Nodeedit

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 and between nodes and the Java TransportClient; the HTTP layer is used only by external REST clients.

All nodes know about all the other nodes in the cluster and can forward client requests to the appropriate node. Besides that, each node serves one or more purpose:

Master-eligible node
A node that has node.master set to true (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 to true (default). Data nodes hold data and perform data related operations such as CRUD, search, and aggregations.
Client node
A client node has both node.master and node.data set to false. It can neither hold data nor become the master node. It behaves as a “smart router” and is used to forward cluster-level requests to the master node and data-related requests (such as search) to the appropriate data nodes.
Tribe node
A tribe node, configured via the tribe.* settings, is a special type of client node that can connect to multiple clusters and perform search and other operations across all connected clusters.

By default a node is both a master-eligible node and a data node. This is very convenient for small clusters but, as the cluster grows, it becomes important to consider separating dedicated master-eligible nodes from dedicated data nodes.

Note

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 resultset.

This means that a client node needs to have enough memory and CPU in order to deal with the gather phase.

Master Eligible Nodeedit

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 (all nodes by default) may be elected to become the master node by the master election process.

Indexing and searching your data is CPU-, memory-, and I/O-intensive work which can put pressure on a node’s resources. To ensure that your master node is stable and not under pressure, it is a good idea in a bigger cluster to split the roles between dedicated master-eligible nodes and dedicated data nodes.

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. It is important for the stability of the cluster that master-eligible nodes do as little work as possible.

To create a standalone master-eligible node, set:

node.master: true 
node.data: false 

The node.master role is enabled by default.

Disable the node.data role (enabled by default).

Avoiding split brain with minimum_master_nodesedit

To prevent data loss, it is vital to configure the discovery.zen.minimum_master_nodes setting (which defaults to 1) so that each master-eligible node knows the minimum number of master-eligible nodes that must be visible in order to form a cluster.

To explain, imagine that you have a cluster consisting of two master-eligible nodes. A network failure breaks communication between these two nodes. Each node sees one master-eligible node… itself. With minimum_master_nodes set to the default of 1, this is sufficient to form a cluster. Each node elects itself as the new master (thinking that the other master-eligible node has died) and the result is two clusters, or a split brain. These two nodes will never rejoin until one node is restarted. Any data that has been written to the restarted node will be lost.

Now imagine that you have a cluster with three master-eligible nodes, and minimum_master_nodes set to 2. If a network split separates one node from the other two nodes, the side with one node cannot see enough master-eligible nodes and will realise that it cannot elect itself as master. The side with two nodes will elect a new master (if needed) and continue functioning correctly. As soon as the network split is resolved, the single node will rejoin the cluster and start serving requests again.

This setting should be set to a quorum of master-eligible nodes:

(master_eligible_nodes / 2) + 1

In other words, if there are three master-eligible nodes, then minimum master nodes should be set to (3 / 2) + 1 or 2:

discovery.zen.minimum_master_nodes: 2 

Defaults to 1.

This setting can also be changed dynamically on a live cluster with the cluster update settings API:

PUT _cluster/settings
{
  "transient": {
    "discovery.zen.minimum_master_nodes": 2
  }
}
Tip

An advantage of splitting the master and data roles between dedicated nodes is that you can have just three master-eligible nodes and set minimum_master_nodes to 2. You never have to change this setting, no matter how many dedicated data nodes you add to the cluster.

Data Nodeedit

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.master: false 
node.data: true 

Disable the node.master role (enabled by default).

The node.data role is enabled by default.

Client Nodeedit

If you take away the ability to be able to handle master duties and take away the ability to hold data, then you are left with a client node that can only route requests, handle the search reduce phase, and distribute bulk indexing. Essentially, client nodes behave as smart load balancers.

Standalone client nodes can benefit large clusters by offloading the coordinating node role from data and master-eligible nodes. Client nodes 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).

Warning

Adding too many client 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 client nodes should not be overstated — data nodes can happily serve the same purpose as client nodes.

To create a deciated client node, set:

node.master: false 
node.data: false 

Disable the node.master role (enabled by default).

Disable the node.data role (enabled by default).

Node data path settingsedit

path.dataedit

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 --path.data /var/elasticsearch/data
Tip

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_nodesedit

The data path can be shared by multiple nodes, even by nodes from different clusters. This is very useful for testing failover and different configurations on your development machine. In production, however, it is recommended to run only one node of Elasticsearch per server.

To prevent more than one node from sharing the same data path, add this setting to the elasticsearch.yml config file:

node.max_local_storage_nodes: 1
Warning

Never run different node types (i.e. master, data, client) from the same data directory. This can lead to unexpected data loss.

Other node settingsedit

More node settings can be found in Modules. Of particular note are the cluster.name, the node.name and the network settings.

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