declare - Page 25 - Developer IT

interface section of a unit??

- by osabri

how we declare in interface section of a unit ???

How to Compare two strings using a if in a stored procedure in sql server 2008?

- by VJ

I want to do something like this- declare @temp as varchar set @temp='Measure' if(@temp == 'Measure') Select Measure from Measuretable else Select OtherMeasure from Measuretable

Is a selector like + safe to use?

I recently came across this CSS selector while trying to find a way to easily space out major blog elements such as paragraphs and images. An example of its use would be something like this: .post *+* {margin-top: 15px;} /* or... */ .post > *+* {margin-top: 15px;} /* if you don't want the margin to apply to nested elements */ At first glance, it seemed pretty useful. So my question is: What downsides are there to using these selectors? Specifically: What's the browser support like for this? Are there any cases you wouldn't want an even margin spacing between elements in an article and if not, is it easier to declare this first and then overwrite or simply declare each element individually? Does this have performance issues since you're selecting everything twice?

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How to change a vairable type in C#?

- by Mosho Mulan

I wanted to use something like this: if(x==5) { var mydb= ........ ; } else { var mydb = ........ ; } but it didn't work because I can't declare a variable inside if statement. So I tried to do this: var mydb; if (x==5) { mydb= ............. ; } else { mydb=.............; } but id didn't work either because I had to initialize the variable (mydb). So the question is: I don't necessarily know the type of the variable, can I declare it anyway and then change the type inside the if statement?

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How to avoid Foreign Keys constraints for all tables in DB truncate ?

- by eugeneK

Hi, for designing purposes i need to truncate all DB which has lots of FK's. I cannot use DELETE command simply because some tables set with Identity of TinyInts and contain about 150 items. this is a query ( truncate all tables in selected DB ) i'm trying to run Declare @t varchar (1024) Declare tbl_cur cursor for select TABLE_NAME from INFORMATION_SCHEMA.TABLES WHERE TABLE_TYPE = 'BASE TABLE' OPEN tbl_cur FETCH NEXT from tbl_cur INTO @t WHILE @@FETCH_STATUS = 0 BEGIN EXEC ('TRUNCATE TABLE '+ @t) FETCH NEXT from tbl_cur INTO @t END CLOSE tbl_cur DEALLOCATE tbl_Cur What the best and easiest way to achieve truncate on DB with many FK's ?

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Loop through non-integer rows using SQL

- by Jesse

I know how to accomplish my task with .NET, but I wanted to do this just in SQL. I need to loop through all of the rows where the primary key is somewhat arbitrary. It can be a number or a series of letters, and probably any number of unusual things. I know I could do something like this... DECLARE @numRows INT SET @numRows = (SELECT COUNT(pkField) FROM myTable) DECLARE @I INT SET @I = 1 WHILE (@I <= @numRows) BEGIN --Do what I need to here SET @I = @I + 1 END ...if my rows were indexed in a contiguous fashion, but I don't know enough about SQL to do that if they're not. I keep coming across the use of "cursors," but I come across just as much reading about avoiding cursors. I found this SO solution but I'm not sure if that's what I'm needing? I appreciate any ideas.

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exec sp_executesql error 'Incorrect syntax near 1' when using datetime parameter

- by anne78

I have a Ssrs report which sends the following text to the database : EXEC ( 'DECLARE @TeamIds as TeamIdTableType ' + @Teams + ' EXEC rpt.DWTypeOfSicknessByCategoryReport @TeamIds , ' + @DateFrom + ', ' + @DateTo + ', ' + @InputRankGroups + ', ' + @SubCategories ) When I view this in profiler it interprets this as : exec sp_executesql N'EXEC ( ''DECLARE @TeamIds as TeamIdTableType '' + @Teams + '' EXEC rpt.DWTypeOfSicknessByCategoryAndEmployeeDetailsReport @TeamIds, '' + @DateFrom + '', '' + @DateTo + '', '' + @InputRankGroups + '', '' + @SubCategories )',N'@Teams nvarchar(34),@DateFrom datetime,@DateTo datetime,@InputRankGroups varchar(1),@SubCategories bit',@Teams=N'INSERT INTO @TeamIds VALUES (5); ',@DateFrom='2010-02-01 00:00:00',@DateTo='2010-04-30 00:00:00',@InputRankGroups=N'1',@SubCategories=1 When this sql runs it errors, on the dates. I have tried changing the format of the date but it does not help. If I remove the dates it works fine. Any help would be appreciated.

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Determining child count of path

- by sqlnewbie

I have a table whose 'path' column has values and I would like to update the table's 'child_count' column so that I get the following output. path | child_count --------+------------- | 5 /a | 3 /a/a | 0 /a/b | 1 /a/b/c | 0 /b | 0 My present solution - which is way too inefficient - uses a stored procedure as follows: CREATE FUNCTION child_count() RETURNS VOID AS $$ DECLARE parent VARCHAR; BEGIN FOR parent IN SELECT path FROM my_table LOOP DECLARE tokens VARCHAR[] := REGEXP_SPLIT_TO_ARRAY(parent, '/'); str VARCHAR := ''; BEGIN FOR i IN 2..ARRAY_LENGTH(tokens, 1) LOOP UPDATE my_table SET child_count = child_count + 1 WHERE path = str; str := str || '/' || tokens[i]; END LOOP; END; END LOOP; END; $$ LANGUAGE plpgsql; Anyone knows of a single UPDATE statement that does the same thing?

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C++ User-Defined Vector

- by Berlioz

How do you declare a vector in c++ while allowing user input to define the vector's name?

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Encryption By Certificate

- by user1817240

I am encrypting customer name in database at database level. While saving in database only first letter of customer name is saved and hence while decrypting only first letter is retrieved. The following code shows the test sp. ALTER PROCEDURE [dbo].[spc_test_insert] ( @sFIRST_NAME typ_encryptedtext, ) AS BEGIN DECLARE @sSENCRYPTION_KEY char(15) DECLARE @sCERTIFICATE char(22) SET @sSENCRYPTION_KEY='SymmetricKey1' SET @sCERTIFICATE='CustomerCertificate' OPEN SYMMETRIC KEY SymmetricKey1 DECRYPTION BY CERTIFICATE CustomerCertificate; INSERT INTO test_table ( FIRST_NAME, ) Values ( -- Add the Params to be Added... EncryptByKey(Key_GUID(@sSENCRYPTION_KEY),@sFIRST_NAME), ) CLOSE SYMMETRIC KEY SymmetricKey1 END encryption decryption working fine in normal insert but its not working in stored procedure.

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About memory and delete object in c++

- by barssala

I will give some examples and explain. First, I declare some object like CString* param = new CString[100] And when I declare this one, my memory would increase a little bit because it's some implemented string. Then I store this object in some list of CString just like List<CString> myList = new List<CString>; // new list of CString myList.add(param); This is my question: I wanna know, when I delete myList, my param isn't deleted, right? And memory in param still exists. Do I misunderstand?

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Having access to a private variable from other classes in Java

- by Crystal

If I want to create a form that adds people to a List, how do I have access to that List from another class? Where would I define that List so other classes can access the members, the size, etc? For example, if I have Class Foo that has the GUI for my form, along with buttons to add and remove people to the List, it would make sense to me to declare the List as a private instance variable of Class Foo. But then if I have another class, Class Bar, how does it get the values that are currently in that List to update some other graphical components? Or is that the wrong place to declare the List in general? Thanks.

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Iterators over a LInked List in a Game in Java

- by Matthew

I am using OpenGl in android and they have a callback method called draw that gets called with out my control. (As fast as the device can handle if I am not mistaken) I have a list of "GameObjects" that have a .draw method and a .update method. I have two different threads that handle each of those. So, the question is, can I declare two different iterators in two different methods in two different threads that iterate over the same Linked List? If so, do I simply declare ListIterator<GameObject> l = objets.listIterator() each time I want a new iterator and it won't interfere with other iterators?

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Microsoft SQL Server xml data

- by cf_PhillipSenn

This site has a technique to pass xml data around in Microsoft SQL Server: DECLARE @productIds xml SET @productIds ='<Products><id>3</id><id>6</id><id>15</id></Products>' SELECT ParamValues.ID.value('.','VARCHAR(20)') FROM @productIds.nodes('/Products/id') as ParamValues(ID) But what is the syntax if I add another field? The following does NOT work: DECLARE @productIds xml SET @productIds ='<Products><id>3</id><descr>Three</descr><id>6</id><descr>six</descr><id>15</id><descr>Fifteen</descr></Products>' SELECT ParamValues.ID.value('.','VARCHAR(20)') ,ParamValues.descr.value('.','VARCHAR(20)') FROM @productIds.nodes('/Products/id') as ParamValues(ID) Note: Maybe I've constructed my xml wrong.

