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• SQL SERVER – Guest Post – Jacob Sebastian – Filestream – Wait Types – Wait Queues – Day 22 of 28

  - by pinaldave

  Jacob Sebastian is a SQL Server MVP, Author, Speaker and Trainer. Jacob is one of the top rated expert community. Jacob wrote the book The Art of XSD – SQL Server XML Schema Collections and wrote the XML Chapter in SQL Server 2008 Bible. See his Blog | Profile. He is currently researching on the subject of Filestream and have submitted this interesting article on the very subject. What is FILESTREAM? FILESTREAM is a new feature introduced in SQL Server 2008 which provides an efficient storage and management option for BLOB data. Many applications that deal with BLOB data today stores them in the file system and stores the path to the file in the relational tables. Storing BLOB data in the file system is more efficient that storing them in the database. However, this brings up a few disadvantages as well. When the BLOB data is stored in the file system, it is hard to ensure transactional consistency between the file system data and relational data. Some applications store the BLOB data within the database to overcome the limitations mentioned earlier. This approach ensures transactional consistency between the relational data and BLOB data, but is very bad in terms of performance. FILESTREAM combines the benefits of both approaches mentioned above without the disadvantages we examined. FILESTREAM stores the BLOB data in the file system (thus takes advantage of the IO Streaming capabilities of NTFS) and ensures transactional consistency between the BLOB data in the file system and the relational data in the database. For more information on the FILESTREAM feature, visit: http://beyondrelational.com/filestream/default.aspx FILESTREAM Wait Types Since this series is on the different SQL Server wait types, let us take a look at the various wait types that are related to the FILESTREAM feature. FS_FC_RWLOCK This wait type is generated by FILESTREAM Garbage Collector. This occurs when Garbage collection is disabled prior to a backup/restore operation or when a garbage collection cycle is being executed. FS_GARBAGE_COLLECTOR_SHUTDOWN This wait type occurs when during the cleanup process of a garbage collection cycle. It indicates that that garbage collector is waiting for the cleanup tasks to be completed. FS_HEADER_RWLOCK This wait type indicates that the process is waiting for obtaining access to the FILESTREAM header file for read or write operation. The FILESTREAM header is a disk file located in the FILESTREAM data container and is named “filestream.hdr”. FS_LOGTRUNC_RWLOCK This wait type indicates that the process is trying to perform a FILESTREAM log truncation related operation. It can be either a log truncate operation or to disable log truncation prior to a backup or restore operation. FSA_FORCE_OWN_XACT This wait type occurs when a FILESTREAM file I/O operation needs to bind to the associated transaction, but the transaction is currently owned by another session. FSAGENT This wait type occurs when a FILESTREAM file I/O operation is waiting for a FILESTREAM agent resource that is being used by another file I/O operation. FSTR_CONFIG_MUTEX This wait type occurs when there is a wait for another FILESTREAM feature reconfiguration to be completed. FSTR_CONFIG_RWLOCK This wait type occurs when there is a wait to serialize access to the FILESTREAM configuration parameters. Waits and Performance System waits has got a direct relationship with the overall performance. In most cases, when waits increase the performance degrades. SQL Server documentation does not say much about how we can reduce these waits. However, following the FILESTREAM best practices will help you to improve the overall performance and reduce the wait types to a good extend. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology Tagged: Filestream

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• A (Late) Meme Monday Post: On SQLFamily

