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  • SQL SERVER – Concurrency Basics – Guest Post by Vinod Kumar

    - by pinaldave
    This guest post is by Vinod Kumar. Vinod Kumar has worked with SQL Server extensively since joining the industry over a decade ago. Working on various versions from SQL Server 7.0, Oracle 7.3 and other database technologies – he now works with the Microsoft Technology Center (MTC) as a Technology Architect. Let us read the blog post in Vinod’s own voice. Learning is always fun when it comes to SQL Server and learning the basics again can be more fun. I did write about Transaction Logs and recovery over my blogs and the concept of simplifying the basics is a challenge. In the real world we always see checks and queues for a process – say railway reservation, banks, customer supports etc there is a process of line and queue to facilitate everyone. Shorter the queue higher is the efficiency of system (a.k.a higher is the concurrency). Every database does implement this using checks like locking, blocking mechanisms and they implement the standards in a way to facilitate higher concurrency. In this post, let us talk about the topic of Concurrency and what are the various aspects that one needs to know about concurrency inside SQL Server. Let us learn the concepts as one-liners: Concurrency can be defined as the ability of multiple processes to access or change shared data at the same time. The greater the number of concurrent user processes that can be active without interfering with each other, the greater the concurrency of the database system. Concurrency is reduced when a process that is changing data prevents other processes from reading that data or when a process that is reading data prevents other processes from changing that data. Concurrency is also affected when multiple processes are attempting to change the same data simultaneously. Two approaches to managing concurrent data access: Optimistic Concurrency Model Pessimistic Concurrency Model Concurrency Models Pessimistic Concurrency Default behavior: acquire locks to block access to data that another process is using. Assumes that enough data modification operations are in the system that any given read operation is likely affected by a data modification made by another user (assumes conflicts will occur). Avoids conflicts by acquiring a lock on data being read so no other processes can modify that data. Also acquires locks on data being modified so no other processes can access the data for either reading or modifying. Readers block writer, writers block readers and writers. Optimistic Concurrency Assumes that there are sufficiently few conflicting data modification operations in the system that any single transaction is unlikely to modify data that another transaction is modifying. Default behavior of optimistic concurrency is to use row versioning to allow data readers to see the state of the data before the modification occurs. Older versions of the data are saved so a process reading data can see the data as it was when the process started reading and not affected by any changes being made to that data. Processes modifying the data is unaffected by processes reading the data because the reader is accessing a saved version of the data rows. Readers do not block writers and writers do not block readers, but, writers can and will block writers. Transaction Processing A transaction is the basic unit of work in SQL Server. Transaction consists of SQL commands that read and update the database but the update is not considered final until a COMMIT command is issued (at least for an explicit transaction: marked with a BEGIN TRAN and the end is marked by a COMMIT TRAN or ROLLBACK TRAN). Transactions must exhibit all the ACID properties of a transaction. ACID Properties Transaction processing must guarantee the consistency and recoverability of SQL Server databases. Ensures all transactions are performed as a single unit of work regardless of hardware or system failure. A – Atomicity C – Consistency I – Isolation D- Durability Atomicity: Each transaction is treated as all or nothing – it either commits or aborts. Consistency: ensures that a transaction won’t allow the system to arrive at an incorrect logical state – the data must always be logically correct.  Consistency is honored even in the event of a system failure. Isolation: separates concurrent transactions from the updates of other incomplete transactions. SQL Server accomplishes isolation among transactions by locking data or creating row versions. Durability: After a transaction commits, the durability property ensures that the effects of the transaction persist even if a system failure occurs. If a system failure occurs while a transaction is in progress, the transaction is completely undone, leaving no partial effects on data. Transaction Dependencies In addition to supporting all four ACID properties, a transaction might exhibit few other behaviors (known as dependency problems or consistency problems). Lost Updates: Occur when two processes read the same data and both manipulate the data, changing its value and then both try to update the original data to the new value. The second process might overwrite the first update completely. Dirty Reads: Occurs when a process reads uncommitted data. If one process has changed data but not yet committed the change, another process reading the data will read it in an inconsistent state. Non-repeatable Reads: A read is non-repeatable if a process might get different values when reading the same data in two reads within the same transaction. This can happen when another process changes the data in between the reads that the first process is doing. Phantoms: Occurs when membership in a set changes. It occurs if two SELECT operations using the same predicate in the same transaction return a different number of rows. Isolation Levels SQL Server supports 5 isolation levels that control the behavior of read operations. Read Uncommitted All behaviors except for lost updates are possible. Implemented by allowing the read operations to not take any locks, and because of this, it won’t be blocked by conflicting locks acquired by other processes. The process can read data that another process has modified but not yet committed. When using the read uncommitted isolation level and scanning an entire table, SQL Server can decide to do an allocation order scan (in page-number order) instead of a logical order scan (following page pointers). If another process doing concurrent operations changes data and move rows to a new location in the table, the allocation order scan can end up reading the same row twice. Also can happen if you have read a row before it is updated and then an update moves the row to a higher page number than your scan encounters later. Performing an allocation order scan under Read Uncommitted can cause you to miss a row completely – can happen when a row on a high page number that hasn’t been read yet is updated and moved to a lower page number that has already been read. Read Committed Two varieties of read committed isolation: optimistic and pessimistic (default). Ensures that a read never reads data that another application hasn’t committed. If another transaction is updating data and has exclusive locks on data, your transaction will have to wait for the locks to be released. Your transaction must put share locks on data that are visited, which means that data might be unavailable for others to use. A share lock doesn’t prevent others from reading but prevents them from updating. Read committed (snapshot) ensures that an operation never reads uncommitted data, but not by forcing other processes to wait. SQL Server generates a version of the changed row with its previous committed values. Data being changed is still locked but other processes can see the previous versions of the data as it was before the update operation began. Repeatable Read This is a Pessimistic isolation level. Ensures that if a transaction revisits data or a query is reissued the data doesn’t change. That is, issuing the same query twice within a transaction cannot pickup any changes to data values made by another user’s transaction because no changes can be made by other transactions. However, this does allow phantom rows to appear. Preventing non-repeatable read is a desirable safeguard but cost is that all shared locks in a transaction must be held until the completion of the transaction. Snapshot Snapshot Isolation (SI) is an optimistic isolation level. Allows for processes to read older versions of committed data if the current version is locked. Difference between snapshot and read committed has to do with how old the older versions have to be. It’s possible to have two transactions executing simultaneously that give us a result that is not possible in any serial execution. Serializable This is the strongest of the pessimistic isolation level. Adds to repeatable read isolation level by ensuring that if a query is reissued rows were not added in the interim, i.e, phantoms do not appear. Preventing phantoms is another desirable safeguard, but cost of this extra safeguard is similar to that of repeatable read – all shared locks in a transaction must be held until the transaction completes. In addition serializable isolation level requires that you lock data that has been read but also data that doesn’t exist. Ex: if a SELECT returned no rows, you want it to return no. rows when the query is reissued. This is implemented in SQL Server by a special kind of lock called the key-range lock. Key-range locks require that there be an index on the column that defines the range of values. If there is no index on the column, serializable isolation requires a table lock. Gets its name from the fact that running multiple serializable transactions at the same time is equivalent of running them one at a time. Now that we understand the basics of what concurrency is, the subsequent blog posts will try to bring out the basics around locking, blocking, deadlocks because they are the fundamental blocks that make concurrency possible. Now if you are with me – let us continue learning for SQL Server Locking Basics. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Concurrency

