What is the hot and warm architecture of Elasticsearch cluster

In this issue, the editor will bring you about the hot and warm structure of Elasticsearch cluster. The article is rich in content and analyzed and described from a professional point of view. I hope you can get something after reading this article.

Subject to Elasticsearch 7.9.2.

What is the hot-warm architecture?

The data nodes of ES cluster are divided into two categories, which are used to store frequently accessed and infrequently accessed data respectively.

Hot node hardware configuration is high (CPU, network, memory are good, and usually equipped with SSD), warm node hardware configuration is low (usually equipped with mechanical disk).

The purpose of the hot-warm architecture

Save money.

Applicable scenario

There are few data update operations, and the amount of data is relatively large (otherwise the money saved is not enough to build complex clusters). Typical examples are monitoring data and log data.

How to configure

Tagging the node:

Configure the node.attr field in the yml file (this is a KV group whose KV value can be written at will), such as node.attr.t_type=hot.

When you create an index, you can specify the location of the data slice of the index:

{"setting": {/ / other fields "index.routing.allocation.require.t_type": "hot"}} the above is what the hot and warm architecture of the Elasticsearch cluster is shared by the editor. If you happen to have similar doubts, please refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.