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  • Get Trained in Storage

    - by mseika
    Oracle University has scheduled the following OPN Only Storage course: Course: Pillar Axiom 600 Install and MaxRep Replication Dates:         14-18 Jul 2014                     27-31 Oct 2014 Location:    Edinburgh You will gain the knowledge and skills necessary to install, administer, configure, and maintain Pillar Axiom 600 SAN Storage and Pillar Axiom MaxRep Replication. More details and online registration Remember: your OPN discount will be applied to the standard prices shown on Oracle University web pages. For assistance in booking and more information, contact the Oracle University Service Desk: eMail: [email protected] Telephone: 01 189 249 066

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  • Shared storage for web cluster

    - by user52475
    Hi all! Have a big question about shared/clustered/distributed file system for storage. It will shared storage for shared web hosting (web files + maildir) and OpenVZ containers storage . Have any one working example of such system? The options are: Lustre GFS1/GFS2 - GFS2 - as I understand is EXPERIMENTAL... NFS This 3 systems which I consider for shared storage. Now I have storage with HW RAID 10 - 1TB. NFS - As I know there will be problem with locking? GFS/Lustre - problems when there will be a lot of small files , what is typical for hosting environment and problems with maildir.

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  • Achieve Named Criteria with multiple tables in EJB Data control

    - by Deepak Siddappa
    In EJB create a named criteria using sparse xml and in named criteria wizard, only attributes related to the that particular entities will be displayed.  So here we can filter results only on particular entity bean. Take a scenario where we need to create Named Criteria based on multiple tables using EJB. In BC4J we can achieve this by creating view object based on multiple tables. So in this article, we will try to achieve named criteria based on multiple tables using EJB.Implementation StepsCreate Java EE Web Application with entity based on Departments and Employees, then create a session bean and data control for the session bean.Create a Java Bean, name as CustomBean and add below code to the file. Here in java bean from both Departments and Employees tables three fields are taken. public class CustomBean { private BigDecimal departmentId; private String departmentName; private BigDecimal locationId; private BigDecimal employeeId; private String firstName; private String lastName; public CustomBean() { super(); } public void setDepartmentId(BigDecimal departmentId) { this.departmentId = departmentId; } public BigDecimal getDepartmentId() { return departmentId; } public void setDepartmentName(String departmentName) { this.departmentName = departmentName; } public String getDepartmentName() { return departmentName; } public void setLocationId(BigDecimal locationId) { this.locationId = locationId; } public BigDecimal getLocationId() { return locationId; } public void setEmployeeId(BigDecimal employeeId) { this.employeeId = employeeId; } public BigDecimal getEmployeeId() { return employeeId; } public void setFirstName(String firstName) { this.firstName = firstName; } public String getFirstName() { return firstName; } public void setLastName(String lastName) { this.lastName = lastName; } public String getLastName() { return lastName; } } Open the sessionEJb file and add the below code to the session bean and expose the method in local/remote interface and generate a data control for that. Note:- Here in the below code "em" is a EntityManager. public List<CustomBean> getCustomBeanFindAll() { String queryString = "select d.department_id, d.department_name, d.location_id, e.employee_id, e.first_name, e.last_name from departments d, employees e\n" + "where e.department_id = d.department_id"; Query genericSearchQuery = em.createNativeQuery(queryString, "CustomQuery"); List resultList = genericSearchQuery.getResultList(); Iterator resultListIterator = resultList.iterator(); List<CustomBean> customList = new ArrayList(); while (resultListIterator.hasNext()) { Object col[] = (Object[])resultListIterator.next(); CustomBean custom = new CustomBean(); custom.setDepartmentId((BigDecimal)col[0]); custom.setDepartmentName((String)col[1]); custom.setLocationId((BigDecimal)col[2]); custom.setEmployeeId((BigDecimal)col[3]); custom.setFirstName((String)col[4]); custom.setLastName((String)col[5]); customList.add(custom); } return customList; } Open the DataControls.dcx file and create sparse xml for customBean. In sparse xml navigate to Named criteria tab -> Bind Variable section, create two binding variables deptId,fName. In sparse xml navigate to Named criteria tab ->Named criteria, create a named criteria and map the query attributes to the bind variables. In the ViewController create a file jspx page, from data control palette drop customBeanFindAll->Named Criteria->CustomBeanCriteria->Query as ADF Query Panel with Table. Run the jspx page and enter values in search form with departmentId as 50 and firstName as "M". Named criteria will filter the query of a data source and display the result like below.