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  • Next in Concurrency

    - by Jatin
    For past year I have been working a lot on concurrency in Java and have build and worked on many concurrent packages. So in terms of development in the concurrent world, I am quite confident. Further I am very much interested to learn and understand more about concurrent programming. But I am unable to answer myself what next? What extra should I learn or work on to inherit more skills related to Multi-core processing. If there is any nice book (read and enjoyed 'concurrency in practice' and 'concurrent programming in java') or resource's related to Multi-core processing so that I can go to the next level?

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  • Requiring multithreading/concurrency for implementation of scripting language

    - by Ricky Stewart
    Here's the deal: I'm looking at designing my own scripting/interpreted language for fun. I'm only in the planning stages right now; I want to make sure I have a very strong hold on exactly how I will implement everything before I start coding. What I'm currently struggling with is concurrency. It seems to me like an easy way to avoid the unpredictable performance that comes with garbage collection would be to put the garbage collector in its own thread, and have it run concurrently with the interpreter itself. (To be clear, I don't plan to allow the scripts to be multithreaded themselves; I would simply put a garbage collector to work in a different thread than the interpreter.) This doesn't seem to be a common strategy for many popular scripting languages, probably for portability reasons; I would probably write the interpreter in the UNIX/POSIX threading framework initially and then port it to other platforms (Windows, etc.) if need be. Does anyone have any thoughts in this issue? Would whatever gains I receive by exploiting concurrency be nullified by the portability issues that will inevitably arise? (On that note, am I really correct in my assumption that I would experience great performance gains with a concurrent garbage collector?) Should I move forward with this strategy or step away from it?

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  • Queued Loadtest to remove Concurrency issues using Shared Data Service in OpenScript

