Related
For example I have three table where say DataTable1, DataTable2 and DataTable3
and need to filter it from DataRange table, every time I have used NOT exist as shown below,
Is there a better way to write this.
Temp table to hold some daterange which is used for fiter:
Declare #DateRangeTable as Table(
StartDate datetime,
EndDate datetime
)
Some temp table which will hold data on which we need to apply date range filter
INSERT INTO #DateRangeTable values
('07/01/2020','07/04/2020'),
('07/06/2020','07/08/2020');
/*Table 1 which will hold some data*/
Declare #DataTable1 as Table(
Id numeric,
Date datetime
)
INSERT INTO #DataTable1 values
(1,'07/09/2020'),
(2,'07/06/2020');
Declare #DataTable2 as Table(
Id numeric,
Date datetime
)
INSERT INTO #DataTable2 values
(1,'07/10/2020'),
(2,'07/06/2020');
Declare #DataTable3 as Table(
Id numeric,
Date datetime
)
INSERT INTO #DataTable3 values
(1,'07/11/2020'),
(2,'07/06/2020');
Now I want to filter data based on DateRange table, here I need some optimized way so that i don't have to use not exists mutiple times, In real senario, I have mutiple tables where I have to filter based on the daterange table.
Select * from #DataTable1
where NOT EXISTS(
Select 1 from #DateRangeTable
where [Date] between StartDate and EndDate
)
Select * from #DataTable2
where NOT EXISTS(
Select 1 from #DateRangeTable
where [Date] between StartDate and EndDate
)
Select * from #DataTable3
where NOT EXISTS(
Select 1 from #DateRangeTable
where [Date] between StartDate and EndDate
)
Instead of using NOT EXISTS you could join the date range table:
SELECT dt.*
FROM #DataTable1 dt
LEFT JOIN #DateRangeTable dr ON dt.[Date] BETWEEN dr.StartDate and dr.EndDate
WHERE dr.StartDate IS NULL
It may perform better on large tables but you would have to compare the execution plans and make sure you have indexes on the date columns.
I would write the same query... but if you can change table structure I would try to improve performance adding two columns to specify the month as an integer (I suppose is the first couple of figures).
Obviously you have to test with your data and compare the timings.
Declare #DateRangeTable as Table(
StartDate datetime,
EndDate datetime,
StartMonth tinyint,
EndMonth tinyint
)
INSERT INTO #DateRangeTable values
('07/01/2020','07/04/2020', 7, 7),
('07/06/2020','07/08/2020', 7, 7),
('07/25/2020','08/02/2020', 7, 8); // (another record with different months)
Now your queries can use the new column to try to reduce comparisons (is a tinyint, sql server can partition records if you define a secondary index for StartMonth and EndMonth):
Select * from #DataTable1
where NOT EXISTS(
Select 1 from #DateRangeTable
where (DATEPART('month', [Date]) between StartMonth and EndMonth)
and ([Date] between StartDate and EndDate)
)
I have the set of data below which I created to emulate what my live data looks like. I am trying to pull the LATEST standard costs based on date ascending from a standard cost CTE where the dates considered are only those which are before the inventory transaction date. What I have so far is this, which works but is not very efficient based on the execution plan.
