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  • SQL SERVER Stored Procedure and Transactions

    I just overheard the following statement – “I do not use Transactions in SQL as I use Stored Procedure“. I just realized that there are so many misconceptions about this subject. Transactions has nothing to do with Stored Procedures. Let me demonstrate that with a simple example. USE tempdb GO --Create3TestTables CREATETABLE TABLE1 (ID INT); [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • SQL SERVER – Weekend Project – Experimenting with ACID Transactions, SQL Compliant, Elastically Scalable Database

    - by pinaldave
    Database technology is huge and big world. I like to explore always beyond what I know and share the learning. Weekend is the best time when I sit around download random software on my machine which I like to call as a lab machine (it is a pretty old laptop, hardly a quality as lab machine) and experiment it. There are so many free betas available for download that it’s hard to keep track and even harder to find the time to play with very many of them.  This blog is about one you shouldn’t miss if you are interested in the learning various relational databases. NuoDB just released their Beta 7.  I had already downloaded their Beta 6 and yesterday did the same for 7.   My impression is that they are onto something very very interesting.  In fact, it might be something really promising in terms of database elasticity, scale and operational cost reduction. The folks at NuoDB say they are working on the world’s first “emergent” database which they tout as a brand new transitional database that is intended to dramatically change what’s possible with OLTP.  It is SQL compliant, guarantees ACID transactions, yet scales elastically on heterogeneous and decentralized cloud-based resources. Interesting note for sure, making me explore more. Based on what I’ve seen so far, they are solving the architectural challenge that exists between elastic, cloud-based compute infrastructures designed to scale out in response to workload requirements versus the traditional relational database management system’s architecture of central control. Here’s my experience with the NuoDB Beta 6 so far: First they pretty much threw away all the features you’d associate with existing RDBMS architectures except the SQL and ACID transactions which they were smart to keep.  It looks like they have incorporated a number of the big ideas from various algorithms, systems and techniques to achieve maximum DB scalability. From a user’s perspective, the NuoDB Beta software behaves like any other traditional SQL database and seems to offer all the benefits users have come to expect from standards-based SQL solutions. One of the interesting feature is that one can run a transactional node and a storage node on my Windows laptop as well on other platforms – indeed interesting for sure. It’s quite amazing to see a database elastically scale across machine boundaries. So, one of the basic NuoDB concepts is that as you need to scale out, you can easily use more inexpensive hardware when/where you need it.  This is unlike what we have traditionally done to scale a database for an application – we replace the hardware with something more powerful (faster CPU and Disks). This is where I started to feel like NuoDB is on to something that has the potential to elastically scale on commodity hardware while reducing operational expense for a big OLTP database to a degree we’ve never seen before. NuoDB is able to fully leverage the cloud in an asynchronous and highly decentralized manner – while providing both SQL compliance and ACID transactions. Basically what NuoDB is doing is so new that it is all hard to believe until you’ve experienced it in action.  I will keep you up to date as I test the NuoDB Beta 7 but if you are developing a web-scale application or have an on-premise app you are thinking of moving to the cloud, testing this beta is worth your time. If you do try it, let me know what you think.  Before I say anything more, I am going to do more experiments and more test on this product and compare it with other existing similar products. For me it was a weekend worth spent on learning something new. I encourage you to download Beta 7 version and share your opinions here. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • MSDTC attempts to enlist client machine in a distributed transaction

    - by Ken
    Hi there We're seeing the following intermittent warning logged by MSDTC: A caller has attempted to propagate a transaction to a remote system, but MSDTC network DTC access is currently disabled on machine 'X'. Please review the MS DTC configuration settings. However, MSDTC is disabled on machine X by design - it's a client machine, and has no business being enlisted in the transaction! Several windows service endpoints hosting WCF services over TCP Single SQL Server 2005 instance beneath Linq to Sql Remote client receives event callbacks over WCF/TCP The issue is tricky to reproduce - usually following restart of services. We suspect a callback to the client machine is occurring within the context of a transaction. Just wondering if anyone has seen similar issues?? Ken

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  • From Transactions To Engagement

    - by David Dorf
    I've mentioned in the past that Oracle has invested quite a bit in acquiring social companies to build out its Social Relationship Management suite.  The concept is to shift away from transactions and towards engagement.  Social media represents a great opportunity to engage with customers, learn what they want, and personalize the shopping experience for them. I look at SRM as the bridge between traditional CRM and CX.  If you're looking for ideas, check out Five Social Retailing Suggestions and Social Analytics and the Customer.  There are lots of ways to leverage social media to enhance the customer experience and thus drive more sales. My friends over at 8th Bridge have just released their Social IQ report in which they rate retailers on their social capabilities.  They also produced a nice infographic so you can consume the data quickly, but I'd still encourage you to download the full report. Retailers interested in upping their SRM abilities should definitely stop by the Oracle booth at NRF in January.