    - by stefan.thieme(at)oracle.com
    Queued Processing to remove Concurrency issues in Loadtest ScriptsSome scripts act on information returned by the server, e.g. act on first item in the returned list of pending tasks/actions. This may lead to concurrency issues if the virtual users simulated in a load test scenario are not synchronized in some way.As the load test cases should be carried out in a comparable and straight forward manner simply cancel a transaction in case a collision occurs is clearly not an option. In case you increase the number of virtual users this approach would lead to a high number of requests for the early steps in your transaction (e.g. login, retrieve list of action points, assign an action point to the virtual user) but later steps would be rarely visited successfully or at all, depending on the application logic.A way to tackle this problem is to enqueue the virtual users in a Shared Data Service queue. Only the first virtual user in this queue will be allowed to carry out the critical steps (retrieve list of action points, assign an action point to the virtual user) in your transaction at any one time.Once a virtual user has passed the critical path it will dequeue himself from the head of the queue and continue with his actions. This does theoretically allow virtual users to run in parallel all steps of the transaction which are not part of the critical path.In practice it has been seen this is rarely the case, though it does not allow adding more than N users to perform a transaction without causing delays due to virtual users waiting in the queue. N being the time of the total transaction divided by the sum of the time of all critical steps in this transaction.While this problem can be circumvented by allowing multiple queues to act on individual segments of the list of actions, e.g. per country filter, ends with 0..9 filter, etc.This would require additional handling of these additional queues of slots for the virtual users at the head of the queue in order to maintain the mutually exclusive access to the first element in the list returned by the server at any one time of the load test. Such an improved handling of multiple queues and/or multiple slots is above the subject of this paper.Shared Data Services Pre-RequisitesStart WebLogic Server to host Shared Data ServicesYou will have to make sure that your WebLogic server is installed and started. Shared Data Services may not work if you installed only the minimal installation package for OpenScript. If however you installed the default package including OLT and OTM, you may follow the instructions below to start and verify WebLogic installation.To start the WebLogic Server deployed underneath of Oracle Load Testing and/or Oracle Test Manager you can go to your Start menu, Oracle Application Testing Suite and select the Restart Oracle Application Testing Suite Application Service entry from the Tools submenu.To verify the service has been started you can run the Microsoft Management Console for Services by Selecting Run from the Start Menu and entering services.msc. Look for the entry that reads Oracle Application Testing Suite Application Service, once it has changed it status from Starting to Started you can proceed to verify the login. Please note that this may take several minutes, I would say up to 10 minutes depending on the strength of your CPU horse-power.Verify WebLogic Server user credentialsYou will have to make sure that your WebLogic Server is installed and started. Next open the Oracle WebLogic Server Adminstration Console on http://localhost:8088/console.It may take a while until the application is deployed and started. It may display the following until the Administration Console has been deployed on the fly.Afterwards you can login using the username oats and the password that you selected during install time for your Application Testing Suite administrative purposes.This will bring up the Home page of you WebLogic Server. You have actually verified that you are able to login with these credentials already. However if you want to check the details, navigate to Security Realms, myrealm, Users and Groups tab.Here you could add users to your WebLogic Server which could be used in the later steps. Details on the Groups required for such a custom user to work are exceeding this quick overview and have to be selected with the WebLogic Server Adminstration Guide in mind.Shared Data Services pre-requisites for Load testingOpenScript Preferences have to be set to enable Encryption and provide a default Shared Data Service Connection for Playback.These are pre-requisites you want to use for load testing with Shared Data Services.Please note that the usage of the Connection Parameters (individual directive in the script) for Shared Data Services did not playback reliably in the current version 9.20.0370 of Oracle Load Testing (OLT) and encryption of credentials still seemed to be mandatory as well.General Encryption settingsSelect OpenScript Preferences from the View menu and navigate to the General, Encryption entry in the tree on the left. Select the Encrypt script data option from the list and enter the same password that you used for securing your WebLogic Server Administration Console.Enable global shared data access credentialsSelect OpenScript Preferences from the View menu and navigate to the Playback, Shared Data entry in the tree on the left. Enable the global shared data access credentials and enter the Address, User name and Password determined for your WebLogic Server to host Shared Data Services.Please note, that you may want to replace the localhost in Address with the hosts realname in case you plan to run load tests with Loadtest Agents running on remote systems.Queued Processing of TransactionsEnable Shared Data Services Module in Script PropertiesThe Shared Data Services Module has to be enabled for each Script that wants to employ the Shared Data Service Queue functionality in OpenScript. It can be enabled under the Script menu selecting Script Properties. On the Script Properties Dialog select the Modules section and check Shared Data to enable Shared Data Service Module for your script. Checking the Shared Data Services option will effectively add a line to your script code that adds the sharedData ScriptService to your script class of IteratingVUserScript.@ScriptService oracle.oats.scripting.modules.sharedData.api.SharedDataService sharedData;Record your scriptRecord your script as usual and then add the following things for Queue handling in the Initialize code block, before the first step and after the last step of your critical path and in the Finalize code block.The java code to be added at individual locations is explained in the following sections in full detail.Create a Shared Data Queue in InitializeTo create a Shared Data Queue go to the Java view of your script and enter the following statements to the initialize() code block.