CREATE TABLE stdcosts
(item varchar(20) not null,
indt date not null,
rev integer not null,
[MC00.010] money default 0,
[OC00.000] money default 0,
[GC00.025] money default 0,
[MS00.010] money default 0) ;
INSERT INTO stdcosts
VALUES
('201226-03','02/26/2019',1,2000,0,100,50),
('201226-03','09/07/2019',2,700,0,0,50),
('201226-03','10/07/2019',3,500,0,20,10)
CREATE TABLE inventoryOH
(item varchar(20) not null,
warehouse varchar(8) not null,
TransDate date not null,
seq integer not null default 1,
owner varchar(10) ,
project varchar(10),
orderID varchar(10),
onHand integer default 0,
Age bigint,
costMethod varchar(15) ,
WVG_flag varchar(1),
WVG char(4),
rowno int );
INSERT INTO inventoryOH
VALUES
('201226-03','B','6/18/2019',1,'','','NPO312979',5,134,'STANDARD','N','',1),
('201226-03','B','9/3/2019',1,'','','NPO315960',14,57,'STANDARD','N','',2),
('201226-03','B','9/23/2019',1,'','','SFC037624',1,37,'STANDARD','N','',3),
('201226-03','B','10/1/2019',1,'','','NPO316472',6,29,'STANDARD','N','',4);
Output:
SELECT i.*, s.*
FROM inventoryOH i
LEFT JOIN stdcosts s
ON s.item = i.item
AND s.indt <= i.TransDate
AND s.rev IN (SELECT MAX(s1.rev)
FROM stdcosts s1
WHERE s1.item = s.item
AND s1.indt <= i.TransDate)
I am wondering if anyone has a way to optimize this using either a rank/row number or additional method(s) to make this run faster.
link --> http://sqlfiddle.com/#!18/2b4865/2
You can use OUTER APPLY to perform the lateral join.
For each row in inventoryOH we need to find one row from stdcosts, that has the same item, that has indt on or before TransDate and that has the maximum rev.
SELECT
inventoryOH.*
,Costs.*
FROM
inventoryOH
OUTER APPLY
(
SELECT TOP(1)
item
,indt
,rev
,[MC00.010]
,[OC00.000]
,[GC00.025]
,[MS00.010]
FROM stdcosts
WHERE
stdcosts.item = inventoryOH.item
AND stdcosts.indt <= inventoryOH.TransDate
ORDER BY
stdcosts.rev DESC
) AS Costs
;
To make it work efficiently you should create an index in stdcosts table on (item, indt) include (rev, [MC00.010],[OC00.000],[GC00.025],[MS00.010]). The order of columns in an index is important.
I'm not sure what should be the logic around the rev values, but if you need the latest row based only on indt (not on rev), then sorting should be by indt: ORDER BY stdcosts.indt DESC. It would also work more efficiently with the suggested index.
I need to store simple data - suppose I have some products with codes as a primary key, some properties and validity ranges. So data could look like this:
Products
code value begin_date end_date
10905 13 2005-01-01 2016-12-31
10905 11 2017-01-01 null
Those ranges are not overlapping, so on every date I have a list of unique products and their properties. So to ease the use of it I've created the function:
create function dbo.f_Products
(
#date date
)
returns table
as
return (
select
from dbo.Products as p
where
#date >= p.begin_date and
#date <= p.end_date
)
This is how I'm going to use it:
select
*
from <some table with product codes> as t
left join dbo.f_Products(#date) as p on
p.code = t.product_code
This is all fine, but how I can let optimizer know that those rows are unique to have better execution plan?
I did some googling, and found a couple of really nice articles for DDL which prevents storing overlapping ranges in the table:
Self-maintaining, Contiguous Effective Dates in Temporal Tables
Storing intervals of time with no overlaps
But even if I try those constraint I see that optimizer cannot understand that resulting recordset will return unique codes.
What I'd like to have is certain approach which gives me basically the same performance as if I stored those products list on certain date and selected it with date = #date.
I know that some RDMBS (like PostgreSQL) have special data types for this (Range Types). But SQL Server doesn't have anything like this.
Am I missing something or there're no way to do this properly in SQL Server?
You can create an indexed view that contains a row for each code/date in the range.
ProductDate (indexed view)
code value date
10905 13 2005-01-01
10905 13 2005-01-02
10905 13 ...
10905 13 2016-12-31
10905 11 2017-01-01
10905 11 2017-01-02
10905 11 ...
