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  • SQL SERVER – Extending SQL Azure with Azure worker role – Guest Post by Paras Doshi

    - by pinaldave
    This is guest post by Paras Doshi. Paras Doshi is a research Intern at SolidQ.com and a Microsoft student partner. He is currently working in the domain of SQL Azure. SQL Azure is nothing but a SQL server in the cloud. SQL Azure provides benefits such as on demand rapid provisioning, cost-effective scalability, high availability and reduced management overhead. To see an introduction on SQL Azure, check out the post by Pinal here In this article, we are going to discuss how to extend SQL Azure with the Azure worker role. In other words, we will attempt to write a custom code and host it in the Azure worker role; the aim is to add some features that are not available with SQL Azure currently or features that need to be customized for flexibility. This way we extend the SQL Azure capability by building some solutions that run on Azure as worker roles. To understand Azure worker role, think of it as a windows service in cloud. Azure worker role can perform background processes, and to handle processes such as synchronization and backup, it becomes our ideal tool. First, we will focus on writing a worker role code that synchronizes SQL Azure databases. Before we do so, let’s see some scenarios in which synchronization between SQL Azure databases is beneficial: scaling out access over multiple databases enables us to handle workload efficiently As of now, SQL Azure database can be hosted in one of any six datacenters. By synchronizing databases located in different data centers, one can extend the data by enabling access to geographically distributed data Let us see some scenarios in which SQL server to SQL Azure database synchronization is beneficial To backup SQL Azure database on local infrastructure Rather than investing in local infrastructure for increased workloads, such workloads could be handled by cloud Ability to extend data to different datacenters located across the world to enable efficient data access from remote locations Now, let us develop cloud-based app that synchronizes SQL Azure databases. For an Introduction to developing cloud based apps, click here Now, in this article, I aim to provide a bird’s eye view of how a code that synchronizes SQL Azure databases look like and then list resources that can help you develop the solution from scratch. Now, if you newly add a worker role to the cloud-based project, this is how the code will look like. (Note: I have added comments to the skeleton code to point out the modifications that will be required in the code to carry out the SQL Azure synchronization. Note the placement of Setup() and Sync() function.) Click here (http://parasdoshi1989.files.wordpress.com/2011/06/code-snippet-1-for-extending-sql-azure-with-azure-worker-role1.pdf ) Enabling SQL Azure databases synchronization through sync framework is a two-step process. In the first step, the database is provisioned and sync framework creates tracking tables, stored procedures, triggers, and tables to store metadata to enable synchronization. This is one time step. The code for the same is put in the setup() function which is called once when the worker role starts. Now, the second step is continuous (or on demand) synchronization of SQL Azure databases by propagating changes between databases. This is done on a continuous basis by calling the sync() function in the while loop. The code logic to synchronize changes between SQL Azure databases should be put in the sync() function. Discussing the coding part step by step is out of the scope of this article. Therefore, let me suggest you a resource, which is given here. Also, note that before you start developing the code, you will need to install SYNC framework 2.1 SDK (download here). Further, you will reference some libraries before you start coding. Details regarding the same are available in the article that I just pointed to. You will be charged for data transfers if the databases are not in the same datacenter. For pricing information, go here Currently, a tool named DATA SYNC, which is built on top of sync framework, is available in CTP that allows SQL Azure <-> SQL server and SQL Azure <-> SQL Azure synchronization (without writing single line of code); however, in some cases, the custom code shown in this blogpost provides flexibility that is not available with Data SYNC. For instance, filtering is not supported in the SQL Azure DATA SYNC CTP2; if you wish to have such a functionality now, then you have the option of developing a custom code using SYNC Framework. Now, this code can be easily extended to synchronize at some schedule. Let us say we want the databases to get synchronized every day at 10:00 pm. This is what the code will look like now: (http://parasdoshi1989.files.wordpress.com/2011/06/code-snippet-2-for-extending-sql-azure-with-azure-worker-role.pdf) Don’t you think that by writing such a code, we are imitating the functionality provided by the SQL server agent for a SQL server? Think about it. We are scheduling our administrative task by writing custom code – in other words, we have developed a “Light weight SQL server agent for SQL Azure!” Since the SQL server agent is not currently available in cloud, we have developed a solution that enables us to schedule tasks, and thus we have extended SQL Azure with the Azure worker role! Now if you wish to track jobs, you can do so by storing this data in SQL Azure (or Azure tables). The reason is that Windows Azure is a stateless platform, and we will need to store the state of the job ourselves and the choice that you have is SQL Azure or Azure tables. Note that this solution requires custom code and also it is not UI driven; however, for now, it can act as a temporary solution until SQL server agent is made available in the cloud. Moreover, this solution does not encompass functionalities that a SQL server agent provides, but it does open up an interesting avenue to schedule some of the tasks such as backup and synchronization of SQL Azure databases by writing some custom code in the Azure worker role. Now, let us see one more possibility – i.e., running BCP through a worker role in Azure-hosted services and then uploading the backup files either locally or on blobs. If you upload it locally, then consider the data transfer cost. If you upload it to blobs residing in the same datacenter, then no transfer cost applies but the cost on blob size applies. So, before choosing the option, you need to evaluate your preferences keeping the cost associated with each option in mind. In this article, I have shown that Azure worker role solution could be developed to synchronize SQL Azure databases. Moreover, a light-weight SQL server agent for SQL Azure can be developed. Also we discussed the possibility of running BCP through a worker role in Azure-hosted services for backing up our precious SQL Azure data. Thus, we can extend SQL Azure with the Azure worker role. But remember: you will be charged for running Azure worker roles. So at the end of the day, you need to ask – am I willing to build a custom code and pay money to achieve this functionality? I hope you found this blog post interesting. If you have any questions/feedback, you can comment below or you can mail me at Paras[at]student-partners[dot]com Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Azure, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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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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  • SQL SERVER – A Quick Look at Logging and Ideas around Logging

