Given the following SQL tables: https://imgur.com/a/NI8VrC7. For each specific ID_t I need to return the MAX() and MIN() value of Cena_c(total price) column of a given ID_t.
| ID_t | Nazwa |
| ---- | ----- |
| 1 | T1 |
| 2 | T2 |
| 3 | T3 |
| 4 | T4 |
| 5 | T5 |
| 6 | T6 |
| 7 | T7 |
| ID | ID_t | Ilosc | Cena_j | Cena_c | ID_p |
| ---- | ---- | ----- | ------ | ------ | ---- |
| 100 | 1 | 1 | 10 | 10 | 1 |
| 101 | 2 | 3 | 20 | 60 | 2 |
| 102 | 4 | 5 | 10 | 50 | 7 |
| 103 | 2 | 2 | 20 | 40 | 5 |
| 104 | 5 | 1 | 30 | 30 | 5 |
| 105 | 7 | 6 | 80 | 480 | 1 |
| 106 | 6 | 7 | 15 | 105 | 2 |
| 107 | 6 | 5 | 15 | 75 | 1 |
| 108 | 3 | 3 | 25 | 75 | 7 |
| 109 | 7 | 1 | 80 | 80 | 5 |
| 110 | 4 | 1 | 10 | 10 | 2 |
| 111 | 2 | 9 | 20 | 180 | 2 |
Based on provided tables the correct result should look like this:
| ID_t | Cena_c_max | Cena_c_min |
| ----- | ---------- | ---------- |
| T1 | 10 | 10 |
| T2 | 180 | 60 |
| T3 | 75 | 75 |
| T4 | 50 | 10 |
| T5 | 30 | 30 |
| T6 | 105 | 75 |
| T7 | 480 | 80 |
Is this even possible?
I haven't found anything yet that I could use to implement my solution.
SELECT concat('T',ID_t), max(Cena_c) as Cena_c_max, min(Cena_c) as Cena_c_min
FROM table
GROUP BY ID_t
Better is to solve it with joins of tables, because it will be avoided in the future if the prefix T is changed to another letter.
Hardcoding should be avoided.
select b.nazva as "Nazva", max(a.cena.c) as "Cena_c_max", min(a.cena.c) as "Cena_c_min"
from table1 as a
left join table2 as b on (
a.id_t = b.id_t
)
group by id_t
Related
I would like to calculate the Theil–Sen estimator per ID for the value column in the sample table below using hive. The Theil–Sen estimator is defined here https://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator, I tried to use arrays but could not figure out a solution. Any help is appreciated.
+----+-------+-------+
| 1 | 1 | 10 |
| 1 | 2 | 20 |
| 1 | 3 | 30 |
| 1 | 4 | 40 |
| 1 | 5 | 50 |
| 2 | 1 | 100 |
| 2 | 2 | 90 |
| 2 | 3 | 102 |
| 2 | 4 | 75 |
| 2 | 5 | 70 |
| 2 | 6 | 50 |
| 2 | 7 | 100 |
| 2 | 8 | 80 |
| 2 | 9 | 60 |
| 2 | 10 | 50 |
| 2 | 11 | 40 |
| 2 | 12 | 40 |
+----+-------+-------+
I have the following sql to calculate a % total:
SELECT tblTourns_atp.ID_Ti,
Sum([FS_1]/(SELECT Sum(FSOF_1)
FROM stat_atp
WHERE stat_atp.ID_T = tblTourns_atp.ID_T)) AS S1_IP
FROM stat_atp
INNER JOIN tblTourns_atp ON stat_atp.ID_T = tblTourns_atp.ID_T
GROUP BY tblTourns_atp.ID_Ti
I'm getting the 'aggregate error' because it wants the ID_T fields either grouped or in an aggregate function. I've read loads of examples but none of them seem to apply when the offending field is the subject of 'WHERE'.
