Elasticsearch：ES|QL 查询 TypeScript 类型（二）

在我之前的文章 "Elasticsearch：ES|QL 查询 TypeScript 类型（一）"，我们讲述了如何在 Nodejs 里对 ES|QL 进行查询。在今天的文章中，我们来使用一个完整的例子来进行详细描述。更多有关如何使用 Nodejs 来访问 Elasticsearch的知识，请参阅文章 "Elasticsearch：使用最新的 Nodejs client 8.x 来创建索引并搜索"。

在一下的演示中，我将使用 Elastic Stack 8.13.4 来进行展示。

安装

Elasticsearch 及 Kibana

如果你还没有安装好自己的 Elasticsearch 及 Kibana，请参考如下的链接来进行安装：

在安装的时候，我们选择 Elastic Stack 8.x 来进行安装。特别值得指出的是：ES|QL 只在 Elastic Stack 8.11 及以后得版本中才有。你需要下载 Elastic Stack 8.11 及以后得版本来进行安装。

在首次启动 Elasticsearch 的时候，我们可以看到如下的输出：

我们需要记下 Elasticsearch 超级用户 elastic 的密码。

我们还可以在安装 Elasticsearch 目录中找到 Elasticsearch 的访问证书：

$ pwd
/Users/liuxg/elastic/elasticsearch-8.13.4/config/certs
$ ls
http.p12      http_ca.crt   transport.p12

在上面，http_ca.crt 是我们需要用来访问 Elasticsearch 的证书。

Nodejs 依赖包

我们可以使用如下的命令来安装最新的 nodejs 客户端包：

yarn add @elastic/elasticsearch

或者

npm install @elastic/elasticsearch

我们可以通过如下的命令来查看安装的版本：

$ npm -v @elastic/elasticsearch
8.19.2

创建项目目录并拷贝证书

我们在电脑里创建一个目录，并拷贝相应的 Elasticsearch 访问证书到该目录下：

$ pwd
/Users/liuxg/nodejs/esql
$ cp ~/elastic/elasticsearch-8.13.4/config/certs/http_ca.crt .
$ ls http_ca.crt 
http_ca.crt

我们使用如下的命令来安装：

npm install --save-dev @types/node

创建一个叫做 esql.ts 的文件

touch esql.ts

我们使用如下的命令来安装 ts-node：

npm install -g ts-node typescript '@types/node'

在下面我们将使用如下的命令来运行代码：

ts-node esql.ts

展示

连接到 Elasticsearch

我们编辑 esql.ts 如下：

import { Client } from '@elastic/elasticsearch'
import * as fs from "fs";

const client = new Client({
    node: 'https://localhost:9200',
    auth: {
      username: 'elastic',
      password: '=VnaMJck+DbYXpHR1Fch'
    },
    tls: {
      ca: fs.readFileSync('./http_ca.crt'),
      rejectUnauthorized: false
    }
  })

client.info()
  .then((response) => console.log(JSON.stringify(response)))
  .catch((error) => console.error(JSON.stringify(error)));

在上面，我们使用超级账号 elastic 来进行连接。我们使用证书来访问自签名证书的集群。你需要根据自己的 Elasticsearch 配置修改上面的代码。更多关于如何访问 Elasticsearch 的知识，请阅读文章 "Elasticsearch：使用最新的 Nodejs client 8.x 来创建索引并搜索"。运行上面的代码，返回：

$ ts-node esql.ts 
{"name":"liuxgm.local","cluster_name":"elasticsearch","cluster_uuid":"JXoZ_Xu-QnasteO4AWnVvQ","version":{"number":"8.13.4","build_flavor":"default","build_type":"tar","build_hash":"da95df118650b55a500dcc181889ac35c6d8da7c","build_date":"2024-05-06T22:04:45.107454559Z","build_snapshot":false,"lucene_version":"9.10.0","minimum_wire_compatibility_version":"7.17.0","minimum_index_compatibility_version":"7.0.0"},"tagline":"You Know, for Search"}

