While trying to map some data to a table, I wanted to obtain the ID of a table and its modulo respect the total rows in the same table. For example, given this table:
id
--
1
3
10
12
I would like this result:
id | mod
---+----
1 | 1 <- 1 mod 4
3 | 3 <- 3 mod 4
10 | 2 <- 10 mod 4
12 | 0 <- 12 mod 4
Is there an easy way to achieve this dynamically (as in, not counting the rows on before hand or doing it in an atomic way)?
So far I've tried something like this:
SELECT t1.id, t1.id % COUNT(t1.id) mod FROM tbl t1, tbl t2 GROUP BY t1.id;
This works but you must have the GROUP BY and tbl t2 as otherwise it returns 0 for the mod column which makes sense because I think it works by multiplying the table by itself so each ID gets a full set of the table. I guess for small enough tables this is ok but I can see how this becomes problematic for larger tables.
Edit: Found another hack-ish way:
WITH total AS (
SELECT COUNT(*) cnt FROM tbl
)
SELECT t1.id, t1.id % t2.cnt mod FROM tbl t1, total t2
It similar to the previous query but it "collapses" the multiplication to a single row with the previous count.
You can use COUNT() window function:
SELECT id,
id % COUNT(*) OVER () mod
FROM tbl;
I'm sure that the optimizer is smart enough to calculate the result of the window function only once.
See the demo.
Related
Recently I've faced with pretty rare filtering case in PSQL.
My question is: How to filter redundant elements in each group of the grouped table?
For example: we have a nexp table:
id | group_idx | filter_idx
1 1 x
2 3 z
3 3 x
4 2 x
5 1 x
6 3 x
7 2 x
8 1 z
9 2 z
Firstly, to group rows:
SELECT group_idx FROM table
GROUP BY group_idx;
But how I can filter redundant fields (filter_idx = z) from each group after grouping?
P.S. I can't just write like that because I need to find groups firstly.
SELECT group_idx FROM table
where filter_idx <> z;
Thanks.
Assuming that you want to see all groups at all times, even when you filter out all records of some group:
drop table if exists test cascade;
create table test (id integer, group_idx integer, filter_idx character);
insert into test
(id,group_idx,filter_idx)
values
(1,1,'x'),
(2,3,'z'),
(3,3,'x'),
(4,2,'x'),
(5,1,'x'),
(6,3,'x'),
(7,2,'x'),
(8,1,'z'),
(9,2,'z'),
(0,4,'y');--added an example of a group that would be discarded using WHERE.
Get groups in one query, filter your rows in another, then left join the two.
select groups.group_idx,
string_agg(filtered_rows.filter_idx,',')
from
(select distinct group_idx from test) groups
left join
(select group_idx,filter_idx from test where filter_idx<>'y') filtered_rows
using (group_idx)
group by 1;
-- group_idx | string_agg
-------------+------------
-- 3 | z,x,x
-- 4 |
-- 2 | x,x,z
-- 1 | x,x,z
--(4 rows)
I was looking at a problem of reshaping a table creating new columns according based on values.
I'm using the same example as this problem discussed there: A complicated sum in R data.table that involves looking at other columns
so I have a table:
df:([]ID:1+til 5;
Group:1 1 2 2 2;
V1:10 + 2 * til 5;
Type_v1:`t1`t2`t1`t1`t2;
V2:3 0N 0N 7 8;
Type_v2:`t2```t3`t3);
ID Group V1 Type_v1 V2 Type_v2
------------------------------
1 1 10 t1 3 t2
2 1 12 t2
3 2 14 t1
4 2 16 t1 7 t3
5 2 18 t2 8 t3
and the goal is to transform it to get the sum of values by group and type. please note the new columns created. basically all types in Type_v1 and Type_v2 are used to create columns for the resulting table.
# group v_1 type_1 v_2 type_2 v_3 type_3
#1: 1 10 t1 15 t2 NA <NA>
#2: 2 30 t1 18 t2 15 t3
I did the beginning but I am unable to transform the table and create the new columns.
also of course I'm trying to get all the columns created in a dynamic way, as it would not be possible to input 20k columns manually.
