Nodes in Elasticsearch

What it is

Simply explained a node is a single server that is part of a cluster. Each node is assigned with one or more roles, which describes the node responsibility and operations – Data nodes stores the data, and participates in the cluster’s indexing and search capabilities, while master nodes are responsible for managing the cluster activities and storing the cluster state, including the metadata.

While it’s 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.

Coordinator Node (aka client node)

Coordinator Node – is a node that does not hold any configured role. It doesn’t hold data, not part of the master eligible group nor execute ingest pipelines. Coordinator node serves incoming search requests and is acting as the query coordinator – running the query and fetch phases, sending requests to every node which holds a shard being queried. The client node also distributes bulk indexing operations and route queries to shards copies based on the nodes responsiveness.

Index in Elasticsearch

What it is

In Elasticsearch, an index (indices in plural) can be thought of as a table inside a database that has a schema and can have one or more shards and replicas. An Elasticsearch index is divided into shards and each shard is an instance of a Lucene index.

Indices are used to store the documents in dedicated data structures corresponding to the data type of fields. For example, text fields are stored inside an inverted index whereas numeric and geo fields are stored inside BKD trees.

Examples

Create Index

The following example is based on Elasticsearch version 5.x onwards. An index with two shards, each having one replica will be created with the name test_index1

PUT /test_index1?pretty
{
    "settings" : {
        "number_of_shards" : 2,
        "number_of_replicas" : 1
    },
    "mappings" : {
        "properties" : {
            "tags" : { "type" : "keyword" },
            "updated_at" : { "type" : "date" }
        }
    }
}

List Indices

All the index names and their basic information can be retrieved using the following command:

GET _cat/indices?v

Index a document

Let’s add a document in the index with below command:

PUT test_index1/_doc/1
{
  "tags": [
    "opster",
    "elasticsearch"
  ],
  "date": "01-01-2020"
}

Query an index

GET test_index1/_search
{
  "query": {
    "match_all": {}
  }
}

Query Multiple Indices

It is possible to search multiple indices with a single request. If it is a raw HTTP request, Index names should be sent in comma-separated format, as shown in the example below, and in the case of a query via a programming language client such as python or Java, index names are to be sent in a list format.

GET test_index1,test_index2/_search

Delete Indices

DELETE test_index1

Common Problems

DELETE /*

action.destructive_requires_name: true
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