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  • JMS Step 4 - How to Create an 11g BPEL Process Which Writes a Message Based on an XML Schema to a JMS Queue

    - by John-Brown.Evans
    JMS Step 4 - How to Create an 11g BPEL Process Which Writes a Message Based on an XML Schema to a JMS Queue ol{margin:0;padding:0} .c11_4{vertical-align:top;width:129.8pt;border-style:solid;background-color:#f3f3f3;border-color:#000000;border-width:1pt;padding:5pt 5pt 5pt 5pt} .c9_4{vertical-align:top;width:207pt;border-style:solid;background-color:#f3f3f3;border-color:#000000;border-width:1pt;padding:5pt 5pt 5pt 5pt}.c14{vertical-align:top;width:207pt;border-style:solid;border-color:#000000;border-width:1pt;padding:5pt 5pt 5pt 5pt} .c17_4{vertical-align:top;width:129.8pt;border-style:solid;border-color:#000000;border-width:1pt;padding:5pt 5pt 5pt 5pt} .c7_4{vertical-align:top;width:130pt;border-style:solid;border-color:#000000;border-width:1pt;padding:0pt 5pt 0pt 5pt} .c19_4{vertical-align:top;width:468pt;border-style:solid;border-color:#000000;border-width:1pt;padding:5pt 5pt 5pt 5pt} .c22_4{background-color:#ffffff} .c20_4{list-style-type:disc;margin:0;padding:0} .c6_4{font-size:8pt;font-family:"Courier New"} .c24_4{color:inherit;text-decoration:inherit} .c23_4{color:#1155cc;text-decoration:underline} .c0_4{height:11pt;direction:ltr} .c10_4{font-size:10pt;font-family:"Courier New"} .c3_4{padding-left:0pt;margin-left:36pt} .c18_4{font-size:8pt} .c8_4{text-align:center} .c12_4{background-color:#ffff00} .c2_4{font-weight:bold} .c21_4{background-color:#00ff00} .c4_4{line-height:1.0} .c1_4{direction:ltr} .c15_4{background-color:#f3f3f3} .c13_4{font-family:"Courier New"} .c5_4{font-style:italic} .c16_4{border-collapse:collapse} .title{padding-top:24pt;line-height:1.15;text-align:left;color:#000000;font-size:36pt;font-family:"Arial";font-weight:bold;padding-bottom:6pt} .subtitle{padding-top:18pt;line-height:1.15;text-align:left;color:#666666;font-style:italic;font-size:24pt;font-family:"Georgia";padding-bottom:4pt} li{color:#000000;font-size:10pt;font-family:"Arial"} p{color:#000000;font-size:10pt;margin:0;font-family:"Arial"} h1{padding-top:0pt;line-height:1.15;text-align:left;color:#888;font-size:18pt;font-family:"Arial";font-weight:normal;padding-bottom:0pt} h2{padding-top:0pt;line-height:1.15;text-align:left;color:#888;font-size:18pt;font-family:"Arial";font-weight:bold;padding-bottom:0pt} h3{padding-top:0pt;line-height:1.15;text-align:left;color:#888;font-size:14pt;font-family:"Arial";font-weight:normal;padding-bottom:0pt} h4{padding-top:0pt;line-height:1.15;text-align:left;color:#888;font-style:italic;font-size:11pt;font-family:"Arial";padding-bottom:0pt} h5{padding-top:0pt;line-height:1.15;text-align:left;color:#888;font-size:10pt;font-family:"Arial";font-weight:normal;padding-bottom:0pt} h6{padding-top:0pt;line-height:1.15;text-align:left;color:#888;font-style:italic;font-size:10pt;font-family:"Arial";padding-bottom:0pt} This post continues the series of JMS articles which demonstrate how to use JMS queues in a SOA context. The previous posts were: JMS Step 1 - How to Create a Simple JMS Queue in Weblogic Server 11g JMS Step 2 - Using the QueueSend.java Sample Program to Send a Message to a JMS Queue JMS Step 3 - Using the QueueReceive.java Sample Program to Read a Message from a JMS Queue In this example we will create a BPEL process which will write (enqueue) a message to a JMS queue using a JMS adapter. The JMS adapter will enqueue the full XML payload to the queue. This sample will use the following WebLogic Server objects. The first two, the Connection Factory and JMS Queue, were created as part of the first blog post in this series, JMS Step 1 - How to Create a Simple JMS Queue in Weblogic Server 11g. If you haven't created those objects yet, please see that post for details on how to do so. The Connection Pool will be created as part of this example. Object Name Type JNDI Name TestConnectionFactory Connection Factory jms/TestConnectionFactory TestJMSQueue JMS Queue jms/TestJMSQueue eis/wls/TestQueue Connection Pool eis/wls/TestQueue 1. Verify Connection Factory and JMS Queue As mentioned above, this example uses a WLS Connection Factory called TestConnectionFactory and a JMS queue TestJMSQueue. As these are prerequisites for this example, let us verify they exist. Log in to the WebLogic Server Administration Console. Select Services > JMS Modules > TestJMSModule You should see the following objects: If not, or if the TestJMSModule is missing, please see the abovementioned article and create these objects before continuing. 2. Create a JMS Adapter Connection Pool in WebLogic Server The BPEL process we are about to create uses a JMS adapter to write to the JMS queue. The JMS adapter is deployed to the WebLogic server and needs to be configured to include a connection pool which references the connection factory associated with the JMS queue. In the WebLogic Server Console Go to Deployments > Next and select (click on) the JmsAdapter Select Configuration > Outbound Connection Pools and expand oracle.tip.adapter.jms.IJmsConnectionFactory. This will display the list of connections configured for this adapter. For example, eis/aqjms/Queue, eis/aqjms/Topic etc. These JNDI names are actually quite confusing. We are expecting to configure a connection pool here, but the names refer to queues and topics. One would expect these to be called *ConnectionPool or *_CF or similar, but to conform to this nomenclature, we will call our entry eis/wls/TestQueue . This JNDI name is also the name we will use later, when creating a BPEL process to access this JMS queue! Select New, check the oracle.tip.adapter.jms.IJmsConnectionFactory check box and Next. Enter JNDI Name: eis/wls/TestQueue for the connection instance, then press Finish. Expand oracle.tip.adapter.jms.IJmsConnectionFactory again and select (click on) eis/wls/TestQueue The ConnectionFactoryLocation must point to the JNDI name of the connection factory associated with the JMS queue you will be writing to. In our example, this is the connection factory called TestConnectionFactory, with the JNDI name jms/TestConnectionFactory.( As a reminder, this connection factory is contained in the JMS Module called TestJMSModule, under Services > Messaging > JMS Modules > TestJMSModule which we verified at the beginning of this document. )Enter jms/TestConnectionFactory  into the Property Value field for Connection Factory Location. After entering it, you must press Return/Enter then Save for the value to be accepted. If your WebLogic server is running in Development mode, you should see the message that the changes have been activated and the deployment plan successfully updated. If not, then you will manually need to activate the changes in the WebLogic server console. Although the changes have been activated, the JmsAdapter needs to be redeployed in order for the changes to become effective. This should be confirmed by the message Remember to update your deployment to reflect the new plan when you are finished with your changes as can be seen in the following screen shot: The next step is to redeploy the JmsAdapter.Navigate back to the Deployments screen, either by selecting it in the left-hand navigation tree or by selecting the “Summary of Deployments” link in the breadcrumbs list at the top of the screen. Then select the checkbox next to JmsAdapter and press the Update button On the Update Application Assistant page, select “Redeploy this application using the following deployment files” and press Finish. After a few seconds you should get the message that the selected deployments were updated. The JMS adapter configuration is complete and it can now be used to access the JMS queue. To summarize: we have created a JMS adapter connection pool connector with the JNDI name jms/TestConnectionFactory. This is the JNDI name to be accessed by a process such as a BPEL process, when using the JMS adapter to access the previously created JMS queue with the JNDI name jms/TestJMSQueue. In the following step, we will set up a BPEL process to use this JMS adapter to write to the JMS queue. 3. Create a BPEL Composite with a JMS Adapter Partner Link This step requires that you have a valid Application Server Connection defined in JDeveloper, pointing to the application server on which you created the JMS Queue and Connection Factory. You can create this connection in JDeveloper under the Application Server Navigator. Give it any name and be sure to test the connection before completing it. This sample will use the connection name jbevans-lx-PS5, as that is the name of the connection pointing to my SOA PS5 installation. When using a JMS adapter from within a BPEL process, there are various configuration options, such as the operation type (consume message, produce message etc.), delivery mode and message type. One of these options is the choice of the format of the JMS message payload. This can be structured around an existing XSD, in which case the full XML element and tags are passed, or it can be opaque, meaning that the payload is sent as-is to the JMS adapter. In the case of an XSD-based message, the payload can simply be copied to the input variable of the JMS adapter. In the case of an opaque message, the JMS adapter’s input variable is of type base64binary. So the payload needs to be converted to base64 binary first. I will go into this in more detail in a later blog entry. This sample will pass a simple message to the adapter, based on the following simple XSD file, which consists of a single string element: stringPayload.xsd <?xml version="1.0" encoding="windows-1252" ?> <xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns="http://www.example.org" targetNamespace="http://www.example.org" elementFormDefault="qualified" <xsd:element name="exampleElement" type="xsd:string"> </xsd:element> </xsd:schema> The following steps are all executed in JDeveloper. The SOA project will be created inside a JDeveloper Application. If you do not already have an application to contain the project, you can create a new one via File > New > General > Generic Application. Give the application any name, for example JMSTests and, when prompted for a project name and type, call the project JmsAdapterWriteWithXsd and select SOA as the project technology type. If you already have an application, continue below. Create a SOA Project Create a new project and choose SOA Tier > SOA Project as its type. Name it JmsAdapterWriteSchema. When prompted for the composite type, choose Composite With BPEL Process. When prompted for the BPEL Process, name it JmsAdapterWriteSchema too and choose Synchronous BPEL Process as the template. This will create a composite with a BPEL process and an exposed SOAP service. Double-click the BPEL process to open and begin editing it. You should see a simple BPEL process with a Receive and Reply activity. As we created a default process without an XML schema, the input and output variables are simple strings. Create an XSD File An XSD file is required later to define the message format to be passed to the JMS adapter. In this step, we create a simple XSD file, containing a string variable and add it to the project. First select the xsd item in the left-hand navigation tree to ensure that the XSD file is created under that item. Select File > New > General > XML and choose XML Schema. Call it stringPayload.xsd and when the editor opens, select the Source view. then replace the contents with the contents of the stringPayload.xsd example above and save the file. You should see it under the xsd item in the navigation tree. Create a JMS Adapter Partner Link We will create the JMS adapter as a service at the composite level. If it is not already open, double-click the composite.xml file in the navigator to open it. From the Component Palette, drag a JMS adapter over onto the right-hand swim lane, under External References. This will start the JMS Adapter Configuration Wizard. Use the following entries: Service Name: JmsAdapterWrite Oracle Enterprise Messaging Service (OEMS): Oracle Weblogic JMS AppServer Connection: Use an existing application server connection pointing to the WebLogic server on which the above JMS queue and connection factory were created. You can use the “+” button to create a connection directly from the wizard, if you do not already have one. This example uses a connection called jbevans-lx-PS5. Adapter Interface > Interface: Define from operation and schema (specified later) Operation Type: Produce Message Operation Name: Produce_message Destination Name: Press the Browse button, select Destination Type: Queues, then press Search. Wait for the list to populate, then select the entry for TestJMSQueue , which is the queue created earlier. JNDI Name: The JNDI name to use for the JMS connection. This is probably the most important step in this exercise and the most common source of error. This is the JNDI name of the JMS adapter’s connection pool created in the WebLogic Server and which points to the connection factory. JDeveloper does not verify the value entered here. If you enter a wrong value, the JMS adapter won’t find the queue and you will get an error message at runtime, which is very difficult to trace. In our example, this is the value eis/wls/TestQueue . (See the earlier step on how to create a JMS Adapter Connection Pool in WebLogic Server for details.) MessagesURL: We will use the XSD file we created earlier, stringPayload.xsd to define the message format for the JMS adapter. Press the magnifying glass icon to search for schema files. Expand Project Schema Files > stringPayload.xsd and select exampleElement: string. Press Next and Finish, which will complete the JMS Adapter configuration. Wire the BPEL Component to the JMS Adapter In this step, we link the BPEL process/component to the JMS adapter. From the composite.xml editor, drag the right-arrow icon from the BPEL process to the JMS adapter’s in-arrow. This completes the steps at the composite level. 4. Complete the BPEL Process Design Invoke the JMS Adapter Open the BPEL component by double-clicking it in the design view of the composite.xml, or open it from the project navigator by selecting the JmsAdapterWriteSchema.bpel file. This will display the BPEL process in the design view. You should see the JmsAdapterWrite partner link under one of the two swim lanes. We want it in the right-hand swim lane. If JDeveloper displays it in the left-hand lane, right-click it and choose Display > Move To Opposite Swim Lane. An Invoke activity is required in order to invoke the JMS adapter. Drag an Invoke activity between the Receive and Reply activities. Drag the right-hand arrow from the Invoke activity to the JMS adapter partner link. This will open the Invoke editor. The correct default values are entered automatically and are fine for our purposes. We only need to define the input variable to use for the JMS adapter. By pressing the green “+” symbol, a variable of the correct type can be auto-generated, for example with the name Invoke1_Produce_Message_InputVariable. Press OK after creating the variable. ( For some reason, while I was testing this, the JMS Adapter moved back to the left-hand swim lane again after this step. There is no harm in leaving it there, but I find it easier to follow if it is in the right-hand lane, because I kind-of think of the message coming in on the left and being routed through the right. But you can follow your personal preference here.) Assign Variables Drag an Assign activity between the Receive and Invoke activities. We will simply copy the input variable to the JMS adapter and, for completion, so the process has an output to print, again to the process’s output variable. Double-click the Assign activity and create two Copy rules: for the first, drag Variables > inputVariable > payload > client:process > client:input_string to Invoke1_Produce_Message_InputVariable > body > ns2:exampleElement for the second, drag the same input variable to outputVariable > payload > client:processResponse > client:result This will create two copy rules, similar to the following: Press OK. This completes the BPEL and Composite design. 5. Compile and Deploy the Composite We won’t go into too much detail on how to compile and deploy. In JDeveloper, compile the process by pressing the Make or Rebuild icons or by right-clicking the project name in the navigator and selecting Make... or Rebuild... If the compilation is successful, deploy it to the SOA server connection defined earlier. (Right-click the project name in the navigator, select Deploy to Application Server, choose the application server connection, choose the partition on the server (usually default) and press Finish. You should see the message ---- Deployment finished. ---- in the Deployment frame, if the deployment was successful. 6. Test the Composite This is the exciting part. Open two tabs in your browser and log in to the WebLogic Administration Console in one tab and the Enterprise Manager 11g Fusion Middleware Control (EM) for your SOA installation in the other. We will use the Console to monitor the messages being written to the queue and the EM to execute the composite. In the Console, go to Services > Messaging > JMS Modules > TestJMSModule > TestJMSQueue > Monitoring. Note the number of messages under Messages Current. In the EM, go to SOA > soa-infra (soa_server1) > default (or wherever you deployed your composite to) and click on JmsAdapterWriteSchema [1.0], then press the Test button. Under Input Arguments, enter any string into the text input field for the payload, for example Test Message then press Test Web Service. If the instance is successful you should see the same text in the Response message, “Test Message”. In the Console, refresh the Monitoring screen to confirm a new message has been written to the queue. Check the checkbox and press Show Messages. Click on the newest message and view its contents. They should include the full XML of the entered payload. 7. Troubleshooting If you get an exception similar to the following at runtime ... BINDING.JCA-12510 JCA Resource Adapter location error. Unable to locate the JCA Resource Adapter via .jca binding file element The JCA Binding Component is unable to startup the Resource Adapter specified in the element: location='eis/wls/QueueTest'. The reason for this is most likely that either 1) the Resource Adapters RAR file has not been deployed successfully to the WebLogic Application server or 2) the '' element in weblogic-ra.xml has not been set to eis/wls/QueueTest. In the last case you will have to add a new WebLogic JCA connection factory (deploy a RAR). Please correct this and then restart the Application Server at oracle.integration.platform.blocks.adapter.fw.AdapterBindingException. createJndiLookupException(AdapterBindingException.java:130) at oracle.integration.platform.blocks.adapter.fw.jca.cci. JCAConnectionManager$JCAConnectionPool.createJCAConnectionFactory (JCAConnectionManager.java:1387) at oracle.integration.platform.blocks.adapter.fw.jca.cci. JCAConnectionManager$JCAConnectionPool.newPoolObject (JCAConnectionManager.java:1285) ... then this is very likely due to an incorrect JNDI name entered for the JMS Connection in the JMS Adapter Wizard. Recheck those steps. The error message prints the name of the JNDI name used. In this example, it was incorrectly entered as eis/wls/QueueTest instead of eis/wls/TestQueue. This concludes this example. Best regards John-Brown Evans Oracle Technology Proactive Support Delivery