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Dynamic Types and DynamicObject References in C#

- by Rick Strahl

I've been working a bit with C# custom dynamic types for several customers recently and I've seen some confusion in understanding how dynamic types are referenced. This discussion specifically centers around types that implement IDynamicMetaObjectProvider or subclass from DynamicObject as opposed to arbitrary type casts of standard .NET types. IDynamicMetaObjectProvider types are treated special when they are cast to the dynamic type. Assume for a second that I've created my own implementation of a custom dynamic type called DynamicFoo which is about as simple of a dynamic class that I can think of:public class DynamicFoo : DynamicObject { Dictionary<string, object> properties = new Dictionary<string, object>(); public string Bar { get; set; } public DateTime Entered { get; set; } public override bool TryGetMember(GetMemberBinder binder, out object result) { result = null; if (!properties.ContainsKey(binder.Name)) return false; result = properties[binder.Name]; return true; } public override bool TrySetMember(SetMemberBinder binder, object value) { properties[binder.Name] = value; return true; } } This class has an internal dictionary member and I'm exposing this dictionary member through a dynamic by implementing DynamicObject. This implementation exposes the properties dictionary so the dictionary keys can be referenced like properties (foo.NewProperty = "Cool!"). I override TryGetMember() and TrySetMember() which are fired at runtime every time you access a 'property' on a dynamic instance of this DynamicFoo type. Strong Typing and Dynamic Casting I now can instantiate and use DynamicFoo in a couple of different ways: Strong TypingDynamicFoo fooExplicit = new DynamicFoo(); var fooVar = new DynamicFoo(); These two commands are essentially identical and use strong typing. The compiler generates identical code for both of them. The var statement is merely a compiler directive to infer the type of fooVar at compile time and so the type of fooExplicit is DynamicFoo, just like fooExplicit. This is very static - nothing dynamic about it - and it completely ignores the IDynamicMetaObjectProvider implementation of my class above as it's never used. Using either of these I can access the native properties:DynamicFoo fooExplicit = new DynamicFoo();// static typing assignmentsfooVar.Bar = "Barred!"; fooExplicit.Entered = DateTime.Now; // echo back static values Console.WriteLine(fooVar.Bar); Console.WriteLine(fooExplicit.Entered); but I have no access whatsoever to the properties dictionary. Basically this creates a strongly typed instance of the type with access only to the strongly typed interface. You get no dynamic behavior at all. The IDynamicMetaObjectProvider features don't kick in until you cast the type to dynamic. If I try to access a non-existing property on fooExplicit I get a compilation error that tells me that the property doesn't exist. Again, it's clearly and utterly non-dynamic. Dynamicdynamic fooDynamic = new DynamicFoo(); fooDynamic on the other hand is created as a dynamic type and it's a completely different beast. I can also create a dynamic by simply casting any type to dynamic like this:DynamicFoo fooExplicit = new DynamicFoo(); dynamic fooDynamic = fooExplicit; Note that dynamic typically doesn't require an explicit cast as the compiler automatically performs the cast so there's no need to use as dynamic. Dynamic functionality works at runtime and allows for the dynamic wrapper to look up and call members dynamically. A dynamic type will look for members to access or call in two places: Using the strongly typed members of the object Using theIDynamicMetaObjectProvider Interface methods to access members So rather than statically linking and calling a method or retrieving a property, the dynamic type looks up - at runtime - where the value actually comes from. It's essentially late-binding which allows runtime determination what action to take when a member is accessed at runtime *if* the member you are accessing does not exist on the object. Class members are checked first before IDynamicMetaObjectProvider interface methods are kick in. All of the following works with the dynamic type:dynamic fooDynamic = new DynamicFoo(); // dynamic typing assignments fooDynamic.NewProperty = "Something new!"; fooDynamic.LastAccess = DateTime.Now; // dynamic assigning static properties fooDynamic.Bar = "dynamic barred"; fooDynamic.Entered = DateTime.Now; // echo back dynamic values Console.WriteLine(fooDynamic.NewProperty); Console.WriteLine(fooDynamic.LastAccess); Console.WriteLine(fooDynamic.Bar); Console.WriteLine(fooDynamic.Entered); The dynamic type can access the native class properties (Bar and Entered) and create and read new ones (NewProperty,LastAccess) all using a single type instance which is pretty cool. As you can see it's pretty easy to create an extensible type this way that can dynamically add members at runtime dynamically. The Alter Ego of IDynamicObject The key point here is that all three statements - explicit, var and dynamic - declare a new DynamicFoo(), but the dynamic declaration results in completely different behavior than the first two simply because the type has been cast to dynamic. Dynamic binding means that the type loses its typical strong typing, compile time features. You can see this easily in the Visual Studio code editor. As soon as you assign a value to a dynamic you lose Intellisense and you see which means there's no Intellisense and no compiler type checking on any members you apply to this instance. If you're new to the dynamic type it might seem really confusing that a single type can behave differently depending on how it is cast, but that's exactly what happens when you use a type that implements IDynamicMetaObjectProvider. Declare the type as its strong type name and you only get to access the native instance members of the type. Declare or cast it to dynamic and you get dynamic behavior which accesses native members plus it uses IDynamicMetaObjectProvider implementation to handle any missing member definitions by running custom code. You can easily cast objects back and forth between dynamic and the original type:dynamic fooDynamic = new DynamicFoo(); fooDynamic.NewProperty = "New Property Value"; DynamicFoo foo = fooDynamic; foo.Bar = "Barred"; Here the code starts out with a dynamic cast and a dynamic assignment. The code then casts back the value to the DynamicFoo. Notice that when casting from dynamic to DynamicFoo and back we typically do not have to specify the cast explicitly - the compiler can induce the type so I don't need to specify as dynamic or as DynamicFoo. Moral of the Story This easy interchange between dynamic and the underlying type is actually super useful, because it allows you to create extensible objects that can expose non-member data stores and expose them as an object interface. You can create an object that hosts a number of strongly typed properties and then cast the object to dynamic and add additional dynamic properties to the same type at runtime. You can easily switch back and forth between the strongly typed instance to access the well-known strongly typed properties and to dynamic for the dynamic properties added at runtime. Keep in mind that dynamic object access has quite a bit of overhead and is definitely slower than strongly typed binding, so if you're accessing the strongly typed parts of your objects you definitely want to use a strongly typed reference. Reserve dynamic for the dynamic members to optimize your code. The real beauty of dynamic is that with very little effort you can build expandable objects or objects that expose different data stores to an object interface. I'll have more on this in my next post when I create a customized and extensible Expando object based on DynamicObject.© Rick Strahl, West Wind Technologies, 2005-2012Posted in CSharp .NET Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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using ‘using’ and scope. Not try finally!

- by Edward Boyle

An object that implements IDisposable has, you guessed it, a Dispose() method. In the code you write you should both declare and instantiate any object that implements IDisposable with the using statement. The using statement allows you to set the scope of an object and when your code exits that scope, the object will be disposed of. Note that when an exception occurs, this will pull your code out of scope, so it still forces a Dispose() using (mObject o = new mObject()) { // do stuff } //<- out of Scope, object is disposed. // Note that you can also use multiple objects using // the using statement if of the same type: using (mObject o = new mObject(), o2 = new mObject(), o3 = new mObject()) { // do stuff } //<- out of Scope, objects are disposed. What about try{ }finally{}? It is not needed when you use the using statement. Additionally, using is preferred, Microsoft’s own documents put it this way: As a rule, when you use an IDisposable object, you should declare and instantiate it in a using statement. When I started out in .NET I had a very bad habit of not using the using statement. As a result I ran into what many developers do: #region BAD CODE - DO NOT DO try { mObject o = new mObject(); //do stuff } finally { o.Dispose(); // error - o is out of scope, no such object. } // and here is what I find on blogs all over the place as a solution // pox upon them for creating bad habits. mObject o = new mObject(); try { //do stuff } finally { o.Dispose(); } #endregion So when should I use the using statement? Very simple rule, if an object implements IDisposable, use it. This of course does not apply if the object is going to be used as a global object outside of a method. If that is the case, don’t forget to dispose of the object in code somewhere. It should be made clear that using the try{}finally{} code block is not going to break your code, nor cause memory leaks. It is perfectly acceptable coding practice, just not best coding practice in C#. This is how VB.NET developers must code, as there is no using equivalent for them to use.

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Session memory – who’s this guy named Max and what’s he doing with my memory?