df1:select Group, Value:V1, Type:Type_v1 from df;
df2:select Group, Value:V2, Type:Type_v2 from df;
tr:df1,df2;
tr:0!select sum Value by Group, Type from tr where Type <> ` ;
basically I'm missing the equivalent of:
dcast(tmp, group ~ rowid(group), value.var = c("v", "type"))
any help and explanations appreciated,
The last piece you're missing is a pivot: https://code.kx.com/q/kb/pivoting-tables/
q)P:exec distinct Type from tr
q)exec P#(Type!Value) by Group:Group from tr
Group| t1 t2 t3
-----| --------
1 | 10 15
2 | 30 18 15
It doesn't quite get you the exact output but pivot is the concept
You could expand on Terry's pivot to dynamically do the select parts above using functional form. See more detail here:
https://code.kx.com/q/basics/funsql/
// Personally, I would try to stay clear of column names too similar to reserved keywords in kdb
df: `id`grpCol`v_1`typCol_1`v_2`typCol_2 xcol df;
{[df;n]
// dynamically create cols from 1 to n
cls:`$("v_";"typCol_"),\:/:string 1 + til n;
// functional form of select for each type/value col before joining together
df:(,/) {?[x;();0b;`grpCol`v`typCol!`grpCol,y]}[df] each cls;
// sum, then pivot
df:0!select sum v by grpCol, typCol from df where typCol <> `;
P:exec distinct typCol from df;
df:exec P#(typCol!v) by grpCol:grpCol from df;
// Type cols seem unnecessary but
// Can be done with another functional select
?[df;();0b;(`grpCol,raze P,'`$"typCol_",/:string 1 + til count P)!`grpCol,raze flip (P;enlist each P)]
}[df;2]
grpCol t1 typCol_1 t2 typCol_2 t3 typCol_3
1 10 t1 15 t2 0N t3
2 30 t1 18 t2 15 t3
EDIT - More detailed breakdown below:
cls:`$("v_";"typCol_") ,\:/: string 1 + til n;
Dynamically create a symbol list for the columns as they are required for column names when using functional form. I start by creating a list of v_ and typCol_ up to number n.
,\:/: -> join with each left and each right iterators
https://code.kx.com/q/ref/maps/#each-left-and-each-right
This allows me to join every item on the left ("v_";"typCol_") with every item on the right.
The same could be achieved with cross but you would have to restructure the list with flip and cut
flip n cut `$("v_";"typCol_") cross string 1 + til n
(,/) {?[x;();0b;`grpCol`v`typCol!`grpCol,y]}[df] each cls;
(,/) -> This is the over iterator used with join. It takes the 1st table, joins it to the 2nd, then takes that and joins on to the 3rd etc.
https://code.kx.com/q/ref/over/
{?[x;();0b;`grpCol`v`typCol!`grpCol,y]}[df] each cls
// functional select
?[table; where; by; columns]
?[x; (); 0b; `grpCol`v`typCol!`grpCol,y]
This creates a list of tables, 1 for each column pair in the cls variable. Notice how I don't explicitly state x or y in the function like this {[x;y]}. This is because x y and z can be used implicitly, so this function works with or without.
The important part here is the last param (columns). For a functional select it is a dictionary with column names as the key and what the columns are as the values
e.g. `grpCol`v`typCol!`grpCol`v_1`typCol_1 -> this is renaming each v and typCol so they are the same to then join them all together with (,/).
There is a useful keyword to help with figuring out functional form -> parse
parse"select Group, Value:V1, Type:Type_v1 from df"
0 ?
1 `df
2 ()
3 0b
4 (`Group`Value`Type)!`Group`V1`Type_v1
P:exec distinct typCol from df;
df:exec P#(typCol!v) by grpCol:grpCol from df;
pivoting is outlined here: https://code.kx.com/q/kb/pivoting-tables/
It effectively flips/rotates a section of the table. It takes the distinct types from typCol as the columns and uses the v column as the rows for each corresponding typCol
?[table; where; by; columns]
?[df;();0b;(`grpCol,raze P,'`$"typCol_",/:string 1 + til count P)!`grpCol,raze flip (P;enlist each P)]
Again look at the last param in the functional select i.e. columns. This is how it looks after being dynamically generated:
(`grpCol`t1`typCol_1`t2`typCol_2`t3`typCol_3)!(`grpCol;`t1;enlist `t1;`t2;enlist `t2;`t3;enlist `t3)
It is kind of a hacky way to get the type columns, I select each t1 t2 t3 with a typeCol_1 _2 _3,
`t1 = (column) `t1
`typCol_1 = enlist `t1 -> the enlist here tells kdb I want the value `t1 rather than the column
In a table I have records with id's 2,4,5,8. How can I receive a list with values 1,3,6,7. I have tried in this way
SELECT t1.id + 1
FROM table t1
WHERE NOT EXISTS (
SELECT *
FROM table t2
WHERE t2.id = t1.id + 1
)
but it's not working correctly. It doesn't bring all available positions.
Is it possible without another table?
You can get all the missing ID's from a recursive CTE, like this:
with recursive numbers as (
select 1 number
from rdb$database
union all
select number+1
from rdb$database
join numbers on numbers.number < 1024
)
select n.number
from numbers n
where not exists (select 1
from table t
where t.id = n.number)
the number < 1024 condition in my example limit the query to the max 1024 recursion depth. After that, the query will end with an error. If you need more than 1024 consecutive ID's you have either run the query multiple times adjusting the interval of numbers generated or think in a different query that produces consecutive numbers without reaching that level of recursion, which is not too difficult to write.
