Parse Numeric Ranges in PostgreSQL - postgresql

I would like to produce a string containing some parsed numeric ranges.
I have a table with some data
b_id,s_id
1,50
1,51
1,53
1,61
1,62
1,63
2,91
2,95
2,96
2,97
Using only SQL in PostgreSQL, how could I produce this output:
b_id,s_seqs
1,"50-51,53,61-63"
2,"91,95-97"
How on earth do I do that?

select b_id, string_agg(seq, ',' order by seq_no) as s_seqs
from (
select
b_id, seq_no,
replace(regexp_replace(string_agg(s_id::text, ','), ',.+,', '-'), ',', '-') seq
from (
select
b_id, s_id,
sum(mark) over w as seq_no
from (
select
b_id, s_id,
(s_id- 1 <> lag(s_id, 1, s_id) over w)::int as mark
from my_table
window w as (partition by b_id order by s_id)
) s
window w as (partition by b_id order by s_id)
) s
group by 1, 2
) s
group by 1;
Here you can find a step-by-step analyse from the innermost query towards the outside.

Related

how to order output of arrays when using union

I have a query like this:
SELECT array_agg(candles) as candles FROM ( SELECT * FROM ... ) AS candles
UNION ALL
SELECT array_agg(trades) as trades FROM ( SELECT * FROM ... ) AS trades
UNION ALL
SELECT ...
But then I'll get rows that contain arrays, but the order of the rows doesn't necessarily match the query order.
For example, it is possible that the output will have the trades row before the candles row.
How can I get the rows in a predictable order?
Edit:
updated the query based on the answer but getting an error:
SELECT a FROM
(
SELECT 1 as o, array_agg(candles) as a
FROM (
SELECT ts, open, high, low, close, midpoint, volume
FROM exchange.binance.candles
WHERE instrument = 'BTCUSDT' AND ts >= '2022-04-01 00:00:00' AND ts < '2022-04-01 01:00:00'
ORDER BY ts) AS candles
UNION ALL
SELECT 2 as o, array_agg(trades)
FROM (
SELECT ts, price, quantity, direction
FROM exchange.binance.trades
WHERE instrument = 'BTCUSDT' AND ts >= '2022-04-01 00:00:00' AND ts < '2022-04-01 01:00:00'
ORDER BY ts) AS trades
UNION ALL
SELECT 3 as o, array_agg(kvwap)
FROM (
SELECT ts, price, "interval"
FROM exchange.binance.kvwap
WHERE instrument = 'BTCUSDT' AND "interval" IN ('M5', 'H1', 'H4') AND ts >= '2022-04-01 00:00:00' AND ts < '2022-04-01 01:00:00'
ORDER BY ts) AS kvwap
)
ORDER BY o;
the error is:
[42601] ERROR: subquery in FROM must have an alias Hint: For example, FROM (SELECT ...) [AS] foo. Position: 15
Add a column for ordering to each subquery, but don't include it in the output:
SELECT a FROM (
SELECT 1 as o, array_agg(candles) as a FROM ( SELECT * FROM ... ) c group by 1
UNION ALL
SELECT 2, array_agg(trades) FROM ( SELECT * FROM ... ) t group by 1
UNION ALL
SELECT ...
) x
ORDER BY o
Note that with UNION only the first subquery's column names are relevant - the entire union uses column names from the first subquery - so don't bother providing aliases for the others.