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  • Shouldn't storage classes be taught early in a C class or book?

    - by Adam Mendoza
    Shouldn't storage classes be taught early in a C class or book? I notice that a lot of books, even some of the better ones, covert it toward and end of the book and some books just add it as an appendix. I would teach it together with variables. This is so foundational and I think unfortunately many do not make it that far in a book. Now that auto has a different meaning (vs being optional) it may confuse people that didn't realize it has always been there. for example: C Programming: A Modern Approach 18.2 Storage Classes 401 Properties of Variables 401 The auto Storage Class 402 The static Storage Class 403 The extern Storage Class 404 The register Storage Class 405 The Storage Class of a Function 406 Summary 407

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  • How to Load Oracle Tables From Hadoop Tutorial (Part 5 - Leveraging Parallelism in OSCH)

    - by Bob Hanckel
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Using OSCH: Beyond Hello World In the previous post we discussed a “Hello World” example for OSCH focusing on the mechanics of getting a toy end-to-end example working. In this post we are going to talk about how to make it work for big data loads. We will explain how to optimize an OSCH external table for load, paying particular attention to Oracle’s DOP (degree of parallelism), the number of external table location files we use, and the number of HDFS files that make up the payload. We will provide some rules that serve as best practices when using OSCH. The assumption is that you have read the previous post and have some end to end OSCH external tables working and now you want to ramp up the size of the loads. Using OSCH External Tables for Access and Loading OSCH external tables are no different from any other Oracle external tables.  They can be used to access HDFS content using Oracle SQL: SELECT * FROM my_hdfs_external_table; or use the same SQL access to load a table in Oracle. INSERT INTO my_oracle_table SELECT * FROM my_hdfs_external_table; To speed up the load time, you will want to control the degree of parallelism (i.e. DOP) and add two SQL hints. ALTER SESSION FORCE PARALLEL DML PARALLEL  8; ALTER SESSION FORCE PARALLEL QUERY PARALLEL 8; INSERT /*+ append pq_distribute(my_oracle_table, none) */ INTO my_oracle_table SELECT * FROM my_hdfs_external_table; There are various ways of either hinting at what level of DOP you want to use.  The ALTER SESSION statements above force the issue assuming you (the user of the session) are allowed to assert the DOP (more on that in the next section).  Alternatively you could embed additional parallel hints directly into the INSERT and SELECT clause respectively. /*+ parallel(my_oracle_table,8) *//*+ parallel(my_hdfs_external_table,8) */ Note that the "append" hint lets you load a target table by reserving space above a given "high watermark" in storage and uses Direct Path load.  In other doesn't try to fill blocks that are already allocated and partially filled. It uses unallocated blocks.  It is an optimized way of loading a table without incurring the typical resource overhead associated with run-of-the-mill inserts.  The "pq_distribute" hint in this context unifies the INSERT and SELECT operators to make data flow during a load more efficient. Finally your target Oracle table should be defined with "NOLOGGING" and "PARALLEL" attributes.   The combination of the "NOLOGGING" and use of the "append" hint disables REDO logging, and its overhead.  The "PARALLEL" clause tells Oracle to try to use parallel execution when operating on the target table. Determine Your DOP It might feel natural to build your datasets in Hadoop, then afterwards figure out how to tune the OSCH external table definition, but you should start backwards. You should focus on Oracle database, specifically the DOP you want to use when loading (or accessing) HDFS content using external tables. The DOP in Oracle controls how many PQ slaves are launched in parallel when executing an external table. Typically the DOP is something you want to Oracle to control transparently, but for loading content from Hadoop with OSCH, it's something that you will want to control. Oracle computes the maximum DOP that can be used by an Oracle user. The maximum value that can be assigned is an integer value typically equal to the number of CPUs on your Oracle instances, times the number of cores per CPU, times the number of Oracle instances. For example, suppose you have a RAC environment with 2 Oracle instances. And suppose that each system has 2 CPUs with 32 cores. The maximum DOP would be 128 (i.e. 2*2*32). In point of fact if you are running on a production system, the maximum DOP you are allowed to use will be restricted by the Oracle DBA. This is because using a system maximum DOP can subsume all system resources on Oracle and starve anything else that is executing. Obviously on a production system where resources need to be shared 24x7, this can’t be allowed to happen. The use cases for being able to run OSCH with a maximum DOP are when you have exclusive access to all the resources on an Oracle system. This can be in situations when your are first seeding tables in a new Oracle database, or there is a time where normal activity in the production database can be safely taken off-line for a few hours to free up resources for a big incremental load. Using OSCH on high end machines (specifically Oracle Exadata and Oracle BDA cabled with Infiniband), this mode of operation can load up to 15TB per hour. The bottom line is that you should first figure out what DOP you will be allowed to run with by talking to the DBAs who manage the production system. You then use that number to derive the number of location files, and (optionally) the number of HDFS data files that you want to generate, assuming that is