Installation under Linux Centos internal Docker Elasticsearch

Based on the introduction Elasticsearch

1. Elasticsearch Overview

• Elasticsearch is a highly scalable open source full-text search and analysis engine, which allows the storage, search and analyze large amounts of data, and this process is near real-time. It is commonly used as the underlying engine technology and to provide power for the complex search functions and requirements. Elasticsearch or a distributed document database, where each field can be indexed, and the data for each field can be searched, ES can scale to hundreds of server storage and handling PB-level data. Can be stored in a very short period of time, search and analyze large amounts of data. As is usually the core of the engine in case of a complex scene search.

• ElasticSearch is highly available and scalable born. System expansion may be accomplished through the purchase of more powerful server or upgraded hardware, called a vertical or upward extension (Vertical Scale / Scaling Up). On the other hand, adding more servers to complete the system expansion, expand or extend outwardly called horizontal (Horizontal Scale / Scaling Out).

2. Elasticsearch What you can do

• An online mall system, users need to search for items on the mall.
  Here you can store all product information and inventory information es, users only need to enter the "air conditioning" you can search for his need to search the goods.
• A running system needs to collect logs, use these logs to analyze, trend mining system in order to gain business in the future.
  You can collect a logstash (a product of elk, elasticsearch / logstash / kibana), convert your logs and stores them in the es. Once the data reaches es in which you can search for it, running tap polymerization operation functions like any information of interest.
• If you want to have a lot of data-based (millions or even billions of data) rapid investigation, analysis and visualization of results you want to analyze demand. Es can be used to store your data, build custom graphical visualization, reporting with kibana, provide scientific data basis for business decisions.

start installation

1. Here we install the latest version elasticsearch

拉取elasticsearch最新镜像
docker pull docker.elastic.co/elasticsearch/elasticsearch:7.5.1

2. Check whether the installation is successful

docker  images   查看docker内部镜像 

Installed as successfully

3. Start elasticsearch, and see whether a successful start

//启动elasticsearch
docker run -d --name es -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" docker.elastic.co/elasticsearch/elasticsearch:7.5.1
//查看docker内部启动的容器
 docker ps

Start Parameter Description

 -d  后台启动
 --name  指定启动容器的名称
 -p 9200 是ES节点与外部通讯使用的端口。它是http协议的RESTful接口（各种CRUD操作都是走的该端口,如查询：http://localhost:9200/user/_search）。
 -p 9300是ES节点之间通讯使用的端口。它是tcp通讯端口，集群间和TCPclient都走的它。（java程序中使用ES时，在配置文件中要配置该端口）
 -e 设置环境变量

Successful results as shown elasticsearch start

4. native access test

// 使用curl命令
curl 127.0.0.1:9200

Figure testing started successfully

5. external host to access the test
open the browser, enter the server's id: 9200, the following figure is successful

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