Tables and output as follows:
+----------+------+--------+--+---------------+-------+--+--------+--------+
| stat_atp | | | | tblTourns_atp | | | Output | |
+----------+------+--------+--+---------------+-------+--+--------+--------+
| ID_T | FS_1 | FSOF_1 | | ID_T | ID_Ti | | ID_Ti | S1_IP |
| 1 | 20 | 40 | | 1 | 1 | | 1 | 31.03% |
| 2 | 30 | 100 | | 2 | 1 | | 2 | 28.57% |
| 3 | 40 | 150 | | 3 | 1 | | 3 | 33.33% |
| 4 | 30 | 100 | | 4 | 2 | | | |
| 5 | 30 | 100 | | 5 | 2 | | | |
| 6 | 40 | 150 | | 6 | 2 | | | |
| 7 | 20 | 40 | | 7 | 3 | | | |
| 8 | 30 | 100 | | 8 | 3 | | | |
| 9 | 40 | 150 | | 9 | 3 | | | |
| 10 | 20 | 40 | | 10 | 3 | | | |
+----------+------+--------+--+---------------+-------+--+--------+--------+
Since you already have an inner join between the two tables, a separate subquery isn't required:
select t.id_ti, sum(s.fs_1)/sum(s.fsof_1) as pct
from tbltourns_atp t inner join stat_atp s on t.id_t = s.id_t
group by t.id_ti
I have a hive external table with data say, (version less than 0.14)
+--------+------+------+------+
| id | A | B | C |
+--------+------+------+------+
| 10011 | 10 | 3 | 0 |
| 10012 | 9 | 0 | 40 |
| 10015 | 10 | 3 | 0 |
| 10017 | 9 | 0 | 40 |
+--------+------+------+------+
And I have a delta file having data given below.
+--------+------+------+------+
| id | A | B | C |
+--------+------+------+------+
| 10012 | 50 | 3 | 10 | --> update
| 10013 | 29 | 0 | 40 | --> insert
| 10014 | 10 | 3 | 0 | --> update
| 10013 | 19 | 0 | 40 | --> update
| 10015 | 70 | 3 | 0 | --> update
| 10016 | 17 | 0 | 40 | --> insert
+--------+------+------+------+
How can I update my hive table with the delta file, without using sqoop. Any help on how to proceed will be great! Thanks.
This is because there is duplicates in the file. How do you know which you should keep? The last one?
In that case you can use, for example, the row_number and then get the maximum value. Something like that.
SELECT coalesce(tmp.id,initial.id) as id,
coalesce(tmp.A, initial.A) as A,
coalesce(tmp.B,initial.B) as B,
coalesce(tmp.C, initial.C) as C
FROM
table_a initial
FULL OUTER JOIN
( SELECT *, row_number() over( partition by id ) as row_num
,COUNT(*) OVER (PARTITION BY id) AS cnt
FROM temp_table
) tmp
ON initial.id=tmp.id
WHERE row_num=cnt
OR row_num IS NULL;
Output:
+--------+-----+----+-----+--+
| id | a | b | c |
+--------+-----+----+-----+--+
| 10011 | 10 | 3 | 0 |
| 10012 | 50 | 3 | 10 |
| 10013 | 19 | 0 | 40 |
| 10014 | 10 | 3 | 0 |
| 10015 | 70 | 3 | 0 |
| 10016 | 17 | 0 | 40 |
| 10017 | 9 | 0 | 40 |
+--------+-----+----+-----+--+
You can load the file to a temporary table in hive and then execute a FULL OUTER JOIN between the two tables.
Query Example:
SELECT coalesce(tmp.id,initial.id) as id,
coalesce(tmp.A, initial.A) as A,
coalesce(tmp.B,initial.B) as B,
coalesce(tmp.C, initial.C) as C
FROM
table_a initial
FULL OUTER JOIN
temp_table tmp on initial.id=tmp.id;
Output
+--------+-----+----+-----+--+
| id | a | b | c |
+--------+-----+----+-----+--+
| 10011 | 10 | 3 | 0 |
| 10012 | 50 | 3 | 10 |
| 10013 | 29 | 0 | 40 |
| 10013 | 19 | 0 | 40 |
| 10014 | 10 | 3 | 0 |
| 10015 | 70 | 3 | 0 |
| 10016 | 17 | 0 | 40 |
| 10017 | 9 | 0 | 40 |
+--------+-----+----+-----+--+
I have four tables as below:
tblAccount
Id i sprimary key
+----+-----------------+
| Id | AccName |
+----+-----------------+
| 1 | AccountA |
| 2 | AccountB |
+----+-----------------+
tblLocation
Id is primary key.