写入数据

esql.ts

import { Client } from '@elastic/elasticsearch'
import * as fs from "fs";

const client = new Client({
    node: 'https://localhost:9200',
    auth: {
      username: 'elastic',
      password: '=VnaMJck+DbYXpHR1Fch'
    },
    tls: {
      ca: fs.readFileSync('./http_ca.crt'),
      rejectUnauthorized: false
    }
  })

client.info()
  .then((response) => console.log(JSON.stringify(response)))
  .catch((error) => console.error(JSON.stringify(error))); 

async function run () {
    // Lets index some data into Elasticsearch
    await client.indices.exists({
        index: "books"
    }).then(function (exists) {
        if(exists) {
            console.log("the index already existed")
        } else {
            console.log("the index has not been createdyet")
            
            client.helpers.bulk({
                datasource: [
                  { name: "Revelation Space", author: "Alastair Reynolds", release_date: "2000-03-15", page_count: 585 },
                  { name: "1984", author: "George Orwell", release_date: "1985-06-01", page_count: 328 },
                  { name: "Fahrenheit 451", author: "Ray Bradbury", release_date: "1953-10-15", page_count: 227 },
                  { name: "Brave New World", author: "Aldous Huxley", release_date: "1932-06-01", page_count: 268 },
                ],
                onDocument(_doc) {
                  return { index: { _index: "books" } }
                },
                  
            })
        }
    })
}

run().catch(console.log)

在运行完上面的代码后，我们可以在 Kibana 中进行查看：

对数据进行 ES|QL 查询

    const response = await client.esql.query({ query: 'FROM books' })
    console.log(response)

完整的代码为：

esql.ts

import { Client } from '@elastic/elasticsearch'
import * as fs from "fs";

const client = new Client({
    node: 'https://localhost:9200',
    auth: {
      username: 'elastic',
      password: '=VnaMJck+DbYXpHR1Fch'
    },
    tls: {
      ca: fs.readFileSync('./http_ca.crt'),
      rejectUnauthorized: false
    }
  })

client.info()
  .then((response) => console.log(JSON.stringify(response)))
  .catch((error) => console.error(JSON.stringify(error))); 

async function run () {
    // Lets index some data into Elasticsearch
    await client.indices.exists({
        index: "books"
    }).then(function (exists) {
        if(exists) {
            console.log("the index already existed")
        } else {
            console.log("the index has not been createdyet")

            client.helpers.bulk({
                datasource: [
                  { name: "Revelation Space", author: "Alastair Reynolds", release_date: "2000-03-15", page_count: 585 },
                  { name: "1984", author: "George Orwell", release_date: "1985-06-01", page_count: 328 },
                  { name: "Fahrenheit 451", author: "Ray Bradbury", release_date: "1953-10-15", page_count: 227 },
                  { name: "Brave New World", author: "Aldous Huxley", release_date: "1932-06-01", page_count: 268 },
                ],
                onDocument(_doc) {
                  return { index: { _index: "books" } }
                },
                  
            })
        }
    })


    const response = await client.esql.query({ query: 'FROM books' })
    console.log(response)
}

run().catch(console.log)

上面代码的完整响应为：

$ ts-node esql.ts 
the index already existed
{"name":"liuxgm.local","cluster_name":"elasticsearch","cluster_uuid":"JXoZ_Xu-QnasteO4AWnVvQ","version":{"number":"8.13.4","build_flavor":"default","build_type":"tar","build_hash":"da95df118650b55a500dcc181889ac35c6d8da7c","build_date":"2024-05-06T22:04:45.107454559Z","build_snapshot":false,"lucene_version":"9.10.0","minimum_wire_compatibility_version":"7.17.0","minimum_index_compatibility_version":"7.0.0"},"tagline":"You Know, for Search"}
{
  columns: [
    { name: 'author', type: 'text' },
    { name: 'author.keyword', type: 'keyword' },
    { name: 'name', type: 'text' },
    { name: 'name.keyword', type: 'keyword' },
    { name: 'page_count', type: 'long' },
    { name: 'release_date', type: 'date' }
  ],
  values: [
    [
      'Alastair Reynolds',
      'Alastair Reynolds',
      'Revelation Space',
      'Revelation Space',
      585,
      '2000-03-15T00:00:00.000Z'
    ],
    [
      'George Orwell',
      'George Orwell',
      '1984',
      '1984',
      328,
      '1985-06-01T00:00:00.000Z'
    ],
    [
      'Ray Bradbury',
      'Ray Bradbury',
      'Fahrenheit 451',
      'Fahrenheit 451',
      227,
      '1953-10-15T00:00:00.000Z'
    ],
    [
      'Aldous Huxley',
      'Aldous Huxley',
      'Brave New World',
      'Brave New World',
      268,
      '1932-06-01T00:00:00.000Z'
    ]
  ]
}