    - by pinaldave
    This blog post is written in response to the T-SQL Tuesday post on Logging. When someone talks about logging, personally I get lots of ideas about it. I have seen logging as a very generic term. Let me ask you this question first before I continue writing about logging. What is the first thing comes to your mind when you hear word “Logging”? Now ask the same question to the guy standing next to you. I am pretty confident that you will get  a different answer from different people. I decided to do this activity and asked 5 SQL Server person the same question. Question: What is the first thing comes to your mind when you hear the word “Logging”? Strange enough I got a different answer every single time. Let me just list what answer I got from my friends. Let us go over them one by one. Output Clause The very first person replied output clause. Pretty interesting answer to start with. I see what exactly he was thinking. SQL Server 2005 has introduced a new OUTPUT clause. OUTPUT clause has access to inserted and deleted tables (virtual tables) just like triggers. OUTPUT clause can be used to return values to client clause. OUTPUT clause can be used with INSERT, UPDATE, or DELETE to identify the actual rows affected by these statements. Here are some references for Output Clause: OUTPUT Clause Example and Explanation with INSERT, UPDATE, DELETE Reasons for Using Output Clause – Quiz Tips from the SQL Joes 2 Pros Development Series – Output Clause in Simple Examples Error Logs I was expecting someone to mention Error logs when it is about logging. The error log is the most looked place when there is any error either with the application or there is an error with the operating system. I have kept the policy to check my server’s error log every day. The reason is simple – enough time in my career I have figured out that when I am looking at error logs I find something which I was not expecting. There are cases, when I noticed errors in the error log and I fixed them before end user notices it. Other common practices I always tell my DBA friends to do is that when any error happens they should find relevant entries in the error logs and document the same. It is quite possible that they will see the same error in the error log  and able to fix the error based on the knowledge base which they have created. There can be many different kinds of error log files exists in SQL Server as well – 1) SQL Server Error Logs 2) Windows Event Log 3) SQL Server Agent Log 4) SQL Server Profile Log 5) SQL Server Setup Log etc. Here are some references for Error Logs: Recycle Error Log – Create New Log file without Server Restart SQL Error Messages Change Data Capture I got surprised with this answer. I think more than the answer I was surprised by the person who had answered me this one. I always thought he was expert in HTML, JavaScript but I guess, one should never assume about others. Indeed one of the cool logging feature is Change Data Capture. Change Data Capture records INSERTs, UPDATEs, and DELETEs applied to SQL Server tables, and makes a record available of what changed, where, and when, in simple relational ‘change tables’ rather than in an esoteric chopped salad of XML. These change tables contain columns that reflect the column structure of the source table you have chosen to track, along with the metadata needed to understand the changes that have been made. Here are some references for Change Data Capture: Introduction to Change Data Capture (CDC) in SQL Server 2008 Tuning the Performance of Change Data Capture in SQL Server 2008 Download Script of Change Data Capture (CDC) CDC and TRUNCATE – Cannot truncate table because it is published for replication or enabled for Change Data Capture Dynamic Management View (DMV) I like this answer. If asked I would have not come up with DMV right away but in the spirit of the original question, I think DMV does log the data. DMV logs or stores or records the various data and activity on the SQL Server. Dynamic management views return server state information that can be used to monitor the health of a server instance, diagnose problems, and tune performance. One can get plethero of information from DMVs – High Availability Status, Query Executions Details, SQL Server Resources Status etc. Here are some references for Dynamic Management View (DMV): SQL SERVER – Denali – DMV Enhancement – sys.dm_exec_query_stats – New Columns DMV – sys.dm_os_windows_info – Information about Operating System DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28 DMV sys.dm_exec_describe_first_result_set_for_object – Describes the First Result Metadata for the Module Transaction Log Impact Detection Using DMV – dm_tran_database_transactions Log Files I almost flipped with this final answer from my friend. This should be probably the first answer. Yes, indeed log file logs the SQL Server activities. One can write infinite things about log file. SQL Server uses log file with the extension .ldf to manage transactions and maintain database integrity. Log file ensures that valid data is written out to database and system is in a consistent state. Log files are extremely useful in case of the database failures as with the help of full backup file database can be brought in the desired state (point in time recovery is also possible). SQL Server database has three recovery models – 1) Simple, 2) Full and 3) Bulk Logged. Each of the model uses the .ldf file for performing various activities. It is very important to take the backup of the log files (along with full backup) as one never knows when backup of the log file come into the action and save the day! How to Stop Growing Log File Too Big Reduce the Virtual Log Files (VLFs) from LDF file Log File Growing for Model Database – model Database Log File Grew Too Big master Database Log File Grew Too Big SHRINKFILE and TRUNCATE Log File in SQL Server 2008 Can I just say I loved this month’s T-SQL Tuesday Question. It really provoked very interesting conversation around me. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Using expressor Composite Types to Enforce Business Rules

    - by pinaldave
    One of the features that distinguish the expressor Data Integration Platform from other products in the data integration space is its concept of composite types, which provide an effective and easily reusable way to clearly define the structure and characteristics of data within your application.  An important feature of the composite type approach is that it allows you to easily adjust the content of a record to its ultimate purpose.  For example, a record used to update a row in a database table is easily defined to include only the minimum set of columns, that is, a value for the key column and values for only those columns that need to be updated. Much like a class in higher level programming languages, you can also use the composite type as a way to enforce business rules onto your data by encapsulating a datum’s name, data type, and constraints (for example, maximum, minimum, or acceptable values) as a single entity, which ensures that your data can not assume an invalid value.  To what extent you use this functionality is a decision you make when designing your application; the expressor design paradigm does not force this approach on you. Let’s take a look at how these features are used.  Suppose you want to create a group of applications that maintain the employee table in your human resources database. Your table might have a structure similar to the HumanResources.Employee table in the AdventureWorks database.  This table includes two columns, EmployeID and rowguid, that are maintained by the relational database management system; you cannot provide values for these columns when inserting new rows into the table. Additionally, there are columns such as VacationHours and SickLeaveHours that you might choose to update for all employees on a monthly basis, which justifies creation of a dedicated application. By creating distinct composite types for the read, insert and update operations against this table, you can more easily manage this table’s content. When developing this application within expressor Studio, your first task is to create a schema artifact for the database table.  This process is completely driven by a wizard, only requiring that you select the desired database schema and table.  The resulting schema artifact defines the mapping of result set records to a record within the expressor data integration application.  The structure of the record within the expressor application is a composite type that is given the default name CompositeType1.  As you can see in the following figure, all columns from the table are included in the result set and mapped to an identically named attribute in the default composite type. If you are developing an application that needs to read this table, perhaps to prepare a year-end report of employees by department, you would probably not be interested in the data in the rowguid and ModifiedDate columns.  A typical approach would be to drop this unwanted data in a downstream operator.  But using an alternative composite type provides a better approach in which the unwanted data never enters your application. While working in expressor  Studio’s schema editor, simply create a second composite type within the same schema artifact, which you could name ReadTable, and remove the attributes corresponding to the unwanted columns. The value of an alternative composite type is even more apparent when you want to insert into or update the table.  In the composite type used to insert rows, remove the attributes corresponding to the EmployeeID primary key and rowguid uniqueidentifier columns since these values are provided by the relational database management system. And to update just the VacationHours and SickLeaveHours columns, use a composite type that includes only the attributes corresponding to the EmployeeID, VacationHours, SickLeaveHours and ModifiedDate columns. By specifying this schema artifact and composite type in a Write Table operator, your upstream application need only deal with the four required attributes and there is no risk of unintentionally overwriting a value in a column that does not need to be updated. Now, what about the option to use the composite type to enforce business rules?  If you review the composition of the default composite type CompositeType1, you will note that the constraints defined for many of the attributes mirror the table column specifications.  For example, the maximum number of characters in the NationaIDNumber, LoginID and Title attributes is equivalent to the maximum width of the target column, and the size of the MaritalStatus and Gender attributes is limited to a single character as required by the table column definition.  If your application code leads to a violation of these constraints, an error will be raised.  The expressor design paradigm then allows you to handle the error in a way suitable for your application.  For example, a string value could be truncated or a numeric value could be rounded. Moreover, you have the option of specifying additional constraints that support business rules unrelated to the table definition. Let’s assume that the only acceptable values for marital status are S, M, and D.  Within the schema editor, double-click on the MaritalStatus attribute to open the Edit Attribute window.  Then click the Allowed Values checkbox and enter the acceptable values into the Constraint Value text box. The schema editor is updated accordingly. There is one more option that the expressor semantic type paradigm supports.  Since the MaritalStatus attribute now clearly specifies how this type of information should be represented (a single character limited to S, M or D), you can convert this attribute definition into a shared type, which will allow you to quickly incorporate this definition into another composite type or into the description of an output record from a transform operator. Again, double-click on the MaritalStatus attribute and in the Edit Attribute window, click Convert, which opens the Share Local Semantic Type window that you use to name this shared type.  There’s no requirement that you give the shared type the same name as the attribute from which it was derived.  You should supply a name that makes it obvious what the shared type represents. In this posting, I’ve overviewed the expressor semantic type paradigm and shown how it can be used to make your application development process more productive.  The beauty of this feature is that you choose when and to what extent you utilize the functionality, but I’m certain that if you opt to follow this approach your efforts will become more efficient and your work will progress more quickly.  As always, I encourage you to download and evaluate expressor Studio for your current and future data integration needs. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: CodeProject, Pinal Dave, PostADay, SQL, SQL Authority, SQL Documentation, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Long polling using Spring MVC 3.2M1

