I need help with ranking of rows in one table.
+-----+-------+-------------+------------+-------+------+
| ID | group | typeInGroup | rankOfType | score | Rank |
+-----+-------+-------------+------------+-------+------+
| 1 | a | type1 | 1 | 40 | |
| 2 | a | type2 | 2 | 55 | |
| 3 | a | type1 | 1 | 20 | |
| 4 | b | type3 | 3 | 80 | |
| 5 | b | type2 | 2 | 60 | |
| 6 | b | type1 | 1 | 70 | |
| 7 | b | type1 | 1 | 70 | |
+-----+-------+-------------+------------+-------+------+
I am basically looking for solution which would give me order for last column "Rank".
Each "group" has up to 9 "typeInGroup" which are ranked by 1-9 in column "rankOfTypes". Each "typeInGroup" has "score". When i am calculating last column "Rank" i look at the "score" and "rankOfType" column.
The row with the higgest score should be ranked first unless there is row with "rankOfType" column that has lower value and score that is <= 15 than the score we have been looking at. Order of rows with same "score" and "rankOfType" is not important.
I should do this check for every single row in group and in the end end with something like this:
+-----+-------+-------------+------------+-------+------+
| ID | group | typeInGroup | rankOfType | score | Rank |
+-----+-------+-------------+------------+-------+------+
| 1 | a | type1 | 1 | 40 | 1 |
| 2 | a | type2 | 2 | 55 | 2 |
| 3 | a | type1 | 1 | 20 | 3 |
| 4 | b | type3 | 3 | 80 | 3 |
| 5 | b | type2 | 2 | 60 | 4 |
| 6 | b | type1 | 1 | 70 | 1 |
| 7 | b | type1 | 1 | 70 | 2 |
+-----+-------+-------------+------------+-------+------+
Any idea how to do this?
the CROSS APPLY query, checks for any rows that meet your special requirement, if exists, than that row will have higher priority
try it out with larger data set and verify the result
declare #tbl table
(
ID int,
Grp char,
typeInGrp varchar(5),
rankOfType int,
score int
)
insert into #tbl select 1, 'a', 'type1', 1, 40
insert into #tbl select 2, 'a', 'type2', 2, 55
insert into #tbl select 3, 'a', 'type1', 1, 20
insert into #tbl select 4, 'b', 'type3', 3, 80
insert into #tbl select 5, 'b', 'type2', 2, 60
insert into #tbl select 6, 'b', 'type1', 1, 70
insert into #tbl select 7, 'b', 'type1', 1, 70
select *,
[rank] = row_number() over (partition by Grp
order by case when cnt > 0 then 1 else 2 end,
score desc)
from #tbl t
cross apply
(
select cnt = count(*)
from #tbl x
where x.Grp = t.Grp
and x.ID <> t.ID
and x.rankOfType > t.rankOfType
and x.score - t.score <= 15
) s
order by ID
Related
I have a dataset looks like this
| Country | id |
-------------------
| a | 5 |
| a | 1 |
| a | 2 |
| b | 1 |
| b | 5 |
| b | 4 |
| b | 7 |
| c | 5 |
| c | 1 |
| c | 2 |
and i need a query which returns 2 random values from where country in ('a', 'c'):
| Country | id |
------------------
| a | 2 | -- Two random rows from Country = 'a'
| a | 1 |
| c | 1 |
| c | 5 | --Two random rows from Country = 'c'
This should work:
select Country, id from
(select Country,
id,
row_number() over(partition by Country order by rand()) as rn
from table_name
) t
where Country in ('a', 'c') and rn <= 2
Replace rand() with random() if you're using Postgres or newid() in SQL Server.
