I want to join table 1 with table2 twice becuase I need to get the first minimum record and the second minimum. However, I can only think of using a cte to get the second minimum record. Is there a better way to do it?
Here is the table table:
I want to join Member with output table FirstRunID whose Output value is 1 and second RunID whose Output value is 0
current code I am using:
select memid, a.runid as aRunid,b.runid as bRunid
into #temp
from FirstTable m inner join
(select min(RunID), MemID [SecondTable] where ouput=1 group by memid)a on m.memid=a.memid
inner join (select RunID, MemID [SecondTable] where ouput=0 )b on m.memid=a.memid and b.runid>a.runid
with cte as
(
select row_number() over(partition by memid, arunid order by brunid ),* from #temp
)
select * from cte where n=1
You can use outer apply operator for this:
select * from t1
outer apply(select top 1 t2.runid from t2
where t1.memid = t2.memid and t2.output = 1 order by t2.runid) as oa1
outer apply(select top 1 t2.runid from t2
where t1.memid = t2.memid and t2.output = 0 order by t2.runid) as oa2
You can do this with conditional aggregation. Based on your results, you don't need the first table:
select t2.memid,
max(case when output = 1 and seqnum = 1 then runid end) as OutputValue1,
max(case when output = 0 and seqnum = 2 then runid end) as OutputValue2
from (select t2.*,
row_number() over (partition by memid, output order by runid) a seqnum
from t2
) t2
group by t2.memid;
declare #FirstTable table
(memid int, name varchar(20))
insert into #firsttable
values
(1,'John'),
(2,'Victor')
declare #secondtable table
(runid int,memid int,output int)
insert into #secondtable
values
(1,1,0),(1,2,1),(2,1,1),(2,2,1),(3,1,1),(3,2,0),(4,1,0),(4,2,0)
;with cte as
(
SELECT *, row_number() over (partition by memid order by runid) seq --sequence
FROM #SECONDTABLE T
where t.output = 1
union all
SELECT *, row_number() over (partition by memid order by runid) seq --sequence
FROM #SECONDTABLE T
where t.output = 0 and
t.runid > (select min(x.runid) from #secondtable x where x.memid = t.memid and x.output = 1 group by x.memid) --lose any O output record where there is no prior 1 output record
)
select cte1.memid,cte1.runid,cte2.runid from cte cte1
join cte cte2 on cte2.memid = cte1.memid and cte2.seq = cte1.seq
where cte1.seq = 1 --remove this test if you want matched pairs
and cte1.output = 1 and cte2.output = 0
Related
I want to count number fullvisitorID where rank in /page_y is higher then rank in page_x. So in this case result would be 1, only 111
fullvisitorID
rank
page
111
1
/page_x
111
2
/page_y
222
1
/page_x
222
2
/page_x
333
2
/page_x
333
1
/page_y
Consider below approach
select count(*) from (
select distinct fullvisitorID
from your_table
qualify max(if(page='/page_y',rank,null)) over win > max(if(page='/page_x',rank,null)) over win
window win as (partition by fullvisitorID)
)
SELECT COUNTIF(page = '/page_y') cnt FROM (
SELECT * FROM sample_table WHERE page IN ('/page_x', '/page_y')
QUALIFY ROW_NUMBER() OVER (PARTITION BY fullvisitorID ORDER BY rank DESC) = 1
);
for count you can use COUNT and GROUP BY
SELECT fullvisitorID, COUNT(fullvisitorID), Page FROM table t1
WHERE rank = (SELECT MAX(t2.rank) FROM table t2 WHERE t2.fullvisitorID = t1.fullvisitorID)
Group By fullvisitorID, Page
You can apply a SELF JOIN between the two tables, by matching on the "fullvisitorID" field, then force
the first table to have "page_y" values
the second table to have "page_x" values
rank of the first table to have higher rank of the second table
SELECT *
FROM tab t1
INNER JOIN tab t2
ON t1.fullvisitorID = t2.fullvisitorID
AND t1.page = '/page_y'
AND t2.page = '/page_x'
AND t1.rank > t2.rank
Table separation approach:
DECLARE #t1 TABLE ( fullvisitorID INT, [rank] INTEGER,[page] VARCHAR (max)) --here where page = x
DECLARE #t2 TABLE ( fullvisitorID INT, [rank] INTEGER,[page] VARCHAR (max)) --here where page = y
INSERT INTO #t1 SELECT * FROM #test t WHERE t.[page] LIKE '/page_x'