10905 11 Today
Like this:
create schema digits
go
create table digits.Ones (digit tinyint not null primary key)
insert into digits.Ones (digit) values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)
create table digits.Tens (digit tinyint not null primary key)
insert into digits.Tens (digit) values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)
create table digits.Hundreds (digit tinyint not null primary key)
insert into digits.Hundreds (digit) values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)
create table digits.Thousands (digit tinyint not null primary key)
insert into digits.Thousands (digit) values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)
create table digits.TenThousands (digit tinyint not null primary key)
insert into digits.TenThousands (digit) values (0),(1),(2),(3),(4),(5),(6),(7),(8),(9)
go
create schema info
go
create table info.Products (code int not null, [value] int not null, begin_date date not null, end_date date null, primary key (code, begin_date))
insert into info.Products (code, [value], begin_date, end_date) values
(10905, 13, '2005-01-01', '2016-12-31'),
(10905, 11, '2017-01-01', null)
create table info.DateRange ([begin] date not null, [end] date not null, [singleton] bit not null default(1) check ([singleton] = 1))
insert into info.DateRange ([begin], [end]) values ((select min(begin_date) from info.Products), getdate())
go
create view info.ProductDate with schemabinding
as
select
p.code,
p.value,
dateadd(day, ones.digit + tens.digit*10 + huns.digit*100 + thos.digit*1000 + tthos.digit*10000, dr.[begin]) as [date]
from
info.DateRange as dr
cross join
digits.Ones as ones
cross join
digits.Tens as tens
cross join
digits.Hundreds as huns
cross join
digits.Thousands as thos
cross join
digits.TenThousands as tthos
join
info.Products as p on
dateadd(day, ones.digit + tens.digit*10 + huns.digit*100 + thos.digit*1000 + tthos.digit*10000, dr.[begin]) between p.begin_date and isnull(p.end_date, datefromparts(9999, 12, 31))
go
create unique clustered index idx_ProductDate on info.ProductDate ([date], code)
go
select *
from info.ProductDate with (noexpand)
where
date = '2014-01-01'
drop view info.ProductDate
drop table info.Products
drop table info.DateRange
drop table digits.Ones
drop table digits.Tens
drop table digits.Hundreds
drop table digits.Thousands
drop table digits.TenThousands
drop schema digits
drop schema info
go
A solution without gaps might be this:
DECLARE #tbl TABLE(ID INT IDENTITY,[start_date] DATE);
INSERT INTO #tbl VALUES({d'2016-10-01'}),({d'2016-09-01'}),({d'2016-08-01'}),({d'2016-07-01'}),({d'2016-06-01'});
SELECT * FROM #tbl;
DECLARE #DateFilter DATE={d'2016-08-13'};
SELECT TOP 1 *
FROM #tbl
WHERE [start_date]<=#DateFilter
ORDER BY [start_date] DESC
Important: Be sure that there is an (unique) index on start_date
UPDATE: for different products
DECLARE #tbl TABLE(ID INT IDENTITY,ProductID INT,[start_date] DATE);
INSERT INTO #tbl VALUES
--product 1
(1,{d'2016-10-01'}),(1,{d'2016-09-01'}),(1,{d'2016-08-01'}),(1,{d'2016-07-01'}),(1,{d'2016-06-01'})
--product 1
,(2,{d'2016-10-17'}),(2,{d'2016-09-16'}),(2,{d'2016-08-15'}),(2,{d'2016-07-10'}),(2,{d'2016-06-11'});
DECLARE #DateFilter DATE={d'2016-08-13'};
WITH PartitionedCount AS
(
SELECT ROW_NUMBER() OVER(PARTITION BY ProductID ORDER BY [start_date] DESC) AS Nr
,*
FROM #tbl
WHERE [start_date]<=#DateFilter
)
SELECT *
FROM PartitionedCount
WHERE Nr=1
First you need to create a unique clustered index for (begin_date, end_date, code)
Then SQL engine will be able to do INDEX SEEK.
Additionally, you can also try to create a view for dbo.Products table to join that table with pre-populated dbo.Dates table.
select p.code, p.val, p.begin_date, p.end_date, d.[date]
from dbo.Product as p
inner join dbo.dates d on p.begin_date <= d.[date] and d.[date] <= p.end_date
Then in your function, you use that view as "where #date = view.date". The result can be either better or slightly worse... it depends on the actual data.
