Issue joining serveral datasets together

[Max]

Hello,

Im trying to join several datasets together and wrap that in a object called

overallMetrics. Im running into an issue when I add a mapper after the union snap. Its adding overallMetrics to each object .

I have attached screen shots of the pipeline and mapper snap. Below is the input and the expected output. Thank you for your help.

Input:

[

{

"riskDetails":{

"riskScore":{

"overallRisk":"87.33"

"lowRiskCount":3

"mediumRiskCount":0

"highRiskCount":0

"statesByLowRisk":["Minnesota"]

"statesByMediumRisk":[]

"statesByHighRisk":[]

"countriesByLowRisk":["SWEDEN","UNITED STATES"]

"countriesByMediumRisk":[]

"countriesByHighRisk":[]

}

"mitigationStrategies":{

"lowRiskMitigationCodes":["Increased Inventory","Implementing a contract"]

"mediumRiskMitigationCodes":[]

"highRiskMitigationCodes":[]

}

}

},

{

"diversityMetrics":[

{

"diversityClassificationCode":"HUBZone Small Businesses",

"percentOfTotalSpend":0.1,

"percentOfTotalSuppliers":0.2

},

{

"diversityClassificationCode":"Minority Owned",

"percentOfTotalSpend":0.6,

"percentOfTotalSuppliers":1.4

},

{

"diversityClassificationCode":"Service Disabled Veteran Owned Small Businesses",

"percentOfTotalSpend":0.0,

"percentOfTotalSuppliers":0.1

},

{

"diversityClassificationCode":"Small Businesses",

"percentOfTotalSpend":9.8,

"percentOfTotalSuppliers":26.1

},

{

"diversityClassificationCode":"Small Disadvantaged Businesses",

"percentOfTotalSpend":0.4,

"percentOfTotalSuppliers":1.9

},

{

"diversityClassificationCode":"Veteran Owned",

"percentOfTotalSpend":0.0,

"percentOfTotalSuppliers":0.1

},

{

"diversityClassificationCode":"Veteran Owned Small Businesses",

"percentOfTotalSpend":0.3,

"percentOfTotalSuppliers":1.2

},

{

"diversityClassificationCode":"Woman Owned",

"percentOfTotalSpend":0.3,

"percentOfTotalSuppliers":1.5

},

{

"diversityClassificationCode":"Woman Owned Small Businesses",

"percentOfTotalSpend":0.6,

"percentOfTotalSuppliers":2.7

}

]

},

{

"rawMaterialSource":{

"insideUsaPercentage":72

"statesInsideUsa":[

"Arizona","Connecticut","Florida","Georgia","Illinois","Indiana","Massachusetts","Michigan","Minnesota","New Hampshire"

]

"outsideUsaPercentage":28

"countriesOutsideUsa":[

"AUSTRALIA","CANADA","DENMARK","GERMANY","IRELAND","JAPAN","SWITZERLAND"

]

}

}

]

Expected output:

{

overallMetrics:

{

"riskDetails":{

"riskScore":{

"overallRisk":"87.33"

"lowRiskCount":3

"mediumRiskCount":0

"highRiskCount":0

"statesByLowRisk":["Minnesota"]

"statesByMediumRisk":[]

"statesByHighRisk":[]

"countriesByLowRisk":["SWEDEN","UNITED STATES"]

"countriesByMediumRisk":[]

"countriesByHighRisk":[]

}

"mitigationStrategies":{

"lowRiskMitigationCodes":["Increased Inventory","Implementing a contract"]

"mediumRiskMitigationCodes":[]

"highRiskMitigationCodes":[]

}

}

},

{

"diversityMetrics":[

{

"diversityClassificationCode":"HUBZone Small Businesses",

"percentOfTotalSpend":0.1,

"percentOfTotalSuppliers":0.2

},

{

"diversityClassificationCode":"Minority Owned",

"percentOfTotalSpend":0.6,

"percentOfTotalSuppliers":1.4

},

{

"diversityClassificationCode":"Service Disabled Veteran Owned Small Businesses",

"percentOfTotalSpend":0.0,

"percentOfTotalSuppliers":0.1

},

{

"diversityClassificationCode":"Small Businesses",

"percentOfTotalSpend":9.8,

"percentOfTotalSuppliers":26.1

},

{

"diversityClassificationCode":"Small Disadvantaged Businesses",

"percentOfTotalSpend":0.4,

"percentOfTotalSuppliers":1.9

},

{

"diversityClassificationCode":"Veteran Owned",

"percentOfTotalSpend":0.0,

"percentOfTotalSuppliers":0.1

},

{

"diversityClassificationCode":"Veteran Owned Small Businesses",

"percentOfTotalSpend":0.3,

"percentOfTotalSuppliers":1.2

},

{

"diversityClassificationCode":"Woman Owned",

"percentOfTotalSpend":0.3,

"percentOfTotalSuppliers":1.5

},

{

"diversityClassificationCode":"Woman Owned Small Businesses",

"percentOfTotalSpend":0.6,

"percentOfTotalSuppliers":2.7

}

]

},

{

"rawMaterialSource":{

"insideUsaPercentage":72

"statesInsideUsa":[

"Arizona","Connecticut","Florida","Georgia","Illinois","Indiana","Massachusetts","Michigan","Minnesota","New Hampshire"

]

"outsideUsaPercentage":28

"countriesOutsideUsa":[

"AUSTRALIA","CANADA","DENMARK","GERMANY","IRELAND","JAPAN","SWITZERLAND"

]

}

}

}

 

 

 

[Aleksandar_A · Accepted solution]

Hello @Max,

You can try by using Join Snap instead, with Join Type set to Merge.

After this just use a Mapper Snap with the following Mapping Table:

Attached below is the sample pipeline.