flexible. Rule 1: Find out the maximum DOP you will be allowed to use with OSCH on the target Oracle system Determining the Number of Location Files Let’s assume that the DBA told you that your maximum DOP was 8. You want the number of location files in your external table to be big enough to utilize all 8 PQ slaves, and you want them to represent equally balanced workloads. Remember location files in OSCH are metadata lists of HDFS files and are created using OSCH’s External Table tool. They also represent the workload size given to an individual Oracle PQ slave (i.e. a PQ slave is given one location file to process at a time, and only it will process the contents of the location file.) Rule 2: The size of the workload of a single location file (and the PQ slave that processes it) is the sum of the content size of the HDFS files it lists For example, if a location file lists 5 HDFS files which are each 100GB in size, the workload size for that location file is 500GB. The number of location files that you generate is something you control by providing a number as input to OSCH’s External Table tool. Rule 3: The number of location files chosen should be a small multiple of the DOP Each location file represents one workload for one PQ slave. So the goal is to keep all slaves busy and try to give them equivalent workloads. Obviously if you run with a DOP of 8 but have 5 location files, only five PQ slaves will have something to do and the other three will have nothing to do and will quietly exit. If you run with 9 location files, then the PQ slaves will pick up the first 8 location files, and assuming they have equal work loads, will finish up about the same time. But the first PQ slave to finish its job will then be rescheduled to process the ninth location file, potentially doubling the end to end processing time. So for this DOP using 8, 16, or 32 location files would be a good idea. Determining the Number of HDFS Files Let’s start with the next rule and then explain it: Rule 4: The number of HDFS files should try to be a multiple of the number of location files and try to be relatively the same size In our running example, the DOP is 8. This means that the number of location files should be a small multiple of 8. Remember that each location file represents a list of unique HDFS files to load, and that the sum of the files listed in each location file is a workload for one Oracle PQ slave. The OSCH External Table tool will look in an HDFS directory for a set of HDFS files to load.  It will generate N number of location files (where N is the value you gave to the tool). It will then try to divvy up the HDFS files and do its best to make sure the workload across location files is as balanced as possible. (The tool uses a greedy algorithm that grabs the biggest HDFS file and delegates it to a particular location file. It then looks for the next biggest file and puts in some other location file, and so on). The tools ability to balance is reduced if HDFS file sizes are grossly out of balance or are too few. For example suppose my DOP is 8 and the number of location files is 8. Suppose I have only 8 HDFS files, where one file is 900GB and the others are 100GB. When the tool tries to balance the load it will be forced to put the singleton 900GB into one location file, and put each of the 100GB files in the 7 remaining location files. The load balance skew is 9 to 1. One PQ slave will be working overtime, while the slacker PQ slaves are off enjoying happy hour. If however the total payload (1600 GB) were broken up into smaller HDFS files, the OSCH External Table tool would have an easier time generating a list where each workload for each location file is relatively the same.  Applying Rule 4 above to our DOP of 8, we could divide the workload into160 files that were approximately 10 GB in size.  For this scenario the OSCH External Table tool would populate each location file with 20 HDFS file references, and all location files would have similar workloads (approximately 200GB per location file.) As a rule, when the OSCH External Table tool has to deal with more and smaller files it will be able to create more balanced loads. How small should HDFS files get? Not so small that the HDFS open and close file overhead starts having a substantial impact. For our performance test system (Exadata/BDA with Infiniband), I compared three OSCH loads of 1 TiB. One load had 128 HDFS files living in 64 location files where each HDFS file was about 8GB. I then did the same load with 12800 files where each HDFS file was about 80MB size. The end to end load time was virtually the same. However when I got ridiculously small (i.e. 128000 files at about 8MB per file), it started to make an impact and slow down the load time. What happens if you break rules 3 or 4 above? Nothing draconian, everything will still function. You just won’t be taking full advantage of the generous DOP that was allocated to you by your friendly DBA. The key point of the rules articulated above is this: if you know that HDFS content is ultimately going to be loaded into Oracle using OSCH, it makes sense to chop them up into the right number of files roughly the same size, derived from the DOP that you expect to use for loading. Next Steps So far we have talked about OLH and OSCH as alternative models for loading. That’s not quite the whole story. They can be used together in a way that provides for more efficient OSCH loads and allows one to be more flexible about scheduling on a Hadoop cluster and an Oracle Database to perform load operations. The next lesson will talk about Oracle Data Pump files generated by OLH, and loaded using OSCH. It will also outline the pros and cons of using various load methods.  This will be followed up with a final tutorial lesson focusing on how to optimize OLH and OSCH for use on Oracle's engineered systems: specifically Exadata and the BDA. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;}

