Translating idempotent merge example not working - sql

Question

How can I get this merge statement to handle (just inserts for now) in an idempotent way? I would like to follow this rough example / template proposed by databricks.
The example data contains a base set with 2 rows for 2 dates. The change set contains 2 rows for 2 dates, with 1 row being a duplicate, and 1 row being "new" data that should be "merged".
Some data
create table #baseset
(
Date varchar(30),
ID varchar(30),
State varchar(30),
Count varchar(30)
)
insert into #baseset values('2/7/2023', 'A', 'A', null)
insert into #baseset values('2/6/2023', 'A', 'A', null)
create table #changeset
(
Date varchar(30),
ID varchar(30),
State varchar(30),
Count varchar(30)
)
insert into #changeset values('2/8/2023', 'A', 'A', null)
insert into #changeset values('2/7/2023', 'A', 'A', null)
Mockup MERGE
(
-- These rows will either UPDATE the existing data or INSERT new data that does not yet exist
SELECT
#changeset.ID as mergeKey, #changeset.*
FROM
#changeset
UNION ALL
-- These rows will INSERT data of existing rows
-- Setting the mergeKey to NULL forces these rows to NOT MATCH and be INSERTed.
SELECT
NULL as mergeKey,
#changeset.*
FROM
#changeset
JOIN #baseset ON #changeset.ID = #baseset.ID
WHERE
#changeset.Date <> #baseset.Date
)
Yielding
+--------+--------+---+-----+-----+
|mergeKey| Date| ID|State|Count|
+--------+--------+---+-----+-----+
| A|2/8/2023| A| A| null|
| A|2/7/2023| A| A| null|
| null|2/8/2023| A| A| null|
| null|2/7/2023| A| A| null|
| null|2/8/2023| A| A| null|
+--------+--------+---+-----+-----+
Expected
+--------+--------+---+-----+-----+
|mergeKey| Date| ID|State|Count|
+--------+--------+---+-----+-----+
| A|2/8/2023| A| A| null|
| A|2/7/2023| A| A| null|
| null|2/8/2023| A| A| null|
+--------+--------+---+-----+-----+
Full Merge Statement
Its the same query as above.
MERGE INTO #baseset
USING (
-- These rows will either UPDATE the existing data or INSERT new data that does not yet exist
SELECT
#changeset.ID as mergeKey, #changeset.*
FROM
#changeset
UNION ALL
-- These rows will INSERT data of existing rows
-- Setting the mergeKey to NULL forces these rows to NOT MATCH and be INSERTed.
SELECT
NULL as mergeKey,
#changeset.*
FROM
#changeset
JOIN #baseset ON #changeset.ID = #baseset.ID
WHERE
#changeset.Date <> #baseset.Date
) staged_updates
ON #baseset.id = mergeKey
WHEN NOT MATCHED BY TARGET THEN
INSERT (Date, ID, State, Count)
VALUES (staged_updates.Date, staged_updates.ID, staged_updates.State, staged_updates.Count)
;

Answer 1

It sounds like you're kinda mixing up your terminology, but anyways.
The canonical merge example with your data:
drop table #baseset
drop table #changeset
go
create table #baseset
(
Date varchar(30),
ID varchar(30),
State varchar(30),
Count varchar(30)
)
insert into #baseset values('2/7/2023', 'A', 'A', null)
insert into #baseset values('2/6/2023', 'A', 'A', null)
create table #changeset
(
Date varchar(30),
ID varchar(30),
State varchar(30),
Count varchar(30)
)
insert into #changeset values('2/8/2023', 'A', 'A', 3)
insert into #changeset values('2/7/2023', 'A', 'A', 4)
;merge #baseset as t
using #changeset as s
ON s.date = t.date
and s.ID = t.ID
when matched then update
set state = s.state
, count = s.count
when not matched by target then insert
(date, id, state, count)
values (s.date, s.id, s.state, s.count)
;
select *
from #baseset
This does a so called upsert which updates #baseset from the #changeset when ID and date matches, and when not matched by #baseset (ie. missing), it inserts the missing rows