- by extended_events

SQL Server MVP Jonathan Kehayias (blog) emailed me a question last week when he noticed that the total memory used by the buffers for an event session was larger than the value he specified for the MAX_MEMORY option in the CREATE EVENT SESSION DDL. The answer here seems like an excellent subject for me to kick-off my new “401 – Internals” tag that identifies posts where I pull back the curtains a bit and let you peek into what’s going on inside the extended events engine. In a previous post (Option Trading: Getting the most out of the event session options) I explained that we use a set of buffers to store the event data before we write the event data to asynchronous targets. The MAX_MEMORY along with the MEMORY_PARTITION_MODE defines how big each buffer will be. Theoretically, that means that I can predict the size of each buffer using the following formula: max memory / # of buffers = buffer size If it was that simple I wouldn’t be writing this post. I’ll take “boundary” for 64K Alex For a number of reasons that are beyond the scope of this blog, we create event buffers in 64K chunks. The result of this is that the buffer size indicated by the formula above is rounded up to the next 64K boundary and that is the size used to create the buffers. If you think visually, this means that the graph of your max_memory option compared to the actual buffer size that results will look like a set of stairs rather than a smooth line. You can see this behavior by looking at the output of dm_xe_sessions, specifically the fields related to the buffer sizes, over a range of different memory inputs: Note: This test was run on a 2 core machine using per_cpu partitioning which results in 5 buffers. (Seem my previous post referenced above for the math behind buffer count.) input_memory_kb total_regular_buffers regular_buffer_size total_buffer_size 637 5 130867 654335 638 5 130867 654335 639 5 130867 654335 640 5 196403 982015 641 5 196403 982015 642 5 196403 982015 This is just a segment of the results that shows one of the “jumps” between the buffer boundary at 639 KB and 640 KB. You can verify the size boundary by doing the math on the regular_buffer_size field, which is returned in bytes: 196403 – 130867 = 65536 bytes 65536 / 1024 = 64 KB The relationship between the input for max_memory and when the regular_buffer_size is going to jump from one 64K boundary to the next is going to change based on the number of buffers being created. The number of buffers is dependent on the partition mode you choose. If you choose any partition mode other than NONE, the number of buffers will depend on your hardware configuration. (Again, see the earlier post referenced above.) With the default partition mode of none, you always get three buffers, regardless of machine configuration, so I generated a “range table” for max_memory settings between 1 KB and 4096 KB as an example. start_memory_range_kb end_memory_range_kb total_regular_buffers regular_buffer_size total_buffer_size 1 191 NULL NULL NULL 192 383 3 130867 392601 384 575 3 196403 589209 576 767 3 261939 785817 768 959 3 327475 982425 960 1151 3 393011 1179033 1152 1343 3 458547 1375641 1344 1535 3 524083 1572249 1536 1727 3 589619 1768857 1728 1919 3 655155 1965465 1920 2111 3 720691 2162073 2112 2303 3 786227 2358681 2304 2495 3 851763 2555289 2496 2687 3 917299 2751897 2688 2879 3 982835 2948505 2880 3071 3 1048371 3145113 3072 3263 3 1113907 3341721 3264 3455 3 1179443 3538329 3456 3647 3 1244979 3734937 3648 3839 3 1310515 3931545 3840 4031 3 1376051 4128153 4032 4096 3 1441587 4324761 As you can see, there are 21 “steps” within this range and max_memory values below 192 KB fall below the 64K per buffer limit so they generate an error when you attempt to specify them. Max approximates True as memory approaches 64K The upshot of this is that the max_memory option does not imply a contract for the maximum memory that will be used for the session buffers (Those of you who read Take it to the Max (and beyond) know that max_memory is really only referring to the event session buffer memory.) but is more of an estimate of total buffer size to the nearest higher multiple of 64K times the number of buffers you have. The maximum delta between your initial max_memory setting and the true total buffer size occurs right after you break through a 64K boundary, for example if you set max_memory = 576 KB (see the green line in the table), your actual buffer size will be closer to 767 KB in a non-partitioned event session. You get “stepped up” for every 191 KB block of initial max_memory which isn’t likely to cause a problem for most machines. Things get more interesting when you consider a partitioned event session on a computer that has a large number of logical CPUs or NUMA nodes. Since each buffer gets “stepped up” when you break a boundary, the delta can get much larger because it’s multiplied by the number of buffers. For example, a machine with 64 logical CPUs will have 160 buffers using per_cpu partitioning or if you have 8 NUMA nodes configured on that machine you would have 24 buffers when using per_node. If you’ve just broken through a 64K boundary and get “stepped up” to the next buffer size you’ll end up with total buffer size approximately 10240 KB and 1536 KB respectively (64K * # of buffers) larger than max_memory value you might think you’re getting. Using per_cpu partitioning on large machine has the most impact because of the large number of buffers created. If the amount of memory being used by your system within these ranges is important to you then this is something worth paying attention to and considering when you configure your event sessions. The DMV dm_xe_sessions is the tool to use to identify the exact buffer size for your sessions. In addition to the regular buffers (read: event session buffers) you’ll also see the details for large buffers if you have configured MAX_EVENT_SIZE. The “buffer steps” for any given hardware configuration should be static within each partition mode so if you want to have a handy reference available when you configure your event sessions you can use the following code to generate a range table similar to the one above that is applicable for your specific machine and chosen partition mode. DECLARE @buf_size_output table (input_memory_kb bigint, total_regular_buffers bigint, regular_buffer_size bigint, total_buffer_size bigint) DECLARE @buf_size int, @part_mode varchar(8) SET @buf_size = 1 -- Set to the begining of your max_memory range (KB) SET @part_mode = 'per_cpu' -- Set to the partition mode for the table you want to generate WHILE @buf_size <= 4096 -- Set to the end of your max_memory range (KB) BEGIN BEGIN TRY IF EXISTS (SELECT * from sys.server_event_sessions WHERE name = 'buffer_size_test') DROP EVENT SESSION buffer_size_test ON SERVER DECLARE @session nvarchar(max) SET @session = 'create event session buffer_size_test on server add event sql_statement_completed add target ring_buffer with (max_memory = ' + CAST(@buf_size as nvarchar(4)) + ' KB, memory_partition_mode = ' + @part_mode + ')' EXEC sp_executesql @session SET @session = 'alter event session buffer_size_test on server state = start' EXEC sp_executesql @session INSERT @buf_size_output (input_memory_kb, total_regular_buffers, regular_buffer_size, total_buffer_size) SELECT @buf_size, total_regular_buffers, regular_buffer_size, total_buffer_size FROM sys.dm_xe_sessions WHERE name = 'buffer_size_test' END TRY BEGIN CATCH INSERT @buf_size_output (input_memory_kb) SELECT @buf_size END CATCH SET @buf_size = @buf_size + 1 END DROP EVENT SESSION buffer_size_test ON SERVER SELECT MIN(input_memory_kb) start_memory_range_kb, MAX(input_memory_kb) end_memory_range_kb, total_regular_buffers, regular_buffer_size, total_buffer_size from @buf_size_output group by total_regular_buffers, regular_buffer_size, total_buffer_size Thanks to Jonathan for an interesting question and a chance to explore some of the details of Extended Event internals. - Mike

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It’s time that you ought to know what you don’t know

- by fatherjack

There is a famous quote about unknown unknowns and known knowns and so on but I’ll let you review that if you are interested. What I am worried about is that there are things going on in your environment that you ought to know about, indeed you have asked to be told about but you are not getting the information. When you schedule a SQL Agent job you can set it to send an email to an inbox monitored by someone who needs to know and indeed can do something about it. However, what happens if the email process isnt successful? Check your servers with this: USE [msdb] GO /* This code selects the top 10 most recent SQLAgent jobs that failed to complete successfully and where the email notification failed too. Jonathan Allen Jul 2012 */ DECLARE @Date DATETIME SELECT @Date = DATEADD(d, DATEDIFF(d, '19000101', GETDATE()) - 1, '19000101') SELECT TOP 10 [s].[name] , [sjh].[step_name] , [sjh].[sql_message_id] , [sjh].[sql_severity] , [sjh].[message] , [sjh].[run_date] , [sjh].[run_time] , [sjh].[run_duration] , [sjh].[operator_id_emailed] , [sjh].[operator_id_netsent] , [sjh].[operator_id_paged] , [sjh].[retries_attempted] FROM [dbo].[sysjobhistory] AS sjh INNER JOIN [dbo].[sysjobs] AS s ON [sjh].[job_id] = [s].[job_id] WHERE EXISTS ( SELECT * FROM [dbo].[sysjobs] AS s INNER JOIN [dbo].[sysjobhistory] AS s2 ON [s].[job_id] = [s2].[job_id] WHERE [sjh].[job_id] = [s2].[job_id] AND [s2].[message] LIKE '%failed to notify%' AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) >= @date AND [s2].[run_status] = 0 ) AND sjh.[run_status] = 0 AND sjh.[step_id] != 0 AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [run_date])) >= @date ORDER BY [sjh].[run_date] DESC , [sjh].[run_time] DESC go USE [msdb] go /* This code summarises details of SQLAgent jobs that failed to complete successfully and where the email notification failed too. Jonathan Allen Jul 2012 */ DECLARE @Date DATETIME SELECT @Date = DATEADD(d, DATEDIFF(d, '19000101', GETDATE()) - 1, '19000101') SELECT [s].name , [s2].[step_id] , CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) AS [rundate] , COUNT(*) AS [execution count] FROM [dbo].[sysjobs] AS s INNER JOIN [dbo].[sysjobhistory] AS s2 ON [s].[job_id] = [s2].[job_id] WHERE [s2].[message] LIKE '%failed to notify%' AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) >= @date AND [s2].[run_status] = 0 GROUP BY name , [s2].[step_id] , [s2].[run_date] ORDER BY [s2].[run_dateDESC] These two result sets will show if there are any SQL Agent jobs that have run on your servers that failed and failed to successfully email about the failure. I hope it’s of use to you. Disclaimer – Jonathan is a Friend of Red Gate and as such, whenever they are discussed, will have a generally positive disposition towards Red Gate tools. Other tools are often available and you should always try others before you come back and buy the Red Gate ones. All code in this blog is provided “as is” and no guarantee, warranty or accuracy is applicable or inferred, run the code on a test server and be sure to understand it before you run it on a server that means a lot to you or your manager.

