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https://github.com/avidbyte/escurlgen
生成 es curl 命令的小工具
https://github.com/avidbyte/escurlgen
Last synced: 6 days ago
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生成 es curl 命令的小工具
- Host: GitHub
- URL: https://github.com/avidbyte/escurlgen
- Owner: avidbyte
- License: apache-2.0
- Created: 2024-10-15T09:14:35.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-10-18T00:10:15.000Z (3 months ago)
- Last Synced: 2024-10-19T14:07:09.590Z (3 months ago)
- Language: HTML
- Size: 285 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ESCurlGen
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
```json
{
"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
```json
{
"properties": {
"address": { "type": "text", "fields": { "keyword": { "type": "keyword" } } }
}
}
```
## 3.查询 settings
## 4.查询 Mapping
## 5.新增数据
```json
{
"id": "1",
"name": "John Doe",
"phone": "123-456-7890",
"birthday": "1990-01-01",
"createTime": "2023-10-10T08:00:00Z",
"address": "123 Main St"
}
```
```json
{
"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）
```json lines
{ "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
```json
{
"query": {
"match": {
"name": "John Doe"
}
}
}
```
## 9.根据 ID 查询
## 10.滚动查询
```json
{
"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：
```json
{
"scroll": "1m",
"scroll_id": "DXF1ZXJ5QW5kRmV0Y2gBAAAAAA..."
}
```
## 11.根据 ID 更新数据
```json
{
"doc": {
"phone": "555-555-5555",
"createTime": "2024-10-17T00:00:00Z"
}
}
```
## 12.根据自定义条件更新数据
```json
{
"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
```json
{
"query": {
"match": {
"name": "Jane Doe"
}
}
}
```
## 15.删除索引
## 16.批量更新文档 (2024-12-14新增)