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  • SQL SERVER – Table Variables and Transactions – SQL in Sixty Seconds #007 – Video

    - by pinaldave
    Today’s SQL in Sixty Seconds video is inspired from my presentation at TechEd India 2012 on Misconception and Resolution. Quite often I have seen people getting confused with certain behavior of the T-SQL. They expect SQL to behave certain way and SQL Server behave differently. This kind of issue often creates confusion and frustration. Sometime I have seen them also confusing it with bug and submitting the bug, where reality is totally different. Similar concept which are going to see today. I have seen quite commonly developer assuming that table various will be rolled back when transaction is rolled back. This sixty seconds video describes that table various are not rolled back when transactions are rolled back. More on Errors: Difference Temp Table and Table Variable – Effect of Transaction Effect of TRANSACTION on Local Variable – After ROLLBACK and After COMMIT Debate – Table Variables vs Temporary Tables – Quiz – Puzzle – 13 of 31 I encourage you to submit your ideas for SQL in Sixty Seconds. We will try to accommodate as many as we can. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Video

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  • Distributed transactions and queues, ruby, erlang

    - by chrispanda
    I have a problem that involves several machines, message queues, and transactions. So for example a user clicks on a web page, the click sends a message to another machine which adds a payment to the user's account. There may be many thousands of clicks per second. All aspects of the transaction should be fault tolerant. I've never had to deal with anything like this before, but a bit of reading suggests this is a well known problem. So to my questions. Am I correct in assuming that secure way of doing this is with a two phase commit, but the protocol is blocking and so I won't get the required performance? It appears that DBs like redis and message queuing system like Rescue, RabbitMQ etc don't really help me a lot - even if I implement some sort of two phase commit, the data will be lost if redis crashes because it is essentially memory-only. All of this has led me to look at erlang - but before I wade in and start learning a new language, I would really like to understand better if this is worth the effort. Specifically, am I right in thinking that because of its parallel processing capabilities, erlang is a better choice for implementing a blocking protocol like two phase commit, or am I confused?

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  • How can I get SQL Server transactions to use record-level locks?

    - by Joe White
    We have an application that was originally written as a desktop app, lo these many years ago. It starts a transaction whenever you open an edit screen, and commits if you click OK, or rolls back if you click Cancel. This worked okay for a desktop app, but now we're trying to move to ADO.NET and SQL Server, and the long-running transactions are problematic. I found that we'll have a problem when multiple users are all trying to edit (different subsets of) the same table at the same time. In our old database, each user's transaction would acquire record-level locks to every record they modified during their transaction; since different users were editing different records, everyone gets their own locks and everything works. But in SQL Server, as soon as one user edits a record inside a transaction, SQL Server appears to get a lock on the entire table. When a second user tries to edit a different record in the same table, the second user's app simply locks up, because the SqlConnection blocks until the first user either commits or rolls back. I'm aware that long-running transactions are bad, and I know that the best solution would be to change these screens so that they no longer keep transactions open for a long time. But since that would mean some invasive and risky changes, I also want to research whether there's a way to get this code up and running as-is, just so I know what my options are. How can I get two different users' transactions in SQL Server to lock individual records instead of the entire table? Here's a quick-and-dirty console app that illustrates the issue. I've created a database called "test1", with one table called "Values" that just has ID (int) and Value (nvarchar) columns. If you run the app, it asks for an ID to modify, starts a transaction, modifies that record, and then leaves the transaction open until you press ENTER. I want to be able to start the program and tell it to update ID 1; let it get its transaction and modify the record; start a second copy of the program and tell it to update ID 2; have it able to update (and commit) while the first app's transaction is still open. Currently it freezes at step 4, until I go back to the first copy of the app and close it or press ENTER so it commits. The call to command.ExecuteNonQuery blocks until the first connection is closed. public static void Main() { Console.Write("ID to update: "); var id = int.Parse(Console.ReadLine()); Console.WriteLine("Starting transaction"); using (var scope = new TransactionScope()) using (var connection = new SqlConnection(@"Data Source=localhost\sqlexpress;Initial Catalog=test1;Integrated Security=True")) { connection.Open(); var command = connection.CreateCommand(); command.CommandText = "UPDATE [Values] SET Value = 'Value' WHERE ID = " + id; Console.WriteLine("Updating record"); command.ExecuteNonQuery(); Console.Write("Press ENTER to end transaction: "); Console.ReadLine(); scope.Complete(); } } Here are some things I've already tried, with no change in behavior: Changing the transaction isolation level to "read uncommitted" Specifying a "WITH (ROWLOCK)" on the UPDATE statement