TSQL - in a string, replace a character with a fixed one every 2 characters

I can't replace every 2 characters of a string with a '.'
select STUFF('abcdefghi', 3, 1, '.') c3,STUFF('abcdefghi', 5, 1,
'.') c5,STUFF('abcdefghi', 7, 1, '.') c7,STUFF('abcdefghi', 9, 1, '.')
c9
if I use STUFF I should subsequently overlap the strings c3, c5, c7 and c9. but I can't find a method
can you help me?
initial string:
abcdefghi
the result I would like is
ab.de.gh.
the string can be up to 50 characters
Create a numbers / tally / digits table, if you don't have one already, then you can use this to target each character position:
with digits as ( /* This would be a real table, here it's just to test */
select n from (values(1),(2),(3),(4),(5),(6),(7),(8),(9),(10))x(n)
), t as (
select 'abcdefghi' as s
)
select String_Agg( case when d.n%3 = 0 then '.' else Substring(t.s, d.n, 1) end, '')
from t
cross apply digits d
where d.n <Len(t.s)
Using for xml with existing table
with digits as (
select n from (values(1),(2),(3),(4),(5),(6),(7),(8),(9),(10))x(n)
),
r as (
select t.id, case when d.n%3=0 then '.' else Substring(t.s, d.n, 1) end ch
from t
cross apply digits d
where d.n <Len(t.s)
)
select result=(select '' + ch
from r r2
where r2.id=r.id
for xml path('')
)
from r
group by r.id
You can try it like this:
Easiest might be a quirky update ike here:
DECLARE #string VARCHAR(100)='abcdefghijklmnopqrstuvwxyz';
SELECT #string = STUFF(#string,3*A.pos,1,'.')
FROM (SELECT TOP(LEN(#string)/3) ROW_NUMBER() OVER(ORDER BY (SELECT NULL))
FROM master..spt_values) A(pos);
SELECT #string;
Better/Cleaner/Prettier was a recursive CTE:
We use a declared table to have some tabular sample data
DECLARE #tbl TABLE(ID INT IDENTITY, SomeString VARCHAR(200));
INSERT INTO #tbl VALUES('')
,('a')
,('ab')
,('abc')
,('abcd')
,('abcde')
,('abcdefghijklmnopqrstuvwxyz');
--the query
WITH recCTE AS
(
SELECT ID
,SomeString
,(LEN(SomeString)+1)/3 AS CountDots
,1 AS OccuranceOfDot
,SUBSTRING(SomeString,4,LEN(SomeString)) AS RestString
,CAST(LEFT(SomeString,2) AS VARCHAR(MAX)) AS Growing
FROM #tbl
UNION ALL
SELECT t.ID
,r.SomeString
,r.CountDots
,r.OccuranceOfDot+2
,SUBSTRING(RestString,4,LEN(RestString))
,CONCAT(Growing,'.',LEFT(r.RestString,2))
FROM #tbl t
INNER JOIN recCTE r ON t.ID=r.ID
WHERE r.OccuranceOfDot/2<r.CountDots-1
)
SELECT TOP 1 WITH TIES ID,Growing
FROM recCTE
ORDER BY ROW_NUMBER() OVER(PARTITION BY ID ORDER BY OccuranceOfDot DESC);
--the result
1
2 a
3 ab
4 ab
5 ab
6 ab.de
7 ab.de.gh.jk.mn.pq.st.vw.yz
The idea in short
We use a recursive CTE to walk along the string
we add the needed portion together with a dot
We stop, when the remaining length is to short to continue
a little magic is the ORDER BY ROW_NUMBER() OVER() together with TOP 1 WITH TIES. This will allow all first rows (frist per ID) to appear.

