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  • Create account for service

    - by Andy
    I am configuring a new server. The server is running Hudson that is going to copy some files from this server to another. The other server is a virtual machine. Both running Windows Server 2012. Hudson is started on server A with log on as "Local System". When I come to the copy phase it says "Access denied". Changing the log on to "Administrator" works. However, I guess this is bad. I do not have much experience with user management. I tried to create a own hudson account on both servers A and B. I tried to log on as hudson account in the service-management but it doesn't start. How would you create an account for this particular service that has access to the shared folder on server B and can be used to start the service on server A? I guess I need two accounts with same username and password on server A and server B? The folder on Server B is shared with everyone and the guest account is enabled.

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  • Why the “Toilet” Analogy for SQL might be bad

    - by Jonathan Kehayias
    Robert Davis(blog/twitter) recently blogged The Toilet Analogy … or Why I Never Recommend Increasing Worker Threads , in which he uses an analogy for why increasing the value for the ‘max worker threads’ sp_configure option can be bad inside of SQL Server.  While I can’t make an argument against Robert’s assertion that increasing worker threads may not improve performance, I can make an argument against his suggestion that, simply increasing the number of logical processors, for example from...(read more)

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  • Sep 10 Week - I'll be on the West Coast Speaking in Irvine and San Fran

    - by RickHeiges
    In my role as a Solutions Architect for Scalability Experts, I often get to present to customers about the work that we performed. Unfortunately, this is often on short notice and I can't coordinate a trip to participate in a User Group Meeting. Next week, I was able to coordinate my west coast trip to be able to present. I am heading to Irvine at the MTC on Sepember 11 and San Francisco at the MSFT offices on Sep 13 to speak to customers who want to learn more about SQL Server 2012.To register for...(read more)

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  • Microsoft SQL Server High-Availability Videos and Q&A Log

    - by KKline
    You Want Videos? We Got Videos! I always enjoy getting the chance to catch up with author, consultant, and Microsoft Clustering MVP Allan Hirt . Allan and I recently presented two sessions covering an overview of high availability in Microsoft SQL Server and, the following week, a demo of how to implement several different kinds of high availability techniques including database mirroring, transactional replication, and Windows clustering services. You can see videos of these presentations at the...(read more)

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  • Hugh Bin-Haad's SQL Rumours

    - by Paul Nielsen
    Insider rumours and gossip from the murky world of the Database Industry, and from the colourful characters that inhabit it http://www.simple-talk.com/sql/editors-corner/insider-insights/ Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!...(read more)

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  • Hugh Bin-Haad's SQL Rumours

    - by Paul Nielsen
    Insider rumours and gossip from the murky world of the Database Industry, and from the colourful characters that inhabit it http://www.simple-talk.com/sql/editors-corner/insider-insights/ Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!...(read more)

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  • Good practices - database programming, unit testing

    - by Piotr Rodak
    Jason Brimhal wrote today on his blog that new book, Defensive Database Programming , written by Alex Kuznetsov ( blog ) is coming to bookstores. Alex writes about various techniques that make your code safer to run. SQL injection is not the only one vulnerability the code may be exposed to. Some other include inconsistent search patterns, unsupported character sets, locale settings, issues that may occur during high concurrency conditions, logic that breaks when certain conditions are not met. The...(read more)

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  • Simon Sabin has a great discount for the SQL Server Masterclass

    - by Testas
    Check out Simons blog post to get a discount of £100 for this event http://sqlblogcasts.com/blogs/simons/archive/2010/05/14/paul-and-kimberly-are-coming-the-uk.aspx   Remember as well  Pencil the 17th June in your diary, send an email [email protected] with the title of Masterclass in the subject line. On Friday 25th May we will draw out a name and the winner will have free entrance to a must see seminar on SQL Server from two of the industry’s leading experts. Thanks Chris

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  • Azure, don't give me multiple VMs, give me one elastic VM

