作者：来自 Elastic  Jeffrey Rengifo

讲解如何用 JavaScript 创建一个可用于生产环境的 Elasticsearch 后端。

想获得 Elastic 认证？看看下一期 Elasticsearch 工程师培训什么时候开始吧！

Elasticsearch 拥有大量新功能，能帮助你为你的使用场景构建最佳搜索解决方案。深入了解我们的示例笔记本、开始免费的云端试用，或者立即在本地机器上尝试 Elastic。

---

这是一个系列文章的第一篇，讲解如何在 JavaScript 中使用 Elasticsearch。在这个系列中，你将学习在 JavaScript 环境中使用 Elasticsearch 的基础知识，并了解创建搜索应用时最相关的功能和最佳实践。到最后，你将掌握使用 JavaScript 运行 Elasticsearch 所需的一切。

在第一部分中，我们将介绍：

• 环境设置
  • 前端、后端还是无服务器架构？
  • 连接客户端
• 文档索引
  • Elasticsearch 客户端
  • 语义映射
  • 批量助手
• 数据搜索
  • 词法查询
  • 语义查询
  • 混合查询

你可以在这里查看包含示例的源代码。

什么是 Elasticsearch Node.js 客户端？

Elasticsearch Node.js 客户端是一个 JavaScript 库，它将 Elasticsearch API 的 HTTP REST 调用封装成 JavaScript，使处理变得更简单，还提供了一些助手功能，方便执行像批量索引文档这样的任务。

更多阅读，请参阅文章 “Elasticsearch：使用最新的 Nodejs client 8.x 来创建索引并搜索”。

环境

前端、后端，还是无服务器？

为了使用 JavaScript 客户端创建搜索应用，我们至少需要两个组件：一个 Elasticsearch 集群和一个运行客户端的 JavaScript 运行时。

JavaScript 客户端支持所有 Elasticsearch 解决方案（云端、本地部署和无服务器），它在内部处理了各种差异，因此你不需要担心使用哪一种。

不过，JavaScript 运行时必须运行在服务器上，不能直接在浏览器中运行。

这是因为如果从浏览器直接调用 Elasticsearch，用户可能会获取敏感信息，比如集群的 API 密钥、主机地址或查询本身。Elasticsearch 建议绝不要将集群直接暴露在互联网上，而是使用一个中间层来屏蔽这些信息，让用户只能看到参数。你可以在这里相关内容。

我们建议使用这样的架构：

在这种情况下，客户端只会发送搜索词和一个用于你服务器的认证密钥，而你的服务器将完全控制查询内容以及与 Elasticsearch 的通信。

连接客户端

首先按照这些步骤创建一个 API 密钥。

根据前面的示例，我们将创建一个简单的 Express 服务器，并通过一个 Node.js 服务器中的客户端与它连接。

我们将使用 NPM 初始化项目，并安装 Elasticsearch 客户端和 Express。Express 是一个在 Node.js 中搭建服务器的库。通过使用 Express，我们可以通过 HTTP 与后端进行交互。

让我们来初始化项目：

npm init -y

安装依赖项：

npm install @elastic/elasticsearch express split2 dotenv

让我为你拆解说明：

• @elastic/elasticsearch：这是官方的 Node.js 客户端

• express：允许我们快速搭建一个轻量级的 Node.js 服务器，用来暴露 Elasticsearch

• split2：将文本按行拆分成流，便于我们逐行处理 ndjson 文件

• dotenv：允许我们通过 .env 文件管理环境变量

在项目根目录创建一个 .env 文件，并添加以下内容：

ELASTICSEARCH_ENDPOINT="Your Elasticsearch endpoint"
ELASTICSEARCH_API_KEY="Your Elasticssearch API"