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SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

- by Pinal Dave

In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D: S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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Advanced TSQL Tuning: Why Internals Knowledge Matters

- by Paul White

There is much more to query tuning than reducing logical reads and adding covering nonclustered indexes. Query tuning is not complete as soon as the query returns results quickly in the development or test environments. In production, your query will compete for memory, CPU, locks, I/O and other resources on the server. Today’s entry looks at some tuning considerations that are often overlooked, and shows how deep internals knowledge can help you write better TSQL. As always, we’ll need some example data. In fact, we are going to use three tables today, each of which is structured like this: Each table has 50,000 rows made up of an INTEGER id column and a padding column containing 3,999 characters in every row. The only difference between the three tables is in the type of the padding column: the first table uses CHAR(3999), the second uses VARCHAR(MAX), and the third uses the deprecated TEXT type. A script to create a database with the three tables and load the sample data follows: USE master; GO IF DB_ID('SortTest') IS NOT NULL DROP DATABASE SortTest; GO CREATE DATABASE SortTest COLLATE LATIN1_GENERAL_BIN; GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest', SIZE = 3GB, MAXSIZE = 3GB ); GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest_log', SIZE = 256MB, MAXSIZE = 1GB, FILEGROWTH = 128MB ); GO ALTER DATABASE SortTest SET ALLOW_SNAPSHOT_ISOLATION OFF ; ALTER DATABASE SortTest SET AUTO_CLOSE OFF ; ALTER DATABASE SortTest SET AUTO_CREATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_SHRINK OFF ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS_ASYNC ON ; ALTER DATABASE SortTest SET PARAMETERIZATION SIMPLE ; ALTER DATABASE SortTest SET READ_COMMITTED_SNAPSHOT OFF ; ALTER DATABASE SortTest SET MULTI_USER ; ALTER DATABASE SortTest SET RECOVERY SIMPLE ; USE SortTest; GO CREATE TABLE dbo.TestCHAR ( id INTEGER IDENTITY (1,1) NOT NULL, padding CHAR(3999) NOT NULL, CONSTRAINT [PK dbo.TestCHAR (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestMAX ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL, CONSTRAINT [PK dbo.TestMAX (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestTEXT ( id INTEGER IDENTITY (1,1) NOT NULL, padding TEXT NOT NULL, CONSTRAINT [PK dbo.TestTEXT (id)] PRIMARY KEY CLUSTERED (id), ) ; -- ============= -- Load TestCHAR (about 3s) -- ============= INSERT INTO dbo.TestCHAR WITH (TABLOCKX) ( padding ) SELECT padding = REPLICATE(CHAR(65 + (Data.n % 26)), 3999) FROM ( SELECT TOP (50000) n = ROW_NUMBER() OVER (ORDER BY (SELECT 0)) - 1 FROM master.sys.columns C1, master.sys.columns C2, master.sys.columns C3 ORDER BY n ASC ) AS Data ORDER BY Data.n ASC ; -- ============ -- Load TestMAX (about 3s) -- ============ INSERT INTO dbo.TestMAX WITH (TABLOCKX) ( padding ) SELECT CONVERT(VARCHAR(MAX), padding) FROM dbo.TestCHAR ORDER BY id ; -- ============= -- Load TestTEXT (about 5s) -- ============= INSERT INTO dbo.TestTEXT WITH (TABLOCKX) ( padding ) SELECT CONVERT(TEXT, padding) FROM dbo.TestCHAR ORDER BY id ; -- ========== -- Space used -- ========== -- EXECUTE sys.sp_spaceused @objname = 'dbo.TestCHAR'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAX'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestTEXT'; ; CHECKPOINT ; That takes around 15 seconds to run, and shows the space allocated to each table in its output: To illustrate the points I want to make today, the example task we are going to set ourselves is to return a random set of 150 rows from each table. The basic shape of the test query is the same for each of the three test tables: SELECT TOP (150) T.id, T.padding FROM dbo.Test AS T ORDER BY NEWID() OPTION (MAXDOP 1) ; Test 1 – CHAR(3999) Running the template query shown above using the TestCHAR table as the target, we find that the query takes around 5 seconds to return its results. This seems slow, considering that the table only has 50,000 rows. Working on the assumption that generating a GUID for each row is a CPU-intensive operation, we might try enabling parallelism to see if that speeds up the response time. Running the query again (but without the MAXDOP 1 hint) on a machine with eight logical processors, the query now takes 10 seconds to execute – twice as long as when run serially. Rather than attempting further guesses at the cause of the slowness, let’s go back to serial execution and add some monitoring. The script below monitors STATISTICS IO output and the amount of tempdb used by the test query. We will also run a Profiler trace to capture any warnings generated during query execution. DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TC.id, TC.padding FROM dbo.TestCHAR AS TC ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; Let’s take a closer look at the statistics and query plan generated from this: Following the flow of the data from right to left, we see the expected 50,000 rows emerging from the Clustered Index Scan, with a total estimated size of around 191MB. The Compute Scalar adds a column containing a random GUID (generated from the NEWID() function call) for each row. With this extra column in place, the size of the data arriving at the Sort operator is estimated to be 192MB. Sort is a blocking operator – it has to examine all of the rows on its input before it can produce its first row of output (the last row received might sort first). This characteristic means that Sort requires a memory grant – memory allocated for the query’s use by SQL Server just before execution starts. In this case, the Sort is the only memory-consuming operator in the plan, so it has access to the full 243MB (248,696KB) of memory reserved by SQL Server for this query execution. Notice that the memory grant is significantly larger than the expected size of the data to be sorted. SQL Server uses a number of techniques to speed up sorting, some of which sacrifice size for comparison speed. Sorts typically require a very large number of comparisons, so this is usually a very effective optimization. One of the drawbacks is that it is not possible to exactly predict the sort space needed, as it depends on the data itself. SQL Server takes an educated guess based on data types, sizes, and the number of rows expected, but the algorithm is not perfect. In spite of the large memory grant, the Profiler trace shows a Sort Warning event (indicating that the sort ran out of memory), and the tempdb usage monitor shows that 195MB of tempdb space was used – all of that for system use. The 195MB represents physical write activity on tempdb, because SQL Server strictly enforces memory grants – a query cannot ‘cheat’ and effectively gain extra memory by spilling to tempdb pages that reside in memory. Anyway, the key point here is that it takes a while to write 195MB to disk, and this is the main reason that the query takes 5 seconds overall. If you are wondering why using parallelism made the problem worse, consider that eight threads of execution result in eight concurrent partial sorts, each receiving one eighth of the memory grant. The eight sorts all spilled to tempdb, resulting in inefficiencies as the spilled sorts competed for disk resources. More importantly, there are specific problems at the point where the eight partial results are combined, but I’ll cover that in a future post. CHAR(3999) Performance Summary: 5 seconds elapsed time 243MB memory grant 195MB tempdb usage 192MB estimated sort set 25,043 logical reads Sort Warning Test 2 – VARCHAR(MAX) We’ll now run exactly the same test (with the additional monitoring) on the table using a VARCHAR(MAX) padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TM.id, TM.padding FROM dbo.TestMAX AS TM ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query takes around 8 seconds to complete (3 seconds longer than Test 1). Notice that the estimated row and data sizes are very slightly larger, and the overall memory grant has also increased very slightly to 245MB. The most marked difference is in the amount of tempdb space used – this query wrote almost 391MB of sort run data to the physical tempdb file. Don’t draw any general conclusions about VARCHAR(MAX) versus CHAR from this – I chose the length of the data specifically to expose this edge case. In most cases, VARCHAR(MAX) performs very similarly to CHAR – I just wanted to make test 2 a bit more exciting. MAX Performance Summary: 8 seconds elapsed time 245MB memory grant 391MB tempdb usage 193MB estimated sort set 25,043 logical reads Sort warning Test 3 – TEXT The same test again, but using the deprecated TEXT data type for the padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TT.id, TT.padding FROM dbo.TestTEXT AS TT ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query runs in 500ms. If you look at the metrics we have been checking so far, it’s not hard to understand why: TEXT Performance Summary: 0.5 seconds elapsed time 9MB memory grant 5MB tempdb usage 5MB estimated sort set 207 logical reads 596 LOB logical reads Sort warning SQL Server’s memory grant algorithm still underestimates the memory needed to perform the sorting operation, but the size of the data to sort is so much smaller (5MB versus 193MB previously) that the spilled sort doesn’t matter very much. Why is the data size so much smaller? The query still produces the correct results – including the large amount of data held in the padding column – so what magic is being performed here? TEXT versus MAX Storage The answer lies in how columns of the TEXT data type are stored. By default, TEXT data is stored off-row in separate LOB pages – which explains why this is the first query we have seen that records LOB logical reads in its STATISTICS IO output. You may recall from my last post that LOB data leaves an in-row pointer to the separate storage structure holding the LOB data. SQL Server can see that the full LOB value is not required by the query plan until results are returned, so instead of passing the full LOB value down the plan from the Clustered Index