How can I produce an aggregated result with subgroups in Clickhouse?

I want to be able to effectively produce an aggregated result from clickhouse table along with sort of an array with subgroups

So, let me give an example

Say, I have the following exemplary table

Starting with simple aggregation query, like

SELECT id, AVG(v1) AVG1, SUM(v2) SUM2 FROM table WHERE When > today() GROUP BY id
that will produce something like

I want extend the result with something like this

The rows per client field is aggregated with the same filters as the main query, but also applies extra group by to its results

I'm curios, if something like this is even possible in Clickhouse (and, if so, what's the most efficient way to do so), or do I have to use Join and then programmatically parse the results?

Joins are the best I've managed to accomplish so far, but the resulting query wasn't optimal, as I had to select the same data twice (note, that the table and queries I used are indeed exemplary, and the real ones has far more fields and more sophisticated aggregation), and the results are not quite the same to what I'm trying to accomplish

create table I_AM_TIRED_TO_WRITE_EXAMPLES_WHY_ARE_YOU_SO_LAZY(
  id 	String,
  client 	String,
  v1 	Int,
  v2 	Int,
When 	DateTime) Engine=Memory;

insert into I_AM_TIRED_TO_WRITE_EXAMPLES_WHY_ARE_YOU_SO_LAZY
select number, arrayJoin(['client1', 'client2', 'client3']),
     number%10, number%3, today()
from numbers(15);


SELECT
    id,
    avgMerge(AVG1s) AS AVG1,
    sum(SUM2s) AS SUM2,
    CAST(groupArray((client, (finalizeAggregation(AVG1s), SUM2s))), 'Map(String, Tuple(avg Float64, sum Int64))') AS r
FROM
(
    SELECT
        id,
        client,
        avgState(v1) AS AVG1s,
        SUM(v2) AS SUM2s
    FROM I_AM_TIRED_TO_WRITE_EXAMPLES_WHY_ARE_YOU_SO_LAZY
    WHERE When >= today()
    GROUP BY
        id,
        client
)
GROUP BY id
ORDER BY id ASC

┌─id─┬─AVG1─┬─SUM2─┬─r─────────────────────────────────────────────────┐
│ 0  │    0 │    0 │ {'client2':(0,0),'client3':(0,0),'client1':(0,0)} │
│ 1  │    1 │    3 │ {'client1':(1,1),'client2':(1,1),'client3':(1,1)} │
│ 10 │    0 │    3 │ {'client3':(0,1),'client2':(0,1),'client1':(0,1)} │
│ 11 │    1 │    6 │ {'client3':(1,2),'client2':(1,2),'client1':(1,2)} │
│ 12 │    2 │    0 │ {'client2':(2,0),'client3':(2,0),'client1':(2,0)} │
│ 13 │    3 │    3 │ {'client2':(3,1),'client3':(3,1),'client1':(3,1)} │
│ 14 │    4 │    6 │ {'client3':(4,2),'client2':(4,2),'client1':(4,2)} │
│ 2  │    2 │    6 │ {'client1':(2,2),'client3':(2,2),'client2':(2,2)} │
│ 3  │    3 │    0 │ {'client3':(3,0),'client2':(3,0),'client1':(3,0)} │
│ 4  │    4 │    3 │ {'client1':(4,1),'client3':(4,1),'client2':(4,1)} │
│ 5  │    5 │    6 │ {'client3':(5,2),'client2':(5,2),'client1':(5,2)} │
│ 6  │    6 │    0 │ {'client2':(6,0),'client3':(6,0),'client1':(6,0)} │
│ 7  │    7 │    3 │ {'client1':(7,1),'client2':(7,1),'client3':(7,1)} │
│ 8  │    8 │    6 │ {'client3':(8,2),'client2':(8,2),'client1':(8,2)} │
│ 9  │    9 │    0 │ {'client1':(9,0),'client3':(9,0),'client2':(9,0)} │
└────┴──────┴──────┴───────────────────────────────────────────────────┘