I have a situation where I am required to create a copy of the data of one table within itself with a different range of foreign key in one of the columns. For example:
--------------------------------------------------------------
|TYPES |ITEMS |SUBITEMS |
|--------------|----------------------|----------------------|
| ID | VALUE | ID | VALUE | TYPEID | ID | VALUE | ITEMID |
|----|---------|----|--------|--------|----|--------|--------|
| 1 | TYPE1 | 1 | ITEMA | 1 | 1 | SUB1 | 1 |
| 2 | TYPE2 | 2 | ITEMB | 1 | 2 | SUB2 | 2 |
| | | 3 | ITEMC | 1 | 3 | SUB3 | 3 |
| | | 4 | ITEMD | 2 | | | |
| | | 5 | ITEME | 2 | | | |
| | | 6 | ITEMF | 2 | | | |
--------------------------------------------------------------
Here I have to copy from SUBITEMS and insert back but with ITEMIDs that have TYPEID as 2 resulting in the following example:
--------------------------------------------------------------
|TYPES |ITEMS |SUBITEMS |
|--------------|----------------------|----------------------|
| ID | VALUE | ID | VALUE | TYPEID | ID | VALUE | ITEMID |
|----|---------|----|--------|--------|----|--------|--------|
| 1 | TYPE1 | 1 | ITEMA | 1 | 1 | SUB1 | 1 |
| 2 | TYPE2 | 2 | ITEMB | 1 | 2 | SUB2 | 2 |
| | | 3 | ITEMC | 1 | 3 | SUB3 | 3 |
| | | 4 | ITEMD | 2 | 4 | SUB1 | 4 |
| | | 5 | ITEME | 2 | 5 | SUB2 | 5 |
| | | 6 | ITEMF | 2 | 6 | SUB3 | 6 |
--------------------------------------------------------------
EDIT 2: If the amount of rows differ in either of the tables (4 Items while 3 SubItems or 3 Items while 4 SubItems) then only those rows should be considered that are enough for a 1:1 relation between the two tables (3 result since that is the least count among either) as shown in the following example.
--------------------------------------------------------------
|TYPES |ITEMS |SUBITEMS |
|--------------|----------------------|----------------------|
| ID | VALUE | ID | VALUE | TYPEID | ID | VALUE | ITEMID |
|----|---------|----|--------|--------|----|--------|--------|
| 1 | TYPE1 | 1 | ITEMA | 1 | 1 | SUB1 | 1 |
| 2 | TYPE2 | 2 | ITEMB | 1 | 2 | SUB2 | 2 |
| | | 3 | ITEMC | 1 | 3 | SUB3 | 3 |
| | | 4 | ITEMD | 2 | 4 | SUB1 | 4 |
| | | 5 | ITEME | 2 | 5 | SUB2 | 5 |
| | | 6 | ITEMF | 2 | 6 | SUB3 | 6 |
| | | 7 | ITEMG | 2 | | | |
--------------------------------------------------------------
Of course the actual data isn't as simple and has many other types and items n subitems and the required IDs would be missing some sequence like 10001, 10008, 40042, etc with many other columns all defining what data is being copied and which IDs need to be thrown over them. It's just the matter of how each data row obtained should get mapped 1:1 to each ID obtained (assuming both as if in their own temp tables before the moment of this merger). Following is a sample of what I am able to do so far:
CREATE TABLE #SubItemsTemp (Value VARCHAR(100))
CREATE TABLE #ItemIDsTemp (TypeID INT)
INSERT INTO #SubItemsTemp (Value)
SELECT
SI.Value
FROM
SubItems SI
JOIN Items IT ON SI.ItemID = IT.ID
WHERE
IT.TypeID = 1
INSERT INTO #ItemIDsTemp(Value)
SELECT IT.ID
FROM Items IT
WHERE IT.TypeID = 2
--What next?
EDIT 1: Forgot to mention the actual question line... How to insert them together into the SUBITEMS table such that the second example comes to fruition?
Footnote: This is a extreme simplification of the actual queries that have several joins to get to "TYPE"
Try this query. Query assumes that ID column in SUBITEMS table is identity and will work only with TypeId's 1 and 2
declare #TYPES table(ID int, VALUE varchar(100))
declare #ITEMS table(ID int, VALUE varchar(100), TYPEID int)
declare #SUBITEMS table(ID int identity(1,1), VALUE varchar(100), ITEMID int)
insert into #TYPES values (1, 'TYPE1'), (2, 'TYPE2')
insert into #ITEMS values (1, 'ITEMA', 1), (2, 'ITEMB', 1), (3, 'ITEMC', 1), (4, 'ITEMD', 2), (5, 'ITEME', 2), (6, 'ITEMF', 2), (7, 'ITEMG', 2)
insert into #SUBITEMS values ('SUB1', 1), ('SUB2', 2), ('SUB3', 3)
; with cte_1 as (
select
s.VALUE, rn = row_number() over (order by i.ID)
from
#ITEMS i
join #SUBITEMS s on s.ITEMID = i.ID
where
i.TYPEID = 1
)
, cte_2 as (
select
ID, rn = row_number() over (order by ID)
from
#ITEMS
where
TYPEID = 2
)
insert into #SUBITEMS
select
a.VALUE, b.ID
from
cte_1 a
join cte_2 b on a.rn = b.rn
select * from #SUBITEMS
Output
ID Value ItemId
------------------
1 SUB1 1
2 SUB2 2
3 SUB3 3
4 SUB1 4
5 SUB2 5
6 SUB3 6
I am trying to find a way to count based on groups and I was not able to figure out a way without having to use a Cursor. Since using a Cursor will be relatively slow I was hoping there might be a better way.