You also can try to make that view indexed (depends on how often it is being updated).
Alternatively, you can have better performance if you populate dbo.Products table for every date in the [begin_date] .. [end_date] range.
Approach with ROW_NUMBER scans the whole Products table once. It is the best method if you have a lot of product codes in the Products table and few validity ranges for each code.
WITH
CTE_rn
AS
(
SELECT
code
,value
,ROW_NUMBER() OVER (PARTITION BY code ORDER BY begin_date DESC) AS rn
FROM Products
WHERE begin_date <= #date
)
SELECT *
FROM
<some table with product codes> as t
LEFT JOIN CTE_rn ON CTE_rn.code = t.product_code AND CTE_rn.rn = 1
;
If you have few product codes and a lot of validity ranges for each code in the Products table, then it is better to seek the Products table for each code using OUTER APPLY.
SELECT *
FROM
<some table with product codes> as t
OUTER APPLY
(
SELECT TOP(1)
Products.value
FROM Products
WHERE
Products.code = t.product_code
AND Products.begin_date <= #date
ORDER BY Products.begin_date DESC
) AS A
;
Both variants need unique index on (code, begin_date DESC) include (value).
Note how the queries don't even look at end_date, because they assume that intervals don't have gaps. They will work in SQL Server 2008.
EDIT: My original answer was using an INNER JOIN, but the questioner wanted a LEFT JOIN.
CREATE TABLE Products
(
[Code] INT NOT NULL
, [Value] VARCHAR(30) NOT NULL
, Begin_Date DATETIME NOT NULL
, End_Date DATETIME NULL
)
/*
Products
code value begin_date end_date
10905 13 2005-01-01 2016-12-31
10905 11 2017-01-01 null
*/
INSERT INTO Products ([Code], [Value], Begin_Date, End_Date) VALUES (10905, 13, '2005-01-01', '2016-12-31')
INSERT INTO Products ([Code], [Value], Begin_Date, End_Date) VALUES (10905, 11, '2017-01-01', NULL)
CREATE NONCLUSTERED INDEX SK_ProductDate ON Products ([Code], Begin_Date, End_Date) INCLUDE ([Value])
CREATE TABLE SomeTableWithProductCodes
(
[CODE] INT NOT NULL
)
INSERT INTO SomeTableWithProductCodes ([Code]) VALUES (10905)
Here is a prototypical query, with a date predicate. Note that there are more optimal ways to do this in a bulletproof fashion, using a "less than" operator on the upper bound, but that's a different discussion.
SELECT
P.[Code]
, P.[Value]
, P.[Begin_Date]
, P.[End_Date]
FROM
SomeTableWithProductCodes ST
LEFT JOIN Products AS P ON
ST.[Code] = P.[Code]
AND '2016-06-30' BETWEEN P.[Begin_Date] AND ISNULL(P.[End_Date], '9999-12-31')
This query will perform an Index Seek on the Product table.