这样，我们可以使用 dotenv 包导入这些变量。

创建一个 server.js 文件：

const express = require("express");
const bodyParser = require("body-parser");
const { Client } = require("@elastic/elasticsearch");require("dotenv").config(); //environment variables setupconst ELASTICSEARCH_ENDPOINT = process.env.ELASTICSEARCH_ENDPOINT;
const ELASTICSEARCH_API_KEY = process.env.ELASTICSEARCH_API_KEY;
const PORT = 3000;const app = express();app.listen(PORT, () => {console.log("Server running on port", PORT);
});
app.use(bodyParser.json());let esClient = new Client({node: ELASTICSEARCH_ENDPOINT,auth: { apiKey: ELASTICSEARCH_API_KEY },  
});app.get("/ping", async (req, res) => {try {const result = await esClient.info();res.status(200).json({success: true,clusterInfo: result,});} catch (error) {console.error("Error getting Elasticsearch info:", error);res.status(500).json({success: false,clusterInfo: null,error: error.message,});}
});

这段代码搭建了一个基础的 Express.js 服务器，监听 3000 端口，并使用 API 密钥连接到 Elasticsearch 集群进行认证。它包含一个 /ping 端点，通过 GET 请求访问时，会使用 Elasticsearch 客户端的 .info() 方法查询集群的基本信息。

如果查询成功，会以 JSON 格式返回集群信息；否则返回错误信息。服务器还使用了 body-parser 中间件来处理 JSON 请求体。

运行该文件启动服务器：

node server.js

答案应该是这样的：

Server running on port 3000

现在，让我们访问 /ping 端点来检查 Elasticsearch 集群的状态。

curl http://localhost:3000/ping
{"success": true,"clusterInfo": {"name": "instance-0000000000","cluster_name": "61b7e19eec204d59855f5e019acd2689","cluster_uuid": "BIfvfLM0RJWRK_bDCY5ldg","version": {"number": "9.0.0","build_flavor": "default","build_type": "docker","build_hash": "112859b85d50de2a7e63f73c8fc70b99eea24291","build_date": "2025-04-08T15:13:46.049795831Z","build_snapshot": false,"lucene_version": "10.1.0","minimum_wire_compatibility_version": "8.18.0","minimum_index_compatibility_version": "8.0.0"},"tagline": "You Know, for Search"}
}

索引文档

连接成功后，我们可以使用像 semantic_text（语义搜索）和 text（全文查询）这样的映射来索引文档。通过这两种字段类型，我们还可以进行混合搜索（hybrid search）。

我们将创建一个新的 load.js 文件来生成映射并上传文档。

Elasticsearch 客户端

我们首先需要实例化并认证客户端：

const { Client } = require("@elastic/elasticsearch");const ELASTICSEARCH_ENDPOINT = "cluster/project_endpoint";
const ELASTICSEARCH_API_KEY = "apiKey";const esClient = new Client({node: ELASTICSEARCH_ENDPOINT,auth: { apiKey: ELASTICSEARCH_API_KEY },
});

语义映射 - semantic mappings

我们将创建一个包含兽医医院数据的索引。存储的信息包括主人、宠物和就诊详情。

需要进行全文搜索的数据，如姓名和描述，将存为 text 类型。类别数据，如动物的种类或品种，将存为 keyword 类型。

此外，我们会将所有字段的值复制到一个 semantic_text 字段，以便也能针对这些信息进行语义搜索。

const INDEX_NAME = "vet-visits";const createMappings = async (indexName, mapping) => {try {const body = await esClient.indices.create({index: indexName,body: {mappings: mapping,},});console.log("Index created successfully:", body);} catch (error) {console.error("Error creating mapping:", error);}
};await createMappings(INDEX_NAME, {properties: {owner_name: {type: "text",copy_to: "semantic_field",},pet_name: {type: "text",copy_to: "semantic_field",},species: {type: "keyword",copy_to: "semantic_field",},breed: {type: "keyword",copy_to: "semantic_field",},vaccination_history: {type: "keyword",copy_to: "semantic_field",},visit_details: {type: "text",copy_to: "semantic_field",},semantic_field: {type: "semantic_text",},},
});

批量助手 - bulk helper

客户端的另一个优势是可以使用批量助手（bulk helper）批量索引。批量助手方便处理并发、重试以及每个文档成功或失败时的处理方式。

这个助手的一个吸引人功能是支持流式处理。它允许你逐行发送文件，而不是将整个文件存入内存后一次性发送给 Elasticsearch。

要上传数据到 Elasticsearch，请在项目根目录创建一个名为 data.ndjson 的文件，并添加以下信息（或者，你也可以从这里下载包含数据集的文件）：