将每行返回为值数组是一个简单的默认设置，在许多情况下很有用。不过，如果你想要一个记录数组（JavaScript 应用程序中的标准结构），则需要额外的努力来转换数据。

幸运的是，在 8.14.0 中，JavaScript 客户端将包含一个新的 ES|QL 助手来为你执行此操作：

const { records } = await client.helpers.esql({ query: 'FROM books' }).toRecords()

/*
Returns:
[
  { name: "Revelation Space", author: "Alastair Reynolds", release_date: "2000-03-15", page_count: 585 },
  { name: "1984", author: "George Orwell", release_date: "1985-06-01", page_count: 328 },
  { name: "Fahrenheit 451", author: "Ray Bradbury", release_date: "1953-10-15", page_count: 227 },
  { name: "Brave New World", author: "Aldous Huxley", release_date: "1932-06-01", page_count: 268 },
]
*/

截止目前为止，8.14 还没有发布。期待在正式发布后，我们再重新尝试。

更多关于 ES|QL 的查询，请详细阅读文章 "Elasticsearch：ES|QL 动手实践"。

在文章的最后，我们可以来完成另外一个查询。我们使用 Kibana 来进行查询：

POST _query?format=txt
{
  "query": """
    FROM books
    | WHERE release_date > "1985-06-01"
    | LIMIT 5
  """
}

我们使用 Nodejs 来进行查询：

    const query = 'FROM books | WHERE release_date > "1985-06-01" | LIMIT 5'
    const response1 = await client.esql.query({ query: query })
    console.log(response1)

esql.ts

import { Client } from '@elastic/elasticsearch'
import * as fs from "fs";

const client = new Client({
    node: 'https://localhost:9200',
    auth: {
      username: 'elastic',
      password: '=VnaMJck+DbYXpHR1Fch'
    },
    tls: {
      ca: fs.readFileSync('./http_ca.crt'),
      rejectUnauthorized: false
    }
  })

client.info()
  .then((response) => console.log(JSON.stringify(response)))
  .catch((error) => console.error(JSON.stringify(error))); 

async function run () {
    // Lets index some data into Elasticsearch
    await client.indices.exists({
        index: "books"
    }).then(function (exists) {
        if(exists) {
            console.log("the index already existed")
        } else {
            console.log("the index has not been createdyet")

            client.helpers.bulk({
                datasource: [
                  { name: "Revelation Space", author: "Alastair Reynolds", release_date: "2000-03-15", page_count: 585 },
                  { name: "1984", author: "George Orwell", release_date: "1985-06-01", page_count: 328 },
                  { name: "Fahrenheit 451", author: "Ray Bradbury", release_date: "1953-10-15", page_count: 227 },
                  { name: "Brave New World", author: "Aldous Huxley", release_date: "1932-06-01", page_count: 268 },
                ],
                onDocument(_doc) {
                  return { index: { _index: "books" } }
                },
                  
            })
        }
    })


    const response = await client.esql.query({ query: 'FROM books' })
    console.log(response)

    const query = 'FROM books | WHERE release_date > "1985-06-01" | LIMIT 5'
    const response1 = await client.esql.query({ query: query })
    console.log(response1)
}

run().catch(console.log)

上面最后一个查询的结果为：