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• Using Unity – Part 3

  - by nmarun

  The previous blog was about registering and invoking different types dynamically. In this one I’d like to show how Unity manages/disposes the instances – say hello to Lifetime Managers. When a type gets registered, either through the config file or when RegisterType method is explicitly called, the default behavior is that the container uses a transient lifetime manager. In other words, the unity container creates a new instance of the type when Resolve or ResolveAll method is called. Whereas, when you register an existing object using the RegisterInstance method, the container uses a container controlled lifetime manager - a singleton pattern. It does this by storing the reference of the object and that means so as long as the container is ‘alive’, your registered instance does not go out of scope and will be disposed only after the container either goes out of scope or when the code explicitly disposes the container. Let’s see how we can use these and test if something is a singleton or a transient instance. Continuing on the same solution used in the previous blogs, I have made the following changes: First is to add typeAlias elements for TransientLifetimeManager type: 1: <typeAlias alias="transient" type="Microsoft.Practices.Unity.TransientLifetimeManager, Microsoft.Practices.Unity"/> You then need to tell what type(s) you want to be transient by nature: 1: <type type="IProduct" mapTo="Product2"> 2: <lifetime type="transient" /> 3: </type> 4: <!--<type type="IProduct" mapTo="Product2" />--> The lifetime element’s type attribute matches with the alias attribute of the typeAlias element. Now since ‘transient’ is the default behavior, you can have a concise version of the same as line 4 shows. Also note that I’ve changed the mapTo attribute from ‘Product’ to ‘Product2’. I’ve done this to help understand the transient nature of the instance of the type Product2. By making this change, you are basically saying when a type of IProduct needs to be resolved, Unity should create an instance of Product2 by default. 1: public string WriteProductDetails() 2: { 3: return string.Format("Name: {0}<br/>Category: {1}<br/>Mfg Date: {2}<br/>Hash Code: {3}", 4: Name, Category, MfgDate.ToString("MM/dd/yyyy hh:mm:ss tt"), GetHashCode()); 5: } Again, the above change is purely for the purpose of making the example more clear to understand. The display will show the full date and also displays the hash code of the current instance. The GetHashCode() method returns an integer when an instance gets created – a new integer for every instance. When you run the application, you’ll see something like the below: Now when you click on the ‘Get Product2 Instance’ button, you’ll see that the Mfg Date (which is set in the constructor) and the Hash Code are different from the one created on page load. This proves to us that a new instance is created every single time. To make this a singleton, we need to add a type alias for the ContainerControlledLifetimeManager class and then change the type attribute of the lifetime element to singleton. 1: <typeAlias alias="singleton" type="Microsoft.Practices.Unity.ContainerControlledLifetimeManager, Microsoft.Practices.Unity"/> 2: ... 3: <type type="IProduct" mapTo="Product2"> 4: <lifetime type="singleton" /> 5: </type> Running the application now gets me the following output: Click on the button below and you’ll see that the Mfg Date and the Hash code remain unchanged => the unity container is storing the reference the first time it is created and then returns the same instance every time the type needs to be resolved. Digging more deeper into this, Unity provides more than the two lifetime managers. ExternallyControlledLifetimeManager – maintains a weak reference to type mappings and instances. Unity returns the same instance as long as the some code is holding a strong reference to this instance. For this, you need: 1: <typeAlias alias="external" type="Microsoft.Practices.Unity.ExternallyControlledLifetimeManager, Microsoft.Practices.Unity"/> 2: ... 3: <type type="IProduct" mapTo="Product2"> 4: <lifetime type="external" /> 5: </type> PerThreadLifetimeManager – Unity returns a unique instance of an object for each thread – so this effectively is a singleton behavior on a  per-thread basis. 1: <typeAlias alias="perThread" type="Microsoft.Practices.Unity.PerThreadLifetimeManager, Microsoft.Practices.Unity"/> 2: ... 3: <type type="IProduct" mapTo="Product2"> 4: <lifetime type="perThread" /> 5: </type> One thing to note about this is that if you use RegisterInstance method to register an existing object, this instance will be returned for every thread, making this a purely singleton behavior. Needless to say, this type of lifetime management is useful in multi-threaded applications (duh!!). I hope this blog provided some basics on lifetime management of objects resolved in Unity and in the next blog, I’ll talk about Injection. Please see the code used here.

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• Parallelism in .NET – Part 7, Some Differences between PLINQ and LINQ to Objects

