Synchronize your Google Sheets with Postgres
工作流概述
这是一个包含10个节点的复杂工作流，主要用于自动化处理各种任务。
工作流源代码
{
"id": "wDD4XugmHIvx3KMT",
"meta": {
"instanceId": "149cdf730f0c143663259ddc6124c9c26e824d8d2d059973b871074cf4bda531"
},
"name": "Synchronize your Google Sheets with Postgres",
"tags": [],
"nodes": [
{
"id": "44171bad-84b6-49f8-b538-fb0c2d52db43",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
900,
360
],
"parameters": {
"rule": {
"interval": [
{
"field": "hours"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "1d1558cc-523b-4985-81e2-da49e3d0f4b7",
"name": "Compare Datasets",
"type": "n8n-nodes-base.compareDatasets",
"position": [
1820,
380
],
"parameters": {
"options": {},
"resolve": "preferInput1",
"mergeByFields": {
"values": [
{
"field1": "first_name",
"field2": "first_name"
}
]
}
},
"typeVersion": 2.3
},
{
"id": "b4442fd7-6817-40bb-a76e-851659c836ec",
"name": "Split Out Relevant Fields",
"type": "n8n-nodes-base.splitOut",
"position": [
1460,
240
],
"parameters": {
"options": {},
"fieldToSplitOut": "first_name, last_name, town, age"
},
"typeVersion": 1
},
{
"id": "b63899bd-f842-4ead-a590-9bdacdc9b3c0",
"name": "Retrieve Sheets Data",
"type": "n8n-nodes-base.googleSheets",
"position": [
1200,
240
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1jhUobbdaEuX093J745TsPFMPFbzAIIgx6HnIzdqYqhg/edit#gid=0",
"cachedResultName": "Sheet1"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1jhUobbdaEuX093J745TsPFMPFbzAIIgx6HnIzdqYqhg",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1jhUobbdaEuX093J745TsPFMPFbzAIIgx6HnIzdqYqhg/edit?usp=drivesdk",
"cachedResultName": "Testing_Sheet"
}
},
"typeVersion": 4.2
},
{
"id": "ae4918fb-07ef-48db-ba25-ea34c5af43af",
"name": "Select Rows in Postgres",
"type": "n8n-nodes-base.postgres",
"position": [
1200,
540
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "testing",
"cachedResultName": "testing"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"options": {},
"operation": "select",
"returnAll": true
},
"typeVersion": 2.3
},
{
"id": "4d08d771-0e80-445e-92db-08197418512d",
"name": "Insert Rows",
"type": "n8n-nodes-base.postgres",
"position": [
2300,
260
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "testing",
"cachedResultName": "testing"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"value": {},
"schema": [
{
"id": "first_name",
"type": "string",
"display": true,
"required": false,
"displayName": "first_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "last_name",
"type": "string",
"display": true,
"required": false,
"displayName": "last_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "town",
"type": "string",
"display": true,
"required": false,
"displayName": "town",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "age",
"type": "number",
"display": true,
"required": false,
"displayName": "age",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "autoMapInputData",
"matchingColumns": []
},
"options": {}
},
"typeVersion": 2.3
},
{
"id": "3fd7baa1-72c7-4587-a557-02eb4dfa92f5",
"name": "Update Rows",
"type": "n8n-nodes-base.postgres",
"position": [
2300,
460
],
"parameters": {
"table": {
"__rl": true,
"mode": "list",
"value": "testing",
"cachedResultName": "testing"
},
"schema": {
"__rl": true,
"mode": "list",
"value": "public"
},
"columns": {
"value": {
"age": "={{ $json.age }}",
"town": "={{ $json.town }}",
"last_name": "={{ $json.last_name }}",
"first_name": "={{ $json.first_name }}"
},
"schema": [
{