INSERT INTO #t2 SELECT * FROM #test t WHERE t.[page] LIKE '/page_y'
SELECT COUNT(*) FROM #t1 INNER JOIN #t2 ON [#t1].fullvisitorID = [#t2].fullvisitorID WHERE [#t1].rank < [#t2].rank
I have the following dataset:
id
id_rev
time
1
1
08.01.2022
1
0
31.02.2021
2
2
28.01.2017
2
1
25.07.2021
2
0
25.07.2021
I am looking for a SQL query that can return an entry per id but only the one where the id_rev is maximum. So in this case it should return these two rows:
(id=1, id_rev=1,time)
(id=2, id_rev=2, time)
One canonical approach uses ROW_NUMBER:
WITH cte AS (
SELECT t.*, ROW_NUMBER() OVER (PARTITION BY id ORDER BY id_rev DESC) rn
FROM yourTable t
)
SELECT id, id_rev, time
FROM cte
WHERE rn = 1
ORDER BY id;
Another approach would be to use exists logic:
SELECT id, id_rev, time
FROM yourTable t1
WHERE NOT EXISTS (
SELECT 1
FROM yourTable t2
WHERE t2.id = t1.id AND t2.id_rev > t1.id_rev
);
#result =
SELECT
*,
RANK()
OVER (PARTITION BY id ORDER BY id_rev DESC) AS Rank
FROM dataset ORDER BY Rank;
#result =
SELECT *
FROM #result
WHERE Rank = 1;
I have the below table where names will be inserted first. Then I will get IDs where I need to map with names
ID NAME
null Test1
null Test2
1 null
2 null
I need the result like
ID NAME
1 Test1
2 Test2
I tried below query but it doesn't work for me
select t1.ID , t2.Name from table1 T1 join table1 t2 on T1.id = t2.id
According to screen short you are working with SQL Server , you could try cte expression which may help you
;with cte as
(
select max(id) id, row_number() over (order by (select 1)) rn from
(
select *, rank() over(order by id) rnk from table
) a
group by a.rnk
having max(id) is not null
), cte1 as
(
select max(name) name, row_number() over (order by (select 1)) rn from
(
select *, rank() over(order by name) rnk from table
) a
group by a.rnk
having max(name) is not null
)
select c.id, c1.name from cte c
join cte1 c1 on c1.rn = c.rn
Result :
id name
1 test1
2 test2
I have a table like this
Date----- ----------Value--------- Group <br>
2017-01-01--------10--------------1--<br>
2017-01-02---------9---------------1--<br>
2017-01-03 --------5---------------2--<br>
2017-01-04 --------4---------------2--<br>
i want to update all value column in the table such that it is set to minimum date's value in that group
like this
Date----- ----------Value--------- Group <br>
2017-01-01--------10--------------1--<br>
2017-01-02---------10---------------1--<br>
2017-01-03 --------5---------------2--<br>
2017-01-04 --------5---------------2--<br>
Here you go, 2 sub-queries, the first to calculate min date per group then join back to original table to get the associated value. Then finally join this to the original table to update all associated groups with that value:
UPDATE M SET M.Value = RESULT.Value FROM MyTable M
INNER JOIN (
SELECT MV.Group, M.Value FROM MyTable M
INNER JOIN (
SELECT MIN(Date) as MinDateValue, Group FROM MyTable
GROUP BY Group
) MV ON MV.MinDateValue = M.Date AND MV.Group = M.Group
) RESULT ON RESULT.Group = M.Group
First get min date and value from sub query.Based on this result update main table
CREATE TABLE #Table(_Date Date,value INT,_Group INT)
INSERT INTO #Table(_Date ,value ,_Group)
SELECT '2017-01-01',10,1 UNION ALL
SELECT '2017-01-02',9,1 UNION ALL
SELECT '2017-01-03',5,2 UNION ALL
SELECT '2017-01-04',4,2
UPDATE #Table SET value = _Output._Value
FROM
(
SELECT A._Date , A._Group , T.value _Value
FROM #Table T
JOIN
(
SELECT MIN(_Date) _Date ,_Group
FROM #Table
GROUP BY _Group
) A ON A._Date = T._Date
) _Output WHERE _Output._Group = #Table._Group
SELECT * FROM #Table
You can also use a CTE.
Query
;with cte as(
select [rn] = row_number() over(
partition by [Group]
order by [Date]
), *
from [your_table_name]
)
update t1
set t1.[Value] = t2.[Value]
from cte t1
join cte t2
on t1.[Group] = t2.[Group]
and t1.[rn] > t2.[rn];
I need to concatenate the name in a recursive cross join way. I don't know how to do this, I have tried a CTE using WITH RECURSIVE but no success.