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  • Visual Studio 2010 Zooming – Keyboard Commands, Global Zoom

    - by Jon Galloway
    One of my favorite features in Visual Studio 2010 is zoom. It first caught my attention as a useful tool for screencasts and presentations, but after getting used to it I’m finding that it’s really useful when I’m developing – letting me zoom out to see the big picture, then zoom in to concentrate on a few lines of code. Zooming without the scroll wheel The common way you’ll see this feature demonstrated is with the mouse wheel – you hold down the control key and scroll up or down to change font size. However, I’m often using this on my laptop, which doesn’t have a mouse wheel. It turns out that there are other ways to control zooming in Visual Studio 2010. Keyboard commands You can use Control+Shift+Comma to zoom out and Control+Shift+Period to zoom in. I find it’s easier to remember these by the greater-than / less-than signs, so it’s really Control+> to zoom in and Control+< to zoom out. Like most Visual Studio commands, you can change those the keyboard buttons. In the tools menu, select Options / Keyboard, then either scroll down the list to the three View.Zoom commands or filter by typing View.Zoom into the “Show commands containing” textbox. The Scroll Dropdown If you forget the keyboard commands and you don’t have a scroll wheel, there’s a zoom menu in the text editor. I’m mostly pointing it out because I’ve been using Visual Studio 2010 for months and never noticed it until this week. It’s down in the lower left corner. Keeping Zoom In Sync Across All Tabs Zoom setting is per-tab, which is a problem if you’re cranking up your font sizes for a presentation. Fortunately there’s a great new Visual Studio Extension called Presentation Zoom. It’s a nice, simple extension that just does one thing – updates all your editor windows to keep the zoom setting in sync. It’s written by Chris Granger, a Visual Studio Program Manager, in case you’re worried about installing random extensions. See it in action Of course, if you’ve got Visual Studio 2010 installed, you’ve hopefully already been zooming like mad as you read this. If not, you can watch a 2 minute video by the Visual Studio showing it off.

