Jolt Transform to "tabular format" - json

Question

I'm using Nifi to pull in some Meteomatics API data and store it in our SQL Datawarehouse.
Nifi architecture is mostly set-up, but I would like to convert the JSON response of the API call to row/column format. I get the feeling this should be possible with a single shift operation, but I'm struggling to get multiple levels of data into my output.
See sample input (single set of coordinates, and same three parameters can be assumed):
{
"version": "3.0",
"user": "USERNAME",
"dateGenerated": "2022-09-01T07:52:43Z",
"status": "OK",
"data": [
{
"parameter": "precip_24h:mm",
"coordinates": [
{
"lat": 123,
"lon": 456,
"dates": [
{
"date": "2022-09-01T00:00:00Z",
"value": 11.6
},
{
"date": "2022-09-02T00:00:00Z",
"value": 4.49
},
{
"date": "2022-09-03T00:00:00Z",
"value": 7.79
},
{
"date": "2022-09-04T00:00:00Z",
"value": 6.6
},
{
"date": "2022-09-05T00:00:00Z",
"value": 12.7
},
{
"date": "2022-09-06T00:00:00Z",
"value": 2.01
}
]
}
]
},
{
"parameter": "heavy_rain_warning_24h:idx",
"coordinates": [
{
"lat": 123,
"lon": 456,
"dates": [
{
"date": "2022-09-01T00:00:00Z",
"value": 0
},
{
"date": "2022-09-02T00:00:00Z",
"value": 0
},
{
"date": "2022-09-03T00:00:00Z",
"value": 0
},
{
"date": "2022-09-04T00:00:00Z",
"value": 0
},
{
"date": "2022-09-05T00:00:00Z",
"value": 0
},
{
"date": "2022-09-06T00:00:00Z",
"value": 0
}
]
}
]
},
{
"parameter": "t_0m:C",
"coordinates": [
{
"lat": 123,
"lon": 456,
"dates": [
{
"date": "2022-09-01T00:00:00Z",
"value": 27.2
},
{
"date": "2022-09-02T00:00:00Z",
"value": 27.3
},
{
"date": "2022-09-03T00:00:00Z",
"value": 27.3
},
{
"date": "2022-09-04T00:00:00Z",
"value": 27.3
},
{
"date": "2022-09-05T00:00:00Z",
"value": 27.3
},
{
"date": "2022-09-06T00:00:00Z",
"value": 28.2
}
]
}
]
}
]
}
Desired Output:
[
{
"date": "2022-09-01T00:00:00Z",
"value": 11.6,
"parameter": "precip_24h:mm",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-02T00:00:00Z",
"value": 4.49,
"parameter": "precip_24h:mm",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-03T00:00:00Z",
"value": 7.79,
"parameter": "precip_24h:mm",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-04T00:00:00Z",
"value": 6.6,
"parameter": "precip_24h:mm",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-05T00:00:00Z",
"value": 12.7,
"parameter": "precip_24h:mm",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-06T00:00:00Z",
"value": 2.01,
"parameter": "precip_24h:mm",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-01T00:00:00Z",
"value": 0,
"parameter": "heavy_rain_warning_24h:idx",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-02T00:00:00Z",
"value": 0,
"parameter": "heavy_rain_warning_24h:idx",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
},
{
"date": "2022-09-03T00:00:00Z",
"value": 0,
"parameter": "heavy_rain_warning_24h:idx",
"lat": "123",
"lon": "456",
"dateGenerated": "2022-09-01T07:52:43Z"
etc...
This way I can put in a simple avro converter and push directly to a SQL table with columns "date,value,parameter,lat,lon,dateGenerated".
Currently, I've gotten to this response:
[
{
"date": "2022-09-01T00:00:00Z",
"value": 11.6
},
{
"date": "2022-09-02T00:00:00Z",
"value": 4.49
},
{
"date": "2022-09-03T00:00:00Z",
"value": 7.79
}
etc...
Using the following spec (loop through at the lowest level, return the data and put in a big array):
[
{
"operation": "shift",
"spec": {
"data": {
"*": {
"coordinates": {
"*": {
"dates": {
"*": {
"#": "[]"
}
}
}
}
}
}
}
}
]
Including dateGenerated/other fields from further up the tree is giving me difficulty. I wanted to include something like this (traverse 5 levels up, get the DataGenerated Field and map it to DateGen?). This doesn't work, and I'm a little lost:
[
{
"operation": "shift",
"spec": {
"data": {
"*": {
"coordinates": {
"*": {
"dates": {
"*": {
"#": "[]",
"#5.DateGenerated":"[].DateGen"
}
}
}
}
}
}
}
}
]

Answer 1

You can use two succesive shift transformations such as
[
{
// distinguish each objects by some common values
"operation": "shift",
"spec": {
"data": {
"*": {
"coo*": {
"*": {
"da*": {
"*": {
"#": "#(5,parameter)[&1]", // separate the object by their presumed id values(parameter) after going five levels up the tree to reach its level
"#(2,lat)": "#(5,parameter)[&1].lat", // go two levels up the tree to reach the level of "lat" and "lon"
"#(2,lon)": "#(5,parameter)[&1].lon",
"#(4,parameter)": "#(5,parameter)[&1].parameter",
"#(6,dateGenerated)": "#(5,parameter)[&1].dateGenerated"
}
}
}
}
}
}
}
},
{
// get rid of labels and square brackets
"operation": "shift",
"spec": {
"*": {
"*": ""
}
}
}
]