Multi Value in Query Select PrestoDB - sql

I'm trying to perfom some query to Prestodb like this:
SELECT *
FROM (
VALUES
concat('<a href="https:test?preselect_filters=',
url_encode(concat('{"27":{','"column_name":["', CAST({{ "'" +
"','".join(filter_values('column_name', concat('#value1', '#value2'))) +
"'" }} AS VARCHAR), '"]', ',','}}')),
'#TAB-bEGT8cU5h">Qun', '</a>')
) dashboard_link (links)
my problem is concat('#value1','#value2'), any idea to select an array of values?


Is this what you need?
select * from (values concat(ARRAY [1,2,3], ARRAY [4,5,6]));
You can refer to prestodb doc

Related

trouble with dynamic year filter in MDX

I have the following query that I use in Azure data factory(this is on the source of a copy action):
SELECT
{ [Measures].[0INV_QTY],
[Measures].[0NET_VAL_S] }
ON COLUMNS,
NON EMPTY
{ [0CUST_SALES].[LEVEL01].MEMBERS *
[0SALESORG].[LEVEL01].MEMBERS *
[0COMPANY].[LEVEL01].MEMBERS *
[0MATERIAL].[LEVEL01].MEMBERS *
[ZDEBITOR].[LEVEL01].MEMBERS *
[0FISCPER].[LEVEL01].MEMBERS *
[0DEB_CRED].[LEVEL01].MEMBERS *
[0BILLTOPRTY].[LEVEL01].MEMBERS *
[0DOC_CATEG].[LEVEL01].MEMBERS *
[0SHIP_TO].[LEVEL01].MEMBERS }
DIMENSION PROPERTIES
[0SALESORG].[20SALESORG],
[0COMPANY].[20COMPANY],
[0CUST_SALES].[80CUST_SALES],
[0CUST_SALES].[20CUST_GRP1],
[0CUST_SALES].[20PMNTTRMS],
[ZDEBITOR].[20CRED_LIMIT],
[0MATERIAL].[20MATERIAL],
[0DEB_CRED].[20DEB_CRED],
[0BILLTOPRTY].[20BILLTOPRTY],
[0DOC_CATEG].[20DOC_CATEG],
[0SHIP_TO].[20SHIP_TO],
[0FISCPER].[80FISCPER]
ON ROWS
FROM $0SD_C03
WHERE ({[0CALYEAR].[2020], [0CALYEAR].[2021], [0CALYEAR].[2018], [0CALYEAR].[2019]})
In here I would like to replace the WHERE with something like Cast(YEAR(GETDATE())-4 as varchar(10)) Now I am really new to MDX and I keep getting stuck. Could anyone point me in the right direction?
So what i want to achieve is not having to adjust the query every year and be able to only have the last 4 years.

If you are looking for a SQL equivalent as below in MDX
SELECT ... From ... WHERE date > DATEADD(year,-4,GETDATE())
Try using "with member" and function parallelperiod.
CREATE MEMBER CurrentCube.Measures.[Last4Years] AS
ParallelPeriod( [Date].[Date].[Date Yr], 4, StrToMember(“[Date].[Date].&[” + Format(now(), “yyyyMMdd”) + “]”))
: StrToMember(“[Date].[Date].&[” + Format(now(), “yyyyMMdd”) + “]”)
;

need to hardcode a column in Hive with a custom word appending along with a column_name from a table

select distinct 'CART-data-map_val.role_name' as ProdMN
from VRN_544.RLT_001 AS mk_roles
JOIN VRMM.map_valxx AS map_val
ON ( Upper(Trim(map_val.role_name)) = Upper(Trim(mk_roles.rltx_02)) )
so, CART-data is the word which should append to the role_name into ProdMN column
ProdMN column Example - CART-data-map_val.role_name - 1- CART-data-reducer-role
2- CART-data-modular-role

how about using concat ?:
select distinct concat('CART-data-',map_val.role_name) as ProdMN
from VRN_544.RLT_001 AS mk_roles
JOIN VRMM.map_valxx AS map_val
ON ( Upper(Trim(map_val.role_name)) = Upper(Trim(mk_roles.rltx_02)) )

How to apply a user defined function to multiple columns in BigQuery SQL?

