docker搭建es集群實現(xiàn)過程詳解

更新時間：2023年01月31日 15:02:29 作者：程序員皮卡秋

這篇文章主要為大家介紹了docker搭建es集群實現(xiàn)過程詳解，有需要的朋友可以借鑒參考下，希望能夠有所幫助，祝大家多多進步，早日升職加薪

前言

該系列默認開啟Nacos 服務,還不會搭建的小伙伴可以參考往期文章~

本節(jié)重點是給大家介紹利用docker來搭建Es集群,廢話不多說直接開整吧~

什么是es

同樣的，在學習之前，先了解一下這玩意到底是個啥?

es這個名詞或許大家都聽過，它的全稱是Elasticsearch,它是一個分布式文檔儲存中間件，它不會將信息儲存為列數(shù)據(jù)行，而是儲存已序列化為 JSON 文檔的復雜數(shù)據(jù)結(jié)構(gòu)。當你在一個集群中有多個節(jié)點時，儲存的文檔分布在整個集群里面，并且立刻可以從任意節(jié)點去訪問。

當文檔被儲存時，它將建立索引并且近實時（1s）被搜索。 Elasticsearch 使用一種被稱為倒排索引的數(shù)據(jù)結(jié)構(gòu)，該結(jié)構(gòu)支持快速全文搜索。在倒排索引里列出了所有文檔中出現(xiàn)的每一個唯一單詞并分別標識了每個單詞在哪一個文檔中。有時候面試官會問，es為什么這么快?這也是一個小的知識點。

通過上面簡單的介紹，我們大體可以知道，它是用來做數(shù)據(jù)檢索的，而且速度特別快。

不知道小伙伴們有沒有遇到過這樣一個問題，比方說我們在用sql查商品庫表的時候,想要通過某個關鍵詞來匹配相應的商品，當數(shù)據(jù)量很小的時候ok,但是隨著商品數(shù)據(jù)的不斷導入，后期的數(shù)據(jù)量越來越大，而且都是關聯(lián)著好幾張表，這時候我們用sql去查詢我們想要的數(shù)據(jù)的時候，會顯得特別吃力，這種是相當危險的操作，因為可能會把整張表鎖死，導致我們的系統(tǒng)出現(xiàn)故障，如果其它系統(tǒng)也使用這個庫，那么也會受到影響。所以這時候，我們就需要借助es這種中間件來幫我們處理這種需求，系統(tǒng)的性能也會有顯著的提升，當然，維護上也會增加一些難度，當然也不是啥都上es的。其實我們也可以使用其它的比如mongo，如何選取，取決于系統(tǒng)架構(gòu)和實際的業(yè)務場景。

使用docker搭建es集群

為了大家快速的體驗到es，這里推薦大家使用docker來搭建，因為它比較方便。但是生產(chǎn)中，如果你對docker不是很熟悉，維護會稍微有點麻煩，那么建議你還是到官網(wǎng)去下載具體的安裝包，本節(jié)默認大家都已經(jīng)安裝好了docker。如果你還不知道docker是啥也沒關系，這個后邊我會專門給大家講講，本節(jié)跟著我敲就可以了。

docker的安裝非常簡單，官網(wǎng)都有具體的平臺的安裝包,win和mac都有，無腦安裝就好了。win11安裝可能會遇到wsl的問題，需要開啟linux子系統(tǒng)，如果啟動錯誤，直接百度錯誤就好了，已經(jīng)有人踩過坑了。

下面，我們進入正題,首先啟動好docker，本節(jié)帶大家安裝的是7.6.2的版本，這個版本相對好一些，控制臺的功能也都很完善。

執(zhí)行已下命令獲取官方鏡像，打開cmd/mac終端：

# es鏡像
docker pull docker.elastic.co/elasticsearch/elasticsearch:7.6.2
# kibana鏡像
docker pull docker.elastic.co/kibana/kibana:7.6.2

kibana它是一個可視化的平臺，我們查看數(shù)據(jù)就是通過它，es只是用作數(shù)據(jù)引擎，市面上也有一些第三方的工具，但是官方的這個已經(jīng)非常完善了，界面也很美觀。

緊接著，進入指定安裝目錄,比方說當前目錄叫es,終端進入這個目錄后執(zhí)行一下命令:

# kibana數(shù)據(jù)掛載的目錄
mkdir data/kibana
# 三個節(jié)點數(shù)據(jù)掛載的目錄
mkdir data/node1
mkdir data/node2
mkdir data/node3

