本文將使用Docker 快速部署Elasticsearch 集羣，使用容器模擬多個實例。
最新的6.x版本似乎不能通過 -Epath.config 參數去指定特定的配置文件位置，文檔說明：
For the archive distributions, the config directory location defaults to$ES_HOME/config. The location of the >config directorycan be changedvia theES_PATH_CONFenvironment variable as follows:ES_PATH_CONF=/path/to/my/config ./bin/elasticsearch
Alternatively, you can export the ES_PATH_CONF environment variable via the command line or via your shell profile.
即交給環境變量 ES_PATH_CONF 決定加載路徑了，官方文檔，不使用容器部署單機多實例的同學多多注意。
準備工作
安裝 docker & docker-compose
這裏推進使用 daocloud 做個加速安裝：
#docker
curl -sSL https://get.daocloud.io/docker | sh
#docker-compose
curl -L \
https://get.daocloud.io/docker/compose/releases/download/1.23.2/docker-compose-`uname -s`-`uname -m` \
> /usr/local/bin/docker-compose
chmod +x /usr/local/bin/docker-compose
#查看安裝結果
docker-compose -v數據目錄
#創建數據/日誌目錄 這裏我們部署3個節點
mkdir /opt/elasticsearch/data/{node0,nod1,node2} -p
mkdir /opt/elasticsearch/logs/{node0,nod1,node2} -p
cd /opt/elasticsearch
#權限我也很懵逼啦 給了 privileged 也不行 索性0777好了
chmod 0777 data/* -R && chmod 0777 logs/* -R
#防止JVM報錯
echo vm.max_map_count=262144 >> /etc/sysctl.conf
sysctl -pdocker-compse創建服務
創建編排文件
vim docker-compose.yml
參數說明
- cluster.name=elasticsearch-cluster
集羣名稱
- node.name=node0- node.master=true- node.data=true
節點名稱、是否可作爲主節點、是否存儲數據
- bootstrap.memory_lock=true
鎖定進程的物理內存地址避免交換（swapped）來提高性能
- http.cors.enabled=true- http.cors.allow-origin=*
開啓cors以便使用Head插件
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
JVM內存大小配置
- "discovery.zen.ping.unicast.hosts=elasticsearch_n0,elasticsearch_n1,elasticsearch_n2"- "discovery.zen.minimum_master_nodes=2"
由於5.2.1後的版本是不支持多播的，所以需要手動指定集羣各節點的tcp數據交互地址，用於集羣的節點發現和failover，默認缺省9300端口，如設定了其它端口需另行指定，這裏我們直接藉助容器通信，也可以將各節點的9300映射至宿主機，通過網絡端口通信。
設定failover選取的quorum = nodes/2 + 1
當然，你也可以掛在配置文件，ES鏡像的配置文件是/usr/share/elasticsearch/config/elasticsearch.yml:
volumes:
- path/to/local/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml:rodocker-compose.yml
version: '3'
services:
elasticsearch_n0:
image: elasticsearch:6.6.2
container_name: elasticsearch_n0
privileged: true
environment:
- cluster.name=elasticsearch-cluster
- node.name=node0
- node.master=true
- node.data=true
- bootstrap.memory_lock=true
- http.cors.enabled=true
- http.cors.allow-origin=*
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=elasticsearch_n0,elasticsearch_n1,elasticsearch_n2"
- "discovery.zen.minimum_master_nodes=2"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- ./data/node0:/usr/share/elasticsearch/data
- ./logs/node0:/usr/share/elasticsearch/logs
ports:
- 9200:9200
elasticsearch_n1:
image: elasticsearch:6.6.2
container_name: elasticsearch_n1
privileged: true
environment:
- cluster.name=elasticsearch-cluster
- node.name=node1
- node.master=true
- node.data=true
- bootstrap.memory_lock=true
- http.cors.enabled=true
- http.cors.allow-origin=*
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=elasticsearch_n0,elasticsearch_n1,elasticsearch_n2"
- "discovery.zen.minimum_master_nodes=2"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- ./data/node1:/usr/share/elasticsearch/data
- ./logs/node1:/usr/share/elasticsearch/logs
ports:
- 9201:9200
elasticsearch_n2:
image: elasticsearch:6.6.2
container_name: elasticsearch_n2
privileged: true
environment:
- cluster.name=elasticsearch-cluster
- node.name=node2
- node.master=true
- node.data=true
- bootstrap.memory_lock=true
- http.cors.enabled=true
- http.cors.allow-origin=*
- "ES_JAVA_OPTS=-Xms512m -Xmx512m"
- "discovery.zen.ping.unicast.hosts=elasticsearch_n0,elasticsearch_n1,elasticsearch_n2"
- "discovery.zen.minimum_master_nodes=2"
ulimits:
memlock:
soft: -1
hard: -1
volumes:
- ./data/node2:/usr/share/elasticsearch/data
- ./logs/node2:/usr/share/elasticsearch/logs
ports:
- 9202:9200這裏我們分別爲node0/node1/node2開放宿主機的9200/9201/9202作爲http服務端口，各實例的tcp數據傳輸用默認的9300通過容器管理通信。
如果需要多機部署，則將ES的transport.tcp.port: 9300端口映射至宿主機xxxx端口，discovery.zen.ping.unicast.hosts填寫各主機代理的地址即可：
#比如其中一臺宿主機爲192.168.1.100
...