  - by Argenis

    Yesterday a member of the SQL community who I deeply admire sent me a DM on Twitter asking whether I had done a SQLFamily post for Thomas LaRock’s (blog|@SQLRockstar) Meme Monday for November. I replied that I did not, and I regretted not having done so. A subtle DM followed my response: “Get on it, you have all week”. And indeed I must. So here’s an attempt to express some of my feelings on a community that has catapulted my career like nothing else before I embraced it. Nanos Gigantium Humeris Insidentes I stand on the shoulders of giants. My SQLFamily has given me support at all levels. Professionally and personally. There is never a lack of will to help and provide advice to others in this community. And I do my best to help. On #SQLHelp on Twitter, via email, or even on the phone. I expect no retribution, because I know that when and if I do run into problems, my SQLFamily will be there for me. I have met some of the most humble, dedicated and most professional people in the SQL community. And some of them have pretty big titles: MVPs, MCMs, Regional Mentors, and even leaders of PASS, SQLCAT members, and even PMs and Devs on the SQL Server team. All are welcome, and that includes YOU! I have also met some people that are rather reserved and don’t participate as much in the community, for whatever reason. Be as it may, let it be know to all that we are a very welcoming community – heck, some of my closest friends and people I can count on in the community have completely opposite political views. We share one goal: to get better and help others get better. Even if you are a lurker – my hope is that one day you’ll decide to give back some of what you have learned. You have to take it to the next level On one of my previous jobs as an IT Supervisor I used to tell my team all the time about the benefits of continuous education and self-driven learning. Shortly after I left that job, the company went bankrupt and some of my staff got laid off – some without any severance pay whatsoever. I eventually found out that some of them had a really hard time finding another job, because their skills were simply outdated. They had become stale professionals. Don’t be one of them. If you don’t take advantage of these learning resources, somebody else will – and that person has an advantage over you when applying for that awesome job position that got opened. There’s a severe shortage of good DBAs and DB Devs out there. What’s your excuse for not being excellent? Even if your knowledge of SQL Server is at the beginner level, really – you have no excuse to get better. Just go to SQLUniversity and learn from there. Don’t get stale! Thank You To all of you in the SQL community who put so much time and energy into helping others, my deepest gratitude to you. I can’t wait to meet you all again at the next event and share our SQL stories over a pint of beer (or a shot of Jaeger) Cheers! -Argenis

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• Build 2012, the first post

  - by Dennis Vroegop

  Yes, I was one of the lucky few who made it to Build. Build, formerly known as the Professional Developers Conference (or PDC) is the place to be if you are a developer on the Microsoft platform. Since I take my job seriously I took out some time on my busy schedule, sighed at the thought of not seeing my family for another week and signed up for it. Now, before I talk about the amazing Surface devices (yes, this posting is written on one of them), the great Lumia 920 we all got, the long deserved love for touch, NUI and other things I have been talking about for years, I need to do some ranting. So if you are anxious to read about the technical goodies you’ll have to wait until the next post. Still here? Good. When I signed up for the Build conference during my holidays this summer it was pretty obvious that demand would be high. Therefor I made sure I was on time. But even though I registered only 7 minutes after the initial opening time the Early Bird discount for the first 500 attendees was already sold out. I later learned that registration actually started 5 minutes before the scheduled time but even though it is still impressive how fast things went. The whole event sold out in 57 minutes Or so they say… A lot of people got put on the waiting list. There was room for about 1500 attendees and I heard that at least 1000 people were on that waiting list, including a lot of people I know. Strangely, all of them got tickets assigned after 2 weeks. Here at the conference I heard from a guy from Nokia that they had shipped 2500 Lumia 920 phones. That number matches the rumors that the organization added 1000 extra tickets. This, of course is no problem. I am not an elitist and I think large crowds have a special atmosphere that I quite like. But…. The Microsoft Campus is not equipped for that sheer volume of visitors. That was painfully obvious during on-site registration where people had to stand in line for over 2 hours. The conference is spread out over 2 buildings, divided by a 15 minute busride (yes, the campus is that big). I have seen queues of over 200 people waiting for the bus and when that arrived it had a capacity of 16. I can assure you: that doesn’t fit. This of course means that travelling from one site to the other might take about 30 minutes. So you arrive at the session room just in time, only to find out it’s full. Since you can’ get into that session you try to find another one but now you’re even more late so you have no chance at all of entering. The doors are closed and you’re told: “Well, you can watch the live stream online”. Mmmm… So I spend thousands of dollars, a week away from home, family and work to be told I can also watch the sessions online? Are you fricking kidding me? I could go on but I won’t. You get the idea. It’s jus badly organized, something I am not really used to in my 20 years of experience at Microsoft events. Yes, I am disappointed. I hope a lot of people here in Redmond will also fill in the evals and that the organization next year will do a better job. Really, Build deserves better. </rantmode>

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• SQL SERVER – Guest Post by Sandip Pani – SQL Server Statistics Name and Index Creation