Scan, it passes the small in-row structure instead. SQL Server estimates that each row coming from the scan will be 79 bytes long – 11 bytes for row overhead, 4 bytes for the integer id column, and 64 bytes for the LOB pointer (in fact the pointer is rather smaller – usually 16 bytes – but the details of that don’t really matter right now). OK, so this query is much more efficient because it is sorting a very much smaller data set – SQL Server delays retrieving the LOB data itself until after the Sort starts producing its 150 rows. The question that normally arises at this point is: Why doesn’t SQL Server use the same trick when the padding column is defined as VARCHAR(MAX)? The answer is connected with the fact that if the actual size of the VARCHAR(MAX) data is 8000 bytes or less, it is usually stored in-row in exactly the same way as for a VARCHAR(8000) column – MAX data only moves off-row into LOB storage when it exceeds 8000 bytes. The default behaviour of the TEXT type is to be stored off-row by default, unless the ‘text in row’ table option is set suitably and there is room on the page. There is an analogous (but opposite) setting to control the storage of MAX data – the ‘large value types out of row’ table option. By enabling this option for a table, MAX data will be stored off-row (in a LOB structure) instead of in-row. SQL Server Books Online has good coverage of both options in the topic In Row Data. The MAXOOR Table The essential difference, then, is that MAX defaults to in-row storage, and TEXT defaults to off-row (LOB) storage. You might be thinking that we could get the same benefits seen for the TEXT data type by storing the VARCHAR(MAX) values off row – so let’s look at that option now. This script creates a fourth table, with the VARCHAR(MAX) data stored off-row in LOB pages: CREATE TABLE dbo.TestMAXOOR ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL, CONSTRAINT [PK dbo.TestMAXOOR (id)] PRIMARY KEY CLUSTERED (id), ) ; EXECUTE sys.sp_tableoption @TableNamePattern = N'dbo.TestMAXOOR', @OptionName = 'large value types out of row', @OptionValue = 'true' ; SELECT large_value_types_out_of_row FROM sys.tables WHERE [schema_id] = SCHEMA_ID(N'dbo') AND name = N'TestMAXOOR' ; INSERT INTO dbo.TestMAXOOR WITH (TABLOCKX) ( padding ) SELECT SPACE(0) FROM dbo.TestCHAR ORDER BY id ; UPDATE TM WITH (TABLOCK) SET padding.WRITE (TC.padding, NULL, NULL) FROM dbo.TestMAXOOR AS TM JOIN dbo.TestCHAR AS TC ON TC.id = TM.id ; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAXOOR' ; CHECKPOINT ; Test 4 – MAXOOR We can now re-run our test on the MAXOOR (MAX out of row) table: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) MO.id, MO.padding FROM dbo.TestMAXOOR AS MO ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; TEXT Performance Summary: 0.3 seconds elapsed time 245MB memory grant 0MB tempdb usage 193MB estimated sort set 207 logical reads 446 LOB logical reads No sort warning The query runs very quickly – slightly faster than Test 3, and without spilling the sort to tempdb (there is no sort warning in the trace, and the monitoring query shows zero tempdb usage by this query). SQL Server is passing the in-row pointer structure down the plan and only looking up the LOB value on the output side of the sort. The Hidden Problem There is still a huge problem with this query though – it requires a 245MB memory grant. No wonder the sort doesn’t spill to tempdb now – 245MB is about 20 times more memory than this query actually requires to sort 50,000 records containing LOB data pointers. Notice that the estimated row and data sizes in the plan are the same as in test 2 (where the MAX data was stored in-row). The optimizer assumes that MAX data is stored in-row, regardless of the sp_tableoption setting ‘large value types out of row’. Why? Because this option is dynamic – changing it does not immediately force all MAX data in the table in-row or off-row, only when data is added or actually changed. SQL Server does not keep statistics to show how much MAX or TEXT data is currently in-row, and how much is stored in LOB pages. This is an annoying limitation, and one which I hope will be addressed in a future version of the product. So why should we worry about this? Excessive memory grants reduce concurrency and may result in queries waiting on the RESOURCE_SEMAPHORE wait type while they wait for memory they do not need. 245MB is an awful lot of memory, especially on 32-bit versions where memory grants cannot use AWE-mapped memory. Even on a 64-bit server with plenty of memory, do you really want a single query to consume 0.25GB of memory unnecessarily? That’s 32,000 8KB pages that might be put to much better use. The Solution The answer is not to use the TEXT data type for the padding column. That solution happens to have better performance characteristics for this specific query, but it still results in a spilled sort, and it is hard to recommend the use of a data type which is scheduled for removal. I hope it is clear to you that the fundamental problem here is that SQL Server sorts the whole set arriving at a Sort operator. Clearly, it is not efficient to sort the whole table in memory just to return 150 rows in a random order. The TEXT example was more efficient because it dramatically reduced the size of the set that needed to be sorted. We can do the same thing by selecting 150 unique keys from the table at random (sorting by NEWID() for example) and only then retrieving the large padding column values for just the 150 rows we need. The following script implements that idea for all four tables: SET STATISTICS IO ON ; WITH TestTable AS ( SELECT * FROM dbo.TestCHAR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id = ANY (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAX ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestTEXT ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAXOOR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; All four queries now return results in much less than a second, with memory grants between 6 and 12MB, and without spilling to tempdb. The small remaining inefficiency is in reading the id column values from the clustered primary key index. As a clustered index, it contains all the in-row data at its leaf. The CHAR and VARCHAR(MAX) tables store the padding column in-row, so id values are separated by a 3999-character column, plus row overhead. The TEXT and MAXOOR tables store the padding values off-row, so id values in the clustered index leaf are separated by the much-smaller off-row pointer structure. This difference is reflected in the number of logical page reads performed by the four queries: Table 'TestCHAR' logical reads 25511 lob logical reads 000 Table 'TestMAX'. logical reads 25511 lob logical reads 000 Table 'TestTEXT' logical reads 00412 lob logical reads 597 Table 'TestMAXOOR' logical reads 00413 lob logical reads 446 We can increase the density of the id values by creating a separate nonclustered index on the id column only. This is the same key as the clustered index, of course, but the nonclustered index will not include the rest of the in-row column data. CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestCHAR (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAX (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestTEXT (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAXOOR (id); The four queries can now use the very dense nonclustered index to quickly scan the id values, sort them by NEWID(), select the 150 ids we want, and then look up the padding data. The logical reads with the new indexes in place are: Table 'TestCHAR' logical reads 835 lob logical reads 0 Table 'TestMAX' logical reads 835 lob logical reads 0 Table 'TestTEXT' logical reads 686 lob logical reads 597 Table 'TestMAXOOR' logical reads 686 lob logical reads 448 With the new index, all four queries use the same query plan (click to enlarge): Performance Summary: 0.3 seconds elapsed time 6MB memory grant 0MB tempdb usage 1MB sort set 835 logical reads (CHAR, MAX) 686 logical reads (TEXT, MAXOOR) 597 LOB logical reads (TEXT) 448 LOB logical reads (MAXOOR) No sort warning I’ll leave it as an exercise for the reader to work out why trying to eliminate the Key Lookup by adding the padding column to the new nonclustered indexes would be a daft idea Conclusion This post is not about tuning queries that access columns containing big strings. It isn’t about the internal differences between TEXT and MAX data types either. It isn’t even about the cool use of UPDATE .WRITE used in the MAXOOR table load. No, this post is about something else: Many developers might not have tuned our starting example query at all – 5 seconds isn’t that bad, and the original query plan looks reasonable at first glance. Perhaps the NEWID() function would have been blamed for ‘just being slow’ – who knows. 5 seconds isn’t awful – unless your users expect sub-second responses – but using 250MB of memory and writing 200MB to tempdb certainly is! If ten sessions ran that query at the same time in production that’s 2.5GB of memory usage and 2GB hitting tempdb. Of course, not all queries can be rewritten to avoid large memory grants and sort spills using the key-lookup technique in this post, but that’s not the point either. The point of this post is that a basic understanding of execution plans is not enough. Tuning for logical reads and adding covering indexes is not enough. If you want to produce high-quality, scalable TSQL that won’t get you paged as soon as it hits production, you need a deep understanding of execution plans, and as much accurate, deep knowledge about SQL Server as you can lay your hands on. The advanced database developer has a wide range of tools to use in writing queries that perform well in a range of circumstances. By the way, the examples in this post were written for SQL Server 2008. They will run on 2005 and demonstrate the same principles, but you won’t get the same figures I did because 2005 had a rather nasty bug in the Top N Sort operator. Fair warning: if you do decide to run the scripts on a 2005 instance (particularly the parallel query) do it before you head out for lunch… This post is dedicated to the people of Christchurch, New Zealand. © 2011 Paul White email: @[email protected] twitter: @SQL_Kiwi