Simplified the data is structured as follows:
+----+--------+-------+--------+
| ID | NEXTID | RowNo | Status |
+----+--------+-------+--------+
| 1 | 2 | 1 | 1 |
| 2 | 3 | 1 | 1 |
| 3 | 4 | 1 | 0 |
| 4 | | 1 | 1 |
| 1 | 2 | 2 | 0 |
| 2 | 3 | 2 | 1 |
| 3 | 4 | 2 | 1 |
| 4 | | 2 | 1 |
| 1 | 2 | 3 | 1 |
| 2 | 3 | 3 | 1 |
| 3 | 4 | 3 | 1 |
| 4 | | 3 | 1 |
+----+--------+-------+--------+
I now want to COUNT the Status column in groups resulting in:
+-----+-------------+
| Row | StatusCount |
+-----+-------------+
| 1 | 2 |
| 1 | 1 |
| 2 | 3 |
| 3 | 4 |
+-----+-------------+
For Testing purposes I creating the following code:
SELECT
ID,
NEXTID,
RowNo,
Status,
LEAD(ID,1,0)
OVER (ORDER BY RowNo,ID) AS LEADER
INTO #TestTable
FROM
(
VALUES
(1, 2, 1, 1),
(2, 3, 1, 1),
(3, 4, 1, 0),
(4, '', 1, 1),
(1, 2, 2, 0),
(2, 3, 2, 1),
(3, 4, 2, 1),
(4, '', 2, 1),
(1, 2, 3, 1),
(2, 3, 3, 1),
(3, 4, 3, 1),
(4, '', 3, 1)
)
AS TestTable(
ID,
NEXTID,
RowNo,
Status);
GO
SELECT
RowNo,
Count(Status) AS StatusCount
FROM #TestTable
WHERE
Status = 1
GROUP BY
RowNo
This results in
+-----+-------------+
| Row | StatusCount |
+-----+-------------+
| 1 | 3 |
| 2 | 3 |
| 3 | 4 |
+-----+-------------+
Not separating the first row. I do realise that I need another GROUP BY condition but I can not figure out the appropriate condition.
Thank you very much for your help. If this has already been answered I was unable to find the topic and hints will also be appreciated.
With kind regards
freubau
You can identify the groups by doing a cumulative sum of the zeros up to each number. Then, the rest is just aggregation:
select rowno, count(*)
from (select t.*,
sum(case when status = 0 then 1 else 0 end) over (partition by rowno order by id) as grp
from #TestTable t
) t
where status = 1
group by rowno, grp
order by rowno, grp;
Here is a rex tester for it.