{"owner_name":"Alice Johnson","pet_name":"Buddy","species":"Dog","breed":"Golden Retriever","vaccination_history":["Rabies","Parvovirus","Distemper"],"visit_details":"Annual check-up and nail trimming. Healthy and active."}
{"owner_name":"Marco Rivera","pet_name":"Milo","species":"Cat","breed":"Siamese","vaccination_history":["Rabies","Feline Leukemia"],"visit_details":"Slight eye irritation, prescribed eye drops."}
{"owner_name":"Sandra Lee","pet_name":"Pickles","species":"Guinea Pig","breed":"Mixed","vaccination_history":[],"visit_details":"Loss of appetite, recommended dietary changes."}
{"owner_name":"Jake Thompson","pet_name":"Luna","species":"Dog","breed":"Labrador Mix","vaccination_history":["Rabies","Bordetella"],"visit_details":"Mild ear infection, cleaning and antibiotics given."}
{"owner_name":"Emily Chen","pet_name":"Ziggy","species":"Cat","breed":"Mixed","vaccination_history":["Rabies","Feline Calicivirus"],"visit_details":"Vaccination update and routine physical."}
{"owner_name":"Tomás Herrera","pet_name":"Rex","species":"Dog","breed":"German Shepherd","vaccination_history":["Rabies","Parvovirus","Leptospirosis"],"visit_details":"Follow-up for previous leg strain, improving well."}
{"owner_name":"Nina Park","pet_name":"Coco","species":"Ferret","breed":"Mixed","vaccination_history":["Rabies"],"visit_details":"Slight weight loss; advised new diet."}
{"owner_name":"Leo Martínez","pet_name":"Simba","species":"Cat","breed":"Maine Coon","vaccination_history":["Rabies","Feline Panleukopenia"],"visit_details":"Dental cleaning. Minor tartar buildup removed."}
{"owner_name":"Rachel Green","pet_name":"Rocky","species":"Dog","breed":"Bulldog Mix","vaccination_history":["Rabies","Parvovirus"],"visit_details":"Skin rash, antihistamines prescribed."}
{"owner_name":"Daniel Kim","pet_name":"Mochi","species":"Rabbit","breed":"Mixed","vaccination_history":[],"visit_details":"Nail trimming and general health check. No issues."}

我们使用 split2 来流式读取文件的每一行，同时批量助手将它们发送到 Elasticsearch。

const { createReadStream } = require("fs");
const split = require("split2");const indexData = async (filePath, indexName) => {try {console.log(`Indexing data from ${filePath} into ${indexName}...`);const result = await esClient.helpers.bulk({datasource: createReadStream(filePath).pipe(split()),onDocument: () => {return {index: { _index: indexName },};},onDrop(doc) {console.error("Error processing document:", doc);},});console.log("Bulk indexing successful elements:", result.items.length);} catch (error) {console.error("Error indexing data:", error);throw error;}
};await indexData("./data.ndjson", INDEX_NAME);

上面的代码逐行读取 .ndjson 文件，并使用 helpers.bulk 方法批量将每个 JSON 对象索引到指定的 Elasticsearch 索引中。它通过 createReadStream 和 split2 流式读取文件，为每个文档设置索引元数据，并记录处理失败的文档。完成后，会输出成功索引的条目数量。

除了使用 indexData 函数，你也可以通过 Kibana 的 UI 直接上传文件，使用上传数据文件的界面。

我们运行该文件，将文档上传到 Elasticsearch 集群。

node load.js

Creating mappings for index vet-visits...
Index created successfully: { acknowledged: true, shards_acknowledged: true, index: 'vet-visits' }
Indexing data from ./data.ndjson into vet-visits...
Bulk indexing completed. Total documents: 10, Failed: 0

搜索数据

回到我们的 server.js 文件，我们将创建不同的端点来执行词法搜索、语义搜索或混合搜索。

简而言之，这些搜索类型不是互斥的，而是取决于你需要回答的问题类型。

Query type	Use case	Example question
词汇搜索	问题中的词或词根很可能出现在索引文档中。问题和文档之间的词元相似度。	I’m looking for a blue sport t-shirt.
语义搜索	问题中的词不太可能出现在文档中。问题和文档之间的概念相似度。	I’m looking for clothing for cold weather.
混合搜索	问题包含词法和/或语义成分。问题和文档之间的词元相似度和语义相似度。	I’m looking for an S size dress for a beach wedding.