  - by pinaldave

  Sometimes something very small or a common error which we observe in daily life teaches us new things. SQL Server Expert Sandip Pani (winner of Joes 2 Pros Contests) has come across similar experience. Sandip has written a guest post on an error he faced in his daily work. Sandip is working for QSI Healthcare as an Associate Technical Specialist and have more than 5 years of total experience. He blogs at SQLcommitted.com and contribute in various forums. His social media hands are LinkedIn, Facebook and Twitter. Once I faced following error when I was working on performance tuning project and attempt to create an Index. Mug 1913, Level 16, State 1, Line 1 The operation failed because an index or statistics with name ‘Ix_Table1_1′ already exists on table ‘Table1′. The immediate reaction to the error was that I might have created that index earlier and when I researched it further I found the same as the index was indeed created two times. This totally makes sense. This can happen due to many reasons for example if the user is careless and executes the same code two times as well, when he attempts to create index without checking if there was index already on the object. However when I paid attention to the details of the error, I realize that error message also talks about statistics along with the index. I got curious if the same would happen if I attempt to create indexes with the same name as statistics already created. There are a few other questions also prompted in my mind. I decided to do a small demonstration of the subject and build following demonstration script. The goal of my experiment is to find out the relation between statistics and the index. Statistics is one of the important input parameter for the optimizer during query optimization process. If the query is nontrivial then only optimizer uses statistics to perform a cost based optimization to select a plan. For accuracy and further learning I suggest to read MSDN. Now let’s find out the relationship between index and statistics. We will do the experiment in two parts. i) Creating Index ii) Creating Statistics We will be using the following T-SQL script for our example. IF (OBJECT_ID('Table1') IS NOT NULL) DROP TABLE Table1 GO CREATE TABLE Table1 (Col1 INT NOT NULL, Col2 VARCHAR(20) NOT NULL) GO We will be using following two queries to check if there are any index or statistics on our sample table Table1. -- Details of Index SELECT OBJECT_NAME(OBJECT_ID) AS TableName, Name AS IndexName, type_desc FROM sys.indexes WHERE OBJECT_NAME(OBJECT_ID) = 'table1' GO -- Details of Statistics SELECT OBJECT_NAME(OBJECT_ID) TableName, Name AS StatisticsName FROM sys.stats WHERE OBJECT_NAME(OBJECT_ID) = 'table1' GO When I ran above two scripts on the table right after it was created it did not give us any result which was expected. Now let us begin our test. 1) Create an index on the table Create following index on the table. CREATE NONCLUSTERED INDEX Ix_Table1_1 ON Table1(Col1) GO Now let us use above two scripts and see their results. We can see that when we created index at the same time it created statistics also with the same name. Before continuing to next set of demo – drop the table using following script and re-create the table using a script provided at the beginning of the table. DROP TABLE table1 GO 2) Create a statistic on the table Create following statistics on the table. CREATE STATISTICS Ix_table1_1 ON Table1 (Col1) GO Now let us use above two scripts and see their results. We can see that when we created statistics Index is not created. The behavior of this experiment is different from the earlier experiment. Clean up the table setup using the following script: DROP TABLE table1 GO Above two experiments teach us very valuable lesson that when we create indexes, SQL Server generates the index and statistics (with the same name as the index name) together. Now due to the reason if we have already had statistics with the same name but not the index, it is quite possible that we will face the error to create the index even though there is no index with the same name. A Quick Check To validate that if we create statistics first and then index after that with the same name, it will throw an error let us run following script in SSMS. Make sure to drop the table and clean up our sample table at the end of the experiment. -- Create sample table CREATE TABLE TestTable (Col1 INT NOT NULL, Col2 VARCHAR(20) NOT NULL) GO -- Create Statistics CREATE STATISTICS IX_TestTable_1 ON TestTable (Col1) GO -- Create Index CREATE NONCLUSTERED INDEX IX_TestTable_1 ON TestTable(Col1) GO -- Check error /*Msg 1913, Level 16, State 1, Line 2 The operation failed because an index or statistics with name 'IX_TestTable_1' already exists on table 'TestTable'. */ -- Clean up DROP TABLE TestTable GO While creating index it will throw the following error as statistics with the same name is already created. In simple words – when we create index the name of the index should be different from any of the existing indexes and statistics. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Error Messages, SQL Index, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: SQL Statistics

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• Tellago is still hiring….