    - by Dangling Piyush
    I want to implement Long polling Using Spring 3.2 DeferredResult. I got only this tutorial available on internet Long Polling with Spring MVC. It's a good tutorial but I could not understand it fully because I am pretty new to Spring MVC. So if anyone could explain me how to use DeferredResult for implenting long polling efficiently (server-side code) I would be grateful. I have posted this question before on Stack Overflow but got zero response so I thought of reposting it here again.

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  • Writing long line support for text editor

    - by Mathematician82
    I know that some some text editors have problems to show long lines https://bugzilla.gnome.org/show_bug.cgi?id=172099 . What is the best way to fix the bug or are they equally well? Modify the GTK+ source code and add a support for long lines. Modify the text editor source code such that it does not use GTK+ if it meets a long line. Split the long lines into part (maybe by cut on the Bash ) I'm just a junior programmer so I don't know what people does when they meet a bug that is on the library they use.

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  • Convert all short (8.3) paths to long paths in the registry?

    - by Mehrdad
    Running FSUtil 8Dot3Name Scan /v /s C: gives you a list of potential 8.3 paths in the registry that are referring to your file system, but is there any tool that can actually convert those paths to long paths in the registry? I do understand this could break some programs, but I have backups so I'd be willing to give it a try. (I tried to make a tool like this myself, but it's harder than it looks, because of false positives and all the varieties of ways the path could be embedded.)

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  • SQLAuthority Book Review – DBA Survivor: Become a Rock Star DBA

    - by pinaldave
    DBA Survivor: Become a Rock Star DBA – Thomas LaRock Link to Amazon Link to Flipkart First of all, I thank all my readers when I wrote that I could not get this book in any local book stores, because they offered me to send a copy of this good book. A very special mention goes to Sripada and Jayesh for they gave so much effort in finding my home address and sending me the hard copy. Before, I did not have the copy of the book, but now I have two of it already! It surprises me how my readers were able to find my home address, which I have not publicly shared. Quick Review: This is indeed a one easy-to-read and fun book. We all work day and night with technology yet we should not forget to show our love and care for our family at home. For our souls that starve for peace and guidance, this one book is the “it” book for all the technology enthusiasts. Though this book was specifically written for DBAs, the reach is not limited to DBAs only because the lessons incorporated in it actually applies to all. This is one of the most motivating technical books I have read. Detailed Review: Let us go over a few questions first: Who wants to be as famous as rockstars in the field of Database Administration? How can one learn what it takes to become a top notch software developer? If you are a beginner in your field, how will you go to next level? Your boss may be very kind or like Dilbert’s Boss, what will you do? How do you keep growing when Eco-system around you does not support you? You are almost at top but there is someone else at the TOP, what do you do and how do you avoid office politics? As a database developer what should be your basic responsibility? and many more… I was able to completely read book in one sitting and I loved it. Before I continue with my opinion, I want to echo the opinion of Kevin Kline who has written the Forward of the book. He has truly suggested that “You hold in your hands a collection of insights and wisdom on the topic of database administration gained through many years of hard-won experience, long nights of study, and direct mentorship under some of the industry’s most talented database professionals and information technology (IT) experts.” Today, IT field is getting bigger and better, while talking about terabytes of the database becomes “more” normal every single day. The gods and demigods of database professionals are taking care of these large scale databases and are carefully maintaining them. In this world, there are only a few beginnings on the first step. There are many experts in different technology fields who are asked to address the issues with databases. There is YOU and ME, who is just new to this work. So we ask ourselves WHERE to begin and HOW to begin. We adore and follow the religion of our rockstars, but oftentimes we really have no idea about their background and their struggles. Every rockstar has his success story which needs to be digested before learning his tricks and tips. This book starts with the same note and teaches the two most important lessons for anybody who wants to be a DBA Rockstar –  to focus on their single goal of learning and to excel the technology. The story starts with three simple guidelines – Get Prepared, Get Trained, Get Certified. Once a person learns the skills, and then, it would be about time that he needs to enrich or to improve those skills you have learned. I am sure that the right opportunity will come finding themselves and they will not have to go run behind it. However, the real challenge for any person is the first day or first week. A new employee, no matter how much experienced he is, sometimes has no clue about what should one do at new job. Chapter 2 and chapter 3 precisely talk about what one should do as soon as the new job begins. It is also written with keeping the fact in focus that each job can be very much different but there are few infrastructure setups and programming concepts are the same. Learning basics of database was really interesting. I like to focus on the roots of any technology. It is important to understand the structure of the database before suggesting what indexes needs to be created, the same way this book covers the most essential knowledge one must learn by most database developers. I think the title of the fourth chapter is my favorite sentence in this book. I can see that I will be saying this again and again in the future – “A Development Server Is a Production Server to a Developer“. I have worked in the software industry for almost 8 years now and I have seen so many developers sitting on their chairs and waiting for instructions from their lead about how to improve the code or what to do the next. When I talk to them, I suggest that the experiment with their server and try various techniques. I think they all should understand that for them, a development server is their production server and needs to pay proper attention to the code from the beginning. There should be NO any inappropriate code from the beginning. One has to fully focus and give their best, if they are not sure they should ask but should do something and stay active. Chapter 5 and 6 talks about two essential skills for any developer and database administration – what are the ethics of developers when they are working with production server and how to support software which is running on the production server. I have met many people who know the theory by heart but when put in front of keyboard they do not know where to start. The first thing they do opening the browser and searching online, instead of opening SQL Server Management Studio. This can very well happen to anybody who is experienced as well. Chapter 5 and 6 addresses that situation as well includes the handy scripts which can solve almost all the basic trouble shooting issues. “Where’s the Buffet?” By far, this is the best chapter in this book. If you have ever met me, you would know that I love food. I think after reading this chapter, I felt Thomas has written this just keeping me in mind. I think there will be many other people who feel the same way, too. Even my wife who read this chapter thought this was specifically written for me. I will not talk any more about this chapter as this is one must read chapter. And of course this is about real ‘FOOD‘. I am an SQL Server Trainer and Consultant and I totally agree with the point made in the chapter 8 of this book. Yes, it says here that what is necessary to train employees and people. Millions of dollars worth the labor is continuously done in the world which has faults and incorrect. Once something goes wrong, very expensive consultant comes in and fixes the problem. This whole cycle which can be stopped and improved if proper training is done. There is plenty of free trainings available as well, if one cannot afford paid training. “Connect. Learn. Share” – I think this is a great summary and bird’s eye view of this book. Networking is the key. Everything which is discussed in this book can be taken to next level if one properly uses this tips and continuously grow with it. Connecting with others, helping learn each other and building the good knowledge sharing environment should be the goal of everyone. Before I end the review I want to share a real experience. I have personally met one DBA who has worked in a single department in a company for so long that when he was put in a different department in his company due to closing that department, he could not adjust and quit the job despite the same people and company around him. Adjusting in the new environment gets much tougher as one person gets more and more experienced. This book precisely addresses the same issue along with their solutions. I just cannot stop comparing the book with my personal journey. I found so many things which are coincidently in the book is written as how we developer and DBA think. I must express special thanks to Thomas for taking time in his personal life and write this book for us. This book is indeed a book for everybody who wants to grow healthy in the tough and competitive environment. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Book Review, SQLAuthority News, SQLServer, T SQL, Technology

