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  • Standard Network Tiers in a Distributed N-Tier System

    Distributed N-Tier client/server architecture allows for segments of an application to be broken up and distributed across multiple locations on a network.  Listed below are standard tiers in a Distributed N-Tier System. End-User Client Tier The End-User Client is responsible for sending and receiving requests from web servers and other applications servers and translating the responses so that the End-User can interpret the data effectively. The primary roles for this tier are to communicate with servers and translate server responses back to the end-user to interpret. Business-Specific Functions Validate Data Display Data Send Data to Webserver Web Server Tier The Web server tier processes new requests for information coming in from the HTTP and HTTPS ports. This primarily handles the generation of user interfaces and calls the application server when needed to access Data and business logic when needed. Business-specific functions Send Data to application server Format Data for Display Validate Data Application Server Tier The application server stores and executes predefined business logic that is applied to various pieces of data as the business determines. The processed data is then returned back to the Webserver. Additionally, this server directly calls the database to obtain and store any data used by the system Business-Specific Functions Validate Data Process Data Send Data to Database Server Database Server Tier The Database Server is responsible for storing and returning all data need by the calling applications. The primary role for this this server is storage. Data is stored as needed and can be recalled at any point later in time. Business-Specific Functions Insert Data Delete Data Return Data to Application Server

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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 – Shard No More – An Innovative Look at Distributed Peer-to-peer SQL Database

    - by pinaldave
    There is no doubt that SQL databases play an important role in modern applications. In an ideal world, a single database can handle hundreds of incoming connections from multiple clients and scale to accommodate the related transactions. However the world is not ideal and databases are often a cause of major headaches when applications need to scale to accommodate more connections, transactions, or both. In order to overcome scaling issues, application developers often resort to administrative acrobatics, also known as database sharding. Sharding helps to improve application performance and throughput by splitting the database into two or more shards. Unfortunately, this practice also requires application developers to code transactional consistency into their applications. Getting transactional consistency across multiple SQL database shards can prove to be very difficult. Sharding requires developers to think about things like rollbacks, constraints, and referential integrity across tables within their applications when these types of concerns are best handled by the database. It also makes other common operations such as joins, searches, and memory management very difficult. In short, the very solution implemented to overcome throughput issues becomes a bottleneck in and of itself. What if database sharding was no longer required to scale your application? Let me explain. For the past several months I have been following and writing about NuoDB, a hot new SQL database technology out of Cambridge, MA. NuoDB is officially out of beta and they have recently released their first release candidate so I decided to dig into the database in a little more detail. Their architecture is very interesting and exciting because it completely eliminates the need to shard a database to achieve higher throughput. Each NuoDB database consists of at least three or more processes that enable a single database to run across multiple hosts. These processes include a Broker, a Transaction Engine and a Storage Manager.  Brokers are responsible for connecting client applications to Transaction Engines and maintain a global view of the network to keep track of the multiple Transaction Engines available at any time. Transaction Engines are in-memory processes that client applications connect to for processing SQL transactions. Storage Managers are responsible for persisting data to disk and serving up records to the Transaction Managers if they don’t exist in memory. The secret to NuoDB’s approach to solving the sharding problem is that it is a truly distributed, peer-to-peer, SQL database. Each of its processes can be deployed across multiple hosts. When client applications need to connect to a Transaction Engine, the Broker will automatically route the request to the most available process. Since multiple Transaction Engines and Storage Managers running across multiple host machines represent a single logical database, you never have to resort to sharding to get the throughput your application requires. NuoDB is a new pioneer in the SQL database world. They are making database scalability simple by eliminating the need for acrobatics such as sharding, and they are also making general administration of the database simpler as well.  Their distributed database appears to you as a user like a single SQL Server database.  With their RC1 release they have also provided a web based administrative console that they call NuoConsole. This tool makes it extremely easy to deploy and manage NuoDB processes across one or multiple hosts with the click of a mouse button. See for yourself by downloading NuoDB here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: CodeProject, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology Tagged: NuoDB

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  • Are there any viable DNS or LDAP alternatives for distributed key/value storage and retrieval?

    - by makerofthings7
    I'm working on a software app that needs distributed decentralized name resolution, and isn't bound to TCP/IP. Or more precisely, I need to store a "key" and look up it's value, and the key may be a string, a number, or any other realistic data type. Examples: With a phone number, look up a name. (or with an area code, redirect to the server that handles that exchange) With an IP Address get a DNS name, or a Whois contact (string value) With a string, get an IP, ( like a DNS TXT or SRV record). I'm thinking out of the box here and looking for any software that allows for this. (more info below) Are there any secure, scalable DNS alternatives that have gained notoriety? I could ask on StackOverflow, but think the infrastructure groups would have better insight on this. Edit More info: I'm looking at "Namecoin" the DNS version of Bitcoin, and since that project is faltering, I'm looking at alternative ways to store name-value pairs, with an optional qualifier. I think a name value pair is of global interest is useful, but on a limited scale. Namecoin tried to be too much, and ended up becoming nothing. I'm trying to solve that problem in researching alternatives and applying distributed technologies where applicable. Bitcoin/Namecoin offers a Distributed Hash Table, which has some positive aspects, but not useful for DNS, except for root servers.

