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This article shows you what the functions and features of ElasticSearch are, the content is concise and easy to understand, it can definitely brighten your eyes. I hope you can get something through the detailed introduction of this article.

1. Automatically maintain resumes with indexes of data distributed to multiple nodes, as well as execution of search requests distributed to multiple nodes

two。 Automatically maintain redundant copies of data, ensuring that some machines are down and will not lose any data

3. Encapsulate more advanced functions to provide more advanced support for rapid development of applications

The function of Elaticsearch

1. Distributed search engine and data analysis engine search: Baidu, site site search, OA data analysis: e-commerce site, distributed among the top sellers of toothpaste in the last 7 days

two。 Full-text search Data analysis full-text search: search for commodity names containing toothpaste select * from products where product_name like "% toothpaste%" structured search: search for commodities classified as daily chemical products select * from peoducts where category_id=' daily chemical products partial search, automatic completion, search error correction, search recommendation data analysis: analyze the number of commodities under each commodity category select categoey_id,count (*) from products group by category_id

3. Real-time distributed processing of massive data: es can automatically distribute massive data to multiple servers to store and retrieve massive data: after distributed, a large number of servers can be used to store and retrieve data, so it is natural to achieve near real-time processing of massive data: it takes 1 hour to retrieve data (this is not called near real-time, offline batch processing, batch-peocessing) Searching and analyzing data at the second level is the opposite of distributed / massive data: lucence stand-alone applications can only be used on a single service and can only handle the amount of data that a single server can handle.

Working with scen

1.github

2.Stack Overflow

3. E-commerce search for goods

4. Log data Analysis ELK Technology elasticsearch+logstash+kibana complex data Analysis

5. Commodity price monitoring website

6.BI business intelligence, Business Intelligence data mining analyzes the trend of user consumption in a certain area in the last three years, generates data reports, es for data analysis and mining, kibanna for data visualization

Domestic: on-site search: e-commerce, recruitment, portal

It system search, OA,crm,Erp data Analysis: a popular usage scenario at present

Characteristics

1. It can be used as a large distributed cluster technology to deal with PB-level data to serve large companies, or it can be used on a stand-alone machine to serve small companies.

2.es is not a new technology. It mainly combines full-text retrieval, data analysis and distributed technology to form es lucene full-text retrieval, distributed database mycat.

Core concept

1.Near Realtime (NRT): near real-time, from writing data to data can be searched, there is a small delay of about 1 second 2.Cluster: cluster, including multiple nodes 3.Node: node 4.Dcoument&field: document, usually represented by json data structure, each index under the type, can store multiple document. There are multiple field in a document, and each field is a data field 5.index: index, which contains a pile of document data with similar structure, such as customer index, commodity classification index, order index commodity index: it stores all the commodity data, commodity document 6.Type types, and one or more type type in each index. There are many categories of goods.

7.shard: a single machine cannot store a large amount of data. Es can split the data in an index into multiple shard and distribute them on abortion servers. With shard, you can scale out and store more data, allowing search and analysis and other operations to be performed on multiple servers to improve throughput and performance. Each shard is a lucene index 8.replica: the server fails or goes down, so the shard may be lost, multiple replica is created per shard to provide backup services in the event of a shard failure, and multiple splica can improve the throughput of search operations. Primaryshard (set at once and cannot be modified by default), replica shard (the number can be modified at any time, default is 1), default is 10 shard,5 and primaryshard,5 replia shard per index, the minimum high available configuration is two servers.

Shard and replia are partially stored on the node

ElasticSearch core concepts vs database core concepts

Elasticsearch database document row Type table index database

How to quickly understand the health status of the cluster? Green 、 yellow 、 red

Green: the primary shard and replica shard of each index are active state yellow: the primary shard of each index is active state, but some replica shard is not active state and is not available red: not all index peimary shard is active state, some indexes have lost data

The reason for being in the case of yellow is that because it is a notebook, an es process is started, which is equivalent to only one node. Now there is an index in es, that is, the index built in by kibanna itself. Since five primary shard and relica shard are assigned to each index by default, and primary shard and replica shard can no longer be on the same machine (for fault tolerance), only one primary shard is assigned and started, but a replica shard does not have a second machine to boot.

The above content is what are the functions and characteristics of ElasticSearch? have you learned any knowledge or skills? If you want to learn more skills or enrich your knowledge reserve, you are welcome to follow the industry information channel.

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