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  • customer.name joining transactions.name vs. customer.id [serial] joining transactions.id [integer]

    - by Frank Computer
    INFORMIX-SQL 7.32 Pawnshop Application: one-to-many relationship where each customer (master) can have many transactions (detail). customer( id serial, pk_name char(30), {PATERNAL-NAME MATERNAL-NAME, FIRST-NAME MIDDLE-NAME} [...] ); unique index on id; unique cluster index on name; transaction( fk_name char(30), ticket_number serial, [...] ); dups cluster index on fk_name; unique index on ticket_number; Several people have told me this is not the correct way to join master to detail. They said I should always join customer.id[serial] to transactions.id[integer]. When a customer pawns merchandise, clerk queries the master using wildcards on name. The query usually returns several customers, clerk scrolls until locating the right name, enters a 'D' to change to detail transactions table, all transactions are automatically queried, then clerk enters an 'A' to add a new transaction. The problem with using customer.id joining transaction.id is that although the customer table is maintained in sorted name order, clustering the transaction table by fk_id groups the transactions by fk_id, but they are not in the same order as the customer name, so when clerk is scrolling through customer names in the master, the system has to jump allover the place to locate the clustered transactions belonging to each customer. As each new customer is added, the next id is assigned to that customer, but new customers dont show up in alphabetical order. I experimented using id joins and confirmed the decrease in performance. How can I use id joins instead of name joins and still preserve the clustered transaction order by name if transactions has no name column?

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  • Do you know of a C dictionary that supports COW transactions?

    - by Tim Post
    I'm looking for a key - value dictionary library written in C that supports a theoretically unlimited number of cheap transactions. I'd like to have one dictionary in memory, with hundreds of threads starting transactions, possibly modifying the dictionary, ending (completing) the transaction or potentially aborting the transaction. Only 50% of the time will these threads actually modify the dictionary. Most dictionary transaction implementations that I've seen copy always, instead of copying on write, whenever a transaction is started. Given the expected size ( 1GB) of the dictionary, I'm hoping to find something that COWs only when something is actually changed during a transaction. I'm also hoping for something that is packaged by most major GNU/Linux distributions. Any suggestions or links are very much appreciated.

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  • How to avoid using duplicate savepoint names in nested transactions in nested stored procs?

    - by Gary McGill
    I have a pattern that I almost always follow, where if I need to wrap up an operation in a transaction, I do this: BEGIN TRANSACTION SAVE TRANSACTION TX -- Stuff IF @error <> 0 ROLLBACK TRANSACTION TX COMMIT TRANSACTION That's served me well enough in the past, but after years of using this pattern (and copy-pasting the above code), I've suddenly discovered a flaw which comes as a complete shock. Quite often, I'll have a stored procedure calling other stored procedures, all of which use this same pattern. What I've discovered (to my cost) is that because I'm using the same savepoint name everywhere, I can get into a situation where my outer transaction is partially committed - precisely the opposite of the atomicity that I'm trying to achieve. I've put together an example that exhibits the problem. This is a single batch (no nested stored procs), and so it looks a little odd in that you probably wouldn't use the same savepoint name twice in the same batch, but my real-world scenario would be too confusing to post. CREATE TABLE Test (test INTEGER NOT NULL) BEGIN TRAN SAVE TRAN TX BEGIN TRAN SAVE TRAN TX INSERT INTO Test(test) VALUES (1) COMMIT TRAN TX BEGIN TRAN SAVE TRAN TX INSERT INTO Test(test) VALUES (2) COMMIT TRAN TX DELETE FROM Test ROLLBACK TRAN TX COMMIT TRAN TX SELECT * FROM Test DROP TABLE Test When I execute this, it lists one record, with value "1". In other words, even though I rolled back my outer transaction, a record was added to the table. What's happening is that the ROLLBACK TRANSACTION TX at the outer level is rolling back as far as the last SAVE TRANSACTION TX at the inner level. Now that I write this all out, I can see the logic behind it: the server is looking back through the log file, treating it as a linear stream of transactions; it doesn't understand the nesting/hierarchy implied by either the nesting of the transactions (or, in my real-world scenario, by the calls to other stored procedures). So, clearly, I need to start using unique savepoint names instead of blindly using "TX" everywhere. But - and this is where I finally get to the point - is there a way to do this in a copy-pastable way so that I can still use the same code everywhere? Can I auto-generate the savepoint name on the fly somehow? Is there a convention or best-practice for doing this sort of thing? It's not exactly hard to come up with a unique name every time you start a transaction (could base it off the SP name, or somesuch), but I do worry that eventually there would be a conflict - and you wouldn't know about it because rather than causing an error it just silently destroys your data... :-(