    - by FransBouma
    Yesterday, Microsoft revealed new major features for Windows Azure (see ScottGu's post). It all looks shiny and great, but after reading most of the material describing the new features, I still find the overall idea behind all of it flawed: why should I care on how much VMs my web app runs? Isn't that a problem to solve for the Windows Azure engineers / software? And what if I need the file system, why can't I simply get a virtual filesystem ? To illustrate my point, let's use a real example: a product website with a customer system/database and next to it a support site with accompanying database. Both are written in .NET, using ASP.NET and use a SQL Server database each. The product website offers files to download by customers, very simple. You have a couple of options to host these websites: Buy a server, place it in a rack at an ISP and run the sites on that server Use 'shared hosting' with an ISP, which means your sites' appdomains are running on the same machine, as well as the files stored, and the databases are hosted in the same server as the other shared databases. Hire a VM, install your OS of choice at an ISP, and host the sites on that VM, basically the same as the first option, except you don't have a physical server At some cloud-vendor, either host the sites 'shared' or in a VM. See above. With all of those options, scalability is a problem, even the cloud-based ones, though not due to the same reasons: The physical server solution has the obvious problem that if you need more power, you need to buy a bigger server or more servers which requires you to add replication and other overhead Shared hosting solutions are almost always capped on memory usage / traffic and database size: if your sites get too big, you have to move out of the shared hosting environment and start over with one of the other solutions The VM solution, be it a VM at an ISP or 'in the cloud' at e.g. Windows Azure or Amazon, in theory allows scaling out by simply instantiating more VMs, however that too introduces the same overhead problems as with the physical servers: suddenly more than 1 instance runs your sites. If a cloud vendor offers its services in the form of VMs, you won't gain much over having a VM at some ISP: the main problems you have to work around are still there: when you spin up more than one VM, your application must be completely stateless at any moment, including the DB sub system, because what's in memory in instance 1 might not be in memory in instance 2. This might sounds trivial but it's not. A lot of the websites out there started rather small: they were perfectly runnable on a single machine with normal memory and CPU power. After all, you don't need a big machine to run a website with even thousands of users a day. Moving these sites to a multi-VM environment will cause a problem: all the in-memory state they use, all the multi-page transitions they use while keeping state across the transition, they can't do that anymore like they did that on a single machine: state is something of the past, you have to store every byte of state in either a DB or in a viewstate or in a cookie somewhere so with the next request, all state information is available through the request, as nothing is kept in-memory. Our example uses a bunch of files in a file system. Using multiple VMs will require that these files move to a cloud storage system which is mounted in each VM so we don't have to store the files on each VM. This might require different file paths, but this change should be minor. What's perhaps less minor is the maintenance procedure in place on the new type of cloud storage used: instead of ftp-ing into a VM, you might have to update the files using different ways / tools. All in all this makes moving an existing website which was written for an environment that's based around a VM (namely .NET with its CLR) overly cumbersome and problematic: it forces you to refactor your website system to be able to be used 'in the cloud', which is caused by the limited way how e.g. Windows Azure offers its cloud services: in blocks of VMs. Offer a scalable, flexible VM which extends with my needs Instead, cloud vendors should offer simply one VM to me. On that VM I run the websites, store my DB and my files. As it's a virtual machine, how this machine is actually ran on physical hardware (e.g. partitioned), I don't care, as that's the problem for the cloud vendor to solve. If I need more resources, e.g. I have more traffic to my server, way more visitors per day, the VM stretches, like I bought a bigger box. This frees me from the problem which comes with multiple VMs: I don't have any refactoring to do at all: I can simply build my website as if it runs on my local hardware server, upload it to the VM offered by the cloud vendor, install it on the VM and I'm done. "But that might require changes to windows!" Yes, but Microsoft is Windows. Windows Azure is their service, they can make whatever change to what they offer to make it look like it's windows. Yet, they're stuck, like Amazon, in thinking in VMs, which forces developers to 'think ahead' and gamble whether they would need to migrate to a cloud with multiple VMs in the future or not. Which comes down to: gamble whether they should invest time in code / architecture which they might never need. (YAGNI anyone?) So the VM we're talking about, is that a low-level VM which runs a guest OS, or is that VM a different kind of VM? The flexible VM: .NET's CLR ? My example websites are ASP.NET based, which means they run inside a .NET appdomain, on the .NET CLR, which is a VM. The only physical OS resource the sites need is the file system, however this too is accessed through .NET. In short: all the websites see is what .NET allows the websites to see, the world as the websites know it is what .NET shows them and lets them access. How the .NET appdomain is run physically, that's the concern of .NET, not mine. This begs the question why Windows Azure doesn't offer virtual appdomains? Or better: .NET environments which look like one machine but could be physically multiple machines. In such an environment, no change has to be made to the websites to migrate them from a local machine or own server to the cloud to get proper scaling: the .NET VM will simply scale with the need: more memory needed, more CPU power needed, it stretches. What it offers to the application running inside the appdomain is simply increasing, but not fragmented: all resources are available to the application: this means that the problem of how to scale is back to where it should be: with the cloud vendor. "Yeah, great, but what about the databases?" The .NET application communicates with the database server through a .NET ADO.NET provider. Where the database is located is not a problem of the appdomain: the ADO.NET provider has to solve that. I.o.w.: we can host the databases in an environment which offers itself as a single resource and is accessible through one connection string without replication overhead on the outside, and use that environment inside the .NET VM as if it was a single DB. But what about memory replication and other problems? This environment isn't simple, at least not for the cloud vendor. But it is simple for the customer who wants to run his sites in that cloud: no work needed. No refactoring needed of existing code. Upload it, run it. Perhaps I'm dreaming and what I described above isn't possible. Yet, I think if cloud vendors don't move into that direction, what they're offering isn't interesting: it doesn't solve a problem at all, it simply offers a way to instantiate more VMs with the guest OS of choice at the cost of me needing to refactor my website code so it can run in the straight jacket form factor dictated by the cloud vendor. Let's not kid ourselves here: most of us developers will never build a website which needs a truck load of VMs to run it: almost all websites created by developers can run on just a few VMs at most. Yet, the most expensive change is right at the start: moving from one to two VMs. As soon as you have refactored your website code to run across multiple VMs, adding another one is just as easy as clicking a mouse button. But that first step, that's the problem here and as it's right there at the beginning of scaling the website, it's particularly strange that cloud vendors refuse to solve that problem and leave it to the developers to solve that. Which makes migrating 'to the cloud' particularly expensive.

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  • Plan Operator Tuesday round-up