I want to convert columns to rows in SQL Server:
Id Value Jan1 Jan2
----------------------
1 2 25 35
2 5 45 45
result should be
Id Value Month 1 2
----------------------
1 2 Jan 25 35
2 5 Jan 45 45
How can I get this result? Anyone please help
What you are asking seems a little strange. If I extend your example to include columns for Feb1 and Feb2, then I see two options for transposing your columns from this:
+----+-------+------+------+------+------+
| Id | Value | Jan1 | Jan2 | Feb1 | feb2 |
+----+-------+------+------+------+------+
| 1 | 2 | 25 | 35 | 15 | 28 |
| 2 | 5 | 45 | 45 | 60 | 60 |
+----+-------+------+------+------+------+
Transpose just the month part:
select Id, Value, MonthName, MonthValue1, MonthValue2
from t
cross apply (values ('Jan',Jan1,Jan2),('Feb',Feb1,Feb2)
) v (MonthName,MonthValue1,MonthValue2)
returns:
+----+-------+-----------+-------------+-------------+
| Id | Value | MonthName | MonthValue1 | MonthValue2 |
+----+-------+-----------+-------------+-------------+
| 1 | 2 | Jan | 25 | 35 |
| 1 | 2 | Feb | 15 | 28 |
| 2 | 5 | Jan | 45 | 45 |
| 2 | 5 | Feb | 60 | 60 |
+----+-------+-----------+-------------+-------------+
Or completely transpose the month columns like so:
select Id, Value, MonthName, MonthValue
from t
cross apply (values ('Jan1',Jan1),('Jan2',Jan2),('Feb1',Feb1),('Feb2',Feb2)
) v (MonthName,MonthValue)
returns:
+----+-------+-----------+------------+
| Id | Value | MonthName | MonthValue |
+----+-------+-----------+------------+
| 1 | 2 | Jan1 | 25 |
| 1 | 2 | Jan2 | 35 |
| 1 | 2 | Feb1 | 15 |
| 1 | 2 | Feb2 | 28 |
| 2 | 5 | Jan1 | 45 |
| 2 | 5 | Jan2 | 45 |
| 2 | 5 | Feb1 | 60 |
| 2 | 5 | Feb2 | 60 |
+----+-------+-----------+------------+
rextester demo: http://rextester.com/KZV45690
This would appear to be:
select Id, Value, 'Jan' as [month], Jan1 as [1], Jan2 as [2]
from t;
You are basically just adding another column to the output.
I don't recommend using numbers as column names, nor SQL Server keywords such as month.
Here is an option that you won't have to specify up to 365 fields
Declare #YourTable table (Id int,Value int,Jan1 int,Jan2 int,Feb1 int, Feb2 int)
Insert Into #YourTable values
(1, 2, 25, 35, 100, 101),
(2, 5, 45, 45, 200, 201)
Select [Id],[Value],[Month],[1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31]
From (
Select A.Id
,A.Value
,[Month] = Left(C.Item,3)
,[Col] = substring(C.Item,4,5)
,[Measure] = C.Value
From #YourTable A
Cross Apply (Select XMLData = cast((Select A.* for XML Raw) as xml)) B
Cross Apply (
Select Item = attr.value('local-name(.)','varchar(100)')
,Value = attr.value('.','int')
From B.XMLData.nodes('/row') as A(r)
Cross Apply A.r.nodes('./#*') AS B(attr)
Where attr.value('local-name(.)','varchar(100)') not in ('ID','Value')
) C
) A
Pivot (sum(Measure) For [Col] in ([1],[2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26],[27],[28],[29],[30],[31]) ) p
Returns
I've got a table of temperature samples over time from several sources and I want to find the minimum, maximum, and average temperatures across all sources at set time intervals. At first glance this is easily done like so:
SELECT MIN(temp), MAX(temp), AVG(temp) FROM samples GROUP BY time;
However, things become much more complicated (to the point of where I'm stumped!) if sources drop in and out and rather than ignoring the missing sources during the intervals in question I want to use the sources' last know temperatures for the missing samples. Using datetimes and constructing intervals (say every minute) across samples unevenly distributed over time further complicates things.
I think it should be possible to create the results I want by doing a self-join on the samples table where the time from the first table is greater than or equal to the time of the second table and then calculating aggregate values for rows grouped by source. However, I'm stumped about how to actually do this.