這一步主要是創(chuàng)建相關的目錄，因為后邊docker的數(shù)據(jù)卷會映射到該目錄，這樣做的目的是防止容器意外銷毀后的數(shù)據(jù)丟失。這里為什么是三個節(jié)點,因為es集群至少需要三個節(jié)點，這是跟它的內(nèi)部機制有關，為了防止腦裂現(xiàn)象，這里就不給大家過多展開了

接下來進入data/kibana目錄,新建kibana.yml,這個文件是它的配置文件，后邊我們會把它映射到docker容器內(nèi)部

#
## ** THIS IS AN AUTO-GENERATED FILE **
##
#  
#  # Default Kibana configuration for docker target
server.name: kibana
server.host: "0"
elasticsearch.hosts: [ "http://es01:9200","http://es02:9200","http://es03:9200" ]
xpack.monitoring.ui.container.elasticsearch.enabled: true
i18n.locale: zh-CN

elasticsearch.hosts指的是三個es節(jié)點,會和這些節(jié)點進行通信

進入node1，同樣新建配置文件elasticsearch.yml

# ======================== Elasticsearch Configuration =========================
#
# NOTE: Elasticsearch comes with reasonable defaults for most settings.
#       Before you set out to tweak and tune the configuration, make sure you
#       understand what are you trying to accomplish and the consequences.
#
# The primary way of configuring a node is via this file. This template lists
# the most important settings you may want to configure for a production cluster.
#
# Please consult the documentation for further information on configuration options:
# https://www.elastic.co/guide/en/elasticsearch/reference/index.html
#
# ---------------------------------- Cluster -----------------------------------
#
# Use a descriptive name for your cluster:
#
 cluster.name: es-cluster
#
# ------------------------------------ Node ------------------------------------
#
# Use a descriptive name for the node:
#
 node.name: es01
#
# Add custom attributes to the node:
#
#node.attr.rack: r1
#
# ----------------------------------- Paths ------------------------------------
#
# Path to directory where to store the data (separate multiple locations by comma):
#
#path.data: /path/to/data
#
# Path to log files:
#
#path.logs: /path/to/logs
#
# ----------------------------------- Memory -----------------------------------
#
# Lock the memory on startup:
#
#bootstrap.memory_lock: true
#
# Make sure that the heap size is set to about half the memory available
# on the system and that the owner of the process is allowed to use this
# limit.
#
# Elasticsearch performs poorly when the system is swapping the memory.
#
# ---------------------------------- Network -----------------------------------
#
# Set the bind address to a specific IP (IPv4 or IPv6):
#
 network.host: 0.0.0.0
#
# Set a custom port for HTTP:
#
 http.port: 9200
#
# For more information, consult the network module documentation.
#
# --------------------------------- Discovery ----------------------------------
#
# Pass an initial list of hosts to perform discovery when this node is started:
# The default list of hosts is ["127.0.0.1", "[::1]"]
#
 discovery.seed_hosts: ["es01","es02","es03"]
#
# Bootstrap the cluster using an initial set of master-eligible nodes:
#
 cluster.initial_master_nodes: ["es01","es02","es03"]
# bootstrap.memory_lock: true
#
# For more information, consult the discovery and cluster formation module documentation.
#
# ---------------------------------- Gateway -----------------------------------
#
# Block initial recovery after a full cluster restart until N nodes are started:
#
#gateway.recover_after_nodes: 3
#
# For more information, consult the gateway module documentation.
#
# ---------------------------------- Various -----------------------------------
#
# Require explicit names when deleting indices:
#
#action.destructive_requires_name: true
 http.cors.enabled: true
 http.cors.allow-origin: '*'
 http.cors.allow-headers: Authorization,X-Requested-With,Content-Length,Content-Type
 node.master: true

我們把node1作為主節(jié)點,也就是老大，node.master: true可以配置。為了使它支持中文分詞,我們給它安裝一下插件, 到倉庫下載指定版本的插件https://github.com/medcl/elasticsearch-analysis-ik/releases,然后我們解壓到node1根目錄，然后重新命名為ik目錄,然后再新建一個Dockerfile用來重構(gòu)```es````鏡像，沒錯，后邊我們就使用我們重構(gòu)好的鏡像，這樣就自動安裝好了插件

Dockerfile文件內(nèi)容

FROM docker.elastic.co/elasticsearch/elasticsearch:7.6.2
COPY --chown=elasticsearch:elasticsearch elasticsearch.yml /usr/share/elasticsearch/config/
ADD ik /usr/share/elasticsearch/plugins/ik
ADD ik/config /data/erms/es/node1/ik/config