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  • SQL SERVER – Simple Example of Snapshot Isolation – Reduce the Blocking Transactions

    - by pinaldave
    To learn any technology and move to a more advanced level, it is very important to understand the fundamentals of the subject first. Today, we will be talking about something which has been quite introduced a long time ago but not properly explored when it comes to the isolation level. Snapshot Isolation was introduced in SQL Server in 2005. However, the reality is that there are still many software shops which are using the SQL Server 2000, and therefore cannot be able to maintain the Snapshot Isolation. Many software shops have upgraded to the later version of the SQL Server, but their respective developers have not spend enough time to upgrade themselves with the latest technology. “It works!” is a very common answer of many when they are asked about utilizing the new technology, instead of backward compatibility commands. In one of the recent consultation project, I had same experience when developers have “heard about it” but have no idea about snapshot isolation. They were thinking it is the same as Snapshot Replication – which is plain wrong. This is the same demo I am including here which I have created for them. In Snapshot Isolation, the updated row versions for each transaction are maintained in TempDB. Once a transaction has begun, it ignores all the newer rows inserted or updated in the table. Let us examine this example which shows the simple demonstration. This transaction works on optimistic concurrency model. Since reading a certain transaction does not block writing transaction, it also does not block the reading transaction, which reduced the blocking. First, enable database to work with Snapshot Isolation. Additionally, check the existing values in the table from HumanResources.Shift. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO Now, we will need two different sessions to prove this example. First Session: Set Transaction level isolation to snapshot and begin the transaction. Update the column “ModifiedDate” to today’s date. -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO Please note that we have not yet been committed to the transaction. Now, open the second session and run the following “SELECT” statement. Then, check the values of the table. Please pay attention on setting the Isolation level for the second one as “Snapshot” at the same time when we already start the transaction using BEGIN TRAN. -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values in the table are still original values. They have not been modified yet. Once again, go back to session 1 and begin the transaction. -- Session 1 COMMIT After that, go back to Session 2 and see the values of the table. -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values are yet not changed and they are still the same old values which were there right in the beginning of the session. Now, let us commit the transaction in the session 2. Once committed, run the same SELECT statement once more and see what the result is. -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that it now reflects the new updated value. I hope that this example is clear enough as it would give you good idea how the Snapshot Isolation level works. There is much more to write about an extra level, READ_COMMITTED_SNAPSHOT, which we will be discussing in another post soon. If you wish to use this transaction’s Isolation level in your production database, I would appreciate your comments about their performance on your servers. I have included here the complete script used in this example for your quick reference. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 COMMIT -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Transaction Isolation

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  • An XEvent a Day (11 of 31) – Targets Week – Using Multiple Targets to Debug Orphaned Transactions

    - by Jonathan Kehayias
    Yesterday’s blog post Targets Week – etw_classic_sync_target covered the ETW integration that is built into Extended Events and how the etw_classic_sync_target can be used in conjunction with other ETW traces to provide troubleshooting at a level previously not possible with SQL Server. In today’s post we’ll look at how to use multiple targets to simplify analysis of Event collection. Why Multiple Targets? You might ask why you would want to use multiple Targets in an Event Session with Extended...(read more)

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  • SQL SERVER – Simple Example of Snapshot Isolation – Reduce the Blocking Transactions