In the database I'm working on there are a several wage variables that are recorded as strings with entries like 0000001155,00. I am using a combination of CAST and REPLACE to transform these variables into float. For just one variable, I used:
CAST (REPLACE (wage_var, ",", ".") AS float64) as wage_formatted
I would like to perform this procedure for all variables that have the same problem, without repeating the same line of code. My idea is to use a function and then iterate the function through the columns.
I figure out how I can create a function to perform the standardization after reading the documentation. Then I wrote the following function:
CREATE TEMP FUNCTION wage2float(x STRING) AS (CAST(REPLACE(x, ",", ".") AS float64));
SELECT
wage_var,
wage2float(wage_var) as wage_formatted
FROM
`mydataset.mytable`
However, it's not clear to me how I can iterate this function on several columns. Is there a way to loop through the columns and apply the wage2float function for each column?
EDIT:
Here is sample of input (csv):
vl_remun_media_nom,vl_remun_media_sm,vl_remun_dezembro_nom,vl_remun_dezembro_sm,vl_ultima_remuneracao_ano,vl_salario_contratual,vl_rem_janeiro_cc,vl_rem_fevereiro_cc,vl_rem_marco_cc,vl_rem_abril_cc,vl_rem_maio_cc,vl_rem_junho_cc,vl_rem_julho_cc,vl_rem_agosto_cc,vl_rem_setembro_cc,vl_rem_outubro_cc,vl_rem_novembro_cc
"0000006025,55","000006,42","0000005921,09","000006,31","0005921,09","0005148,77","000000005866,27","000000005866,27","000000005866,27","000000005866,27","000000005866,27","000000005866,27","000000007169,88","000000006254,78","000000005921,09","000000005921,09","000000005921,09"
"0000001447,68","000001,54","0000001726,67","000001,84","0001726,67","0000014,00","000000001645,55","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00"
"0000001304,35","000001,39","0000001304,35","000001,39","0001304,35","0001304,35","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000001304,35","000000001304,35","000000001304,35","000000001304,35"
"0000001447,68","000001,54","0000001726,67","000001,84","0001726,67","0000014,00","000000001645,55","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00"
"0000001447,68","000001,54","0000001726,67","000001,84","0001726,67","0000014,00","000000001645,56","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00"
"0000001447,68","000001,54","0000001726,67","000001,84","0001726,67","0000014,00","000000001645,55","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00","000000000014,00"
"0000001427,95","000001,52","0000001420,68","000001,51","0001420,68","0001420,68","000000001379,30","000000001379,30","000000001379,30","000000001379,30","000000001379,30","000000001379,30","000000001839,07","000000001379,30","000000001379,30","000000001420,68","000000001420,68"
"0000005937,88","000006,33","0000005900,00","000006,29","0005900,00","0000059,00","000000000057,38","000000000057,38","000000000057,38","000000000057,38","000000007650,67","000000000057,38","000000000057,38","000000000057,38","000000000057,38","000000000059,00","000000000059,00"
"0000001087,04","000001,15","0000001076,20","000001,14","0001076,20","0001076,20","000000000010,00","000000000010,00","000000000010,00","000000001076,20","000000001076,20","000000001076,20","000000001076,20","000000001434,93","000000001076,20","000000001076,20","000000001076,20"
"0000002395,30","000002,55","0000002448,79","000002,61","0002448,79","0002448,79","000000002377,47","000000002377,47","000000002377,47","000000002377,47","000000002377,47","000000002377,47","000000002377,47","000000002377,47","000000002377,47","000000002448,79","000000002448,79"
"0000001870,56","000001,99","0000001820,00","000001,94","0001820,00","0000018,00","000000001820,01","000000001820,01","000000001820,01","000000001820,01","000000001820,01","000000000018,20","000000000018,20","000000000018,20","000000000018,20","000000002426,67","000000000018,20"
"0000002960,08","000003,15","0000003068,59","000003,27","0003068,59","0000027,00","000000002724,53","000000002500,09","000000003454,64","000000002700,88","000000002943,15","000000002943,42","000000002943,69","000000003098,28","000000003098,24","000000002976,73","000000003068,79"
"0000003798,04","000004,04","0000003852,69","000004,11","0003852,69","0000030,00","000000002500,45","000000002500,57","000000002500,79","000000005306,55","000000005079,02","000000003430,02","000000004239,21","000000004182,29","000000004913,02","000000003247,38","000000003824,52"
"0000004945,06","000005,27","0000005286,81","000005,64","0005286,81","0000045,00","000000004000,10","000000004000,16","000000005392,43","000000004919,14","000000004500,98","000000004500,21","000000005936,10","000000006133,08","000000004795,43","000000004576,91","000000005299,44"
"0000005810,00","000006,19","0000005540,00","000005,91","0005540,00","0000055,40","000000006933,33","000000000055,40","000000000055,40","000000000055,40","000000000055,40","000000000055,40","000000000055,40","000000007386,67","000000000055,40","000000000055,40","000000000055,40"
"0000001103,62","000001,17","0000001090,00","000001,16","0001090,00","0000010,90","000000000010,31","000000000010,31","000000000010,31","000000001086,20","000000001086,20","000000001086,20","000000001086,20","000000001086,20","000000001086,20","000000001453,33","000000000010,90"