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  • Transactional Messaging in the Windows Azure Service Bus

    - by Alan Smith
    Introduction I’m currently working on broadening the content in the Windows Azure Service Bus Developer Guide. One of the features I have been looking at over the past week is the support for transactional messaging. When using the direct programming model and the WCF interface some, but not all, messaging operations can participate in transactions. This allows developers to improve the reliability of messaging systems. There are some limitations in the transactional model, transactions can only include one top level messaging entity (such as a queue or topic, subscriptions are no top level entities), and transactions cannot include other systems, such as databases. As the transaction model is currently not well documented I have had to figure out how things work through experimentation, with some help from the development team to confirm any questions I had. Hopefully I’ve got the content mostly correct, I will update the content in the e-book if I find any errors or improvements that can be made (any feedback would be very welcome). I’ve not had a chance to look into the code for transactions and asynchronous operations, maybe that would make a nice challenge lab for my Windows Azure Service Bus course. Transactional Messaging Messaging entities in the Windows Azure Service Bus provide support for participation in transactions. This allows developers to perform several messaging operations within a transactional scope, and ensure that all the actions are committed or, if there is a failure, none of the actions are committed. There are a number of scenarios where the use of transactions can increase the reliability of messaging systems. Using TransactionScope In .NET the TransactionScope class can be used to perform a series of actions in a transaction. The using declaration is typically used de define the scope of the transaction. Any transactional operations that are contained within the scope can be committed by calling the Complete method. If the Complete method is not called, any transactional methods in the scope will not commit.   // Create a transactional scope. using (TransactionScope scope = new TransactionScope()) {     // Do something.       // Do something else.       // Commit the transaction.     scope.Complete(); }     In order for methods to participate in the transaction, they must provide support for transactional operations. Database and message queue operations typically provide support for transactions. Transactions in Brokered Messaging Transaction support in Service Bus Brokered Messaging allows message operations to be performed within a transactional scope; however there are some limitations around what operations can be performed within the transaction. In the current release, only one top level messaging entity, such as a queue or topic can participate in a transaction, and the transaction cannot include any other transaction resource managers, making transactions spanning a messaging entity and a database not possible. When sending messages, the send operations can participate in a transaction allowing multiple messages to be sent within a transactional scope. This allows for “all or nothing” delivery of a series of messages to a single queue or topic. When receiving messages, messages that are received in the peek-lock receive mode can be completed, deadlettered or deferred within a transactional scope. In the current release the Abandon method will not participate in a transaction. The same restrictions of only one top level messaging entity applies here, so the Complete method can be called transitionally on messages received from the same queue, or messages received from one or more subscriptions in the same topic. Sending Multiple Messages in a Transaction A transactional scope can be used to send multiple messages to a queue or topic. This will ensure that all the messages will be enqueued or, if the transaction fails to commit, no messages will be enqueued.     An example of the code used to send 10 messages to a queue as a single transaction from a console application is shown below.   QueueClient queueClient = messagingFactory.CreateQueueClient(Queue1);   Console.Write("Sending");   // Create a transaction scope. using (TransactionScope scope = new TransactionScope()) {     for (int i = 0; i < 10; i++)     {         // Send a message         BrokeredMessage msg = new BrokeredMessage("Message: " + i);         queueClient.Send(msg);         Console.Write(".");     }     Console.WriteLine("Done!");     Console.WriteLine();       // Should we commit the transaction?     Console.WriteLine("Commit send 10 messages? (yes or no)");     string reply = Console.ReadLine();     if (reply.ToLower().Equals("yes"))     {         // Commit the transaction.         scope.Complete();     } } Console.WriteLine(); messagingFactory.Close();     The transaction scope is used to wrap the sending of 10 messages. Once the messages have been sent the user has the option to either commit the transaction or abandon the transaction. If the user enters “yes”, the Complete method is called on the scope, which will commit the transaction and result in the messages being enqueued. If the user enters anything other than “yes”, the transaction will not commit, and the messages will not be enqueued. Receiving Multiple Messages in a Transaction The receiving of multiple messages is another scenario where the use of transactions can improve reliability. When receiving a group of messages that are related together, maybe in the same message session, it is possible to receive the messages in the peek-lock receive mode, and then complete, defer, or deadletter the messages in one transaction. (In the current version of Service Bus, abandon is not transactional.)   