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);This will create an instantiation of the Shared Data Queue object named queueA which is maintained for upto 120 minutes.If you want to use the code for multiple scripts, make sure to use a different queue name for each one here and in the subsequent steps. You may even consider to use a dynamic queueName based on filters of your result list being concurrently accessed.Prepare a unique id for each IterationIn order to keep track of individual virtual users in our queue we need to create a unique identifier from the virtual user id and the used username right after retrieving the next record from our databank file.getDatabank("Usernames").getNextDatabankRecord();getVariables().set("usernameValue1","VU_{{@vuid}}_{{@iterationnum}}_{{db.Usernames.Username}}_{{@timestamp}}_{{@random(10000)}}");String usernameValue = getVariables().get("usernameValue1");info("Now running virtual user " + usernameValue);As you can see from the above code block, we have set the OpenScript variable usernameValue1 to VU_{{@vuid}}_{{@iterationnum}}_{{db.Usernames.Username}}_{{@timestamp}}_{{@random(10000)}} which is a concatenation of the virtual user id and the iterationnumber for general uniqueness; as well as the username from our databank, the timestamp and a random number for making it further unique and ease spotting of errors.Not all of these fields are actually required to make it really unique, but adding the queue name may also be considered to help troubleshoot multiple queues.The value is then retrieved with the getVariables.get() method call and assigned to the usernameValue String used throughout the script.Please note that moving the getDatabank("Usernames").getNextDatabankRecord(); call to the initialize block was later considered to remove concurrency of multiple virtual users running with the same userid and therefor accessing the same "My Inbox" in step 6. This will effectively give each virtual user a userid from the databank file. Make sure you have enough userids to remove this second hurdle.Enqueue and attend Queue before Critical PathTo maintain the right order of virtual users being allowed into the critical path of the transaction the following pseudo step has to be added in front of the first critical step. In the case of this example this is right in front of the step where we retrieve the list of actions from which we select the first to be assigned to us.beginStep("[0] Waiting in the Queue", 0);{info("Enqueued virtual user " + usernameValue + " at the end of queueA");sharedData.offerLast("queueA", usernameValue);info("Wait until the user is the first in queueA");String queueValue1 = null;do {// we wait for at least 0.7 seconds before we check the head of the// queue. This is the time it takes one user to move through the// critical path, i.e. pass steps [5] Enter country and [6] Assign// to meThread.sleep(700);queueValue1 = (String) sharedData.peekFirst("queueA");info("The first user in queueA is currently: '" + queueValue1 + "' " + queueValue1.getClass() + " length " + queueValue1.length() );info("The current user is '"+ usernameValue + "' " + usernameValue.getClass() + " length " + usernameValue.length() + ": indexOf " + usernameValue.indexOf(queueValue1) + " equals " + usernameValue.equals(queueValue1) );} while ( queueValue1.indexOf(usernameValue) < 0 );info("Now the user is the first in queueA");}endStep();This will enqueue the username to the tail of our Queue. It will will wait for at least 700 milliseconds, the time it takes for one user to exit the critical path and then compare the head of our queue with it's username. This last step will be repeated while the two are not equal (indexOf less than zero). If they are equal the indexOf will yield a value of zero or larger and we will perform the critical steps.Dequeue after Critical PathAfter the virtual user has left the critical path and complete its last step the following code block needs to dequeue the virtual user. In the case of our example this is right after the action has been actually assigned to the virtual user. This will allow the next virtual user to retrieve the list of actions still available and in turn let him make his selection/assignment.info("Get and remove the current user from the head of queueA");String pollValue1 = (String) sharedData.pollFirst("queueA");The current user is removed from the head of the queue. The next one will now be able to match his username against the head of the queue.Clear and Destroy Queue for FinishWhen the script has completed, it should clear and destroy the queue. This code block can be put in the finish block of your script and/or in a separate script in order to clear and remove the queue in case you have spotted an error or want to reset the queue for some reason.info("Clear queueA");sharedData.clearQueue("queueA");info("Destroy queueA");sharedData.destroyQueue("queueA");The users waiting in queueA are cleared and the queue is destroyed. If you have scripts still executing they will be caught in a loop.I found it better to maintain a separate Reset Queue script which contained only the following code in the initialize() block. I use to call this script to make sure the queue is cleared in between multiple Loadtest runs. This script could also even be added as the first in a larger scenario, which would execute it only once at very start of the Loadtest and make sure the queues do not contain any stale entries.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);info("Clear queueA");sharedData.clearQueue("queueA");This will create a Shared Data Queue instance of queueA and clear all entries from this queue.Monitoring QueueWhile creating the scripts it was useful to monitor the contents, i.e. the current first user in the Queue. The following code block will make sure the Shared Data Queue is accessible in the initialize() block.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);In the run() block the following code will continuously monitor the first element of the Queue and write an informational message with the current username Value to the Result window.info("Monitor the first users in queueA");String queueValue1 = null;do {queueValue1 = (String) sharedData.peekFirst("queueA");if (queueValue1 != null)info("The first user in queueA is currently: '" + queueValue1 + "' " + queueValue1.getClass() + " length " + queueValue1.length() );} while ( true );This script can be run from OpenScript parallel to a loadtest performed by the Oracle Load Test.However it is not recommend to run this in a production loadtest as the performance impact is unknown. Accessing the Queue's head with the peekFirst() method has been reported with about 2 seconds response time by both OpenScript and OTL. It is advised to log a Service Request to see if this could be lowered in future releases of Application Testing Suite, as the pollFirst() and even offerLast() writing to the tail of the Queue usually returned after an average 0.1 seconds.Debugging QueueWhile debugging the scripts the following was useful to remove single entries from its head, i.e. the current first user in the Queue. The following code block will make sure the Shared Data Queue is accessible in the initialize() block.info("Create queueA with life time of 120 minutes");sharedData.createQueue("queueA", 120);In the run() block the following code will remove the first element of the Queue and write an informational message with the current username Value to the Result window.info("Get and remove the current user from the head of queueA");String pollValue1 = (String) sharedData.pollFirst("queueA");info("The first user in queueA was currently: '" + pollValue1 + "' " + pollValue1.getClass() + " length " + pollValue1.length() );ReferencesOracle Functional Testing OpenScript User's Guide Version 9.20 [E15488-05]Chapter 17 Using the Shared Data Modulehttp://download.oracle.com/otn/nt/apptesting/oats-docs-9.21.0030.zipOracle Fusion Middleware Oracle WebLogic Server Administration Console Online Help 11g Release 1 (10.3.4) [E13952-04]Administration Console Online Help - Manage users and groupshttp://download.oracle.com/docs/cd/E17904_01/apirefs.1111/e13952/taskhelp/security/ManageUsersAndGroups.htm