"id": "first_name",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "first_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "last_name",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "last_name",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "town",
"type": "string",
"display": true,
"required": false,
"displayName": "town",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "age",
"type": "number",
"display": true,
"required": false,
"displayName": "age",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"first_name",
"last_name"
]
},
"options": {},
"operation": "update"
},
"typeVersion": 2.3
},
{
"id": "fc8dbe79-a54d-46fb-8ef7-4bb8b2a402ee",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
360,
260
],
"parameters": {
"width": 485.5994596522446,
"height": 350.08576009540855,
"content": "## Setup ##
In order to make this automation work for you, you need to make a few adjustments:
1. Add your Postgres & Google Sheets Credentials to the respective Nodes
2. Select the Sheet (Google Sheets) and the table (Postgres) you want to sync
3. Update the Insert & Update Queries so that the data is updated in the table you also selected the rows from in the first step"
},
"typeVersion": 1
},
{
"id": "3719112b-1ec7-4402-a366-b1b845819e8d",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
2080,
160
],
"parameters": {
"width": 485.5994596522446,
"height": 486.693620858174,
"content": "## Updating Your Database
Using Insert Rows & Update Rows as Separate Postgres Node's"
},
"typeVersion": 1
},
{
"id": "7742972b-7996-4f9a-9c1d-700737b94eec",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1080,
140
],
"parameters": {
"width": 543.3950930518761,
"height": 553.2461684092643,
"content": "## Retrieving Data & Spitting Out Fields
Get the Data you want to compare and split out the relevant fields"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "ac0f0ed3-3f25-4672-a34a-29b5f4402e63",
"connections": {
"Compare Datasets": {
"main": [
[
{
"node": "Insert Rows",
"type": "main",
"index": 0
}
],
[],
[
{
"node": "Update Rows",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Retrieve Sheets Data",
"type": "main",
"index": 0
},
{
"node": "Select Rows in Postgres",
"type": "main",
"index": 0
}
]
]
},
"Retrieve Sheets Data": {
"main": [
[
{
"node": "Split Out Relevant Fields",
"type": "main",
"index": 0
}
]
]
},
"Select Rows in Postgres": {
"main": [
[
{
"node": "Compare Datasets",
"type": "main",
"index": 1
}
]
]
},
"Split Out Relevant Fields": {
"main": [
[
{
"node": "Compare Datasets",
"type": "main",
"index": 0
}
]
]
}
}
}功能特点
- 自动检测新邮件
- AI智能内容分析
- 自定义分类规则
- 批量处理能力
- 详细的处理日志
技术分析
节点类型及作用
- Scheduletrigger
- Comparedatasets
- Splitout
- Googlesheets
- Postgres
复杂度评估
配置难度：
维护难度：
扩展性：
实施指南
前置条件
- 有效的Gmail账户
- n8n平台访问权限
- Google API凭证
- AI分类服务订阅
配置步骤
- 在n8n中导入工作流JSON文件
- 配置Gmail节点的认证信息
- 设置AI分类器的API密钥
- 自定义分类规则和标签映射
- 测试工作流执行
- 配置定时触发器（可选）
关键参数
| 参数名称 | 默认值 | 说明 |
|---|---|---|
| maxEmails | 50 | 单次处理的最大邮件数量 |
| confidenceThreshold | 0.8 | 分类置信度阈值 |
| autoLabel | true | 是否自动添加标签 |
最佳实践
优化建议
- 定期更新AI分类模型以提高准确性
- 根据邮件量调整处理批次大小
- 设置合理的分类置信度阈值
- 定期清理过期的分类规则
安全注意事项
- 妥善保管API密钥和认证信息
- 限制工作流的访问权限
- 定期审查处理日志
- 启用双因素认证保护Gmail账户
性能优化
- 使用增量处理减少重复工作
- 缓存频繁访问的数据
- 并行处理多个邮件分类任务
- 监控系统资源使用情况
故障排除
常见问题
邮件未被正确分类
检查AI分类器的置信度阈值设置，适当降低阈值或更新训练数据。
Gmail认证失败
确认Google API凭证有效且具有正确的权限范围，重新进行OAuth授权。
调试技巧
- 启用详细日志记录查看每个步骤的执行情况
- 使用测试邮件验证分类逻辑
- 检查网络连接和API服务状态
- 逐步执行工作流定位问题节点
错误处理
工作流包含以下错误处理机制：
- 网络超时自动重试（最多3次）
- API错误记录和告警
- 处理失败邮件的隔离机制
- 异常情况下的回滚操作