Sep 15

My links of the week – September 15, 2013

big-data

As a way to at least keep me writing, I am starting a links of the week category of post, that I expect to be a weekly staple. Links can cover just about any issue I find interesting, from technology to politics. So, let’s start.

  • My favorite link of the week is Derek Colley’s  Compare Big Data Platforms vs.SQL Server.

    NoSQL is a big word these days, and although there are good reasons to pick a NoSQL platform, it obviously should be done only when that choice is actually the best possible choice for the situation at hand. Derek makes a good presentation of the reasons relational databases are still a great solution, when they fit the bill. Every so often a new type technology is hyped beyond reason and that is surely the case with NoSQL. Derek’s article brings some sense into the discussion and even points out some of the issues in NoSQL technologies that may have a negative impact in the future.

  • Rob Farley’s Not-So-Dirty SQL Hacks presents a couple of interestings hacks for string concatenation in T-SQL.
  • David Kuhsner’s The Geeks in the Front Lines is an interesting account of how hackers are in short supply and are being hired by the US government to shore up cyber defenses.

That’s all for this week. 

Image courtesy of photoexplorer / FreeDigitalPhotos.net

Mar 22

Set thinking

It’s quite frequent to read about the efficiency of relational database systems when executing set based operations. Relational DBMSs are, indeed, efficient when executing set based operations especially when compared to cursor based operations. Of course, the debate can become quite heated, leading some people to excommunicate cursor based operations as the devil incarnate of inefficiency. As in everything, such views regarding cursors are extreme, as there are situations where cursors may be a valid choice. While the focus is usually on avoiding cursors, there are other ways in which we can take advantage of the efficiency of set operations. A situation I faced recently involved a stored procedure that was being executed multiple times, with a single changing value each time. The situation is illustrated by the stored procedure shown below (Initial Stored Proc). The stored proc performs a few queries similar to one included.
CREATE PROC myProc(@year int, @month int)
As

-- Temporary table to hold just the relevant cost centers

CREATE TABLE #CC (
	CCID int,
	 CCName varchar(1000)
	);

-- Add the cost centers to the temp table
INSERT INTO #CC
SELECT DISTINCT C.Id, C.Name
	FROM AccountsInCostCenters AI INNER JOIN CostCenters C ON AI.CostCenterId=C.Id
	 WHERE AI.Year=@year or AI.Year=@year-1

-- calculate the results and add them to the results table

INSERT INTO DemoViewFinalResults(GroupID,AccountLevel,RowType,Value,[Year],[Month],(...),CostCenterID,CostCenterName)
SELECT D.GroupID, D.GroupOrder,D.RowOrder,D.AccountID,A.[Description],D.AccountSign, D.AccountLevel,4,
(SELECT SUM(F2.Value) FROM DemoViewFinalResults F2 
						WHERE F2.AccountID IN (SELECT C.AccountID FROM CalcRowAssociatedAccountID C WHERE C.RefRowID=D.RowID)
						AND F2.GroupID = D.GroupID AND F2.Month=@month and F2.Year=@year AND F2.CostCenterID=C.CCID) As Value,
		@year,@month,NULL,D.OriginalRow, C.CCID,C.CCName
FROM DemoViewAccountsAssociatedRowModel D INNER JOIN Accounts A ON A.Id = D.AccountId, #CC C
WHERE D.RowType=2 AND D.IncludeAccount=1;

(...)
The stored procedure was being executed multiples times, one for each month needed, with a simple loop, as illustrated below.
DECLARE @month int
DECLARE @year int

SET @month = 1

WHILE @month < 8
BEGIN
	exec myProc @year,@month
END
Some investment had been done making sure each query running in the stored procedure was optimized. The queries are used to implement a datasheet recursive model, so it was rather hard to avoid correlated subqueries and the individual query performance was good enough. The problem was that, in some cases, we needed to execute the stored procedure for multiple months and the overall execution time for was unsatisfactory, so we need to do much better in such situations. The solution for the performance issue, was of course, in taking advantage of set operations. Instead of looping for each month, we could just execute the code once, if we had a way to have all the required year / month pairs in a table, just as we had done for the cost centers (you can, in line #30 see that the temporary table #CC is cross-joined into the query). The approach used in the final stored procedure is shown below. Lines #23-34 show the new temporary table and the code used to add all the needed records, which are the ones resulting from a cross-join between the “previous version” table and a new temporary table containing all the month / year pairs. 
CREATE PROC myProcForMultipleMonths(@year int, @startMonth int)
As

CREATE TABLE #Months_Years (
	[Month] int,
	[Year] int
	);

DECLARE @tMonth int,
		@tYear int

SET @tMonth = 1

WHILE @tMonth <= @startMonth 
BEGIN
	INSERT INTO #Months_Years
		SELECT @tMonth,@year

	SET @tMonth = @tMonth + 1
END

CREATE TABLE #CC (
	 CCID int,
	 CCName varchar(1000),
	 [Month] int,
	 [Year] int
	 );

INSERT INTO #CC
SELECT DISTINCT C.Id, C.Name, MY.[Month],MY.[Year]
	FROM AccountsInCostCenters AI INNER JOIN CostCenters C ON AI.CostCenterId=C.Id, #Months_Years MY
	 WHERE AI.Year=@year or AI.Year=@year-1

INSERT INTO DemoViewFinalResults 
	(GroupID,GroupOrder,RowOrder,AccountID,AccountDescription,AccountSign,AccountLevel,RowType,Value,[Year],[Month],Reference,OriginalRow,CostCenterID,CostCenterName)
	SELECT D.GroupID, D.GroupOrder,D.RowOrder,D.AccountID,A.[Description],D.AccountSign, D.AccountLevel,4,
	(SELECT SUM(IsNULL(F2.Value,0)) FROM DemoViewFinalResults F2 
						  WHERE F2.AccountID IN (SELECT C.AccountID FROM CalcRowAssociatedAccountID C WHERE C.RefRowID=D.RowID)
						  AND F2.GroupID = D.GroupID AND F2.Month=C.month and F2.Year=C.year AND F2.CostCenterID=C.CCID) As Value,
		   C.year,C.month,NULL,D.OriginalRow, C.CCID,C.CCName
	FROM DemoViewAccountsAssociatedRowModel D INNER JOIN Accounts A ON A.Id = D.AccountId, #CC C
	WHERE D.RowType=2 AND D.IncludeAccount=1;

(...)
This approach resulted in a very obvious performance improvement, since execution time was reduced to less than a third of the time needed to execute the first version of the procedure for the same number of months. The execution time is obviously reduced because operations that were being performed as many times as there were months, now are done just once, regardless of the number of months. The join including the year and month ensures that. This major improvement was essential to validate this approach as a feasible solution to to initial performance problem we set to solve. This overall result showed, yet again, the advantages of adopting a set based “thinking” and it made clear that we can avoid cursors and still fall into a similar performance trap.  The solution here  came from a temporary table, used in a cross-join. A simple solution with a remarkable impact on performance.