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  • SQL SERVER – Guest Post – Jonathan Kehayias – Wait Type – Day 16 of 28

    - by pinaldave
    Jonathan Kehayias (Blog | Twitter) is a MCITP Database Administrator and Developer, who got started in SQL Server in 2004 as a database developer and report writer in the natural gas industry. After spending two and a half years working in TSQL, in late 2006, he transitioned to the role of SQL Database Administrator. His primary passion is performance tuning, where he frequently rewrites queries for better performance and performs in depth analysis of index implementation and usage. Jonathan blogs regularly on SQLBlog, and was a coauthor of Professional SQL Server 2008 Internals and Troubleshooting. On a personal note, I think Jonathan is extremely positive person. In every conversation with him I have found that he is always eager to help and encourage. Every time he finds something needs to be approved, he has contacted me without hesitation and guided me to improve, change and learn. During all the time, he has not lost his focus to help larger community. I am honored that he has accepted to provide his views on complex subject of Wait Types and Queues. Currently I am reading his series on Extended Events. Here is the guest blog post by Jonathan: SQL Server troubleshooting is all about correlating related pieces of information together to indentify where exactly the root cause of a problem lies. In my daily work as a DBA, I generally get phone calls like, “So and so application is slow, what’s wrong with the SQL Server.” One of the funny things about the letters DBA is that they go so well with Default Blame Acceptor, and I really wish that I knew exactly who the first person was that pointed that out to me, because it really fits at times. A lot of times when I get this call, the problem isn’t related to SQL Server at all, but every now and then in my initial quick checks, something pops up that makes me start looking at things further. The SQL Server is slow, we see a number of tasks waiting on ASYNC_IO_COMPLETION, IO_COMPLETION, or PAGEIOLATCH_* waits in sys.dm_exec_requests and sys.dm_exec_waiting_tasks. These are also some of the highest wait types in sys.dm_os_wait_stats for the server, so it would appear that we have a disk I/O bottleneck on the machine. A quick check of sys.dm_io_virtual_file_stats() and tempdb shows a high write stall rate, while our user databases show high read stall rates on the data files. A quick check of some performance counters and Page Life Expectancy on the server is bouncing up and down in the 50-150 range, the Free Page counter consistently hits zero, and the Free List Stalls/sec counter keeps jumping over 10, but Buffer Cache Hit Ratio is 98-99%. Where exactly is the problem? In this case, which happens to be based on a real scenario I faced a few years back, the problem may not be a disk bottleneck at all; it may very well be a memory pressure issue on the server. A quick check of the system spec’s and it is a dual duo core server with 8GB RAM running SQL Server 2005 SP1 x64 on Windows Server 2003 R2 x64. Max Server memory is configured at 6GB and we think that this should be enough to handle the workload; or is it? This is a unique scenario because there are a couple of things happening inside of this system, and they all relate to what the root cause of the performance problem is on the system. If we were to query sys.dm_exec_query_stats for the TOP 10 queries, by max_physical_reads, max_logical_reads, and max_worker_time, we may be able to find some queries that were using excessive I/O and possibly CPU against the system in their worst single execution. We can also CROSS APPLY to sys.dm_exec_sql_text() and see the statement text, and also CROSS APPLY sys.dm_exec_query_plan() to get the execution plan stored in cache. Ok, quick check, the plans are pretty big, I see some large index seeks, that estimate 2.8GB of data movement between operators, but everything looks like it is optimized the best it can be. Nothing really stands out in the code, and the indexing looks correct, and I should have enough memory to handle this in cache, so it must be a disk I/O problem right? Not exactly! If we were to look at how much memory the plan cache is taking by querying sys.dm_os_memory_clerks for the CACHESTORE_SQLCP and CACHESTORE_OBJCP clerks we might be surprised at what we find. In SQL Server 2005 RTM and SP1, the plan cache was allowed to take up to 75% of the memory under 8GB. I’ll give you a second to go back and read that again. Yes, you read it correctly, it says 75% of the memory under 8GB, but you don’t have to take my word for it, you can validate this by reading Changes in Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2. In this scenario the application uses an entirely adhoc workload against SQL Server and this leads to plan cache bloat, and up to 4.5GB of our 6GB of memory for SQL can be consumed by the plan cache in SQL Server 2005 SP1. This in turn reduces the size of the buffer cache to just 1.5GB, causing our 2.8GB of data movement in this expensive plan to cause complete flushing of the buffer cache, not just once initially, but then another time during the queries execution, resulting in excessive physical I/O from disk. Keep in mind that this is not the only query executing at the time this occurs. Remember the output of sys.dm_io_virtual_file_stats() showed high read stalls on the data files for our user databases versus higher write stalls for tempdb? The memory pressure is also forcing heavier use of tempdb to handle sorting and hashing in the environment as well. The real clue here is the Memory counters for the instance; Page Life Expectancy, Free List Pages, and Free List Stalls/sec. The fact that Page Life Expectancy is fluctuating between 50 and 150 constantly is a sign that the buffer cache is experiencing constant churn of data, once every minute to two and a half minutes. If you add to the Page Life Expectancy counter, the