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  • Improving Partitioned Table Join Performance

    - by Paul White
    The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

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  • Setup Reverse DNS with Cpanel and WHM?

    - by m3d
    I needed to set-up a reverse DNS via cpanel. I followed the steps in this tutorial but it didn't work: http://docs.cpanel.net/twiki/bin/view/11_30/WHMDocs/RdnsForBind. I use my own name servers registered with go-daddy. But I am with VPS hosting company. I did use a new serial number and exactly as the tutorial however didnt seems to be working When I check this via windows nslookup {ip-address} I still get the my hosting company name, when reversed.

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  • C#/.NET Little Wonders: The Concurrent Collections (1 of 3)

    - by James Michael Hare
    Once again we consider some of the lesser known classes and keywords of C#.  In the next few weeks, we will discuss the concurrent collections and how they have changed the face of concurrent programming. This week’s post will begin with a general introduction and discuss the ConcurrentStack<T> and ConcurrentQueue<T>.  Then in the following post we’ll discuss the ConcurrentDictionary<T> and ConcurrentBag<T>.  Finally, we shall close on the third post with a discussion of the BlockingCollection<T>. For more of the "Little Wonders" posts, see the index here. A brief history of collections In the beginning was the .NET 1.0 Framework.  And out of this framework emerged the System.Collections namespace, and it was good.  It contained all the basic things a growing programming language needs like the ArrayList and Hashtable collections.  The main problem, of course, with these original collections is that they held items of type object which means you had to be disciplined enough to use them correctly or you could end up with runtime errors if you got an object of a type you weren't expecting. Then came .NET 2.0 and generics and our world changed forever!  With generics the C# language finally got an equivalent of the very powerful C++ templates.  As such, the System.Collections.Generic was born and we got type-safe versions of all are favorite collections.  The List<T> succeeded the ArrayList and the Dictionary<TKey,TValue> succeeded the Hashtable and so on.  The new versions of the library were not only safer because they checked types at compile-time, in many cases they were more performant as well.  So much so that it's Microsoft's recommendation that the System.Collections original collections only be used for backwards compatibility. So we as developers came to know and love the generic collections and took them into our hearts and embraced them.  The problem is, thread safety in both the original collections and the generic collections can be problematic, for very different reasons. Now, if you are only doing single-threaded development you may not care – after all, no locking is required.  Even if you do have multiple threads, if a collection is “load-once, read-many” you don’t need to do anything to protect that container from multi-threaded access, as illustrated below: 1: public static class OrderTypeTranslator 2: { 3: // because this dictionary is loaded once before it is ever accessed, we don't need to synchronize 4: // multi-threaded read access 5: private static readonly Dictionary<string, char> _translator = new Dictionary<string, char> 6: { 7: {"New", 'N'}, 8: {"Update", 'U'}, 9: {"Cancel", 'X'} 10: }; 11:  12: // the only public interface into the dictionary is for reading, so inherently thread-safe 13: public static char? Translate(string orderType) 14: { 15: char charValue; 16: if (_translator.TryGetValue(orderType, out charValue)) 17: { 18: return charValue; 19: } 20:  21: return null; 22: } 23: } Unfortunately, most of our computer science problems cannot get by with just single-threaded applications or with multi-threading in a load-once manner.  Looking at  today's trends, it's clear to see that computers are not so much getting faster because of faster processor speeds -- we've nearly reached the limits we can push through with today's technologies -- but more because we're adding more cores to the boxes.  With this new hardware paradigm, it is even more important to use multi-threaded applications to take full advantage of parallel processing to achieve higher application speeds. So let's look at how to use collections in a thread-safe manner. Using historical collections in a concurrent fashion The early .NET collections (System.Collections) had a Synchronized() static method that could be used to wrap the early collections to make them completely thread-safe.  This paradigm was dropped in the generic collections (System.Collections.Generic) because having a synchronized wrapper resulted in atomic locks for all operations, which could prove overkill in many multithreading situations.  Thus the paradigm shifted to having the user of the collection specify their own locking, usually with an external object: 1: public class OrderAggregator 2: { 3: private static readonly Dictionary<string, List<Order>> _orders = new Dictionary<string, List<Order>>(); 4: private static readonly _orderLock = new object(); 5:  6: public void Add(string accountNumber, Order newOrder) 7: { 8: List<Order> ordersForAccount; 9:  10: // a complex operation like this should all be protected 11: lock (_orderLock) 12: { 13: if (!_orders.TryGetValue(accountNumber, out ordersForAccount)) 14: { 15: _orders.Add(accountNumber, ordersForAccount = new List<Order>()); 16: } 17:  18: ordersForAccount.Add(newOrder); 19: } 20: } 21: } Notice how we’re performing several operations on the dictionary under one lock.  With the Synchronized() static methods of the early collections, you wouldn’t be able to specify this level of locking (a more macro-level).  So in the generic collections, it was decided that if a user needed synchronization, they could implement their own locking scheme instead so that they could provide synchronization as needed. The need for better concurrent access to collections Here’s the problem: it’s relatively easy to write a collection that locks itself down completely for access, but anything more complex than that can be difficult and error-prone to write, and much less to make it perform efficiently!  For example, what if you have a Dictionary that has frequent reads but in-frequent updates?  Do you want to lock down the entire Dictionary for every access?  This would be overkill and would prevent concurrent reads.  In such cases you could use something like a ReaderWriterLockSlim which allows for multiple readers in a lock, and then once a writer grabs the lock it blocks all further readers until the writer is done (in a nutshell).  This is all very complex stuff to consider. Fortunately, this is where the Concurrent Collections come in.  The Parallel Computing Platform team at Microsoft went through great pains to determine how to make a set of concurrent collections that would have the best performance characteristics for general case multi-threaded use. Now, as in all things involving threading, you should always make sure you evaluate all your container options based on the particular usage scenario and the degree of parallelism you wish to acheive. This article should not be taken to understand that these collections are always supperior to the generic collections. Each fills a particular need for a particular situation. Understanding what each container is optimized for is key to the success of your application whether it be single-threaded or multi-threaded. General points to consider with the concurrent collections The MSDN points out that the concurrent collections all support the ICollection interface. However, since the collections are already synchronized, the IsSynchronized property always returns false, and SyncRoot always returns null.  Thus you should not attempt to use these properties for synchronization purposes. Note that since the concurrent collections also may have different operations than the traditional data structures you may be used to.  Now you may ask why they did this, but it was done out of necessity to keep operations safe and atomic.  For example, in order to do a Pop() on a stack you have to know the stack is non-empty, but between the time you check the stack’s IsEmpty property and then do the Pop() another thread may have come in and made the stack empty!  This is why some of the traditional operations have been changed to make them safe for concurrent use. In addition, some properties and methods in the concurrent collections achieve concurrency by creating a snapshot of the collection, which means that some operations that were traditionally O(1) may now be O(n) in the concurrent models.  I’ll try to point these out as we talk about each collection so you can be aware of any potential performance impacts.  Finally, all the concurrent containers are safe for enumeration even while being modified, but some of the containers support this in different ways (snapshot vs. dirty iteration).  Once again I’ll highlight how thread-safe enumeration works for each collection. ConcurrentStack<T>: The thread-safe LIFO container The ConcurrentStack<T> is the thread-safe counterpart to the System.Collections.Generic.Stack<T>, which as you may remember is your standard last-in-first-out container.  If you think of algorithms that favor stack usage (for example, depth-first searches of graphs and trees) then you can see how using a thread-safe stack would be of benefit. The ConcurrentStack<T> achieves thread-safe access by using System.Threading.Interlocked operations.  This means that the multi-threaded access to the stack requires no traditional locking and is very, very fast! For the most part, the ConcurrentStack<T> behaves like it’s Stack<T> counterpart with a few differences: Pop() was removed in favor of TryPop() Returns true if an item existed and was popped and false if empty. PushRange() and TryPopRange() were added Allows you to push multiple items and pop multiple items atomically. Count takes a snapshot of the stack and then counts the items. This means it is a O(n) operation, if you just want to check for an empty stack, call IsEmpty instead which is O(1). ToArray() and GetEnumerator() both also take snapshots. This means that iteration over a stack will give you a static view at the time of the call and will not reflect updates. Pushing on a ConcurrentStack<T> works just like you’d expect except for the aforementioned PushRange() method that was added to allow you to push a range of items concurrently. 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: // but you can also push multiple items in one atomic operation (no interleaves) 7: stack.PushRange(new [] { "Second", "Third", "Fourth" }); For looking at the top item of the stack (without removing it) the Peek() method has been removed in favor of a TryPeek().  This is because in order to do a peek the stack must be non-empty, but between the time you check for empty and the time you execute the peek the stack contents may have changed.  Thus the TryPeek() was created to be an atomic check for empty, and then peek if not empty: 1: // to look at top item of stack without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (stack.TryPeek(out item)) 5: { 6: Console.WriteLine("Top item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Stack was empty."); 11: } Finally, to remove items from the stack, we have the TryPop() for single, and TryPopRange() for multiple items.  Just like the TryPeek(), these operations replace Pop() since we need to ensure atomically that the stack is non-empty before we pop from it: 1: // to remove items, use TryPop or TryPopRange to get multiple items atomically (no interleaves) 2: if (stack.TryPop(out item)) 3: { 4: Console.WriteLine("Popped " + item); 5: } 6:  7: // TryPopRange will only pop up to the number of spaces in the array, the actual number popped is returned. 8: var poppedItems = new string[2]; 9: int numPopped = stack.TryPopRange(poppedItems); 10:  11: foreach (var theItem in poppedItems.Take(numPopped)) 12: { 13: Console.WriteLine("Popped " + theItem); 14: } Finally, note that as stated before, GetEnumerator() and ToArray() gets a snapshot of the data at the time of the call.  That means if you are enumerating the stack you will get a snapshot of the stack at the time of the call.  This is illustrated below: 1: var stack = new ConcurrentStack<string>(); 2:  3: // adding to stack is much the same as before 4: stack.Push("First"); 5:  6: var results = stack.GetEnumerator(); 7:  8: // but you can also push multiple items in one atomic operation (no interleaves) 9: stack.PushRange(new [] { "Second", "Third", "Fourth" }); 10:  11: while(results.MoveNext()) 12: { 13: Console.WriteLine("Stack only has: " + results.Current); 14: } The only item that will be printed out in the above code is "First" because the snapshot was taken before the other items were added. This may sound like an issue, but it’s really for safety and is more correct.  You don’t want to enumerate a stack and have half a view of the stack before an update and half a view of the stack after an update, after all.  In addition, note that this is still thread-safe, whereas iterating through a non-concurrent collection while updating it in the old collections would cause an exception. ConcurrentQueue<T>: The thread-safe FIFO container The ConcurrentQueue<T> is the thread-safe counterpart of the System.Collections.Generic.Queue<T> class.  The concurrent queue uses an underlying list of small arrays and lock-free System.Threading.Interlocked operations on the head and tail arrays.  Once again, this allows us to do thread-safe operations without the need for heavy locks! The ConcurrentQueue<T> (like the ConcurrentStack<T>) has some departures from the non-concurrent counterpart.  Most notably: Dequeue() was removed in favor of TryDequeue(). Returns true if an item existed and was dequeued and false if empty. Count does not take a snapshot It subtracts the head and tail index to get the count.  This results overall in a O(1) complexity which is quite good.  It’s still recommended, however, that for empty checks you call IsEmpty instead of comparing Count to zero. ToArray() and GetEnumerator() both take snapshots. This means that iteration over a queue will give you a static view at the time of the call and will not reflect updates. The Enqueue() method on the ConcurrentQueue<T> works much the same as the generic Queue<T>: 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5: queue.Enqueue("Second"); 6: queue.Enqueue("Third"); For front item access, the TryPeek() method must be used to attempt to see the first item if the queue.  There is no Peek() method since, as you’ll remember, we can only peek on a non-empty queue, so we must have an atomic TryPeek() that checks for empty and then returns the first item if the queue is non-empty. 1: // to look at first item in queue without removing it, can use TryPeek. 2: // Note that there is no Peek(), this is because you need to check for empty first. TryPeek does. 3: string item; 4: if (queue.TryPeek(out item)) 5: { 6: Console.WriteLine("First item was " + item); 7: } 8: else 9: { 10: Console.WriteLine("Queue was empty."); 11: } Then, to remove items you use TryDequeue().  Once again this is for the same reason we have TryPeek() and not Peek(): 1: // to remove items, use TryDequeue. If queue is empty returns false. 2: if (queue.TryDequeue(out item)) 3: { 4: Console.WriteLine("Dequeued first item " + item); 5: } Just like the concurrent stack, the ConcurrentQueue<T> takes a snapshot when you call ToArray() or GetEnumerator() which means that subsequent updates to the queue will not be seen when you iterate over the results.  Thus once again the code below will only show the first item, since the other items were added after the snapshot. 1: var queue = new ConcurrentQueue<string>(); 2:  3: // adding to queue is much the same as before 4: queue.Enqueue("First"); 5:  6: var iterator = queue.GetEnumerator(); 7:  8: queue.Enqueue("Second"); 9: queue.Enqueue("Third"); 10:  11: // only shows First 12: while (iterator.MoveNext()) 13: { 14: Console.WriteLine("Dequeued item " + iterator.Current); 15: } Using collections concurrently You’ll notice in the examples above I stuck to using single-threaded examples so as to make them deterministic and the results obvious.  Of course, if we used these collections in a truly multi-threaded way the results would be less deterministic, but would still be thread-safe and with no locking on your part required! For example, say you have an order processor that takes an IEnumerable<Order> and handles each other in a multi-threaded fashion, then groups the responses together in a concurrent collection for aggregation.  This can be done easily with the TPL’s Parallel.ForEach(): 1: public static IEnumerable<OrderResult> ProcessOrders(IEnumerable<Order> orderList) 2: { 3: var proxy = new OrderProxy(); 4: var results = new ConcurrentQueue<OrderResult>(); 5:  6: // notice that we can process all these in parallel and put the results 7: // into our concurrent collection without needing any external locking! 8: Parallel.ForEach(orderList, 9: order => 10: { 11: var result = proxy.PlaceOrder(order); 12:  13: results.Enqueue(result); 14: }); 15:  16: return results; 17: } Summary Obviously, if you do not need multi-threaded safety, you don’t need to use these collections, but when you do need multi-threaded collections these are just the ticket! The plethora of features (I always think of the movie The Three Amigos when I say plethora) built into these containers and the amazing way they acheive thread-safe access in an efficient manner is wonderful to behold. Stay tuned next week where we’ll continue our discussion with the ConcurrentBag<T> and the ConcurrentDictionary<TKey,TValue>. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this wonderful whitepaper by the Microsoft Parallel Computing Platform team here.   Tweet Technorati Tags: C#,.NET,Concurrent Collections,Collections,Multi-Threading,Little Wonders,BlackRabbitCoder,James Michael Hare