SQL Server - Select with Group By together Raw_Number

I'm using SQL Server 2000 (80). So, it's not possible to use the LAG function.
I have a code a data set with four columns:
Purchase_Date
Facility_no
Seller_id
Sale_id
I need to identify missing Sale_ids. So every sale_id is a 100% sequential, so the should not be any gaps in order.
This code works for a specific date and store if specified. But i need to work on entire data set looping looping through every facility_id and every seller_id for ever purchase_date
declare #MAXCOUNT int
set #MAXCOUNT =
(
select MAX(Sale_Id)
from #table
where
Facility_no in (124) and
Purchase_date = '2/7/2020'
and Seller_id = 1
)
;WITH TRX_COUNT AS
(
SELECT 1 AS Number
union all
select Number + 1 from TRX_COUNT
where Number < #MAXCOUNT
)
select * from TRX_COUNT
where
Number NOT IN
(
select Sale_Id
from #table
where
Facility_no in (124)
and Purchase_Date = '2/7/2020'
and seller_id = 1
)
order by Number
OPTION (maxrecursion 0)
My Dataset
This column:
case when
Sale_Id=0 or 1=Sale_Id-LAG(Sale_Id) over (partition by Facility_no, Purchase_Date, Seller_id)
then 'OK' else 'Previous Missing' end
will tell you which Seller_Ids have some sale missing. If you want to go a step further and have exactly your desired output, then filter out and distinct the 'Previous Missing' ones, and join with a tally table on not exists.
Edit: OP mentions in comments they can't use LAG(). My suggestion, then, would be:
Make a temp table that that has the max(sale_id) group by facility/seller_id
Then you can get your missing results by this pseudocode query:
Select ...
from temptable t
inner join tally N on t.maxsale <=N.num
where not exists( select ... from sourcetable s where s.facility=t.facility and s.seller=t.seller and s.sale=N.num)
> because the only way to "construct" nonexisting combinations is to construct them all and just remove the existing ones.
This one worked out
; WITH cte_Rn AS (
SELECT *, ROW_NUMBER() OVER(PARTITION BY Facility_no, Purchase_Date, Seller_id ORDER BY Purchase_Date) AS [Rn_Num]
FROM (
SELECT
Facility_no,
Purchase_Date,
Seller_id,
Sale_id
FROM MyTable WITH (NOLOCK)
) a
)
, cte_Rn_0 as (
SELECT
Facility_no,
Purchase_Date,
Seller_id,
Sale_id,
-- [Rn_Num] AS 'Skipped Sale'
-- , case when Sale_id = 0 Then [Rn_Num] - 1 Else [Rn_Num] End AS 'Skipped Sale for 0'
, [Rn_Num] - 1 AS 'Skipped Sale for 0'
FROM cte_Rn a
)
SELECT
Facility_no,
Purchase_Date,
Seller_id,
Sale_id,
-- [Skipped Sale],
[Skipped Sale for 0]
FROM cte_Rn_0 a
WHERE NOT EXISTS
(
select * from cte_Rn_0 b
where b.Sale_id = a.[Skipped Sale for 0]
and a.Facility_no = b.Facility_no
and a.Purchase_Date = b.Purchase_Date
and a.Seller_id = b.Seller_id
)
--ORDER BY Purchase_Date ASC