consistent bottoming out of Free List Pages along with Free List Stalls/sec consistently spiking over 10, and you have the perfect memory pressure scenario. All of sudden it may not be that our disk subsystem is the problem, but is instead an innocent bystander and victim. Side Note: The Page Life Expectancy counter dropping briefly and then returning to normal operating values intermittently is not necessarily a sign that the server is under memory pressure. The Books Online and a number of other references will tell you that this counter should remain on average above 300 which is the time in seconds a page will remain in cache before being flushed or aged out. This number, which equates to just five minutes, is incredibly low for modern systems and most published documents pre-date the predominance of 64 bit computing and easy availability to larger amounts of memory in SQL Servers. As food for thought, consider that my personal laptop has more memory in it than most SQL Servers did at the time those numbers were posted. I would argue that today, a system churning the buffer cache every five minutes is in need of some serious tuning or a hardware upgrade. Back to our problem and its investigation: There are two things really wrong with this server; first the plan cache is excessively consuming memory and bloated in size and we need to look at that and second we need to evaluate upgrading the memory to accommodate the workload being performed. In the case of the server I was working on there were a lot of single use plans found in sys.dm_exec_cached_plans (where usecounts=1). Single use plans waste space in the plan cache, especially when they are adhoc plans for statements that had concatenated filter criteria that is not likely to reoccur with any frequency.  SQL Server 2005 doesn’t natively have a way to evict a single plan from cache like SQL Server 2008 does, but MVP Kalen Delaney, showed a hack to evict a single plan by creating a plan guide for the statement and then dropping that plan guide in her blog post Geek City: Clearing a Single Plan from Cache. We could put that hack in place in a job to automate cleaning out all the single use plans periodically, minimizing the size of the plan cache, but a better solution would be to fix the application so that it uses proper parameterized calls to the database. You didn’t write the app, and you can’t change its design? Ok, well you could try to force parameterization to occur by creating and keeping plan guides in place, or we can try forcing parameterization at the database level by using ALTER DATABASE <dbname> SET PARAMETERIZATION FORCED and that might help. If neither of these help, we could periodically dump the plan cache for that database, as discussed as being a problem in Kalen’s blog post referenced above; not an ideal scenario. The other option is to increase the memory on the server to 16GB or 32GB, if the hardware allows it, which will increase the size of the plan cache as well as the buffer cache. In SQL Server 2005 SP1, on a system with 16GB of memory, if we set max server memory to 14GB the plan cache could use at most 9GB  [(8GB*.75)+(6GB*.5)=(6+3)=9GB], leaving 5GB for the buffer cache.  If we went to 32GB of memory and set max server memory to 28GB, the plan cache could use at most 16GB [(8*.75)+(20*.5)=(6+10)=16GB], leaving 12GB for the buffer cache. Thankfully we have SQL Server 2005 Service Pack 2, 3, and 4 these days which include the changes in plan cache sizing discussed in the Changes to Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2 blog post. In real life, when I was troubleshooting this problem, I spent a week trying to chase down the cause of the disk I/O bottleneck with our Server Admin and SAN Admin, and there wasn’t much that could be done immediately there, so I finally asked if we could increase the memory on the server to 16GB, which did fix the problem. It wasn’t until I had this same problem occur on another system that I actually figured out how to really troubleshoot this down to the root cause.  I couldn’t believe the size of the plan cache on the server with 16GB of memory when I actually learned about this and went back to look at it. SQL Server is constantly telling a story to anyone that will listen. As the DBA, you have to sit back and listen to all that it’s telling you and then evaluate the big picture and how all the data you can gather from SQL about performance relate to each other. One of the greatest tools out there is actually a free in the form of Diagnostic Scripts for SQL Server 2005 and 2008, created by MVP Glenn Alan Berry. Glenn’s scripts collect a majority of the information that SQL has to offer for rapid troubleshooting of problems, and he includes a lot of notes about what the outputs of each individual query might be telling you. When I read Pinal’s blog post SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28, I noticed that he referenced Checking Memory Related Performance Counters in his post, but there was no real explanation about why checking memory counters is so important when looking at an I/O related wait type. I thought I’d chat with him briefly on Google Talk/Twitter DM and point this out, and offer a couple of other points I noted, so that he could add the information to his blog post if he found it useful.  Instead he asked that I write a guest blog for this. I am honored to be a guest blogger, and to be able to share this kind of information with the community. The information contained in this blog post is a glimpse at how I do troubleshooting almost every day of the week in my own environment. SQL Server provides us with a lot of information about how it is running, and where it may be having problems, it is up to us to play detective and find out how all that information comes together to tell us what’s really the problem. This blog post is written by Jonathan Kehayias (Blog | Twitter). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: MVP, 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