  - by Reed

  In my previous post on Declarative Data Parallelism, I mentioned that PLINQ extends LINQ to Objects to support parallel operations.  Although nearly all of the same operations are supported, there are some differences between PLINQ and LINQ to Objects.  By introducing Parallelism to our declarative model, we add some extra complexity.  This, in turn, adds some extra requirements that must be addressed. In order to illustrate the main differences, and why they exist, let’s begin by discussing some differences in how the two technologies operate, and look at the underlying types involved in LINQ to Objects and PLINQ . LINQ to Objects is mainly built upon a single class: Enumerable.  The Enumerable class is a static class that defines a large set of extension methods, nearly all of which work upon an IEnumerable<T>.  Many of these methods return a new IEnumerable<T>, allowing the methods to be chained together into a fluent style interface.  This is what allows us to write statements that chain together, and lead to the nice declarative programming model of LINQ: double min = collection .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Other LINQ variants work in a similar fashion.  For example, most data-oriented LINQ providers are built upon an implementation of IQueryable<T>, which allows the database provider to turn a LINQ statement into an underlying SQL query, to be performed directly on the remote database. PLINQ is similar, but instead of being built upon the Enumerable class, most of PLINQ is built upon a new static class: ParallelEnumerable.  When using PLINQ, you typically begin with any collection which implements IEnumerable<T>, and convert it to a new type using an extension method defined on ParallelEnumerable: AsParallel().  This method takes any IEnumerable<T>, and converts it into a ParallelQuery<T>, the core class for PLINQ.  There is a similar ParallelQuery class for working with non-generic IEnumerable implementations. This brings us to our first subtle, but important difference between PLINQ and LINQ – PLINQ always works upon specific types, which must be explicitly created. Typically, the type you’ll use with PLINQ is ParallelQuery<T>, but it can sometimes be a ParallelQuery or an OrderedParallelQuery<T>.  Instead of dealing with an interface, implemented by an unknown class, we’re dealing with a specific class type.  This works seamlessly from a usage standpoint – ParallelQuery<T> implements IEnumerable<T>, so you can always “switch back” to an IEnumerable<T>.  The difference only arises at the beginning of our parallelization.  When we’re using LINQ, and we want to process a normal collection via PLINQ, we need to explicitly convert the collection into a ParallelQuery<T> by calling AsParallel().  There is an important consideration here – AsParallel() does not need to be called on your specific collection, but rather any IEnumerable<T>.  This allows you to place it anywhere in the chain of methods involved in a LINQ statement, not just at the beginning.  This can be useful if you have an operation which will not parallelize well or is not thread safe.  For example, the following is perfectly valid, and similar to our previous examples: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); However, if SomeOperation() is not thread safe, we could just as easily do: double min = collection .Select(item => item.SomeOperation()) .AsParallel() .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); In this case, we’re using standard LINQ to Objects for the Select(…) method, then converting the results of that map routine to a ParallelQuery<T>, and processing our filter (the Where method) and our aggregation (the Min method) in parallel. PLINQ also provides us with a way to convert a ParallelQuery<T> back into a standard IEnumerable<T>, forcing sequential processing via standard LINQ to Objects.  If SomeOperation() was thread-safe, but PerformComputation() was not thread-safe, we would need to handle this by using the AsEnumerable() method: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .AsEnumerable() .Min(item => item.PerformComputation()); Here, we’re converting our collection into a ParallelQuery<T>, doing our map operation (the Select(…) method) and our filtering in parallel, then converting the collection back into a standard IEnumerable<T>, which causes our aggregation via Min() to be performed sequentially. This could also be written as two statements, as well, which would allow us to use the language integrated syntax for the first portion: var tempCollection = from item in collection.AsParallel() let e = item.SomeOperation() where (e.SomeProperty > 6 && e.SomeProperty < 24) select e; double min = tempCollection.AsEnumerable().Min(item => item.PerformComputation()); This allows us to use the standard LINQ style language integrated query syntax, but control whether it’s performed in parallel or serial by adding AsParallel() and AsEnumerable() appropriately. The second important difference between PLINQ and LINQ deals with order preservation.  PLINQ, by default, does not preserve the order of of source collection. This is by design.  In order to process a collection in parallel, the system needs to naturally deal with multiple elements at the same time.  Maintaining the original ordering of the sequence adds overhead, which is, in many cases, unnecessary.  Therefore, by default, the system is allowed to completely change the order of your sequence during processing.  If you are doing a standard query operation, this is usually not an issue.  However, there are times when keeping a specific ordering in place is important.  If this is required, you can explicitly request the ordering be preserved throughout all operations done on a ParallelQuery<T> by using the AsOrdered() extension method.  This will cause our sequence ordering to be preserved. For example, suppose we wanted to take a collection, perform an expensive operation which converts it to a new type, and display the first 100 elements.  In LINQ to Objects, our code might look something like: // Using IEnumerable<SourceClass> collection IEnumerable<ResultClass> results = collection .Select(e => e.CreateResult()) .Take(100); If we just converted this to a parallel query naively, like so: IEnumerable<ResultClass> results = collection .AsParallel() .Select(e => e.CreateResult()) .Take(100); We could very easily get a very different, and non-reproducable, set of results, since the ordering of elements in the input collection is not preserved.  To get the same results as our original query, we need to use: IEnumerable<ResultClass> results = collection .AsParallel() .AsOrdered() .Select(e => e.CreateResult()) .Take(100); This requests that PLINQ process our sequence in a way that verifies that our resulting collection is ordered as if it were processed serially.  This will cause our query to run slower, since there is overhead involved in maintaining the ordering.  However, in this case, it is required, since the ordering is required for correctness. PLINQ is incredibly useful.  It allows us to easily take nearly any LINQ to Objects query and run it in parallel, using the same methods and syntax we’ve used previously.  There are some important differences in operation that must be considered, however – it is not a free pass to parallelize everything.  When using PLINQ in order to parallelize your routines declaratively, the same guideline I mentioned before still applies: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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• Issue Creating SQL Login for AppPoolIdentity on Windows Server 2008

  - by Ben Griswold

  IIS7 introduced the option to run your application pool as AppPoolIdentity. With the release of IIS7.5, AppPoolIdentity was promoted to the default option.  You see this change if you’re running Windows 7 or Windows Server 2008 R2.  On my Windows 7 machine, I’m able to define my Application Pool Identity and then create an associated database login via the SQL Server Management Studio interface.  No problem.  However, I ran into some troubles when recently installing my web application onto a Windows Server 2008 R2 64-bit machine.  Strange, but the same approach failed as SSMS couldn’t find the AppPoolIdentity user.  Instead of using the tools, I created and executed the login via script and it worked fine.  Here’s the script, based off of the DefaultAppPool identity, if the same happens to you: CREATE LOGIN [IIS APPPOOL\DefaultAppPool] FROM WINDOWS WITH DEFAULT_DATABASE=[master] USE [Chinook] CREATE USER [IIS APPPOOL\DefaultAppPool] FOR LOGIN [IIS APPPOOL\DefaultAppPool]

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• Parallelism in .NET – Part 2, Simple Imperative Data Parallelism

  - by Reed

  In my discussion of Decomposition of the problem space, I mentioned that Data Decomposition is often the simplest abstraction to use when trying to parallelize a routine.  If a problem can be decomposed based off the data, we will often want to use what MSDN refers to as Data Parallelism as our strategy for implementing our routine.  The Task Parallel Library in .NET 4 makes implementing Data Parallelism, for most cases, very simple. Data Parallelism is the main technique we use to parallelize a routine which can be decomposed based off data.  Data Parallelism refers to taking a single collection of data, and having a single operation be performed concurrently on elements in the collection.  One side note here: Data Parallelism is also sometimes referred to as the Loop Parallelism Pattern or Loop-level Parallelism.  In general, for this series, I will try to use the terminology used in the MSDN Documentation for the Task Parallel Library.  This should make it easier to investigate these topics in more detail. Once we’ve determined we have a problem that, potentially, can be decomposed based on data, implementation using Data Parallelism in the TPL is quite simple.  Let’s take our example from the Data Decomposition discussion – a simple contrast stretching filter.  Here, we have a collection of data (pixels), and we need to run a simple operation on each element of the pixel.  Once we know the minimum and maximum values, we most likely would have some simple code like the following: for (int row=0; row < pixelData.GetUpperBound(0); ++row) { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This simple routine loops through a two dimensional array of pixelData, and calls the AdjustContrast routine on each pixel. As I mentioned, when you’re decomposing a problem space, most iteration statements are potentially candidates for data decomposition.  Here, we’re using two for loops – one looping through rows in the image, and a second nested loop iterating through the columns.  We then perform one, independent operation on each element based on those loop positions. This is a prime candidate – we have no shared data, no dependencies on anything but the pixel which we want to change.  Since we’re using a for loop, we can easily parallelize this using the Parallel.For method in the TPL: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Here, by simply changing our first for loop to a call to Parallel.For, we can parallelize this portion of our routine.  Parallel.For works, as do many methods in the TPL, by creating a delegate and using it as an argument to a method.  In this case, our for loop iteration block becomes a delegate creating via a lambda expression.  This lets you write code that, superficially, looks similar to the familiar for loop, but functions quite differently at runtime. We could easily do this to our second for loop as well, but that may not be a good idea.  There is a balance to be struck when writing parallel code.  We want to have enough work items to keep all of our processors busy, but the more we partition our data, the more overhead we introduce.  In this case, we have an image of data – most likely hundreds of pixels in both dimensions.  By just parallelizing our first loop, each row of pixels can be run as a single task.  With hundreds of rows of data, we are providing fine enough granularity to keep all of our processors busy. If we parallelize both loops, we’re potentially creating millions of independent tasks.  This introduces extra overhead with no extra gain, and will actually reduce our overall performance.  This leads to my first guideline when writing parallel code: Partition your problem into enough tasks to keep each processor busy throughout the operation, but not more than necessary to keep each processor busy. Also note that I parallelized the outer loop.  I could have just as easily partitioned the inner loop.  However, partitioning the inner loop would have led to many more discrete work items, each with a smaller amount of work (operate on one pixel instead of one row of pixels).  My second guideline when writing parallel code reflects this: Partition your problem in a way to place the most work possible into each task. This typically means, in practice, that you will want to parallelize the routine at the “highest” point possible in the routine, typically the outermost loop.  If you’re looking at parallelizing methods which call other methods, you’ll want to try to partition your work high up in the stack – as you get into lower level methods, the performance impact of parallelizing your routines may not overcome the overhead introduced. Parallel.For works great for situations where we know the number of elements we’re going to process in advance.  If we’re iterating through an IList<T> or an array, this is a typical approach.  However, there are other iteration statements common in C#.  In many situations, we’ll use foreach instead of a for loop.  This can be more understandable and easier to read, but also has the advantage of working with collections which only implement IEnumerable<T>, where we do not know the number of elements involved in advance. As an example, lets take the following situation.  Say we have a collection of Customers, and we want to iterate through each customer, check some information about the customer, and if a certain case is met, send an email to the customer and update our instance to reflect this change.  Normally, this might look something like: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } } Here, we’re doing a fair amount of work for each customer in our collection, but we don’t know how many customers exist.  If we assume that theStore.GetLastContact(customer) and theStore.EmailCustomer(customer) are both side-effect free, thread safe operations, we could parallelize this using Parallel.ForEach: Parallel.ForEach(customers, customer => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } }); Just like Parallel.For, we rework our loop into a method call accepting a delegate created via a lambda expression.  This keeps our new code very similar to our original iteration statement, however, this will now execute in parallel.  The same guidelines apply with Parallel.ForEach as with Parallel.For. The other iteration statements, do and while, do not have direct equivalents in the Task Parallel Library.  These, however, are very easy to implement using Parallel.ForEach and the yield keyword. Most applications can benefit from implementing some form of Data Parallelism.  Iterating through collections and performing “work” is a very common pattern in nearly every application.  When the problem can be decomposed by data, we often can parallelize the workload by merely changing foreach statements to Parallel.ForEach method calls, and for loops to Parallel.For method calls.  Any time your program operates on a collection, and does a set of work on each item in the collection where that work is not dependent on other information, you very likely have an opportunity to parallelize your routine.

