I want to copy all they keys in the json except one which i want to transform.
ex.
Input JSON
{
"ts": "20200420121222",
"name": "broker",
"city": "queensland",
"age": 21,
"gender": "male"
"characteristics": {
"Card Id": "63247354",
"Termination Plan": "paid"
}
}
Output JSON
{
"ts": "20200420121222",
"name": "broker",
"city": "queensland",
"age": 21,
"gender": "male"
"characteristics": {
"card_id": "63247354", // change here
"termination_plan": "paid" // change here
}
}
Is there any better way via which i can just change the following above keys and copy the rest
You can use the "*": "&" construct to include all other fields that have not yet been matched:
[
{
"operation": "shift",
"spec": {
"characteristics": {
"Card Id": "characteristics.card_id",
"Termination Plan": "characteristics.termination_plan"
},
"*": "&"
}
}
]
Related
I'm trying to use JSONata to convert arrays of "key/value" objects into properties of the parent object. My input looks like this:
[
{
"city": "Ottawa",
"properties": [
{
"name": "population",
"value": 37
},
{
"name": "postalCode",
"value": 10001
},
{
"name": "founded",
"value": 1826
}
]
},
{
"city": "Toronto",
"properties": [
{
"name": "population",
"value": 54
},
{
"name": "postalCode",
"value": 10002
}
]
}
]
I'm struggling to generate the output I need, I've seen examples that reference explicit elements, like in this answer, but I need the properties to be converted "dynamically" since I don't know them in advance. I think I need something like this, but I'm missing some particular function:
$[].{
"city": city,
properties.name: properties.value
}
This is the output I need to generate:
[
{
"city": "Ottawa",
"population": 37,
"postalCode": 10001,
"founded": 1826
},
{
"city": "Toronto",
"population": 54,
"postalCode": 10002
}
]
The properties arrays don't always contain the same keys, but the city attributes are always present.
You can use the reduce operator, as described in the Grouping docs here:
$[].(
$city := city;
properties{ "city": $city, name: value }
)
You can play with it live: https://stedi.link/uUANwtE
Please try this expression.
$[].{
"city": $.city,
$.properties[0].name: $.properties[0].value,
$.properties[1].name: $.properties[1].value,
$.properties[2].name: $.properties[2].value,
$.properties[3].name: $.properties[3].value
}
https://try.jsonata.org/s1Ea4kUvo
Can we use string manipulation functions like below in JoltTransformJSON
${BIG:padRight(5, '#')}
Link:
https://jolt-demo.appspot.com/#modify-stringFunctions
Expected Output: BIG##
Like we use
"small_toUpper": "=toUpper(#(1,small))",
"BIG_toLower": "=toLower(#(1,BIG))",
I am trying but it's not giving any error, but not giving the desired result as well. What would be other alternative for this.
Input JSON:
{
"x": [
3,
2,
1,
"go"
],
"small": "small",
"BIG": "BIG",
"people": [
{
"firstName": "Bob",
"lastName": "Smith",
"address": {
"state": null
}
},
{
"firstName": "Sterling",
"lastName": "Archer"
}
]
}
Spec:
[
{
"operation": "modify-default-beta",
"spec": {
"y": "=join(',',#(1,x))",
"z": "=join(' ',#(1,x))",
"small_toUpper": "=toUpper(#(1,small))",
"BIG_toLower": "=toLower(#(1,BIG))",
"BIG_padding": "=padRight(#(5,BIG))"
}
}
]
You can use rightPad function along with modify-xXx-beta (xXx:default or overwrite) transformation such as
[
{
"operation": "modify-default-beta",
"spec": {
"BIG_padding": "=rightPad(#(1,BIG),5,'#')"
}
}
]
I had a task where I needed to compare and filter two JSON arrays based on the same values using one column of each array. So I used this answer of this question.
However, now I need to compare two JSON arrays matching two, or even three columns values.
I already tried to use one map inside other, however, it isn't working.