    - by pinaldave
    To learn any technology and move to a more advanced level, it is very important to understand the fundamentals of the subject first. Today, we will be talking about something which has been quite introduced a long time ago but not properly explored when it comes to the isolation level. Snapshot Isolation was introduced in SQL Server in 2005. However, the reality is that there are still many software shops which are using the SQL Server 2000, and therefore cannot be able to maintain the Snapshot Isolation. Many software shops have upgraded to the later version of the SQL Server, but their respective developers have not spend enough time to upgrade themselves with the latest technology. “It works!” is a very common answer of many when they are asked about utilizing the new technology, instead of backward compatibility commands. In one of the recent consultation project, I had same experience when developers have “heard about it” but have no idea about snapshot isolation. They were thinking it is the same as Snapshot Replication – which is plain wrong. This is the same demo I am including here which I have created for them. In Snapshot Isolation, the updated row versions for each transaction are maintained in TempDB. Once a transaction has begun, it ignores all the newer rows inserted or updated in the table. Let us examine this example which shows the simple demonstration. This transaction works on optimistic concurrency model. Since reading a certain transaction does not block writing transaction, it also does not block the reading transaction, which reduced the blocking. First, enable database to work with Snapshot Isolation. Additionally, check the existing values in the table from HumanResources.Shift. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO Now, we will need two different sessions to prove this example. First Session: Set Transaction level isolation to snapshot and begin the transaction. Update the column “ModifiedDate” to today’s date. -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO Please note that we have not yet been committed to the transaction. Now, open the second session and run the following “SELECT” statement. Then, check the values of the table. Please pay attention on setting the Isolation level for the second one as “Snapshot” at the same time when we already start the transaction using BEGIN TRAN. -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values in the table are still original values. They have not been modified yet. Once again, go back to session 1 and begin the transaction. -- Session 1 COMMIT After that, go back to Session 2 and see the values of the table. -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that the values are yet not changed and they are still the same old values which were there right in the beginning of the session. Now, let us commit the transaction in the session 2. Once committed, run the same SELECT statement once more and see what the result is. -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO You will notice that it now reflects the new updated value. I hope that this example is clear enough as it would give you good idea how the Snapshot Isolation level works. There is much more to write about an extra level, READ_COMMITTED_SNAPSHOT, which we will be discussing in another post soon. If you wish to use this transaction’s Isolation level in your production database, I would appreciate your comments about their performance on your servers. I have included here the complete script used in this example for your quick reference. ALTER DATABASE AdventureWorks SET ALLOW_SNAPSHOT_ISOLATION ON GO SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN UPDATE HumanResources.Shift SET ModifiedDate = GETDATE() GO -- Session 2 SET TRANSACTION ISOLATION LEVEL SNAPSHOT BEGIN TRAN SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 1 COMMIT -- Session 2 SELECT ModifiedDate FROM HumanResources.Shift GO -- Session 2 COMMIT SELECT ModifiedDate FROM HumanResources.Shift GO Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Transaction Isolation

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  • Entity Framework - Using Transactions or SaveChanges(false) and AcceptAllChanges()?

    - by mark smith
    Hi there, I have been investigating transactions and it appears that they take call of them selves in EF as long as i pass false to savechanges.. SaveChanges(false) and if all goes well then AcceptAllChanges() Question is what is something goes bad, don't have to rollback? or as soon as the my method goes out of scope its ended? What happens to any indentiy columns that were assigned half way through the transaction.. i presume if somebody else added a record after mine before mine went bad then this means there will be a missing Identity value. Is there any reason to use standard "transactionScope" in code? ideas? - thanks

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  • How to add Transactions with a DataSet created using the Add Connection Wizard?

    - by RoguePlanetoid
    I have a DataSet that I have added to my project where I can Insert and Add records using the Add Query function in Visual Studio 2010, however I want to add transactions to this, I have found a few examples but cannot seem to find one that works with these. I know I need to use the SQLClient.SQLTransaction Class somehow. I used the Add New Data Source Wizard and added the Tables/View/Functions I need, I just need an example using this process such as How to get the DataConnection my DataSet has used. Assuming all options have been set in the wizard and I am only using the pre-defined adapters and options asked for in this wizard, how to I add the Transaction logic to my Database. For example I have a DataSet called ProductDataSet with the XSD created for this, I have then added my Stock table as a Datasource and Added an AddStock method with a wizard, this also if a new item calls an AddItem method, if either of these fails I want to rollback the AddItem and AddStock in this case.

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  • Threaded Django task doesn't automatically handle transactions or db connections?

    - by Gabriel Hurley
    I've got Django set up to run some recurring tasks in their own threads, and I noticed that they were always leaving behind unfinished database connection processes (pgsql "Idle In Transaction"). I looked through the Postgres logs and found that the transactions weren't being completed (no ROLLBACK). I tried using the various transaction decorators on my functions, no luck. I switched to manual transaction management and did the rollback manually, that worked, but still left the processes as "Idle". So then I called connection.close(), and all is well. But I'm left wondering, why doesn't Django's typical transaction and connection management work for these threaded tasks that are being spawned from the main Django thread?

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  • NHibernate transaction management in ASP.NET MVC - how should it be done?

    - by adrin
    I am writing a simple ASP.NET MVC using session per request and transaction per request patterns (custom HttpModule). It seems to work properly, but.. the performance is terrible (a simple page loads ~7 seconds). For every http request, graphical resources incuding (all images on the site) a transaction is created and that seems to delay the loading times (without the transactions loading times per one image are ~1-10 ms with transactions they are over 1 second). What is the proper way to manage transactions in ASP.NET MVC + NH stack? When i've put all transactions into my repository methods, for some obscure reasons I got 'implicit transactions' warning in NHProf (the SQL statements were executed outside transaction, even that in code session.Save()/Update()/etc methods were invoked within transaction 'using' scope and before transaction.Commit() call) BTW are implicit transactions really bad?

