When trying to get a count of IDs I get a different answer when grouping by day vs when I am not.
select cv.CONV_DAY, count(distinct cv.CLICK_ID)
from
clickcache.click cc
right join(
select distinct cv.CLICK_ID, cv.CONV_DAY, cv.PIXEL_ID
from clickcache.CONVERSION cv
where cv.CLICK_ID IS NOT NULL) cv ON cv.CLICK_ID = cc.ID
where cc.ADV_ACCOUNT_ID = 25176
and cv.CONV_DAY between '2016-8-01' AND '2016-08-07'
and AMP_CLICK_STATUS_ID = 1
AND pixel_id IN
(SELECT DISTINCT conversion_pixel_id
FROM
ampx.campaign_event_funnel ef
JOIN ampx.campaign cp ON
cp.id = ef.campaign_id
AND cp.campaign_status_id = 1
WHERE
ef.account_id IN(25176)
AND include_optimization = 1 )
group by 1
order by 1 asc
This yields 170 which is the correct answer and the I want. This, on the other hand, displays 157.
select count(distinct cv.CLICK_ID)
from
clickcache.click cc
right join(
select distinct cv.CLICK_ID, cv.CONV_DAY, cv.PIXEL_ID
from clickcache.CONVERSION cv
where cv.CLICK_ID IS NOT NULL) cv ON cv.CLICK_ID = cc.ID
where cc.ADV_ACCOUNT_ID = 25176
and cv.CONV_DAY between '2016-8-01' AND '2016-08-07'
and AMP_CLICK_STATUS_ID = 1
AND pixel_id IN
(SELECT DISTINCT conversion_pixel_id
FROM
ampx.campaign_event_funnel ef
JOIN ampx.campaign cp ON
cp.id = ef.campaign_id
AND cp.campaign_status_id = 1
WHERE
ef.account_id IN(25176)
AND include_optimization = 1 )
My question is why do I get this discrepancy and how to fix it to get a proper count?
Thank you!
Your count dependents from right query, maybe you have duplicate row?
example
table1
id name value
1 2 3
table2
id name value
1 4 5
2 6 3
1 6 3
right join tables on value get result
select * from table1 a right join table2 b on a.value = b.value
1 2 3 2 6 3
1 2 3 1 6 3
select count(distinct a.value)
from (select a.id, a.name, a.value, b.id, b.name, b.value
from table1 a right join table2 b on a.value = b.value)
result is 1
select b.id, count(distinct a.value)
from (select a.id, a.name, a.value, b.id, b.name, b.value
from table1 a right join table2 b on a.value = b.value group)
group by b.id
result is two rows
2 1
1 1
My guess is that, you have a problem for this reason.
Related
I have 3 tables:
Basic
id
name
description
2
Name1
description2
3
Name2
description3
LinkA
id
linkA_ID
2
344
3
3221
2
6642
3
2312
2
323
LinkB
id
linkB_ID
2
8287
3
42466
2
616422
3
531
2
2555
2
8592
3
1122
2
33345
I want to get results as the table below:
id
name
description
linkA_count
linkB_count
2
Name1
description2
3
2
3
Name2
description3
5
3
my query:
SELECT
a.id
,a.name
,a.description
,COUNT(b.linkA_ID) AS linkA_count
,COUNT(c.linkB_ID) AS linkb_count
FROM
basic a
JOIN linkA b on (a.id = b.id)
JOIN linkb c on (a.id = c.id)
GROUP BY
a.id
,a.name
,a.description
Result from the query is count of linkA always same as linkB
A more traditional approach is to use "derived tables" (subqueries) so that the counts are performed before joins multiply the rows. Using left joins allows for all id's in basic to be returned by the query even if there are no related rows in either joined tables.