The examples could be the ones in the answer I used. Compare db.code = file.code, db.name = file.nm and db.id = file.identity
var db = [
{
"CODE": "A11",
"NAME": "Alpha",
"ID": "C10000"
},
{
"CODE": "B12",
"NAME": "Bravo",
"ID": "B20000"
},
{
"CODE": "C11",
"NAME": "Charlie",
"ID": "C30000"
},
{
"CODE": "D12",
"NAME": "Delta",
"ID": "D40000"
},
{
"CODE": "E12",
"NAME": "Echo",
"ID": "E50000"
}
]
var file = [
{
"IDENTITY": "D40000",
"NM": "Delta",
"CODE": "D12"
},
{
"IDENTITY": "C30000",
"NM": "Charlie",
"CODE": "C11"
}
]
See if this works for you
%dw 2.0
output application/json
var file = [
{
"IDENTITY": "D40000",
"NM": "Delta",
"CODE": "D12"
},
{
"IDENTITY": "C30000",
"NM": "Charlie",
"CODE": "C11"
}
]
var db = [
{
"CODE": "A11",
"NAME": "Alpha",
"ID": "C10000"
},
{
"CODE": "B12",
"NAME": "Bravo",
"ID": "B20000"
},
{
"CODE": "C11",
"NAME": "Charlie",
"ID": "C30000"
},
{
"CODE": "D12",
"NAME": "Delta",
"ID": "D40000"
},
{
"CODE": "E12",
"NAME": "Echo",
"ID": "E50000"
}
]
---
file flatMap(v) -> (
db filter (v.IDENTITY == $.ID and v.NM == $.NAME and v.CODE == $.CODE)
)
Using flatMap instead of map to flatten otherwise will get array of arrays in the output which is cleaner unless you are expecting a possibility of multiple matches per file entry, in which case I'd stick with map.
You can compare objects in DW directly, so the solution you linked can be modified to the following:
%dw 2.0
import * from dw::core::Arrays
output application/json
var db = [
{
"CODE": "A11",
"NAME": "Alpha",
"ID": "C10000"
},
{
"CODE": "B12",
"NAME": "Bravo",
"ID": "B20000"
},
{
"CODE": "C11",
"NAME": "Charlie",
"ID": "C30000"
},
{
"CODE": "D12",
"NAME": "Delta",
"ID": "D40000"
},
{
"CODE": "E12",
"NAME": "Echo",
"ID": "E50000"
}
]
var file = [
{
"IDENTITY": "D40000",
"NM": "Delta",
"CODE": "D12"
},
{
"IDENTITY": "C30000",
"NM": "Charlie",
"CODE": "C11"
}
]
---
db partition (e) -> file contains {IDENTITY:e.ID,NM:e.NAME,CODE:e.CODE}
You can make use of filter directly and using contains
db filter(value) -> file contains {IDENTITY: value.ID, NM: value.NAME, CODE: value.CODE}
This tells you to filter the db array based on if the file contains the object {IDENTITY: value.ID, NM: value.NAME, CODE: value.CODE}. However, this will not work if objects in the file array has other fields that you will not use for comparison. Using above, you can update filter condition to check if an object in file array exist (using data selector) where the condition applies. You can use below to check that.
db filter(value) -> file[?($.IDENTITY==value.ID and $.NM == value.NAME and $.CODE == value.CODE)] != null
I have the following json document to be uploaded to a full text search index
{
"bank_id": {
"country_code": "AT",
"bank_code": "ASPKAT2LXXX",
"bank_code_type": "SWIFT_CODE"
},
"institution": {
"name": "Allgemeine Sparkasse Oberoesterreich Bankaktiengesellschaft"
},
"address": {
"address_line_1": "Promenade 11-13",
"address_line_2": "Linz",
"country_code": "AT"
},
"bank_capabilities": ["INSTANT_CREDIT"],
"payment_network_details": [{
"network": "REAL_TIME_PAYMENTS",
"capabilities": ["INSTANT_CREDIT"]
}]
}
And I want to generate key with country_code and bank_code. How can i accomplish this?
tried with -g %bank_id.country_code%::%bank_id.bank_code% and it is not working.