  - by gsusx

  Tellago 's SOA practice is rapidly growing and we are still hiring. In that sense, we are looking to for Connected Systems (WCF, BizTalk, WF) experts who are passionate about building game changing solutions with the latest Microsoft technologies. You will be working alongside technology gurus like DonXml , Pablo Cibraro or Dwight Goins . If you are interested and not afraid of working with a bunch of crazy people ;)please drop me a line at jesus dot rodriguez at tellago dot com. Hope to hear from...(read more)

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• We are hiring (take a minute to read this, is not another BS talk ;) )

  - by gsusx

  I really wanted to wait until our new website was out to blog about this but I hope you can put up with the ugly website for a few more days J. Tellago keeps growing and, after a quick break at the beginning of the year, we are back in hiring mode J. We are currently expanding our teams in the United States and Argentina and have various positions open in the following categories. .NET developers: If you are an exceptional .NET programmer with a passion for creating great software solutions working...(read more)

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• Back from Teched US

  - by gsusx

  It's been a few weeks since I last blogged and, trust me, I am not happy about it :( I have been crazily busy with some of our projects at Tellago which you are going to hear more about in the upcoming weeks :) I was so busy that I didn't even have time to blog about my sessions at Teched US last week. This year I ended up presenting three sessions on three different tracks: BIE403 | Real-Time Business Intelligence with Microsoft SQL Server 2008 R2 Session Type: Breakout Session Real-time business...(read more)

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• Tellago && Tellago Studios 2010

  - by gsusx

  With 2011 around the corner we, at Tellago and Tellago Studios , we have been spending a lot of times evaluating our successes and failures (yes those too ;)) of 2010 and delineating some of our goals and strategies for 2011. When I look at 2010 here are some of the things that quickly jump off the page: Growing Tellago by 300% Launching a brand new company: Tellago Studios Expanding our customer base Establishing our business intelligence practice http://tellago.com/what-we-say/events/business-intelligence...(read more)

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• Limiting DOPs &ndash; Who rules over whom?

  - by jean-pierre.dijcks

  I've gotten a couple of questions from Dan Morgan and figured I start to answer them in this way. While Dan is running on a big system he is running with Database Resource Manager and he is trying to make sure the system doesn't go crazy (remember end user are never, ever crazy!) on very high DOPs. Q: How do I control statements with very high DOPs driven from user hints in queries? A: The best way to do this is to work with DBRM and impose limits on consumer groups. The Max DOP setting you can set in DBRM allows you to overwrite the hint. Now let's go into some more detail here. Assume my object (and for simplicity we assume there is a single object - and do remember that we always pick the highest DOP when in doubt and when conflicting DOPs are available in a query) has PARALLEL 64 as its setting. Assume that the query that selects something cool from that table lives in a consumer group with a max DOP of 32. Assume no goofy things (like running out of parallel_max_servers) are happening. A query selecting from this table will run at DOP 32 because DBRM caps the DOP. As of 11.2.0.1 we also use the DBRM cap to create the original plan (at compile time) and not just enforce the cap at runtime. Now, my user is smart and writes a query with a parallel hint requesting DOP 128. This query is still capped by DBRM and DBRM overrules the hint in the statement. The statement, despite the hint, runs at DOP 32. Note that in the hinted scenario we do compile the statement with DOP 128 (the optimizer obeys the hint). This is another reason to use table decoration rather than hints. Q: What happens if I set parallel_max_servers higher than processes (e.g. the max number of processes allowed to run on my machine)? A: Processes rules. It is important to understand that processes are fixed at startup time. If you increase parallel_max_servers above the number of processes in the processes parameter you should get a warning in the alert log stating it can not take effect. As a follow up, a hinted query requesting more parallel processes than either parallel_max_servers or processes will not be able to acquire the requested number. Parallel_max_processes will prevent this. And since parallel_max_servers should be lower than max processes you can never go over either...

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• Tellago speaks about Business Intellligence with SQL Server 2008 R2

  - by gsusx

  At Tellago , we always try to stay in the frontlines of technology that can enhance our solution development practices. This year we are putting a lot of emphasis on business intelligence and in particular the new set of BI technologies such as Microsoft's PowerPivot, Master Data Services and StreamInsight that are scheduled to be release with SQL Server 2008 R2. In the last few weeks we have been working closely with different Microsoft field offices to coordinate a series of customers events that...(read more)

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• SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

  - by pinaldave

  Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Shader effect similar to Metro 2033 gasmask

  - by Tim

  I was thinking about effects in games the other day and I was reminded of the Gasmask effect from Metro 2033. Once you put the gasmask on it blurred a bit in the corners and could ice up and even get cracked. I assume that something like that is done using a shader. I have been experimenting a bit with game development, so far mostly playing with existing rendering engines and adding physics support etc. I would like to learn more about this sort of effect. Can someone give me a simple example of a shader that would alter the entire scene like this. Or if not a shader then an idea on how it would be done. Thanks. Edit : Include screenshot of the metro 2033 gasmask effect.