Here is a SQL Fiddle: SQL Fiddle - Products and Dates
I have a query that creates an #TABLE of a population of interest. It's structure is like this:
DECLARE #SepsisTbl TABLE (
PK INT IDENTITY(1, 1) PRIMARY KEY
, Name VARCHAR(500)
, MRN INT
, Account INT
, Age INT -- Age at arrival
, Arrival DATETIME
, Triage_StartDT DATETIME
, Left_ED_DT DATETIME
, Disposition VARCHAR(500)
, Mortality CHAR(1)
);
WITH Patients AS (
SELECT UPPER(Patient) AS [Name]
, MR#
, Account
, DATEDIFF(YEAR, AgeDob, Arrival) AS [Age_at_Arrival]
, Arrival
, Triage_Start
, TimeLeftED
, Disposition
, CASE
WHEN Disposition IN (
'Medical Examiner', 'Morgue'
)
THEN 'Y'
ELSE 'N'
END AS [Mortality]
FROM SMSDSS.c_Wellsoft_Rpt_tbl
WHERE Triage_Start IS NOT NULL
AND (
Diagnosis LIKE '%SEPSIS%'
OR
Diagnosis LIKE '%SEPTIC%'
)
)
INSERT INTO #SepsisTbl
SELECT * FROM Patients
From this point forward I have 5 more queries of the same sort that are looking for different types of orders that I then LEFT OUTER JOIN onto this table. My question is, why does my performance degrade so much when I change the where clause of the tables from this:
AND A.Account IN (
SELECT Account
FROM SMSDSS.c_Wellsoft_Rpt_tbl
WHERE (
Diagnosis LIKE '%SEPSIS%'
OR
Diagnosis LIKE '%SEPTIC%'
)
to this:
AND A.Account IN (
SELECT Account
FROM #SepsisTbl
)
The run time goes from 2.5 minutes to over 10 minutes with still no results. The CTE itself runs as fast as I can press F5.
Thank you,
I suspect that the problem is because the table variable doesn't have an index on Account. If you add an index on Account then I would expect better performance.
See the answer to this question for details on how to add an index: Creating an index on a table variable
EDITED:
I'm working in Sql Server 2005 and I'm trying to get a year over year (YOY) count of distinct users for the current fiscal year (say Jun 1-May 30) and the past 3 years. I'm able to do what I need by running a select statement four times, but I can't seem to find a better way at this point. I'm able to get a distinct count for each year in one query, but I need it to a cumulative distinct count. Below is a mockup of what I have so far:
SELECT [Year], COUNT(DISTINCT UserID)
FROM
(
SELECT u.uID AS UserID,
CASE
WHEN dd.ddEnd BETWEEN #yearOneStart AND #yearOneEnd THEN 'Year1'
WHEN dd.ddEnd BETWEEN #yearTwoStart AND #yearTwoEnd THEN 'Year2'
WHEN dd.ddEnd BETWEEN #yearThreeStart AND #yearThreeEnd THEN 'Year3'
WHEN dd.ddEnd BETWEEN #yearFourStart AND #yearFourEnd THEN 'Year4'
ELSE 'Other'
END AS [Year]
FROM Users AS u
INNER JOIN UserDataIDMatch AS udim
ON u.uID = udim.udim_FK_uID
INNER JOIN DataDump AS dd
ON udim.udimUserSystemID = dd.ddSystemID
) AS Data
WHERE LOWER([Year]) 'other'
GROUP BY
[Year]
I get something like:
Year1 1
Year2 1
Year3 1
Year4 1
But I really need:
Year1 1
Year2 2
Year3 3
Year4 4
Below is a rough schema and set of values (updated for simplicity). I tried to create a SQL Fiddle, but I'm getting a disk space error when I attempt to build the schema.
CREATE TABLE Users
(
uID int identity primary key,
uFirstName varchar(75),
uLastName varchar(75)
);
INSERT INTO Users (uFirstName, uLastName)
VALUES
('User1', 'User1'),
('User2', 'User2')
('User3', 'User3')
('User4', 'User4');
CREATE TABLE UserDataIDMatch
(
udimID int indentity primary key,
udim.udim_FK_uID int foreign key references Users(uID),
udimUserSystemID varchar(75)
);
INSERT INTO UserDataIDMatch (udim_FK_uID, udimUserSystemID)
VALUES
(1, 'SystemID1'),
(2, 'SystemID2'),
(3, 'SystemID3'),
(4, 'SystemID4');
CREATE TABLE DataDump
(
ddID int identity primary key,
ddSystemID varchar(75),
ddEnd datetime
);
INSERT INTO DataDump (ddSystemID, ddEnd)
VALUES
('SystemID1', '10-01-2013'),
('SystemID2', '10-01-2014'),
('SystemID3', '10-01-2015'),
('SystemID4', '10-01-2016');
Unless I'm missing something, you just want to know how many records there are where the date is less than or equal to the current fiscal year.