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• Node.js Adventure - When Node Flying in Wind

  - by Shaun

  In the first post of this series I mentioned some popular modules in the community, such as underscore, async, etc.. I also listed a module named “Wind (zh-CN)”, which is created by one of my friend, Jeff Zhao (zh-CN). Now I would like to use a separated post to introduce this module since I feel it brings a new async programming style in not only Node.js but JavaScript world. If you know or heard about the new feature in C# 5.0 called “async and await”, or you learnt F#, you will find the “Wind” brings the similar async programming experience in JavaScript. By using “Wind”, we can write async code that looks like the sync code. The callbacks, async stats and exceptions will be handled by “Wind” automatically and transparently.   What’s the Problem: Dense “Callback” Phobia Let’s firstly back to my second post in this series. As I mentioned in that post, when we wanted to read some records from SQL Server we need to open the database connection, and then execute the query. In Node.js all IO operation are designed as async callback pattern which means when the operation was done, it will invoke a function which was taken from the last parameter. For example the database connection opening code would be like this. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: } 8: }); And then if we need to query the database the code would be like this. It nested in the previous function. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: conn.queryRaw(command, function(error, results) { 8: if(error) { 9: // failed to execute this command 10: } 11: else { 12: // records retrieved successfully 13: } 14: }; 15: } 16: }); Assuming if we need to copy some data from this database to another then we need to open another connection and execute the command within the function under the query function. 1: sql.open(connectionString, function(error, conn) { 2: if(error) { 3: // some error handling code 4: } 5: else { 6: // connection opened successfully 7: conn.queryRaw(command, function(error, results) { 8: if(error) { 9: // failed to execute this command 10: } 11: else { 12: // records retrieved successfully 13: target.open(targetConnectionString, function(error, t_conn) { 14: if(error) { 15: // connect failed 16: } 17: else { 18: t_conn.queryRaw(copy_command, function(error, results) { 19: if(error) { 20: // copy failed 21: } 22: else { 23: // and then, what do you want to do now... 24: } 25: }; 26: } 27: }; 28: } 29: }; 30: } 31: }); This is just an example. In the real project the logic would be more complicated. This means our application might be messed up and the business process will be fragged by many callback functions. I would like call this “Dense Callback Phobia”. This might be a challenge how to make code straightforward and easy to read, something like below. 1: try 2: { 3: // open source connection 4: var s_conn = sqlConnect(s_connectionString); 5: // retrieve data 6: var results = sqlExecuteCommand(s_conn, s_command); 7: 8: // open target connection 9: var t_conn = sqlConnect(t_connectionString); 10: // prepare the copy command 11: var t_command = getCopyCommand(results); 12: // execute the copy command 13: sqlExecuteCommand(s_conn, t_command); 14: } 15: catch (ex) 16: { 17: // error handling 18: }   What’s the Problem: Sync-styled Async Programming Similar as the previous problem, the callback-styled async programming model makes the upcoming operation as a part of the current operation, and mixed with the error handling code. So it’s very hard to understand what on earth this code will do. And since Node.js utilizes non-blocking IO mode, we cannot invoke those operations one by one, as they will be executed concurrently. For example, in this post when I tried to copy the records from Windows Azure SQL Database (a.k.a. WASD) to Windows Azure Table Storage, if I just insert the data into table storage one by one and then print the “Finished” message, I will see the message shown before the data had been copied. This is because all operations were executed at the same time. In order to make the copy operation and print operation executed synchronously I introduced a module named “async” and the code was changed as below. 1: async.forEach(results.rows, 2: function (row, callback) { 3: var resource = { 4: "PartitionKey": row[1], 5: "RowKey": row[0], 6: "Value": row[2] 7: }; 8: client.insertEntity(tableName, resource, function (error) { 9: if (error) { 10: callback(error); 11: } 12: else { 13: console.log("entity inserted."); 14: callback(null); 15: } 16: }); 17: }, 18: function (error) { 19: if (error) { 20: error["target"] = "insertEntity"; 21: res.send(500, error); 22: } 23: else { 24: console.log("all done."); 25: res.send(200, "Done!"); 26: } 27: }); It ensured that the “Finished” message will be printed when all table entities had been inserted. But it cannot promise that the records will be inserted in sequence. It might be another challenge to make the code looks like in sync-style? 1: try 2: { 3: forEach(row in rows) { 4: var entity = { /* ... */ }; 5: tableClient.insert(tableName, entity); 6: } 7:  8: console.log("Finished"); 9: } 10: catch (ex) { 11: console.log(ex); 12: }   How “Wind” Helps “Wind” is a JavaScript library which provides the control flow with plain JavaScript for asynchronous programming (and more) without additional pre-compiling steps. It’s available in NPM so that we can install it through “npm install wind”. Now let’s create a very simple Node.js application as the example. This application will take some website URLs from the command arguments and tried to retrieve the body length and print them in console. Then at the end print “Finish”. I’m going to use “request” module to make the HTTP call simple so I also need to install by the command “npm install request”. The code would be like this. 1: var request = require("request"); 2:  3: // get the urls from arguments, the first two arguments are `node.exe` and `fetch.js` 4: var args = process.argv.splice(2); 5:  6: // main function 7: var main = function() { 8: for(var i = 0; i < args.length; i++) { 9: // get the url 10: var url = args[i]; 11: // send the http request and try to get the response and body 12: request(url, function(error, response, body) { 13: if(!error && response.statusCode == 200) { 14: // log the url and the body length 15: console.log( 16: "%s: %d.", 17: response.request.uri.href, 18: body.length); 19: } 20: else { 21: // log error 22: console.log(error); 23: } 24: }); 25: } 26: 27: // finished 28: console.log("Finished"); 29: }; 30:  31: // execute the main function 32: main(); Let’s execute this application. (I made them in multi-lines for better reading.) 1: node fetch.js 2: "http://www.igt.com/us-en.aspx" 3: "http://www.igt.com/us-en/games.aspx" 4: "http://www.igt.com/us-en/cabinets.aspx" 5: "http://www.igt.com/us-en/systems.aspx" 6: "http://www.igt.com/us-en/interactive.aspx" 7: "http://www.igt.com/us-en/social-gaming.aspx" 8: "http://www.igt.com/support.aspx" Below is the output. As you can see the finish message was printed at the beginning, and the pages’ length retrieved in a different order than we specified. This is because in this code the request command, console logging command are executed asynchronously and concurrently. Now let’s introduce “Wind” to make them executed in order, which means it will request the websites one by one, and print the message at the end.   First of all we need to import the “Wind” package and make sure the there’s only one global variant named “Wind”, and ensure it’s “Wind” instead of “wind”. 1: var Wind = require("wind");   Next, we need to tell “Wind” which code will be executed asynchronously so that “Wind” can control the execution process. In this case the “request” operation executed asynchronously so we will create a “Task” by using a build-in helps function in “Wind” named Wind.Async.Task.create. 