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  • iPad client for SharePoint

    - by gabouy
    I´m pleased to announce that at SouthLabs we´ve released a native iPad client for SharePoint , called SharePlus Office Mobile Client , already available in the app store . It consumes SharePoint's web services API, and supports offline browsing. The following is a brief presentation on it, with some screenshots. SharePlus iPad client for SharePoint View more presentations from SouthLabs ....(read more)

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  • Xobni Free Powers Up Outlook’s Search and Contacts

    - by Matthew Guay
    Want to find out more about your contacts, discover email trends, and even sync Yahoo! email accounts in Outlook?  Here’s how you can do this and more with Xobni Free. Email is one of the most important communications mediums today, but even with all of the advances in Outlook over the years it can still be difficult to keep track of conversations, files, and contacts.  Xobni makes it easy by indexing your emails and organizing them by sender.  You can use its powerful search to quickly find any email, find related messages, and then view more information about that contact with information from social networks.  And, to top it off, it even lets you view your Yahoo! emails directly in Outlook without upgrading to a Yahoo! Plus account.  Xobni runs in Outlook 2003, 2007, and 2010, including the 64 bit version of Outlook 2010, and users of older versions will especially enjoy the new features Xobni brings for free. Getting started Download the Xobni Free installer (link below), and run to start the installation.  Make sure to exit Outlook before installing.  Xobni may need to download additional files which may take a few moments. When the download is finished, proceed with the install as normal.  You can opt out of the Product Improvement Program at the end of the installation by unchecking the box.  Additionally, you are asked to share Xobni with your friends on social networks, but this is not required.   Next time you open Outlook, you’ll notice the new Xobni sidebar in Outlook.  You can choose to watch an introduction video that will help you quickly get up to speed on how Xobni works. While this is playing, Xobni is working at indexing your email in the background.  Once the first indexing is finished, click Let’s Go! to start using Xobni. Here’s how Xobni looks in Outlook 2010: Advanced Email Information Select an email, and now you can see lots of info about it in your new Xobni sidebar.   On the top of the sidebar, select the graph icon to see when and how often you email with a contact.  Each contact is given an Xobni rank so you can quickly see who you email the most.   You can see all related emails sorted into conversations, and also all attachments in the conversation, not just this email. Xobni can also show you all scheduled appointments and links exchanged with a contact, but this is only available in the Plus version.  If you’d rather not see the tab for a feature you can’t use, click Don’t show this tab to banish it from Xobni for good.   Searching emails from the Xobni toolbar is very fast, and you can preview a message by simply hovering over it from the search pane. Get More Information About Your Contacts Xobni’s coolest feature is its social integration.  Whenever you select an email, you may see a brief bio, picture, and more, all pulled from social networks.   Select one of the tabs to find more information.  You may need to login to view information on your contacts from certain networks. The Twitter tab lets you see recent tweets.  Xobni will search for related Twitter accounts, and will ask you to confirm if the choice is correct.   Now you can see this contact’s recent Tweets directly from Outlook.   The Hoovers tab can give you interesting information about the businesses you’re in contact with. If the information isn’t correct, you can edit it and add your own information.  Click the Edit button, and the add any information you want.   You can also remove a network you don’t wish to see.  Right-click on the network tabs, select Manage Extensions, and uncheck any you don’t want to see. But sometimes online contact just doesn’t cut it.  For these times, click on the orange folder button to request a contact’s phone number or schedule a time with them. This will open a new email message ready to send with the information you want.  Edit as you please, and send. Add Yahoo! Email to Outlook for Free One of Xobni’s neatest features is that it let’s you add your Yahoo! email account to Outlook for free.  Click the gear icon in the bottom of the Xobni sidebar and select Options to set it up. Select the Integration tab, and click Enable to add Yahoo! mail to Xobni. Sign in with your Yahoo! account, and make sure to check the Keep me signed in box. Note that you may have to re-signin every two weeks to keep your Yahoo! account connected.  Select I agree to finish setting it up. Xobni will now download and index your recent Yahoo! mail. Your Yahoo! messages will only show up in the Xobni sidebar.  Whenever you select a contact, you will see related messages from your Yahoo! account as well.  Or, you can search from the sidebar to find individual messages from your Yahoo! account.  Note the Y! logo beside Yahoo! messages.   Select a message to read it in the Sidebar.  You can open the email in Yahoo! in your browser, or can reply to it using your default Outlook email account. If you have many older messages in your Yahoo! account, make sure to go back to the Integration tab and select Index Yahoo! Mail to index all of your emails. Conclusion Xobni is a great tool to help you get more out of your daily Outlook experience.  Whether you struggle to find attachments a coworker sent you or want to access Yahoo! email from Outlook, Xobni might be the perfect tool for you.  And with the extra things you learn about your contacts with the social network integration, you might boost your own PR skills without even trying! Link Download Xobni Similar Articles Productive Geek Tips Speed up Windows Vista Start Menu Search By Limiting ResultsFix for New Contact Group Button Not Displaying in VistaGet Maps and Directions to Your Contacts in Outlook 2007Backup Windows Mail Messages and Contacts in VistaHow to Import Gmail Contacts Into Outlook 2007 TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Acronis Online Backup DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows iFixit Offers Gadget Repair Manuals Online Vista style sidebar for Windows 7 Create Nice Charts With These Web Based Tools Track Daily Goals With 42Goals Video Toolbox is a Superb Online Video Editor Fun with 47 charts and graphs

