在nodejs中使用ElasticSearch（一）安装，使用

使用docker安装ElasticSearch和Kibana

1）创建相应的data文件夹和子文件夹用来持久化ElasticSearch和kibana数据

2）提前创建好elasticsearch配置文件 data/elasticsearch/config/elasticsearch.yml文件

# ======================== 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: # .elastic.co/guide/en/elasticsearch/reference/index.html # xpack.security.enabled: false network.host: 0.0.0.0 # xpack.security.enrollment.enabled: true # xpack.security.http.ssl.enabled: true # xpack.security.http.sslkeystore.path: certs/http.p12 # xpack.security.transport.ssl.enabled: true # xpack.security.transport.ssl.verification_mode: certificate # xpack.security.transport.ssl.client_authentication: required # xpack.security.transport.ssl.keystore.path: elastic-certificates.p12 # xpack.security.transport.ssl.truststore.path: elastic-certificates.p12 # 禁用磁盘水位检查 cluster.routing.allocation.disk.watermark.low: 100% cluster.routing.allocation.disk.watermark.high: 100% cluster.routing.allocation.disk.watermark.flood_stage: 100% # 禁用基于磁盘水位的磁盘卸载 cluster.routing.allocation.disk.threshold_enabled: false # ---------------------------------- Cluster ----------------------------------- # # Use a descriptive name for your cluster: # #cluster.name: my-application # # ------------------------------------ Node ------------------------------------ # # Use a descriptive name for the node: # #node.name: node-1 # # 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 ----------------------------------- # # By default Elasticsearch is only accessible on localhost. Set a different # address here to expose this node on the network: # #network.host: 192.168.0.1 # # By default Elasticsearch listens for HTTP traffic on the first free port it # finds starting at 9200. Set a specific HTTP port here: # #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: ["host1", "host2"] # # Bootstrap the cluster using an initial set of master-eligible nodes: # #cluster.initial_master_nodes: ["node-1", "node-2"] # # For more information, consult the discovery and cluster formation module documentation. # # ---------------------------------- Various ----------------------------------- # # Allow wildcard deletion of indices: # #action.destructive_requires_name: false

3）提前创建好kibana配置文件 data/kibana/config/kibana.yml文件，配置为中文在kibana.yml中添加i18n.locale: "zh-CN" 参数。

# # ** THIS IS AN AUTO-GENERATED FILE ** # # Default Kibana configuration for docker target server.host: "0.0.0.0" server.shutdownTimeout: "5s" elasticsearch.hosts: [ "http://elasticsearch:9200" ] monitoring.ui.container.elasticsearch.enabled: true i18n.locale: "zh-CN" # 设置中文

4）创建docker-compose.yml文件，volumes下持久化数据保存到本机的路径可以自定义。

services: elasticsearch: image: elasticsearch:8.17.2 container_name: elasticsearch environment: - ES_JAVA_OPTS=-Xms1g -Xmx1g - discovery.type=single-node - ELASTICSEARCH_PASSWORD=admin1234 # elastic 用户密码相同 volumes: - D:/VScode/nodejs/intensify/docker/elasticsearch/data/elasticsearch/data:/usr/share/elasticsearch/data - D:/VScode/nodejs/intensify/docker/elasticsearch/data/elasticsearch/plugins:/usr/share/elasticsearch/plugins - D:/VScode/nodejs/intensify/docker/elasticsearch/data/elasticsearch/config/elasticsearch.yml:/usr/share/elasticsearch/config/elasticsearch.yml privileged: true networks: - elastic-net ports: - "9200:9200" - "9300:9300" kibana: image: kibana:8.17.2 container_name: kibana environment: - ELASTICSEARCH_HOSTS=http://elasticsearch:9200 volumes: - D:/VScode/nodejs/intensify/docker/elasticsearch/data/kibana/data:/usr/share/kibana/data - D:/VScode/nodejs/intensify/docker/elasticsearch/data/kibana/config/kibana.yml:/usr/share/kibana/config/kibana.yml networks: - elastic-net ports: - "5601:5601" networks: elastic-net: driver: bridge

5）在docker-compose.yml所在位置运行下述命令,即可直接访问

docker compose up -d

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分词插件安装 一、analysis-icu分词器 

analysis-icu 插件是基于 ICU（International Components for Unicode） 库的分词插件，主要用于处理 Unicode 字符串，支持多种语言的字符集和复杂的文本处理。ICU 是一个开源的跨平台库，支持国际化和本地化特性，尤其擅长处理多语言环境下的文本。

1）进入到运行的elasticSearch容器中 

docker exec -it containerID sh

 2）在ElasticSearch安装的根目录下，执行安装分词插件，安装完后重启

./bin/elasticsearch-plugin install analysis-icu

3）查看已安装的插件 

./bin/elasticsearch-plugin list

4）删除插件

./bin/elasticsearch-plugin remove analysis-icu 二、analysis-ik分词器 

analysis-ik 是一个基于 IK Analyzer 的中文分词插件，IK 分词器是一个非常流行且高效的中文分词器，它基于词典和规则的方式进行中文分词，尤其适合处理中文文本。IK 分词器的优势是精确度高、性能优秀，特别适合中文文本分析。 