    - by Rob Farley
    Eighteen posts for T-SQL Tuesday #43 this month, discussing Plan Operators. I put them together and made the following clickable plan. It’s 1000px wide, so I hope you have a monitor wide enough. Let me explain this plan for you (people’s names are the links to the articles on their blogs – the same links as in the plan above). It was clearly a SELECT statement. Wayne Sheffield (@dbawayne) wrote about that, so we start with a SELECT physical operator, leveraging the logical operator Wayne Sheffield. The SELECT operator calls the Paul White operator, discussed by Jason Brimhall (@sqlrnnr) in his post. The Paul White operator is quite remarkable, and can consume three streams of data. Let’s look at those streams. The first pulls data from a Table Scan – Boris Hristov (@borishristov)’s post – using parallel threads (Bradley Ball – @sqlballs) that pull the data eagerly through a Table Spool (Oliver Asmus – @oliverasmus). A scalar operation is also performed on it, thanks to Jeffrey Verheul (@devjef)’s Compute Scalar operator. The second stream of data applies Evil (I figured that must mean a procedural TVF, but could’ve been anything), courtesy of Jason Strate (@stratesql). It performs this Evil on the merging of parallel streams (Steve Jones – @way0utwest), which suck data out of a Switch (Paul White – @sql_kiwi). This Switch operator is consuming data from up to four lookups, thanks to Kalen Delaney (@sqlqueen), Rick Krueger (@dataogre), Mickey Stuewe (@sqlmickey) and Kathi Kellenberger (@auntkathi). Unfortunately Kathi’s name is a bit long and has been truncated, just like in real plans. The last stream performs a join of two others via a Nested Loop (Matan Yungman – @matanyungman). One pulls data from a Spool (my post – @rob_farley) populated from a Table Scan (Jon Morisi). The other applies a catchall operator (the catchall is because Tamera Clark (@tameraclark) didn’t specify any particular operator, and a catchall is what gets shown when SSMS doesn’t know what to show. Surprisingly, it’s showing the yellow one, which is about cursors. Hopefully that’s not what Tamera planned, but anyway...) to the output from an Index Seek operator (Sebastian Meine – @sqlity). Lastly, I think everyone put in 110% effort, so that’s what all the operators cost. That didn’t leave anything for me, unfortunately, but that’s okay. Also, because he decided to use the Paul White operator, Jason Brimhall gets 0%, and his 110% was given to Paul’s Switch operator post. I hope you’ve enjoyed this T-SQL Tuesday, and have learned something extra about Plan Operators. Keep your eye out for next month’s one by watching the Twitter Hashtag #tsql2sday, and why not contribute a post to the party? Big thanks to Adam Machanic as usual for starting all this. @rob_farley

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  • Generate DROP statements for all extended properties

    - by jamiet
    This evening I have been attempting to migrate an existing on-premise database to SQL Azure using the wizard that is built-in to SQL Server Management Studio (SSMS). When I did so I received the following error: The following objects are not supported = [MS_Description] = Extended Property Evidently databases containing extended properties can not be migrated using this particular wizard so I set about removing all of the extended properties – unfortunately there were over a thousand of them so I needed a better way than simply deleting each and every one of them manually. I found a couple of resources online that went some way toward this: Drop all extended properties in a MSSQL database by Angelo Hongens Modifying and deleting extended properties by Adam Aspin Unfortunately neither provided a script that exactly suited my needs. Angelo’s covered extended properties on tables and columns however I had other objects that had extended properties on them. Adam’s looked more complete but when I ran it I got an error: Msg 468, Level 16, State 9, Line 78 Cannot resolve the collation conflict between "Latin1_General_100_CS_AS" and "Latin1_General_CI_AS" in the equal to operation. So, both great resources but I wasn’t able to use either on their own to get rid of all of my extended properties. Hence, I combined the excellent work that Angelo and Adam had provided in order to manufacture my own script which did successfully manage to generate calls to sp_dropextendedproperty for all of my extended properties. If you think you might be able to make use of such a script then feel free to download it from https://skydrive.live.com/redir.aspx?cid=550f681dad532637&resid=550F681DAD532637!16707&parid=550F681DAD532637!16706&authkey=!APxPIQCatzC7BQ8. This script will remove extended properties on tables, columns, check constraints, default constraints, views, sprocs, foreign keys, primary keys, table triggers, UDF parameters, sproc parameters, databases, schemas, database files and filegroups. If you have any object types with extended properties on them that are not in that list then consult Adam’s aforementioned article – it should prove very useful. I repeat here the message that I have placed at the top of the script: /* This script will generate calls to sp_dropextendedproperty for every extended property that exists in your database. Actually, a caveat: I don't promise that it will catch each and every extended property that exists, but I'm confident it will catch most of them! It is based on this: http://blog.hongens.nl/2010/02/25/drop-all-extended-properties-in-a-mssql-database/ by Angelo Hongens. Also had lots of help from this: http://www.sqlservercentral.com/articles/Metadata/72609/ by Adam Aspin Adam actually provides a script at that link to do something very similar but when I ran it I got an error: Msg 468, Level 16, State 9, Line 78 Cannot resolve the collation conflict between "Latin1_General_100_CS_AS" and "Latin1_General_CI_AS" in the equal to operation. So I put together this version instead. Use at your own risk. Jamie Thomson 2012-03-25 */ Hope this is useful to someone! @Jamiet

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  • Today’s Performance Tip: Views are for Convenience, Not Performance!

    - by Jonathan Kehayias
    I tweeted this last week on twitter and got a lot of retweets so I thought that I’d blog the story behind the tweet. Most vendor databases have views in them, and when people want to retrieve data from a database, it seems like the most common first stop they make are the vendor supplied Views.  This post is in no way a bash against the usage or creation of Views in a SQL Server Database, I have created them before to simplify code and compartmentalize commonly required queries so that there...(read more)