"0000002600,34","000002,77","0000002866,13","000003,05","0002866,13","0000010,91","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000002168,92","000000001999,70","000000002175,13","000000003036,83","000000002909,14","000000002887,45","000000002759,44"
"0000005174,66","000005,51","0000004967,86","000005,30","0004967,86","0000016,15","000000005154,31","000000004621,59","000000005161,25","000000005080,73","000000005185,34","000000004981,24","000000006430,29","000000005584,57","000000005064,43","000000005029,16","000000004835,26"
"0000005693,03","000006,07","0000005650,78","000006,03","0005650,78","0005650,78","000000005433,44","000000005433,44","000000005433,44","000000005433,44","000000007244,59","000000005433,44","000000005433,44","000000005868,12","000000005650,78","000000005650,78","000000005650,78"
"0000002485,76","000002,64","0000002810,52","000002,99","0002810,52","0000010,91","000000002193,56","000000001925,13","000000002352,46","000000002135,21","000000002440,66","000000002232,19","000000002951,81","000000002947,97","000000002588,45","000000002516,61","000000002734,59"
"0000003808,35","000004,06","0000003893,40","000004,15","0003893,40","0003893,40","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000000037,80","000000004006,80"
"0000004648,00","000004,95","0000004549,71","000004,85","0004549,71","0004549,71","000000004212,70","000000004549,71","000000006066,28","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71"
"0000004521,62","000004,82","0000004549,71","000004,85","0004549,71","0004549,71","000000004212,70","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71","000000004549,71"
"0000003024,00","000003,22","0000003024,00","000003,22","0003024,00","0000030,24","000000000028,00","000000000028,00","000000000028,00","000000000028,00","000000000039,20","000000000030,24","000000000030,24","000000000030,24","000000000030,24","000000000030,24","000000000030,24"
"0000002946,43","000003,14","0000002910,00","000003,10","0002910,00","0001923,68","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000000000,00","000000002983,70","000000002945,59"
Desired output:
vl_remun_media_nom,vl_remun_media_sm,vl_remun_dezembro_nom,vl_remun_dezembro_sm,vl_ultima_remuneracao_ano,vl_salario_contratual,vl_rem_janeiro_cc,vl_rem_fevereiro_cc,vl_rem_marco_cc,vl_rem_abril_cc,vl_rem_maio_cc,vl_rem_junho_cc,vl_rem_julho_cc,vl_rem_agosto_cc,vl_rem_setembro_cc,vl_rem_outubro_cc,vl_rem_novembro_cc
6025.55,6.42,5921.09,6.31,5921.09,5148.77,5866.27,5866.27,5866.27,5866.27,5866.27,5866.27,7169.88,6254.78,5921.09,5921.09,5921.09
1447.68,1.54,1726.67,1.84,1726.67,14.0,1645.55,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0
1304.35,1.39,1304.35,1.39,1304.35,1304.35,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1304.35,1304.35,1304.35,1304.35
1447.68,1.54,1726.67,1.84,1726.67,14.0,1645.55,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0
1447.68,1.54,1726.67,1.84,1726.67,14.0,1645.56,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0
1447.68,1.54,1726.67,1.84,1726.67,14.0,1645.55,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0,14.0
1427.95,1.52,1420.68,1.51,1420.68,1420.68,1379.3,1379.3,1379.3,1379.3,1379.3,1379.3,1839.07,1379.3,1379.3,1420.68,1420.68
5937.88,6.33,5900.0,6.29,5900.0,59.0,57.38,57.38,57.38,57.38,7650.67,57.38,57.38,57.38,57.38,59.0,59.0
1087.04,1.15,1076.2,1.14,1076.2,1076.2,10.0,10.0,10.0,1076.2,1076.2,1076.2,1076.2,1434.93,1076.2,1076.2,1076.2
2395.3,2.55,2448.79,2.61,2448.79,2448.79,2377.47,2377.47,2377.47,2377.47,2377.47,2377.47,2377.47,2377.47,2377.47,2448.79,2448.79
1870.56,1.99,1820.0,1.94,1820.0,18.0,1820.01,1820.01,1820.01,1820.01,1820.01,18.2,18.2,18.2,18.2,2426.67,18.2
2960.08,3.15,3068.59,3.27,3068.59,27.0,2724.53,2500.09,3454.64,2700.88,2943.15,2943.42,2943.69,3098.28,3098.24,2976.73,3068.79
3798.04,4.04,3852.69,4.11,3852.69,30.0,2500.45,2500.57,2500.79,5306.55,5079.02,3430.02,4239.21,4182.29,4913.02,3247.38,3824.52
4945.06,5.27,5286.81,5.64,5286.81,45.0,4000.1,4000.16,5392.43,4919.14,4500.98,4500.21,5936.1,6133.08,4795.43,4576.91,5299.44
5810.0,6.19,5540.0,5.91,5540.0,55.4,6933.33,55.4,55.4,55.4,55.4,55.4,55.4,7386.67,55.4,55.4,55.4
1103.62,1.17,1090.0,1.16,1090.0,10.9,10.31,10.31,10.31,1086.2,1086.2,1086.2,1086.2,1086.2,1086.2,1453.33,10.9
2600.34,2.77,2866.13,3.05,2866.13,10.91,0.0,0.0,0.0,0.0,2168.92,1999.7,2175.13,3036.83,2909.14,2887.45,2759.44
5174.66,5.51,4967.86,5.3,4967.86,16.15,5154.31,4621.59,5161.25,5080.73,5185.34,4981.24,6430.29,5584.57,5064.43,5029.16,4835.26
5693.03,6.07,5650.78,6.03,5650.78,5650.78,5433.44,5433.44,5433.44,5433.44,7244.59,5433.44,5433.44,5868.12,5650.78,5650.78,5650.78
2485.76,2.64,2810.52,2.99,2810.52,10.91,2193.56,1925.13,2352.46,2135.21,2440.66,2232.19,2951.81,2947.97,2588.45,2516.61,2734.59
3808.35,4.06,3893.4,4.15,3893.4,3893.4,37.8,37.8,37.8,37.8,37.8,37.8,37.8,37.8,37.8,37.8,4006.8
4648.0,4.95,4549.71,4.85,4549.71,4549.71,4212.7,4549.71,6066.28,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71
4521.62,4.82,4549.71,4.85,4549.71,4549.71,4212.7,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71,4549.71
3024.0,3.22,3024.0,3.22,3024.0,30.24,28.0,28.0,28.0,28.0,39.2,30.24,30.24,30.24,30.24,30.24,30.24
2946.43,3.14,2910.0,3.1,2910.0,1923.68,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,2983.7,2945.59