DECLARE #YearOneStart DATETIME, #YearOneEnd DATETIME,
#YearTwoStart DATETIME, #YearTwoEnd DATETIME,
#YearThreeStart DATETIME, #YearThreeEnd DATETIME,
#YearFourStart DATETIME, #YearFourEnd DATETIME
SELECT #YearOneStart = '06/01/2013', #YearOneEnd = '05/31/2014',
#YearTwoStart = '06/01/2014', #YearTwoEnd = '05/31/2015',
#YearThreeStart = '06/01/2015', #YearThreeEnd = '05/31/2016',
#YearFourStart = '06/01/2016', #YearFourEnd = '05/31/2017'
;WITH cte AS
(
SELECT u.uID AS UserID,
CASE
WHEN dd.ddEnd BETWEEN #yearOneStart AND #yearOneEnd THEN 'Year1'
WHEN dd.ddEnd BETWEEN #yearTwoStart AND #yearTwoEnd THEN 'Year2'
WHEN dd.ddEnd BETWEEN #yearThreeStart AND #yearThreeEnd THEN 'Year3'
WHEN dd.ddEnd BETWEEN #yearFourStart AND #yearFourEnd THEN 'Year4'
ELSE 'Other'
END AS [Year]
FROM Users AS u
INNER JOIN UserDataIDMatch AS udim
ON u.uID = udim.udim_FK_uID
INNER JOIN DataDump AS dd
ON udim.udimUserSystemID = dd.ddSystemID
)
SELECT
DISTINCT [Year],
(SELECT COUNT(*) FROM cte cteInner WHERE cteInner.[Year] <= cteMain.[Year] )
FROM cte cteMain
Concept using an existing query
I have done something similar for finding out the number of distinct customers who bought something in between years, I modified it to use your concept of year, the variables you add would be that start day and start month of the year and the start year and end year.
Technically there is a way to avoid using a loop but this is very clear and you can't go past year 9999 so don't feel like putting clever code to avoid a loop makes sense
Tips for speeding up the query
Also when matching dates make sure you are comparing dates, and not comparing a function evaluation of the column as that would mean running the function on every record set and would make indices useless if they existed on dates (which they should). Use date add on
zero to initiate your target dates subtracting 1900 from the year, one from the month and one from the target date.
Then self join on the table where the dates create a valid range (i.e. yearlessthan to yearmorethan) and use a subquery to create a sum based on that range. Since you want accumulative from the first year to the last limit the results to starting at the first year.
At the end you will be missing the first year as by our definition it does not qualify as a range, to fix this just do a union all on the temp table you created to add the missing year and the number of distinct values in it.
DECLARE #yearStartMonth INT = 6, #yearStartDay INT = 1
DECLARE #yearStart INT = 2008, #yearEnd INT = 2012
DECLARE #firstYearStart DATE =
DATEADD(day,#yearStartDay-1,
DATEADD(month, #yearStartMonth-1,
DATEADD(year, #yearStart- 1900,0)))
DECLARE #lastYearEnd DATE =
DATEADD(day, #yearStartDay-2,
DATEADD(month, #yearStartMonth-1,
DATEADD(year, #yearEnd -1900,0)))
DECLARE #firstdayofcurrentyear DATE = #firstYearStart
DECLARE #lastdayofcurrentyear DATE = DATEADD(day,-1,DATEADD(year,1,#firstdayofcurrentyear))
DECLARE #yearnumber INT = YEAR(#firstdayofcurrentyear)
DECLARE #tempTableYearBounds TABLE
(
startDate DATE NOT NULL,
endDate DATE NOT NULL,
YearNumber INT NOT NULL
)
WHILE #firstdayofcurrentyear < #lastYearEnd
BEGIN
INSERT INTO #tempTableYearBounds
VALUES(#firstdayofcurrentyear,#lastdayofcurrentyear,#yearNumber)
SET #firstdayofcurrentyear = DATEADD(year,1,#firstdayofcurrentyear)
SET #lastdayofcurrentyear = DATEADD(year,1,#lastdayofcurrentyear)
SET #yearNumber = #yearNumber + 1
END
DECLARE #tempTableCustomerCount TABLE
(
[Year] INT NOT NULL,
[CustomerCount] INT NOT NULL
)
INSERT INTO #tempTableCustomerCount