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• SQL University: Parallelism Week - Introduction

  - by Adam Machanic

  Welcome to Parallelism Week at SQL University . My name is Adam Machanic, and I'm your professor. Imagine having 8 brains, or 16, or 32. Imagine being able to break up complex thoughts and distribute them across your many brains, so that you could solve problems faster. Now quit imagining that, because you're human and you're stuck with only one brain, and you only get access to the entire thing if you're lucky enough to have avoided abusing too many recreational drugs. For your database server,...(read more)

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• Integrating BizTalk Server and StreamInsight paper

  - by gsusx

  With all the holidays madness I didn't realized that my "Integrating BizTalk Server and StreamInsight" paper is now available on MSDN . This paper was originally an idea of the BizTalk product team and intends to present some fundamental scenarios that can be enabled by the combination of BizTalk Server and StreamInsight. Thanks to everybody who, directly or indirectly, provided feedback about this paper: Syed Rasheed, Mark Simms , Richard Seroter , Roman Schindlauer and Torsten Grabs from the StreamInsight...(read more)

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• Query Tuning Mastery at PASS Summit 2012: The Video

  - by Adam Machanic

  An especially clever community member was kind enough to reverse-engineer the video stream for me, and came up with a direct link to the PASS TV video stream for my Query Tuning Mastery: The Art and Science of Manhandling Parallelism talk, delivered at the PASS Summit last Thursday. I'm not sure how long this link will work , but I'd like to share it for my readers who were unable to see it in person or live on the stream. Start here. Skip past the keynote, to the 149 minute mark. Enjoy!...(read more)

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• Query Tuning Mastery at PASS Summit 2012: The Video

  - by Adam Machanic

  An especially clever community member was kind enough to reverse-engineer the video stream for me, and came up with a direct link to the PASS TV video stream for my Query Tuning Mastery: The Art and Science of Manhandling Parallelism talk, delivered at the PASS Summit last Thursday. I'm not sure how long this link will work , but I'd like to share it for my readers who were unable to see it in person or live on the stream. Start here. Skip past the keynote, to the 149 minute mark. Enjoy!...(read more)

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• Query Tuning Mastery at PASS Summit 2012: The Demos

  - by Adam Machanic

  For the second year in a row, I was asked to deliver a 500-level "Query Tuning Mastery" talk in room 6E of the Washington State Convention Center, for the PASS Summit. ( Here's some information about last year's talk, on workspace memory. ) And for the second year in a row, I had to deliver said talk at 10:15 in the morning, in a room used as overflow for the keynote, following a keynote speaker that didn't stop speaking on time. Frustrating! Last Thursday, after very, very quickly setting up and...(read more)

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• Tools for modelling data and workflows using structured text files

  - by Alexey

  Consider a case when I want to try some idea of an application. But I want to avoid investing a lot of effort in coding UI/work flows/database schema etc before I see that it's going to be useful to me (as example of potential user). My idea is stay lightweight and put all the data in text files. So the components could be following: Domain objects are represented by text files or their fragments Domain objects are grouped by their type using directories Structure the files using some both human- and machine-friendly format, e.g. YAML Use some smart text editor (e.g. vim, emacs, rubymine) to edit and navigate those files Use color schemes and macros/custom commands of the text editor to effectively manipulate those files Use scripts (or a lightweight web framework like Sinatra) to try some business logic ideas on top of the data model The question is: Are there tools or toolkits that support or can be adopted to this approach? Also any ideas, links to articles/other knowledge sources are very welcome. And more specific question: What is the simplest way to index and update index of files with YAML files?

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• Stereo images rectification and disparity: which algorithms?