I have a table like this:
group_id | name
---------------
13 | A
13 | B
19 | C
19 | D
31 | E
31 | F
31 | G
Desired output:
combinations
------------
ACE
ACF
ACG
ADE
ADF
ADG
BCE
BCF
BCG
BDE
BDF
BDG
Of course, the results should multiply if I add a 4th (or more) group.
Native Postgresql Syntax:
SqlFiddleDemo
WITH RECURSIVE cte1 AS
(
SELECT *, DENSE_RANK() OVER (ORDER BY group_id) AS rn
FROM mytable
),cte2 AS
(
SELECT
CAST(name AS VARCHAR(4000)) AS name,
rn
FROM cte1
WHERE rn = 1
UNION ALL
SELECT
CAST(CONCAT(c2.name,c1.name) AS VARCHAR(4000)) AS name
,c1.rn
FROM cte1 c1
JOIN cte2 c2
ON c1.rn = c2.rn + 1
)
SELECT name as combinations
FROM cte2
WHERE LENGTH(name) = (SELECT MAX(rn) FROM cte1)
ORDER BY name;
Before:
I hope if you don't mind that I use SQL Server Syntax:
Sample:
CREATE TABLE #mytable(
ID INTEGER NOT NULL
,TYPE VARCHAR(MAX) NOT NULL
);
INSERT INTO #mytable(ID,TYPE) VALUES (13,'A');
INSERT INTO #mytable(ID,TYPE) VALUES (13,'B');
INSERT INTO #mytable(ID,TYPE) VALUES (19,'C');
INSERT INTO #mytable(ID,TYPE) VALUES (19,'D');
INSERT INTO #mytable(ID,TYPE) VALUES (31,'E');
INSERT INTO #mytable(ID,TYPE) VALUES (31,'F');
INSERT INTO #mytable(ID,TYPE) VALUES (31,'G');
Main query:
WITH cte1 AS
(
SELECT *, rn = DENSE_RANK() OVER (ORDER BY ID)
FROM #mytable
),cte2 AS
(
SELECT
TYPE = CAST(TYPE AS VARCHAR(MAX)),
rn
FROM cte1
WHERE rn = 1
UNION ALL
SELECT
[Type] = CAST(CONCAT(c2.TYPE,c1.TYPE) AS VARCHAR(MAX))
,c1.rn
FROM cte1 c1
JOIN cte2 c2
ON c1.rn = c2.rn + 1
)
SELECT *
FROM cte2
WHERE LEN(Type) = (SELECT MAX(rn) FROM cte1)
ORDER BY Type;
LiveDemo
I've assumed that the order of "cross join" is dependent on ascending ID.
cte1 generate DENSE_RANK() because your IDs contain gaps
cte2 recursive part with CONCAT
main query just filter out required length and sort string
The recursive query is a bit simpler in Postgres:
WITH RECURSIVE t AS ( -- to produce gapless group numbers
SELECT dense_rank() OVER (ORDER BY group_id) AS grp, name
FROM tbl
)
, cte AS (
SELECT grp, name
FROM t
WHERE grp = 1
UNION ALL
SELECT t.grp, c.name || t.name
FROM cte c
JOIN t ON t.grp = c.grp + 1
)
SELECT name AS combi
FROM cte
WHERE grp = (SELECT max(grp) FROM t)
ORDER BY 1;
The basic logic is the same as in the SQL Server version provided by #lad2025, I added a couple of minor improvements.
Or you can use a simple version if your maximum number of groups is not too big (can't be very big, really, since the result set grows exponentially). For a maximum of 5 groups:
WITH t AS ( -- to produce gapless group numbers
SELECT dense_rank() OVER (ORDER BY group_id) AS grp, name AS n
FROM tbl
)
SELECT concat(t1.n, t2.n, t3.n, t4.n, t5.n) AS combi
FROM (SELECT n FROM t WHERE grp = 1) t1
LEFT JOIN (SELECT n FROM t WHERE grp = 2) t2 ON true
LEFT JOIN (SELECT n FROM t WHERE grp = 3) t3 ON true
LEFT JOIN (SELECT n FROM t WHERE grp = 4) t4 ON true
LEFT JOIN (SELECT n FROM t WHERE grp = 5) t5 ON true
ORDER BY 1;
Probably faster for few groups. LEFT JOIN .. ON true makes this work even if higher levels are missing. concat() ignores NULL values. Test with EXPLAIN ANALYZE to be sure.
SQL Fiddle showing both.