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This article mainly explains "what are the basic knowledge points of Elasticsearch". The content of the explanation is simple and clear, and it is easy to learn and understand. Please follow the editor's train of thought to study and learn "what are the basic knowledge points of Elasticsearch".

What can es do?

Distributed search and distributed engine

Full-text retrieval, structured retrieval, data analysis

Near real-time analysis of massive data

Applicable scenario

Wikipedia search

News website

Exception search of stack overflow

All of github

Log data analysis ELK

Search for e-commerce websites

On the commodity price monitoring website, the user sets the price threshold of the commodity and sends a notification to the user when it is lower than the threshold.

BI system, data Mining, data Analysis

Search within the station (e-commerce. Recruitment. Portal)

Characteristics

It can be used as a large distributed cluster (hundreds of servers) technology to handle PB-level data, or it can run a single server to serve small companies.

Elasticsearch is not a new technology, but only a combination of full-text retrieval, data services and distributed technology to form es

It is very simple for users to use it right out of the box.

Es is a supplement and extension to traditional servers.

Mainly based on Lucene packaging, hiding its complex api

Core concept

NRT (Near Realtime) is near real-time and can be understood from two aspects: there is a delay from writing data to being queried (about 1 second); the search and analysis of genetic es data can reach the level of seconds.

Cluster, a cluster, contains multiple nodes. Which cluster each node belongs to is determined by a configuration.

The name of Node, node and node is very important. If the name of the node is random by default, the default node will join a cluster named "elasticsearch". If you start a bunch of nodes directly, they will automatically assemble into an elasticsearch cluster. Of course, a node can also form an elasticsearch cluster.

The smallest data unit of Document, document, es. A document can be a piece of merchandise data, user information, etc., usually represented by json data structures

Index: an index that contains document data with a similar data structure, such as customer index, commodity index, order index, which can be divided into clothing index, daily index, hardware index, etc.

Type: type. An index can contain one or more type,type is a logical classification in index, and a document under a type contains the same field, for example, a type under a blog index that can contain user data, a blog type, and a type for user comments.

Shard (primary shard), slicing, single machine can not store a large amount of data, es can split the data in an index into multiple shard, distributed on multiple servers to store, with shard can scale horizontally, store more data, let search and analysis and other operations distributed to multiple servers to execute in parallel, improve system throughput and performance, each shard is a lucene index

Replica (replica shard) backup, replication. Any server may go down or fail, so shard may lose data, so multiple replica copies can be created for each shard. Replica can provide backup services in the event of shard failure to ensure that data is not lost and improve high availability. Multiple replica can also improve the throughput and performance of search operations. When primary shard is indexed, it can be set at once and cannot be modified. The default is 5. Replica shared is modified at any time. Default is 1. By default, each index has 10 shard, 5 parimary shard,5 replica shard respectively, and the smallest high availability configuration is 2 servers, which are active and standby to each other.

Comparison with traditional database

Take mysql as an example

New features of ElasticsearchMysqlfield field Document row Type table Index library after Elasticsearch7

Type was abandoned in version 7. 0 and later. (actually, it can be used, but it is no longer recommended)

Multiple Database can be created in one MySQL instance, and multiple Table can be created in one Database.

The obsolete Type of ES corresponds to the traditional database as follows

ElasticsearchMysqlfield field Document row Index table (Table) es case base (Database) Thank you for your reading, these are the contents of "what are the basic knowledge points of Elasticsearch?" after the study of this article, I believe you have a deeper understanding of what the basic knowledge points of Elasticsearch have, and the specific use needs to be verified in practice. Here is, the editor will push for you more related knowledge points of the article, welcome to follow!

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