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  • Slides and Code from my Silverlight MVVM Talk at DevConnections

    - by dwahlin
    I had a great time at the DevConnections conference in Las Vegas this year where Visual Studio 2010 and Silverlight 4 were launched. While at the conference I had the opportunity to give a full-day Silverlight workshop as well as 4 different talks and met a lot of people developing applications in Silverlight. I also had a chance to appear on a live broadcast of Channel 9 with John Papa, Ward Bell and Shawn Wildermuth, record a video with Rick Strahl covering jQuery versus Silverlight and record a few podcasts on Silverlight and ASP.NET MVC 2.  It was a really busy 4 days but I had a lot of fun chatting with people and hearing about different business problems they were solving with ASP.NET and/or Silverlight. Thanks to everyone who attended my sessions and took the time to ask questions and stop by to talk one-on-one. One of the talks I gave covered the Model-View-ViewModel pattern and how it can be used to build architecturally sound applications. Topics covered in the talk included: Understanding the MVVM pattern Benefits of the MVVM pattern Creating a ViewModel class Implementing INotifyPropertyChanged in a ViewModelBase class Binding a ViewModel declaratively in XAML Binding a ViewModel with code ICommand and ButtonBase commanding support in Silverlight 4 Using InvokeCommandBehavior to handle additional commanding needs Working with ViewModels and Sample Data in Blend Messaging support with EventBus classes, EventAggregator and Messenger My personal take on code in a code-beside file (I’m all in favor of it when used appropriately for message boxes, child windows, animations, etc.) One of the samples I showed in the talk was intended to teach all of the concepts mentioned above while keeping things as simple as possible.  The sample demonstrates quite a few things you can do with Silverlight and the MVVM pattern so check it out and feel free to leave feedback about things you like, things you’d do differently or anything else. MVVM is simply a pattern, not a way of life so there are many different ways to implement it. If you’re new to the subject of MVVM check out the following resources. I wish this talk would’ve been recorded (especially since my live and canned demos all worked :-)) but these resources will help get you going quickly. Getting Started with the MVVM Pattern in Silverlight Applications Model-View-ViewModel (MVVM) Explained Laurent Bugnion’s Excellent Talk at MIX10     Download sample code and slides from my DevConnections talk     For more information about onsite, online and video training, mentoring and consulting solutions for .NET, SharePoint or Silverlight please visit http://www.thewahlingroup.com.

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  • Hey, Google: It’s Time to Add Multi-Window Multitasking To Android

    - by Chris Hoffman
    In 2012, Google’s Dianne Hackborn threatened to revoke CyanogenMod’s access to the Android Market if they moved forward with adding “Cornerstone” multitasking to their custom ROM. Samsung has since created their own multi-window multitasking feature. Dianne Hackborn said this “is something that needs to be done at the mainline platform level” so apps wouldn’t break. She was right — Android needs this as a standard feature and it’s time for Google to provide it. Doesn’t Android Have Multitasking? Android originally stood out from Apple’s iOS with its powerful multitasking. Applications can continue running in the background while you’re using another application. This makes Android powerful — you can even have BitTorrent clients downloading files in the background while using another app. Android still kept the design of a single app on screen at a time. This made a lot of sense when Android only ran on smartphones with small screens. Today, Android runs on everything from smaller smartphones all the way up to huge “phablets” like the Galaxy Note. Android has gone beyond phones and runs on 12-inch tablets, convertibles with keyboard docks, laptops, and even Android desktops. Android isn’t just a phone operating system. Samsung’s Multi-Window Isn’t Good Enough Samsung has tried to add value to Android by adding a multi-window feature. When you’re using a high-end phone like the Galaxy Note or Galaxy S, or a Galaxy tablet, you have the ability to run certain apps side-by-side with each other. There are big problems here. This only works on Samsung devices, and only on specific Samsung devices. To add support for this feature in a way that doesn’t break other apps, Samsung’s multi-window feature also only works with specific apps. You can’t just run any app in multi-window view, only the apps on the Multi Window bar Samsung provides. This prevents third-party apps from breaking, which is what Google was worried about with CyanogenMod’s Cornerstone feature. A feature that only works with a handful of apps on specific devices from a single manufacturer isn’t good enough. This feature needs to work on every Android device — or at least ones with suitably large screens and powerful enough internals. It needs to be an Android platform feature so application developers can ensure their apps will work properly with it on every device. Android developers shouldn’t have to add support for each manufacturer’s own multi-window feature if other manufacturers decide to copy Samsung. Floating Apps Are a Dirty Hack Floating apps also enable real multitasking. Remember that Android allows apps to run in the background while you’re using an app in the foreground. These apps can present interfaces that appear floating above the current app — think of it like using “always on top” to make a window always appear over every other app on a desktop operating system. You can install floating apps to browse the web, take notes, chat, and watch videos while using any app. Only apps specifically designed to run as floating apps will work, so you have to seek them out. Floating apps are also awkward to use because they float over the app you’re using, blocking parts of its interface. Microsoft added floating-window support to Skype for Android. You can have a video conversation and the other person’s face will always appear on your screen, even when you leave the Skype app. Microsoft is using more of Android’s multi-window multitasking power than Google is. Custom ROMs and Root-Only Tweaks Aren’t Acceptable Some custom ROMs are adding this feature to Android. Google threatened to revoke CyanogenMod’s access to the Android Market (now known as Google Play) if they added this feature because it could potentially break third-party apps. Today, other custom ROMs are working on split-screen multitasking. Samsung added their own version to their own devices. You can also get this feature by using a root-only Xposed Framework tweak known as XMultiWindow. If you have root access, you can get multi-window multitasking or any app on your device. This shouldn’t require rooting your device or installing a custom ROM. These third-party solutions often have awkward interfaces and bugs. We need an integrated, supported solution that works the same on every device. Why Multi-Window is Important Microsoft’s Windows 8.1 stands out among tablet operating systems for its powerful multitasking support, allowing you to view several apps side-by-side at the same time. Apple is also reported to be working on adding side-by-side apps to the iPad with iOS 8. On every competitor’s operating system, you’ll be able to view a web page while you write an email, watch a video while you browse the web, or chat with someone while you do anything else. But Android’s still remained frozen in time. Despite all Android’s underlying power — and despite the way Android allows apps to adapt to different screen sizes — Google is resisting adding this feature. Large-screen Android tablets like the Nexus 10 (remember that tablet Google hasn’t updated in over 18 months?) need this feature. So do huge phones, convertibles, laptops, and Android desktops. If tablets are the future of personal computing, we should be able to do more than one thing at a time on our tablets’ big screens. Microsoft, Samsung, and even Apple are realizing this — now it’s Google’s turn. Image Credit: Sergey Galyonkin on Flickr, Karlis Dambrans on Flickr

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  • Daily tech links for .net and related technologies - Apr 26-28, 2010

    - by SanjeevAgarwal
    Daily tech links for .net and related technologies - Apr 26-28, 2010 Web Development MVC: Unit Testing Action Filters - Donn ASP.NET MVC 2: Ninja Black Belt Tips - Scott Hanselman Turn on Compile-time View Checking for ASP.NET MVC Projects in TFS Build 2010 - Jim Lamb Web Design List of 25+ New tags introduced in HTML 5 - techfreakstuff 15 CSS Habits to Develop for Frustration-Free Coding - noupe Silverlight, WPF & RIA Essential Silverlight and WPF Skills: The UI Thread, Dispatchers, Background...(read more)

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  • ASP.NET MVC Case Studies

    - by shiju
     The below are the some of the case studies of ASP.NET MVC Jwaala - Online Banking Solution Benefits after ASP.NET MVC Replaces Ruby on Rails, Linux http://www.microsoft.com/casestudies/Case_Study_Detail.aspx?casestudyid=4000006675 Stack Overflow - Developers See Faster Web Coding, Better Performance with Model-View-Controller http://www.microsoft.com/casestudies/Case_Study_Detail.aspx?casestudyid=4000006676 Kelley Blue Book - Pioneer Provider of Vehicle-Pricing Information Uses Technology to Expand Reach http://www.microsoft.com/casestudies/Case_Study_Detail.aspx?casestudyid=4000006272 

