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Elastic Docs ›Elasticsearch Guide [7.10] ›Set up Elasticsearch ›Configuring Elasticsearch

Node

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Node

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Any 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. All data nodes are also transform nodes.

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.

Node roles

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You can define the roles of a node by setting node.roles. If you don’t configure this setting, then the node has the following roles by default:

  • master
  • data
  • data_content
  • data_hot
  • data_warm
  • data_cold
  • ingest
  • ml
  • remote_cluster_client

If you set node.roles, the node is assigned only the roles you specify.

Master-eligible node
A node that has the master role (default), which makes it eligible to be elected as the master node, which controls the cluster.
Data node
A node that has the data role (default). Data nodes hold data and perform data related operations such as CRUD, search, and aggregations. A node with the data role can fill any of the specialised data node roles.
Ingest node
A node that has the ingest role (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 not include the ingest role from nodes that have the master or data roles.
Remote-eligible node
A node that has the remote_cluster_client role (default), which makes it eligible to act as a remote client. By default, any node in the cluster can act as a cross-cluster client and connect to remote clusters.
Machine learning node

A node that has xpack.ml.enabled and the ml role, 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 add the ml role. Otherwise, the node fails to start.

Transform node
A node that has the transform role. 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.

Coordinating node

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 result set.

Every node is implicitly a coordinating node. This means that a node that has an explicit empty list of roles via node.roles 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

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The 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

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It 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, set:

node.roles: [ master ]

Voting-only master-eligible node

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A 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, include master and voting_only in the list of roles. For example to create a voting-only data node:

node.roles: [ data, master, voting_only ]

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 add the voting_only role then the node will fail to start. Also note that only nodes with the master role can be marked as having the voting_only role.

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 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.roles: [ master, voting_only ]

Data node

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Data 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, set:

node.roles: [ data ]

In a multi-tier deployment architecture, you use specialised data roles to assign data nodes to specific tiers: data_content,data_hot, data_warm, or data_cold. A node can belong to multiple tiers, but a node that has one of the specialised data roles cannot have the generic data role.

Content data node

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Content data nodes accommodate user-created content. They enable operations like CRUD, search and aggregations.

To create a dedicated content node, set:

node.roles: [ data_content ]

Hot data node

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Hot data nodes store time series data as it enters Elasticsearch. The hot tier must be fast for both reads and writes, and requires more hardware resources (such as SSD drives).

To create a dedicated hot node, set:

node.roles: [ data_hot ]

Warm data node

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Warm data nodes store indices that are no longer being regularly updated, but are still being queried. Query volume is usually at a lower frequency than it was while the index was in the hot tier. Less performant hardware can usually be used for nodes in this tier.

To create a dedicated warm node, set:

node.roles: [ data_warm ]

Cold data node

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Cold data nodes store read-only indices that are accessed less frequently. This tier uses less performant hardware and may leverage searchable snapshot indices to minimize the resources required.

To create a dedicated cold node, set:

node.roles: [ data_cold ]

Ingest node

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Ingest 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, set:

node.roles: [ ingest ]

Coordinating only node

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If 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, set:

node.roles: [ ]

Remote-eligible node

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By default, any node in a cluster can act as a cross-cluster client and connect to remote clusters. Once connected, you can search remote clusters using cross-cluster search. You can also sync data between clusters using cross-cluster replication.

node.roles: [ remote_cluster_client ]

Machine learning node

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The 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 the node does not have the ml role, 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.roles: [ ml ]
xpack.ml.enabled: true

The xpack.ml.enabled setting is enabled by default.

Transform node

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Transform nodes run transforms and handle transform API requests. 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:

node.roles: [ transform ]

Changing the role of a node

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Each 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 without the data role will refuse to start if they find any shard data on disk at startup, and nodes without both the master and data roles 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 starting the node without the data or master roles.

  • If you want to repurpose a data node by removing the data role 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 neither the data nor master roles 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

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path.data

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Every 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

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The 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

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More node settings can be found in Configuring Elasticsearch and Important Elasticsearch configuration, including:

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