1: var requestBodyLengthAsync = function(url) { 2: return Wind.Async.Task.create(function(t) { 3: request(url, function(error, response, body) { 4: if(error || response.statusCode != 200) { 5: t.complete("failure", error); 6: } 7: else { 8: var data = 9: { 10: uri: response.request.uri.href, 11: length: body.length 12: }; 13: t.complete("success", data); 14: } 15: }); 16: }); 17: }; The code above created a “Task” from the original request calling code. In “Wind” a “Task” means an operation will be finished in some time in the future. A “Task” can be started by invoke its start() method, but no one knows when it actually will be finished. The Wind.Async.Task.create helped us to create a task. The only parameter is a function where we can put the actual operation in, and then notify the task object it’s finished successfully or failed by using the complete() method. In the code above I invoked the request method. If it retrieved the response successfully I set the status of this task as “success” with the URL and body length. If it failed I set this task as “failure” and pass the error out.   Next, we will change the main() function. In “Wind” if we want a function can be controlled by Wind we need to mark it as “async”. This should be done by using the code below. 1: var main = eval(Wind.compile("async", function() { 2: })); When the application is running, Wind will detect “eval(Wind.compile(“async”, function” and generate an anonymous code from the body of this original function. Then the application will run the anonymous code instead of the original one. In our example the main function will be like this. 1: var main = eval(Wind.compile("async", function() { 2: for(var i = 0; i < args.length; i++) { 3: try 4: { 5: var result = $await(requestBodyLengthAsync(args[i])); 6: console.log( 7: "%s: %d.", 8: result.uri, 9: result.length); 10: } 11: catch (ex) { 12: console.log(ex); 13: } 14: } 15: 16: console.log("Finished"); 17: })); As you can see, when I tried to request the URL I use a new command named “$await”. It tells Wind, the operation next to $await will be executed asynchronously, and the main thread should be paused until it finished (or failed). So in this case, my application will be pause when the first response was received, and then print its body length, then try the next one. At the end, print the finish message.   Finally, execute the main function. The full code would be like this. 1: var request = require("request"); 2: var Wind = require("wind"); 3:  4: var args = process.argv.splice(2); 5:  6: var requestBodyLengthAsync = function(url) { 7: return Wind.Async.Task.create(function(t) { 8: request(url, function(error, response, body) { 9: if(error || response.statusCode != 200) { 10: t.complete("failure", error); 11: } 12: else { 13: var data = 14: { 15: uri: response.request.uri.href, 16: length: body.length 17: }; 18: t.complete("success", data); 19: } 20: }); 21: }); 22: }; 23:  24: var main = eval(Wind.compile("async", function() { 25: for(var i = 0; i < args.length; i++) { 26: try 27: { 28: var result = $await(requestBodyLengthAsync(args[i])); 29: console.log( 30: "%s: %d.", 31: result.uri, 32: result.length); 33: } 34: catch (ex) { 35: console.log(ex); 36: } 37: } 38: 39: console.log("Finished"); 40: })); 41:  42: main().start();   Run our new application. At the beginning we will see the compiled and generated code by Wind. Then we can see the pages were requested one by one, and at the end the finish message was printed. Below is the code Wind generated for us. As you can see the original code, the output code were shown. 1: // Original: 2: function () { 3: for(var i = 0; i < args.length; i++) { 4: try 5: { 6: var result = $await(requestBodyLengthAsync(args[i])); 7: console.log( 8: "%s: %d.", 9: result.uri, 10: result.length); 11: } 12: catch (ex) { 13: console.log(ex); 14: } 15: } 16: 17: console.log("Finished"); 18: } 19:  20: // Compiled: 21: /* async << function () { */ (function () { 22: var _builder_$0 = Wind.builders["async"]; 23: return _builder_$0.Start(this, 24: _builder_$0.Combine( 25: _builder_$0.Delay(function () { 26: /* var i = 0; */ var i = 0; 27: /* for ( */ return _builder_$0.For(function () { 28: /* ; i < args.length */ return i < args.length; 29: }, function () { 30: /* ; i ++) { */ i ++; 31: }, 32: /* try { */ _builder_$0.Try( 33: _builder_$0.Delay(function () { 34: /* var result = $await(requestBodyLengthAsync(args[i])); */ return _builder_$0.Bind(requestBodyLengthAsync(args[i]), function (result) { 35: /* console.log("%s: %d.", result.uri, result.length); */ console.log("%s: %d.", result.uri, result.length); 36: return _builder_$0.Normal(); 37: }); 38: }), 39: /* } catch (ex) { */ function (ex) { 40: /* console.log(ex); */ console.log(ex); 41: return _builder_$0.Normal(); 42: /* } */ }, 43: null 44: ) 45: /* } */ ); 46: }), 47: _builder_$0.Delay(function () { 48: /* console.log("Finished"); */ console.log("Finished"); 49: return _builder_$0.Normal(); 50: }) 51: ) 52: ); 53: /* } */ })   How Wind Works Someone may raise a big concern when you find I utilized “eval” in my code. Someone may assume that Wind utilizes “eval” to execute some code dynamically while “eval” is very low performance. But I would say, Wind does NOT use “eval” to run the code. It only use “eval” as a flag to know which code should be compiled at runtime. When the code was firstly been executed, Wind will check and find “eval(Wind.compile(“async”, function”. So that it knows this function should be compiled. Then it utilized parse-js to analyze the inner JavaScript and generated the anonymous code in memory. Then it rewrite the original code so that when the application was running it will use the anonymous one instead of the original one. Since the code generation was done at the beginning of the application was started, in the future no matter how long our application runs and how many times the async function was invoked, it will use the generated code, no need to generate again. So there’s no significant performance hurt when using Wind.   Wind in My Previous Demo Let’s adopt Wind into one of my previous demonstration and to see how it helps us to make our code simple, straightforward and easy to read and understand. In this post when I implemented the functionality that copied the records from my WASD to table storage, the logic would be like this. 1, Open database connection. 2, Execute a query to select all records from the table. 3, Recreate the table in Windows Azure table storage. 4, Create entities from each of the records retrieved previously, and then insert them into table storage. 5, Finally, show message as the HTTP response. But as the image below, since there are so many callbacks and async operations, it’s very hard to understand my logic from the code. Now let’s use Wind to rewrite our code. First of all, of course, we need the Wind package. Then we need to include the package files into project and mark them as “Copy always”. Add the Wind package into the source code. Pay attention to the variant name, you must use “Wind” instead of “wind”. 1: var express = require("express"); 2: var async = require("async"); 3: var sql = require("node-sqlserver"); 4: var azure = require("azure"); 5: var Wind = require("wind"); Now we need to create some async functions by using Wind. All async functions should be wrapped so that it can be controlled by Wind which are open database, retrieve records, recreate table (delete and create) and insert entity in table. Below are these new functions. All of them are created by using Wind.Async.Task.create. 