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  • Large transactions causing "System.Data.SqlClient.SqlException: Timeout expired" error?

    - by Michael
    My application requires a user to log in and allows them to edit a list of things. However, it seems that if the same user always logs in and out and edits the list, this user will run into a "System.Data.SqlClient.SqlException: Timeout expired." error. I've read comments about increasing the timeout period but I've also read a comment about it possibly caused by uncommitted transactions. And I do have one going in the application. I'll provide the code I'm working with and there is an IF statement in there that I was a little iffy about but it seemed like a reasonable thing to do. I'll just go over what's going on here, there is a list of objects to update or add into the database. New objects created in the application are given an ID of 0 while existing objects have their own ID's generated from the DB. If the user chooses to delete some objects, their IDs are stored in a separate list of Integers. Once the user is ready to save their changes, the two lists are passed into this method. By use of the IF statement, objects with ID of 0 are added (using the Add stored procedure) and those objects with non-zero IDs are updated (using the Update stored procedure). After all this, a FOR loop goes through all the integers in the "removal" list and uses the Delete stored procedure to remove them. A transaction is used for all this. Public Shared Sub UpdateSomethings(ByVal SomethingList As List(Of Something), ByVal RemovalList As List(Of Integer)) Using DBConnection As New SqlConnection(conn) DBConnection.Open() Dim MyTransaction As SqlTransaction MyTransaction = DBConnection.BeginTransaction() Try For Each SomethingItem As Something In SomethingList Using MyCommand As New SqlCommand() MyCommand.Connection = DBConnection If SomethingItem.ID > 0 Then MyCommand.CommandText = "UpdateSomething" Else MyCommand.CommandText = "AddSomething" End If MyCommand.Transaction = MyTransaction MyCommand.CommandType = CommandType.StoredProcedure With MyCommand.Parameters If MyCommand.CommandText = "UpdateSomething" Then .Add("@id", SqlDbType.Int).Value = SomethingItem.ID End If .Add("@stuff", SqlDbType.Varchar).Value = SomethingItem.Stuff End With MyCommand.ExecuteNonQuery() End Using Next For Each ID As Integer In RemovalList Using MyCommand As New SqlCommand("DeleteSomething", DBConnection) MyCommand.Transaction = MyTransaction MyCommand.CommandType = CommandType.StoredProcedure With MyCommand.Parameters .Add("@id", SqlDbType.Int).Value = ID End With MyCommand.ExecuteNonQuery() End Using Next MyTransaction.Commit() Catch ex As Exception MyTransaction.Rollback() 'Exception handling goes here End Try End Using End Sub There are three stored procedures used here as well as some looping so I can see how something can be holding everything up if the list is large enough. Other users can log in to the system at the same time just fine though. I'm using Visual Studio 2008 to debug and am using SQL Server 2000 for the DB.

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  • What is "read operations inside transactions can't allow failover" ?