- "discovery.zen.ping.unicast.hosts=192.168.1.100:9300,192.168.1.101:9300,192.168.1.102:9300"
...
ports:
...
- 9300:9300創建並啓動服務
[root@localhost elasticsearch]# docker-compose up -d
[root@localhost elasticsearch]# docker-compose ps
Name Command State Ports
--------------------------------------------------------------------------------------------
elasticsearch_n0 /usr/local/bin/docker-entr ... Up 0.0.0.0:9200->9200/tcp, 9300/tcp
elasticsearch_n1 /usr/local/bin/docker-entr ... Up 0.0.0.0:9201->9200/tcp, 9300/tcp
elasticsearch_n2 /usr/local/bin/docker-entr ... Up 0.0.0.0:9202->9200/tcp, 9300/tcp
#啓動失敗查看錯誤
[root@localhost elasticsearch]# docker-compose logs
#最多是一些訪問權限/JVM vm.max_map_count 的設置問題查看集羣狀態
192.168.20.6 是我的服務器地址
訪問http://192.168.20.6:9200/_cat/nodes?v即可查看集羣狀態：
ip heap.percent ram.percent cpu load_1m load_5m load_15m node.role master name
172.25.0.3 36 98 79 3.43 0.88 0.54 mdi * node0
172.25.0.2 48 98 79 3.43 0.88 0.54 mdi - node2
172.25.0.4 42 98 51 3.43 0.88 0.54 mdi - node1驗證 Failover
通過集羣接口查看狀態
模擬主節點下線，集羣開始選舉新的主節點，並對數據進行遷移，重新分片。
[root@localhost elasticsearch]# docker-compose stop elasticsearch_n0
Stopping elasticsearch_n0 ... done集羣狀態(注意換個http端口 原主節點下線了)，down掉的節點還在集羣中，等待一段時間仍未恢復後就會被剔出
ip heap.percent ram.percent cpu load_1m load_5m load_15m node.role master name
172.25.0.2 57 84 5 0.46 0.65 0.50 mdi - node2
172.25.0.4 49 84 5 0.46 0.65 0.50 mdi * node1
172.25.0.3 mdi - node0等待一段時間
ip heap.percent ram.percent cpu load_1m load_5m load_15m node.role master name
172.25.0.2 44 84 1 0.10 0.33 0.40 mdi - node2
172.25.0.4 34 84 1 0.10 0.33 0.40 mdi * node1恢復節點 node0
[root@localhost elasticsearch]# docker-compose start elasticsearch_n0
Starting elasticsearch_n0 ... done
等待一段時間
ip heap.percent ram.percent cpu load_1m load_5m load_15m node.role master name
172.25.0.2 52 98 25 0.67 0.43 0.43 mdi - node2
172.25.0.4 43 98 25 0.67 0.43 0.43 mdi * node1
172.25.0.3 40 98 46 0.67 0.43 0.43 mdi - node0配合 Head 插件觀察
集羣狀態圖示更容易看出數據自動遷移的過程
1、集羣正常 數據安全分佈在3個節點上
2、下線 node1 主節點 集羣開始遷移數據
遷移中
遷移完成
3、恢復 node1 節點
完