1: sql.openAsync = function (connectionString) { 2: return Wind.Async.Task.create(function (t) { 3: sql.open(connectionString, function (error, conn) { 4: if (error) { 5: t.complete("failure", error); 6: } 7: else { 8: t.complete("success", conn); 9: } 10: }); 11: }); 12: }; 13:  14: sql.queryAsync = function (conn, query) { 15: return Wind.Async.Task.create(function (t) { 16: conn.queryRaw(query, function (error, results) { 17: if (error) { 18: t.complete("failure", error); 19: } 20: else { 21: t.complete("success", results); 22: } 23: }); 24: }); 25: }; 26:  27: azure.recreateTableAsync = function (tableName) { 28: return Wind.Async.Task.create(function (t) { 29: client.deleteTable(tableName, function (error, successful, response) { 30: console.log("delete table finished"); 31: client.createTableIfNotExists(tableName, function (error, successful, response) { 32: console.log("create table finished"); 33: if (error) { 34: t.complete("failure", error); 35: } 36: else { 37: t.complete("success", null); 38: } 39: }); 40: }); 41: }); 42: }; 43:  44: azure.insertEntityAsync = function (tableName, entity) { 45: return Wind.Async.Task.create(function (t) { 46: client.insertEntity(tableName, entity, function (error, entity, response) { 47: if (error) { 48: t.complete("failure", error); 49: } 50: else { 51: t.complete("success", null); 52: } 53: }); 54: }); 55: }; Then in order to use these functions we will create a new function which contains all steps for data copying. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: } 4: catch (ex) { 5: console.log(ex); 6: res.send(500, "Internal error."); 7: } 8: })); Let’s execute steps one by one with the “$await” keyword introduced by Wind so that it will be invoked in sequence. First is to open the database connection. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: } 7: catch (ex) { 8: console.log(ex); 9: res.send(500, "Internal error."); 10: } 11: })); Then retrieve all records from the database connection. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: } 10: catch (ex) { 11: console.log(ex); 12: res.send(500, "Internal error."); 13: } 14: })); After recreated the table, we need to create the entities and insert them into table storage. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage one by one 14: for (var i = 0; i < results.rows.length; i++) { 15: var entity = { 16: "PartitionKey": results.rows[i][1], 17: "RowKey": results.rows[i][0], 18: "Value": results.rows[i][2] 19: }; 20: $await(azure.insertEntityAsync(tableName, entity)); 21: console.log("entity inserted"); 22: } 23: } 24: } 25: catch (ex) { 26: console.log(ex); 27: res.send(500, "Internal error."); 28: } 29: })); Finally, send response back to the browser. 1: var copyRecords = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage one by one 14: for (var i = 0; i < results.rows.length; i++) { 15: var entity = { 16: "PartitionKey": results.rows[i][1], 17: "RowKey": results.rows[i][0], 18: "Value": results.rows[i][2] 19: }; 20: $await(azure.insertEntityAsync(tableName, entity)); 21: console.log("entity inserted"); 22: } 23: // send response 24: console.log("all done"); 25: res.send(200, "All done!"); 26: } 27: } 28: catch (ex) { 29: console.log(ex); 30: res.send(500, "Internal error."); 31: } 32: })); If we compared with the previous code we will find now it became more readable and much easy to understand. It’s very easy to know what this function does even though without any comments. When user go to URL “/was/copyRecords” we will execute the function above. The code would be like this. 1: app.get("/was/copyRecords", function (req, res) { 2: copyRecords(req, res).start(); 3: }); And below is the logs printed in local compute emulator console. As we can see the functions executed one by one and then finally the response back to me browser.   Scaffold Functions in Wind Wind provides not only the async flow control and compile functions, but many scaffold methods as well. We can build our async code more easily by using them. I’m going to introduce some basic scaffold functions here. In the code above I created some functions which wrapped from the original async function such as open database, create table, etc.. All of them are very similar, created a task by using Wind.Async.Task.create, return error or result object through Task.complete function. In fact, Wind provides some functions for us to create task object from the original async functions. If the original async function only has a callback parameter, we can use Wind.Async.Binding.fromCallback method to get the task object directly. For example the code below returned the task object which wrapped the file exist check function. 1: var Wind = require("wind"); 2: var fs = require("fs"); 3:  4: fs.existsAsync = Wind.Async.Binding.fromCallback(fs.exists); In Node.js a very popular async function pattern is that, the first parameter in the callback function represent the error object, and the other parameters is the return values. In this case we can use another build-in function in Wind named Wind.Async.Binding.fromStandard. For example, the open database function can be created from the code below. 1: sql.openAsync = Wind.Async.Binding.fromStandard(sql.open); 2:  3: /* 4: sql.openAsync = function (connectionString) { 5: return Wind.Async.Task.create(function (t) { 6: sql.open(connectionString, function (error, conn) { 7: if (error) { 8: t.complete("failure", error); 9: } 10: else { 11: t.complete("success", conn); 12: } 13: }); 14: }); 15: }; 16: */ When I was testing the scaffold functions under Wind.Async.Binding I found for some functions, such as the Azure SDK insert entity function, cannot be processed correctly. So I personally suggest writing the wrapped method manually.   Another scaffold method in Wind is the parallel tasks coordination. In this example, the steps of open database, retrieve records and recreated table should be invoked one by one, but it can be executed in parallel when copying data from database to table storage. In Wind there’s a scaffold function named Task.whenAll which can be used here. Task.whenAll accepts a list of tasks and creates a new task. It will be returned only when all tasks had been completed, or any errors occurred. For example in the code below I used the Task.whenAll to make all copy operation executed at the same time. 1: var copyRecordsInParallel = eval(Wind.compile("async", function (req, res) { 2: try { 3: // connect to the windows azure sql database 4: var conn = $await(sql.openAsync(connectionString)); 5: console.log("connection opened"); 6: // retrieve all records from database 7: var results = $await(sql.queryAsync(conn, "SELECT * FROM [Resource]")); 8: console.log("records selected. count = %d", results.rows.length); 9: if (results.rows.length > 0) { 10: // recreate the table 11: $await(azure.recreateTableAsync(tableName)); 12: console.log("table created"); 13: // insert records in table storage in parallal 14: var tasks = new Array(results.rows.length); 15: for (var i = 0; i < results.rows.length; i++) { 16: var entity = { 17: "PartitionKey": results.rows[i][1], 18: "RowKey": results.rows[i][0], 19: "Value": results.rows[i][2] 20: }; 21: tasks[i] = azure.insertEntityAsync(tableName, entity); 22: } 23: $await(Wind.Async.Task.whenAll(tasks)); 24: // send response 25: console.log("all done"); 26: res.send(200, "All done!"); 27: } 28: } 29: catch (ex) { 30: console.log(ex); 31: res.send(500, "Internal error."); 32: } 33: })); 34:  35: app.get("/was/copyRecordsInParallel", function (req, res) { 36: copyRecordsInParallel(req, res).start(); 37: });   Besides the task creation and coordination, Wind supports the cancellation solution so that we can send the cancellation signal to the tasks. It also includes exception solution which means any exceptions will be reported to the caller function.   Summary In this post I introduced a Node.js module named Wind, which created by my friend Jeff Zhao. As you can see, different from other async library and framework, adopted the idea from F# and C#, Wind utilizes runtime code generation technology to make it more easily to write async, callback-based functions in a sync-style way. By using Wind there will be almost no callback, and the code will be very easy to understand. Currently Wind is still under developed and improved. There might be some problems but the author, Jeff, should be very happy and enthusiastic to learn your problems, feedback, suggestion and comments. You can contact Jeff by - Email: [email protected] - Group: https://groups.google.com/d/forum/windjs - GitHub: https://github.com/JeffreyZhao/wind/issues   Source code can be download here.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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• ERROR: Attempted to read or write protected memory. This is often an indication that other memory is corrupt