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  • SQL SERVER – Import CSV into Database – Transferring File Content into a Database Table using CSVexpress

    - by pinaldave
    One of the most common data integration tasks I run into is a desire to move data from a file into a database table.  Generally the user is familiar with his data, the structure of the file, and the database table, but is unfamiliar with data integration tools and therefore views this task as something that is difficult.  What these users really need is a point and click approach that minimizes the learning curve for the data integration tool.  This is what CSVexpress (www.CSVexpress.com) is all about!  It is based on expressor Studio, a data integration tool I’ve been reviewing over the last several months. With CSVexpress, moving data between data sources can be as simple as providing the database connection details, describing the structure of the incoming and outgoing data and then connecting two pre-programmed operators.   There’s no need to learn the intricacies of the data integration tool or to write code.  Let’s look at an example. Suppose I have a comma separated value data file with data similar to the following, which is a listing of terminated employees that includes their hiring and termination date, department, job description, and final salary. EMP_ID,STRT_DATE,END_DATE,JOB_ID,DEPT_ID,SALARY 102,13-JAN-93,24-JUL-98 17:00,Programmer,60,"$85,000" 101,21-SEP-89,27-OCT-93 17:00,Account Representative,110,"$65,000" 103,28-OCT-93,15-MAR-97 17:00,Account Manager,110,"$75,000" 304,17-FEB-96,19-DEC-99 17:00,Marketing,20,"$45,000" 333,24-MAR-98,31-DEC-99 17:00,Data Entry Clerk,50,"$35,000" 100,17-SEP-87,17-JUN-93 17:00,Administrative Assistant,90,"$40,000" 334,24-MAR-98,31-DEC-98 17:00,Sales Representative,80,"$40,000" 400,01-JAN-99,31-DEC-99 17:00,Sales Manager,80,"$55,000" Notice the concise format used for the date values, the fact that the termination date includes both date and time information, and that the salary is clearly identified as money by the dollar sign and digit grouping.  In moving this data to a database table I want to express the dates using a format that includes the century since it’s obvious that this listing could include employees who left the company in both the 20th and 21st centuries, and I want the salary to be stored as a decimal value without the currency symbol and grouping character.  Most data integration tools would require coding within a transformation operation to effect these changes, but not expressor Studio.  Directives for these modifications are included in the description of the incoming data. Besides starting the expressor Studio tool and opening a project, the first step is to create connection artifacts, which describe to expressor where data is stored.  For this example, two connection artifacts are required: a file connection, which encapsulates the file system location of my file; and a database connection, which encapsulates the database connection information.  With expressor Studio, I use wizards to create these artifacts. First click New Connection > File Connection in the Home tab of expressor Studio’s ribbon bar, which starts the File Connection wizard.  In the first window, I enter the path to the directory that contains the input file.  Note that the file connection artifact only specifies the file system location, not the name of the file. Then I click Next and enter a meaningful name for this connection artifact; clicking Finish closes the wizard and saves the artifact. To create the Database Connection artifact, I must know the location of, or instance name, of the target database and have the credentials of an account with sufficient privileges to write to the target table.  To use expressor Studio’s features to the fullest, this account should also have the authority to create a table. I click the New Connection > Database Connection in the Home tab of expressor Studio’s ribbon bar, which starts the Database Connection wizard.  expressor Studio includes high-performance drivers for many relational database management systems, so I can simply make a selection from the “Supplied database drivers” drop down control.  If my desired RDBMS isn’t listed, I can optionally use an existing ODBC DSN by selecting the “Existing DSN” radio button. In the following window, I enter the connection details.  With Microsoft SQL Server, I may choose to use Windows Authentication rather than rather than account credentials.  After clicking Next, I enter a meaningful name for this connection artifact and clicking Finish closes the wizard and saves the artifact. Now I create a schema artifact, which describes the structure of the file data.  When expressor reads a file, all data fields are typed as strings.  In some use cases this may be exactly what is needed and there is no need to edit the schema artifact.  But in this example, editing the schema artifact will be used to specify how the data should be transformed; that is, reformat the dates to include century designations, change the employee and job ID’s to integers, and convert the salary to a decimal value. Again a wizard is used to create the schema artifact.  I click New Schema > Delimited Schema in the Home tab of expressor Studio’s ribbon bar, which starts the Database Connection wizard.  In the first window, I click Get Data from File, which then displays a listing of the file connections in the project.  When I click on the file connection I previously created, a browse window opens to this file system location; I then select the file and click Open, which imports 10 lines from the file into the wizard. I now view the file’s content and confirm that the appropriate delimiter characters are selected in the “Field Delimiter” and “Record Delimiter” drop down controls; then I click Next. Since the input file includes a header row, I can easily indicate that fields in the file should be identified through the corresponding header value by clicking “Set All Names from Selected Row. “ Alternatively, I could enter a different identifier into the Field Details > Name text box.  I click Next and enter a meaningful name for this schema artifact; clicking Finish closes the wizard and saves the artifact. Now I open the schema artifact in the schema editor.  When I first view the schema’s content, I note that the types of all attributes in the Semantic Type (the right-hand panel) are strings and that the attribute names are the same as the field names in the data file.  To change an attribute’s name and type, I highlight the attribute and click Edit in the Attributes grouping on the Schema > Edit tab of the editor’s ribbon bar.  This opens the Edit Attribute window; I can change the attribute name and select the desired type from the “Data type” drop down control.  In this example, I change the name of each attribute to the name of the corresponding database table column (EmployeeID, StartingDate, TerminationDate, JobDescription, DepartmentID, and FinalSalary).  Then for the EmployeeID and DepartmentID attributes, I select Integer as the data type, for the StartingDate and TerminationDate attributes, I select Datetime as the data type, and for the FinalSalary attribute, I select the Decimal type. But I can do much more in the schema editor.  For the datetime attributes, I can set a constraint that ensures that the data adheres to some predetermined specifications; a starting date must be later than January 1, 1980 (the date on which the company began operations) and a termination date must be earlier than 11:59 PM on December 31, 1999.  I simply select the appropriate constraint and enter the value (1980-01-01 00:00 as the starting date and 1999-12-31 11:59 as the termination date). As a last step in setting up these datetime conversions, I edit the mapping, describing the format of each datetime type in the source file. I highlight the mapping line for the StartingDate attribute and click Edit Mapping in the Mappings grouping on the Schema > Edit tab of the editor’s ribbon bar.  This opens the Edit Mapping window in which I either enter, or select, a format that describes how the datetime values are represented in the file.  Note the use of Y01 as the syntax for the year.  This syntax is the indicator to expressor Studio to derive the century by setting any year later than 01 to the 20th century and any year before 01 to the 21st century.  As each datetime value is read from the file, the year values are transformed into century and year values. For the TerminationDate attribute, my format also indicates that the datetime value includes hours and minutes. And now to the Salary attribute. I open its mapping and in the Edit Mapping window select the Currency tab and the “Use currency” check box.  This indicates that the file data will include the dollar sign (or in Europe the Pound or Euro sign), which should be removed. And on the Grouping tab, I select the “Use grouping” checkbox and enter 3 into the “Group size” text box, a comma into the “Grouping character” text box, and a decimal point into the “Decimal separator” character text box. These entries allow the string to be properly converted into a decimal value. By making these entries into the schema that describes my input file, I’ve specified how I want the data transformed prior to writing to the database table and completely removed the requirement for coding within the data integration application itself. Assembling the data integration application is simple.  Onto the canvas I drag the Read File and Write Table operators, connecting the output of the Read File operator to the input of the Write Table operator. Next, I select the Read File operator and its Properties panel opens on the right-hand side of expressor Studio.  For each property, I can select an appropriate entry from the corresponding drop down control.  Clicking on the button to the right of the “File name” text box opens the file system location specified in the file connection artifact, allowing me to select the appropriate input file.  I indicate also that the first row in the file, the header row, should be skipped, and that any record that fails one of the datetime constraints should be skipped. I then select the Write Table operator and in its Properties panel specify the database connection, normal for the “Mode,” and the “Truncate” and “Create Missing Table” options.  If my target table does not yet exist, expressor will create the table using the information encapsulated in the schema artifact assigned to the operator. The last task needed to complete the application is to create the schema artifact used by the Write Table operator.  This is extremely easy as another wizard is capable of using the schema artifact assigned to the Read Table operator to create a schema artifact for the Write Table operator.  In the Write Table Properties panel, I click the drop down control to the right of the “Schema” property and select “New Table Schema from Upstream Output…” from the drop down menu. The wizard first displays the table description and in its second screen asks me to select the database connection artifact that specifies the RDBMS in which the target table will exist.  The wizard then connects to the RDBMS and retrieves a list of database schemas from which I make a selection.  The fourth screen gives me the opportunity to fine tune the table’s description.  In this example, I set the width of the JobDescription column to a maximum of 40 characters and select money as the type of the LastSalary column.  I also provide the name for the table. This completes development of the application.  The entire application was created through the use of wizards and the required data transformations specified through simple constraints and specifications rather than through coding.  To develop this application, I only needed a basic understanding of expressor Studio, a level of expertise that can be gained by working through a few introductory tutorials.  expressor Studio is as close to a point and click data integration tool as one could want and I urge you to try this product if you have a need to move data between files or from files to database tables. Check out CSVexpress in more detail.  It offers a few basic video tutorials and a preview of expressor Studio 3.5, which will support the reading and writing of data into Salesforce.com. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • SQL SERVER – Securing TRUNCATE Permissions in SQL Server