The following code shows how this can be achieved. using (TransactionScope scope = new TransactionScope()) {       while (true)     {         // Receive a message.         BrokeredMessage msg = q1Client.Receive(TimeSpan.FromSeconds(1));         if (msg != null)         {             // Wrote message body and complete message.             string text = msg.GetBody<string>();             Console.WriteLine("Received: " + text);             msg.Complete();         }         else         {             break;         }     }     Console.WriteLine();       // Should we commit?     Console.WriteLine("Commit receive? (yes or no)");     string reply = Console.ReadLine();     if (reply.ToLower().Equals("yes"))     {         // Commit the transaction.         scope.Complete();     }     Console.WriteLine(); }     Note that if there are a large number of messages to be received, there will be a chance that the transaction may time out before it can be committed. It is possible to specify a longer timeout when the transaction is created, but It may be better to receive and commit smaller amounts of messages within the transaction. It is also possible to complete, defer, or deadletter messages received from more than one subscription, as long as all the subscriptions are contained in the same topic. As subscriptions are not top level messaging entities this scenarios will work. The following code shows how this can be achieved. try {     using (TransactionScope scope = new TransactionScope())     {         // Receive one message from each subscription.         BrokeredMessage msg1 = subscriptionClient1.Receive();         BrokeredMessage msg2 = subscriptionClient2.Receive();           // Complete the message receives.         msg1.Complete();         msg2.Complete();           Console.WriteLine("Msg1: " + msg1.GetBody<string>());         Console.WriteLine("Msg2: " + msg2.GetBody<string>());           // Commit the transaction.         scope.Complete();     } } catch (Exception ex) {     Console.WriteLine(ex.Message); }     Unsupported Scenarios The restriction of only one top level messaging entity being able to participate in a transaction makes some useful scenarios unsupported. As the Windows Azure Service Bus is under continuous development and new releases are expected to be frequent it is possible that this restriction may not be present in future releases. The first is the scenario where messages are to be routed to two different systems. The following code attempts to do this.   try {     // Create a transaction scope.     using (TransactionScope scope = new TransactionScope())     {         BrokeredMessage msg1 = new BrokeredMessage("Message1");         BrokeredMessage msg2 = new BrokeredMessage("Message2");           // Send a message to Queue1         Console.WriteLine("Sending Message1");         queue1Client.Send(msg1);           // Send a message to Queue2         Console.WriteLine("Sending Message2");         queue2Client.Send(msg2);           // Commit the transaction.         Console.WriteLine("Committing transaction...");         scope.Complete();     } } catch (Exception ex) {     Console.WriteLine(ex.Message); }     The results of running the code are shown below. When attempting to send a message to the second queue the following exception is thrown: No active Transaction was found for ID '35ad2495-ee8a-4956-bbad-eb4fedf4a96e:1'. The Transaction may have timed out or attempted to span multiple top-level entities such as Queue or Topic. The server Transaction timeout is: 00:01:00..TrackingId:947b8c4b-7754-4044-b91b-4a959c3f9192_3_3,TimeStamp:3/29/2012 7:47:32 AM.   Another scenario where transactional support could be useful is when forwarding messages from one queue to another queue. This would also involve more than one top level messaging entity, and is therefore not supported.   Another scenario that developers may wish to implement is performing transactions across messaging entities and other transactional systems, such as an on-premise database. In the current release this is not supported.   Workarounds for Unsupported Scenarios There are some techniques that developers can use to work around the one top level entity limitation of transactions. When sending two messages to two systems, topics and subscriptions can be used. If the same message is to be sent to two destinations then the subscriptions would have the default subscriptions, and the client would only send one message. If two different messages are to be sent, then filters on the subscriptions can route the messages to the appropriate destination. The client can then send the two messages to the topic in the same transaction.   In scenarios where a message needs to be received and then forwarded to another system within the same transaction topics and subscriptions can also be used. A message can be received from a subscription, and then sent to a topic within the same transaction. As a topic is a top level messaging entity, and a subscription is not, this scenario will work.