+----+---------------+
| Id | LocName |
+----+---------------+
| 1 | LocationA |
| 2 | LocationB |
| 3 | LocationC |
+----+---------------+
tblAccountwiseLocation
Id i sprimary key.LocId and AccId are foreign key.
+----+---------------+---------------+
| Id | LocId | AccId |
+----+---------------+---------------+
| 1 | 1 | 1 |
| 2 | 2 | 1 |
| 3 | 3 | 1 |
| 4 | 1 | 2 |
| 5 | 2 | 2 |
| 6 | 3 | 2 |
+----+---------------+---------------+
tblRSCMaster
Id i sprimary key.LocId and AccId are foreign key.
+----+---------------+---------------+----------------+------------------+
| Id | LocId | AccId | RSCNo | DateOfAddition |
+----+---------------+---------------+----------------+------------------+
| 1 | 1 | 1 | Acc1_Loc1_1_14 | 15/01/2014 |
| 2 | 2 | 1 | Acc1_Loc2_1_14 | 15/01/2014 |
| 3 | 3 | 1 | Acc1_Loc2_1_14 | 15/01/2014 |
| 4 | 1 | 2 | Acc2_Loc1_1_14 | 15/01/2014 |
| 5 | 2 | 2 | Acc2_Loc2_1_14 | 15/01/2014 |
| 6 | 3 | 2 | Acc2_Loc3_1_14 | 15/01/2014 |
| 7 | 1 | 1 | Acc1_Loc1_2_14 | 15/02/2014 |
| 8 | 2 | 1 | Acc1_Loc2_2_14 | 15/02/2014 |
| 9 | 3 | 1 | Acc1_Loc3_2_14 | 15/02/2014 |
| 10 | 1 | 2 | Acc2_Loc1_2_14 | 15/02/2014 |
| 11 | 2 | 2 | Acc2_Loc2_2_14 | 15/02/2014 |
| 12 | 3 | 2 | Acc2_Loc3_2_14 | 15/02/2014 |
| 13 | 1 | 1 | Acc1_Loc1_3_14 | 15/03/2014 |
| 14 | 2 | 1 | Acc1_Loc2_3_14 | 15/03/2014 |
| 15 | 3 | 1 | Acc1_Loc3_3_14 | 15/03/2014 |
| 16 | 1 | 2 | Acc2_Loc1_3_14 | 15/03/2014 |
| 17 | 2 | 2 | Acc2_Loc2_3_14 | 15/03/2014 |
| 18 | 3 | 2 | Acc2_Loc3_3_14 | 15/03/2014 |
| 19 | 1 | 1 | Acc1_Loc1_4_14 | 15/04/2014 |
| 20 | 2 | 1 | Acc1_Loc2_4_14 | 15/04/2014 |
| 21 | 3 | 1 | Acc1_Loc3_4_14 | 15/04/2014 |
| 22 | 1 | 2 | Acc2_Loc1_4_14 | 15/04/2014 |
| 23 | 2 | 2 | Acc2_Loc2_4_14 | 15/04/2014 |
| 24 | 3 | 2 | Acc2_Loc3_4_14 | 15/04/2014 |
| 25 | 1 | 1 | Acc1_Loc1_5_14 | 15/05/2014 |
| 26 | 2 | 1 | Acc1_Loc2_5_14 | 15/05/2014 |
| 27 | 3 | 1 | Acc1_Loc3_5_14 | 15/05/2014 |
| 28 | 1 | 2 | Acc2_Loc1_5_14 | 15/05/2014 |
| 29 | 2 | 2 | Acc2_Loc2_5_14 | 15/05/2014 |
| 30 | 3 | 2 | Acc2_Loc3_5_14 | 15/05/2014 |
+----+---------------+---------------+----------------+------------------+
Acc1_Loc1_1_14 resembles RSC for LocationA of AccountA for Jan 2014.