    - by pinaldave
    Download the Script of this article from here. On December 11, 2010, Vinod Kumar, a Databases & BI technology evangelist from Microsoft Corporation, graced Ahmedabad by spending some time with the Community during the Community Tech Days (CTD) event. As he was running through a few demos, Vinod asked the audience one of the most fundamental and common interview questions – “What is the difference between a DELETE and TRUNCATE?“ Ahmedabad SQL Server User Group Expert Nakul Vachhrajani has come up with excellent solutions of the same. I must congratulate Nakul for this excellent solution and as a encouragement to User Group member, I am publishing the same article over here. Nakul Vachhrajani is a Software Specialist and systems development professional with Patni Computer Systems Limited. He has functional experience spanning legacy code deprecation, system design, documentation, development, implementation, testing, maintenance and support of complex systems, providing business intelligence solutions, database administration, performance tuning, optimization, product management, release engineering, process definition and implementation. He has comprehensive grasp on Database Administration, Development and Implementation with MS SQL Server and C, C++, Visual C++/C#. He has about 6 years of total experience in information technology. Nakul is an member of the Ahmedabad and Gandhinagar SQL Server User Groups, and actively contributes to the community by actively participating in multiple forums and websites like SQLAuthority.com, BeyondRelational.com, SQLServerCentral.com and many others. Please note: The opinions expressed herein are Nakul own personal opinions and do not represent his employer’s view in anyway. All data from everywhere here on Earth go through a series of  four distinct operations, identified by the words: CREATE, READ, UPDATE and DELETE, or simply, CRUD. Putting in Microsoft SQL Server terms, is the process goes like this: INSERT, SELECT, UPDATE and DELETE/TRUNCATE. Quite a few interesting responses were received and evaluated live during the session. To summarize them, the most important similarity that came out was that both DELETE and TRUNCATE participate in transactions. The major differences (not all) that came out of the exercise were: DELETE: DELETE supports a WHERE clause DELETE removes rows from a table, row-by-row Because DELETE moves row-by-row, it acquires a row-level lock Depending upon the recovery model of the database, DELETE is a fully-logged operation. Because DELETE moves row-by-row, it can fire off triggers TRUNCATE: TRUNCATE does not support a WHERE clause TRUNCATE works by directly removing the individual data pages of a table TRUNCATE directly occupies a table-level lock. (Because a lock is acquired, and because TRUNCATE can also participate in a transaction, it has to be a logged operation) TRUNCATE is, therefore, a minimally-logged operation; again, this depends upon the recovery model of the database Triggers are not fired when TRUNCATE is used (because individual row deletions are not logged) Finally, Vinod popped the big homework question that must be critically analyzed: “We know that we can restrict a DELETE operation to a particular user, but how can we restrict the TRUNCATE operation to a particular user?” After returning home and having a nice cup of coffee, I noticed that my gray cells immediately started to work. Below was the result of my research. As what is always said, the devil is in the details. Upon looking at the Permissions section for the TRUNCATE statement in Books On Line, the following jumps right out: “The minimum permission required is ALTER on table_name. TRUNCATE TABLE permissions default to the table owner, members of the sysadmin fixed server role, and the db_owner and db_ddladmin fixed database roles, and are not transferable. However, you can incorporate the TRUNCATE TABLE statement within a module, such as a stored procedure, and grant appropriate permissions to the module using the EXECUTE AS clause.“ Now, what does this mean? Unlike DELETE, one cannot directly assign permissions to a user/set of users allowing or revoking TRUNCATE rights. However, there is a way to circumvent this. It is important to recall that in Microsoft SQL Server, database engine security surrounds the concept of a “securable”, which is any object like a table, stored procedure, trigger, etc. Rights are assigned to a principal on a securable. Refer to the image below (taken from the SQL Server Books On Line). urable”, which is any object like a table, stored procedure, trigger, etc. Rights are assigned to a principal on a securable. Refer to the image below (taken from the SQL Server Books On Line). SETTING UP THE ENVIRONMENT – (01A_Truncate Table Permissions.sql) Script Provided at the end of the article. By the end of this demo, one will be able to do all the CRUD operations, except the TRUNCATE, and the other will only be able to execute the TRUNCATE. All you will need for this test is any edition of SQL Server 2008. (With minor changes, these scripts can be made to work with SQL 2005.) We begin by creating the following: 1.       A test database 2.        Two database roles: associated logins and users 3.       Switch over to the test database and create a test table. Then, add some data into it. I am using row constructors, which is new to SQL 2008. Creating the modules that will be used to enforce permissions 1.       We have already created one of the modules that we will be assigning permissions to. That module is the table: TruncatePermissionsTest 2.       We will now create two stored procedures; one is for the DELETE operation and the other for the TRUNCATE operation. Please note that for all practical purposes, the end result is the same – all data from the table TruncatePermissionsTest is removed Assigning the permissions Now comes the most important part of the demonstration – assigning permissions. A permissions matrix can be worked out as under: To apply the security rights, we use the GRANT and DENY clauses, as under: That’s it! We are now ready for our big test! THE TEST (01B_Truncate Table Test Queries.sql) Script Provided at the end of the article. I will now need two separate SSMS connections, one with the login AllowedTruncate and the other with the login RestrictedTruncate. Running the test is simple; all that’s required is to run through the script – 01B_Truncate Table Test Queries.sql. What I will demonstrate here via screen-shots is the behavior of SQL Server when logged in as the AllowedTruncate user. There are a few other combinations than what are highlighted here. I will leave the reader the right to explore the behavior of the RestrictedTruncate user and these additional scenarios, as a form of self-study. 1.       Testing SELECT permissions 2.       Testing TRUNCATE permissions (Remember, “deny by default”?) 3.       Trying to circumvent security by trying to TRUNCATE the table using the stored procedure Hence, we have now proved that a user can indeed be assigned permissions to specifically assign TRUNCATE permissions. I also hope that the above has sparked curiosity towards putting some security around the probably “destructive” operations of DELETE and TRUNCATE. I would like to wish each and every one of the readers a very happy and secure time with Microsoft SQL Server. (Please find the scripts – 01A_Truncate Table Permissions.sql and 01B_Truncate Table Test Queries.sql that have been used in this demonstration. Please note that these scripts contain purely test-level code only. These scripts must not, at any cost, be used in the reader’s production environments). 