We are calling invokehttp processes and getting response which json. Example
{
"id": "h569gcjhcm",
"doi": {
"id": "10.17632/h569gcjhcm.1",
"status": "allocated",
"prefix": "10.17632"
},
"name": "Data for: Flooding of the Caspian Sea at the intensification of Northern Hemisphere Glaciations",
"description": "Supplementary data for the Jeirankechmez section in Azerbaijan.\n\n- Appendix A contains all paleomagnetic data and interpretations of the Jeirankechmez section. This .dir file can be imported into the paleomagnetism.org webportal under \"Interpretation Portal\", \"Advanced Options\", \"Import Application Save\". For further details on the use of paleomagnetism.org please refer to the article by Koymans et al. (2016) - https://doi.org/10.1016/j.cageo.2016.05.007.\n- Appendix B contains the magnetic susceptibility data for the analysed samples, including geographic coordinates and stratigraphic levels.\n- Appendix C contains the 40Ar/39Ar data for the three analysed volcanic ash layers. ",
"version": 1,
"publish_date": "2019-01-29T12:51:38.090Z",
"data_licence": {
"id": "01d9c749-3c4d-4431-9df3-620b2dcfe144",
"short_name": "CC BY 4.0",
"full_name": "Creative Commons Attribution 4.0 International",
"description": "This dataset is licensed under a Creative Commons Attribution 4.0 International licence.\n\nWhat does this mean?\nYou can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.",
"url": "http://creativecommons.org/licenses/by/4.0",
"category": "Creative"
},
"contributors": [
{
"first_name": "Christiaan",
"last_name": "van Baak"
},
{
"first_name": "Marius",
"last_name": "Stoica"
},
{
"first_name": "Arjen",
"last_name": "Grothe"
},
{
"first_name": "Gareth",
"last_name": "Davies"
},
{
"profile_id": "72970719-95c8-341b-80d2-afa9e7154baf",
"first_name": "Wout",
"last_name": "Krijgsman"
},
{
"profile_id": "3a4bfe2c-4098-3859-9b88-789fa993e05a",
"first_name": "Keith",
"last_name": "Richards"
},
{
"profile_id": "f1660f3c-ebbd-3289-8240-1f4ea7913df4",
"first_name": "Klaudia",
"last_name": "Kuiper"
},
{
"first_name": "Elmira",
"last_name": "Aliyeva"
}
],
"versions": [
{
"version": 1,
"publish_date": "2019-01-29T12:51:38.090Z",
"available": true
}
],
"files": [
{
"filename": "Appendix_A_Jeirankechmez_pmag_interpretations.dir",
"id": "f2f4cba7-2411-4737-a9b2-f094db30dca1",
"content_details": {
"id": "994bc865-5300-4d76-a373-e528ccd830e8",
"sha256_hash": "2427c4b077372760973ce8224694f2a2ee5383c7f022ad818164d847a20e27cc",
"sha1_hash": "73792dc6d6eb2c1de1e04926ba5d4420dd0aaece",
"content_type": "application/x-director",
"size": 917022,
"created_date": "2019-01-03T00:00:00.000Z"
"download_expiry_time": "2019-01-29T13:52:25.729Z"
},
"metrics": {
"downloads": 0,
"previews": 0
}
},
{
"filename": "Appendix_B_Sample_locations_susceptibility.xlsx",
"id": "64241bf0-5279-49e8-a505-be9075b910e1",
"content_details": {
"id": "af8809d0-8e63-4599-abaa-e7af9ad39959",
"sha256_hash": "0588f44a0cbd477aa2798323e57ce0b2d4a118e767c0b1ffdc9eb1017e4d23c2",
"sha1_hash": "02e89f6f197ebf495e1e2c3d1aab250efc7545e7",
"content_type": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"size": 24770,
"created_date": "2019-01-03T00:00:00.000Z"
,
"download_expiry_time": "2019-01-29T13:52:25.732Z"
},
"metrics": {
"downloads": 0,
"previews": 0
}
},
{
"filename": "Appendix_C_ArAr_data.xlsx",
"id": "2e912027-ff3f-48ad-98b9-b643b59ba0e3",
"content_details": {
"id": "4960377c-060d-41f6-b7af-150617d8ebeb",
"sha256_hash": "235dc32c1e99f350ee5c99908a5f5d72d1aeeab02f78c2e0181d585bd1880fa6",
"sha1_hash": "6483156e4577948cac5d2679eee862c76faed1c9",
"content_type": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
"size": 18510,
"created_date": "2019-01-03T00:00:00.000Z"
},
"metrics": {
"downloads": 0,
"previews": 0
}
}
],
"articles": [
{
"id": "10.1016/j.gloplacha.2019.01.007",
"title": "Flooding of the Caspian Sea at the intensification of Northern Hemisphere Glaciations",
"doi": "10.1016/j.gloplacha.2019.01.007",
"journal": {
"issn": "0921-8181",
"name": "Global and Planetary Change",
"url": "http://www.sciencedirect.com/science/journal/09218181"
}
}
],
"categories": [
{
"id": "http://com/vocabulary/OmniScience/Concept-170590667",
"label": "Geology"
},
{
"id": "http://data.elsevier.com/vocabulary/OmniScience/Concept-473860195",
"label": "Strontium Isotope"
}
],
"institutions": [ ],
"metrics": {
},
"available": true,
"related_links": [ ]
}
I am using $contributors.profile_id from above json to call new endpoint(invokeshttp) (https://api.xxx.com/profile/$.profile_id)
Json response for this
"contributors": [
{
“profile_id”:”cedferfiherhforhforf”
"first_name": “xxx”,
"last_name": "van Baak”,
“other_ids”:[] ,
“Other info”: “deeded” }
I have to call this endpoint depending upon number of object in contributor(let say we have 5 object in contributor ,so I have to call this endpoint 5 time)and combine these 5 response together
Then I have to merge the response(above response to the main response )
just an example:
EvaluateJsonPath to extract "id" into attribute, later join by this attribute
SplitJson to split your json by "contributors"
call endpoint
MergeContent merge by "id" and with count after SplitJson