I need to get a output as below from tblRSCMaster.
+---------------+---------------+----------------+------------------+
| LocId | AccId | RSCNo | DateOfAddition |
+---------------+---------------+----------------+------------------+
| 1 | 1 | Acc1_Loc1_3_14 | 15/03/2014 |
| 1 | 1 | Acc1_Loc1_4_14 | 15/04/2014 |
| 1 | 1 | Acc1_Loc1_5_14 | 15/05/2014 |
| 2 | 1 | Acc1_Loc2_3_14 | 15/03/2014 |
| 2 | 1 | Acc1_Loc2_4_14 | 15/04/2014 |
| 2 | 1 | Acc1_Loc2_5_14 | 15/05/2014 |
| 3 | 1 | Acc1_Loc3_3_14 | 15/03/2014 |
| 3 | 1 | Acc1_Loc3_4_14 | 15/04/2014 |
| 3 | 1 | Acc1_Loc3_5_14 | 15/05/2014 |
+---------------+---------------+----------------+------------------+
Each account has multiple locations and each location has multiple RSCs.
I need to get last three RSCs for each location for AccountA.
I have tried the below query:
SELECT tblAccountwiseLocation.LocId,tblAccountwiseLocation.AccId,tblRSCMaster.RSCNo,tblRSCMaster.DateOfAddition FROM tblAccountwiseLocation
INNER JOIN tblRSCMaster ON tblAccountwiseLocation.LocId= tblRSCMaster.LocId
where tblRSCMaster.AccId=1
But not getting the proper output.
Please help me out.
Thank you all in advance.
You can wrap the existing query inside a common table expression, and use ROW_NUMBER() to get only the last 3 (by tblRSCMaster.DateOfAddition) entries per tblAccountwiseLocation.LocId.
WITH cte AS (
SELECT tblAccountwiseLocation.LocId,
tblAccountwiseLocation.AccId,
tblRSCMaster.RSCNo,
tblRSCMaster.DateOfAddition,
ROW_NUMBER() OVER (PARTITION BY tblAccountwiseLocation.LocId
ORDER BY tblRSCMaster.DateOfAddition DESC) rn
FROM tblAccountwiseLocation
INNER JOIN tblRSCMaster
ON tblAccountwiseLocation.LocId = tblRSCMaster.LocId
AND tblAccountwiseLocation.AccId = tblRSCMaster.AccId
WHERE tblRSCMaster.AccId=1
)
SELECT LocId, AccId, RSCNo, DateOfAddition
FROM cte
WHERE rn <= 3
ORDER BY LocId, AccId, DateOfAddition
An SQLfiddle to test with.
Is this what you need?
select m.*
from (select m.*, row_number() over (partition by accID
order by DateOfAddition desc) as seqnum
from tblRSCMaster
where m.locid = 1
) m
where seqnum <= 3
order by AccId, DateOfAddition;
I think you need to filter on the locid rather than on the AccId to get what you want.