下载地址（注：要和elasticsearch版本一致）：Index of: analysis-ik/stable/

下载完后加压直接放在根目录的plugins文件下，然后重启elasticsearch即可生效。（因为之前已经设置过volume持久化了，docker会自动同步到容器中 ）

analysis-icu 和 analysis-ik 分词器的主要区别 特性analysis-icuanalysis-ik语言支持支持多语言，特别适合多语言环境。专注于中文分词，支持中文分词的各种优化。分词精度对于中文的精度较低，适合多语言环境。对于中文分词精度较高，适合中文文本分析。适用场景多语言的文本分析，尤其是Unicode字符。主要用于中文语料库，精细化中文分词。分词模式基于 ICU 字符库的分词器，语言无关。提供细粒度和粗粒度两种分词模式。扩展性支持复杂的字符过滤和 Unicode 操作。支持用户自定义词典，适合特定行业的分词。性能性能较为一般，适合多语言环境。高效，专为中文设计，性能优越。 示例

 在kibana左侧菜单management，开发工具中测试

# 创建索引 PUT /my-index # 添加索引 POST /my-index/_doc { "id": "park_rocky-mountain", "title": "Rocky Mountain", "description": "Bisected north to south by the Continental Divide, this portion of the Rockies has ecosystems varying from over 150 riparian lakes to montane and subalpine forests to treeless alpine tundra." } # 通过索引查询数据 GET /my-index/_search?q="rocky mountain" # 使用icu分词器 POST /_analyze -H 'Content-Type: application/json' -d' { "analyzer": "icu_analyzer", "text": "中华人民共和国" } # 默认分词会单字拆分 POST /_analyze -H 'Content-Type: application/json' -d' { "analyzer": "standard", "text": "中华人民共和国" } # 使用ik粗粒度分词 POST /_analyze -H 'Content-Type: application/json' -d' { "analyzer": "ik_smart", "text": "中华人民共和国" } # 使用ik细粒度分词 POST /_analyze -H 'Content-Type: application/json' -d' { "analyzer": "ik_max_word", "text": "中华人民共和国" }

在nodejs中连接elasticsearch（注：bun存在兼容性问，无法正确执行，deno，node可以），@elastic/elasticsearch文档： .elastic.co/guide/en/elasticsearch/client/javascript-api/current/getting-started-js.html#_indexing_documents

import { Client } from '@elastic/elasticsearch'; /** * 创建 Elasticsearch 客户端实例。 * 注意： * - 在 elasticsearch.yml 配置文件中设置了 `xpack.security.enabled: false`， * 因此 Elasticsearch 不会进行账号密码验证。 * - 虽然配置了 `elastic` 用户的密码，但在关闭安全验证的情况下，`auth` 参数可以不传。 * - 并且这里设置的密码是错误的，elasticsearch是可以正常连接的。 */ const client = new Client({ node: 'http://localhost:9200', auth: { // 连接云端使用 // apiKey: { // id: 'foo', // api_key: 'bar', // }, username: 'elastic', password: 'elastic1234', }, }); // 创建索引 console.log(await client.indices.create({ index: 'my_index' })); // 创建数据 console.log(await client.index({ index: 'my_index', id: 'my_document_id', document: { foo: 'foo', bar: 'bar', }, })); // 查询数据 console.log(await client.get({ index: 'my_index', id: 'my_document_id', })); // 搜索数据 console.log(await client.search({ query: { match: { foo: 'foo' } } })); // 修改数据 console.log(await client.update({ index: 'my_index', id: 'my_document_id', doc: { foo: 'bar', new_field: 'new value' } })); // 删除数据 console.log(await client.delete({ index: 'my_index', id: 'my_document_id', })); // 删除索引 console.log(await client.indices.delete({ index: 'my_index' })); // 文本分析 // 定义分析文本的函数 async function analyzeText(analyzer, text) { try { const response = await client.indices.analyze({ body: { analyzer: analyzer, text: text, } }); console.log(`Using analyzer: ${analyzer}`); console.log(response); } catch (error) { console.error(`Error using analyzer ${analyzer}:`, error); } } // 分析文本 async function performAnalysis() { // ICU 分词器分析 await analyzeText('icu_analyzer', '中华人民共和国'); // 标准分词器分析 await analyzeText('standard', '中华人民共和国'); // IK 粗粒度分词器分析 await analyzeText('ik_smart', '中华人民共和国'); // IK 细粒度分词器分析 await analyzeText('ik_max_word', '中华人民共和国'); } // 执行分析 performAnalysis();