下面我們進入node2目錄，這個目錄只需要放配置文件就好了

# ======================== Elasticsearch Configuration =========================
#
# NOTE: Elasticsearch comes with reasonable defaults for most settings.
#       Before you set out to tweak and tune the configuration, make sure you
#       understand what are you trying to accomplish and the consequences.
#
# The primary way of configuring a node is via this file. This template lists
# the most important settings you may want to configure for a production cluster.
#
# Please consult the documentation for further information on configuration options:
# https://www.elastic.co/guide/en/elasticsearch/reference/index.html
#
# ---------------------------------- Cluster -----------------------------------
#
# Use a descriptive name for your cluster:
#
 cluster.name: es-cluster
#
# ------------------------------------ Node ------------------------------------
#
# Use a descriptive name for the node:
#
 node.name: es02
#
# Add custom attributes to the node:
#
#node.attr.rack: r1
#
# ----------------------------------- Paths ------------------------------------
#
# Path to directory where to store the data (separate multiple locations by comma):
#
#path.data: /path/to/data
#
# Path to log files:
#
#path.logs: /path/to/logs
#
# ----------------------------------- Memory -----------------------------------
#
# Lock the memory on startup:
#
#bootstrap.memory_lock: true
#
# Make sure that the heap size is set to about half the memory available
# on the system and that the owner of the process is allowed to use this
# limit.
#
# Elasticsearch performs poorly when the system is swapping the memory.
#
# ---------------------------------- Network -----------------------------------
#
# Set the bind address to a specific IP (IPv4 or IPv6):
#
 network.host: 0.0.0.0
#
# Set a custom port for HTTP:
#
 http.port: 9200
#
# For more information, consult the network module documentation.
#
# --------------------------------- Discovery ----------------------------------
#
# Pass an initial list of hosts to perform discovery when this node is started:
# The default list of hosts is ["127.0.0.1", "[::1]"]
#
 discovery.seed_hosts: ["es01","es02","es03"]
#
# Bootstrap the cluster using an initial set of master-eligible nodes:
#
 cluster.initial_master_nodes: ["es01","es02","es03"]
# bootstrap.memory_lock: true
#
# For more information, consult the discovery and cluster formation module documentation.
#
# ---------------------------------- Gateway -----------------------------------
#
# Block initial recovery after a full cluster restart until N nodes are started:
#
#gateway.recover_after_nodes: 3
#
# For more information, consult the gateway module documentation.
#
# ---------------------------------- Various -----------------------------------
#
# Require explicit names when deleting indices:
#
#action.destructive_requires_name: true
 http.cors.enabled: true
 http.cors.allow-origin: '*'
 http.cors.allow-headers: Authorization,X-Requested-With,Content-Length,Content-Type
 node.data: true

這里我們指定為數(shù)據(jù)節(jié)點node.data: true用來做副本

同樣的node3

# ======================== Elasticsearch Configuration =========================
#
# NOTE: Elasticsearch comes with reasonable defaults for most settings.
#       Before you set out to tweak and tune the configuration, make sure you
#       understand what are you trying to accomplish and the consequences.
#
# The primary way of configuring a node is via this file. This template lists
# the most important settings you may want to configure for a production cluster.
#
# Please consult the documentation for further information on configuration options:
# https://www.elastic.co/guide/en/elasticsearch/reference/index.html
#
# ---------------------------------- Cluster -----------------------------------
#
# Use a descriptive name for your cluster:
#
 cluster.name: es-cluster
#
# ------------------------------------ Node ------------------------------------
#
# Use a descriptive name for the node:
#
 node.name: es03
#
# Add custom attributes to the node:
#
#node.attr.rack: r1
#
# ----------------------------------- Paths ------------------------------------
#
# Path to directory where to store the data (separate multiple locations by comma):
#
#path.data: /path/to/data
#
# Path to log files:
#
#path.logs: /path/to/logs
#
# ----------------------------------- Memory -----------------------------------
#
# Lock the memory on startup:
#
#bootstrap.memory_lock: true
#
# Make sure that the heap size is set to about half the memory available
# on the system and that the owner of the process is allowed to use this
# limit.
#
# Elasticsearch performs poorly when the system is swapping the memory.
#
# ---------------------------------- Network -----------------------------------
#
# Set the bind address to a specific IP (IPv4 or IPv6):
#
 network.host: 0.0.0.0
#
# Set a custom port for HTTP:
#
 http.port: 9200
#
# For more information, consult the network module documentation.
#
# --------------------------------- Discovery ----------------------------------
#
# Pass an initial list of hosts to perform discovery when this node is started:
# The default list of hosts is ["127.0.0.1", "[::1]"]
#
 discovery.seed_hosts: ["es01","es02","es03"]
#
# Bootstrap the cluster using an initial set of master-eligible nodes:
#
 cluster.initial_master_nodes: ["es01","es02","es03"]
# bootstrap.memory_lock: true
#
# For more information, consult the discovery and cluster formation module documentation.
#
# ---------------------------------- Gateway -----------------------------------
#
# Block initial recovery after a full cluster restart until N nodes are started:
#
#gateway.recover_after_nodes: 3
#
# For more information, consult the gateway module documentation.
#
# ---------------------------------- Various -----------------------------------
#
# Require explicit names when deleting indices:
#
#action.destructive_requires_name: true
 http.cors.enabled: true
 http.cors.allow-origin: '*'
 http.cors.allow-headers: Authorization,X-Requested-With,Content-Length,Content-Type
 node.data: true