01A_Truncate Table Permissions.sql /* ***************************************************************************************************************** Developed By          : Nakul Vachhrajani Functionality         : This demo is focused on how to allow only TRUNCATE permissions to a particular user How to Use            : 1. Run through, step-by-step through the sequence till Step 08 to create a test database 2. Switch over to the "Truncate Table Test Queries.sql" and execute it step-by-step in two different SSMS windows, one where you have logged in as 'RestrictedTruncate', and the other as 'AllowedTruncate' 3. Come back to "Truncate Table Permissions.sql" 4. Execute Step 10 to cleanup! Modifications         : December 13, 2010 - NAV - Updated to add a security matrix and improve code readability when applying security December 12, 2010 - NAV - Created ***************************************************************************************************************** */ -- Step 01: Create a new test database CREATE DATABASE TruncateTestDB GO USE TruncateTestDB GO -- Step 02: Add roles and users to demonstrate the security of the Truncate operation -- 2a. Create the new roles CREATE ROLE AllowedTruncateRole; GO CREATE ROLE RestrictedTruncateRole; GO -- 2b. Create new logins CREATE LOGIN AllowedTruncate WITH PASSWORD = 'truncate@2010', CHECK_POLICY = ON GO CREATE LOGIN RestrictedTruncate WITH PASSWORD = 'truncate@2010', CHECK_POLICY = ON GO -- 2c. Create new Users using the roles and logins created aboave CREATE USER TruncateUser FOR LOGIN AllowedTruncate WITH DEFAULT_SCHEMA = dbo GO CREATE USER NoTruncateUser FOR LOGIN RestrictedTruncate WITH DEFAULT_SCHEMA = dbo GO -- 2d. Add the newly created login to the newly created role sp_addrolemember 'AllowedTruncateRole','TruncateUser' GO sp_addrolemember 'RestrictedTruncateRole','NoTruncateUser' GO -- Step 03: Change over to the test database USE TruncateTestDB GO -- Step 04: Create a test table within the test databse CREATE TABLE TruncatePermissionsTest (Id INT IDENTITY(1,1), Name NVARCHAR(50)) GO -- Step 05: Populate the required data INSERT INTO TruncatePermissionsTest VALUES (N'Delhi'), (N'Mumbai'), (N'Ahmedabad') GO -- Step 06: Encapsulate the DELETE within another module CREATE PROCEDURE proc_DeleteMyTable WITH EXECUTE AS SELF AS DELETE FROM TruncateTestDB..TruncatePermissionsTest GO -- Step 07: Encapsulate the TRUNCATE within another module CREATE PROCEDURE proc_TruncateMyTable WITH EXECUTE AS SELF AS TRUNCATE TABLE TruncateTestDB..TruncatePermissionsTest GO -- Step 08: Apply Security /* *****************************SECURITY MATRIX*************************************** =================================================================================== Object                   | Permissions |                 Login |             | AllowedTruncate   |   RestrictedTruncate |             |User:NoTruncateUser|   User:TruncateUser =================================================================================== TruncatePermissionsTest  | SELECT,     |      GRANT        |      (Default) | INSERT,     |                   | | UPDATE,     |                   | | DELETE      |                   | -------------------------+-------------+-------------------+----------------------- TruncatePermissionsTest  | ALTER       |      DENY         |      (Default) -------------------------+-------------+----*/----------------+----------------------- proc_DeleteMyTable | EXECUTE | GRANT | DENY -------------------------+-------------+-------------------+----------------------- proc_TruncateMyTable | EXECUTE | DENY | GRANT -------------------------+-------------+-------------------+----------------------- *****************************SECURITY MATRIX*************************************** */ /* Table: TruncatePermissionsTest*/ GRANT SELECT, INSERT, UPDATE, DELETE ON TruncateTestDB..TruncatePermissionsTest TO NoTruncateUser GO DENY ALTER ON TruncateTestDB..TruncatePermissionsTest TO NoTruncateUser GO /* Procedure: proc_DeleteMyTable*/ GRANT EXECUTE ON TruncateTestDB..proc_DeleteMyTable TO NoTruncateUser GO DENY EXECUTE ON TruncateTestDB..proc_DeleteMyTable TO TruncateUser GO /* Procedure: proc_TruncateMyTable*/ DENY EXECUTE ON TruncateTestDB..proc_TruncateMyTable TO NoTruncateUser GO GRANT EXECUTE ON TruncateTestDB..proc_TruncateMyTable TO TruncateUser GO -- Step 09: Test --Switch over to the "Truncate Table Test Queries.sql" and execute it step-by-step in two different SSMS windows: --    1. one where you have logged in as 'RestrictedTruncate', and --    2. the other as 'AllowedTruncate' -- Step 10: Cleanup sp_droprolemember 'AllowedTruncateRole','TruncateUser' GO sp_droprolemember 'RestrictedTruncateRole','NoTruncateUser' GO DROP USER TruncateUser GO DROP USER NoTruncateUser GO DROP LOGIN AllowedTruncate GO DROP LOGIN RestrictedTruncate GO DROP ROLE AllowedTruncateRole GO DROP ROLE RestrictedTruncateRole GO USE MASTER GO DROP DATABASE TruncateTestDB GO 01B_Truncate Table Test Queries.sql /* ***************************************************************************************************************** Developed By          : Nakul Vachhrajani Functionality         : This demo is focused on how to allow only TRUNCATE permissions to a particular user How to Use            : 1. Switch over to this from "Truncate Table Permissions.sql", Step #09 2. Execute this step-by-step in two different SSMS windows a. One where you have logged in as 'RestrictedTruncate', and b. The other as 'AllowedTruncate' 3. Return back to "Truncate Table Permissions.sql" 4. Execute Step 10 to cleanup! Modifications         : December 12, 2010 - NAV - Created ***************************************************************************************************************** */ -- Step 09A: Switch to the test database USE TruncateTestDB GO -- Step 09B: Ensure that we have valid data SELECT * FROM TruncatePermissionsTest GO -- (Expected: Following error will occur if logged in as "AllowedTruncate") -- Msg 229, Level 14, State 5, Line 1 -- The SELECT permission was denied on the object 'TruncatePermissionsTest', database 'TruncateTestDB', schema 'dbo'. --Step 09C: Attempt to Truncate Data from the table without using the stored procedure TRUNCATE TABLE TruncatePermissionsTest GO -- (Expected: Following error will occur) --  Msg 1088, Level 16, State 7, Line 2 --  Cannot find the object "TruncatePermissionsTest" because it does not exist or you do not have permissions. -- Step 09D:Regenerate Test Data INSERT INTO TruncatePermissionsTest VALUES (N'London'), (N'Paris'), (N'Berlin') GO -- (Expected: Following error will occur if logged in as "AllowedTruncate") -- Msg 229, Level 14, State 5, Line 1 -- The INSERT permission was denied on the object 'TruncatePermissionsTest', database 'TruncateTestDB', schema 'dbo'. --Step 09E: Attempt to Truncate Data from the table using the stored procedure EXEC proc_TruncateMyTable GO -- (Expected: Will execute successfully with 'AllowedTruncate' user, will error out as under with 'RestrictedTruncate') -- Msg 229, Level 14, State 5, Procedure proc_TruncateMyTable, Line 1 -- The EXECUTE permission was denied on the object 'proc_TruncateMyTable', database 'TruncateTestDB', schema 'dbo'. -- Step 09F:Regenerate Test Data INSERT INTO TruncatePermissionsTest VALUES (N'Madrid'), (N'Rome'), (N'Athens') GO --Step 09G: Attempt to Delete Data from the table without using the stored procedure DELETE FROM TruncatePermissionsTest GO -- (Expected: Following error will occur if logged in as "AllowedTruncate") -- Msg 229, Level 14, State 5, Line 2 -- The DELETE permission was denied on the object 'TruncatePermissionsTest', database 'TruncateTestDB', schema 'dbo'. -- Step 09H:Regenerate Test Data INSERT INTO TruncatePermissionsTest VALUES (N'Spain'), (N'Italy'), (N'Greece') GO --Step 09I: Attempt to Delete Data from the table using the stored procedure EXEC proc_DeleteMyTable GO -- (Expected: Following error will occur if logged in as "AllowedTruncate") -- Msg 229, Level 14, State 5, Procedure proc_DeleteMyTable, Line 1 -- The EXECUTE permission was denied on the object 'proc_DeleteMyTable', database 'TruncateTestDB', schema 'dbo'. --Step 09J: Close this SSMS window and return back to "Truncate Table Permissions.sql" Thank you Nakul to take up the challenge and prove that Ahmedabad and Gandhinagar SQL Server User Group has talent to solve difficult problems. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Pinal Dave, Readers Contribution, Readers Question, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Security, SQL Server, SQL Tips and Tricks, T SQL, Technology

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