I have a table where I have a list of people, lets say i have 100 people listed in that table
I need to filter out the people using different criteria's and put them in groups, problem is when i start excluding on the 4th-5th level, performance issues come up and it becomes slow
with lst_tous_movements as (
select
t1.refid_eClinibase
t1.[dthrfinmouvement]
t1.[unite_service_id]
t1.[unite_service_suiv_id]
from sometable t1
)
,lst_patients_hospitalisés as (
select distinct
t1.refid_eClinibase
from lst_tous_movements t1
where
t1.[dthrfinmouvement] = '4000-01-01'
)
,lst_patients_admisUIB_transferes as (
select distinct
t1.refid_eClinibase
from lst_tous_movements t1
left join lst_patients_hospitalisés t2 on t1.refid_eClinibase = t2.refid_eClinibase
where
t1.[unite_service_id] = 4
and t1.[unite_service_suiv_id] <> 0
and t2.refid_eClinibase is null
)
,lst_patients_admisUIB_nonTransferes as (
select distinct
t1.refid_eClinibase
from lst_tous_movements t1
left join lst_patients_admisUIB_transferes t2 on t1.refid_eClinibase = t2.refid_eClinibase
left join lst_patients_hospitalisés t3 on t1.refid_eClinibase = t3.refid_eClinibase
where
t1.[unite_service_id] = 4
and t1.[unite_service_suiv_id] = 0
and t2.refid_eClinibase is null
and t3.refid_eClinibase is null
)
,lst_patients_autres as (
select distinct
t1.refid_eClinibase
from lst_patients t1
left join lst_patients_admisUIB_transferes t2 on t1.refid_eClinibase = t2.refid_eClinibase
left join lst_patients_hospitalisés t3 on t1.refid_eClinibase = t3.refid_eClinibase
left join lst_patients_admisUIB_nonTransferes t4 on t1.refid_eClinibase = t4.refid_eClinibase
where
t2.refid_eClinibase is null
and t3.refid_eClinibase is null
and t4.refid_eClinibase is null
)
as you can see i have a multi level filtering out going on here...
1st i get the people where t1.[dthrfinmouvement] = '4000-01-01'
2nd i get the people with another criteria EXCLUDING the 1st group
3rd i get the people with yet another criteria EXCLUDING the 1st and
the 2nd group
etc..
when i get to the 4th level, my query takes 6 - 10 seconds to complete
is there any way to speed this up ?
this is my dataset i'm working with:
+------------------+-------------------------------+------------------+------------------+-----------------------+
| refid_eClinibase | nodossierpermanent_eClinibase | dthrfinmouvement | unite_service_id | unite_service_suiv_id |
+------------------+-------------------------------+------------------+------------------+-----------------------+
| 25611 | P0017379 | 2013-04-27 | 58 | 0 |
| 25611 | P0017379 | 2013-05-02 | 4 | 2 |
| 25611 | P0017379 | 2013-05-18 | 2 | 0 |
| 85886 | P0077918 | 2013-04-10 | 58 | 0 |
| 85886 | P0077918 | 2013-05-06 | 6 | 12 |
| 85886 | P0077918 | 4000-01-01 | 12 | 0 |
| 91312 | P0083352 | 2013-07-24 | 3 | 14 |
| 91312 | P0083352 | 2013-07-24 | 14 | 3 |
| 91312 | P0083352 | 2013-07-30 | 3 | 8 |
| 91312 | P0083352 | 4000-01-01 | 8 | 0 |
| 93835 | P0085879 | 2013-04-30 | 58 | 0 |
| 93835 | P0085879 | 2013-05-07 | 4 | 2 |
| 93835 | P0085879 | 2013-05-16 | 2 | 0 |
| 93835 | P0085879 | 2013-05-22 | 58 | 0 |
| 93835 | P0085879 | 2013-05-24 | 4 | 0 |
| 93835 | P0085879 | 2013-05-31 | 58 | 0 |
| 93836 | P0085880 | 2013-05-20 | 58 | 0 |
| 93836 | P0085880 | 2013-05-22 | 4 | 2 |
| 93836 | P0085880 | 2013-05-31 | 2 | 0 |
