实战案例丨用 Docker Compose 快速运行一个 3 节点 Elasticsearch 集群

出品丨Docker公司（ID：docker-cn）
编译丨小东
每周一、三、五，与您不见不散！

---

使用 Docker 在笔记本电脑上安装 Elasticsearch 集群进行测试是非常方便的。在这篇文章中，我将向您展示如何快速、简便地在 docker 上运行一个3节点的 elasticsearch 集群进行测试。

---

先决条件

我们需要设置“vm.max_map_count”内核参数：

$ sudo sysctl -w vm.max_map_count=262144 

若要永久设置此值，请将其添加到“/etc/sysctl.conf”并使用“sudo sysctl -p”命令重新加载。

---

Docker Compose

我们将引用的 docker compose 文件：

version: '2.2' services: elasticsearch: image: docker.elastic.co/elasticsearch/elasticsearch:6.2.4 container_name: elasticsearch environment: - cluster.name=docker-cluster - bootstrap.memory_lock=true - http.cors.enabled=true - http.cors.allow-origin=* - "ES_JAVA_OPTS=-Xms512m -Xmx512m" ulimits: memlock: soft: -1 hard: -1 volumes: - esdata1:/home/ruan/workspace/docker/elasticsearch/data ports: - 9200:9200 networks: - esnet elasticsearch2: image: docker.elastic.co/elasticsearch/elasticsearch:6.2.4 container_name: elasticsearch2 environment: - cluster.name=docker-cluster - bootstrap.memory_lock=true - http.cors.enabled=true - http.cors.allow-origin=* - "ES_JAVA_OPTS=-Xms512m -Xmx512m" - "discovery.zen.ping.unicast.hosts=elasticsearch" ulimits: memlock: soft: -1 hard: -1 volumes: - esdata2:/home/ruan/workspace/docker/elasticsearch/data networks: - esnet elasticsearch3: image: docker.elastic.co/elasticsearch/elasticsearch:6.2.4 container_name: elasticsearch3 environment: - cluster.name=docker-cluster - bootstrap.memory_lock=true - http.cors.enabled=true - http.cors.allow-origin=* - "ES_JAVA_OPTS=-Xms512m -Xmx512m" - "discovery.zen.ping.unicast.hosts=elasticsearch" ulimits: memlock: soft: -1 hard: -1 volumes: - esdata3:/home/ruan/workspace/docker/elasticsearch/data networks: - esnet kibana: image: 'docker.elastic.co/kibana/kibana:6.3.2' container_name: kibana environment: SERVER_NAME: kibana.local ELASTICSEARCH_URL: http://elasticsearch:9200 ports: - '5601:5601' networks: - esnet headPlugin: image: 'mobz/elasticsearch-head:5' container_name: head ports: - '9100:9100' networks: - esnet volumes: esdata1: driver: local esdata2: driver: local esdata3: driver: local networks: esnet: 

现在，只需确保我们在 compose 文件中所引用的路径是真实存在的，在我展示的实例中，其路径是“/home/ruan/workspace/docker/elasticsearch/data”。

---

部 署

使用 docker compose 来部署 elasticsearch 集群：

$ docker-compose up 

它将在前台运行，您可以在控制台看到其输出结果。

---

测试 Elasticsearch

接下来，让我们运行几个查询。首先，检查群集运行状况 api：

$ curl http://127.0.0.1:9200/_cluster/health?pretty { "cluster_name" : "docker-cluster", "status" : "green", "timed_out" : false, "number_of_nodes" : 3, "number_of_data_nodes" : 3, "active_primary_shards" : 1, "active_shards" : 2, "relocating_shards" : 0, "initializing_shards" : 0, "unassigned_shards" : 0, "delayed_unassigned_shards" : 0, "number_of_pending_tasks" : 0, "number_of_in_flight_fetch" : 0, "task_max_waiting_in_queue_millis" : 0, "active_shards_percent_as_number" : 100.0 } 

创建一个复制计数为2的索引：

$ curl -H "Content-Type: application/json" -XPUT http://127.0.0.1:9200/test -d '{"number_of_replicas": 2}' 

将文档提取到 elasticsearch：

$ curl -H "Content-Type: application/json" -XPUT http://127.0.0.1:9200/test/docs/1 -d '{"name": "ruan"}' {"_index":"test","_type":"docs","_id":"1","_version":1,"result":"created","_shards":{"total":3,"successful":3,"failed":0},"_seq_no":0,"_primary_term":1} 

查看索引：

$ curl http://127.0.0.1:9200/_cat/indices?v health status index uuid pri rep docs.count docs.deleted store.size pri.store.size green open test w4p2Q3fTR4uMSYBfpNVPqw 5 2 1 0 3.3kb 1.1kb green open .monitoring-es-6-2018.04.29 W69lql-rSbORVfHZrj4vug 1 1 1601 38 4mb 2mb 

---

Kibana

Kibana 也包含在应用栈中，可以通过“http://localhost:5601/”访问它，如下图所示：

---

Elasticsearch Head UI

我喜欢直接使用 RESTFul API，但是如果您想使用 UI 与 Elasticsearch 进行交互，你可以通过“http：// localhost：9100/”访问它，如下图所示：

---

删除群集

因为它在前台运行，所以您只需按下“ctrl + c”就可以持续地将数据保存在我们的 compose 文件中。当您再次启动集群时，数据仍然会存在。

浏览 https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html 了解更多Elasticsearch 的相关信息！