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  • Concurrency checking with Last Change Time

    - by Lijo
    I have a following three tables Email (emailNumber, Address) Recipients (reportNumber, emailNumber, lastChangeTime) Report (reportNumber, reportName) I have a C# application that uses inline queries for data selection. I have a select query that selects all reports and their Recipients. Recipients are selected as comma separacted string. During updating, I need to check concurrency. Currently I am using MAX(lastChangeTime) for each reportNumber. This is selected as maxTime. Before update, it checks that the lastChangeTime <= maxTime. --//It works fine One of my co-developers asked why not use GETDATE() as “maxTime” rather than using a MAX operation. That is also working. Here what we are checking is the records are not updated after the record selection time. Is there any pitfalls in using GETDATE() for this purpose?

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  • Concurrency Violation in NHibernate( c#) example

    - by vijaysylvester
    For quite some time , I was reading about the optimistic concurrency in NHibernate. If what i understood was correct then the below sample should hold good. Consider two transactions T1 and T2. When T1 and T2 are done simultaneously , the state(DB entries) gets updated with the values of the most latest update.(T1 or T2). Though it seems to be conceptually sound , how do i simulate this for the purpose of understanding and integration testing.? Can someone help me with a sample c# code.? Thanks , vijay

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  • Issues in Ada Concurrency

    - by Arkapravo
    Hi I need some help and also some insight. This is a program in Ada-2005 which has 3 tasks. The output is 'z'. If the 3 tasks do not happen in the order of their placement in the program then output can vary from z = 2, z = 1 to z = 0 ( That is easy to see in the program, mutual exclusion is attempted to make sure output is z = 2). WITH Ada.Text_IO; USE Ada.Text_IO; WITH Ada.Integer_Text_IO; USE Ada.Integer_Text_IO; WITH System; USE System; procedure xyz is x : Integer := 0; y : Integer := 0; z : Integer := 0; task task1 is pragma Priority(System.Default_Priority + 3); end task1; task task2 is pragma Priority(System.Default_Priority + 2); end task2; task task3 is pragma Priority(System.Default_Priority + 1); end task3; task body task1 is begin x := x + 1; end task1; task body task2 is begin y := x + y; end task2; task body task3 is begin z := x + y + z; end task3; begin Put(" z = "); Put(z); end xyz; I first tried this program (a) without pragmas, the result : In 100 tries, occurence of 2: 86, occurence of 1: 10, occurence of 0: 4. Then (b) with pragmas, the result : In 100 tries, occurence of 2: 84, occurence of 1 : 14, occurence of 0: 2. Which is unexpected as the 2 results are nearly identical. Which means pragmas or no pragmas the output has same behavior. Those who are Ada concurrency Gurus please shed some light on this topic. Alternative solutions with semaphores (if possible) is also invited. Further in my opinion for a critical process (that is what we do with Ada), with pragmas the result should be z = 2, 100% at all times, hence or otherwise this program should be termed as 85% critical !!!! (That should not be so with Ada)

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  • Static objects and concurrency in a web application

    - by Ionut
    I'm developing small Java Web Applications on Tomcat server and I'm using MySQL as my database. Up until now I was using a connection singleton for accessing the database but I found out that this will ensure just on connection per Application and there will be problems if multiple users want to access the database in the same time. (They all have to make us of that single Connection object). I created a Connection Pool and I hope that this is the correct way of doing things. Furthermore it seems that I developed the bad habit of creating a lot of static object and static methods (mainly because I was under the wrong impression that every static object will be duplicated for every client which accesses my application). Because of this all the Service Classes ( classes used to handle database data) are static and distributed through a ServiceFactory: public class ServiceFactory { private static final String JDBC = "JDBC"; private static String impl; private static AccountService accountService; private static BoardService boardService; public static AccountService getAccountService(){ initConfig(); if (accountService == null){ if (impl.equalsIgnoreCase(JDBC)){ accountService = new JDBCAccountService(); } } return accountService; } public static BoardService getBoardService(){ initConfig(); if (boardService == null){ if (impl.equalsIgnoreCase(JDBC)){ boardService = new JDBCBoardService(); } } return boardService; } private static void initConfig(){ if (StringUtil.isEmpty(impl)){ impl = ConfigUtil.getProperty("service.implementation"); // If the config failed initialize with standard if (StringUtil.isEmpty(impl)){ impl = JDBC; } } } This was the factory class which, as you can see, allows just one Service to exist at any time. Now, is this a bad practice? What happens if let's say 1k users access AccountService simultaneously? I know that all this questions and bad practices come from a bad understanding of the static attribute in a web application and the way the server handles this attributes. Any help on this topic would be more than welcomed. Thank you for your time!

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  • How to handle concurrency in Entity Framework

    - by nikolaosk
    This is going to be the fifth post of a series of posts regarding ASP.Net and the Entity Framework and how we can use Entity Framework to access our datastore. You can find the first one here , the second one here and the third one here . You can read the fourth one here . I have a post regarding ASP.Net and EntityDataSource. You can read it here .I have 3 more posts on Profiling Entity Framework applications. You can have a look at them here , here and here . In this post I will be looking into...(read more)

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  • Concurrency and Coordination Runtime (CCR) Learning Resources