  - by SPSamL

  I get this error after having edited a few pages in SharePoint 2010. I have to do an IISReset on both front ends to get this to resolve. I don't know how to fix it or even what else to supply here, but please let me know as the resets now happen several times per day. Log Name: Application Source: ASP.NET 2.0.50727.0 Date: 1/26/2011 11:12:48 AM Event ID: 1309 Task Category: Web Event Level: Warning Keywords: Classic User: N/A Computer: PINTSPSFE02.samcstl.org Description: Event code: 3005 Event message: An unhandled exception has occurred. Event time: 1/26/2011 11:12:48 AM Event time (UTC): 1/26/2011 5:12:48 PM Event ID: c52fb336b7f147a3913fff3617a99d57 Event sequence: 4965 Event occurrence: 2178 Event detail code: 0 Application information: Application domain: /LM/W3SVC/1449762715/ROOT-2-129405348166941887 Trust level: WSS_Minimal Application Virtual Path: / Application Path: C:\inetpub\wwwroot\wss\VirtualDirectories\80\ Machine name: PINTSPSFE02 Process information: Process ID: 5928 Process name: w3wp.exe Account name: SAMC\MossAppPool Exception information: Exception type: AccessViolationException Exception message: Attempted to read or write protected memory. This is often an indication that other memory is corrupt. Request information: Request URL: http://mosscluster/Pages/Home.aspx Request path: /Pages/Home.aspx User host address: 10.3.60.26 User: SAMC\BARNMD Is authenticated: True Authentication Type: NTLM Thread account name: SAMC\MossAppPool Thread information: Thread ID: 110 Thread account name: SAMC\MossAppPool Is impersonating: False Stack trace: at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Delete(String key, Boolean recursive, DeletionReason reason) at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Get(String key) at Microsoft.Office.Server.ObjectCache.SPCache.Get(String objectTypeName, String id) at Microsoft.Office.Server.Administration.UserProfileServiceProxy.GetPartitionPropertiesCache(Guid applicationID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.get_PartitionPropertiesCache() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.DataCache.get_PartitionProperties() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, Guid partitionID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, SPServiceContext serviceContext) at Microsoft.Office.Server.WebControls.MyLinksRibbon.EnsureMySiteUrls() at Microsoft.Office.Server.WebControls.MyLinksRibbon.get_PortalMySiteUrlAvailable() at Microsoft.Office.Server.WebControls.MyLinksRibbon.OnLoad(EventArgs e) at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) Custom event details: Event Xml: <Event xmlns="http://schemas.microsoft.com/win/2004/08/events/event"> <System> <Provider Name="ASP.NET 2.0.50727.0" /> <EventID Qualifiers="32768">1309</EventID> <Level>3</Level> <Task>3</Task> <Keywords>0x80000000000000</Keywords> <TimeCreated SystemTime="2011-01-26T17:12:48.000000000Z" /> <EventRecordID>35834</EventRecordID> <Channel>Application</Channel> <Computer>PINTSPSFE02.samcstl.org</Computer> <Security /> </System> <EventData> <Data>3005</Data> <Data>An unhandled exception has occurred.</Data> <Data>1/26/2011 11:12:48 AM</Data> <Data>1/26/2011 5:12:48 PM</Data> <Data>c52fb336b7f147a3913fff3617a99d57</Data> <Data>4965</Data> <Data>2178</Data> <Data>0</Data> <Data>/LM/W3SVC/1449762715/ROOT-2-129405348166941887</Data> <Data>WSS_Minimal</Data> <Data>/</Data> <Data>C:\inetpub\wwwroot\wss\VirtualDirectories\80\</Data> <Data>PINTSPSFE02</Data> <Data> </Data> <Data>5928</Data> <Data>w3wp.exe</Data> <Data>SAMC\MossAppPool</Data> <Data>AccessViolationException</Data> <Data></Data> <Data>http://mosscluster/Pages/Home.aspx</Data> <Data>/Pages/Home.aspx</Data> <Data>10.3.60.26</Data> <Data>SAMC\BARNMD</Data> <Data>True</Data> <Data>NTLM</Data> <Data>SAMC\MossAppPool</Data> <Data>110</Data> <Data>SAMC\MossAppPool</Data> <Data>False</Data> <Data> at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Delete(String key, Boolean recursive, DeletionReason reason) at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Get(String key) at Microsoft.Office.Server.ObjectCache.SPCache.Get(String objectTypeName, String id) at Microsoft.Office.Server.Administration.UserProfileServiceProxy.GetPartitionPropertiesCache(Guid applicationID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.get_PartitionPropertiesCache() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.DataCache.get_PartitionProperties() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, Guid partitionID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, SPServiceContext serviceContext) at Microsoft.Office.Server.WebControls.MyLinksRibbon.EnsureMySiteUrls() at Microsoft.Office.Server.WebControls.MyLinksRibbon.get_PortalMySiteUrlAvailable() at Microsoft.Office.Server.WebControls.MyLinksRibbon.OnLoad(EventArgs e) at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) </Data> </EventData> </Event>

