- 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
Node
editNode
editAny time that you start an instance of Elasticsearch, you are starting a node. A collection of connected nodes is called a cluster. If you are running a single node of Elasticsearch, then you have a cluster of one node.
Every node in the cluster can handle HTTP and Transport traffic by default. The transport layer is used exclusively for communication between nodes; the HTTP layer is used by REST clients.
All nodes know about all the other nodes in the cluster and can forward client requests to the appropriate node.
By default, a node is all of the following types: master-eligible, data, ingest, and (if available) machine learning and transform.
As the cluster grows and in particular if you have large machine learning jobs or continuous transforms, consider separating dedicated master-eligible nodes from dedicated data nodes, machine learning nodes, and transform nodes.
- Master-eligible node
-
A node that has
node.master
set totrue
(default), which makes it eligible to be elected as the master node, which controls the cluster. - Data node
-
A node that has
node.data
set totrue
(default). Data nodes hold data and perform data related operations such as CRUD, search, and aggregations. - Ingest node
-
A node that has
node.ingest
set totrue
(default). Ingest nodes are able to apply an ingest pipeline to a document in order to transform and enrich the document before indexing. With a heavy ingest load, it makes sense to use dedicated ingest nodes and to mark the master and data nodes asnode.ingest: false
. - Machine learning node
-
A node that has
xpack.ml.enabled
andnode.ml
set totrue
, which is the default behavior in the Elasticsearch default distribution. If you want to use machine learning features, there must be at least one machine learning node in your cluster. For more information about machine learning features, see Machine learning in the Elastic Stack.If you use the OSS-only distribution, do not set
node.ml
. Otherwise, the node fails to start. - Transform node
-
A node that has
xpack.transform.enabled
andnode.transform
set totrue
. If you want to use transforms, there must be at least one transform node in your cluster. For more information, see Transforms settings and Transforming data.
Requests like search requests or bulk-indexing requests may involve data held on different data nodes. A search request, for example, is executed in two phases which are coordinated by the node which receives the client request — the coordinating node.
In the scatter phase, the coordinating node forwards the request to the data nodes which hold the data. Each data node executes the request locally and returns its results to the coordinating node. In the gather phase, the coordinating node reduces each data node’s results into a single global resultset.
Every node is implicitly a coordinating node. This means that a node that has
all three node.master
, node.data
and node.ingest
set to false
will
only act as a coordinating node, which cannot be disabled. As a result, such
a node needs to have enough memory and CPU in order to deal with the gather
phase.
Master-eligible node
editThe master node is responsible for lightweight cluster-wide actions such as creating or deleting an index, tracking which nodes are part of the cluster, and deciding which shards to allocate to which nodes. It is important for cluster health to have a stable master node.
Any master-eligible node that is not a voting-only node may be elected to become the master node by the master election process.
Master nodes must have access to the data/
directory (just like
data
nodes) as this is where the cluster state is persisted between node
restarts.
Dedicated master-eligible node
editIt is important for the health of the cluster that the elected master node has
the resources it needs to fulfill its responsibilities. If the elected master
node is overloaded with other tasks then the cluster may not operate well. In
particular, indexing and searching your data can be very resource-intensive, so
in large or high-throughput clusters it is a good idea to avoid using the
master-eligible nodes for tasks such as indexing and searching. You can do this
by configuring three of your nodes to be dedicated master-eligible nodes.
Dedicated master-eligible nodes only have the master
role, allowing them to
focus on managing the cluster. While master nodes can also behave as
coordinating nodes and route search and indexing requests
from clients to data nodes, it is better not to use dedicated master nodes for
this purpose.
To create a dedicated master-eligible node in the default distribution, set:
node.master: true node.voting_only: false node.data: false node.ingest: false node.ml: false xpack.ml.enabled: true node.transform: false xpack.transform.enabled: true node.remote_cluster_client: false
The |
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Disable the |
|
The |
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Disable remote cluster connections (enabled by default). |
To create a dedicated master-eligible node in the OSS-only distribution, set:
Voting-only master-eligible node
editA voting-only master-eligible node is a node that participates in master elections but which will not act as the cluster’s elected master node. In particular, a voting-only node can serve as a tiebreaker in elections.
