通过 SSIS 将 Shopify 数据连接到 SQL Server 时出错
我正在使用 SSIS+ 2.0.101.2677 和 Visual Studio 15.9.28307.1800,针对 SQL Server 2017。
我关注您的视频 将 Shopify 连接到 MS SQL Server。 Easy Shopify 和SQL Server 集成。加载、导出和同步数据
将 Shopify 连接到 SQL Server。 Easy Shopify 和SQL Server 集成。加载、导出和同步数据
在最后一步开始将 shopify REST 源连接到 OLE DB 目标(我在数据库中创建表)时,我收到此错误:
标题:包验证错误
其他信息:
数据流任务 [OLE DB 目标 [316]] 出错:列“标题”无法在 unicode 和非 unicode 字符串数据类型之间转换。
数据流任务 [OLE DB 目标 [316]] 出错:列“供应商”无法在 unicode 和非 unicode 字符串数据类型之间转换。
数据流任务 [SSIS.Pipeline] 出错:“OLE DB 目标”验证失败并返回验证状态“VS_ISBROKEN”。
数据流任务 [SSIS.Pipeline] 出错:一个或多个组件验证失败。
数据流任务出错:任务验证期间出现错误。 (Microsoft.DataTransformationServices.VsIntegration)
有人知道如何修复此错误吗?
I am using SSIS+ 2.0.101.2677 with Visual Studio 15.9.28307.1800, targeting SQL Server 2017.
I follow your video Connect Shopify to MS SQL Server. Easy Shopify & SQL Server integration. Load, Export and Sync data
Connect Shopify to SQL Server. Easy Shopify & SQL Server integration. Load, Export, and Sync data
In last step start connect shopify REST Source to OLE DB Destination (I create table in my database), I got this error:
TITLE: Package Validation Error
ADDITIONAL INFORMATION:
Error at Data Flow Task [OLE DB Destination [316]]: Column "title" cannot convert between unicode and non-unicode string data types.
Error at Data Flow Task [OLE DB Destination [316]]: Column "vendor" cannot convert between unicode and non-unicode string data types.
Error at Data Flow Task [SSIS.Pipeline]: "OLE DB Destination" failed validation and returned validation status "VS_ISBROKEN".
Error at Data Flow Task [SSIS.Pipeline]: One or more component failed validation.
Error at Data Flow Task: There were errors during task validation. (Microsoft.DataTransformationServices.VsIntegration)
Does someone know how to fix this error?
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您面临的主要错误是:
由于您尝试将 Unicode 字符串值 (nvarchar) 插入非 Unicode 字符串列 (varchar),因此会引发此错误。
您只需添加派生列或数据转换即可解决此问题。或者,您可以将目标列数据类型更改为
nvarchar
。您可以参考以下链接以获取替代方案和更多指导:
The main error you are facing is:
This error is thrown since you are trying to insert a Unicode string value (nvarchar) into a non-Unicode string column (varchar).
You can simply add a derived column or a data conversion transformation to solve this issue. Or you can change the target columns data type to
nvarchar
.You can refer to the following links for alternatives and more guidance: