- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.14
- 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
- Field data cache settings
- 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
- Networking
- Node query cache settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot lifecycle management settings
- Transforms settings
- Thread pools
- Watcher settings
- Advanced 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 pipelines
- Example: Parse logs
- Enrich your data
- Processor reference
- Append
- Bytes
- Circle
- Community ID
- Convert
- CSV
- Date
- Date index name
- Dissect
- Dot expander
- Drop
- Enrich
- Fail
- Fingerprint
- Foreach
- GeoIP
- Grok
- Gsub
- HTML strip
- Inference
- Join
- JSON
- KV
- Lowercase
- Network direction
- Pipeline
- Registered domain
- Remove
- Rename
- Script
- Set
- Set security user
- Sort
- Split
- Trim
- Uppercase
- URL decode
- URI parts
- User agent
- Aliases
- 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
- Multi Terms
- 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
- Average bucket
- Bucket script
- Bucket count K-S test
- Bucket correlation
- Bucket selector
- Bucket sort
- Cumulative cardinality
- Cumulative sum
- Derivative
- Extended stats bucket
- Inference bucket
- Max bucket
- Min bucket
- Moving average
- Moving function
- Moving percentiles
- Normalize
- Percentiles bucket
- Serial differencing
- Stats bucket
- Sum bucket
- Bucket aggregations
- 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
- Overview
- Concepts
- Automate rollover
- Customize built-in ILM policies
- 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
- 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
- Configuring security
- Updating node security certificates
- User authentication
- Built-in users
- Service accounts
- 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 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
- Cross cluster search, 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
- How to
- REST APIs
- API conventions
- Autoscaling APIs
- 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
- EQL APIs
- Features APIs
- Fleet APIs
- Find structure API
- Graph explore API
- Index APIs
- Alias exists
- Aliases
- Analyze
- 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
- Delete index template
- Delete index template (legacy)
- Exists
- Flush
- Force merge
- Freeze index
- Get alias
- Get component template
- 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
- Synced flush
- Type exists
- Unfreeze index
- Update index settings
- Update mapping
- Index lifecycle management APIs
- Ingest APIs
- Info API
- Licensing APIs
- Logstash 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
- Reset jobs
- Revert model snapshots
- Set upgrade mode
- Start datafeeds
- Stop datafeeds
- Update datafeeds
- Update filters
- Update jobs
- Update model snapshots
- Upgrade model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Create or update trained model aliases
- Create trained models
- Update data frame analytics jobs
- Delete data frame analytics jobs
- Delete trained models
- Delete trained model aliases
- 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
- Preview data frame analytics
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Migration APIs
- Reload search analyzers API
- Repositories metering APIs
- Rollup APIs
- Script APIs
- Search 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
- 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
- SAML prepare authentication
- SAML authenticate
- SAML logout
- SAML invalidate
- SAML complete logout
- SAML service provider metadata
- SSL certificate
- Snapshot and restore APIs
- Snapshot lifecycle management APIs
- SQL APIs
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Migration guide
- Release notes
- Elasticsearch version 7.14.2
- Elasticsearch version 7.14.1
- Elasticsearch version 7.14.0
- Elasticsearch version 7.13.4
- Elasticsearch version 7.13.3
- Elasticsearch version 7.13.2
- Elasticsearch version 7.13.1
- Elasticsearch version 7.13.0
- Elasticsearch version 7.12.1
- Elasticsearch version 7.12.0
- Elasticsearch version 7.11.2
- Elasticsearch version 7.11.1
- Elasticsearch version 7.11.0
- 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
Create datafeeds API
editCreate datafeeds API
editInstantiates a datafeed.
Request
editPUT _ml/datafeeds/<feed_id>
Prerequisites
edit- You must create an anomaly detection job before you create a datafeed.
-
Requires the following privileges:
-
cluster:
manage_ml
(themachine_learning_admin
built-in role grants this privilege) -
source index configured in the datafeed:
read
-
cluster:
Description
editDatafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job. You can associate only one datafeed to each anomaly detection job.
The datafeed contains a query that runs at a defined interval (frequency
). If
you are concerned about delayed data, you can add a delay (query_delay
) at
each interval. See Handling delayed data.
-
You must use Kibana or this API to create a datafeed. Do not add a
datafeed directly to the
.ml-config
index using the Elasticsearch index API. If Elasticsearch security features are enabled, do not give userswrite
privileges on the.ml-config
index. - When Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had at the time of creation and runs the query using those same roles. If you provide secondary authorization headers, those credentials are used instead.
Path parameters
edit-
<feed_id>
- (Required, string) A numerical character string that uniquely identifies the datafeed. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.
Request body
edit-
aggregations
- (Optional, object) If set, the datafeed performs aggregation searches. Support for aggregations is limited and should be used only with low cardinality data. For more information, see Aggregating data for faster performance.