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SQL Server Split() Function

- by HighAltitudeCoder

Title goes here Ever wanted a dbo.Split() function, but not had the time to debug it completely? Let me guess - you are probably working on a stored procedure with 50 or more parameters; two or three of them are parameters of differing types, while the other 47 or so all of the same type (id1, id2, id3, id4, id5...). Worse, you've found several other similar stored procedures with the ONLY DIFFERENCE being the number of like parameters taped to the end of the parameter list. If this is the situation you find yourself in now, you may be wondering, "why am I working with three different copies of what is basically the same stored procedure, and why am I having to maintain changes in three different places? Can't I have one stored procedure that accomplishes the job of all three? My answer to you: YES! Here is the Split() function I've created. /****************************************************************************** Split.sql ******************************************************************************/ /****************************************************************************** Split a delimited string into sub-components and return them as a table. Parameter 1: Input string which is to be split into parts. Parameter 2: Delimiter which determines the split points in input string. Works with space or spaces as delimiter. Split() is apostrophe-safe. SYNTAX: SELECT * FROM Split('Dvorak,Debussy,Chopin,Holst', ',') SELECT * FROM Split('Denver|Seattle|San Diego|New York', '|') SELECT * FROM Split('Denver is the super-awesomest city of them all.', ' ') ******************************************************************************/ USE AdventureWorks GO IF EXISTS (SELECT * FROM sysobjects WHERE xtype = 'TF' AND name = 'Split' ) BEGIN DROP FUNCTION Split END GO CREATE FUNCTION Split ( @InputString VARCHAR(8000), @Delimiter VARCHAR(50) ) RETURNS @Items TABLE ( Item VARCHAR(8000) ) AS BEGIN IF @Delimiter = ' ' BEGIN SET @Delimiter = ',' SET @InputString = REPLACE(@InputString, ' ', @Delimiter) END IF (@Delimiter IS NULL OR @Delimiter = '') SET @Delimiter = ',' --INSERT INTO @Items VALUES (@Delimiter) -- Diagnostic --INSERT INTO @Items VALUES (@InputString) -- Diagnostic DECLARE @Item VARCHAR(8000) DECLARE @ItemList VARCHAR(8000) DECLARE @DelimIndex INT SET @ItemList = @InputString SET @DelimIndex = CHARINDEX(@Delimiter, @ItemList, 0) WHILE (@DelimIndex != 0) BEGIN SET @Item = SUBSTRING(@ItemList, 0, @DelimIndex) INSERT INTO @Items VALUES (@Item) -- Set @ItemList = @ItemList minus one less item SET @ItemList = SUBSTRING(@ItemList, @DelimIndex+1, LEN(@ItemList)-@DelimIndex) SET @DelimIndex = CHARINDEX(@Delimiter, @ItemList, 0) END -- End WHILE IF @Item IS NOT NULL -- At least one delimiter was encountered in @InputString BEGIN SET @Item = @ItemList INSERT INTO @Items VALUES (@Item) END -- No delimiters were encountered in @InputString, so just return @InputString ELSE INSERT INTO @Items VALUES (@InputString) RETURN END -- End Function GO ---- Set Permissions --GRANT SELECT ON Split TO UserRole1 --GRANT SELECT ON Split TO UserRole2 --GO The syntax is basically as follows: SELECT <fields> FROM Table 1 JOIN Table 2 ON ... JOIN Table 3 ON ... WHERE LOGICAL CONDITION A AND LOGICAL CONDITION B AND LOGICAL CONDITION C AND TABLE2.Id IN (SELECT * FROM Split(@IdList, ',')) @IdList is a parameter passed into the stored procedure, and the comma (',') is the delimiter you have chosen to split the parameter list on. You can also use it like this: SELECT <fields> FROM Table 1 JOIN Table 2 ON ... JOIN Table 3 ON ... WHERE LOGICAL CONDITION A AND LOGICAL CONDITION B AND LOGICAL CONDITION C HAVING COUNT(SELECT * FROM Split(@IdList, ',') Similarly, it can be used in other aggregate functions at run-time: SELECT MIN(SELECT * FROM Split(@IdList, ','), <fields> FROM Table 1 JOIN Table 2 ON ... JOIN Table 3 ON ... WHERE LOGICAL CONDITION A AND LOGICAL CONDITION B AND LOGICAL CONDITION C GROUP BY <fields> Now that I've (hopefully effectively) explained the benefits to using this function and implementing it in one or more of your database objects, let me warn you of a caveat that you are likely to encounter. You may have a team member who waits until the right moment to ask you a pointed question: "Doesn't this function just do the same thing as using the IN function? Why didn't you just use that instead? In other words, why bother with this function?" What's happening is, one or more team members has failed to understand the reason for implementing this kind of function in the first place. (Note: this is THE MOST IMPORTANT ASPECT OF THIS POST). Allow me to outline a few pros to implementing this function, so you may effectively parry this question. Touche. 1) Code consolidation. You don't have to maintain what is basically the same code and logic, but with varying numbers of the same parameter in several SQL objects. I'm not going to go into the cons related to using this function, because the afore mentioned team member is probably more than adept at pointing these out. Remember, the real positive contribution is ou are decreasing the liklihood that your team fails to update all (x) duplicate copies of what are basically the same stored procedure, and so on... This is the classic downside to duplicate code. It is a virus, and you should kill it. You might be better off rejecting your team member's question, and responding with your own: "Would you rather maintain the same logic in multiple different stored procedures, and hope that the team doesn't forget to always update all of them at the same time?". In his head, he might be thinking "yes, I would like to maintain several different copies of the same stored procedure", although you probably will not get such a direct response. 2) Added flexibility - you can use the Split function elsewhere, and for splitting your data in different ways. Plus, you can use any kind of delimiter you wish. How can you know today the ways in which you might want to examine your data tomorrow? Segue to my next point. 3) Because the function takes a delimiter parameter, you can split the data in any number of ways. This greatly increases the utility of such a function and enables your team to work with the data in a variety of different ways in the future. You can split on a single char, symbol, word, or group of words. You can split on spaces. (The list goes on... test it out). Finally, you can dynamically define the behavior of a stored procedure (or other SQL object) at run time, through the use of this function. Rather than have several objects that accomplish almost the same thing, why not have only one instead?

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SQL SERVER – Various Leap Year Logics

- by pinaldave

Earlier I wrote one article on Leap Year and created one video about Leap Year. My point of view was to demonstrate how we can use SQL Server 2012 features to identify Leap year. How ever during the conversation I had some really good conversation. Here are updates for those who have missed reading the excellent comments on the blog. Incorrect Logic There are so many people still think Leap Year is the event which is consistently happening at every four year and the way to find it is divide the year with 4 and if the remainder is 0. That year is leap year. Well, it is not correct. Comment by David Bridge Check out this excerpt from wikipedia page http://en.wikipedia.org/wiki/Leap_year “most years that are evenly divisible by 4 are leap years…” “…Some exceptions to this rule are required since the duration of a solar year is slightly less than 365.25 days. Years that are evenly divisible by 100 are not leap years, unless they are also evenly divisible by 400, in which case they are leap years. For example, 1600 and 2000 were leap years, but 1700, 1800 and 1900 were not. Similarly, 2100, 2200, 2300, 2500, 2600, 2700, 2900 and 3000 will not be leap years, but 2400 and 2800 will be.” If you use logic of divide by 4 and remainder is 0 to find leap year, you will may end up with inaccurate result. The correct way to identify the year is to figure out the days of February and if the count is 29, the year is for sure leap year. Valid Alternate Solutions Comment by sainswor99insworth IIF((@Year%4=0 AND @Year%100 != 0) OR @Year%400=0, 1,0) Comment by Madhivanan Madhivanan has written a blog post about an year ago where he listed multiple ways to find leap year. Comment by Jayan DECLARE @year INT SET @year = 2012 IF (((@year % 4 = 0) AND (@year % 100 != 0)) OR (@year % 400 = 0)) PRINT ’1' ELSE print ’0' Comment by David DECLARE @Year INT = 2012 SELECT ISDATE('2/29/' + CAST(@Year AS CHAR(4))) Comment by David Bridge Incidentally – Another approach would be to take one day off March 1st and see if it is 29. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL DateTime, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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« SteamOS va aider Linux sur les ordinateurs de bureau » pour Linus Torvalds, qui n'est pas inquiet par la gratuité d'OS X

« SteamOS va aider Linux sur les ordinateurs de bureau» pour Linus Torvalds, qui n'est pas inquiet par la gratuité d'OS X Linus Torvalds, père du noyau Linux, loue l'initiative de Valve avec son système d'exploitation SteamOS.S'exprimant lors de l'événement LinuxCon qui s'est tenu à Edinburgh, Torvalds a déclaré qu'il « aime les annonces Steam » et qu'il « pense que c'est une occasion qui pourrait aider [Linux] sur les ordinateurs de bureau ».Le père de Linux s'aligne ainsi avec la vision de...

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Passing text message to web page from web user control

- by Narendra Tiwari

Here is a brief summary how we can send a text message to webpage by a web user control. Delegates is the slolution. There are many good articles on .net delegates you can refer some of them below. The scenario is we want to send a text message to the page on completion of some activity on webcontrol. 1/ Create a Base class for webcontrol (refer code below), assuming we are passing some text messages to page from web user control - Declare a delegate - Declare an event of type delegate using System; using System.Data; using System.Configuration; using System.Web; using System.Web.Security; using System.Web.UI; using System.Web.UI.WebControls; using System.Web.UI.WebControls.WebParts; using System.Web.UI.HtmlControls; //Declaring delegate with message parameter public delegate void SendMessageToThePageHandler(string messageToThePage); public } class ControlBase: System.Web.UI.UserControl { public ControlBase() { // TODO: Add constructor logic here }protected override void OnInit(EventArgs e) { base.OnInit(e); }private string strMessageToPass;/// <summary> /// MessageToPass - Property to pass text message to page /// </summary> public string MessageToPass { get { return strMessageToPass; } set { strMessageToPass = value; } }/// <summary> /// SendMessageToPage - Called from control to invoke the event /// </summary> /// <param name="strMessage">Message to pass</param> public void SendMessageToPage(string strMessage) { if (this.sendMessageToThePage != null) this.sendMessageToThePage(strMessage); } 2/ Register events on webpage on page Load eventthis.AddControlEventHandler((ControlBase)WebUserControl1); this.AddControlEventHandler((ControlBase)WebUserControl2); /// <summary> /// AddControlEventHandler- Hooking web user control event /// </summary> /// <param name="ctrl"></param> private void AddControlEventHandler(ControlBase ctrl) { ctrl.sendMessageToThePage += delegate(string strMessage) { //display message lblMessage.Text = strMessage; }; } References: http://www.akadia.com/services/dotnet_delegates_and_events.html 3/

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Using the ASP.NET Cache to cache data in a Model or Business Object layer, without a dependency on System.Web in the layer - Part One.