SELECT
YearNumber as [Year],
COUNT(DISTINCT CustomerNumber) as CutomerCount
FROM Ticket
JOIN #tempTableYearBounds ON
TicketDate >= startDate AND TicketDate <=endDate
GROUP BY YearNumber
SELECT * FROM(
SELECT t2.Year as [Year],
(SELECT
SUM(CustomerCount)
FROM #tempTableCustomerCount
WHERE Year>=t1.Year
AND Year <=t2.Year) AS CustomerCount
FROM #tempTableCustomerCount t1 JOIN #tempTableCustomerCount t2
ON t1.Year < t2.Year
WHERE t1.Year = #yearStart
UNION
SELECT [Year], [CustomerCount]
FROM #tempTableCustomerCount
WHERE [YEAR] = #yearStart
) tt
ORDER BY tt.Year
It isn't efficient but at the end the temp table you are dealing with is so small I don't think it really matters, and adds a lot more versatility versus the method you are using.
Update: I updated the query to reflect the result you wanted with my data set, I was basically testing to see if this was faster, it was faster by 10 seconds but the dataset I am dealing with is relatively small. (from 12 seconds to 2 seconds).
Using your data
I changed the tables you gave to temp tables so it didn't effect my environment and I removed the foreign key because they are not supported for temp tables, the logic is the same as the example included but just changed for your dataset.
DECLARE #startYear INT = 2013, #endYear INT = 2016
DECLARE #yearStartMonth INT = 10 , #yearStartDay INT = 1
DECLARE #startDate DATETIME = DATEADD(day,#yearStartDay-1,
DATEADD(month, #yearStartMonth-1,
DATEADD(year,#startYear-1900,0)))
DECLARE #endDate DATETIME = DATEADD(day,#yearStartDay-1,
DATEADD(month,#yearStartMonth-1,
DATEADD(year,#endYear-1899,0)))
DECLARE #tempDateRangeTable TABLE
(
[Year] INT NOT NULL,
StartDate DATETIME NOT NULL,
EndDate DATETIME NOT NULL
)
DECLARE #currentDate DATETIME = #startDate
WHILE #currentDate < #endDate
BEGIN
DECLARE #nextDate DATETIME = DATEADD(YEAR, 1, #currentDate)
INSERT INTO #tempDateRangeTable(Year,StartDate,EndDate)
VALUES(YEAR(#currentDate),#currentDate,#nextDate)
SET #currentDate = #nextDate
END
CREATE TABLE Users
(
uID int identity primary key,
uFirstName varchar(75),
uLastName varchar(75)
);
INSERT INTO Users (uFirstName, uLastName)
VALUES
('User1', 'User1'),
('User2', 'User2'),
('User3', 'User3'),
('User4', 'User4');
CREATE TABLE UserDataIDMatch
(
udimID int indentity primary key,
udim.udim_FK_uID int foreign key references Users(uID),
udimUserSystemID varchar(75)
);
INSERT INTO UserDataIDMatch (udim_FK_uID, udimUserSystemID)
VALUES
(1, 'SystemID1'),
(2, 'SystemID2'),
(3, 'SystemID3'),
(4, 'SystemID4');
CREATE TABLE DataDump
(
ddID int identity primary key,
ddSystemID varchar(75),
ddEnd datetime
);
INSERT INTO DataDump (ddSystemID, ddEnd)
VALUES
('SystemID1', '10-01-2013'),
('SystemID2', '10-01-2014'),
('SystemID3', '10-01-2015'),
('SystemID4', '10-01-2016');
DECLARE #tempIndividCount TABLE
(
[Year] INT NOT NULL,
UserCount INT NOT NULL
)
-- no longer need to filter out other because you are using an
--inclusion statement rather than an exclusion one, this will
--also make your query faster (when using real tables not temp ones)
INSERT INTO #tempIndividCount(Year,UserCount)
SELECT tdr.Year, COUNT(DISTINCT UId) FROM
Users u JOIN UserDataIDMatch um
ON um.udim_FK_uID = u.uID
JOIN DataDump dd ON
um.udimUserSystemID = dd.ddSystemID
JOIN #tempDateRangeTable tdr ON
dd.ddEnd >= tdr.StartDate AND dd.ddEnd < tdr.EndDate
GROUP BY tdr.Year
-- will show you your result
SELECT * FROM #tempIndividCount
--add any ranges that did not have an entry but were in your range
--can easily remove this by taking this part out.