It may seem confusing to use the term "master-eligible" to describe a voting-only node since such a node is not actually eligible to become the master at all. This terminology is an unfortunate consequence of history: master-eligible nodes are those nodes that participate in elections and perform certain tasks during cluster state publications, and voting-only nodes have the same responsibilities even if they can never become the elected master.
To configure a master-eligible node as a voting-only node, set the following setting:
The voting_only
role requires the default distribution of Elasticsearch and is not
supported in the OSS-only distribution. If you use the OSS-only distribution and set
node.voting_only
then the node will fail to start. Also note that only
master-eligible nodes can be marked as voting-only.
High availability (HA) clusters require at least three master-eligible nodes, at least two of which are not voting-only nodes. Such a cluster will be able to elect a master node even if one of the nodes fails.
Since voting-only nodes never act as the cluster’s elected master, they may require require less heap and a less powerful CPU than the true master nodes. However all master-eligible nodes, including voting-only nodes, require reasonably fast persistent storage and a reliable and low-latency network connection to the rest of the cluster, since they are on the critical path for publishing cluster state updates.
Voting-only master-eligible nodes may also fill other roles in your cluster. For instance, a node may be both a data node and a voting-only master-eligible node. A dedicated voting-only master-eligible nodes is a voting-only master-eligible node that fills no other roles in the cluster. To create a dedicated voting-only master-eligible node in the default distribution, set:
node.master: true node.voting_only: true node.data: false node.ingest: false node.ml: false xpack.ml.enabled: true node.transform: false xpack.transform.enabled: true node.remote_cluster_client: false
The |
|
Enable the |
|
Disable the |
|
Disable the |
|
Disable the |
|
The |
|
Disable the |
|
The |
|
Disable remote cluster connections (enabled by default). |
Data node
editData nodes hold the shards that contain the documents you have indexed. Data nodes handle data related operations like CRUD, search, and aggregations. These operations are I/O-, memory-, and CPU-intensive. It is important to monitor these resources and to add more data nodes if they are overloaded.
The main benefit of having dedicated data nodes is the separation of the master and data roles.
To create a dedicated data node in the default distribution, set:
node.master: false node.voting_only: false node.data: true node.ingest: false node.ml: false node.transform: false xpack.transform.enabled: true node.remote_cluster_client: false
Disable the |
|
The |
|
The |
|
Disable the |
|
Disable the |
|
Disable the |
|
The |
|
Disable remote cluster connections (enabled by default). |
To create a dedicated data node in the OSS-only distribution, set:
Ingest node
editIngest nodes can execute pre-processing pipelines, composed of one or more ingest processors. Depending on the type of operations performed by the ingest processors and the required resources, it may make sense to have dedicated ingest nodes, that will only perform this specific task.
To create a dedicated ingest node in the default distribution, set:
node.master: false node.voting_only: false node.data: false node.ingest: true node.ml: false node.transform: false node.remote_cluster_client: false
Disable the |
|
The |
|
Disable the |
|
The |
|
Disable the |
|
Disable the |
|
Disable remote cluster connections (enabled by default). |
To create a dedicated ingest node in the OSS-only distribution, set:
Coordinating only node
editIf you take away the ability to be able to handle master duties, to hold data, and pre-process documents, then you are left with a coordinating node that can only route requests, handle the search reduce phase, and distribute bulk indexing. Essentially, coordinating only nodes behave as smart load balancers.
Coordinating only nodes can benefit large clusters by offloading the coordinating node role from data and master-eligible nodes. They join the cluster and receive the full cluster state, like every other node, and they use the cluster state to route requests directly to the appropriate place(s).
Adding too many coordinating only nodes to a cluster can increase the burden on the entire cluster because the elected master node must await acknowledgement of cluster state updates from every node! The benefit of coordinating only nodes should not be overstated — data nodes can happily serve the same purpose.
To create a dedicated coordinating node in the default distribution, set:
node.master: false node.voting_only: false node.data: false node.ingest: false node.ml: false xpack.ml.enabled: true node.transform: false xpack.transform.enabled: true node.remote_cluster_client: false
Disable the |
|
The |
|
Disable the |
|
Disable the |
|
Disable the |
|
The |
|
Disable the |
|
The |
|
Disable remote cluster connections (enabled by default). |
To create a dedicated coordinating node in the OSS-only distribution, set:
Machine learning node
editThe machine learning features provide machine learning nodes, which run jobs and handle machine learning API
requests. If xpack.ml.enabled
is set to true
and node.ml
is set to false
,
the node can service API requests but it cannot run jobs.