select
basic.id
, coalesce(a.LinkACount,0) LinkACount
, coalesce(b.linkBCount,0) linkBCount
from basic
left join (
select id, Count(linkA_ID) LinkACount from LinkA group by id
) as a on a.id=basic.id
left join (
select id, Count(linkB_ID) LinkBCount from LinkB group by id
) as b on b.id=basic.id
Try This (using SubQuery)
SELECT
basic.id
,basic.name
,basic.description
,(select Count(linkA_ID) from LinkA where LinkA.id=basic.id) as LinkACount
,(select Count(linkB_ID) from LinkB where LinkB.id=basic.id) as LinkBCount FROM basic
Method 2 (Try CTE)
with a as(select id,Count(linkA_ID)LinkACount from LinkA group by id)
, b as (select id,Count(linkB_ID)LinkBCount from LinkB group by id)
select basic.id,a.LinkACount,b.linkBCount
from basic
join a on (a.id=basic.id)
join b on (b.id=basic.id)
If you only select from your table you see why your query cannot work.
SELECT
*
FROM
basic a
JOIN linkA b on (a.id = b.id)
JOIN linkb c on (a.id = c.id)
WHERE a.ID = 3
=> just use distinct in your count
SELECT
a.id
,a.name
,a.description
,COUNT(DISTINCT(b.linkA_ID)) AS linkA_count
,COUNT(DISTINCT(c.linkB_ID)) AS linkb_count
FROM
basic a
JOIN linkA b on (a.id = b.id)
JOIN linkb c on (a.id = c.id)
GROUP BY
a.id
,a.name
,a.description
I have two datasets in Oracle Table1 and Table2.
When I run this:
SELECT A.ID, B.NUM_X
FROM TABLE1 A
LEFT JOIN TABLE2 B ON A.ID=B.ID
WHERE B.BOOK = 1
It returns this.
ID NUM_X
1 10
1 5
1 9
2 2
2 1
3 20
3 11
What I want are the DISTINCT ID where NUM_X is the MAX value, something like this:
ID NUM_x
1 10
2 2
3 20
You can use aggregation:
SELECT A.ID, MAX(B.NUM_X)
FROM TABLE1 A LEFT JOIN
TABLE2 B
ON A.ID = B.ID
WHERE B.BOOK = 1
GROUP BY A.ID;
If you wanted additional columns, I would recommend window functions:
SELECT A.ID, MAX(B.NUM_X)
FROM TABLE1 A LEFT JOIN
(SELECT B.*,
ROW_NUMBER() OVER (PARTITION BY ID ORDER BY NUM_X DESC) as seqnum
FROM TABLE2 B
) B
ON A.ID = B.ID AND B.seqnum = 1
WHERE B.BOOK = 1
GROUP BY A.ID;
I'd like to group by region where there are customerswho has type=a
region customer type score
A a a 1
A b b 2
A c a 3
B d c 4
B e d 5
C f a 6
C g c 7
Therefore after first step
region customer type score
A a a 1
A b b 2
A c a 3
C f a 6
C g c 7
And then I groupby in region
region sum(score)
A 6
C 13
also I'd like to extract customer whose type=a
region customer type
A a a
A c a
C f a
Then I'd like to merge above.
My desired result is like following
customer sum_in_region
a 6
c 6
f 13
Are there any way to achieve this?
My work is till the second step..
How can I proceed further?
SELECT t1.region,t1.customer, t1.type, t1.score
FROM yourTable t1
WHERE EXISTS (SELECT 1
FROM yourTable t2
WHERE t2.region = t1.region
AND t2.type = 'a');
Thanks
Join the table to a derived table that does your first two steps.
SELECT t3.customer,
x1.score
FROM yourtable t3
INNER JOIN (SELECT t1.region,
sum(score) score
FROM yourtable t1
WHERE EXISTS (SELECT *
FROM yourtable t2
WHERE t2.region = t1.region
AND t2.type = 'a')
GROUP BY t1.region) x1
ON x1.region = t3.region
WHERE t2.type = 'a';
You could use the windows functions to get your result; the first step filters for only rows where type is a, based on the region. The second step then gets the sum of scores, based again on the region, before selecting only customer and sum columns :
with filter_type_a as
(select region, customer, type, score
from
(select *,
sum(type=="a") over (partition by region) as counter
from your_table)
where counter > 0)
select customer, sum_region
from
(select customer, type,
sum(score) over (partition by region) as sum_region
from filter_type_a)
where type=="a";
You can use below query:
SQLFiddle
with country_tmp as
(SELECT t1.region,t1.customer, t1.type, t1.score
FROM country t1
WHERE EXISTS (SELECT 1
FROM country t2
WHERE t2.region = t1.region
AND t2.type = 'a'))
select y.customer, x.score from
(select a.region, sum(a.score) score from (
SELECT t1.region,t1.customer, t1.type, t1.score
FROM country_tmp t1) a
group by region) x , (SELECT t1.region,t1.customer, t1.type
FROM country_tmp t1
Where t1.type = 'a') y where x.region = y.region;
I have this query that generates about 40,000 records and the execution time of this query is about 1 minute 30 seconds.