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  • Service Broker, not ETL

    - by jamiet
    I have been very quiet on this blog of late and one reason for that is I have been very busy on a client project that I would like to talk about a little here. The client that I have been working for has a website that runs on a distributed architecture utilising a messaging infrastructure for communication between different endpoints. My brief was to build a system that could consume these messages and produce analytical information in near-real-time. More specifically I basically had to deliver a data warehouse however it was the real-time aspect of the project that really intrigued me. This real-time requirement meant that using an Extract transformation, Load (ETL) tool was out of the question and so I had no choice but to write T-SQL code (i.e. stored-procedures) to process the incoming messages and load the data into the data warehouse. This concerned me though – I had no way to control the rate at which data would arrive into the system yet we were going to have end-users querying the system at the same time that those messages were arriving; the potential for contention in such a scenario was pretty high and and was something I wanted to minimise as much as possible. Moreover I did not want the processing of data inside the data warehouse to have any impact on the customer-facing website. As you have probably guessed from the title of this blog post this is where Service Broker stepped in! For those that have not heard of it Service Broker is a queuing technology that has been built into SQL Server since SQL Server 2005. It provides a number of features however the one that was of interest to me was the fact that it facilitates asynchronous data processing which, in layman’s terms, means the ability to process some data without requiring the system that supplied the data having to wait for the response. That was a crucial feature because on this project the customer-facing website (in effect an OLTP system) would be calling one of our stored procedures with each message – we did not want to cause the OLTP system to wait on us every time we processed one of those messages. This asynchronous nature also helps to alleviate the contention problem because the asynchronous processing activity is handled just like any other task in the database engine and hence can wait on another task (such as an end-user query). Service Broker it was then! The stored procedure called by the OLTP system would simply put the message onto a queue and we would use a feature called activation to pick each message off the queue in turn and process it into the warehouse. At the time of writing the system is not yet up to full capacity but so far everything seems to be working OK (touch wood) and crucially our users are seeing data in near-real-time. By near-real-time I am talking about latencies of a few minutes at most and to someone like me who is used to building systems that have overnight latencies that is a huge step forward! So then, am I advocating that you all go out and dump your ETL tools? Of course not, no! What this project has taught me though is that in certain scenarios there may be better ways to implement a data warehouse system then the traditional “load data in overnight” approach that we are all used to. Moreover I have really enjoyed getting to grips with a new technology and even if you don’t want to use Service Broker you might want to consider asynchronous messaging architectures for your BI/data warehousing solutions in the future. This has been a very high level overview of my use of Service Broker and I have deliberately left out much of the minutiae of what has been a very challenging implementation. Nonetheless I hope I have caused you to reflect upon your own approaches to BI and question whether other approaches may be more tenable. All comments and questions gratefully received! Lastly, if you have never used Service Broker before and want to kick the tyres I have provided below a very simple “Service Broker Hello World” script that will create all of the objects required to facilitate Service Broker communications and then send the message “Hello World” from one place to anther! This doesn’t represent a “proper” implementation per se because it doesn’t close down down conversation objects (which you should always do in a real-world scenario) but its enough to demonstrate the capabilities! @Jamiet ----------------------------------------------------------------------------------------------- /*This is a basic Service Broker Hello World app. Have fun! -Jamie */ USE MASTER GO CREATE DATABASE SBTest GO --Turn Service Broker on! ALTER DATABASE SBTest SET ENABLE_BROKER GO USE SBTest GO -- 1) we need to create a message type. Note that our message type is -- very simple and allowed any type of content CREATE MESSAGE TYPE HelloMessage VALIDATION = NONE GO -- 2) Once the message type has been created, we need to create a contract -- that specifies who can send what types of messages CREATE CONTRACT HelloContract (HelloMessage SENT BY INITIATOR) GO --We can query the metadata of the objects we just created SELECT * FROM   sys.service_message_types WHERE name = 'HelloMessage'; SELECT * FROM   sys.service_contracts WHERE name = 'HelloContract'; SELECT * FROM   sys.service_contract_message_usages WHERE  service_contract_id IN (SELECT service_contract_id FROM sys.service_contracts WHERE name = 'HelloContract') AND        message_type_id IN (SELECT message_type_id FROM sys.service_message_types WHERE name = 'HelloMessage'); -- 3) The communication is between two endpoints. Thus, we need two queues to -- hold messages CREATE QUEUE SenderQueue CREATE QUEUE ReceiverQueue GO --more querying metatda SELECT * FROM sys.service_queues WHERE name IN ('SenderQueue','ReceiverQueue'); --we can also select from the queues as if they were tables SELECT * FROM SenderQueue   SELECT * FROM ReceiverQueue   -- 4) Create the required services and bind them to be above created queues CREATE SERVICE Sender   ON QUEUE SenderQueue CREATE SERVICE Receiver   ON QUEUE ReceiverQueue (HelloContract) GO --more querying metadata SELECT * FROM sys.services WHERE name IN ('Receiver','Sender'); -- 5) At this point, we can begin the conversation between the two services by -- sending messages DECLARE @conversationHandle UNIQUEIDENTIFIER DECLARE @message NVARCHAR(100) BEGIN   BEGIN TRANSACTION;   BEGIN DIALOG @conversationHandle         FROM SERVICE Sender         TO SERVICE 'Receiver'         ON CONTRACT HelloContract WITH ENCRYPTION=OFF   -- Send a message on the conversation   SET @message = N'Hello, World';   SEND  ON CONVERSATION @conversationHandle         MESSAGE TYPE HelloMessage (@message)   COMMIT TRANSACTION END GO --check contents of queues SELECT * FROM SenderQueue   SELECT * FROM ReceiverQueue   GO -- Receive a message from the queue RECEIVE CONVERT(NVARCHAR(MAX), message_body) AS MESSAGE FROM ReceiverQueue GO --If no messages were received and/or you can't see anything on the queues you may wish to check the following for clues: SELECT * FROM sys.transmission_queue -- Cleanup DROP SERVICE Sender DROP SERVICE Receiver DROP QUEUE SenderQueue DROP QUEUE ReceiverQueue DROP CONTRACT HelloContract DROP MESSAGE TYPE HelloMessage GO USE MASTER GO DROP DATABASE SBTest GO

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  • COLUMNS_UPDATED() for audit triggers

    - by Piotr Rodak
    In SQL Server 2005, triggers are pretty much the only option if you want to audit changes to a table. There are many ways you can decide to store the change information. You may decide to store every changed row as a whole, either in a history table or as xml in audit table. The former case requires having a history table with exactly same schema as the audited table, the latter makes data retrieval and management of the table a bit tricky. Both approaches also suffer from the tendency to consume...(read more)

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  • Third Party Applications and Other Acts of Violence Against Your SQL Server

