Shulou(Shulou.com)06/02 Report--

This article to share with you is about the in-depth analysis of ElasticSearch cluster principle, Xiaobian think quite practical, so share to everyone to learn, I hope you can read this article after some harvest, not much to say, follow Xiaobian to see it.

ElasticSearch's main thrust is always available and scalable on demand. Scalability can be achieved by purchasing more powerful servers (vertical or vertical) or by increasing the number of servers (horizontal or horizontal).

While ElasticSearch can benefit from more powerful hardware, vertical scaling has its limits. True scalability comes from horizontal scale-adding more nodes to the cluster and spreading load stress and stability across them.

For most databases, significant changes to the application are usually required to take advantage of the new resources that are being scaled up horizontally. ElastiSearch, by contrast, is inherently distributed and knows how to improve scalability and availability by managing multiple nodes. This also means that your app doesn't have to worry about it.

A running ElasticSearch instance is called a node, and a cluster is made up of one or more nodes with the same cluster.name configuration that share the burden of data and load. When nodes are added to or removed from the cluster, the cluster redistributes all data evenly.

When a node is elected master, it is responsible for managing all cluster-wide changes, such as adding or deleting indexes, or adding or deleting nodes. The master node does not need to involve document-level changes and searches, so when the cluster has only one master node, it does not become a bottleneck even if traffic increases. Any node can be a master node. Our example cluster has only one node, so it also becomes the master node.

As users, we can send requests to any node in the cluster, including the master node. Each node knows where any document is located and is able to forward our requests directly to the node storing the document we want. No matter which node we send the request to, it is responsible for collecting data back from each node that contains the documents we need and returning the final result to the client. ElasticSearch manages all of this transparently.

Cluster Health:

ElasticSearch cluster monitoring information contains a lot of statistics, the most important of which is cluster health, which is displayed as green, yellow or red in the status field.

In an empty cluster that contains no indexes, it will have a return content similar to the following:

{

"cluster_name": "elasticsearch",

"status": "green",

"timed_out": false,

"number_of_nodes": 1,

"number_of_data_nodes": 1,

"active_primary_shards": 0,

"active_shards": 0,

"relocating_shards": 0,

"initializing_shards": 0,

"unassigned_shards": 0

}

green：

All primary and replica shards are functioning properly.

yellow：

All primary shards are up and running, but not all replica shards are up and running.

red：

A primary shard failed to function properly.

The above is an in-depth analysis of the principle of ElasticSearch cluster, Xiaobian believes that some knowledge points may be seen or used in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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