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• Parallelism in .NET – Part 4, Imperative Data Parallelism: Aggregation

  - by Reed

  In the article on simple data parallelism, I described how to perform an operation on an entire collection of elements in parallel.  Often, this is not adequate, as the parallel operation is going to be performing some form of aggregation. Simple examples of this might include taking the sum of the results of processing a function on each element in the collection, or finding the minimum of the collection given some criteria.  This can be done using the techniques described in simple data parallelism, however, special care needs to be taken into account to synchronize the shared data appropriately.  The Task Parallel Library has tools to assist in this synchronization. The main issue with aggregation when parallelizing a routine is that you need to handle synchronization of data.  Since multiple threads will need to write to a shared portion of data.  Suppose, for example, that we wanted to parallelize a simple loop that looked for the minimum value within a dataset: double min = double.MaxValue; foreach(var item in collection) { double value = item.PerformComputation(); min = System.Math.Min(min, value); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This seems like a good candidate for parallelization, but there is a problem here.  If we just wrap this into a call to Parallel.ForEach, we’ll introduce a critical race condition, and get the wrong answer.  Let’s look at what happens here: // Buggy code! Do not use! double min = double.MaxValue; Parallel.ForEach(collection, item => { double value = item.PerformComputation(); min = System.Math.Min(min, value); }); This code has a fatal flaw: min will be checked, then set, by multiple threads simultaneously.  Two threads may perform the check at the same time, and set the wrong value for min.  Say we get a value of 1 in thread 1, and a value of 2 in thread 2, and these two elements are the first two to run.  If both hit the min check line at the same time, both will determine that min should change, to 1 and 2 respectively.  If element 1 happens to set the variable first, then element 2 sets the min variable, we’ll detect a min value of 2 instead of 1.  This can lead to wrong answers. Unfortunately, fixing this, with the Parallel.ForEach call we’re using, would require adding locking.  We would need to rewrite this like: // Safe, but slow double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach(collection, item => { double value = item.PerformComputation(); lock(syncObject) min = System.Math.Min(min, value); }); This will potentially add a huge amount of overhead to our calculation.  Since we can potentially block while waiting on the lock for every single iteration, we will most likely slow this down to where it is actually quite a bit slower than our serial implementation.  The problem is the lock statement – any time you use lock(object), you’re almost assuring reduced performance in a parallel situation.  This leads to two observations I’ll make: When parallelizing a routine, try to avoid locks. That being said: Always add any and all required synchronization to avoid race conditions. These two observations tend to be opposing forces – we often need to synchronize our algorithms, but we also want to avoid the synchronization when possible.  Looking at our routine, there is no way to directly avoid this lock, since each element is potentially being run on a separate thread, and this lock is necessary in order for our routine to function correctly every time. However, this isn’t the only way to design this routine to implement this algorithm.  Realize that, although our collection may have thousands or even millions of elements, we have a limited number of Processing Elements (PE).  Processing Element is the standard term for a hardware element which can process and execute instructions.  This typically is a core in your processor, but many modern systems have multiple hardware execution threads per core.  The Task Parallel Library will not execute the work for each item in the collection as a separate work item. Instead, when Parallel.ForEach executes, it will partition the collection into larger “chunks” which get processed on different threads via the ThreadPool.  This helps reduce the threading overhead, and help the overall speed.  In general, the Parallel class will only use one thread per PE in the system. Given the fact that there are typically fewer threads than work items, we can rethink our algorithm design.  We can parallelize our algorithm more effectively by approaching it differently.  Because the basic aggregation we are doing here (Min) is communitive, we do not need to perform this in a given order.  We knew this to be true already – otherwise, we wouldn’t have been able to parallelize this routine in the first place.  With this in mind, we can treat each thread’s work independently, allowing each thread to serially process many elements with no locking, then, after all the threads are complete, “merge” together the results. This can be accomplished via a different set of overloads in the Parallel class: Parallel.ForEach<TSource,TLocal>.  The idea behind these overloads is to allow each thread to begin by initializing some local state (TLocal).  The thread will then process an entire set of items in the source collection, providing that state to the delegate which processes an individual item.  Finally, at the end, a separate delegate is run which allows you to handle merging that local state into your final results. To rewriting our routine using Parallel.ForEach<TSource,TLocal>, we need to provide three delegates instead of one.  The most basic version of this function is declared as: public static ParallelLoopResult ForEach<TSource, TLocal>( IEnumerable<TSource> source, Func<TLocal> localInit, Func<TSource, ParallelLoopState, TLocal, TLocal> body, Action<TLocal> localFinally ) The first delegate (the localInit argument) is defined as Func<TLocal>.  This delegate initializes our local state.  It should return some object we can use to track the results of a single thread’s operations. The second delegate (the body argument) is where our main processing occurs, although now, instead of being an Action<T>, we actually provide a Func<TSource, ParallelLoopState, TLocal, TLocal> delegate.  This delegate will receive three arguments: our original element from the collection (TSource), a ParallelLoopState which we can use for early termination, and the instance of our local state we created (TLocal).  It should do whatever processing you wish to occur per element, then return the value of the local state after processing is completed. The third delegate (the localFinally argument) is defined as Action<TLocal>.  This delegate is passed our local state after it’s been processed by all of the elements this thread will handle.  This is where you can merge your final results together.  This may require synchronization, but now, instead of synchronizing once per element (potentially millions of times), you’ll only have to synchronize once per thread, which is an ideal situation. Now that I’ve explained how this works, lets look at the code: // Safe, and fast! double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach( collection, // First, we provide a local state initialization delegate. () => double.MaxValue, // Next, we supply the body, which takes the original item, loop state, // and local state, and returns a new local state (item, loopState, localState) => { double value = item.PerformComputation(); return System.Math.Min(localState, value); }, // Finally, we provide an Action<TLocal>, to "merge" results together localState => { // This requires locking, but it's only once per used thread lock(syncObj) min = System.Math.Min(min, localState); } ); Although this is a bit more complicated than the previous version, it is now both thread-safe, and has minimal locking.  This same approach can be used by Parallel.For, although now, it’s Parallel.For<TLocal>.  When working with Parallel.For<TLocal>, you use the same triplet of delegates, with the same purpose and results. Also, many times, you can completely avoid locking by using a method of the Interlocked class to perform the final aggregation in an atomic operation.  The MSDN example demonstrating this same technique using Parallel.For uses the Interlocked class instead of a lock, since they are doing a sum operation on a long variable, which is possible via Interlocked.Add. By taking advantage of local state, we can use the Parallel class methods to parallelize algorithms such as aggregation, which, at first, may seem like poor candidates for parallelization.  Doing so requires careful consideration, and often requires a slight redesign of the algorithm, but the performance gains can be significant if handled in a way to avoid excessive synchronization.