    - by Harry
    I have recently been learning the in's and out's of the Concurrency and Coordination Runtime (CCR). Finding good learning resources for this relatively new technology has been quite difficult. (A quick google search brings up "Creedence Clearwater Revival" as the top result!) Some of the resources I have found: Free e-book chapter from WROX on the Robotics Developer Studio Good Article/post on InfoQ Robotic's Member blog Very active MSDN CCR Forum - Got plenty of help from here! Great MSDN Magazine by Jeffrey Richter Official CCR User Guide - Didn't find this very helpful Great blogging series on CCR iodyner CCR Related Blog - Update: Moved to here Eight or so Videos on Channel9.msdn.com CCR Patterns page on MS Robotics Studio - I haven't read this yet 4 x CCR Questions on Stackoverflow - Most of the questions have been Mine! LOL CCR and DSS toolkit has now been released to MSDN Members Do you have any good learning resources for the CCR? I really hope that Microsoft will publish more material, so far it has been too Robotics specific. I believe that MS needs to acknowledge that most people are using the CCR in issolation from the DSS and Robotics Studio. Update The Mix 2010 conference had a presentation by Myspace about how they have used the CCR framework in their middle tier. They also open sourced the code base. MySpace DataRelay Mix Video Presentation

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  • Are these advanced/unfair interview questions regarding Java concurrency?

    - by sparc_spread
    Here are some questions I've recently asked interviewees who say they know Java concurrency: Explain the hazard of "memory visibility" - the way the JVM can reorder certain operations on variables that are unprotected by a monitor and not declared volatile, such that one thread may not see the changes made by another thread. Usually I ask this one by showing code where this hazard is present (e.g. the NoVisibility example in Listing 3.1 from "Java Concurrency in Practice" by Goetz et al) and asking what is wrong. Explain how volatile affects not just the actual variable declared volatile, but also any changes to variables made by a thread before it changes the volatile variable. Why might you use volatile instead of synchronized? Implement a condition variable with wait() and notifyAll(). Explain why you should use notifyAll(). Explain why the condition variable should be tested with a while loop. My question is - are these appropriate or too advanced to ask someone who says they know Java concurrency? And while we're at it, do you think that someone working in Java concurrency should be expected to have an above-average knowledge of Java garbage collection?

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  • Linq to SQL and concurrency with Rob Conery repository pattern

    - by David Hall
    I have implemented a DAL using Rob Conery's spin on the repository pattern (from the MVC Storefront project) where I map database objects to domain objects using Linq and use Linq to SQL to actually get the data. This is all working wonderfully giving me the full control over the shape of my domain objects that I want, but I have hit a problem with concurrency that I thought I'd ask about here. I have concurrency working but the solution feels like it might be wrong (just one of those gitchy feelings). The basic pattern is: private MyDataContext _datacontext private Table _tasks; public Repository(MyDataContext datacontext) { _dataContext = datacontext; } public void GetTasks() { _tasks = from t in _dataContext.Tasks; return from t in _tasks select new Domain.Task { Name = t.Name, Id = t.TaskId, Description = t.Description }; } public void SaveTask(Domain.Task task) { Task dbTask = null; // Logic for new tasks omitted... dbTask = (from t in _tasks where t.TaskId == task.Id select t).SingleOrDefault(); dbTask.Description = task.Description, dbTask.Name = task.Name, _dataContext.SubmitChanges(); } So with that implementation I've lost concurrency tracking because of the mapping to the domain task. I get it back by storing the private Table which is my datacontext list of tasks at the time of getting the original task. I then update the tasks from this stored Table and save what I've updated This is working - I get change conflict exceptions raised when there are concurrency violations, just as I want. However, it just screams to me that I've missed a trick. Is there a better way of doing this? I've looked at the .Attach method on the datacontext but that appears to require storing the original version in a similar way to what I'm already doing. I also know that I could avoid all this by doing away with the domain objects and letting the Linq to SQL generated objects all the way up my stack - but I dislike that just as much as I dislike the way I'm handling concurrency.

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  • Google I/O 2012 - Go Concurrency Patterns

    Google I/O 2012 - Go Concurrency Patterns Rob Pike Concurrency is the key to designing high performance network services. Go's concurrency primitives (goroutines and channels) provide a simple and efficient means of expressing concurrent execution. In this talk we see how tricky concurrency problems can be solved gracefully with simple Go code. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 169 2 ratings Time: 51:27 More in Science & Technology

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  • Parallelism implies concurrency but not the other way round right?

    - by Cedric Martin
    I often read that parallelism and concurrency are different things. Very often the answerers/commenters go as far as writing that they're two entirely different things. Yet in my view they're related but I'd like some clarification on that. For example if I'm on a multi-core CPU and manage to divide the computation into x smaller computation (say using fork/join) each running in its own thread, I'll have a program that is both doing parallel computation (because supposedly at any point in time several threads are going to run on several cores) and being concurrent right? While if I'm simply using, say, Java and dealing with UI events and repaints on the Event Dispatch Thread plus running the only thread I created myself, I'll have a program that is concurrent (EDT + GC thread + my main thread etc.) but not parallel. I'd like to know if I'm getting this right and if parallelism (on a "single but multi-cores" system) always implies concurrency or not? Also, are multi-threaded programs running on multi-cores CPU but where the different threads are doing totally different computation considered to be using "parallelism"?

