- 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
- HTML Strip 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
- 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
- Monitor a cluster
- Frozen indices
- Set up a cluster for high availability
- Roll up or transform your data
- X-Pack APIs
- Info API
- Cross-cluster replication APIs
- Explore API
- Freeze index
- Index lifecycle management API
- Licensing APIs
- Machine learning 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
- 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
- Migration APIs
- 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
- OpenID Connect Prepare Authentication API
- OpenID Connect Authenticate API
- OpenID Connect Logout API
- SSL certificate
- Transform APIs
- 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
- Security files
- FIPS 140-2
- 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
- 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
- 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
- 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
Bootstrapping a cluster
editBootstrapping a cluster
editStarting an Elasticsearch cluster for the very first time requires the initial set of master-eligible nodes to be explicitly defined on one or more of the master-eligible nodes in the cluster. This is known as cluster bootstrapping. This is only required the first time a cluster starts up: nodes that have already joined a cluster store this information in their data folder for use in a full cluster restart, and freshly-started nodes that are joining a running cluster obtain this information from the cluster’s elected master.
The initial set of master-eligible nodes is defined in the
cluster.initial_master_nodes
setting. This should be
set to a list containing one of the following items for each master-eligible
node:
- The node name of the node.
-
The node’s hostname if
node.name
is not set, becausenode.name
defaults to the node’s hostname. You must use either the fully-qualified hostname or the bare hostname depending on your system configuration. -
The IP address of the node’s publish address, if it is
not possible to use the
node.name
of the node. This is normally the IP address to whichnetwork.host
resolves but this can be overridden. -
The IP address and port of the node’s publish address, in the form
IP:PORT
, if it is not possible to use thenode.name
of the node and there are multiple nodes sharing a single IP address.
When you start a master-eligible node, you can provide this setting on the
command line or in the elasticsearch.yml
file. After the cluster has formed,
this setting is no longer required. It should not be set for master-ineligible
nodes, master-eligible nodes joining an existing cluster, or cluster restarts.
It is technically sufficient to set cluster.initial_master_nodes
on a single
master-eligible node in the cluster, and only to mention that single node in the
setting’s value, but this provides no fault tolerance before the cluster has
fully formed. It is therefore better to bootstrap using at least three
master-eligible nodes, each with a cluster.initial_master_nodes
setting
containing all three nodes.
You must set cluster.initial_master_nodes
to the same list of nodes
on each node on which it is set in order to be sure that only a single cluster
forms during bootstrapping and therefore to avoid the risk of data loss.
For a cluster with 3 master-eligible nodes (with node names
master-a
, master-b
and master-c
) the configuration will look as follows:
cluster.initial_master_nodes: - master-a - master-b - master-c
Like all node settings, it is also possible to specify the initial set of master nodes on the command-line that is used to start Elasticsearch:
$ bin/elasticsearch -Ecluster.initial_master_nodes=master-a,master-b,master-c
The node names used in the
cluster.initial_master_nodes
list must exactly match the node.name
properties of the nodes. By default the node name is set to the machine’s
hostname which may or may not be fully-qualified depending on your system
configuration. If each node name is a fully-qualified domain name such as
master-a.example.com
then you must use fully-qualified domain names in the
cluster.initial_master_nodes
list too; conversely if your node names are bare
hostnames (without the .example.com
suffix) then you must use bare hostnames
in the cluster.initial_master_nodes
list. If you use a mix of fully-qualifed
and bare hostnames, or there is some other mismatch between node.name
and
cluster.initial_master_nodes
, then the cluster will not form successfully and
you will see log messages like the following.
[master-a.example.com] master not discovered yet, this node has not previously joined a bootstrapped (v7+) cluster, and this node must discover master-eligible nodes [master-a, master-b] to bootstrap a cluster: have discovered [{master-b.example.com}{...
This message shows the node names master-a.example.com
and
master-b.example.com
as well as the cluster.initial_master_nodes
entries
master-a
and master-b
, and it is clear from this message that they do not
match exactly.
Choosing a cluster name
editThe cluster.name
setting enables you to create multiple
clusters which are separated from each other. Nodes verify that they agree on
their cluster name when they first connect to each other, and Elasticsearch
will only form a cluster from nodes that all have the same cluster name. The
default value for the cluster name is elasticsearch
, but it is recommended to
change this to reflect the logical name of the cluster.
Auto-bootstrapping in development mode
editIf the cluster is running with a completely default configuration then it will automatically bootstrap a cluster based on the nodes that could be discovered to be running on the same host within a short time after startup. This means that by default it is possible to start up several nodes on a single machine and have them automatically form a cluster which is very useful for development environments and experimentation. However, since nodes may not always successfully discover each other quickly enough this automatic bootstrapping cannot be relied upon and cannot be used in production deployments.
If any of the following settings are configured then auto-bootstrapping will not
take place, and you must configure cluster.initial_master_nodes
as described
in the section on cluster bootstrapping:
-
discovery.seed_providers
-
discovery.seed_hosts
-
cluster.initial_master_nodes
If you start an Elasticsearch node
without configuring these settings then it will start up in development mode and
auto-bootstrap itself into a new cluster. If you start some Elasticsearch nodes on
different hosts then by default they will not discover each other and will form
a different cluster on each host. Elasticsearch will not merge separate clusters together
after they have formed, even if you subsequently try and configure all the nodes
into a single cluster. This is because there is no way to merge these separate
clusters together without a risk of data loss. You can tell that you have formed
separate clusters by checking the cluster UUID reported by GET /
on each node.
If you intended to form a single cluster then you should start again:
- Shut down all the nodes.
- Completely wipe each node by deleting the contents of their data folders.
-
Configure
cluster.initial_master_nodes
as described above. - Restart all the nodes and verify that they have formed a single cluster.