-
chunking_config
-
(Optional, object) Datafeeds might be required to search over long time periods, for several months or years. This search is split into time chunks in order to ensure the load on Elasticsearch is managed. Chunking configuration controls how the size of these time chunks are calculated and is an advanced configuration option.
Properties of
chunking_config
-
mode
-
(string) There are three available modes:
-
auto
: The chunk size is dynamically calculated. This is the default and recommended value when the datafeed does not use aggregations. -
manual
: Chunking is applied according to the specifiedtime_span
. Use this mode when the datafeed uses aggregations. -
off
: No chunking is applied.
-
-
time_span
-
(time units)
The time span that each search will be querying. This setting is only applicable
when the mode is set to
manual
. For example:3h
.
-
-
delayed_data_check_config
-
(Optional, object) Specifies whether the datafeed checks for missing data and the size of the window. For example:
{"enabled": true, "check_window": "1h"}
.The datafeed can optionally search over indices that have already been read in an effort to determine whether any data has subsequently been added to the index. If missing data is found, it is a good indication that the
query_delay
option is set too low and the data is being indexed after the datafeed has passed that moment in time. See Working with delayed data.This check runs only on real-time datafeeds.
Properties of
delayed_data_check_config
-
check_window
-
(time units) The window of time that is searched for late data.
This window of time ends with the latest finalized bucket. It defaults to
null
, which causes an appropriatecheck_window
to be calculated when the real-time datafeed runs. In particular, the defaultcheck_window
span calculation is based on the maximum of2h
or8 * bucket_span
. -
enabled
-
(Boolean) Specifies whether the datafeed periodically checks for delayed data.
Defaults to
true
.
-
-
frequency
-
(Optional, time units)
The interval at which scheduled queries are made while the datafeed runs in real
time. The default value is either the bucket span for short bucket spans, or,
for longer bucket spans, a sensible fraction of the bucket span. For example:
150s
. Whenfrequency
is shorter than the bucket span, interim results for the last (partial) bucket are written then eventually overwritten by the full bucket results. If the datafeed uses aggregations, this value must be divisible by the interval of the date histogram aggregation. -
indices
-
(Required, array) An array of index names. Wildcards are supported. For example:
["it_ops_metrics", "server*"]
.If any indices are in remote clusters then the machine learning nodes need to have the
remote_cluster_client
role. -
indices_options
-
(Optional, object) Specifies index expansion options that are used during search.
For example:
{ "expand_wildcards": ["all"], "ignore_unavailable": true, "allow_no_indices": "false", "ignore_throttled": true }
For more information about these options, see Multi-target syntax.
-
job_id
- (Required, string) Identifier for the anomaly detection job.
-
max_empty_searches
-
(Optional,integer)
If a real-time datafeed has never seen any data (including during any initial
training period) then it will automatically stop itself and close its associated
job after this many real-time searches that return no documents. In other words,
it will stop after
frequency
timesmax_empty_searches
of real-time operation. If not set then a datafeed with no end time that sees no data will remain started until it is explicitly stopped. By default this setting is not set. -
query
-
(Optional, object)
The Elasticsearch query domain-specific language (DSL). This value corresponds to the
query object in an Elasticsearch search POST body. All the options that are supported by
Elasticsearch can be used, as this object is passed verbatim to Elasticsearch. By default, this
property has the following value:
{"match_all": {"boost": 1}}
. -
query_delay
-
(Optional, time units)
The number of seconds behind real time that data is queried. For example, if
data from 10:04 a.m. might not be searchable in Elasticsearch until 10:06 a.m., set this
property to 120 seconds. The default value is randomly selected between
60s
and120s
. This randomness improves the query performance when there are multiple jobs running on the same node. For more information, see Handling delayed data. -
runtime_mappings
-
(Optional, object) Specifies runtime fields for the datafeed search.
For example:
{ "day_of_week": { "type": "keyword", "script": { "source": "emit(doc['@timestamp'].value.dayOfWeekEnum.getDisplayName(TextStyle.FULL, Locale.ROOT))" } } }
-
script_fields
- (Optional, object) Specifies scripts that evaluate custom expressions and returns script fields to the datafeed. The detector configuration objects in a job can contain functions that use these script fields. For more information, see Transforming data with script fields and Script fields.
-
scroll_size
-
(Optional, unsigned integer)
The
size
parameter that is used in Elasticsearch searches when the datafeed does not use aggregations. The default value is1000
. The maximum value is the value ofindex.max_result_window
which is 10,000 by default.
Examples
editPUT _ml/datafeeds/datafeed-total-requests { "job_id": "total-requests", "indices": ["server-metrics"] }
When the datafeed is created, you receive the following results:
{ "datafeed_id": "datafeed-total-requests", "job_id": "total-requests", "query_delay": "83474ms", "indices": [ "server-metrics" ], "query": { "match_all": { "boost": 1.0 } }, "scroll_size": 1000, "chunking_config": { "mode": "auto" } }