SELECT DISTINCT
a.ID,
a.NAME,
a.DIV,
a.UID,
(select NAME from EMPLOYEE where UID= a.UID and UID<>'') as boss_id,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 1 and id = a.ID) as TERM1,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 2 and id = a.ID) as TERM2,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 3 and id = a.ID) as TERM3,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 4 and id = a.ID) as TERM4,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 5 and id = a.ID) as TERM5,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 6 and id = a.ID) as TERM6,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 7 and id = a.ID) as TERM7,
(select DATE(MAX(create_time)) from XYZ where XYZ_ID= 8 and id = a.ID) as TERM8
FROM EMPLOYEE a
WHERE ID LIKE 'D%'
I tried using group by, different kinds of join to improve the execution time but couldn't succeed.Both the tables ABC and XYZ are indexed.
Also, I think that the root cause of this problem is either the DISTINCT keyword or the MAX function.
How can I optimize the above query to bring down the execution time to at least less than a minute?
Any help is appreciated.
Query is not tested, this is just an idea on how you could get this done in two different ways.
(SQL Server solutions here)
Using LEFT JOIN for each ID should look something like this:
SELECT a.ID,
a.NAME,
a.DIV,
a.UID,
b.Name as boss_id,
MAX(xyz1.create_time) as TERM1,
MAX(xyz2.create_time) as TERM2,
MAX(xyz3.create_time) as TERM3,
MAX(xyz4.create_time) as TERM4,
MAX(xyz5.create_time) as TERM5,
MAX(xyz6.create_time) as TERM6,
MAX(xyz7.create_time) as TERM7,
MAX(xyz8.create_time) as TERM8
FROM EMPLOYEE a
JOIN EMPLOYEE b on a.UID = b.UID and b.UID <> ''
LEFT JOIN XYZ xyz1 on a.ID = xyz1.ID and xyz1.XYZ_ID = 1
LEFT JOIN XYZ xyz2 on a.ID = xyz2.ID and xyz1.XYZ_ID = 2
LEFT JOIN XYZ xyz3 on a.ID = xyz3.ID and xyz1.XYZ_ID = 3
LEFT JOIN XYZ xyz4 on a.ID = xyz4.ID and xyz1.XYZ_ID = 4
LEFT JOIN XYZ xyz5 on a.ID = xyz5.ID and xyz1.XYZ_ID = 5
LEFT JOIN XYZ xyz6 on a.ID = xyz6.ID and xyz1.XYZ_ID = 6
LEFT JOIN XYZ xyz7 on a.ID = xyz7.ID and xyz1.XYZ_ID = 7
LEFT JOIN XYZ xyz8 on a.ID = xyz8.ID and xyz1.XYZ_ID = 8
WHERE a.ID LIKE 'D%'
GROUP BY a.ID, a.NAME, a.DIV, a.UID, b.Name
Using PIVOT would look something like this:
select * from (
SELECT DISTINCT
a.ID,
a.NAME,
a.DIV,
a.UID,
b.NAME as boss_id,
xyz.xyz_id,
xyz.create_time
FROM EMPLOYEE a
JOIN EMPLOYEE b on a.UID = b.UID and b.UID <> ''
LEFT JOIN (SELECT DATE(MAX(create_time)) create_time, XYZ_ID, ID
from XYZ
where XYZ_ID between 1 and 8
group by XYZ_ID, ID) xyz on a.ID = xyz1.ID
WHERE a.ID LIKE 'D%') src
PIVOT (
max(create_time) for xyz_id IN (['1'], ['2'], ['3'], ['4'],
['5'], ['6'], ['7'], ['8'])
) PIV
Give it a shot
