- Elasticsearch Guide: other versions:
- What is Elasticsearch?
- What’s new in 7.7
- 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 recovery settings
- Indexing buffer settings
- License settings
- Local gateway settings
- Logging configuration
- Machine learning settings
- Monitoring settings
- Node
- Network settings
- Node query cache settings
- Search settings
- Security settings
- Shard request cache settings
- Snapshot lifecycle management settings
- SQL access 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
- Search your data
- Query DSL
- 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
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Weighted Avg Aggregation
- Boxplot Aggregation
- Cardinality Aggregation
- Stats Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
- Geo Centroid Aggregation
- Max Aggregation
- Min Aggregation
- Median Absolute Deviation Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- String Stats Aggregation
- Sum Aggregation
- Top Hits Aggregation
- Top Metrics Aggregation
- Value Count Aggregation
- Bucket Aggregations
- Adjacency Matrix Aggregation
- Auto-interval Date Histogram Aggregation
- Children Aggregation
- Composite aggregation
- Date histogram aggregation
- Date Range Aggregation
- Diversified Sampler Aggregation
- Filter Aggregation
- Filters Aggregation
- Geo Distance Aggregation
- GeoHash grid Aggregation
- GeoTile Grid Aggregation
- Global Aggregation
- Histogram Aggregation
- IP Range Aggregation
- Missing Aggregation
- Nested Aggregation
- Parent Aggregation
- Range Aggregation
- Rare Terms Aggregation
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Subtleties of bucketing range fields
- Pipeline Aggregations
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Bucket Sort Aggregation
- Avg Bucket Aggregation
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Cumulative Cardinality Aggregation
- Cumulative Sum Aggregation
- Derivative Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
- Moving Function Aggregation
- Serial Differencing Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Indexing aggregation results with transforms
- Metrics Aggregations
- Scripting
- Mapping
- Text analysis
- Overview
- Concepts
- Configure text analysis
- Built-in analyzer reference
- Tokenizer reference
- Char Group Tokenizer
- Classic Tokenizer
- Edge n-gram tokenizer
- Keyword Tokenizer
- Letter Tokenizer
- Lowercase Tokenizer
- N-gram tokenizer
- Path Hierarchy Tokenizer
- Path Hierarchy Tokenizer Examples
- Pattern Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Standard Tokenizer
- Thai Tokenizer
- UAX URL Email Tokenizer
- Whitespace Tokenizer
- 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 modules
- Ingest node
- Pipeline Definition
- Accessing Data in Pipelines
- Conditional Execution in Pipelines
- Handling Failures in Pipelines
- Enrich your data
- Processors
- Append Processor
- Bytes Processor
- Circle Processor
- Convert Processor
- CSV Processor
- Date Processor
- Date Index Name Processor
- Dissect Processor
- Dot Expander Processor
- Drop Processor
- Enrich Processor
- Fail Processor
- Foreach Processor
- GeoIP Processor
- Grok Processor
- Gsub Processor
- HTML Strip Processor
- Inference Processor
- Join Processor
- JSON Processor
- KV Processor
- Lowercase Processor
- Pipeline Processor
- Remove Processor
- Rename Processor
- Script Processor
- Set Processor
- Set Security User Processor
- Split Processor
- Sort Processor
- Trim Processor
- Uppercase Processor
- URL Decode Processor
- User Agent processor
- ILM: Manage the index lifecycle
- 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
- Security privileges
- Document level security
- Field level security
- Granting privileges for indices 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
- 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
- Alerting on cluster and index events
- Command line tools
- How To
- Glossary of terms
- REST APIs
- API conventions
- 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 shards
- cat segments
- 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
- Document APIs
- Enrich APIs
- Explore API
- Index APIs
- Add index alias
- Analyze
- Clear cache
- Clone index
- Close index
- Create index
- Delete index
- Delete index alias
- Delete index template
- Flush
- Force merge
- Freeze index
- Get field mapping
- Get index
- Get index alias
- Get index settings
- Get index template
- Get mapping
- Index alias exists
- Index exists
- Index recovery
- Index segments
- Index shard stores
- Index stats
- Index template exists
- Open index
- Put index template
- Put mapping
- Refresh
- Rollover index
- Shrink index
- Split index
- Synced flush
- Type exists
- Unfreeze index
- Update index alias
- Update index settings
- Index lifecycle management API
- Ingest APIs
- Info API
- Licensing APIs
- Machine learning anomaly detection APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create jobs
- Create calendar
- Create datafeeds
- Create filter
- Delete calendar
- Delete datafeeds
- Delete events from calendar
- Delete filter
- Delete forecast
- 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 filter
- Update jobs
- Update model snapshots
- Machine learning data frame analytics APIs
- Create data frame analytics jobs
- Create inference trained model