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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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  • SQLAuthority News – Mark the Date: October 16, 2013 – Introducing NuoDB Blackbirds: THE Distributed Database

    - by Pinal Dave
    I am very excited to announce first on this blog about the release of NuoDB Blackbirds (NuoDB Release 2.0). NuoDB is my favorite application to work with data now a days. They are increasingly gaining market share as well as brining out new features with their every new release. I was very excited when I learned that NuoDB is releasing their flagship release of 2.0 on October 16, 2013. Interesting enough I will be in USA while this release happens and I will be watching it live during my day time. Even though if I had to stay up the entire night to just watch this release, I would do it. Here is the details of the announcements: Introducing NuoDB Blackbirds: THE Distributed Database Date: October 16, 2013 Time: 1:00 PM EDT Location: Online Registration Link What is the best DBMS architecture to handle today’s and tomorrow’s evolving needs? The days of shared disk are over. The times are “a-changin” and IT infrastructure has to change with them. Join NuoDB live for the introduction of our latest major product release, NuoDB Blackbirds, and take a look at why the NuoDB distributed database architecture is the only answer for customers like Fathom Voice, a leading provider of Voice Over IP (VoIP). NuoDB CEO, Barry Morris, welcomes Cameron Weeks, CEO of Fathom Voice to discuss how his company is using DBMS to break away from the pack and become the hottest player in VoIP. The webcast will include demonstrations of a single, logical database running in multiple geographies and a live Q&A. If due to any reason, you cannot watch it live, do not worry at all, just register at this Registration Link, as after the event you will get the link to watch the event on-demand. You can watch the launch event at any time if you have registered for the launch. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: NuoDB

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  • Test Data in a Distributed System

    - by Davin Tryon
    A question that has been vexing me lately has been about how to effectively test (end-to-end) features in a distributed system. Particuarly, how to effectively manage (through time) test data for feature testing. The system in question is a typical SOA setup. The composition is done in JavaScript when call to several REST APIs. Each service is built as an independent block. Each service has some kind of persistent storage (SQL Server in most cases). The main issue at the moment is how to approach test data when testing end-to-end features. Functional end-to-end testing occurs through the UI, and it is therefore necessary for test data to be set up before the test run (this could be manual or automated testing). As is typical in a distributed system, identifiers from one service are used as a link in another service. So, some level of synchronization needs to be present in the data to effectively test. What is the best way to manage and set up this data after a successful deployment to a test environment? For example, is it better to manage this test data inside each service? Or package it together with the testing suite? Does that testing suite exist as a separate project? I'm interested in design guidance about how to store and manage this test data as the application features evolve.

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  • Distributed Rendering in the UDK and Unity

    - by N0xus
    At the moment I'm looking at getting a game engine to run in a CAVE environment. So far, during my research I've seen a lot of people being able to get both Unity and the Unreal engine up and running in a CAVE (someone did get CryEngine to work in one, but there is little research data about it). As of yet, I have not cemented my final choice of engine for use in the next stage of my project. I've experience in both, so the learning curve will be gentle on both. And both of the engines offer stereoscopic rendering, either already inbuilt with ReadD (Unreal) or by doing it yourself (Unity). Both can also make use of other input devices as well, such as the kinect or other devices. So again, both engines are still on the table. For the last bit of my preliminary research, I was advised to see if either, or both engines could do distributed rendering. I was advised this, as the final game we make could go into a variety of differently sized CAVEs. The one I have access to is roughly 2.4m x 3m cubed, and have been duly informed that this one is a "baby" compared to others. So, finally onto my question: Can either the Unreal Engine, or Unity Engine make it possible for developers to allow distributed rendering? Either through in built devices, or by creating my own plugin / script?

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  • Communication Between Different Technologies in a Distributed Application

    - by sjtaheri
    I had to a incorporate several legacy applications and services in a network-distributed application. The existing services and applications are written using different languages and technologies, including: java, C#.Net and C++; all running on MS Windows machines. Now I'm wondering about the communication mechanism between them. What is the simple and standard way? Thanks! PS. communications include simple message sending and remote method invocations.

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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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  • Discussion of a Distributed Data Storage implementation

    - by fegol
    I want to implement a distributed data storage using a client/server architecture. Each data item will be stored persistently in disk in one of several remote servers. The client uses a library to update and query the data, shielding the client from its actual location. This should allow a client to associate keys (String) to values(byte[]), much as a Map does. The system must ensure that the amount of data stored in each server is approximately the same. The set of servers is known beforehand by other servers and clients. Both the client and the server will be written in Java, using sockets, threads, and files. I open this topic with the objective of discussing the best way to implement this idea, assuming simplicity, what are the issues of this implementation, performance measurements and discussion of the limitations.

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  • Azure Futures - Distributed Computing and Number Crunching

    - by JoshReuben
    "the biggest Azure customers today are the ones using HPC on-premises at the current time" - http://www.zdnet.com/blog/microsoft/windows-azure-futures-turning-the-cloud-into-a-supercomputer/8592?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+zdnet%2Fmicrosoft+%28ZDNet+All+About+Microsoft%29&utm_content=Google+Reader   Orleans Framework for cloud computing - http://research.microsoft.com/en-us/projects/orleans     HPC on Azure - http://www.zdnet.com/blog/microsoft/microsoft-finalizes-its-latest-supercomputing-operating-system-release/7414   Dryad is Microsoft’s competitor to Google MapReduce and Apache Hadoop  - http://www.zdnet.com/blog/microsoft/microsoft-takes-a-step-toward-commercializing-its-dryad-distributed-computing-technologies/8255?tag=mantle_skin;content   SQL Server Analysis Services DataMining in the cloud - http://www.sqlmag.com/article/reporting2/azure-data-mining-in-the-cloud.aspx

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  • Distributed Computing - Hybrid Systems Considerations

    When the Cloud was new, it was often presented as an 'all or nothing' solution. Nowadays, the canny Systems Architect will exploit the best advantages of 'cloud' distributed computing in the right place, and use in-house services where most appropriate. So what are the issues that govern these architectural decisions? What can SQL Monitor 3.2 monitor?Whatever you think is most important. Use custom metrics to monitor and alert on data that's most important for your environment. Find out more.

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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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