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

In this issue, Xiaobian will bring you the basic concept of ES. The article is rich in content and analyzes and narrates it from a professional perspective. After reading this article, I hope you can gain something.

(1) Near Realtime (NRT): Near real-time, two meanings, there is a small delay (about 1 second) from writing data to data can be searched; search and analysis based on es can reach seconds

(2) Cluster: Cluster, which contains multiple nodes. Which cluster each node belongs to is determined by a configuration (cluster name, default is elasticsearch). For small and medium-sized applications, it is normal to have one node at the beginning of a cluster.

（3）Node： Node, a node in a cluster. The node also has a name (randomly assigned by default). The node name is very important (when performing operation and maintenance management operations). The default node will join a cluster named "elasticsearch." If a bunch of nodes are started directly, they will automatically form an elasticsearch cluster. Of course, a node can also form an elasticsearch cluster.

(4) Document&field: document, the smallest data unit in es, a document can be a customer data, a commodity classification data, an order data, usually represented by JSON data structure, each index type, can store multiple documents. There are multiple fields in a document, and each field is a data field.

(5) Index: index, containing a bunch of document data with similar structure, such as a customer index, commodity classification index, order index, index has a name. An index contains many documents, and an index represents a class of similar or identical documents. For example, create a product index, commodity index, which may store all commodity data, all commodity documents.

(6) Type: Each index can have one or more types, type is a logical data classification in the index, documents under a type have the same field, such as blog system, there is an index, you can define user data type, blog data type, comment data type.

(7) Shard: A single machine cannot store a large amount of data. ES can divide the data in an index into multiple shards and store them on multiple servers. With shard, you can scale out, store more data, distribute search and analysis across multiple servers, and improve throughput and performance. Each shard is a lucene index.

(8) Replica: Any server can fail or go down at any time, and the shard can be lost, so multiple replicas can be created for each shard. Replicas can provide backup service in case of shard failure, ensuring that data is not lost, and multiple replicas can also improve the throughput and performance of search operations. primary shard (set once when establishing index, cannot be modified, default 5), replica shard (modify quantity at any time, default 1), default 10 shards per index, 5 primary shards, 5 replica shards, minimum high availability configuration, 2 servers.

The above is what the basic concept of ES shared by Xiaobian is. If there is a similar doubt, please refer to the above analysis for understanding. If you want to know more about it, please pay attention to the industry information channel.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.