Assume we have a table and we want to do a sum of the Expend column so that the summation only adds up values of the same Week_Name.
SN Week_Name Exp Sum
-- --------- --- ---
1 Week 1 10 0
2 Week 1 20 0
3 Week 1 30 60
4 Week 2 40 0
5 Week 2 50 90
6 Week 3 10 0
I will assume we will need to `Order By' Week_Name, then compare the previous Week_Name(previous row) with the current row Week_name(Current row).
If both are the same, put zero in the SUM column.
If not the same, add all expenditure, where Week_Name = Week_Name(Previous row) and place in the Sum column. The final output should look like the table above.
Any help on how to achieve this in T-SQL is highly appreciated.
Okay, I was eventually able to resolve this issue, praise Jesus! If you want the exact table I gave above, you can use GilM's response below, it is perfect. If you want your table to have running Cumulatives, i.e. Rows 3 shoud have 60, Row 5, should have 150, Row 6 160 etc. Then, you can use my code below:
USE CAPdb
IF OBJECT_ID ('dbo.[tablebp]') IS NOT NULL
DROP TABLE [tablebp]
GO
CREATE TABLE [tablebp] (
tablebpcCol1 int PRIMARY KEY
,tabledatekey datetime
,tableweekname varchar(50)
,expenditure1 numeric
,expenditure_Cummulative numeric
)
INSERT INTO [tablebp](tablebpcCol1,tabledatekey,tableweekname,expenditure1,expenditure_Cummulative)
SELECT b.s_tablekey,d.PK_Date,d.Week_Name,
SUM(b.s_expenditure1) AS s_expenditure1,
SUM(b.s_expenditure1) + COALESCE((SELECT SUM(s_expenditure1)
FROM source_table bs JOIN dbo.Time dd ON bs.[DATE Key] = dd.[PK_Date]
WHERE dd.PK_Date < d.PK_Date),0)
FROM source_table b
INNER JOIN dbo.Time d ON b.[Date key] = d.PK_Date
GROUP BY d.[PK_Date],d.Week_Name,b.s_tablekey,b.s_expenditure1
ORDER BY d.[PK_Date]
;WITH CTE AS (
SELECT tableweekname
,Max(expenditure_Cummulative) AS Week_expenditure_Cummulative
,MAX(tablebpcCol1) AS MaxSN
FROM [tablebp]
GROUP BY tableweekname
)
SELECT [tablebp].*
,CASE WHEN [tablebp].tablebpcCol1 = CTE.MaxSN THEN Week_expenditure_Cummulative
ELSE 0 END AS [RunWeeklySum]
FROM [tablebp]
JOIN CTE on CTE.tableweekname = [tablebp].tableweekname
I'm not sure why your SN=6 line is 0 rather than 10. Do you really not want the sum for the last Week? If having the last week total is okay, then you might want something like:
;WITH CTE AS (
SELECT Week_Name,SUM([Expend.]) as SumExpend
,MAX(SN) AS MaxSN
FROM T
GROUP BY Week_Name
)
SELECT T.*,CASE WHEN T.SN = CTE.MaxSN THEN SumExpend
ELSE 0 END AS [Sum]
FROM T
JOIN CTE on CTE.Week_Name = T.Week_Name
Based on the requst in the comment wanting a running total in SUM you could try this:
;WITH CTE AS (
SELECT Week_Name, MAX(SN) AS MaxSN
FROM T
GROUP BY Week_Name
)
SELECT T.SN, T.Week_Name,T.Exp,
CASE WHEN T.SN = CTE.MaxSN THEN
(SELECT SUM(EXP) FROM T T2
WHERE T2.SN <= T.SN) ELSE 0 END AS [SUM]
FROM T
JOIN CTE ON CTE.Week_Name = T.Week_Name
ORDER BY SN
This one is probably a softball question for any DBA, but here's my challenge. I have a table that looks like this:
id parent_id active
--- --------- -------
1 5 y
2 6 y
3 6 y
4 6 y
5 7 y
6 8 y
The way the system I am working on operates, it should only have one active row per parent. Thus, it'd be ok if ID #2 and #3 were active = 'n'.
I need to run a query that finds all rows that have duplicate parent_ids who are active and flip all but the highest ID to active = 'y'.
Can this be done in a single query, or do I have to write a script for it? (Using Postgresql, btw)
ANSI style:
update table set
active = 'n'
where
id <> (select max(id) from table t1 where t1.parent_id = table.parent_id)
Postgres specific:
update t1 set
active = 'n'
from
table t1
inner join (select max(id) as topId, parent_id from table group by parent_id) t2 on
t1.id < t2.topId
and t1.parent_id = t2.parent_id
The second one is probably a bit faster, since it's not doing a correlated subquery for each row. Enjoy!