Elasticsearch Nodes

By Opster Team

Updated: Jan 28, 2024

| 1 min read

Overview

To put it simply, a node is a single server that is part of a cluster. Each node is assigned one or more roles, which describe the node’s responsibility and operations. Data nodes store the data, and participate in the cluster’s indexing and search capabilities, while master nodes are responsible for managing the cluster’s activities and storing the cluster state, including the metadata.

While it is possible to run several node instances of Elasticsearch on the same hardware, it’s considered a best practice to limit a server to a single running instance of Elasticsearch.

Nodes connect to each other and form a cluster by using a discovery method. 

Roles

Master node

Master nodes are in charge of cluster-wide settings and changes – deleting or creating indices and fields, adding or removing nodes and allocating shards to nodes. Each cluster has a single master node that is elected from the master eligible nodes using a distributed consensus algorithm and is reelected if the current master node fails.

Coordinating (client) node

There is some confusion in the use of coordinating node terminology. Client nodes were removed from Elasticsearch after version 2.4 and became coordinating nodes.

Coordinating nodes are nodes that do not hold any configured role. They don’t hold data and are not part of the master eligible group nor execute ingest pipelines. Coordinating nodes serve incoming search requests and act as the query coordinator running query and fetch phases, sending requests to every node that holds a shard being queried. The coordinating node also distributes bulk indexing operations and route queries to shards based on the node’s responsiveness.

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Related log errors to this ES concept


Starting node shutdown sequence for ML
There were node failures waiting for tasks
Caught node failures waiting for tasks to be unassigned
Error detecting load for node
Upgrade task reassigned to another node while failed
Close request for job while it was vacating the node
Aborted upgrading snapshot %s for job %s as node is dying
Ignoring node %s as no load could be detected
Node closed while execution action for request
Failed to gather node load limits failure Returning no scale
Couldn t schedule ML memory update - node might be shutting down
JobId not refreshing anomaly detector memory as node is shutting down

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