How to group by single field and return more values together - group-by

Question

I'm starting to use apache druid but having some difficult to run native queries (and some SQL too).
1- Is it possible to groupBy a single column while also returning more channels?
2- How could I groupBy a single column, while returning different grouped itens on same query/row ?
Query I'm trying to use:
{
"queryType": "groupBy",
"dataSource": "my-data-source",
"granularity": "all",
"intervals": ["2022-06-27T03:00:00.000Z/2022-06-28T03:00:00.000Z"],
"context:": { "timeout: 30000 },
"dimensions": ["userId"],
"filter": {
"type": "and",
"fields": [
{
"type": "or",
"fields": [{...}]
}
]
},
"aggregations": [
{
"type": "count",
"name": "count"
}
]
}
Tried to add a filtered type inside aggregations:[] but 0 changes happened.
"aggregations": [
{
"type: "count",
"name": "count"
},
{
"type": "filtered",
"filter": {
"type": "selector",
"dimension": "block_id",
"value": "block1"
},
"aggregator": {
"type": "count",
"name": "block1",
"fieldName": "block_id"
}
}
]
Grouping Aggregator also didn't work.
"aggregations": [
{
"type": "count",
"name": "count"
},
{
"type": "grouping",
"name": "groupedData",
"groupings": ["block_id"]
}
],
Below is the image illustrating the results I'm trying to achieve.

Answer 1

Not sure yet how to get the results in the format you want, but as a start, something like this might be a step:
{
"queryType": "groupBy",
"dataSource": {
"type": "table",
"name": "dataTest"
},
"intervals": {
"type": "intervals",
"intervals": [
"-146136543-09-08T08:23:32.096Z/146140482-04-24T15:36:27.903Z"
]
},
"filter": null,
"granularity": {
"type": "all"
},
"dimensions": [
{
"type": "default",
"dimension": "d2_ts2",
"outputType": "STRING"
},
{
"type": "default",
"dimension": "d3_email",
"outputType": "STRING"
}
],
"aggregations": [
{
"type": "count",
"name": "myCount",
}
],
"descending": false
}

Answer 2

I'm curious, what is the use case?
Using a SQL query you can do it this way:
SELECT UserID,
sum(1) FILTER (WHERE BlockId = 'block1') as Block1,
sum(1) FILTER (WHERE BlockId = 'block2') as Block2,
sum(1) FILTER (WHERE BlockId = 'block3') as Block3
FROM inline_data
GROUP BY 1
The Native Query for this (from the explain) is:
{
"queryType": "topN",
"dataSource": {
"type": "table",
"name": "inline_data"
},
"virtualColumns": [
{
"type": "expression",
"name": "v0",
"expression": "1",
"outputType": "LONG"
}
],
"dimension": {
"type": "default",
"dimension": "UserID",
"outputName": "d0",
"outputType": "STRING"
},
"metric": {
"type": "dimension",
"previousStop": null,
"ordering": {
"type": "lexicographic"
}
},
"threshold": 101,
"intervals": {
"type": "intervals",
"intervals": [
"-146136543-09-08T08:23:32.096Z/146140482-04-24T15:36:27.903Z"
]
},
"filter": null,
"granularity": {
"type": "all"
},
"aggregations": [
{
"type": "filtered",
"aggregator": {
"type": "longSum",
"name": "a0",
"fieldName": "v0",
"expression": null
},
"filter": {
"type": "selector",
"dimension": "BlockId",
"value": "block1",
"extractionFn": null
},
"name": "a0"
},
{
"type": "filtered",
"aggregator": {
"type": "longSum",
"name": "a1",
"fieldName": "v0",
"expression": null
},
"filter": {
"type": "selector",
"dimension": "BlockId",
"value": "block2",
"extractionFn": null
},
"name": "a1"
},
{
"type": "filtered",
"aggregator": {
"type": "longSum",
"name": "a2",
"fieldName": "v0",
"expression": null
},
"filter": {
"type": "selector",
"dimension": "BlockId",
"value": "block3",
"extractionFn": null
},
"name": "a2"
}
],
"postAggregations": [],
"context": {
"populateCache": false,
"sqlOuterLimit": 101,
"sqlQueryId": "bb92e899-c127-49b0-be1b-d4b38909d166",
"useApproximateCountDistinct": false,
"useApproximateTopN": false,
"useCache": false,
"useNativeQueryExplain": true
},
"descending": false
}