- Delete data frame analytics jobs
- Delete inference trained model
- Evaluate data frame analytics
- Explain data frame analytics API
- Get data frame analytics jobs
- Get data frame analytics jobs stats
- Get inference trained model
- Get inference trained model stats
- Start data frame analytics jobs
- Stop data frame analytics jobs
- Migration APIs
- Reload search analyzers
- Rollup APIs
- Search APIs
- Security APIs
- Authenticate
- Change passwords
- Clear cache
- Clear roles 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
- Has privileges
- Invalidate API key
- Invalidate token
- OpenID Connect Prepare Authentication API
- OpenID Connect authenticate API
- OpenID Connect logout API
- SAML prepare authentication API
- SAML authenticate API
- SAML logout API
- SAML invalidate API
- SSL certificate
- Snapshot and restore APIs
- Snapshot lifecycle management API
- Transform APIs
- Usage API
- Watcher APIs
- Definitions
- Breaking changes
- Release notes
- 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
Set up an enrich processor
editSet up an enrich processor
editTo set up an enrich processor, follow these steps:
Once you have an enrich processor set up, you can update your enrich data and update your enrich policies.
The enrich processor performs several operations and may impact the speed of your ingest pipeline.
We strongly recommend testing and benchmarking your enrich processors before deploying them in production.
We do not recommend using the enrich processor to append real-time data. The enrich processor works best with reference data that doesn’t change frequently.
Prerequisites
editIf you use Elasticsearch security features, you must have:
-
read
index privileges for any indices used -
The
enrich_user
built-in role
Add enrich data
editTo begin, add documents to one or more source indices. These documents should contain the enrich data you eventually want to add to incoming documents.
You can manage source indices just like regular Elasticsearch indices using the document and index APIs.
You also can set up Beats, such as a Filebeat, to automatically send and index documents to your source indices. See Getting started with Beats.
Create an enrich policy
editAfter adding enrich data to your source indices, you can define an enrich policy. When defining the enrich policy, you should include at least the following:
- A list of one or more source indices which store enrich data as documents
- The policy type which determines how the processor matches the enrich data to incoming documents
- A match field from the source indices used to match incoming documents
- Enrich fields containing enrich data from the source indices you want to add to incoming documents
You can use this definition to create the enrich policy with the put enrich policy API.
Once created, you can’t update or change an enrich policy. See Update an enrich policy.
Execute the enrich policy
editOnce the enrich policy is created, you can execute it using the execute enrich policy API to create an enrich index.
The enrich index contains documents from the policy’s source indices.
Enrich indices always begin with .enrich-*
,
are read-only,
and are force merged.
Enrich indices should be used by the enrich processor only. Avoid using enrich indices for other purposes.
Add an enrich processor to an ingest pipeline
editOnce you have source indices, an enrich policy, and the related enrich index in place, you can set up an ingest pipeline that includes an enrich processor for your policy.
Define an enrich processor and add it to an ingest pipeline using the put pipeline API.
When defining the enrich processor, you must include at least the following:
- The enrich policy to use.
- The field used to match incoming documents to the documents in your enrich index.
- The target field to add to incoming documents. This target field contains the match and enrich fields specified in your enrich policy.
You also can use the max_matches
option to set the number of enrich documents
an incoming document can match. If set to the default of 1
, data is added to
an incoming document’s target field as a JSON object. Otherwise, the data is
added as an array.
See Enrich Processor for a full list of configuration options.
You also can add other processors to your ingest pipeline.
Ingest and enrich documents
editYou can now use your ingest pipeline to enrich and index documents.
Before implementing the pipeline in production, we recommend indexing a few test documents first and verifying enrich data was added correctly using the get API.
Update an enrich index
editOnce created, you cannot update or index documents to an enrich index. Instead, update your source indices and execute the enrich policy again. This creates a new enrich index from your updated source indices and deletes the previous enrich index.
If wanted, you can reindex or update any already ingested documents using your ingest pipeline.
Update an enrich policy
editOnce created, you can’t update or change an enrich policy. Instead, you can:
- Create and execute a new enrich policy.
- Replace the previous enrich policy with the new enrich policy in any in-use enrich processors.
- Use the delete enrich policy API to delete the previous enrich policy.
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