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  • Windows Azure AppFabric: ServiceBus Queue WPF Sample

    - by xamlnotes
    The latest version of the AppFabric ServiceBus now has support for queues and topics. Today I will show you a bit about using queues and also talk about some of the best practices in using them. If you are just getting started, you can check out this site for more info on Windows Azure. One of the 1st things I thought if when Azure was announced back when was how we handle fault tolerance. Web sites hosted in Azure are no much of an issue unless they are using SQL Azure and then you must account for potential fault or latency issues. Today I want to talk a bit about ServiceBus and how to handle fault tolerance.  And theres stuff like connecting to the servicebus and so on you have to take care of. To demonstrate some of the things you can do, let me walk through this sample WPF app that I am posting for you to download. To start off, the application is going to need things like the servicenamespace, issuer details and so forth to make everything work.  To facilitate this I created settings in the wpf app for all of these items. Then I mapped a static class to them and set the values when the program loads like so: StaticElements.ServiceNamespace = Convert.ToString(Properties.Settings.Default["ServiceNamespace"]); StaticElements.IssuerName = Convert.ToString(Properties.Settings.Default["IssuerName"]); StaticElements.IssuerKey = Convert.ToString(Properties.Settings.Default["IssuerKey"]); StaticElements.QueueName = Convert.ToString(Properties.Settings.Default["QueueName"]);   Now I can get to each of these elements plus some other common values or instances directly from the StaticElements class. Now, lets look at the application.  The application looks like this when it starts:   The blue graphic represents the queue we are going to use.  The next figure shows the form after items were added and the queue stats were updated . You can see how the queue has grown: To add an item to the queue, click the Add Order button which displays the following dialog: After you fill in the form and press OK, the order is published to the ServiceBus queue and the form closes. The application also allows you to read the queued items by clicking the Process Orders button. As you can see below, the form shows the queued items in a list and the  queue has disappeared as its now empty. In real practice we normally would use a Windows Service or some other automated process to subscribe to the queue and pull items from it. I created a class named ServiceBusQueueHelper that has the core queue features we need. There are three public methods: * GetOrCreateQueue – Gets an instance of the queue description if the queue exists. if not, it creates the queue and returns a description instance. * SendMessageToQueue = This method takes an order instance and sends it to the queue. The call to the queue is wrapped in the ExecuteAction method from the Transient Fault Tolerance Framework and handles all the retry logic for the queue send process. * GetOrderFromQueue – Grabs an order from the queue and returns a typed order from the queue. It also marks the message complete so the queue can remove it.   Now lets turn to the WPF window code (MainWindow.xaml.cs). The constructor contains the 4 lines shown about to setup the static variables and to perform other initialization tasks. The next few lines setup certain features we need for the ServiceBus: TokenProvider credentials = TokenProvider.CreateSharedSecretTokenProvider(StaticElements.IssuerName, StaticElements.IssuerKey); Uri serviceUri = ServiceBusEnvironment.CreateServiceUri("sb", StaticElements.ServiceNamespace, string.Empty); StaticElements.CurrentNamespaceManager = new NamespaceManager(serviceUri, credentials); StaticElements.CurrentMessagingFactory = MessagingFactory.Create(serviceUri, credentials); The next two lines update the queue name label and also set the timer to 20 seconds.             QueueNameLabel.Content = StaticElements.QueueName;             _timer.Interval = TimeSpan.FromSeconds(20);             Next I call the UpdateQueueStats to initialize the UI for the queue:             UpdateQueueStats();             _timer.Tick += new EventHandler(delegate(object s, EventArgs a)                         {                      UpdateQueueStats();                  });             _timer.Start();         } The UpdateQueueStats method shown below. You can see that it uses the GetOrCreateQueue method mentioned earlier to grab the queue description, then it can get the MessageCount property.         private void UpdateQueueStats()         {             _queueDescription = _serviceBusQueueHelper.GetOrCreateQueue();             QueueCountLabel.Content = "(" + _queueDescription.MessageCount + ")";             long count = _queueDescription.MessageCount;             long queueWidth = count * 20;             QueueRectangle.Width = queueWidth;             QueueTickCount += 1;             TickCountlabel.Content = QueueTickCount.ToString();         }   The ReadQueueItemsButton_Click event handler calls the GetOrderFromQueue method and adds the order to the listbox. If you look at the SendQueueMessageController, you can see the SendMessage method that sends an order to the queue. Its pretty simple as it just creates a new CustomerOrderEntity instance,fills it and then passes it to the SendMessageToQueue. As you can see, all of our interaction with the queue is done through the helper class (ServiceBusQueueHelper). Now lets dig into the helper class. First, before you create anything like this, download the Transient Fault Handling Framework. Microsoft provides this free and they also provide the C# source. Theres a great article that shows how to use this framework with ServiceBus. I included the entire ServiceBusQueueHelper class in List 1. Notice the using statements for TransientFaultHandling: using Microsoft.AzureCAT.Samples.TransientFaultHandling; using Microsoft.AzureCAT.Samples.TransientFaultHandling.ServiceBus; The SendMessageToQueue in Listing 1 shows how to use the async send features of ServiceBus with them wrapped in the Transient Fault Handling Framework.  