    - by KKline
    I just got finished reading a great blog post from my buddy, Thomas LaRock ( t | b ), in which he describes a useful personal policy he used to track changes made to his SQL Servers when installing third-party products. Note that I'm talking about line-of-business applications here - your inventory management systems and help desk ticketing apps. I'm not talking about monitoring and tuning applications since they, by their very nature, need a different sort of access to your back-end server resources....(read more)

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  • SQL Server Training in the UK–SSIS, MDX, Admin, MDS, Internals

    - by simonsabin
    If you are looking for SQL Server training they there is no better place to start than a new company Technitrain Its been setup by a fellow MVP and SQLBits Organiser Chris Webb. Why this company rather than any others? Training based on real world experience by the best in the business. The key to Technitrain’s model is not to cram the shelves high with courses and get some average Joe trainers to deliver them. Technitrain bring in world renowned experts in their fields to deliver courses written...(read more)

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  • Highlight Word add-in for Visual Studio 2010 [SSDT]

    - by jamiet
    I’ve just been alerted by my colleague Kyle Harvie to a Visual Studio 2010 add-in that should prove very useful if you are an SSDT user. Its simply called Highlight all occurrences of selected word and does exactly what it says on the tin, you highlight a word and it shows all other occurrences of that word in your script: There’s a limitation for .sql files (which I have reported) where the highlighting doesn’t work if the word is wrapped in square brackets but what the heck, its free, it takes about ten seconds to install….install it already! @Jamiet

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  • VBUG Manchester March 3rd 2010 - Slides and examples

    - by MartinBell
    At the VBUG meeting in Manchester on 3rd March, I was scheduled to talk about Table Valued Parameters, but when I got there the guys wanted something more general so I talked about some of the new features of SQL 2008. The presentation is here and the TVP demo project is here . My blog postings on TVPs are listed at http://sqlblogcasts.com/blogs/martinbell/archive/tags/TVP/default.aspx . Information about the new date and time data types http://sqlblogcasts.com/blogs/martinbell/archive/2009/05/15...(read more)

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  • The SSIS tuning tip that everyone misses

    - by Rob Farley
    I know that everyone misses this, because I’m yet to find someone who doesn’t have a bit of an epiphany when I describe this. When tuning Data Flows in SQL Server Integration Services, people see the Data Flow as moving from the Source to the Destination, passing through a number of transformations. What people don’t consider is the Source, getting the data out of a database. Remember, the source of data for your Data Flow is not your Source Component. It’s wherever the data is, within your database, probably on a disk somewhere. You need to tune your query to optimise it for SSIS, and this is what most people fail to do. I’m not suggesting that people don’t tune their queries – there’s plenty of information out there about making sure that your queries run as fast as possible. But for SSIS, it’s not about how fast your query runs. Let me say that again, but in bolder text: The speed of an SSIS Source is not about how fast your query runs. If your query is used in a Source component for SSIS, the thing that matters is how fast it starts returning data. In particular, those first 10,000 rows to populate that first buffer, ready to pass down the rest of the transformations on its way to the Destination. Let’s look at a very simple query as an example, using the AdventureWorks database: We’re picking the different Weight values out of the Product table, and it’s doing this by scanning the table and doing a Sort. It’s a Distinct Sort, which means that the duplicates are discarded. It'll be no surprise to see that the data produced is sorted. Obvious, I know, but I'm making a comparison to what I'll do later. Before I explain the problem here, let me jump back into the SSIS world... If you’ve investigated how to tune an SSIS flow, then you’ll know that some SSIS Data Flow Transformations are known to be Blocking, some are Partially Blocking, and some are simply Row transformations. Take the SSIS Sort transformation, for example. I’m using a larger data set for this, because my small list of Weights won’t demonstrate it well enough. Seven buffers of data came out of the source, but none of them could be pushed past the Sort operator, just in case the last buffer contained the data that would be sorted into the first buffer. This is a blocking operation. Back in the land of T-SQL, we consider our Distinct Sort operator. It’s also blocking. It won’t let data through until it’s seen all of it. If you weren’t okay with blocking operations in SSIS, why would you be happy with them in an execution plan? The source of your data is not your OLE DB Source. Remember this. The source of your data is the NCIX/CIX/Heap from which it’s being pulled. Picture it like this... the data flowing from the Clustered Index, through the Distinct Sort operator, into the SELECT operator, where a series of SSIS Buffers are populated, flowing (as they get full) down through the SSIS transformations. Alright, I know that I’m taking some liberties here, because the two queries aren’t the same, but consider the visual. The data is flowing from your disk and through your execution plan before it reaches SSIS, so you could easily find that a blocking operation in your plan is just as painful as a blocking operation in your SSIS Data Flow. Luckily, T-SQL gives us a brilliant query hint to help avoid this. OPTION (FAST 10000) This hint means that it will choose a query which will optimise for the first 10,000 rows – the default SSIS buffer size. And the effect can be quite significant. First let’s consider a simple example, then we’ll look at a larger one. Consider our weights. We don’t have 10,000, so I’m going to use OPTION (FAST 1) instead. You’ll notice that the query is more expensive, using a Flow Distinct operator instead of the Distinct Sort. This operator is consuming 84% of the query, instead of the 59% we saw from the Distinct Sort. But the first row could be returned quicker – a Flow Distinct operator is non-blocking. The data here isn’t sorted, of course. It’s in the same order that it came out of the index, just with duplicates removed. As soon as a Flow Distinct sees a value that it hasn’t come across before, it pushes it out to the operator on its left. It still has to maintain the list of what it’s seen so far, but by handling it one row at a time, it can push rows through quicker. Overall, it’s a lot more work than the Distinct Sort, but if the priority is the first few rows, then perhaps that’s exactly what we want. The Query Optimizer seems to do this by optimising the query as if there were only one row coming through: This 1 row estimation is caused by the Query Optimizer imagining the SELECT operation saying “Give me one row” first, and this message being passed all the way along. The request might not make it all the way back to the source, but in my simple example, it does. I hope this simple example has helped you understand the significance of the blocking operator. Now I’m going to show you an example on a much larger data set. This data was fetching about 780,000 rows, and these are the Estimated Plans. The data needed to be Sorted, to support further SSIS operations that needed that. First, without the hint. ...and now with OPTION (FAST 10000): A very different plan, I’m sure you’ll agree. In case you’re curious, those arrows in the top one are 780,000 rows in size. In the second, they’re estimated to be 10,000, although the Actual figures end up being 780,000. The top one definitely runs faster. It finished several times faster than the second one. With the amount of data being considered, these numbers were in minutes. Look at the second one – it’s doing Nested Loops, across 780,000 rows! That’s not generally recommended at all. That’s “Go and make yourself a coffee” time. In this case, it was about six or seven minutes. The faster one finished in about a minute. But in SSIS-land, things are different. The particular data flow that was consuming this data was significant. It was being pumped into a Script Component to process each row based on previous rows, creating about a dozen different flows. The data flow would take roughly ten minutes to run – ten minutes from when the data first appeared. The query that completes faster – chosen by the Query Optimizer with no hints, based on accurate statistics (rather than pretending the numbers are smaller) – would take a minute to start getting the data into SSIS, at which point the ten-minute flow would start, taking eleven minutes to complete. The query that took longer – chosen by the Query Optimizer pretending it only wanted the first 10,000 rows – would take only ten seconds to fill the first buffer. Despite the fact that it might have taken the database another six or seven minutes to get the data out, SSIS didn’t care. Every time it wanted the next buffer of data, it was already available, and the whole process finished in about ten minutes and ten seconds. When debugging SSIS, you run the package, and sit there waiting to see the Debug information start appearing. You look for the numbers on the data flow, and seeing operators going Yellow and Green. Without the hint, I’d sit there for a minute. With the hint, just ten seconds. You can imagine which one I preferred. By adding this hint, it felt like a magic wand had been waved across the query, to make it run several times faster. It wasn’t the case at all – but it felt like it to SSIS.