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  • [GEEK SCHOOL] Network Security 4: Windows Firewall: Your System’s Best Defense

    - by Ciprian Rusen
    If you have your computer connected to a network, or directly to your Internet connection, then having a firewall is an absolute necessity. In this lesson we will discuss the Windows Firewall – one of the best security features available in Windows! The Windows Firewall made its debut in Windows XP. Prior to that, Windows system needed to rely on third-party solutions or dedicated hardware to protect them from network-based attacks. Over the years, Microsoft has done a great job with it and it is one of the best firewalls you will ever find for Windows operating systems. Seriously, it is so good that some commercial vendors have decided to piggyback on it! Let’s talk about what you will learn in this lesson. First, you will learn about what the Windows Firewall is, what it does, and how it works. Afterward, you will start to get your hands dirty and edit the list of apps, programs, and features that are allowed to communicate through the Windows Firewall depending on the type of network you are connected to. Moving on from there, you will learn how to add new apps or programs to the list of allowed items and how to remove the apps and programs that you want to block. Last but not least, you will learn how to enable or disable the Windows Firewall, for only one type of networks or for all network connections. By the end of this lesson, you should know enough about the Windows Firewall to use and manage it effectively. What is the Windows Firewall? Windows Firewall is an important security application that’s built into Windows. One of its roles is to block unauthorized access to your computer. The second role is to permit authorized data communications to and from your computer. Windows Firewall does these things with the help of rules and exceptions that are applied both to inbound and outbound traffic. They are applied depending on the type of network you are connected to and the location you have set for it in Windows, when connecting to the network. Based on your choice, the Windows Firewall automatically adjusts the rules and exceptions applied to that network. This makes the Windows Firewall a product that’s silent and easy to use. It bothers you only when it doesn’t have any rules and exceptions for what you are trying to do or what the programs running on your computer are trying to do. If you need a refresher on the concept of network locations, we recommend you to read our How-To Geek School class on Windows Networking. Another benefit of the Windows Firewall is that it is so tightly and nicely integrated into Windows and all its networking features, that some commercial vendors decided to piggyback onto it and use it in their security products. For example, products from companies like Trend Micro or F-Secure no longer provide their proprietary firewall modules but use the Windows Firewall instead. Except for a few wording differences, the Windows Firewall works the same in Windows 7 and Windows 8.x. The only notable difference is that in Windows 8.x you will see the word “app” being used instead of “program”. Where to Find the Windows Firewall By default, the Windows Firewall is turned on and you don’t need to do anything special in order for it work. You will see it displaying some prompts once in a while but they show up so rarely that you might forget that is even working. If you want to access it and configure the way it works, go to the Control Panel, then go to “System and Security” and select “Windows Firewall”. Now you will see the Windows Firewall window where you can get a quick glimpse on whether it is turned on and the type of network you are connected to: private networks or public network. For the network type that you are connected to, you will see additional information like: The state of the Windows Firewall How the Windows Firewall deals with incoming connections The active network When the Windows Firewall will notify you You can easily expand the other section and view the default settings that apply when connecting to networks of that type. If you have installed a third-party security application that also includes a firewall module, chances are that the Windows Firewall has been disabled, in order to avoid performance issues and conflicts between the two security products. If that is the case for your computer or device, you won’t be able to view any information in the Windows Firewall window and you won’t be able to configure the way it works. Instead, you will see a warning that says: “These settings are being managed by vendor application – Application Name”. In the screenshot below you can see an example of how this looks. How to Allow Desktop Applications Through the Windows Firewall Windows Firewall has a very comprehensive set of rules and most Windows programs that you install add their own exceptions to the Windows Firewall so that they receive network and Internet access. This means that you will see prompts from the Windows Firewall on occasion, generally when you install programs that do not add their own exceptions to the Windows Firewall’s list. In a Windows Firewall prompt, you are asked to select the network locations to which you allow access for that program: private networks or public networks. By default, Windows Firewall selects the checkbox that’s appropriate for the network you are currently using. You can decide to allow access for both types of network locations or just to one of them. To apply your setting press “Allow access”. If you want to block network access for that program, press “Cancel” and the program will be set as blocked for both network locations. At this step you should note that only administrators can set exceptions in the Windows Firewall. If you are using a standard account without administrator permissions, the programs that do not comply with the Windows Firewall rules and exceptions are automatically blocked, without any prompts being shown. You should note that in Windows 8.x you will never see any Windows Firewall prompts related to apps from the Windows Store. They are automatically given access to the network and the Internet based on the assumption that you are aware of the permissions they require based on the information displayed by the Windows Store. Windows Firewall rules and exceptions are automatically created for each app that you install from the Windows Store. However, you can easily block access to the network and the Internet for any app, using the instructions in the next section. How to Customize the Rules for Allowed Apps Windows Firewall allows any user with an administrator account to change the list of rules and exceptions applied for apps and desktop programs. In order to do this, first start the Windows Firewall. On the column on the left, click or tap “Allow an app or feature through Windows Firewall” (in Windows 8.x) or “Allow a program or feature through Windows Firewall” (in Windows 7). Now you see the list of apps and programs that are allowed to communicate through the Windows Firewall. At this point, the list is grayed out and you can only view which apps, features, and programs have rules that are enabled in the Windows Firewall.

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  • Deployment Options for AutoVue 20.0 Users

    - by celine.beck
    AutoVue release 20.0 boasts a brand new architecture. As part of this product rearchitecture, AutoVue can now be deployed either as a desktop deployment to serve the needs of individual users in their personal productivity; or in a Client / Server deployment for those that require connections to enterprise applications / back-end systems. The most common question that we hear from our customers about this new architecture is the following: "Is AutoVue Desktop Version still part of release 20.0 and if so, what is the difference between AutoVue Desktop Version and the Desktop deployment of AutoVue release 20.0?" A detailed answer to these questions is provided in a very complete article entitled Understanding Deployment Options for AutoVue 19.3 Desktop Version users upgrading to AutoVue 20.0 (note 1058254.1) which was posted on My Oracle Support. Is AutoVue Desktop Version still part of AutoVue 20.0? Yes, AutoVue Desktop Version 20.0 is still available to customers and partners, as a maintenance release of AutoVue 19.3. As such, it will not contain any of the new capabilities featured in AutoVue release 20.0. All format enhancements and new format support have been added to release 20.0 Desktop Version though. What is the different between AutoVue Desktop Version 20.0 and the Desktop Deployment of AutoVue release 20.0? AutoVue 20.0 Desktop deployment works like the AutoVue Desktop version. It is installed as a standalone product on each user's machine and runs a local instance of AutoVue. The AutoVue 20.0 Desktop deployment includes all new features, formats and performance enhancements included in release 20.0 (walkthrough capability, improved compare, ...) What deployment options are available to AutoVue 19.3 Desktop Version customers? AutoVue Desktop Version users can evolve at their own pace to the new AutoVue platform. With release 20.0, customers can opt to: Option 1: Stay on AutoVue Desktop Version 20.0 Option 2: Migrate to AutoVue and select the desktop deployment method Option 3: Migrate to AutoVue and select the Client/Server deployment method What is the Client / Server deployment of AutoVue 20.0? The Client/Server deployment has AutoVue installed on a server, to which local client machines connect to access and view documents. AutoVue 20.0 Client Server Deployment allows users to leverage the new online/offline capabilities in release 20.0 and easily switch between online and offline modes of operation. With the Client/Server deployment, customers also get a complete, open and standards-based set of integration tools that allows them to tie AutoVue to any enterprise applications to provide users with a consistent view of data and business objects and expand workflow automation to document-based processes. Related articles: AutoVue Release 20.0 Now Available, New Walkthrough Capability in AutoVue 20.0, Watch the AutoVue 20.0 Release Webcast, April 27 at 12pm EST

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  • Oracle Unveils Oracle Social Relationship Management Suite at Oracle OpenWorld

    - by Richard Lefebvre
    New Service Enables Companies to Listen, Engage, Create, Market and Analyze Interactions across Multiple Social Platforms in Real-Time During his keynote presentation, Oracle CEO Larry Ellison announced the Oracle Social Relationship Management (SRM) Suite.   Oracle Social Relationship Management Suite is an integrated enterprise service that enables companies to listen, engage, create, market, and analyze interactions across multiple social platforms in real-time providing a holistic view of the consumer.   Oracle Social Relationship Management Suite is integrated with Oracle’s enterprise applications, including Oracle Fusion Marketing, Oracle Fusion Sales Catalog, Oracle ATG Web Commerce, and Oracle Enterprise Resource Planning (ERP), allowing organizations to use social to transform their corporate business processes and systems.   Additionally, Oracle Social Relationship Management Suite is integrated with Oracle Platform Services, including Oracle Java Cloud Service and Oracle Database Cloud Service, enabling marketing teams to integrate social with their custom Web pages, landing pages and marketing tools. Unleashing the Power of Social • Providing a holistic view of consumer interactions, Oracle Social Relationship Management Suite includes: Oracle Social Network (OSN): Provides a secure collaboration platform that supports real-time collaboration and networking for users inside and outside the organization. Oracle Social Marketing: Enables marketers to centrally create, publish, moderate, manage, measure and report across multiple social campaigns and platforms. It also helps marketers publish social content, engage fans and customize their brand's look and feel. Oracle Social Engagement & Monitoring Cloud Service: Enables organizations to analyze social media interactions while also empowering customer service and sales teams to effectively engage with customers and prospects. It gives organizations the tools they need to understand customers and take the appropriate actions by monitoring, listening, learning, and responding to signals and trends across the social web. Oracle Social Sites: provides brands and agencies a powerful and rich editing experience that end users can leverage to dynamically develop and launch social sites. Oracle Data and Insights. A service that caters to a growing enterprise need for externally information by providing information, directory and insights about common business entities. Supporting Quote “By fundamentally changing the way organizations connect with their different stakeholders, social is changing the rules of business,” said Thomas Kurian, executive vice president, Oracle Product Development. “With the Oracle Social Relationship Management Suite we are empowering our customers to embrace this change by integrating the tools required to listen, engage, create, market and analyze social interactions into existing applications and services.”