Just the columns starting with vl. There are several other variables which didn't need this procedure
Below is for BigQuery Standard SQL and uses BQ Scripting
execute immediate (select 'select * replace(' ||
string_agg('cast(replace(' || column || ', ",", ".") as float64) as ' || column, ', ') ||
') from YourTable'
from (
select regexp_extract_all(to_json_string(t), r'"(vl_[^"]*)":') as columns
from YourTable t
limit 1
), unnest(columns) column);
if to apply to below simplified example (it still fully represent OP's use case):
select 1 id, "0000006025,55" vl_x, "000006,42" y, "0000005921,09" vl_z union all
select 2, "0000001447,68", "000001,54", "0000001726,67"
output is
You should click on VIEW RESULTS of last row to see final result
Depends on what you want then to do with result - you can adjust code to replace YourTable with this output or create new one, etc. See example of such adjustment (just first line - the rest are the same)
execute immediate (select 'create table NewTable as select * replace(' ||
. . .

If you want a select query, you would just use:
SELECT CAST(REPLACE(wage_var, ',', '.') AS float64) as wage_formatted,
CAST(REPLACE(taxes_var, ',', '.') AS float64) as taxes_formatted,
. . .
FROM t;
If you want to do this "permanently" . . . well, I would suggest a view:
CREATE VIEW v_t AS
SELECT t.*,
CAST(REPLACE(wage_var, ',', '.') AS float64) as wage_formatted,
CAST(REPLACE(taxes_var, ',', '.') AS float64) as taxes_formatted,
. . .
FROM t;
You could also add new columns into the table and give them the floating point value.