INSERT INTO #tempIndividCount
SELECT t1.Year,0 FROM
#tempDateRangeTable t1 LEFT OUTER JOIN #tempIndividCount t2
ON t1.Year = t2.Year
WHERE t2.Year IS NULL
SELECT YearNumber,UserCount FROM (
SELECT 'Year'+CAST(((t2.Year-t1.Year)+1) AS CHAR) [YearNumber] ,t2.Year,(
SELECT SUM(UserCount)
FROM #tempIndividCount
WHERE Year >= t1.Year AND Year <=t2.Year
) AS UserCount
FROM #tempIndividCount t1
JOIN #tempIndividCount t2
ON t1.Year < t2.Year
WHERE t1.Year = #startYear
UNION ALL
--add the missing first year, union it to include the value
SELECT 'Year1',Year, UserCount FROM #tempIndividCount
WHERE Year = #startYear) tt
ORDER BY tt.Year
Benefits over using a WHEN CASE based approach
More Robust
Do not need to explicitly determine the end and start dates of each year, just like in a logical year just need to know the start and end date. Can easily change what you are looking for with some simple modifications(i.e. say you want all 2 year ranges or 3 year).
Will be faster if the database is indexed properly
Since you are searching based on the same data type you can utilize the indices that should be created on the date columns in the database.
Cons
More Complicated
The query is a lot more complicated to follow, even though it is more robust there is a lot of extra logic in the actual query.
In some circumstance will not provide good boost to execution time
If the dataset is very small, or the number of dates being compared isn't significant then this could not save enough time to be worth it.
In SQL Server once you match a WHEN inside a CASE, it stop evaluating will not going on evaluating next WHEN clauses. Hence you can't accumulate that way.
if I understand you correctly, this would show your results.
;WITH cte AS
(F
SELECT dd.ddEnd [dateEnd], u.uID AS UserID
FROM Users AS u
INNER JOIN UserDataIDMatch AS udim
ON u.uID = udim.udim_FK_uID
INNER JOIN DataDump AS dd
ON udim.udimUserSystemID = dd.ddSystemID
WHERE ddEnd BETWEEN #FiscalYearStart AND #FiscalYearEnd3
)
SELECT datepart(year, #FiscalYearStart) AS [Year], COUNT(DISTINCT UserID) AS CntUserID
FROM cte
WHERE dateEnd BETWEEN #FiscalYearStart AND #FiscalYearEnd1
GROUP BY #FiscalYearStart
UNION
SELECT datepart(year, #FiscalYearEnd1) AS [Year], COUNT(DISTINCT UserID) AS CntUserID
FROM cte
WHERE dateEnd BETWEEN #FiscalYearStart AND #FiscalYearEnd2
GROUP BY #FiscalYearEnd1
UNION
SELECT datepart(year, #FiscalYearEnd3) AS [Year], COUNT(DISTINCT UserID) AS CntUserID
FROM cte
WHERE dateEnd BETWEEN #FiscalYearStart AND #FiscalYearEnd3
GROUP BY #FiscalYearEnd2