Here's my test table:
+------+------+------+
| time | source | temp |
+------+------+------+
| 1 | a | 20 |
| 1 | b | 18 |
| 1 | c | 23 |
| 2 | b | 21 |
| 2 | c | 20 |
| 2 | a | 18 |
| 3 | a | 16 |
| 3 | c | 13 |
| 4 | c | 15 |
| 4 | a | 4 |
| 4 | b | 31 |
| 5 | b | 10 |
| 5 | c | 16 |
| 5 | a | 22 |
| 6 | a | 18 |
| 6 | b | 17 |
| 7 | a | 20 |
| 7 | b | 19 |
+------+------+------+
INSERT INTO samples (time, source, temp) VALUES (1, 'a', 20), (1, 'b', 18), (1, 'c', 23), (2, 'b', 21), (2, 'c', 20), (2, 'a', 18), (3, 'a', 16), (3, 'c', 13), (4, 'c', 15), (4, 'a', 4), (4, 'b', 31), (5, 'b', 10), (5, 'c', 16), (5, 'a', 22), (6, 'a', 18), (6, 'b', 17), (7, 'a', 20), (7, 'b', 19);
To do my min, max and avg calculations, I want an intermediate table that looks like this:
+------+------+------+
| time | source | temp |
+------+------+------+
| 1 | a | 20 |
| 1 | b | 18 |
| 1 | c | 23 |
| 2 | b | 21 |
| 2 | c | 20 |
| 2 | a | 18 |
| 3 | a | 16 |
| 3 | b | 21 |
| 3 | c | 13 |
| 4 | c | 15 |
| 4 | a | 4 |
| 4 | b | 31 |
| 5 | b | 10 |
| 5 | c | 16 |
| 5 | a | 22 |
| 6 | a | 18 |
| 6 | b | 17 |
| 6 | c | 16 |
| 7 | a | 20 |
| 7 | b | 19 |
| 7 | c | 16 |
+------+------+------+
The following query is getting me close to what I want but it takes the temperature value of the source's first result, rather than the most recent one at the given time interval:
SELECT s.dt as sdt, s.mac, ss.temp, MAX(ss.dt) as maxdt FROM (SELECT DISTINCT dt FROM samples) AS s CROSS JOIN samples AS ss WHERE s.dt >= ss.dt GROUP BY sdt, mac HAVING maxdt <= s.dt ORDER BY sdt ASC, maxdt ASC;
+------+------+------+-------+
| sdt | mac | temp | maxdt |
+------+------+------+-------+
| 1 | a | 20 | 1 |
| 1 | c | 23 | 1 |
| 1 | b | 18 | 1 |
| 2 | a | 20 | 2 |
| 2 | c | 23 | 2 |
| 2 | b | 18 | 2 |
| 3 | b | 18 | 2 |
| 3 | a | 20 | 3 |
| 3 | c | 23 | 3 |
| 4 | a | 20 | 4 |
| 4 | c | 23 | 4 |
| 4 | b | 18 | 4 |
| 5 | a | 20 | 5 |
| 5 | c | 23 | 5 |
| 5 | b | 18 | 5 |
| 6 | c | 23 | 5 |
| 6 | a | 20 | 6 |
| 6 | b | 18 | 6 |
| 7 | c | 23 | 5 |
| 7 | b | 18 | 7 |
| 7 | a | 20 | 7 |
+------+------+------+-------+
Update: chadhoc (great name, by the way!) gives a nice solution that unfortunately does not work in MySQL, since it does not support the FULL JOIN he uses. Luckily, I believe a simple UNION is an effective replacement:
-- Unify the original samples with the missing values that we've calculated
(
SELECT time, source, temp
FROM samples
)
UNION
( -- Pull all the time/source combinations that we are missing from the sample set, along with the temp
-- from the last sampled interval for the same time/source combination if we do not have one
SELECT a.time, a.source, (SELECT t2.temp FROM samples AS t2 WHERE t2.time < a.time AND t2.source = a.source ORDER BY t2.time DESC LIMIT 1) AS temp
FROM
( -- All values we want to get should be a cross of time/temp
SELECT t1.time, s1.source
FROM
(SELECT DISTINCT time FROM samples) AS t1
CROSS JOIN
(SELECT DISTINCT source FROM samples) AS s1
) AS a
LEFT JOIN samples s
ON a.time = s.time
AND a.source = s.source
WHERE s.source IS NULL
)
ORDER BY time, source;
Update 2: MySQL gives the following EXPLAIN output for chadhoc's code:
+----+--------------------+------------+------+---------------+------+---------+------+------+-----------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+--------------------+------------+------+---------------+------+---------+------+------+-----------------------------+
| 1 | PRIMARY | temp | ALL | NULL | NULL | NULL | NULL | 18 | |
| 2 | UNION | <derived4> | ALL | NULL | NULL | NULL | NULL | 21 | |
| 2 | UNION | s | ALL | NULL | NULL | NULL | NULL | 18 | Using where |
| 4 | DERIVED | <derived6> | ALL | NULL | NULL | NULL | NULL | 3 | |
| 4 | DERIVED | <derived5> | ALL | NULL | NULL | NULL | NULL | 7 | |
| 6 | DERIVED | temp | ALL | NULL | NULL | NULL | NULL | 18 | Using temporary |