  - by alessandro.francesconi

  I'm trying to figure out what are currently the two most efficent algorithms that permit, starting from a L/R pair of stereo images created using a traditional camera (so affected by some epipolar lines misalignment), to produce a pair of adjusted images plus their depth information by looking at their disparity. Actually I've found lots of papers about these two methods, like: "Computing Rectifying Homographies for Stereo Vision" (Zhang - seems one of the best for rectification only) "Three-step image recti?cation" (Monasse) "Rectification and Disparity" (slideshow by Navab) "A fast area-based stereo matching algorithm" (Di Stefano - seems a bit inaccurate) "Computing Visual Correspondence with Occlusions via Graph Cuts" (Kolmogorov - this one produces a very good disparity map, with also occlusion informations, but is it efficient?) "Dense Disparity Map Estimation Respecting Image Discontinuities" (Alvarez - toooo long for a first review) Anyone could please give me some advices for orienting into this wide topic? What kind of algorithm/method should I treat first, considering that I'll work on a very simple input: a pair of left and right images and nothing else, no more information (some papers are based on additional, pre-taken, calibration infos)? Speaking about working implementations, the only interesting results I've seen so far belongs to this piece of software, but only for automatic rectification, not disparity: http://stereo.jpn.org/eng/stphmkr/index.html I tried the "auto-adjustment" feature and seems really effective. Too bad there is no source code...

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• SQL University: Parallelism Week - Introduction

  - by Adam Machanic

  Welcome to Parallelism Week at SQL University . My name is Adam Machanic, and I'm your professor. Imagine having 8 brains, or 16, or 32. Imagine being able to break up complex thoughts and distribute them across your many brains, so that you could solve problems faster. Now quit imagining that, because you're human and you're stuck with only one brain, and you only get access to the entire thing if you're lucky enough to have avoided abusing too many recreational drugs. For your database server,...(read more)

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• How to properly render a Frame Buffer to the BackBuffer in Stage3D / AGAL

  - by bigp

  After doing a render pass with RenderToTarget (RTT), how do you properly render that texture buffer to the screen while maintaining original scale / proportions so it doesn't stretch or lose quality? Can an AGAL VertexShader & FragmentShader be written so it's adaptable to any Texture size and Viewport dimensions? I find I'm getting some "blocky" effects in some of my first attempts at "ping-ponging" between two Texture buffers (to create trailing effects). Perhaps I'm not using the UVs correctly between the rendering-to-target and/or the backbuffer? Is there a simpler way just to "splash" the texture on the backbuffer, or is a Quad absolutely necessary (4 vertices, 2 triangles)? If it needs the Quad, should the Texture buffer be fully drawn (0.0 to 1.0 for vertical and horizontal UVs), or only a percentage of it should, like the example below? Texture Buffer U: 0.0 to viewport.width/texturebuffer.width; Texture Buffer V: 0.0 to viewport.height/texturebuffer.height; Thanks!

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• XNA - Error while rendering a texture to a 2D render target via SpriteBatch

  - by Jared B

  I've got this simple code that uses SpriteBatch to draw a texture onto a RenderTarget2D: private void drawScene(GameTime g) { GraphicsDevice.Clear(skyColor); GraphicsDevice.SetRenderTarget(targetScene); drawSunAndMoon(); effect.Fog = true; GraphicsDevice.SetVertexBuffer(line); effect.MainEffect.CurrentTechnique.Passes[0].Apply(); GraphicsDevice.DrawPrimitives(PrimitiveType.TriangleStrip, 0, 2); GraphicsDevice.SetRenderTarget(null); SceneTexture = targetScene; } private void drawPostProcessing(GameTime g) { effect.SceneTexture = SceneTexture; GraphicsDevice.SetRenderTarget(targetBloom); spriteBatch.Begin(SpriteSortMode.Immediate, BlendState.Opaque, null, null, null); { if (Bloom) effect.BlurEffect.CurrentTechnique.Passes[0].Apply(); spriteBatch.Draw( targetScene, new Rectangle(0, 0, Window.ClientBounds.Width, Window.ClientBounds.Height), Color.White); } spriteBatch.End(); BloomTexture = targetBloom; GraphicsDevice.SetRenderTarget(null); } Both methods are called from my Draw(GameTime gameTime) function. First drawScene is called, then drawPostProcessing is called. The thing is, when I run this code I get an error on the spriteBatch.Draw call: The render target must not be set on the device when it is used as a texture. I already found the solution, which is to draw the actual render target (targetScene) to the texture so it doesn't create a reference to the loaded render target. However, to my knowledge, the only way of doing this is to write: GraphicsDevice.SetRenderTarget(outputTarget) SpriteBatch.Draw(inputTarget, ...) GraphicsDevice.SetRenderTarget(null) Which encounters the same exact problem I'm having right now. So, the question I'm asking is: how would I render inputTarget to outputTarget without reference issues?