    - by Kenyth
    From time to time I got the following exception message on GAE for my GAE/J app. I searched with Google, no relevant results were found. Does anyone know about this? Thanks in advance for any response! The exception message is as below: Nested in org.springframework.orm.jpa.JpaSystemException: Illegal argument; nested exception is javax.persistence.PersistenceException: Illegal argument: java.lang.IllegalArgumentException: read operations inside transactions can't allow failover at com.google.appengine.api.datastore.DatastoreApiHelper.translateError(DatastoreApiHelper.java: 34) at com.google.appengine.api.datastore.DatastoreApiHelper.makeSyncCall(DatastoreApiHelper.java: 67) at com.google.appengine.api.datastore.DatastoreServiceImpl $1.run(DatastoreServiceImpl.java:128) at com.google.appengine.api.datastore.TransactionRunner.runInTransaction(TransactionRunner.java: 30) at com.google.appengine.api.datastore.DatastoreServiceImpl.get(DatastoreServiceImpl.java: 111) at com.google.appengine.api.datastore.DatastoreServiceImpl.get(DatastoreServiceImpl.java: 84) at com.google.appengine.api.datastore.DatastoreServiceImpl.get(DatastoreServiceImpl.java: 77) at org.datanucleus.store.appengine.RuntimeExceptionWrappingDatastoreService.get(RuntimeExceptionWrappingDatastoreService.java: 53) at org.datanucleus.store.appengine.DatastorePersistenceHandler.get(DatastorePersistenceHandler.java: 94) at org.datanucleus.store.appengine.DatastorePersistenceHandler.get(DatastorePersistenceHandler.java: 106) at org.datanucleus.store.appengine.DatastorePersistenceHandler.fetchObject(DatastorePersistenceHandler.java: 464) at org.datanucleus.state.JDOStateManagerImpl.loadUnloadedFieldsInFetchPlan(JDOStateManagerImpl.java: 1627) at org.datanucleus.state.JDOStateManagerImpl.loadFieldsInFetchPlan(JDOStateManagerImpl.java: 1603) at org.datanucleus.ObjectManagerImpl.performDetachAllOnCommitPreparation(ObjectManagerImpl.java: 3192) at org.datanucleus.ObjectManagerImpl.preCommit(ObjectManagerImpl.java: 2931) at org.datanucleus.TransactionImpl.internalPreCommit(TransactionImpl.java: 369) at org.datanucleus.TransactionImpl.commit(TransactionImpl.java:256) at org.datanucleus.jpa.EntityTransactionImpl.commit(EntityTransactionImpl.java: 104) at org.datanucleus.store.appengine.jpa.DatastoreEntityTransactionImpl.commit(DatastoreEntityTransactionImpl.java: 55) at name.kenyth.playtweets.service.Tx.run(Tx.java:39) at name.kenyth.playtweets.web.controller.TwitterApiController.persistStatus(TwitterApiController.java: 309) at name.kenyth.playtweets.web.controller.TwitterApiController.processStatusesForWebCall(TwitterApiController.java: 271) at name.kenyth.playtweets.web.controller.TwitterApiController.getHomeTimelineUpdates_aroundBody0(TwitterApiController.java: 247) at name.kenyth.playtweets.web.controller.TwitterApiController $AjcClosure1.run(TwitterApiController.java:1) at name.kenyth.playtweets.web.refine.AuthenticationEnforcement.ajc $around$name_kenyth_playtweets_web_refine_AuthenticationEnforcement $2$439820b7proceed(AuthenticationEnforcement.aj:1) at name.kenyth.playtweets.web.refine.AuthenticationEnforcement.ajc $around$name_kenyth_playtweets_web_refine_AuthenticationEnforcement $2$439820b7(AuthenticationEnforcement.aj:168) at name.kenyth.playtweets.web.controller.TwitterApiController.getHomeTimelineUpdates(TwitterApiController.java: 129) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source) at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source) at java.lang.reflect.Method.invoke(Method.java:43) at org.springframework.web.bind.annotation.support.HandlerMethodInvoker.doInvokeMethod(HandlerMethodInvoker.java: 710) at org.springframework.web.bind.annotation.support.HandlerMethodInvoker.invokeHandlerMethod(HandlerMethodInvoker.java: 167) at org.springframework.web.servlet.mvc.annotation.AnnotationMethodHandlerAdapter.invokeHandlerMethod(AnnotationMethodHandlerAdapter.java: 414) at org.springframework.web.servlet.mvc.annotation.AnnotationMethodHandlerAdapter.handle(AnnotationMethodHandlerAdapter.java: 402) at org.springframework.web.servlet.DispatcherServlet.doDispatch(DispatcherServlet.java: 771) at org.springframework.web.servlet.DispatcherServlet.doService(DispatcherServlet.java: 716) at org.springframework.web.servlet.FrameworkServlet.processRequest(FrameworkServlet.java: 647) at org.springframework.web.servlet.FrameworkServlet.doGet(FrameworkServlet.java: 552) at javax.servlet.http.HttpServlet.service(HttpServlet.java:693) at javax.servlet.http.HttpServlet.service(HttpServlet.java:806) at org.mortbay.jetty.servlet.ServletHolder.handle(ServletHolder.java: 511) at org.mortbay.jetty.servlet.ServletHandler.handle(ServletHandler.java: 390) at org.mortbay.jetty.security.SecurityHandler.handle(SecurityHandler.java: 216) at org.mortbay.jetty.servlet.SessionHandler.handle(SessionHandler.java: 182) at