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  • Adding SQL Cache Dependencies to the Loosely coupled .NET Cache Provider

    - by Rhames
    This post adds SQL Cache Dependency support to the loosely coupled .NET Cache Provider that I described in the previous post (http://geekswithblogs.net/Rhames/archive/2012/09/11/loosely-coupled-.net-cache-provider-using-dependency-injection.aspx). The sample code is available on github at https://github.com/RobinHames/CacheProvider.git. Each time we want to apply a cache dependency to a call to fetch or cache a data item we need to supply an instance of the relevant dependency implementation. This suggests an Abstract Factory will be useful to create cache dependencies as needed. We can then use Dependency Injection to inject the factory into the relevant consumer. Castle Windsor provides a typed factory facility that will be utilised to implement the cache dependency abstract factory (see http://docs.castleproject.org/Windsor.Typed-Factory-Facility-interface-based-factories.ashx). Cache Dependency Interfaces First I created a set of cache dependency interfaces in the domain layer, which can be used to pass a cache dependency into the cache provider. ICacheDependency The ICacheDependency interface is simply an empty interface that is used as a parent for the specific cache dependency interfaces. This will allow us to place a generic constraint on the Cache Dependency Factory, and will give us a type that can be passed into the relevant Cache Provider methods. namespace CacheDiSample.Domain.CacheInterfaces { public interface ICacheDependency { } }   ISqlCacheDependency.cs The ISqlCacheDependency interface provides specific SQL caching details, such as a Sql Command or a database connection and table. It is the concrete implementation of this interface that will be created by the factory in passed into the Cache Provider. using System; using System.Collections.Generic; using System.Linq; using System.Text;   namespace CacheDiSample.Domain.CacheInterfaces { public interface ISqlCacheDependency : ICacheDependency { ISqlCacheDependency Initialise(string databaseConnectionName, string tableName); ISqlCacheDependency Initialise(System.Data.SqlClient.SqlCommand sqlCommand); } } If we want other types of cache dependencies, such as by key or file, interfaces may be created to support these (the sample code includes an IKeyCacheDependency interface). Modifying ICacheProvider to accept Cache Dependencies Next I modified the exisitng ICacheProvider<T> interface so that cache dependencies may be passed into a Fetch method call. I did this by adding two overloads to the existing Fetch methods, which take an IEnumerable<ICacheDependency> parameter (the IEnumerable allows more than one cache dependency to be included). I also added a method to create cache dependencies. This means that the implementation of the Cache Provider will require a dependency on the Cache Dependency Factory. It is pretty much down to personal choice as to whether this approach is taken, or whether the Cache Dependency Factory is injected directly into the repository or other consumer of Cache Provider. I think, because the cache dependency cannot be used without the Cache Provider, placing the dependency on the factory into the Cache Provider implementation is cleaner. ICacheProvider.cs using System; using System.Collections.Generic;   namespace CacheDiSample.Domain.CacheInterfaces { public interface ICacheProvider<T> { T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry); T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry, IEnumerable<ICacheDependency> cacheDependencies);   IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry); IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry, IEnumerable<ICacheDependency> cacheDependencies);   U CreateCacheDependency<U>() where U : ICacheDependency; } }   Cache Dependency Factory Next I created the interface for the Cache Dependency Factory in the domain layer. ICacheDependencyFactory.cs namespace CacheDiSample.Domain.CacheInterfaces { public interface ICacheDependencyFactory { T Create<T>() where T : ICacheDependency;   void Release<T>(T cacheDependency) where T : ICacheDependency; } }   I used the ICacheDependency parent interface as a generic constraint on the create and release methods in the factory interface. Now the interfaces are in place, I moved on to the concrete implementations. ISqlCacheDependency Concrete Implementation The concrete implementation of ISqlCacheDependency will need to provide an instance of System.Web.Caching.SqlCacheDependency to the Cache Provider implementation. Unfortunately this class is sealed, so I cannot simply inherit from this. Instead, I created an interface called IAspNetCacheDependency that will provide a Create method to create an instance of the relevant System.Web.Caching Cache Dependency type. This interface is specific to the ASP.NET implementation of the Cache Provider, so it should be defined in the same layer as the concrete implementation of the Cache Provider (the MVC UI layer in the sample code). IAspNetCacheDependency.cs using System.Web.Caching;   namespace CacheDiSample.CacheProviders { public interface IAspNetCacheDependency { CacheDependency CreateAspNetCacheDependency(); } }   Next, I created the concrete implementation of the ISqlCacheDependency interface. This class also implements the IAspNetCacheDependency interface. This concrete implementation also is defined in the same layer as the