If you want to use machine learning features in your cluster, you must enable machine learning
(set xpack.ml.enabled
to true
) on all master-eligible nodes. If you want to
use machine learning features in clients (including Kibana), it must also be enabled on all
coordinating nodes. If you have the OSS-only distribution, do not use these settings.
For more information about these settings, see Machine learning settings.
To create a dedicated machine learning node in the default distribution, set:
node.master: false node.voting_only: false node.data: false node.ingest: false node.ml: true xpack.ml.enabled: true node.transform: false xpack.transform.enabled: true node.remote_cluster_client: false
Disable the |
|
The |
|
Disable the |
|
Disable the |
|
The |
|
The |
|
Disable the |
|
The |
|
Disable remote cluster connections (enabled by default). |
Transform node
editTransform nodes run transforms and handle transform API requests.
If you want to use transforms in your cluster, you must have
xpack.transform.enabled
set to true
on all master-eligible nodes and all
data nodes. If you want to use transforms in clients (including Kibana), it
must also be enabled on all coordinating nodes. You must also have
node.transform
set to true
on at least one node. This is the default
behavior. If you have the OSS-only distribution, do not use these settings. For more
information, see Transforms settings.
To create a dedicated transform node in the default distribution, set:
Changing the role of a node
editEach data node maintains the following data on disk:
- the shard data for every shard allocated to that node,
- the index metadata corresponding with every shard allocated to that node, and
- the cluster-wide metadata, such as settings and index templates.
Similarly, each master-eligible node maintains the following data on disk:
- the index metadata for every index in the cluster, and
- the cluster-wide metadata, such as settings and index templates.
Each node checks the contents of its data path at startup. If it discovers
unexpected data then it will refuse to start. This is to avoid importing
unwanted dangling indices which can lead
to a red cluster health. To be more precise, nodes with node.data: false
will
refuse to start if they find any shard data on disk at startup, and nodes with
both node.master: false
and node.data: false
will refuse to start if they
have any index metadata on disk at startup.
It is possible to change the roles of a node by adjusting its
elasticsearch.yml
file and restarting it. This is known as repurposing a
node. In order to satisfy the checks for unexpected data described above, you
must perform some extra steps to prepare a node for repurposing when setting
its node.data
or node.master
roles to false
:
-
If you want to repurpose a data node by changing
node.data
tofalse
then you should first use an allocation filter to safely migrate all the shard data onto other nodes in the cluster. -
If you want to repurpose a node to have both
node.master: false
andnode.data: false
then it is simplest to start a brand-new node with an empty data path and the desired roles. You may find it safest to use an allocation filter to migrate the shard data elsewhere in the cluster first.
If it is not possible to follow these extra steps then you may be able to use
the elasticsearch-node repurpose
tool to delete any
excess data that prevents a node from starting.
Node data path settings
editpath.data
editEvery data and master-eligible node requires access to a data directory where
shards and index and cluster metadata will be stored. The path.data
defaults
to $ES_HOME/data
but can be configured in the elasticsearch.yml
config
file an absolute path or a path relative to $ES_HOME
as follows:
path.data: /var/elasticsearch/data
Like all node settings, it can also be specified on the command line as:
./bin/elasticsearch -Epath.data=/var/elasticsearch/data
When using the .zip
or .tar.gz
distributions, the path.data
setting
should be configured to locate the data directory outside the Elasticsearch home
directory, so that the home directory can be deleted without deleting your data!
The RPM and Debian distributions do this for you already.
node.max_local_storage_nodes
editThe data path can be shared by multiple nodes, even by nodes from different clusters. It is recommended however to only run one node of Elasticsearch using the same data path. This setting is deprecated in 7.x and will be removed in version 8.0.
By default, Elasticsearch is configured to prevent more than one node from sharing the
same data path. To allow for more than one node (e.g., on your development
machine), use the setting node.max_local_storage_nodes
and set this to a
positive integer larger than one.
Never run different node types (i.e. master, data) from the same data directory. This can lead to unexpected data loss.
Other node settings
editMore node settings can be found in Configuring Elasticsearch and Important Elasticsearch configuration, including:
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