org.mortbay.jetty.handler.ContextHandler.handle(ContextHandler.java: 765) at org.mortbay.jetty.webapp.WebAppContext.handle(WebAppContext.java: 418) at org.mortbay.jetty.servlet.Dispatcher.forward(Dispatcher.java:327) at org.mortbay.jetty.servlet.Dispatcher.forward(Dispatcher.java:126) at org.tuckey.web.filters.urlrewrite.NormalRewrittenUrl.doRewrite(NormalRewrittenUrl.java: 195) at org.tuckey.web.filters.urlrewrite.RuleChain.handleRewrite(RuleChain.java: 159) at org.tuckey.web.filters.urlrewrite.RuleChain.doRules(RuleChain.java: 141) at org.tuckey.web.filters.urlrewrite.UrlRewriter.processRequest(UrlRewriter.java: 90) at org.tuckey.web.filters.urlrewrite.UrlRewriteFilter.doFilter(UrlRewriteFilter.java: 417) at org.mortbay.jetty.servlet.ServletHandler $CachedChain.doFilter(ServletHandler.java:1157) at org.springframework.web.filter.HiddenHttpMethodFilter.doFilterInternal(HiddenHttpMethodFilter.java: 71) at org.springframework.web.filter.OncePerRequestFilter.doFilter(OncePerRequestFilter.java: 76) at org.mortbay.jetty.servlet.ServletHandler $CachedChain.doFilter(ServletHandler.java:1157) at org.springframework.web.filter.CharacterEncodingFilter.doFilterInternal(CharacterEncodingFilter.java: 88) at org.springframework.web.filter.OncePerRequestFilter.doFilter(OncePerRequestFilter.java: 76) at org.mortbay.jetty.servlet.ServletHandler $CachedChain.doFilter(ServletHandler.java:1157) at com.google.apphosting.utils.servlet.ParseBlobUploadFilter.doFilter(ParseBlobUploadFilter.java: 97) at org.mortbay.jetty.servlet.ServletHandler $CachedChain.doFilter(ServletHandler.java:1157) at com.google.apphosting.runtime.jetty.SaveSessionFilter.doFilter(SaveSessionFilter.java: 35) at org.mortbay.jetty.servlet.ServletHandler $CachedChain.doFilter(ServletHandler.java:1157) at com.google.apphosting.utils.servlet.TransactionCleanupFilter.doFilter(TransactionCleanupFilter.java: 43) at org.mortbay.jetty.servlet.ServletHandler $CachedChain.doFilter(ServletHandler.java:1157) at org.mortbay.jetty.servlet.ServletHandler.handle(ServletHandler.java: 388) at org.mortbay.jetty.security.SecurityHandler.handle(SecurityHandler.java: 216) at org.mortbay.jetty.servlet.SessionHandler.handle(SessionHandler.java: 182) at org.mortbay.jetty.handler.ContextHandler.handle(ContextHandler.java: 765) at org.mortbay.jetty.webapp.WebAppContext.handle(WebAppContext.java: 418) at com.google.apphosting.runtime.jetty.AppVersionHandlerMap.handle(AppVersionHandlerMap.java: 238) at org.mortbay.jetty.handler.HandlerWrapper.handle(HandlerWrapper.java: 152) at org.mortbay.jetty.Server.handle(Server.java:326) at org.mortbay.jetty.HttpConnection.handleRequest(HttpConnection.java: 542) at org.mortbay.jetty.HttpConnection $RequestHandler.headerComplete(HttpConnection.java:923) at com.google.apphosting.runtime.jetty.RpcRequestParser.parseAvailable(RpcRequestParser.java: 76) at org.mortbay.jetty.HttpConnection.handle(HttpConnection.java:404) at com.google.apphosting.runtime.jetty.JettyServletEngineAdapter.serviceRequest(JettyServletEngineAdapter.java: 135) at com.google.apphosting.runtime.JavaRuntime.handleRequest(JavaRuntime.java: 250) at com.google.apphosting.base.RuntimePb$EvaluationRuntime $6.handleBlockingRequest(RuntimePb.java:5838) at com.google.apphosting.base.RuntimePb$EvaluationRuntime $6.handleBlockingRequest(RuntimePb.java:5836) at com.google.net.rpc.impl.BlockingApplicationHandler.handleRequest(BlockingApplicationHandler.java: 24) at com.google.net.rpc.impl.RpcUtil.runRpcInApplication

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  • Your Transaction is in Jeopardy -- and You Can't Even Know It!

    - by Adam Machanic
    If you're reading this, please take one minute out of your day and vote for the following Connect item : https://connect.microsoft.com/SQLServer/feedback/details/444030/sys-dm-tran-active-transactions-transaction-state-not-updated-when-an-attention-event-occurs If you're really interested, take three minutes: run the steps to reproduce the issue, and then check the box that says that you were able to reproduce the issue. Why? Imagine that ten hours ago you started a big transaction. You're sitting...(read more)

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  • Your Transaction is in Jeopardy -- and You Can't Even Know It!

    - by Adam Machanic
    If you're reading this, please take one minute out of your day and vote for the following Connect item : https://connect.microsoft.com/SQLServer/feedback/details/444030/sys-dm-tran-active-transactions-transaction-state-not-updated-when-an-attention-event-occurs If you're really interested, take three minutes: run the steps to reproduce the issue, and then check the box that says that you were able to reproduce the issue. Why? Imagine that ten hours ago you started a big transaction. You're sitting...(read more)

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