How to sort a column in sql based on value B where values in fields are in format A-B-C. I w

I am trying to sort a column in a table where the value in the column is in format 00000197-001-00001 and so on.
I have tried with query
select * from <table name> where <condition> order by column name.
Values are sorted till 00000197-099-001. But after this, the value I am getting is 00000197-1000-001 in my list instead 00000197-100-001.
The result I am getting:
00000197-097-000001
00000197-098-000001
00000197-099-000001
00000197-1000-000001
00000197-100-000001
00000197-1001-000001
00000197-1002-000001
00000197-1003-000001
00000197-1004-000001
00000197-1005-000001
00000197-1006-000001
00000197-1007-000001
00000197-1008-000001
00000197-1009-000001
00000197-1010-000001
00000197-101-000001
00000197-1011-000001
00000197-1012-000001
Expected Result:
00000197-097-000001
00000197-098-000001
00000197-099-000001
00000197-100-000001
00000197-101-000001
.
.
.
00000197-999-000001
00000197-1000-000001
00000197-1001-000001
00000197-1002-000001
00000197-1003-000001
.
.
.
Please suggest the solution.
Many Thanks in advance.

Try this
SELECT *
FROM MyTable1
ORDER BY CAST(SUBSTRING(SUBSTRING(MyCol1, CHARINDEX('-', MyCol1, 0) + 1, 100), 0, CHARINDEX('-', substring(MyCol1, CHARINDEX('-', MyCol1, 0) + 1, 100), 0)) as int)
This works for every string of any length in format X-Y-Z.

Given your sample data, you can do:
order by len(column1), column1
This idea will work in any database, although the length function might be length() rather than len().

SQL query trim a column?

I am using the following query to populate some data. From column "query expression" is there a way to remove any text that is to the left of N'Domain\
Basically I only want to see the text after N'Domain\ in the column "Query Expression" Not sure how to do this.
SELECT
v_DeploymentSummary.SoftwareName,
v_DeploymentSummary.CollectionName,
v_CollectionRuleQuery.QueryExpression
FROM
v_DeploymentSummary
INNER JOIN v_CollectionRuleQuery
ON v_DeploymentSummary.CollectionID = v_CollectionRuleQuery.CollectionID

At least for SQL Server:
SUBSTRING([v_CollectionRuleQuery.QueryExpression], CHARINDEX('N''Domain\', [v_CollectionRuleQuery.QueryExpression]) + 9, LEN([v_CollectionRuleQuery.QueryExpression])
Give it a try.
I didn't understand if you wanted to include N'Domain\ in your string if that's the case just remove the +9.
In my understanding you want something like this:
SELECT
v_DeploymentSummary.SoftwareName,
v_DeploymentSummary.CollectionName,
SUBSTRING([v_CollectionRuleQuery.QueryExpression], CHARINDEX('N''Domain\', [v_CollectionRuleQuery.QueryExpression]) + 9, LEN([v_CollectionRuleQuery.QueryExpression])
FROM
v_DeploymentSummary
INNER JOIN v_CollectionRuleQuery
ON v_DeploymentSummary.CollectionID = v_CollectionRuleQuery.CollectionID

Try this, It will not change values for QueryExpression without the text N'Domain and does not require that N'Domain is the first text:
SELECT
ds.SoftwareName,
ds.CollectionName,
crq.QueryExpression
STUFF(crq.QueryExpression, 1, charindex('N''Domain\',
REPLICATE('w', LEN('N''Domain\')-1) + crq.QueryExpression), '')
FROM
v_DeploymentSummary ds
JOIN
v_CollectionRuleQuery crq
ON ds.CollectionID = crq.CollectionID
Example:
SELECT
STUFF(x, 1, charindex('N''Domain\',
replicate('w', LEN('N''Domain\')-1) + x), '')
FROM (values('N''Domain\xxx'),('N''Doma'),('xxN''Domain\yyy')) x(x)
Result:
xxx
N'Doma
yyy

In SQL Server, you can use stuff() for this purpose:
SELECT ds.SoftwareName, ds.CollectionName,
STUFF(crq.QueryExpression, 1,
CHARINDEX('Domain\', rq.QueryExpression) + LEN('Domain\') - 1,
'')
FROM v_DeploymentSummary ds INNER JOIN
v_CollectionRuleQuery crq
ON ds.CollectionID = crq.CollectionID;
Note the use of table aliases makes the query easier to write and to read.