- Elasticsearch Guide: other versions:
- Elasticsearch introduction
- Getting started with Elasticsearch
- Set up Elasticsearch
- Installing Elasticsearch
- Configuring Elasticsearch
- 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
- Starting Elasticsearch
- Stopping Elasticsearch
- Adding nodes to your cluster
- Set up X-Pack
- Configuring X-Pack Java Clients
- Bootstrap Checks for X-Pack
- Upgrade Elasticsearch
- API conventions
- Document APIs
- Search APIs
- Aggregations
- Metrics Aggregations
- Avg Aggregation
- Weighted Avg Aggregation
- Cardinality Aggregation
- Extended Stats Aggregation
- Geo Bounds Aggregation
- Geo Centroid Aggregation
- Max Aggregation
- Min Aggregation
- Percentiles Aggregation
- Percentile Ranks Aggregation
- Scripted Metric Aggregation
- Stats Aggregation
- Sum Aggregation
- Top Hits Aggregation
- Value Count Aggregation
- Median Absolute Deviation 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
- Reverse nested Aggregation
- Sampler Aggregation
- Significant Terms Aggregation
- Significant Text Aggregation
- Terms Aggregation
- Pipeline Aggregations
- Avg Bucket Aggregation
- Derivative Aggregation
- Max Bucket Aggregation
- Min Bucket Aggregation
- Sum Bucket Aggregation
- Stats Bucket Aggregation
- Extended Stats Bucket Aggregation
- Percentiles Bucket Aggregation
- Moving Average Aggregation
- Moving Function Aggregation
- Cumulative Sum Aggregation
- Bucket Script Aggregation
- Bucket Selector Aggregation
- Bucket Sort Aggregation
- Serial Differencing Aggregation
- Matrix Aggregations
- Caching heavy aggregations
- Returning only aggregation results
- Aggregation Metadata
- Returning the type of the aggregation
- Metrics Aggregations
- Indices APIs
- Create Index
- Delete Index
- Get Index
- Indices Exists
- Open / Close Index API
- Shrink Index
- Split Index
- Rollover Index
- Put Mapping
- Get Mapping
- Get Field Mapping
- Types Exists
- Index Aliases
- Update Indices Settings
- Get Settings
- Analyze
- Index Templates
- Indices Stats
- Indices Segments
- Indices Recovery
- Indices Shard Stores
- Clear Cache
- Flush
- Refresh
- Force Merge
- cat APIs
- Cluster APIs
- Query DSL
- Scripting
- Mapping
- Analysis
- Anatomy of an analyzer
- Testing analyzers
- Analyzers
- Normalizers
- Tokenizers
- Standard Tokenizer
- Letter Tokenizer
- Lowercase Tokenizer
- Whitespace Tokenizer
- UAX URL Email Tokenizer
- Classic Tokenizer
- Thai Tokenizer
- NGram Tokenizer
- Edge NGram Tokenizer
- Keyword Tokenizer
- Pattern Tokenizer
- Char Group Tokenizer
- Simple Pattern Tokenizer
- Simple Pattern Split Tokenizer
- Path Hierarchy Tokenizer
- Path Hierarchy Tokenizer Examples
- Token Filters
- ASCII Folding Token Filter
- Flatten Graph Token Filter
- Length Token Filter
- Lowercase Token Filter
- Uppercase Token Filter
- NGram Token Filter
- Edge NGram Token Filter
- Porter Stem Token Filter
- Shingle Token Filter
- Stop Token Filter
- Word Delimiter Token Filter
- Word Delimiter Graph Token Filter
- Multiplexer Token Filter
- Conditional Token Filter
- Predicate Token Filter Script
- Stemmer Token Filter
- Stemmer Override Token Filter
- Keyword Marker Token Filter
- Keyword Repeat Token Filter
- KStem Token Filter
- Snowball Token Filter
- Phonetic Token Filter
- Synonym Token Filter
- Parsing synonym files
- Synonym Graph Token Filter
- Compound Word Token Filters
- Reverse Token Filter
- Elision Token Filter
- Truncate Token Filter
- Unique Token Filter
- Pattern Capture Token Filter
- Pattern Replace Token Filter
- Trim Token Filter
- Limit Token Count Token Filter
- Hunspell Token Filter
- Common Grams Token Filter
- Normalization Token Filter
- CJK Width Token Filter
- CJK Bigram Token Filter
- Delimited Payload Token Filter
- Keep Words Token Filter
- Keep Types Token Filter
- Exclude mode settings example
- Classic Token Filter
- Apostrophe Token Filter
- Decimal Digit Token Filter
- Fingerprint Token Filter