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• How advanced are author-recognition methods?

  - by Nick Rtz

  From a written text by an author if a computer program analyses the text, how much can a computer program tell today about the author of some (long enough to be statistically significant) texts? Can the computer program even tell with "certainty" whether a man or a woman wrote this text based solely on the contents of the text and not an investigation such as ip numbers etc? I'm interested to know if there are algorithms in use for instance to automatically know whether an author was male or female or similar characteristics of an author that a computer program can decide based on analyses of the written text by an author. It could be useful to know before you read a message what a computer analyses says about the author, do you agree? If I for instance get a longer message from my wife that she has had an accident in Nigeria and the computer program says that with 99 % probability the message was written by a male author in his sixties of non-caucasian origin or likewise, or by somebody who is not my wife, then the computer program could help me investigate why a certain message differs in characteristics. There can also be other uses for instance just detecting outliers in a geographically or demographically bounded larger data set. Scam detection is the obvious use I'm thinking of but there could also be other uses. Are there already such programs that analyse a written text to tell something about the author based on word choice, use of pronouns, unusual language usage, or likewise?

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• How to store generated eigen faces for future face recognition?

  - by user3237134

  My code works in the following manner: 1.First, it obtains several images from the training set 2.After loading these images, we find the normalized faces,mean face and perform several calculation. 3.Next, we ask for the name of an image we want to recognize 4.We then project the input image into the eigenspace, and based on the difference from the eigenfaces we make a decision. 5.Depending on eigen weight vector for each input image we make clusters using kmeans command. Source code i tried: clear all close all clc % number of images on your training set. M=1200; %Chosen std and mean. %It can be any number that it is close to the std and mean of most of the images. um=60; ustd=32; %read and show images(bmp); S=[]; %img matrix for i=1:M str=strcat(int2str(i),'.jpg'); %concatenates two strings that form the name of the image eval('img=imread(str);'); [irow icol d]=size(img); % get the number of rows (N1) and columns (N2) temp=reshape(permute(img,[2,1,3]),[irow*icol,d]); %creates a (N1*N2)x1 matrix S=[S temp]; %X is a N1*N2xM matrix after finishing the sequence %this is our S end %Here we change the mean and std of all images. We normalize all images. %This is done to reduce the error due to lighting conditions. for i=1:size(S,2) temp=double(S(:,i)); m=mean(temp); st=std(temp); S(:,i)=(temp-m)*ustd/st+um; end %show normalized images for i=1:M str=strcat(int2str(i),'.jpg'); img=reshape(S(:,i),icol,irow); img=img'; end %mean image; m=mean(S,2); %obtains the mean of each row instead of each column tmimg=uint8(m); %converts to unsigned 8-bit integer. Values range from 0 to 255 img=reshape(tmimg,icol,irow); %takes the N1*N2x1 vector and creates a N2xN1 matrix img=img'; %creates a N1xN2 matrix by transposing the image. % Change image for manipulation dbx=[]; % A matrix for i=1:M temp=double(S(:,i)); dbx=[dbx temp]; end %Covariance matrix C=A'A, L=AA' A=dbx'; L=A*A'; % vv are the eigenvector for L % dd are the eigenvalue for both L=dbx'*dbx and C=dbx*dbx'; [vv dd]=eig(L); % Sort and eliminate those whose eigenvalue is zero v=[]; d=[]; for i=1:size(vv,2) if(dd(i,i)>1e-4) v=[v vv(:,i)]; d=[d dd(i,i)]; end end %sort, will return an ascending sequence [B index]=sort(d); ind=zeros(size(index)); dtemp=zeros(size(index)); vtemp=zeros(size(v)); len=length(index); for i=1:len dtemp(i)=B(len+1-i); ind(i)=len+1-index(i); vtemp(:,ind(i))=v(:,i); end d=dtemp; v=vtemp; %Normalization of eigenvectors for i=1:size(v,2) %access each column kk=v(:,i); temp=sqrt(sum(kk.^2)); v(:,i)=v(:,i)./temp; end %Eigenvectors of C matrix u=[]; for i=1:size(v,2) temp=sqrt(d(i)); u=[u (dbx*v(:,i))./temp]; end %Normalization of eigenvectors for i=1:size(u,2) kk=u(:,i); temp=sqrt(sum(kk.^2)); u(:,i)=u(:,i)./temp; end % show eigenfaces; for i=1:size(u,2) img=reshape(u(:,i),icol,irow); img=img'; img=histeq(img,255); end % Find the weight of each face in the training set. omega = []; for h=1:size(dbx,2) WW=[]; for i=1:size(u,2) t = u(:,i)'; WeightOfImage = dot(t,dbx(:,h)'); WW = [WW; WeightOfImage]; end omega = [omega WW]; end % Acquire new image % Note: the input image must have a bmp or jpg extension. % It should have the same size as the ones in your training set. % It should be placed on your desktop ed_min=[]; srcFiles = dir('G:\newdatabase\*.jpg'); % the folder in which ur images exists for b = 1 : length(srcFiles) filename = strcat('G:\newdatabase\',srcFiles(b).name); Imgdata = imread(filename); InputImage=Imgdata; InImage=reshape(permute((double(InputImage)),[2,1,3]),[irow*icol,1]); temp=InImage; me=mean(temp); st=std(temp); temp=(temp-me)*ustd/st+um; NormImage = temp; Difference = temp-m; p = []; aa=size(u,2); for i = 1:aa pare = dot(NormImage,u(:,i)); p = [p; pare]; end InImWeight = []; for i=1:size(u,2) t = u(:,i)'; WeightOfInputImage = dot(t,Difference'); InImWeight = [InImWeight; WeightOfInputImage]; end noe=numel(InImWeight); % Find Euclidean distance e=[]; for i=1:size(omega,2) q = omega(:,i); DiffWeight = InImWeight-q; mag = norm(DiffWeight); e = [e mag]; end ed_min=[ed_min MinimumValue]; theta=6.0e+03; %disp(e) z(b,:)=InImWeight; end IDX = kmeans(z,5); clustercount=accumarray(IDX, ones(size(IDX))); disp(clustercount); QUESTIONS: 1.It is working fine for M=50(i.e Training set contains 50 images) but not for M=1200(i.e Training set contains 1200 images).It is not showing any error.There is no output.I waited for 10 min still there is no output. I think it is going infinite loop.What is the problem?Where i was wrong? 2.Instead of running the training set everytime how eigen faces generated are stored so that stored eigen faces are used for future face recoginition for a new input image.So it reduces wastage of time.