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  • TFS Auto Shelve - New Visual Studio 2010 / TFS 2010 Extension

    - by MikeParks
    We've been working with the Visual Studio 2010 SDK and the TFS 2010 SDK a lot recently to create new Visual Studio Extensions. You can find these extensions in the Visual Studio Gallery. If you're a developer/programmer, you should check it out, they have some pretty cool tools out there. I'd be surprised if you told me you went there and couldn't find any tools that could help you. One of the new extensions Cory and I made is called TFS Auto Shelve. Check out the description and read about it below. If you're interested and you have VS 2010 w/TFS 2010, feel free to try it out and let us know what you think. You can download it here: http://visualstudiogallery.msdn.microsoft.com/en-us/080540cb-e35f-4651-b71c-86c73e4a633d   Here's a description and screenshots of what it does: Automatically shelves the latest version of all pending changes from local TFS workspaces to the TFS Server every "x" number of minutes when solutions are opened.   ·         Purpose o    Created for Team Foundation Server 2010 and Visual Studio 2010 o    This tool is mainly aimed at the Programmer/Developer audience so they can always have the latest copy of their pending changes backed up to the TFS Server while coding ·         Functionality o    Menu options become active and automatic shelving begins when a solution that mapped to a TFS Workspace is opened in Visual Studio o    In Tools > TFS Auto Shelve (Running/NotRunning):  Automatic shelving can be turned on/off o    In Tools > TFS Auto Shelve Now : Shelve all code can be manually triggered o    Each TFS workspace has its own shelveset which is re-used to save the latest version of pending changes o    Shelvesets are named as Base Name + Workspace Name o    Shelveset comment contains item count o    If there are no pending changes, no shelvesets will be created/updated o    If a solution is opened that is not mapped to a TFS Workspace, menu options are disabled since shelving only works for mapped workspaces. ·         Configuration o    In Tools > Options > TFS Auto Shelve Options: Base Name is configurable o    In Tools > Options > TFS Auto Shelve Options: "x" number of minutes is configurable in options ·         Logging o    Custom Visual Studio Activity Logging is implemented. If you run into any errors, please startup Visual Studio with the /log switch, re-create the error, then close Visual Studio. You can browse to “%AppData%\Microsoft\VisualStudio\10.0\ActivityLog.XML” to view the log. Please feel free to inform us of any errors you see and we can work it out via email. ·         Other Helpful Information o    To view shelvesets, open Source Control Explorer, click on File > Source Control > Unshelve Pending Changes o    Workspaces can be modified by opening the Source Control Explorer > Clicking on Workspaces drop down > Click Workspaces… > Click Add / Edit / Removed   Thanks! - Mike

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  • A couple of nice features when using OracleTextSearch

    - by kyle.hatlestad
    If you have your UCM/URM instance configured to use the Oracle 11g database as the search engine, you can be using OracleTextSearch as the search definition. OracleTextSearch uses the advanced features of Oracle Text for indexing and searching. This includes the ability to specify metadata fields to be optimized for the search index, fast rebuilding, and index optimization. If you are on 10g of UCM, then you'll need to load the OracleTextSearch component that is available in the CS10gR35UpdateBundle component on the support site (patch #6907073). If you are on 11g, no component is needed. Then you specify the search indexer name with the configuration flag of SearchIndexerEngineName=OracleTextSearch. Please see the docs for other configuration settings and setup instructions. So I thought I would highlight a couple of other unique features available with OracleTextSearch. The first is the Drill Down feature. This feature allows you to specify specific metadata fields that will break down the results of that field based on the total results. So in the above graphic, you can see how it broke down the extensions and gives a count for each. Then you just need to click on that link to then drill into that result. This setting is perfect for option list fields and ones with a distinct set of values possible. By default, it will use the fields Type, Security Group, and Account (if enabled). But you can also specify your own fields. In 10g, you can use the following configuration entry: DrillDownFields=xWebsiteObjectType,dExtension,dSecurityGroup,dDocType And in 11g, you can specify it through the Configuration Manager applet. Simply click on the Advanced Search Design, highlight the field to filter, click Edit, and check 'Is a filter category'. The other feature you get with OracleTextSearch are search snippets. These snippets show the occurrence of the search term in context of their usage. This is very similar to how Google displays its results. If you are on 10g, this is enabled by default. If you are on 11g, you need to turn on the feature. The following configuration entry will enable it: OracleTextDisableSearchSnippet=false Once enabled, you can add the snippets to your search results. Go to Change View -> Customize and add a new search result view. In the Available Fields in the Special section, select Snippet and move it to the Main or Additional Information. If you want to include the snippets with the Classic results, you can add the idoc variable of <$srfDocSnippet$> to display them. One caveat is that this can effect search performance on large collections. So plan the infrastructure accordingly.

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  • LINQ to SQL Profiler

    In this article we will be taking a look at the new LINQ to SQL Profiler from HibernatingRhinos. This tool gives you a view into the goings on of LINQ to SQL. Not only does it allow you to see the SQL that is generated by your LINQ queries but it also shows you information about your connections, queries, as well as alerting you to all sorts of information that you might otherwise not know about.

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  • Routing Issue in ASP.NET MVC 3 RC 2

    - by imran_ku07
         Introduction:             Two weeks ago, ASP.NET MVC team shipped the ASP.NET MVC 3 RC 2 release. This release includes some new features and some performance optimization. This release also fixes most of the bugs but still some minor issues are present in this release. Some of these issues are already discussed by Scott Guthrie at Update on ASP.NET MVC 3 RC2 (and a workaround for a bug in it). In addition to these issues, I have found another issue in this release regarding routing. In this article, I will show you the issue regarding routing and a simple workaround for this issue.       Description:             The easiest way to understand an issue is to reproduce it in the application. So create a MVC 2 application and a MVC 3 RC 2 application. Then in both applications, just open global.asax file and update the default route as below,     routes.IgnoreRoute("{resource}.axd/{*pathInfo}"); routes.MapRoute( "Default", // Route name "{controller}/{action}/{id1}/{id2}", // URL with parameters new { controller = "Home", action = "Index", id1 = UrlParameter.Optional, id2 = UrlParameter.Optional } // Parameter defaults );              Then just open Index View and add the following lines,    <%@ Page Language="C#" MasterPageFile="~/Views/Shared/Site.Master" Inherits="System.Web.Mvc.ViewPage" %> <asp:Content ID="Content1" ContentPlaceHolderID="TitleContent" runat="server"> Home Page </asp:Content> <asp:Content ID="Content2" ContentPlaceHolderID="MainContent" runat="server"> <% Html.RenderAction("About"); %> </asp:Content>             The above view will issue a child request to About action method. Now run both applications. ASP.NET MVC 2 application will run just fine. But ASP.NET MVC 3 RC 2 application will throw an exception as shown below,                  You may think that this is a routing issue but this is not the case here as both ASP.NET MVC 2 and ASP.NET MVC  3 RC 2 applications(created above) are built with .NET Framework 4.0 and both will use the same routing defined in System.Web. Something is wrong in ASP.NET MVC 3 RC 2. So after digging into ASP.NET MVC source code, I have found that the UrlParameter class in ASP.NET MVC 3 RC 2 overrides the ToString method which simply return an empty string.     public sealed class UrlParameter { public static readonly UrlParameter Optional = new UrlParameter(); private UrlParameter() { } public override string ToString() { return string.Empty; } }             In MVC 2 the ToString method was not overridden. So to quickly fix the above problem just replace UrlParameter.Optional default value with a different value other than null or empty(for example, a single white space) or replace UrlParameter.Optional default value with a new class object containing the same code as UrlParameter class have except the ToString method is not overridden (or with a overridden ToString method that return a string value other than null or empty). But by doing this you will loose the benefit of ASP.NET MVC 2 Optional URL Parameters. There may be many different ways to fix the above problem and not loose the benefit of optional parameters. Here I will create a new class MyUrlParameter with the same code as UrlParameter class have except the ToString method is not overridden. Then I will create a base controller class which contains a constructor to remove all MyUrlParameter route data parameters, same like ASP.NET MVC doing with UrlParameter route data parameters early in the request.     public class BaseController : Controller { public BaseController() { if (System.Web.HttpContext.Current.CurrentHandler is MvcHandler) { RouteValueDictionary rvd = ((MvcHandler)System.Web.HttpContext.Current.CurrentHandler).RequestContext.RouteData.Values; string[] matchingKeys = (from entry in rvd where entry.Value == MyUrlParameter.Optional select entry.Key).ToArray(); foreach (string key in matchingKeys) { rvd.Remove(key); } } } } public class HomeController : BaseController { public ActionResult Index(string id1) { ViewBag.Message = "Welcome to ASP.NET MVC!"; return View(); } public ActionResult About() { return Content("Child Request Contents"); } }     public sealed class MyUrlParameter { public static readonly MyUrlParameter Optional = new MyUrlParameter(); private MyUrlParameter() { } }     routes.IgnoreRoute("{resource}.axd/{*pathInfo}"); routes.MapRoute( "Default", // Route name "{controller}/{action}/{id1}/{id2}", // URL with parameters new { controller = "Home", action = "Index", id1 = MyUrlParameter.Optional, id2 = MyUrlParameter.Optional } // Parameter defaults );             MyUrlParameter class is a copy of UrlParameter class except that MyUrlParameter class not overrides the ToString method. Note that the default route is modified to use MyUrlParameter.Optional instead of UrlParameter.Optional. Also note that BaseController class constructor is removing MyUrlParameter parameters from the current request route data so that the model binder will not bind these parameters with action method parameters. Now just run the ASP.NET MVC 3 RC 2 application again, you will find that it runs just fine.             In case if you are curious to know that why ASP.NET MVC 3 RC 2 application throws an exception if UrlParameter class contains a ToString method which returns an empty string, then you need to know something about a feature of routing for url generation. During url generation, routing will call the ParsedRoute.Bind method internally. This method includes a logic to match the route and build the url. During building the url, ParsedRoute.Bind method will call the ToString method of the route values(in our case this will call the UrlParameter.ToString method) and then append the returned value into url. This method includes a logic after appending the returned value into url that if two continuous returned values are empty then don't match the current route otherwise an incorrect url will be generated. Here is the snippet from ParsedRoute.Bind method which will prove this statement.       if ((builder2.Length > 0) && (builder2[builder2.Length - 1] == '/')) { return null; } builder2.Append("/"); ........................................................... ........................................................... ........................................................... ........................................................... if (RoutePartsEqual(obj3, obj4)) { builder2.Append(UrlEncode(Convert.ToString(obj3, CultureInfo.InvariantCulture))); continue; }             In the above example, both id1 and id2 parameters default values are set to UrlParameter object and UrlParameter class include a ToString method that returns an empty string. That's why this route will not matched.            Summary:             In this article I showed you the issue regarding routing and also showed you how to workaround this problem. I explained this issue with an example by creating a ASP.NET MVC 2 and a ASP.NET MVC 3 RC 2 application. Finally I also explained the reason for this issue. Hopefully you will enjoy this article too.   SyntaxHighlighter.all()