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  • Concurrency Utilities for Java EE Early Draft (JSR 236)

    - by arungupta
    Concurrency Utilities for Java EE is being worked as JSR 236 and has released an Early Draft. It provides concurrency capabilities to Java EE application components without compromising container integrity. Simple (common) and advanced concurrency patterns are easily supported without sacrificing usability. Using Java SE concurrency utilities such as java.util.concurrent API, java.lang.Thread and java.util.Timer in a Java EE application component such as EJB or Servlet are problematic since the container and server have no knowledge of these resources. JSR 236 enables concurrency largely by extending the Concurrency Utilities API developed under JSR-166. This also allows a consistency between Java SE and Java EE concurrency programming model. There are four main programming interfaces available: ManagedExecutorService ManagedScheduledExecutorService ContextService ManagedThreadFactory ManagedExecutorService is a managed version of java.util.concurrent.ExecutorService. The implementations of this interface are provided by the container and accessible using JNDI reference: <resource-env-ref>  <resource-env-ref-name>    concurrent/BatchExecutor  </resource-env-ref-name>  <resource-env-ref-type>    javax.enterprise.concurrent.ManagedExecutorService  </resource-env-ref-type><resource-env-ref> and available as: @Resource(name="concurrent/BatchExecutor")ManagedExecutorService executor; Its recommended to bind the JNDI references in the java:comp/env/concurrent subcontext. The asynchronous tasks that need to be executed need to implement java.lang.Runnable or java.util.concurrent.Callable interface as: public class MyTask implements Runnable { public void run() { // business logic goes here }} OR public class MyTask2 implements Callable<Date> {  public Date call() { // business logic goes here   }} The task is then submitted to the executor using one of the submit method that return a Future instance. The Future represents the result of the task and can also be used to check if the task is complete or wait for its completion. Future<String> future = executor.submit(new MyTask(), String.class);. . .String result = future.get(); Another example to submit tasks is: class MyTask implements Callback<Long> { . . . }class MyTask2 implements Callback<Date> { . . . }ArrayList<Callable> tasks = new ArrayList<();tasks.add(new MyTask());tasks.add(new MyTask2());List<Future<Object>> result = executor.invokeAll(tasks); The ManagedExecutorService may be configured for different properties such as: Hung Task Threshold: Time in milliseconds that a task can execute before it is considered hung Pool Info Core Size: Number of threads to keep alive Maximum Size: Maximum number of threads allowed in the pool Keep Alive: Time to allow threads to remain idle when # of threads > Core Size Work Queue Capacity: # of tasks that can be stored in inbound buffer Thread Use: Application intend to run short vs long-running tasks, accordingly pooled or daemon threads are picked ManagedScheduledExecutorService adds delay and periodic task running capabilities to ManagedExecutorService. The implementations of this interface are provided by the container and accessible using JNDI reference: <resource-env-ref>  <resource-env-ref-name>    concurrent/BatchExecutor  </resource-env-ref-name>  <resource-env-ref-type>    javax.enterprise.concurrent.ManagedExecutorService  </resource-env-ref-type><resource-env-ref> and available as: @Resource(name="concurrent/timedExecutor")ManagedExecutorService executor; And then the tasks are submitted using submit, invokeXXX or scheduleXXX methods. ScheduledFuture<?> future = executor.schedule(new MyTask(), 5, TimeUnit.SECONDS); This will create and execute a one-shot action that becomes enabled after 5 seconds of delay. More control is possible using one of the newly added methods: MyTaskListener implements ManagedTaskListener {  public void taskStarting(...) { . . . }  public void taskSubmitted(...) { . . . }  public void taskDone(...) { . . . }  public void taskAborted(...) { . . . } }ScheduledFuture<?> future = executor.schedule(new MyTask(), 5, TimeUnit.SECONDS, new MyTaskListener()); Here, ManagedTaskListener is used to monitor the state of a task's future. ManagedThreadFactory provides a method for creating threads for execution in a managed environment. A simple usage is: @Resource(name="concurrent/myThreadFactory")ManagedThreadFactory factory;. . .Thread thread = factory.newThread(new Runnable() { . . . }); concurrent/myThreadFactory is a JNDI resource. There is lot of interesting content in the Early Draft, download it, and read yourself. The implementation will be made available soon and also be integrated in GlassFish 4 as well. Some references for further exploring ... Javadoc Early Draft Specification concurrency-ee-spec.java.net [email protected]

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  • How to run concurrency unit test?

    - by janetsmith
    Hi, How to use junit to run concurrency test? Let's say I have a class public class MessageBoard { public synchronized void postMessage(String message) { .... } public void updateMessage(Long id, String message) { .... } } I wan to test multiple access to this postMessage concurrently. Any advice on this? I wish to run this kind of concurrency test against all my setter functions (or any methodn that involves create/update/delete operation). Thanks

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  • Practical approach to concurrency control

    - by Industrial
    Hi everyone, I'd read this article recently and are very interested on how to make a practical approach to Concurrency control on a web server. The server will run CentOS + PHP + mySQL with Memcached. How would you set it up to work? http://saasinterrupted.com/2010/02/05/high-availability-principle-concurrency-control/ Thanks!

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  • java concurrency assignments

    - by dev
    I am JEE developer, and I want to get skills on concurrency development. Could you provide me some assignments, ideas, or other - just for learning and training concurrency programming? Thanks!