Cache Provider implementation. AspNetSqlCacheDependency.cs using System.Web.Caching; using CacheDiSample.Domain.CacheInterfaces;   namespace CacheDiSample.CacheProviders { public class AspNetSqlCacheDependency : ISqlCacheDependency, IAspNetCacheDependency { private string databaseConnectionName;   private string tableName;   private System.Data.SqlClient.SqlCommand sqlCommand;   #region ISqlCacheDependency Members   public ISqlCacheDependency Initialise(string databaseConnectionName, string tableName) { this.databaseConnectionName = databaseConnectionName; this.tableName = tableName; return this; }   public ISqlCacheDependency Initialise(System.Data.SqlClient.SqlCommand sqlCommand) { this.sqlCommand = sqlCommand; return this; }   #endregion   #region IAspNetCacheDependency Members   public System.Web.Caching.CacheDependency CreateAspNetCacheDependency() { if (sqlCommand != null) return new SqlCacheDependency(sqlCommand); else return new SqlCacheDependency(databaseConnectionName, tableName); }   #endregion   } }   ICacheProvider Concrete Implementation The ICacheProvider interface is implemented by the CacheProvider class. This implementation is modified to include the changes to the ICacheProvider interface. First I needed to inject the Cache Dependency Factory into the Cache Provider: private ICacheDependencyFactory cacheDependencyFactory;   public CacheProvider(ICacheDependencyFactory cacheDependencyFactory) { if (cacheDependencyFactory == null) throw new ArgumentNullException("cacheDependencyFactory");   this.cacheDependencyFactory = cacheDependencyFactory; }   Next I implemented the CreateCacheDependency method, which simply passes on the create request to the factory: public U CreateCacheDependency<U>() where U : ICacheDependency { return this.cacheDependencyFactory.Create<U>(); }   The signature of the FetchAndCache helper method was modified to take an additional IEnumerable<ICacheDependency> parameter:   private U FetchAndCache<U>(string key, Func<U> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry, IEnumerable<ICacheDependency> cacheDependencies) and the following code added to create the relevant System.Web.Caching.CacheDependency object for any dependencies and pass them to the HttpContext Cache: CacheDependency aspNetCacheDependencies = null;   if (cacheDependencies != null) { if (cacheDependencies.Count() == 1) // We know that the implementations of ICacheDependency will also implement IAspNetCacheDependency // so we can use a cast here and call the CreateAspNetCacheDependency() method aspNetCacheDependencies = ((IAspNetCacheDependency)cacheDependencies.ElementAt(0)).CreateAspNetCacheDependency(); else if (cacheDependencies.Count() > 1) { AggregateCacheDependency aggregateCacheDependency = new AggregateCacheDependency(); foreach (ICacheDependency cacheDependency in cacheDependencies) { // We know that the implementations of ICacheDependency will also implement IAspNetCacheDependency // so we can use a cast here and call the CreateAspNetCacheDependency() method aggregateCacheDependency.Add(((IAspNetCacheDependency)cacheDependency).CreateAspNetCacheDependency()); } aspNetCacheDependencies = aggregateCacheDependency; } }   HttpContext.Current.Cache.Insert(key, value, aspNetCacheDependencies, absoluteExpiry.Value, relativeExpiry.Value);   The full code listing for the modified CacheProvider class is shown below: using System; using System.Collections.Generic; using System.Linq; using System.Web; using System.Web.Caching; using CacheDiSample.Domain.CacheInterfaces;   namespace CacheDiSample.CacheProviders { public class CacheProvider<T> : ICacheProvider<T> { private ICacheDependencyFactory cacheDependencyFactory;   public CacheProvider(ICacheDependencyFactory cacheDependencyFactory) { if (cacheDependencyFactory == null) throw new ArgumentNullException("cacheDependencyFactory");   this.cacheDependencyFactory = cacheDependencyFactory; }   public T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) { return FetchAndCache<T>(key, retrieveData, absoluteExpiry, relativeExpiry, null); }   public T Fetch(string key, Func<T> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry, IEnumerable<ICacheDependency> cacheDependencies) { return FetchAndCache<T>(key, retrieveData, absoluteExpiry, relativeExpiry, cacheDependencies); }   public IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry) { return FetchAndCache<IEnumerable<T>>(key, retrieveData, absoluteExpiry, relativeExpiry, null); }   public IEnumerable<T> Fetch(string key, Func<IEnumerable<T>> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry, IEnumerable<ICacheDependency> cacheDependencies) { return FetchAndCache<IEnumerable<T>>(key, retrieveData, absoluteExpiry, relativeExpiry, cacheDependencies); }   public U CreateCacheDependency<U>() where U : ICacheDependency { return this.cacheDependencyFactory.Create<U>(); }   #region Helper Methods   private U FetchAndCache<U>(string key, Func<U> retrieveData, DateTime? absoluteExpiry, TimeSpan? relativeExpiry, IEnumerable<ICacheDependency> cacheDependencies) { U value; if (!TryGetValue<U>(key, out value)) { value = retrieveData(); if (!absoluteExpiry.HasValue) absoluteExpiry = Cache.NoAbsoluteExpiration;   if (!relativeExpiry.HasValue) relativeExpiry = Cache.NoSlidingExpiration;   CacheDependency aspNetCacheDependencies = null;   if (cacheDependencies != null) { if (cacheDependencies.Count() == 1) // We know that the implementations of ICacheDependency will also implement IAspNetCacheDependency // so we