It is not much different than plain old ServiceBus calls but it sure makes it easy to have the fault tolerance added almost for free. The GetOrderFromQueue uses the standard synchronous methods to access the queue. The best practices article walks through using the async approach for a receive operation also.  Notice that this method makes a call to Receive to get the message then makes a call to GetBody to get a new strongly typed instance of CustomerOrderEntity to return. Listing 1 using System; using System.Collections.Generic; using System.Linq; using System.Text; using Microsoft.AzureCAT.Samples.TransientFaultHandling; using Microsoft.AzureCAT.Samples.TransientFaultHandling.ServiceBus; using Microsoft.ServiceBus; using Microsoft.ServiceBus.Messaging; using System.Xml.Serialization; using System.Diagnostics; namespace WPFServicebusPublishSubscribeSample {     class ServiceBusQueueHelper     {         RetryPolicy currentPolicy = new RetryPolicy<ServiceBusTransientErrorDetectionStrategy>(RetryPolicy.DefaultClientRetryCount);         QueueClient currentQueueClient;         public QueueDescription GetOrCreateQueue()         {                        QueueDescription queue = null;             bool createNew = false;             try             {                 // First, let's see if a queue with the specified name already exists.                 queue = currentPolicy.ExecuteAction<QueueDescription>(() => { return StaticElements.CurrentNamespaceManager.GetQueue(StaticElements.QueueName); });                 createNew = (queue == null);             }             catch (MessagingEntityNotFoundException)             {                 // Looks like the queue does not exist. We should create a new one.                 createNew = true;             }             // If a queue with the specified name doesn't exist, it will be auto-created.             if (createNew)             {                 try                 {                     var newqueue = new QueueDescription(StaticElements.QueueName);                     queue = currentPolicy.ExecuteAction<QueueDescription>(() => { return StaticElements.CurrentNamespaceManager.CreateQueue(newqueue); });                 }                 catch (MessagingEntityAlreadyExistsException)                 {                     // A queue under the same name was already created by someone else,                     // perhaps by another instance. Let's just use it.                     queue = currentPolicy.ExecuteAction<QueueDescription>(() => { return StaticElements.CurrentNamespaceManager.GetQueue(StaticElements.QueueName); });                 }             }             currentQueueClient = StaticElements.CurrentMessagingFactory.CreateQueueClient(StaticElements.QueueName);             return queue;         }         public void SendMessageToQueue(CustomerOrderEntity Order)         {             BrokeredMessage msg = null;             GetOrCreateQueue();             // Use a retry policy to execute the Send action in an asynchronous and reliable fashion.             currentPolicy.ExecuteAction             (                 (cb) =>                 {                     // A new BrokeredMessage instance must be created each time we send it. Reusing the original BrokeredMessage instance may not                     // work as the state of its BodyStream cannot be guaranteed to be readable from the beginning.                     msg = new BrokeredMessage(Order);                     // Send the event asynchronously.                     currentQueueClient.BeginSend(msg, cb, null);                 },                 (ar) =>                 {                     try                     {                         // Complete the asynchronous operation.                         // This may throw an exception that will be handled internally by the retry policy.                         currentQueueClient.EndSend(ar);                     }                     finally                     {                         // Ensure that any resources allocated by a BrokeredMessage instance are released.                         if (msg != null)                         {                             msg.Dispose();                             msg = null;                         }                     }                 },                 (ex) =>                 {                     // Always dispose the BrokeredMessage instance even if the send                     // operation has completed unsuccessfully.                     if (msg != null)                     {                         msg.Dispose();                         msg = null;                     }                     // Always log exceptions.                     Trace.TraceError(ex.Message);                 }             );         }                 public CustomerOrderEntity GetOrderFromQueue()         {             CustomerOrderEntity Order = new CustomerOrderEntity();             QueueClient myQueueClient = StaticElements.CurrentMessagingFactory.CreateQueueClient(StaticElements.QueueName, ReceiveMode.PeekLock);             BrokeredMessage message;             ServiceBusQueueHelper serviceBusQueueHelper = new ServiceBusQueueHelper();             QueueDescription queueDescription;             queueDescription = serviceBusQueueHelper.GetOrCreateQueue();             if (queueDescription.MessageCount > 0)             {                 message = myQueueClient.Receive(TimeSpan.FromSeconds(90));                 if (message != null)                 {                     try                     {                         Order = message.GetBody<CustomerOrderEntity>();                         message.Complete();                     }                     catch (Exception ex)                     {                         throw ex;                     }                 }                 else                 {                     throw new Exception("Did not receive the messages");                 }             }             return Order;         }     } } I will post a link to the download demo in a separate post soon.

