由于经常编写复杂的 Elasticsearch 查询，并通过代码生成查询条件，我发现每次使用 curl 请求 Elasticsearch 时，手动复制配置信息并构建 curl 命令的过程非常繁琐，尤其是在管理多个环境的情况下更为不便。因此，我利用 AI 技术开发了一款 Web 工具，经过一系列优化和改进，该工具能够智能拼接配置信息，自动生成完整的 Elasticsearch curl 命令，极大提升了工作效率。

访问地址可直接使用（需科学上网） https://avidbyte.github.io/ESCurlGen/

功能介绍 测试示例 my_user_index 索引

1.创建索引

{
  "mappings": {
    "properties": {
      "id": { "type": "keyword" },
      "name": { "type": "text", "fields": { "keyword": { "type": "keyword" } } },
      "phone": { "type": "text", "fields": { "keyword": { "type": "keyword" } } },
      "birthday": { "type": "date" },
      "createTime": { "type": "date" }
    }
  }
}

2.新增索引字段

{
  "properties": {
    "address": { "type": "text", "fields": { "keyword": { "type": "keyword" } } }
  }
}

3.查询 settings

4.查询 Mapping

5.新增数据

{
  "id": "1",
  "name": "John Doe",
  "phone": "123-456-7890",
  "birthday": "1990-01-01",
  "createTime": "2023-10-10T08:00:00Z",
  "address": "123 Main St"
}

{
  "id": "2",
  "name": "Jane Smith",
  "phone": "098-765-4321",
  "birthday": "1985-05-05",
  "createTime": "2023-10-11T09:00:00Z",
  "address": "456 Oak Ave"
}

6.批量操作（批量新增）

{ "index": { "_id": "3" } }
{ "name": "User One", "phone": "1234567890", "birthday": "1995-05-05", "createTime": "2024-10-17T10:00:00", "address": "789 Elm St" }
{ "index": { "_id": "4" } }
{ "name": "User Two", "phone": "0987654321", "birthday": "1988-07-15", "createTime": "2024-10-17T11:00:00", "address": "1234 Oak St" }

7.查询索引数据条数

8.根据条件查询

{
  "query": {
    "match": {
      "name": "John Doe"
    }
  }
}

9.根据 ID 查询

10.滚动查询

{
  "size": 2,
  "query": {
    "match_all": {
    }
  }
}

在初次滚动查询后，您需要使用 scroll_id 进行后续请求：

{
  "scroll": "1m",
  "scroll_id": "DXF1ZXJ5QW5kRmV0Y2gBAAAAAA..."
}

11.根据 ID 更新数据

{
  "doc": {
    "phone": "555-555-5555",
    "createTime": "2024-10-17T00:00:00Z"
  }
}

12.根据自定义条件更新数据

{
  "query": {
    "match": {
      "name": "Jane Doe"
    }
  },
  "script": {
    "source": "ctx._source.phone = params.phone; ctx._source.address = params.address",
    "params": {
      "phone": "5555555555",
      "address": "222 Elm St"
    },
    "lang": "painless"
  }
}

13.根据 ID 删除数据

14.根据自定义条件删除数据

{
  "query": {
    "match": {
      "name": "Jane Doe"
    }
  }
}

15.删除索引