- Minhash Token Filter
- Remove Duplicates Token Filter
- Character Filters
- Modules
- Index modules
- Ingest node
- Pipeline Definition
- Ingest APIs
- Accessing Data in Pipelines
- Conditional Execution in Pipelines
- Handling Failures in Pipelines
- Processors
- Append Processor
- Bytes Processor
- Convert Processor
- Date Processor
- Date Index Name Processor
- Dissect Processor
- Dot Expander Processor
- Drop Processor
- Fail Processor
- Foreach Processor
- GeoIP Processor
- Grok Processor
- Gsub 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
- Managing the index lifecycle
- Getting started with index lifecycle management
- Policy phases and actions
- Set up index lifecycle management policy
- Using policies to manage index rollover
- Update policy
- Index lifecycle error handling
- Restoring snapshots of managed indices
- Start and stop index lifecycle management
- Using ILM with existing indices
- SQL access
- Monitor a cluster
- Rolling up historical data
- Frozen indices
- Set up a cluster for high availability
- X-Pack APIs
- Info API
- Cross-cluster replication APIs
- Explore API
- Freeze index
- Index lifecycle management API
- Licensing APIs
- Migration APIs
- Machine learning APIs
- Add events to calendar
- Add jobs to calendar
- Close jobs
- Create calendar
- Create datafeeds
- Create filter
- Create jobs
- Delete calendar
- Delete datafeeds
- Delete events from calendar
- Delete filter
- Delete forecast
- Delete jobs
- Delete jobs from calendar
- Delete model snapshots
- Delete expired data
- Find file structure
- Flush jobs
- Forecast jobs
- Get calendars
- Get buckets
- Get overall buckets
- Get categories
- Get datafeeds
- Get datafeed statistics
- Get influencers
- Get jobs
- Get job statistics
- Get machine learning info
- Get model snapshots
- 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
- Rollup 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
- Delete application privileges
- Delete role mappings
- Delete roles
- Delete users
- Disable users
- Enable users
- Get API key information
- Get application privileges
- Get role mappings
- Get roles
- Get token
- Get users
- Has privileges
- Invalidate API key
- Invalidate token
- SSL certificate
- Unfreeze index
- Watcher APIs
- Definitions
- Secure a cluster
- Overview
- Configuring security
- Encrypting communications in Elasticsearch
- Encrypting communications in an Elasticsearch Docker Container
- Enabling cipher suites for stronger encryption
- Separating node-to-node and client traffic
- Configuring an Active Directory realm
- Configuring a file realm
- Configuring an LDAP realm
- Configuring a native realm
- Configuring a PKI realm
- Configuring a SAML realm
- Configuring a Kerberos realm
- FIPS 140-2
- Security files
- How security works
- 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
- 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
- User authorization
- Auditing security events
- 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
- Testing
- Glossary of terms
- Release highlights
- Breaking changes
- Release notes
Miscellaneous cluster settings
editMiscellaneous cluster settings
editMetadata
editAn entire cluster may be set to read-only with the following dynamic setting:
-
cluster.blocks.read_only
- Make the whole cluster read only (indices do not accept write operations), metadata is not allowed to be modified (create or delete indices).
-
cluster.blocks.read_only_allow_delete
-
Identical to
cluster.blocks.read_only
but allows to delete indices to free up resources.
Don’t rely on this setting to prevent changes to your cluster. Any user with access to the cluster-update-settings API can make the cluster read-write again.
Cluster Shard Limit
editThere is a soft limit on the number of shards in a cluster, based on the number of nodes in the cluster. This is intended to prevent operations which may unintentionally destabilize the cluster.