- by Rhames

ASP.NET applications can make use of the System.Web.Caching.Cache object to cache data and prevent repeated expensive calls to a database or other store. However, ideally an application should make use of caching at the point where data is retrieved from the database, which typically is inside a Business Objects or Model layer. One of the key features of using a UI pattern such as Model-View-Presenter (MVP) or Model-View-Controller (MVC) is that the Model and Presenter (or Controller) layers are developed without any knowledge of the UI layer. Introducing a dependency on System.Web into the Model layer would break this independence of the Model from the View. This article gives a solution to this problem, using dependency injection to inject the caching implementation into the Model layer at runtime. This allows caching to be used within the Model layer, without any knowledge of the actual caching mechanism that will be used. Create a sample application to use the caching solution Create a test SQL Server database This solution uses a SQL Server database with the same Sales data used in my previous post on calculating running totals. The advantage of using this data is that it gives nice slow queries that will exaggerate the effect of using caching! To create the data, first create a new SQL database called CacheSample. Next run the following script to create the Sale table and populate it: USE CacheSample GO CREATE TABLE Sale(DayCount smallint, Sales money) CREATE CLUSTERED INDEX ndx_DayCount ON Sale(DayCount) go INSERT Sale VALUES (1,120) INSERT Sale VALUES (2,60) INSERT Sale VALUES (3,125) INSERT Sale VALUES (4,40) DECLARE @DayCount smallint, @Sales money SET @DayCount = 5 SET @Sales = 10 WHILE @DayCount < 5000 BEGIN INSERT Sale VALUES (@DayCount,@Sales) SET @DayCount = @DayCount + 1 SET @Sales = @Sales + 15 END Next create a stored procedure to calculate the running total, and return a specified number of rows from the Sale table, using the following script: USE [CacheSample] GO SET ANSI_NULLS ON GO SET QUOTED_IDENTIFIER ON GO -- ============================================= -- Author: Robin -- Create date: -- Description: -- ============================================= CREATE PROCEDURE [dbo].[spGetRunningTotals] -- Add the parameters for the stored procedure here @HighestDayCount smallint = null AS BEGIN -- SET NOCOUNT ON added to prevent extra result sets from -- interfering with SELECT statements. SET NOCOUNT ON; IF @HighestDayCount IS NULL SELECT @HighestDayCount = MAX(DayCount) FROM dbo.Sale DECLARE @SaleTbl TABLE (DayCount smallint, Sales money, RunningTotal money) DECLARE @DayCount smallint, @Sales money, @RunningTotal money SET @RunningTotal = 0 SET @DayCount = 0 DECLARE rt_cursor CURSOR FOR SELECT DayCount, Sales FROM Sale ORDER BY DayCount OPEN rt_cursor FETCH NEXT FROM rt_cursor INTO @DayCount,@Sales WHILE @@FETCH_STATUS = 0 AND @DayCount <= @HighestDayCount BEGIN SET @RunningTotal = @RunningTotal + @Sales INSERT @SaleTbl VALUES (@DayCount,@Sales,@RunningTotal) FETCH NEXT FROM rt_cursor INTO @DayCount,@Sales END CLOSE rt_cursor DEALLOCATE rt_cursor SELECT DayCount, Sales, RunningTotal FROM @SaleTbl END GO Create the Sample ASP.NET application In Visual Studio create a new solution and add a class library project called CacheSample.BusinessObjects and an ASP.NET web application called CacheSample.UI. The CacheSample.BusinessObjects project will contain a single class to represent a Sale data item, with all the code to retrieve the sales from the database included in it for simplicity (normally I would at least have a separate Repository or other object that is responsible for retrieving data, and probably a data access layer as well, but for this sample I want to keep it simple). The C# code for the Sale class is shown below: using System; using System.Collections.Generic; using System.Data; using System.Data.SqlClient; namespace CacheSample.BusinessObjects { public class Sale { public Int16 DayCount { get; set; } public decimal Sales { get; set; } public decimal RunningTotal { get; set; } public static IEnumerable<Sale> GetSales(int? highestDayCount) { List<Sale> sales = new List<Sale>(); SqlParameter highestDayCountParameter = new SqlParameter("@HighestDayCount", SqlDbType.SmallInt); if (highestDayCount.HasValue) highestDayCountParameter.Value = highestDayCount; else highestDayCountParameter.Value = DBNull.Value; string connectionStr = System.Configuration.ConfigurationManager .ConnectionStrings["CacheSample"].ConnectionString; using(SqlConnection sqlConn = new SqlConnection(connectionStr)) using (SqlCommand sqlCmd = sqlConn.CreateCommand()) { sqlCmd.CommandText = "spGetRunningTotals"; sqlCmd.CommandType = CommandType.StoredProcedure; sqlCmd.Parameters.Add(highestDayCountParameter); sqlConn.Open(); using (SqlDataReader dr = sqlCmd.ExecuteReader()) { while (dr.Read()) { Sale newSale = new Sale(); newSale.DayCount = dr.GetInt16(0); newSale.Sales = dr.GetDecimal(1); newSale.RunningTotal = dr.GetDecimal(2); sales.Add(newSale); } } } return sales; } } } The static GetSale() method makes a call to the spGetRunningTotals stored procedure and then reads each row from the returned SqlDataReader into an instance of the Sale class, it then returns a List of the Sale objects, as IEnnumerable<Sale>. A reference to System.Configuration needs to be added to the CacheSample.BusinessObjects project so that the connection string can be read from the web.config file. In the CacheSample.UI ASP.NET project, create a single web page called ShowSales.aspx, and make this the default start up page. This page will contain a single button to call the GetSales() method and a label to display the results. The html mark up and the C# code behind are shown below: ShowSales.aspx <%@ Page Language="C#" AutoEventWireup="true" CodeBehind="ShowSales.aspx.cs" Inherits="CacheSample.UI.ShowSales" %> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head runat="server"> <title>Cache Sample - Show All Sales</title> </head> <body> <form id="form1" runat="server"> <div> <asp:Button ID="btnTest1" runat="server" onclick="btnTest1_Click" Text="Get All Sales" />     <asp:Label ID="lblResults" runat="server"></asp:Label> </div> </form> </body> </html> ShowSales.aspx.cs using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.Web.UI; using System.Web.UI.WebControls; using CacheSample.BusinessObjects; namespace CacheSample.UI { public partial class ShowSales : System.Web.UI.Page { protected void Page_Load(object sender, EventArgs e) { } protected void btnTest1_Click(object sender, EventArgs e) { System.Diagnostics.Stopwatch stopWatch = new System.Diagnostics.Stopwatch(); stopWatch.Start(); var sales = Sale.GetSales(null); var lastSales = sales.Last(); stopWatch.Stop(); lblResults.Text = string.Format( "Count of Sales: {0}, Last DayCount: {1}, Total Sales: {2}. Query took {3} ms", sales.Count(), lastSales.DayCount, lastSales.RunningTotal, stopWatch.ElapsedMilliseconds); } } } Finally we need to add a connection string to the CacheSample SQL Server database, called CacheSample, to the web.config file: <?xmlversion="1.0"?> <configuration> <connectionStrings> <addname="CacheSample" connectionString="data source=.\SQLEXPRESS;Integrated Security=SSPI;Initial Catalog=CacheSample" providerName="System.Data.SqlClient" /> </connectionStrings> <system.web> <compilationdebug="true"targetFramework="4.0" /> </system.web> </configuration> Run the application and click the button a few times to see how long each call to the database takes. On my system, each query takes about 450ms. Next I shall look at a solution to use the ASP.NET caching to cache the data returned by the query, so that subsequent requests to the GetSales() method are much faster. Adding Data Caching Support I am going to create my caching support in a separate project called CacheSample.Caching, so the next step is to add a class library to the solution. We shall be using the application configuration to define the implementation of our caching system, so we need a reference to System.Configuration adding to the project. ICacheProvider<T> Interface The first step in adding caching to our application is to define an interface, called ICacheProvider, in the CacheSample.Caching project, with methods to retrieve any data from the cache or to retrieve the data from the data source if it is not present in the cache. Dependency Injection will then be used to inject an implementation of this interface at runtime, allowing the users of the interface (i.e. the CacheSample.BusinessObjects project) to be completely unaware of how the caching is actually implemented. As data of any type maybe retrieved from the data source, it makes sense to use generics in the interface, with a generic type parameter defining the data type associated with a particular instance of the cache interface implementation. The C# code for the ICacheProvider interface is shown below: using System; using System.Collections.Generic; namespace CacheSample.Caching { public interface ICacheProvider { } public interface ICacheProvider<T> : ICacheProvider { T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry); IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry); } } The empty non-generic interface will be used as a type in a Dictionary generic collection later to store instances of the ICacheProvider<T> implementation for reuse, I prefer to use a base interface when doing this, as I think the alternative of using object makes for less clear code. The ICacheProvider<T> interface defines two overloaded Fetch methods, the difference between these is that one will return a single instance of the type T and the other will return an IEnumerable<T>, providing support for easy caching of collections of data items. Both methods will take a key parameter, which will uniquely identify the cached data, a delegate of type Func<T> or Func<IEnumerable<T>> which will provide the code to retrieve the data from the store if it is not present in the cache, and absolute or relative expiry policies to define when a cached item should expire. Note that at present there is no support for cache dependencies, but I shall be showing a method of adding this in part two of this article. CacheProviderFactory Class We need a mechanism of creating instances of our ICacheProvider<T> interface, using Dependency Injection to get the implementation of the interface. To do this we shall create a CacheProviderFactory static class in the CacheSample.Caching project. This factory will provide a generic static method called GetCacheProvider<T>(), which shall return instances of ICacheProvider<T>. We can then call this factory method with the relevant data type (for example the Sale class in the CacheSample.BusinessObject project) to get a instance of ICacheProvider for that type (e.g. call CacheProviderFactory.GetCacheProvider<Sale>() to get the ICacheProvider<Sale> implementation). The C# code for the CacheProviderFactory is shown below: using System; using System.Collections.Generic; using CacheSample.Caching.Configuration; namespace CacheSample.Caching { public static class CacheProviderFactory { private static Dictionary<Type, ICacheProvider> cacheProviders = new Dictionary<Type, ICacheProvider>(); private static object syncRoot = new object(); ///<summary> /// Factory method to create or retrieve an implementation of the /// ICacheProvider interface for type <typeparamref name="T"/>. ///</summary> ///<typeparam name="T"> /// The type that this cache provider instance will