Checking Slowly Changing Dimension 2

I have a table that looks like this:
A slowly changing dimension type 2, according to Kimball.
Key is just a surrogate key, a key to make rows unique.
As you can see there are three rows for product A.
Timelines for this product are ok. During time the description of the product changes.
From 1-1-2020 up until 4-1-2020 the description of this product was ProdA1.
From 5-1-2020 up until 12-2-2020 the description of this product was ProdA2 etc.
If you look at product B, you see there are gaps in the timeline.
We use DB2 V12 z/Os. How can I check if there are gaps in the timelines for each and every product?
Tried this, but doesn't work
with selectie (key, tel) as
(select product, count(*)
from PROD_TAB
group by product
having count(*) > 1)
Select * from
PROD_TAB A
inner join selectie B
on A.product = B.product
Where not exists
(SELECT 1 from PROD_TAB C
WHERE A.product = C.product
AND A.END_DATE + 1 DAY = C.START_DATE
)
Does anyone know the answer?
The following query returns all gaps for all products.
The idea is to enumerate (RN column) all periods inside each product by START_DATE and join each record with its next period record.
WITH
/*
MYTAB (PRODUCT, DESCRIPTION, START_DATE, END_DATE) AS
(
SELECT 'A', 'ProdA1', DATE('2020-01-01'), DATE('2020-01-04') FROM SYSIBM.SYSDUMMY1
UNION ALL SELECT 'A', 'ProdA2', DATE('2020-01-05'), DATE('2020-02-12') FROM SYSIBM.SYSDUMMY1
UNION ALL SELECT 'A', 'ProdA3', DATE('2020-02-13'), DATE('2020-12-31') FROM SYSIBM.SYSDUMMY1
UNION ALL SELECT 'B', 'ProdB1', DATE('2020-01-05'), DATE('2020-01-09') FROM SYSIBM.SYSDUMMY1
UNION ALL SELECT 'B', 'ProdB2', DATE('2020-01-12'), DATE('2020-03-14') FROM SYSIBM.SYSDUMMY1
UNION ALL SELECT 'B', 'ProdB3', DATE('2020-03-15'), DATE('2020-04-18') FROM SYSIBM.SYSDUMMY1
UNION ALL SELECT 'B', 'ProdB4', DATE('2020-04-16'), DATE('2020-05-03') FROM SYSIBM.SYSDUMMY1
)
,
*/
MYTAB_ENUM AS
(
SELECT
T.*
, ROWNUMBER() OVER (PARTITION BY PRODUCT ORDER BY START_DATE) RN
FROM MYTAB T
)
SELECT A.PRODUCT, A.END_DATE + 1 START_DT, B.START_DATE - 1 END_DT
FROM MYTAB_ENUM A
JOIN MYTAB_ENUM B ON B.PRODUCT = A.PRODUCT AND B.RN = A.RN + 1
WHERE A.END_DATE + 1 <> B.START_DATE
AND A.END_DATE < B.START_DATE;
The result is:
|PRODUCT|START_DT |END_DT |
|-------|----------|----------|
|B |2020-01-10|2020-01-11|
May be more efficient way:
WITH MYTAB2 AS
(
SELECT
T.*
, LAG(END_DATE) OVER (PARTITION BY PRODUCT ORDER BY START_DATE) END_DATE_PREV
FROM MYTAB T
)
SELECT PRODUCT, END_DATE_PREV + 1 START_DATE, START_DATE - 1 END_DATE
FROM MYTAB2
WHERE END_DATE_PREV + 1 <> START_DATE
AND END_DATE_PREV < START_DATE;
Thnx Mark, will try this one of these days.
Never heard of LAG in DB2 V12 for z/Os
Will read about it
Thnx

How to count the frequency of integers in a set of querystrings in postgres

I have a column in a postgres database which logs search querystrings for a page on our website.
The column contains data like
"a=2&b=4"
"a=2,3"
"b=4&a=3"
"a=4&a=3"
I'd like to work out the frequency of each value for a certain parameter (a).
value | freq
------|------
3 | 3
2 | 2
4 | 1
Anyway to do this in a single SQL statement?
Something like this:
with all_values as (
select string_to_array(split_part(parameter, '=', 2), ',') as query_params
from the_table d,
unnest(string_to_array(d.querystring, '&')) as x(parameter)
where x.parameter like 'a%'
)
select t.value, count(*)
from all_values av, unnest(av.query_params) as t(value)
group by t.value
order by t.value;
Online example: http://rextester.com/OXM67442
try something like this :
select data_value,count(*) from (
select data_name,unnest(string_to_array(data_values,',')) data_value from (
select split_part(data_array,'=',1) data_name ,split_part(data_array,'=',2) data_values from (
select unnest(string_to_array(mydata,'&')) data_array from mytable
) a
) b
) c where data_name='a' group by 1 order by 1
Assuming tha table that keeps the counts is called paramcount:
WITH vals(v) AS
(SELECT regexp_replace(p, '^.*=', '')
FROM regexp_split_to_table(
'b=4&a=3,2',
'&|,'
) p(p)
)
INSERT INTO paramcount (value, freq)
SELECT v, 1 FROM vals
ON CONFLICT (value)
DO UPDATE SET freq = paramcount.freq + 1
WHERE paramcount.value = EXCLUDED.value;
get csv integer after 'a='
split that to numbers
stat values
select v, count(*) from (
SELECT c,unnest(string_to_array(unnest(regexp_matches(c,'a=([0-9,]+)','g')),',')) as v FROM qrs
) x group by v;
Parametrize:
WITH argname(aname) as (values ('a'::TEXT))
select v, count(*) from (SELECT c,unnest(string_to_array(unnest(regexp_matches(c,aname||'=([0-9,]+)','g')),',')) as v FROM qrs,argname) x group by v;