| 97509 | P0089576 | 2013-04-09 | 58 | 0 |
| 97509 | P0089576 | 2013-04-11 | 4 | 0 |
| 102787 | P0094886 | 2013-04-08 | 58 | 0 |
| 102787 | P0094886 | 2013-04-11 | 4 | 2 |
| 102787 | P0094886 | 2013-05-21 | 2 | 0 |
| 103029 | P0095128 | 2013-04-04 | 58 | 0 |
| 103029 | P0095128 | 2013-04-10 | 4 | 1 |
| 103029 | P0095128 | 2013-05-03 | 1 | 0 |
| 103813 | P0095922 | 2013-07-02 | 58 | 0 |
| 103813 | P0095922 | 2013-07-03 | 4 | 6 |
| 103813 | P0095922 | 2013-08-14 | 6 | 0 |
| 105106 | P0097215 | 2013-08-09 | 58 | 0 |
| 105106 | P0097215 | 2013-08-13 | 4 | 0 |
| 105106 | P0097215 | 2013-08-14 | 58 | 0 |
| 105106 | P0097215 | 4000-01-01 | 4 | 0 |
| 106223 | P0098332 | 2013-06-11 | 1 | 0 |
| 106223 | P0098332 | 2013-08-01 | 58 | 0 |
| 106223 | P0098332 | 4000-01-01 | 1 | 0 |
| 106245 | P0098354 | 2013-04-02 | 58 | 0 |
| 106245 | P0098354 | 2013-05-24 | 58 | 0 |
| 106245 | P0098354 | 2013-05-29 | 4 | 1 |
| 106245 | P0098354 | 2013-07-12 | 1 | 0 |
| 106280 | P0098389 | 2013-04-07 | 58 | 0 |
| 106280 | P0098389 | 2013-04-09 | 4 | 0 |
| 106416 | P0098525 | 2013-04-19 | 58 | 0 |
| 106416 | P0098525 | 2013-04-23 | 4 | 0 |
| 106444 | P0098553 | 2013-04-22 | 58 | 0 |
| 106444 | P0098553 | 2013-04-25 | 4 | 0 |
| 106609 | P0098718 | 2013-05-08 | 58 | 0 |
| 106609 | P0098718 | 2013-05-10 | 4 | 11 |
| 106609 | P0098718 | 2013-07-24 | 11 | 12 |
| 106609 | P0098718 | 4000-01-01 | 12 | 0 |
| 106616 | P0098725 | 2013-05-09 | 58 | 0 |
| 106616 | P0098725 | 2013-05-09 | 4 | 1 |
| 106616 | P0098725 | 2013-07-27 | 1 | 0 |
| 106698 | P0098807 | 2013-05-16 | 58 | 0 |
| 106698 | P0098807 | 2013-05-22 | 4 | 6 |
| 106698 | P0098807 | 2013-06-14 | 6 | 1 |
| 106698 | P0098807 | 2013-06-28 | 1 | 0 |
| 106714 | P0098823 | 2013-05-20 | 58 | 0 |
| 106714 | P0098823 | 2013-05-21 | 58 | 0 |
| 106714 | P0098823 | 2013-05-24 | 58 | 0 |
| 106729 | P0098838 | 2013-05-21 | 58 | 0 |
| 106729 | P0098838 | 2013-05-23 | 4 | 1 |
| 106729 | P0098838 | 2013-06-03 | 1 | 0 |
| 107038 | P0099147 | 2013-06-25 | 58 | 0 |
| 107038 | P0099147 | 2013-06-28 | 4 | 1 |
| 107038 | P0099147 | 2013-07-04 | 1 | 0 |
| 107038 | P0099147 | 2013-08-13 | 58 | 0 |
| 107038 | P0099147 | 2013-08-15 | 4 | 6 |
| 107038 | P0099147 | 4000-01-01 | 6 | 0 |
| 107082 | P0099191 | 2013-06-29 | 58 | 0 |
| 107082 | P0099191 | 2013-07-04 | 4 | 6 |
| 107082 | P0099191 | 2013-07-19 | 6 | 0 |
| 107157 | P0099267 | 4000-01-01 | 13 | 0 |
| 107336 | P0099446 | 4000-01-01 | 6 | 0 |
+------------------+-------------------------------+------------------+------------------+-----------------------+
thanks.
It is hard to understand exactly what all your rules are from the question, but the general approach should be to add a "Grouping" column to a singl query that uses a CASE statement to categorize the people.
The conditions in a CASE are evaluated in order, so that if the first criteria is met, then the subsequent criteria are not even evaluated for that row.
Here is some code to get you started....
select t1.refid_eClinibase
,t1.[dthrfinmouvement]
,t1.[unite_service_id]
,t1.[unite_service_suiv_id]
CASE WHEN [dthrfinmouvement] = '4000-01-01' THEN 'Group1 Label'
WHEN condition2 = something THEN 'Group2 Label'
....
WHEN conditionN = something THEN 'GroupN Label'
ELSE 'Catch All Label'
END as person_category
from sometable t1