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  • SQL Sharding and SQL Azure&hellip;

    - by Dave Noderer
    Herve Roggero has just published a paper that outlines patterns for scaling using SQL Azure and the Blue Syntax (he and Scott Klein’s company) sharding api. You can find the paper at: http://www.bluesyntax.net/files/EnzoFramework.pdf Herve and Scott have also just released an Apress book Pro SQL Azure. The idea of being able to split (shard) database operations automatically and control them from a web based management console is very appealing. These ideas have been talked about for a long time and implemented in thousands of very custom ways that have been costly, complicated and fragile. Now, there is light at the end of the tunnel. Scaling database access will become easier and move into the mainstream of application development. The main cost is using an api whenever accessing the database. The api will direct the query to the correct database(s) which may be located locally or in the cloud. It is inevitable that the api will change in the future, perhaps incorporated into a Microsoft offering. Even if this is the case, your application has now been architected to utilize these patterns and details of the actual api will be less important. Herve does a great job of laying out the concepts which every developer and architect should be familiar with!

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  • TechEd 2012: Dude Where&rsquo;s My Azure

    - by Tim Murphy
    It has been a fun first morning at TechEd North America.  They keynote was both informative and entertaining.  Some of the high points included a walk through of Windows Server 2012 and its new Hyper-V capabilities and use of ODX (offloaded data transfer).  Between seeing stats like being able to being able run a Hyper-V VM with 1TB of memory and watching ODX move a 10GB file at a rate of 1GB per second was really impressive. The fun started when Scott Guthrie was doing his keynote demo and popped up an iPhone emulator from Visual Studio.  There is just something wrong with that picture and the WPDev community agreed.  This was followed by an iPad emulator and by that time the groans across Twitter were rolling. Later in the morning The Gu kept us laughing in the Azure Foundations session when he name a server Dude (I believe a suggestion from the crowd).  After that I thought I was watching the turtle in Finding Nemo.  Duuuuude! In the expo area the line for the Windows Phone booth was ridiculous.  Granted this is a Microsoft event and is sure to be full of MS fan boys, but the only other time I have seen that much enthusiasm for Windows Phones in one place was on the flight down. I am sure there will be a lot more to get excited about over the next few days.  Stay tuned. del.icio.us Tags: TechEd 2012,TechEd North America,Windows Phone,Azure,Scott Guthrie

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