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  • Access Your favorite RSS Feeds in Windows Media Center

    - by Mysticgeek
    There are a lot of apps out there that help you organize and view your favorite RSS feeds. If you subscribe to a lot, sitting at a computer to view them all can be overwhelming. Today we take a look at accessing them from the couch with WMC. Using Media Center RSS Feeds To get RSS feeds to work with this plugin you need to subscribe to them through Internet Explorer.   The first thing you’ll need to do is activate Media Center RSS Reader (link below) on their site. Next install the Media Center RSS Reader plugin (link below). Installation is easy, just select the defaults when going through the wizard. Now when you open Media Center you’ll see the RSS icon in the main menu under Accessories. You can also find it in the Extras section. Enter in the username and activation code you received when you activated the plugin earlier. After activation you’ll see a list of the RSS feeds you currently subscribed through Internet Explorer. Click on the site feed you want to read and you’ll get a list of the different items available. Next you get and overview of the contents for the item you selected. From there you can show the page of the website containing that item. For any audio or video feeds you subscribe to, at the overview screen, click on Play to watch it. Then just sit back and watch your favorite video RSS feeds on WMC.   Media Center RSS Reader plugin will work with Vista and Windows 7. If you’re looking for a way to check out your RSS feeds in WMC this is a cool plugin for it. Download Media Center RSS Reader –You can activate it here as well. Similar Articles Productive Geek Tips Using Netflix Watchnow in Windows Vista Media Center (Gmedia)Integrate Boxee with Media Center in Windows 7Integrate Hulu Desktop and Windows Media Center in Windows 7Add Color Coding to Windows 7 Media Center Program GuideSchedule Updates for Windows Media Center TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional 15 Great Illustrations by Chow Hon Lam Easily Sync Files & Folders with Friends & Family Amazon Free Kindle for PC Download Stretch popurls.com with a Stylish Script (Firefox) OldTvShows.org – Find episodes of Hitchcock, Soaps, Game Shows and more Download Microsoft Office Help tab

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  • OWB 11gR2 &ndash; Flexible and extensible

    - by David Allan
    The Oracle data integration extensibility capabilities are something I love, nothing more frustrating than a tool or platform that is very constraining. I think extensibility and flexibility are invaluable capabilities in the data integration arena. I liked Uli Bethke's posting on some extensibility capabilities with ODI (see Nesting ODI Substitution Method Calls here), he has some useful guidance on making customizations to existing KMs, nice to learn by example. I thought I'd illustrate the same capabilities with ODI's partner OWB for the OWB community. There is a whole new world of potential. The LKM/IKM/CKM/JKMs are the primary templates that are supported (plus the Oracle Target code template), so there is a lot of potential for customizing and extending the product in this release. Enough waffle... Diving in at the deep end from Uli's post, in OWB the table operator has a number of additional properties in OWB 11gR2 that let you annotate the column usage with ODI-like properties such as the slowly changing usage or for your own user-defined purpose as in Uli's post, below you see for the target table SALES_TARGET we can use the UD5 property which when assigned the code template (knowledge module) which has been modified with Uli's change we can do custom things such as creating indices - provides The code template used by the mapping has the additional step which is basically the code illustrated from Uli's posting just used directly, the ODI 10g substitution references also supported from within OWB's runtime. Now to see whether this does what we expect before we execute it, we can check out the generated code similar to how the traditional mapping generation and preview works, you do this by clicking on the 'Inspect Code' button on the execution units code template assignment. This then  creates another tab with prefix 'Code - <mapping name>' where the generated code is put, scrolling down we find the last step with the indices being created, looks good, so we are ready to deploy and execute. After executing the mapping we can then use the 'Audit Information' panel (select the mapping in the designer tree and click on View/Audit Information), this gives us a view of the execution where we can drill into the tasks that were executed and inspect both the template and the generated code that was executed and any potential errors. Reflecting back on earlier versions of OWB, these were the kinds of features that were always highly desirable, getting under the hood of the code generation and tweaking bit and pieces - fun and powerful stuff! We can step it up a bit here and explore some further ideas. The example below is a daisy-chained set of execution units where the intermediate table is a target of one unit and the source for another. We want that table to be a global temporary table, so can tweak the templates. Back to the copy of SQL Control Append (for demo purposes) we modify the create target table step to make the table a global temporary table, with the option of on commit preserve rows. You can get a feel for some of the customizations and changes possible, providing some great flexibility and extensibility for the data integration tools.

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  • Throne of Games

    - by Asian Angel
    All hail the King of Games! Note: You can view the full-size version by visiting the deviantART link below and clicking on the display image. Throne of Games [via Neatorama] What Is the Purpose of the “Do Not Cover This Hole” Hole on Hard Drives? How To Log Into The Desktop, Add a Start Menu, and Disable Hot Corners in Windows 8 HTG Explains: Why You Shouldn’t Use a Task Killer On Android

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  • Traditional ASP.Net WebForms vs ASP.Net MVC

    - by Pankaj Upadhyay
    ASP.Net MVC has been around for some time now. The latest one, i.e MVC3 comes with Razor View Engine. My question: How long is traditional ASP.Net here to stay. Does Microsoft have any plans to eliminate it in aid of ASP.Net MVC in the future and will the next release of VS incorporate it? Also, I would like to know if there is any merit of traditional over ASP.Net MVC, other than the controls-aid?

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  • Restore Files from Backups on Windows Home Server

    - by Mysticgeek
    If you use Windows Home Server to backup the machines on your network, your in luck if you accidentally delete important files or they become corrupted. Today we take a look at getting your data back from backups on your home server. Open Windows Home Server Console and click select the Computers and Backup tab. Right-click on the computer you need to restore files for and select View Backups. This will open a list of your recent backups. Highlight the one you want to open, then click the Open button in the Restore or View Files section. If this is the first time you’re restoring a file, you’ll be asked to verify installation of the device software. Check the box next to Always trust software from Microsoft Corporation and click Install. Now wait while the backup data is retrieved. After the backup data has been retrieved, an explorer windows opens up to drive (Z:) which is the backup data. It’s just like if you were opening a drive on your local machine. Now you can browse through the backup and find the files your missing. You can open the files directly, or drag them onto your machine to the location you want to restore them.   Restoring your data is actually a very easy process with Windows Home Server. Of course you’ll want to make sure the computers on your network are being backed up to WHS. if you need help with that, check out our article on how to configure your computer to backup to WHS. If you want to backup your home server shares, check out our article on how to backup WHS folder to an external drive. Similar Articles Productive Geek Tips GMedia Blog: Setting Up a Windows Home ServerRestore Your PC from Windows Home ServerCreate A Windows Home Server Home Computer Restore DiscInstalling Windows Home ServerConfigure Your Computer to Backup to Windows Home Server TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional Make your Joomla & Drupal Sites Mobile with OSMOBI Integrate Twitter and Delicious and Make Life Easier Design Your Web Pages Using the Golden Ratio Worldwide Growth of the Internet How to Find Your Mac Address Use My TextTools to Edit and Organize Text

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  • Tech Germs – Tis the Season [Infographic]

    - by Asian Angel
    Think the tech and household items you work with or use on a daily basis are clean? Then think again. View a Larger Version of the Infographic Tech Germs [infographic] – Blog Post [via Elinor Mills] How to See What Web Sites Your Computer is Secretly Connecting To HTG Explains: When Do You Need to Update Your Drivers? How to Make the Kindle Fire Silk Browser *Actually* Fast!

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