在数据工厂管道中构建 JSON 的合适方法是什么

Question

在我之前的 post、SQL Server complains about invalid json 中，有人建议我使用 'appropriate methods' 来构建 json 字符串，该字符串将被插入到 SQL 服务器 table 用于记录目的。在之前的 post 中，我使用字符串连接来构建一个 json 字符串。

在数据工厂管道中 tools/functions 构建 json 什么是合适的？我研究了 json() 和 string() 函数，但它们仍然依赖于连接。

澄清：我正在尝试生成如下所示的日志消息：现在我正在使用字符串连接来生成日志 json。有没有更好、更优雅（但轻量级）的方法来生成 json 数据？

{   "EventType": "DataFactoryPipelineRunActivity",    
    "DataFactoryName":"fa603ea7-f1bd-48c0-a690-73b92d12176c",   
    "DataFactoryPipelineName":"Import Blob Storage Account Key CSV file into generic SQL table using Data Flow Activity Logging to Target SQL Server",   
    "DataFactoryPipelineActivityName":"Copy Generic CSV Source to Generic SQL Sink",   
    "DataFactoryPipelineActivityOutput":"{runStatus:{computeAcquisitionDuration:316446,dsl: source() ~> ReadFromCSVInBlobStorage  ReadFromCSVInBlobStorage derive() ~> EnrichWithDataFactoryMetadata  EnrichWithDataFactoryMetadata sink() ~> WriteToTargetSqlTable,profile:{ReadFromCSVInBlobStorage:{computed:[],lineage:{},dropped:0,drifted:1,newer:1,total:1,updated:0},EnrichWithDataFactoryMetadata:{computed:[],lineage:{},dropped:0,drifted:1,newer:6,total:7,updated:0},WriteToTargetSqlTable:{computed:[],lineage:{__DataFactoryPipelineName:{mapped:false,from:[{source:EnrichWithDataFactoryMetadata,columns:[__DataFactoryPipelineName]}]},__DataFactoryPipelineRunId:{mapped:false,from:[{source:EnrichWithDataFactoryMetadata,columns:[__DataFactoryPipelineRunId]}]},id:{mapped:true,from:[{source:ReadFromCSVInBlobStorage,columns:[id]}]},__InsertDateTimeUTC:{mapped:false,from:[{source:EnrichWithDataFactoryMetadata,columns:[__InsertDateTimeUTC]}]},__DataFactoryName:{mapped:false,from:[{source:EnrichWithDataFactoryMetadata,columns:[__DataFactoryName]}]},__FileName:{mapped:false,from:[{source:EnrichWithDataFactoryMetadata,columns:[__FileName]}]},__StorageAccountName:{mapped:false,from:[{source:EnrichWithDataFactoryMetadata,columns:[__StorageAccountName]}]}},dropped:0,drifted:1,newer:0,total:7,updated:7}},metrics:{WriteToTargetSqlTable:{rowsWritten:4,sinkProcessingTime:1436,sources:{ReadFromCSVInBlobStorage:{rowsRead:4}},stages:[{stage:3,partitionTimes:[621],bytesWritten:0,bytesRead:24,streams:{WriteToTargetSqlTable:{type:sink,count:4,partitionCounts:[4],cached:false},EnrichWithDataFactoryMetadata:{type:derive,count:4,partitionCounts:[4],cached:false},ReadFromCSVInBlobStorage:{type:source,count:4,partitionCounts:[4],cached:false}},target:WriteToTargetSqlTable,time:811}]}}},effectiveIntegrationRuntime:DefaultIntegrationRuntime (East US)}",   
    "DataFactoryPipelineRunID":"63759585-4acb-48af-8536-ae953efdbbb0",   
    "DataFactoryPipelineTriggerName":"Manual",   
    "DataFactoryPipelineTriggerType":"Manual",   
    "DataFactoryPipelineTriggerTime":"2019-11-05T15:27:44.1568581Z",   
    "Parameters":{    
        "StorageAccountName":"fa603ea7",     
        "FileName":"0030_SourceData1.csv",    
        "TargetSQLServerName":"5a128a64-659d-4481-9440-4f377e30358c.database.windows.net",     
        "TargetSQLDatabaseName":"TargetDatabase",     
        "TargetSQLUsername":"demoadmin"   
    },    
    "InterimValues":{    
        "SchemaName":"utils",     
        "TableName":"vw_0030_SourceData1.csv-2019-11-05T15:27:57.643"   
    }  
}

Answer 1

您可以使用数据流，它可以帮助您在数据工厂的管道内构建 JSON 字符串。

这是数据流教程：Mapping data flow JSON handling。

它可以帮助你：

希望对您有所帮助。

在数据工厂管道中构建 JSON 的合适方法是什么

What is the appropriate way to build JSON within a Data Factory Pipeline

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