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  • Postfix, limit destination concurrency

    - by Hamlet
    Hi, Website sending email using phpmailer - Centos, postfix, php, mysql etc Emails are getting delivered to all hosts correctly except one. Mar 30 14:38:22 server postfix/qmgr[15467]: 7237D218852D: to=, relay=none, delay=0.04, delays=0.04/0.01/0/0, dsn=4.4.2, status=deferred (delivery temporarily suspended: lost connection with mail06.indamail.hu[91.83.45.46] while sending MAIL FROM) They told me to limit concurrent connections to 2 to their server. I did, but they still say I connect more than twice. main.cf: default_destination_concurrency_limit = 1 fallback_relay = smtp_destination_concurrency_limit = 1 initial_destination_concurrency = 1 Any ideas? Thanks, Hamlet

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  • postfix concurrency limit with round robin dns

    - by goose
    Take the following internal round robin dns setup mymta.com. IN A 172.31.1.1 mymta.com. IN A 172.31.1.2 mymta.com. IN A 172.31.1.3 mymta.com. IN A 172.31.1.4 mymta.com. IN A 172.31.1.5 mymta.com. IN A 172.31.1.6 mymta.com. IN A 172.31.1.7 mymta.com. IN A 172.31.1.8 mymta.com. IN A 172.31.1.9 mymta.com. IN A 172.31.1.10 Now assume the following postfix setup (assume these are the only tweaks from defaults in debian package) main.cf: smtp_connection_cache_destinations = mymta.com smtp_connection_cache_reuse_limit = 750 smtp_destination_concurrency_limit = 75 transport * :[mymta.com] I would expect 75 concurrent connections spread across the 10 A records I've set in DNS. However I'm seeing more than a few hundred connections to mymta.com and I'm wondering if Postfix is "smart" enough to set up 75 concurrent connections for each IP address. Thoughts?

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  • postfix destination concurrency

    - by Hamlet
    Hi, I have a website sending email using phpmailer - Centos, postfix, php, mysql etc Emails are getting delivered to all hosts correctly except one. Mar 30 14:38:22 server postfix/qmgr[15467]: 7237D218852D: to=, relay=none, delay=0.04, delays=0.04/0.01/0/0, dsn=4.4.2, status=deferred (delivery temporarily suspended: lost connection with mail06.indamail.hu[91.83.45.46] while sending MAIL FROM) They told me to limit concurrent connections to 2 to their server. I did, but they still say I connect more than twice. main.cf: default_destination_concurrency_limit = 1 fallback_relay = smtp_destination_concurrency_limit = 1 initial_destination_concurrency = 1 Any ideas? Thanks, Hamlet

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  • ASP.NET MVC Concurrency with RowVersion in Edit Action

    - by Jorin
    I'm wanting to do a simple edit form for our Issue Tracking app. For simplicity, the HttpGet Edit action looks something like this: // Issues/Edit/12 public ActionResult Edit(int id) { var thisIssue = edmx.Issues.First(i => i.IssueID == id); return View(thisIssue); } and then the HttpPost action looks something like this: [HttpPost] public ActionResult Edit(int id, FormCollection form) { // this is the dumb part where I grab the object before I update it. // concurrency is sidestepped here. var thisIssue = edmx.Issues.Single(c => c.IssueID == id); TryUpdateModel(thisIssue); if (ModelState.IsValid) { edmx.SaveChanges(); TempData["message"] = string.Format("Issue #{0} successfully modified.", id); return RedirectToAction("Index"); } return View(thisIssue); } Which works wonderfully. However, the concurrency check doesn't work because in the Post, I'm re-retreiving the current entity right before I attempt to update it. However, with EF, I don't know how to use the fanciness of SaveChanges() but attach my thisIssue to the context. I tried to call edmx.Issues.Attach(thisIssue) but I get The object cannot be attached because it is already in the object context. An object can only be reattached when it is in an unchanged state. How do I handle concurrency in MVC with EF and/or how do I properly Attach my edited object to the context? Thanks in advance

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  • Microeconomical simulation: coordination/planning between self-interested trading agents

    - by Milton Manfried
    In a typical perfect-information strategy game like Chess, an agent can calculate its best move by searching the state tree for the best possible move, while assuming that the opponent will also make the best possible move (i.e. Mini-max). I would like to use this approach in a "game" modeling economic activity, where the possible "moves" would be to buy or sell for a given price, and the goal, rather than a specific class of states (e.g. Checkmate), would be to maximize some function F of the agent's state (e.g. F(money, widget) = 10*money + widget). How to handle buy/sell actions that require coordination between both parties, at the very least agreement upon a price? The cheap way out would be to set the price beforehand, maybe based upon the current supply -- but the idea of this simulation is to examine how prices emerge when freely determined by "perfectly rational" agents. A great example of what I do not want is the trading algorithm in SugarScape -- paraphrasing from Growing Artificial Societies p101-102: when a pair of agents interact to trade, they each compute their internal valuations of the goods, then a bargaining process is conducted and a price is agreed to. If this price makes both agents better off, they complete the transaction The protocol itself is beautiful, but what it cannot capture (as far as I can tell) is the ability for an agent to pay more than it might otherwise for a good, because it knows that it can sell it for even more at a later date -- what appears to be called "strategic thinking" in this pape at Google Books Multi-Agent-Based Simulation III: 4th International Workshop, MABS 2003... to get realistic behavior like that, it seems one would either (1) have to build an outrageously-complex internal valuation system which could at best only cover situations that were planned for at compile-time, or otherwise (2) have some mechanism to search the state tree... which would require some way of planning future trades. Note: The chess analogy only works as far as the state-space search goes; the simulation isn't intended to be "zero sum", so a literal mini-max search wouldn't be appropriate -- and ideally, it should work with more than two agents.

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