问题的词汇部分很可能是标题、描述或类别名称的一部分，而语义部分是与这些字段相关的概念。Blue 很可能是类别名称或描述的一部分，而 beach wedding 可能不是，但可以与 linen clothing 在语义上相关。

Lexical query (/search/lexic?q=<query_term>)

词法搜索，也叫全文搜索，指的是基于词元相似度的搜索；也就是说，经过分析后，包含搜索词元的文档会被返回。

你可以在这里查看我们的词法搜索实操教程。

app.get("/search/lexic", async (req, res) => {const { q } = req.query;const INDEX_NAME = "vet-visits";try {const result = await esClient.search({index: INDEX_NAME,size: 5,body: {query: {multi_match: {query: q,fields: ["owner_name", "pet_name", "visit_details"],},},},});res.status(200).json({success: true,results: result.hits.hits});} catch (error) {console.error("Error performing search:", error);res.status(500).json({success: false,results: null,error: error.message,});}
});

我们用 “nail trimming” 测试。

curl http://localhost:3000/search/lexic?q=nail%20trimming

答案：

{"success": true,"results": [{"_index": "vet-visits","_id": "-RY6RJYBLe2GoFQ6-9n9","_score": 2.7075968,"_source": {"pet_name": "Mochi","owner_name": "Daniel Kim","species": "Rabbit","visit_details": "Nail trimming and general health check. No issues.","breed": "Mixed","vaccination_history": []}},{"_index": "vet-visits","_id": "8BY6RJYBLe2GoFQ6-9n9","_score": 2.560356,"_source": {"pet_name": "Buddy","owner_name": "Alice Johnson","species": "Dog","visit_details": "Annual check-up and nail trimming. Healthy and active.","breed": "Golden Retriever","vaccination_history": ["Rabies","Parvovirus","Distemper"]}}]
}

Semantic query (/search/semantic?q=<query_term>)

语义搜索不同于词法搜索，它通过向量搜索找到与搜索词含义相似的结果。

你可以在这里查看我们的语义搜索实操教程。

app.get("/search/semantic", async (req, res) => {const { q } = req.query;const INDEX_NAME = "vet-visits";try {const result = await esClient.search({index: INDEX_NAME,size: 5,body: {query: {semantic: {field: "semantic_field",query: q},},},});res.status(200).json({success: true,results: result.hits.hits,});} catch (error) {console.error("Error performing search:", error);res.status(500).json({success: false,results: null,error: error.message,});}
});

我们用 “Who got a pedicure?” 测试。

curl http://localhost:3000/search/semantic?q=Who%20got%20a%20pedicure?

答案：

{"success": true,"results": [{"_index": "vet-visits","_id": "-RY6RJYBLe2GoFQ6-9n9","_score": 4.861466,"_source": {"owner_name": "Daniel Kim","pet_name": "Mochi","species": "Rabbit","breed": "Mixed","vaccination_history": [],"visit_details": "Nail trimming and general health check. No issues."}},{"_index": "vet-visits","_id": "8BY6RJYBLe2GoFQ6-9n9","_score": 4.7152824,"_source": {"pet_name": "Buddy","owner_name": "Alice Johnson","species": "Dog","visit_details": "Annual check-up and nail trimming. Healthy and active.","breed": "Golden Retriever","vaccination_history": ["Rabies","Parvovirus","Distemper"]}},{"_index": "vet-visits","_id": "9RY6RJYBLe2GoFQ6-9n9","_score": 1.6717153,"_source": {"pet_name": "Rex","owner_name": "Tomás Herrera","species": "Dog","visit_details": "Follow-up for previous leg strain, improving well.","breed": "German Shepherd","vaccination_history": ["Rabies","Parvovirus","Leptospirosis"]}},{"_index": "vet-visits","_id": "9xY6RJYBLe2GoFQ6-9n9","_score": 1.5600781,"_source": {"pet_name": "Simba","owner_name": "Leo Martínez","species": "Cat","visit_details": "Dental cleaning. Minor tartar buildup removed.","breed": "Maine Coon","vaccination_history": ["Rabies","Feline Panleukopenia"]}},{"_index": "vet-visits","_id": "-BY6RJYBLe2GoFQ6-9n9","_score": 1.2696637,"_source": {"pet_name": "Rocky","owner_name": "Rachel Green","species": "Dog","visit_details": "Skin rash, antihistamines prescribed.","breed": "Bulldog Mix","vaccination_history": ["Rabies","Parvovirus"]}}]
}