然后我們回到根目錄(es),新建一個docker-compose.yaml,我們使用docker-compose來編排我們的容器，默認安裝好docker desktop就自動給我們安裝好了docker-compose

version: '3'
services:
  es01:
    image: ${image}
    container_name: es01
    environment:
      - discovery.seed_hosts=es02,es03
      - cluster.initial_master_nodes=es01,es02,es03
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - ./data/node1/data:/usr/share/elasticsearch/data
      - ./data/node1/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml
      - ./data/node1/plugins:/usr/share/elasticsearch/plugins
    ports:
      - 9200:9200
    networks:
      - elastic
  es02:
    image: ${image}
    container_name: es02
    environment:
      - discovery.seed_hosts=es01,es03
      - cluster.initial_master_nodes=es01,es02,es03
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - ./data/node2/data:/usr/share/elasticsearch/data
      - ./data/node2/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml
      - ./data/node2/plugins:/usr/share/elasticsearch/plugins
    ports:
      - 9201:9201
    networks:
      - elastic
  es03:
    image: ${image}
    container_name: es03
    environment:
      - discovery.seed_hosts=es01,es02
      - cluster.initial_master_nodes=es01,es02,es03
      - "ES_JAVA_OPTS=-Xms512m -Xmx512m"
    ulimits:
      memlock:
        soft: -1
        hard: -1
    volumes:
      - ./data/node3/data:/usr/share/elasticsearch/data
      - ./data/node3/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml
      - ./data/node3/plugins:/usr/share/elasticsearch/plugins
    ports:
      - 9202:9202
    networks:
      - elastic
  kibana:
    image: ${image_kibana}
    container_name: kibana
    depends_on:
      - es01
    environment:
      ELASTICSEARCH_URL: http://es01:9200
      ELASTICSEARCH_HOSTS: http://es01:9200
    volumes:
      - ./data/kibana/kibana.yml:/usr/share/kibana/config/kibana.yml
    networks:
      - elastic
    ports:
      - 5601:5601
networks:
  elastic:
    driver: bridge

這個文件有點長，不懂沒關系，跟著配就完了。${image}是一個占位符，所以我們還需要指定環(huán)境變量,然后新建一個.env

image=m/es
image_kibana=docker.elastic.co/kibana/kibana:7.6.2

m/es這個是我們重構(gòu)后的鏡像名稱，下面我們就來重構(gòu)鏡像

進入data/node1執(zhí)行

docker build -t m/es .

執(zhí)行完成后，到根目錄執(zhí)行啟動命令:

docker-compose up -d

如果你想看實時日志，把-d去掉，這個是后臺運行，初次啟動，可能要花費一些時間。

啟動成功后，我們可以訪問一些es1的節(jié)點localhost:9200,可以查看節(jié)點的信息,如果顯示正常，說明已經(jīng)搭建成功了，下面我們直接進入kibana控制臺

http://localhost:5601/,初次進入會讓你設置控制臺的密碼

我們進入控制臺,執(zhí)行一下，有如下輸出，至此我們就搭建成功了

如果你想卸載它們，執(zhí)行docker-compose down就可以了，畢竟這幾個家伙特別的吃資源。這里提醒一下大家，如果想嘗試到服務器安裝，建議新開一個機器，不要直接在生產(chǎn)環(huán)境里安裝，因為挺吃硬件資源的，會容易出問題

以上就是docker搭建es集群實現(xiàn)過程詳解的詳細內(nèi)容，更多關于docker搭建es集群的資料請關注腳本之家其它相關文章！

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