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• Sentence Tree v/s Words List

  - by Rohit Jose

  I was recently tasked with building a Name Entity Recognizer as part of a project. The objective was to parse a given sentence and come up with all the possible combinations of the entities. One approach that was suggested was to keep a lookup table for all the know connector words like articles and conjunctions, remove them from the words list after splitting the sentence on the basis of the spaces. This would leave out the Name Entities in the sentence. A lookup is then done for these identified entities on another lookup table that associates them to the entity type, for example if the sentence was: Remember the Titans was a movie directed by Boaz Yakin, the possible outputs would be: {Remember the Titans,Movie} was {a movie,Movie} directed by {Boaz Yakin,director} {Remember the Titans,Movie} was a movie directed by Boaz Yakin {Remember the Titans,Movie} was {a movie,Movie} directed by Boaz Yakin {Remember the Titans,Movie} was a movie directed by {Boaz Yakin,director} Remember the Titans was {a movie,Movie} directed by Boaz Yakin Remember the Titans was {a movie,Movie} directed by {Boaz Yakin,director} Remember the Titans was a movie directed by {Boaz Yakin,director} Remember the {the titans,Movie,Sports Team} was {a movie,Movie} directed by {Boaz Yakin,director} Remember the {the titans,Movie,Sports Team} was a movie directed by Boaz Yakin Remember the {the titans,Movie,Sports Team} was {a movie,Movie} directed by Boaz Yakin Remember the {the titans,Movie,Sports Team} was a movie directed by {Boaz Yakin,director} The entity lookup table here would contain the following data: Remember the Titans=Movie a movie=Movie Boaz Yakin=director the Titans=Movie the Titans=Sports Team Another alternative logic that was put forward was to build a crude sentence tree that would contain the connector words in the lookup table as parent nodes and do a lookup in the entity table for the leaf node that might contain the entities. The tree that was built for the sentence above would be: The question I am faced with is the benefits of the two approaches, should I be going for the tree approach to represent the sentence parsing, since it provides a more semantic structure? Is there a better approach I should be going for solving it?

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