Hybrid query (/search/hybrid?q=<query_term>)

混合搜索允许我们结合语义搜索和词法搜索，从而兼得两者优势：既有基于词元搜索的精准度，也有语义搜索的意义接近性。

app.get("/search/hybrid", async (req, res) => {const { q } = req.query;const INDEX_NAME = "vet-visits";try {const result = await esClient.search({index: INDEX_NAME,body: {retriever: {rrf: {retrievers: [{standard: {query: {bool: {must: {multi_match: {query: q,fields: ["owner_name", "pet_name", "visit_details"],},},},},},},{standard: {query: {bool: {must: {semantic: {field: "semantic_field",query: q,},},},},},},],},},size: 5,},});res.status(200).json({success: true,results: result.hits.hits,});} catch (error) {console.error("Error performing search:", error);res.status(500).json({success: false,results: null,error: error.message,});}
});

我们用 “Who got a pedicure or dental treatment?” 测试。

curl http://localhost:3000/search/hybrid?q=who%20got%20a%20pedicure%20or%20dental%20treatment

答案：

{"success": true,"results": [{"_index": "vet-visits","_id": "9xY6RJYBLe2GoFQ6-9n9","_score": 0.032522473,"_source": {"pet_name": "Simba","owner_name": "Leo Martínez","species": "Cat","visit_details": "Dental cleaning. Minor tartar buildup removed.","breed": "Maine Coon","vaccination_history": ["Rabies","Feline Panleukopenia"]}},{"_index": "vet-visits","_id": "-RY6RJYBLe2GoFQ6-9n9","_score": 0.016393442,"_source": {"pet_name": "Mochi","owner_name": "Daniel Kim","species": "Rabbit","visit_details": "Nail trimming and general health check. No issues.","breed": "Mixed","vaccination_history": []}},{"_index": "vet-visits","_id": "8BY6RJYBLe2GoFQ6-9n9","_score": 0.015873017,"_source": {"pet_name": "Buddy","owner_name": "Alice Johnson","species": "Dog","visit_details": "Annual check-up and nail trimming. Healthy and active.","breed": "Golden Retriever","vaccination_history": ["Rabies","Parvovirus","Distemper"]}},{"_index": "vet-visits","_id": "9RY6RJYBLe2GoFQ6-9n9","_score": 0.015625,"_source": {"pet_name": "Rex","owner_name": "Tomás Herrera","species": "Dog","visit_details": "Follow-up for previous leg strain, improving well.","breed": "German Shepherd","vaccination_history": ["Rabies","Parvovirus","Leptospirosis"]}},{"_index": "vet-visits","_id": "8xY6RJYBLe2GoFQ6-9n9","_score": 0.015384615,"_source": {"pet_name": "Luna","owner_name": "Jake Thompson","species": "Dog","visit_details": "Mild ear infection, cleaning and antibiotics given.","breed": "Labrador Mix","vaccination_history": ["Rabies","Bordetella"]}}]
}

总结

在本系列的第一部分中，我们讲解了如何搭建环境并创建带有不同搜索端点的服务器，以按照客户端/服务器的最佳实践查询 Elasticsearch 文档。敬请期待第二部分，你将学习生产环境的最佳实践以及如何在无服务器环境中运行 Elasticsearch Node.js 客户端。

原文：https://www.elastic.co/search-labs/blog/how-to-use-elasticsearch-in-javascript-part-i