| 5 | DERIVED | temp | ALL | NULL | NULL | NULL | NULL | 18 | Using temporary |
| 3 | DEPENDENT SUBQUERY | t2 | ALL | NULL | NULL | NULL | NULL | 18 | Using where; Using filesort |
| NULL | UNION RESULT | <union1,2> | ALL | NULL | NULL | NULL | NULL | NULL | Using filesort |
+----+--------------------+------------+------+---------------+------+---------+------+------+-----------------------------+
I was able to get Charles' code working like so:
SELECT T.time, S.source,
COALESCE(
D.temp,
(
SELECT temp FROM samples
WHERE source = S.source AND time = (
SELECT MAX(time)
FROM samples
WHERE
source = S.source
AND time < T.time
)
)
) AS temp
FROM (SELECT DISTINCT time FROM samples) AS T
CROSS JOIN (SELECT DISTINCT source FROM samples) AS S
LEFT JOIN samples AS D
ON D.source = S.source AND D.time = T.time
Its explanation is:
+----+--------------------+------------+------+---------------+------+---------+------+------+-----------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+--------------------+------------+------+---------------+------+---------+------+------+-----------------+
| 1 | PRIMARY | <derived5> | ALL | NULL | NULL | NULL | NULL | 3 | |
| 1 | PRIMARY | <derived4> | ALL | NULL | NULL | NULL | NULL | 7 | |
| 1 | PRIMARY | D | ALL | NULL | NULL | NULL | NULL | 18 | |
| 5 | DERIVED | temp | ALL | NULL | NULL | NULL | NULL | 18 | Using temporary |
| 4 | DERIVED | temp | ALL | NULL | NULL | NULL | NULL | 18 | Using temporary |
| 2 | DEPENDENT SUBQUERY | temp | ALL | NULL | NULL | NULL | NULL | 18 | Using where |
| 3 | DEPENDENT SUBQUERY | temp | ALL | NULL | NULL | NULL | NULL | 18 | Using where |
+----+--------------------+------------+------+---------------+------+---------+------+------+-----------------+
I think you'll get better performance making use of the ranking/windowing functions in mySql, but unfortunately I do not know those as well as the TSQL implementation. Here is an ANSI compliant solution that will work though:
-- Full join across the sample set and anything missing from the sample set, pulling the missing temp first if we do not have one
select coalesce(c1.[time], c2.[time]) as dt, coalesce(c1.source, c2.source) as source, coalesce(c2.temp, c1.temp) as temp
from samples c1
full join ( -- Pull all the time/source combinations that we are missing from the sample set, along with the temp
-- from the last sampled interval for the same time/source combination if we do not have one
select a.time, a.source,
(select top 1 t2.temp from samples t2 where t2.time < a.time and t2.source = a.source order by t2.time desc) as temp
from
( -- All values we want to get should be a cross of time/samples
select t1.[time], s1.source
from
(select distinct [time] from samples) as t1
cross join
(select distinct source from samples) as s1
) a
left join samples s
on a.[time] = s.time
and a.source = s.source
where s.source is null
) c2
on c1.time = c2.time
and c1.source = c2.source
order by dt, source
I know this looks complicated, but it's formatted to explain itself...
It should work... Hope you only have three sources... If you have an arbitrary number of sources than this won't work... In that case see the second query...
EDIT: Removed first attempt
EDIT: If you don't know the sources ahead of time, you'll have to do something where you create an intermediate result set that "Fills in" the missing values..
something like this:
2nd EDIT: Removed need for Coalesce by moving logic to retrieve most recent temp reading for each source from Select clause into the Join condition.
Select T.Time, Max(Temp) MaxTemp,
Min(Temp) MinTemp, Avg(Temp) AvgTemp
From
(Select T.TIme, S.Source, D.Temp
From (Select Distinct Time From Samples) T
Cross Join
(Select Distinct Source From Samples) S
Left Join Samples D
On D.Source = S.Source
And D.Time =
(Select Max(Time)
From Samples
Where Source = S.Source
And Time <= T.Time)) Z
Group By T.Time