This limit is intended as a safety net, not a sizing recommendation. The exact number of shards your cluster can safely support depends on your hardware configuration and workload, but should remain well below this limit in almost all cases, as the default limit is set quite high.
If an operation, such as creating a new index, restoring a snapshot of an index, or opening a closed index would lead to the number of shards in the cluster going over this limit, the operation will fail with an error indicating the shard limit.
If the cluster is already over the limit, due to changes in node membership or setting changes, all operations that create or open indices will fail until either the limit is increased as described below, or some indices are closed or deleted to bring the number of shards below the limit.
Replicas count towards this limit, but closed indexes do not. An index with 5 primary shards and 2 replicas will be counted as 15 shards. Any closed index is counted as 0, no matter how many shards and replicas it contains.
The limit defaults to 1,000 shards per data node, and can be dynamically adjusted using the following property:
-
cluster.max_shards_per_node
- Controls the number of shards allowed in the cluster per data node.
For example, a 3-node cluster with the default setting would allow 3,000 shards total, across all open indexes. If the above setting is changed to 500, then the cluster would allow 1,500 shards total.
If there are no data nodes in the cluster, the limit will not be enforced. This allows the creation of indices during cluster creation if dedicated master nodes are set up before data nodes.
User Defined Cluster Metadata
editUser-defined metadata can be stored and retrieved using the Cluster Settings API.
This can be used to store arbitrary, infrequently-changing data about the cluster
without the need to create an index to store it. This data may be stored using
any key prefixed with cluster.metadata.
. For example, to store the email
address of the administrator of a cluster under the key cluster.metadata.administrator
,
issue this request:
PUT /_cluster/settings { "persistent": { "cluster.metadata.administrator": "sysadmin@example.com" } }
User-defined cluster metadata is not intended to store sensitive or confidential information. Any information stored in user-defined cluster metadata will be viewable by anyone with access to the Cluster Get Settings API, and is recorded in the Elasticsearch logs.
Index Tombstones
editThe cluster state maintains index tombstones to explicitly denote indices that have been deleted. The number of tombstones maintained in the cluster state is controlled by the following property, which cannot be updated dynamically:
-
cluster.indices.tombstones.size
-
Index tombstones prevent nodes that are not part of the cluster when a delete
occurs from joining the cluster and reimporting the index as though the delete
was never issued. To keep the cluster state from growing huge we only keep the
last
cluster.indices.tombstones.size
deletes, which defaults to 500. You can increase it if you expect nodes to be absent from the cluster and miss more than 500 deletes. We think that is rare, thus the default. Tombstones don’t take up much space, but we also think that a number like 50,000 is probably too big.
Logger
editThe settings which control logging can be updated dynamically with the
logger.
prefix. For instance, to increase the logging level of the
indices.recovery
module to DEBUG
, issue this request:
PUT /_cluster/settings { "transient": { "logger.org.elasticsearch.indices.recovery": "DEBUG" } }
Persistent Tasks Allocations
editPlugins can create a kind of tasks called persistent tasks. Those tasks are usually long-live tasks and are stored in the cluster state, allowing the tasks to be revived after a full cluster restart.
Every time a persistent task is created, the master node takes care of assigning the task to a node of the cluster, and the assigned node will then pick up the task and execute it locally. The process of assigning persistent tasks to nodes is controlled by the following properties, which can be updated dynamically:
-
cluster.persistent_tasks.allocation.enable
-
Enable or disable allocation for persistent tasks:
-
all
- (default) Allows persistent tasks to be assigned to nodes -
none
- No allocations are allowed for any type of persistent task
This setting does not affect the persistent tasks that are already being executed. Only newly created persistent tasks, or tasks that must be reassigned (after a node left the cluster, for example), are impacted by this setting.
-
-
cluster.persistent_tasks.allocation.recheck_interval
- The master node will automatically check whether persistent tasks need to be assigned when the cluster state changes significantly. However, there may be other factors, such as memory usage, that affect whether persistent tasks can be assigned to nodes but do not cause the cluster state to change. This setting controls how often assignment checks are performed to react to these factors. The default is 30 seconds. The minimum permitted value is 10 seconds.
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