deployment cache
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- Create trained model vocabulary
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- Get trained models stats
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- Start trained model deployment
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- Update trained model deployment
- Migration APIs
- Node lifecycle APIs
- Query rules APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Script APIs
- Search APIs
- Search Application APIs
- Searchable snapshots APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles cache
- Clear privileges cache
- Clear API key cache
- Clear service account token caches
- Create API keys
- Create or update application privileges
- Create or update role mappings
- Create or update roles
- Create or update users
- Create service account tokens
- Delegate PKI authentication
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete service account token
- Delete users
- Disable users
- 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
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- Update API key
- Bulk update API keys
- SAML prepare authentication
- SAML authenticate
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- SSL certificate
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- Enable user profile
- Get user profiles
- Suggest user profile
- Update user profile data
- Has privileges user profile
- Create Cross-Cluster API key
- Update Cross-Cluster API key
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Synonyms APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- 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
Accessing document fields and special variables
editAccessing document fields and special variables
editDepending on where a script is used, it will have access to certain special variables and document fields.
Update scripts
editA script used in the update,
update-by-query, or reindex
API will have access to the ctx
variable which exposes:
|
Access to the document |
|
The operation that should be applied to the document: |
|
Access to document metadata fields, some of which may be read-only. |
These scripts do not have access to the doc
variable and have to use ctx
to access the documents they operate on.
Search and aggregation scripts
editWith the exception of script fields which are executed once per search hit, scripts used in search and aggregations will be executed once for every document which might match a query or an aggregation. Depending on how many documents you have, this could mean millions or billions of executions: these scripts need to be fast!
Field values can be accessed from a script using
doc-values,
the _source
field, or
stored fields,
each of which is explained below.
Accessing the score of a document within a script
editScripts used in the function_score
query,
in script-based sorting, or in
aggregations have access to the _score
variable which
represents the current relevance score of a document.
Here’s an example of using a script in a
function_score
query to alter the
relevance _score
of each document:
response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { text: 'quick brown fox', popularity: 1 } ) puts response response = client.index( index: 'my-index-000001', id: 2, refresh: true, body: { text: 'quick fox', popularity: 5 } ) puts response response = client.search( index: 'my-index-000001', body: { query: { function_score: { query: { match: { text: 'quick brown fox' } }, script_score: { script: { lang: 'expression', source: "_score * doc['popularity']" } } } } } ) puts response
PUT my-index-000001/_doc/1?refresh { "text": "quick brown fox", "popularity": 1 } PUT my-index-000001/_doc/2?refresh { "text": "quick fox", "popularity": 5 } GET my-index-000001/_search { "query": { "function_score": { "query": { "match": { "text": "quick brown fox" } }, "script_score": { "script": { "lang": "expression", "source": "_score * doc['popularity']" } } } } }
Doc values
editBy far the fastest most efficient way to access a field value from a
script is to use the doc['field_name']
syntax, which retrieves the field
value from doc values. Doc values are a columnar field value
store, enabled by default on all fields except for analyzed text
fields.
response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { cost_price: 100 } ) puts response response = client.search( index: 'my-index-000001', body: { script_fields: { sales_price: { script: { lang: 'expression', source: "doc['cost_price'] * markup", params: { markup: 0.2 } } } } } ) puts response
PUT my-index-000001/_doc/1?refresh { "cost_price": 100 } GET my-index-000001/_search { "script_fields": { "sales_price": { "script": { "lang": "expression", "source": "doc['cost_price'] * markup", "params": { "markup": 0.2 } } } } }
Doc-values can only return "simple" field values like numbers, dates, geo- points, terms, etc, or arrays of these values if the field is multi-valued. It cannot return JSON objects.
Missing fields
The doc['field']
will throw an error if field
is missing from the mappings.
In painless
, a check can first be done with doc.containsKey('field')
to guard
accessing the doc
map. Unfortunately, there is no way to check for the
existence of the field in mappings in an expression
script.
Doc values and text
fields
The doc['field']
syntax can also be used for analyzed text
fields
if fielddata
is enabled, but BEWARE: enabling fielddata on a
text
field requires loading all of the terms into the JVM heap, which can be
very expensive both in terms of memory and CPU. It seldom makes sense to
access text
fields from scripts.
The document _source
editThe document _source
can be accessed using the
_source.field_name
syntax. The _source
is loaded as a map-of-maps, so
properties within object fields can be accessed as, for example,
_source.name.first
.
Prefer doc-values to _source
Accessing the _source
field is much slower than using doc-values. The
_source field is optimised for returning several fields per result, while doc
values are optimised for accessing the value of a specific field in many
documents.
It makes sense to use _source
when generating a
script field for the top ten hits from a
search result but, for other search and aggregation use cases, always prefer
using doc values.
For instance:
response = client.indices.create( index: 'my-index-000001', body: { mappings: { properties: { first_name: { type: 'text' }, last_name: { type: 'text' } } } } ) puts response response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { first_name: 'Barry', last_name: 'White' } ) puts response response = client.search( index: 'my-index-000001', body: { script_fields: { full_name: { script: { lang: 'painless', source: "params._source.first_name + ' ' + params._source.last_name" } } } } ) puts response
PUT my-index-000001 { "mappings": { "properties": { "first_name": { "type": "text" }, "last_name": { "type": "text" } } } } PUT my-index-000001/_doc/1?refresh { "first_name": "Barry", "last_name": "White" } GET my-index-000001/_search { "script_fields": { "full_name": { "script": { "lang": "painless", "source": "params._source.first_name + ' ' + params._source.last_name" } } } }
Stored fields
editStored fields — fields explicitly marked as
"store": true
in the mapping — can be accessed using the
_fields['field_name'].value
or _fields['field_name']
syntax:
response = client.indices.create( index: 'my-index-000001', body: { mappings: { properties: { full_name: { type: 'text', store: true }, title: { type: 'text', store: true } } } } ) puts response response = client.index( index: 'my-index-000001', id: 1, refresh: true, body: { full_name: 'Alice Ball', title: 'Professor' } ) puts response response = client.search( index: 'my-index-000001', body: { script_fields: { name_with_title: { script: { lang: 'painless', source: "params._fields['title'].value + ' ' + params._fields['full_name'].value" } } } } ) puts response
PUT my-index-000001 { "mappings": { "properties": { "full_name": { "type": "text", "store": true }, "title": { "type": "text", "store": true } } } } PUT my-index-000001/_doc/1?refresh { "full_name": "Alice Ball", "title": "Professor" } GET my-index-000001/_search { "script_fields": { "name_with_title": { "script": { "lang": "painless", "source": "params._fields['title'].value + ' ' + params._fields['full_name'].value" } } } }
Stored vs _source
The _source
field is just a special stored field, so the performance is
similar to that of other stored fields. The _source
provides access to the
original document body that was indexed (including the ability to distinguish
null
values from empty fields, single-value arrays from plain scalars, etc).
The only time it really makes sense to use stored fields instead of the
_source
field is when the _source
is very large and it is less costly to
access a few small stored fields instead of the entire _source
.
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