can use a cast here and call the CreateAspNetCacheDependency() method aspNetCacheDependencies = ((IAspNetCacheDependency)cacheDependencies.ElementAt(0)).CreateAspNetCacheDependency(); else if (cacheDependencies.Count() > 1) { AggregateCacheDependency aggregateCacheDependency = new AggregateCacheDependency(); foreach (ICacheDependency cacheDependency in cacheDependencies) { // We know that the implementations of ICacheDependency will also implement IAspNetCacheDependency // so we can use a cast here and call the CreateAspNetCacheDependency() method aggregateCacheDependency.Add( ((IAspNetCacheDependency)cacheDependency).CreateAspNetCacheDependency()); } aspNetCacheDependencies = aggregateCacheDependency; } }   HttpContext.Current.Cache.Insert(key, value, aspNetCacheDependencies, 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 } }   Wiring up the DI Container Now the implementations for the Cache Dependency are in place, I wired them up in the existing Windsor CacheInstaller. First I needed to register the implementation of the ISqlCacheDependency interface: container.Register( Component.For<ISqlCacheDependency>() .ImplementedBy<AspNetSqlCacheDependency>() .LifestyleTransient());   Next I registered the Cache Dependency Factory. Notice that I have not implemented the ICacheDependencyFactory interface. Castle Windsor will do this for me by using the Type Factory Facility. I do need to bring the Castle.Facilities.TypedFacility namespace into scope: using Castle.Facilities.TypedFactory;   Then I registered the factory: container.AddFacility<TypedFactoryFacility>();   container.Register( Component.For<ICacheDependencyFactory>() .AsFactory()); The full code for the CacheInstaller class is: using Castle.MicroKernel.Registration; using Castle.MicroKernel.SubSystems.Configuration; using Castle.Windsor; using Castle.Facilities.TypedFactory;   using CacheDiSample.Domain.CacheInterfaces; using CacheDiSample.CacheProviders;   namespace CacheDiSample.WindsorInstallers { public class CacheInstaller : IWindsorInstaller { public void Install(IWindsorContainer container, IConfigurationStore store) { container.Register( Component.For(typeof(ICacheProvider<>)) .ImplementedBy(typeof(CacheProvider<>)) .LifestyleTransient());   container.Register( Component.For<ISqlCacheDependency>() .ImplementedBy<AspNetSqlCacheDependency>() .LifestyleTransient());   container.AddFacility<TypedFactoryFacility>();   container.Register( Component.For<ICacheDependencyFactory>() .AsFactory()); } } }   Configuring the ASP.NET SQL Cache Dependency There are a couple of configuration steps required to enable SQL Cache Dependency for the application and database. From the Visual Studio Command Prompt, the following commands should be used to enable the Cache Polling of the relevant database tables: aspnet_regsql -S <servername> -E -d <databasename> –ed aspnet_regsql -S <servername> -E -d CacheSample –et –t <tablename>   (The –t option should be repeated for each table that is to be made available for cache dependencies). Finally the SQL Cache Polling needs to be enabled by adding the following configuration to the <system.web> section of web.config: <caching> <sqlCacheDependency pollTime="10000" enabled="true"> <databases> <add name="BloggingContext" connectionStringName="BloggingContext"/> </databases> </sqlCacheDependency> </caching>   (obviously the name and connection string name should be altered as required). Using a SQL Cache Dependency Now all the coding is complete. To specify a SQL Cache Dependency, I can modify my BlogRepositoryWithCaching decorator class (see the earlier post) as follows: public IList<Blog> GetAll() { var sqlCacheDependency = cacheProvider.CreateCacheDependency<ISqlCacheDependency>() .Initialise("BloggingContext", "Blogs");   ICacheDependency[] cacheDependencies = new ICacheDependency[] { sqlCacheDependency };   string key = string.Format("CacheDiSample.DataAccess.GetAll");   return cacheProvider.Fetch(key, () => { return parentBlogRepository.GetAll(); }, null, null, cacheDependencies) .ToList(); }   This will add a dependency of the “Blogs” table in the database. The data will remain in the cache until the contents of this table change, then the cache item will be invalidated, and the next call to the GetAll() repository method will be routed to the parent repository to refresh the data from the database.

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  • R2 download site is looking good

    - by DavidWimbush
    The MSDN downloads for R2 appeared as promised yesterday. Congratulations to everyone on the SQL team. I must have got one of the first downloads of the Developer Edition and it was nice and fast. I've just downloaded Standard Edition and it's still nearly as fast. Nice. I'm guessing they aren't using GUIDs for the clustered indexes this time! ;)

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  • StreamInsight SQL Social Followup

    - by simonsabin
    Thank you for those that attended the SQL Social last night I hope you enjoyed it. When I get presentation details from the team I will pass them on, meanwhile have a look at their blog http://blogs.msdn.com/b/streaminsight/ which has details of most of the things that were discussed last night.   The speakers where Azam Husain Balan Sethu Raman Torsten Grabs Roman Schindlauer   Some interesting videos from these guys are here http://channel9.msdn.com/learn/courses/SQL2008R2TrainingKit...(read more)

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