I would recommend group by and conditional aggregation:
SELECT e.ID, e.NAME, e.DIV, e.UID,
DATE(MAX(CASE WHEN XYZ_ID = 1 THEN create_time END)) as term1,
DATE(MAX(CASE WHEN XYZ_ID = 2 THEN create_time END)) as term2,
DATE(MAX(CASE WHEN XYZ_ID = 3 THEN create_time END)) as term3,
DATE(MAX(CASE WHEN XYZ_ID = 4 THEN create_time END)) as term4,
DATE(MAX(CASE WHEN XYZ_ID = 5 THEN create_time END)) as term5,
DATE(MAX(CASE WHEN XYZ_ID = 6 THEN create_time END)) as term6,
DATE(MAX(CASE WHEN XYZ_ID = 7 THEN create_time END)) as term7,
DATE(MAX(CASE WHEN XYZ_ID = 8 THEN create_time END)) as term8
FROM EMPLOYEE e LEFT JOIN
XYZ
ON xyz.ID = e.id
WHERE e.ID LIKE 'D%'
GROUP BY e.ID, e.NAME, e.DIV, e.UID;
I don't understand the logic for boss_id, so I left that out. This should improve the performance significantly.
I have TableA in a many-to-many relationship with TableC via TableB. That is,
TableA TableB TableC
id | val fkeyA | fkeyC id | data
I wish the do select sum(val) on TableA, grouping by the relationship(s) to TableC. Every entry in TableA has at least one relationship with TableC. For example,
TableA
1 | 25
2 | 30
3 | 50
TableB
1 | 1
1 | 2
2 | 1
2 | 2
2 | 3
3 | 1
3 | 2
should output
75
30
since rows 1 and 3 in Table have the same relationships to TableC, but row 2 in TableA has a different relationship to TableC.
How can I write a SQL query for this?
SELECT
sum(tableA.val) as sumVal,
tableC.data
FROM
tableA
inner join tableB ON tableA.id = tableB.fkeyA
INNER JOIN tableC ON tableB.fkeyC = tableC.id
GROUP by tableC.data
edit
Ah ha - I now see what you're getting at. Let me try again:
SELECT
sum(val) as sumVal,
tableCGroup
FROM
(
SELECT
tableA.val,
(
SELECT cast(tableB.fkeyC as varchar) + ','
FROM tableB WHERE tableB.fKeyA = tableA.id
ORDER BY tableB.fkeyC
FOR XML PATH('')
) as tableCGroup
FROM
tableA
) tmp
GROUP BY
tableCGroup
Hm, in MySQL it could be written like this:
SELECT
SUM(val) AS sumVal
FROM
( SELECT
fkeyA
, GROUP_CONCAT(fkeyC ORDER BY fkeyC) AS grpC
FROM
TableB
GROUP BY
fkeyA
) AS g
JOIN
TableA a
ON a.id = g.fkeyA
GROUP BY
grpC
SELECT sum(a.val)
FROM tablea a
INNER JOIN tableb b ON (b.fKeyA = a.id)
GROUP BY b.fKeyC
It seems that is it needed to create a key_list in orther to allow group by:
75 -> key list = "1 2"
30 -> key list = "1 2 3"
Because GROUP_CONCAT don't exists in T-SQL:
WITH CTE ( Id, key_list )
AS ( SELECT TableA.id, CAST( '' AS VARCHAR(8000) )
FROM TableA
GROUP BY TableA.id
UNION ALL
SELECT TableA.id, CAST( key_list + ' ' + str(TableB.id) AS VARCHAR(8000) )
FROM CTE c
INNER JOIN TableA A
ON c.Id = A.id
INNER join TableB B
ON B.Id = A.id
WHERE A.id > c.id --avoid infinite loop
)
Select
sum( val )
from
TableA inner join
CTE on (tableA.id = CTE.id)
group by
CTE.key_list