work with ///</typeparam> ///<returns>An instance of the implementation of ICacheProvider for type ///<typeparamref name="T"/>, as specified by the application /// configuration</returns> public static ICacheProvider<T> GetCacheProvider<T>() { ICacheProvider<T> cacheProvider = null; // Get the Type reference for the type parameter T Type typeOfT = typeof(T); // Lock the access to the cacheProviders dictionary // so multiple threads can work with it lock (syncRoot) { // First check if an instance of the ICacheProvider implementation // already exists in the cacheProviders dictionary for the type T if (cacheProviders.ContainsKey(typeOfT)) cacheProvider = (ICacheProvider<T>)cacheProviders[typeOfT]; else { // There is not already an instance of the ICacheProvider in // cacheProviders for the type T // so we need to create one // Get the Type reference for the application's implementation of // ICacheProvider from the configuration Type cacheProviderType = Type.GetType(CacheProviderConfigurationSection.Current. CacheProviderType); if (cacheProviderType != null) { // Now get a Type reference for the Cache Provider with the // type T generic parameter Type typeOfCacheProviderTypeForT = cacheProviderType.MakeGenericType(new Type[] { typeOfT }); if (typeOfCacheProviderTypeForT != null) { // Create the instance of the Cache Provider and add it to // the cacheProviders dictionary for future use cacheProvider = (ICacheProvider<T>)Activator. CreateInstance(typeOfCacheProviderTypeForT); cacheProviders.Add(typeOfT, cacheProvider); } } } } return cacheProvider; } } } As this code uses Activator.CreateInstance() to create instances of the ICacheProvider<T> implementation, which is a slow process, the factory class maintains a Dictionary of the previously created instances so that a cache provider needs to be created only once for each type. The type of the implementation of ICacheProvider<T> is read from a custom configuration section in the application configuration file, via the CacheProviderConfigurationSection class, which is described below. CacheProviderConfigurationSection Class The implementation of ICacheProvider<T> will be specified in a custom configuration section in the application’s configuration. To handle this create a folder in the CacheSample.Caching project called Configuration, and add a class called CacheProviderConfigurationSection to this folder. This class will extend the System.Configuration.ConfigurationSection class, and will contain a single string property called CacheProviderType. The C# code for this class is shown below: using System; using System.Configuration; namespace CacheSample.Caching.Configuration { internal class CacheProviderConfigurationSection : ConfigurationSection { public static CacheProviderConfigurationSection Current { get { return (CacheProviderConfigurationSection) ConfigurationManager.GetSection("cacheProvider"); } } [ConfigurationProperty("type", IsRequired=true)] public string CacheProviderType { get { return (string)this["type"]; } } } } Adding Data Caching to the Sales Class We now have enough code in place to add caching to the GetSales() method in the CacheSample.BusinessObjects.Sale class, even though we do not yet have an implementation of the ICacheProvider<T> interface. We need to add a reference to the CacheSample.Caching project to CacheSample.BusinessObjects so that we can use the ICacheProvider<T> interface within the GetSales() method. Once the reference is added, we can first create a unique string key based on the method name and the parameter value, so that the same cache key is used for repeated calls to the method with the same parameter values. Then we get an instance of the cache provider for the Sales type, using the CacheProviderFactory, and pass the existing code to retrieve the data from the database as the retrievalMethod delegate in a call to the Cache Provider Fetch() method. The C# code for the modified GetSales() method is shown below: public static IEnumerable<Sale> GetSales(int? highestDayCount) { string cacheKey = string.Format("CacheSample.BusinessObjects.GetSalesWithCache({0})", highestDayCount); return CacheSample.Caching.CacheProviderFactory. GetCacheProvider<Sale>().Fetch(cacheKey, delegate() { List<Sale> sales = new List<Sale>(); SqlParameter highestDayCountParameter = new SqlParameter("@HighestDayCount", SqlDbType.SmallInt); if (highestDayCount.HasValue) highestDayCountParameter.Value = highestDayCount; else highestDayCountParameter.Value = DBNull.Value; string connectionStr = System.Configuration.ConfigurationManager. ConnectionStrings["CacheSample"].ConnectionString; using (SqlConnection sqlConn = new SqlConnection(connectionStr)) using (SqlCommand sqlCmd = sqlConn.CreateCommand()) { sqlCmd.CommandText = "spGetRunningTotals"; sqlCmd.CommandType = CommandType.StoredProcedure; sqlCmd.Parameters.Add(highestDayCountParameter); sqlConn.Open(); using (SqlDataReader dr = sqlCmd.ExecuteReader()) { while (dr.Read()) { Sale newSale = new Sale(); newSale.DayCount = dr.GetInt16(0); newSale.Sales = dr.GetDecimal(1); newSale.RunningTotal = dr.GetDecimal(2); sales.Add(newSale); } } } return sales; }, null, new TimeSpan(0, 10, 0)); } This example passes the code to retrieve the Sales data from the database to the Cache Provider as an anonymous method, however it could also be written as a lambda. The main advantage of using an anonymous function (method or lambda) is that the code inside the anonymous function can access the parameters passed to the GetSales() method. Finally the absolute expiry is set to null, and the relative expiry set to 10 minutes, to indicate that the cache entry should be removed 10 minutes after the last request for the data. As the ICacheProvider<T> has a Fetch() method that returns IEnumerable<T>, we can simply return the results of the Fetch() method to the caller of the GetSales() method. This should be all that is needed for the GetSales() method to now retrieve data from a cache after the first time the data has be retrieved from the database. Implementing a ASP.NET Cache Provider The final step is to actually implement the ICacheProvider<T> interface, and add the implementation details to the web.config file for the dependency injection. The cache provider implementation needs to have access to System.Web. Therefore it could be placed in the CacheSample.UI project, or in its own project that has a reference to System.Web. Implementing the Cache Provider in a separate project is my favoured approach. Create a new project inside the solution called CacheSample.CacheProvider, and add references to System.Web and CacheSample.Caching to this project. Add a class to the project called AspNetCacheProvider. Make the class a generic class by adding the generic parameter <T> and indicate that the class implements ICacheProvider<T>. The C# code for the AspNetCacheProvider class is shown below: using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.Web.Caching; using CacheSample.Caching; namespace CacheSample.CacheProvider { public class AspNetCacheProvider<T> : ICacheProvider<T> { #region ICacheProvider<T> Members public T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) { return FetchAndCache<T>(key, retrieveData, absoluteExpiry, relativeExpiry); } public IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) { return FetchAndCache<IEnumerable<T>>(key, retrieveData, absoluteExpiry, relativeExpiry); } #endregion #region Helper Methods private U FetchAndCache<U>(string key, Func<U> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) { U value; if (!TryGetValue<U>(key, out value)) { value = retrieveData(); if (!absoluteExpiry.HasValue) absoluteExpiry = Cache.NoAbsoluteExpiration; if (!relativeExpiry.HasValue) relativeExpiry = Cache.NoSlidingExpiration; HttpContext.Current.Cache.Insert(key, value, null, absoluteExpiry.Value, relativeExpiry.Value); } return value; } private bool TryGetValue<U>(string key, out U value) { object cachedValue = HttpContext.Current.Cache.Get(key); if (cachedValue == null) { value = default(U); return false; } else { try { value = (U)cachedValue; return true; } catch { value = default(U); return false; } } } #endregion } } The two interface Fetch() methods call a private method called FetchAndCache(). This method first checks for a element in the HttpContext.Current.Cache with the specified cache key, and if so tries to cast this to the specified type (either T or IEnumerable<T>). If the cached element is found, the FetchAndCache() method simply returns it. If it is not found in the cache, the method calls the retrievalMethod delegate to get the data from the data source, and then adds this to the HttpContext.Current.Cache. The final step is to add the AspNetCacheProvider class to the relevant custom configuration section in the CacheSample.UI.Web.Config file. To do this there needs to be a <configSections> element added as the first element in <configuration>. This will match a custom section called <cacheProvider> with the CacheProviderConfigurationSection. Then we add a <cacheProvider> element, with a type property set to the fully qualified assembly name of the AspNetCacheProvider class, as shown below: <?xmlversion="1.0"?> <configuration> <configSections> <sectionname="cacheProvider" type="CacheSample.Base.Configuration.CacheProviderConfigurationSection, CacheSample.Base" /> </configSections> <connectionStrings> <addname="CacheSample" connectionString="data source=.\SQLEXPRESS;Integrated Security=SSPI;Initial Catalog=CacheSample" providerName="System.Data.SqlClient" /> </connectionStrings> <cacheProvidertype="CacheSample.CacheProvider.AspNetCacheProvider`1, CacheSample.CacheProvider, Version=1.0.0.0, Culture=neutral, PublicKeyToken=null"> </cacheProvider> <system.web> <compilationdebug="true"targetFramework="4.0" /> </system.web> </configuration> One point to note is that the fully qualified assembly name of the AspNetCacheProvider class includes the notation `1 after the class name, which indicates that it is a generic class with a single generic type parameter. The CacheSample.UI project needs to have references added to CacheSample.Caching and CacheSample.CacheProvider so that the actual application is aware of the relevant cache provider implementation. Conclusion After implementing this solution, you should have a working cache provider mechanism, that will allow the middle and data access layers to implement caching support when retrieving data, without any knowledge of the actually caching implementation. If the UI is not ASP.NET based, if for example it is Winforms or WPF, the implementation of ICacheProvider<T> would be written around whatever technology is available. It could even be a standalone caching system that takes full responsibility for adding and removing items from a global store. The next part of this article will show how this caching mechanism may be extended to provide support for cache dependencies, such as the System.Web.Caching.SqlCacheDependency. Another possible extension would be to cache the cache provider implementations instead of storing them in a static Dictionary in the CacheProviderFactory. This would prevent a build up of seldom used cache providers in the application memory, as they could be removed from the cache if not used often enough, although in reality there are probably unlikely to be vast numbers of cache provider implementation instances, as most applications do not have a massive number of business object or model types.

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