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• Soluto’s New Quick Question Button Makes Family Tech Support Simple

  - by Jason Fitzpatrick

  Soluto, a computer and boot management tool, now features a Quick Question button that allows the people you help out to easily click a button and send you both a short message and a screenshot of the problem. Any time your friend or family member presses F8, Soluto will take a screenshot of the screen, the Task Manager history, and a note from the user highlighting what issue they’re experiencing, and then email it all to you. After reviewing the email you can easily login to Soluto to remotely manage your friend’s computer and help with the problem. For more information about Soluto you can check out our previous reviews of the service here and here, or just hit up the link below to read more and take Soluto for a test drive. Soluto is a free service (for the first 5 computers), Windows only. Introducing Quick Question [The Soluto Blog] Java is Insecure and Awful, It’s Time to Disable It, and Here’s How What Are the Windows A: and B: Drives Used For? HTG Explains: What is DNS?

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• SQLAuthority News – SQL Server 2008 R2 Hosted Trial

  - by pinaldave

  This is a bit old news but for me but it will new for many of you know. SQLPASS, Dell, Microsoft and MaximumASP has come together and build hosted environment for free to all of us to use and experiment with. Register now to try out up to seven labs: SQL Server 2008 R2 – Multi Server Management SQL Server 2008 R2 – PowerPivot SQL Server 2008 R2 – Reporting Services SQL Server 2008 R2 – Master Data Services SQL Server 2008 R2 – StreamInsight SQL Server Integration Services – Introduction SQL Server Integration Services – Intermediate to Advanced Now this is indeed wonderful opportunity as you do not need to buy anything and get world class experience with this products. Register here. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, T SQL, Technology Tagged: SQL PASS

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• SQL SERVER – Database Dynamic Caching by Automatic SQL Server Performance Acceleration

  - by pinaldave

  My second look at SafePeak’s new version (2.1) revealed to me few additional interesting features. For those of you who hadn’t read my previous reviews SafePeak and not familiar with it, here is a quick brief: SafePeak is in business of accelerating performance of SQL Server applications, as well as their scalability, without making code changes to the applications or to the databases. SafePeak performs database dynamic caching, by caching in memory result sets of queries and stored procedures while keeping all those cache correct and up to date. Cached queries are retrieved from the SafePeak RAM in microsecond speed and not send to the SQL Server. The application gets much faster results (100-500 micro seconds), the load on the SQL Server is reduced (less CPU and IO) and the application or the infrastructure gets better scalability. SafePeak solution is hosted either within your cloud servers, hosted servers or your enterprise servers, as part of the application architecture. Connection of the application is done via change of connection strings or adding reroute line in the c:\windows\system32\drivers\etc\hosts file on all application servers. For those who would like to learn more on SafePeak architecture and how it works, I suggest to read this vendor’s webpage: SafePeak Architecture. More interesting new features in SafePeak 2.1 In my previous review of SafePeak new I covered the first 4 things I noticed in the new SafePeak (check out my article “SQLAuthority News – SafePeak Releases a Major Update: SafePeak version 2.1 for SQL Server Performance Acceleration”): Cache setup and fine-tuning – a critical part for getting good caching results Database templates Choosing which database to cache Monitoring and analysis options by SafePeak Since then I had a chance to play with SafePeak some more and here is what I found. 5. Analysis of SQL Performance (present and history): In SafePeak v.2.1 the tools for understanding of performance became more comprehensive. Every 15 minutes SafePeak creates and updates various performance statistics. Each query (or a procedure execute) that arrives to SafePeak gets a SQL pattern, and after it is used again there are statistics for such pattern. An important part of this product is that it understands the dependencies of every pattern (list of tables, views, user defined functions and procs). From this understanding SafePeak creates important analysis information on performance of every object: response time from the database, response time from SafePeak cache, average response time, percent of traffic and break down of behavior. One of the interesting things this behavior column shows is how often the object is actually pdated. The break down analysis allows knowing the above information for: queries and procedures, tables, views, databases and even instances level. The data is show now on all arriving queries, both read queries (that can be cached), but also any types of updates like DMLs, DDLs, DCLs, and even session settings queries. The stats are being updated every 15 minutes and SafePeak dashboard allows going back in time and investigating what happened within any time frame. 6. Logon trigger, for making sure nothing corrupts SafePeak cache data If you have an application with many parts, many servers many possible locations that can actually update the database, or the SQL Server is accessible to many DBAs or software engineers, each can access some database directly and do some changes without going thru SafePeak – this can create a potential corruption of the data stored in SafePeak cache. To make sure SafePeak cache is correct it needs to get all updates to arrive to SafePeak, and if a DBA will access the database directly and do some changes, for example, then SafePeak will simply not know about it and will not clean SafePeak cache. In the new version, SafePeak brought a new feature called “Logon Trigger” to solve the above challenge. By special click of a button SafePeak can deploy a special server logon trigger (with a CLR object) on your SQL Server that actually monitors all connections and informs SafePeak on any connection that is coming not from SafePeak. In SafePeak dashboard there is an interface that allows to control which logins can be ignored based on login names and IPs, while the rest will invoke cache cleanup of SafePeak and actually locks SafePeak cache until this connection will not be closed. Important to note, that this does not interrupt any logins, only informs SafePeak on such connection. On the Dashboard screen in SafePeak you will be able to see those connections and then decide what to do with them. Configuration of this feature in SafePeak dashboard can be done here: Settings -> SQL instances management -> click on instance -> Logon Trigger tab. Other features: 7. User management ability to grant permissions to someone without changing its configuration and only use SafePeak as performance analysis tool. 8. Better reports for analysis of performance using 15 minute resolution charts. 9. Caching of client cursors 10. Support for IPv6 Summary SafePeak is a great SQL Server performance acceleration solution for users who want immediate results for sites with performance, scalability and peak spikes challenges. Especially if your apps are packaged or 3rd party, since no code changes are done. SafePeak can significantly increase response times, by reducing network roundtrip to the database, decreasing CPU resource usage, eliminating I/O and storage access. SafePeak team provides a free fully functional trial www.safepeak.com/download and actually provides a one-on-one assistance during such trial. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, Pinal Dave, PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology

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• LIVE WEBCAST March 24 2pm PT- Why Switch from Red Hat and SUSE Linux to Oracle Linux?

  - by Zeynep Koch

  Oracle has been offering affordable Linux support since 2006 and more than 6,000 customers already use it. Oracle's Unbreakable Linux support program draws on the expertise of a world-class support organization that understands how to diagnose and solve Linux issues integrated with the applications being deployed on it. Find out how you can save 50-90% on your support costs. Join Oracle's Monica Kumar, Sr.Director of Linux, Oracle VM and MySQL and Avi Miller, Principal Sales Consultant, Linux and Virtualization on Thursday, March 24, 2pm PT to hear:The "Why and how" of switching to Oracle LinuxTesting and integration with systems and applicationsFree management and high availability toolsReal life customer scenariosIf you are going to get free access to the most advanced Linux operating system, along with world-class support at a fraction of the cost, better testing and integration with your server and applications, why wouldn't you do it? Register Now

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• Enable Automatic Code First Migrations On SQL Database in Azure Web Sites

  - by Steve Michelotti

  Now that Azure supports .NET Framework 4.5, you can use all the latest and greatest available features. A common scenario is to be able to use Entity Framework Code First Migrations with a SQL Database in Azure. Prior to Code First Migrations, Entity Framework provided database initializers. While convenient for demos and prototypes, database initializers weren’t useful for much beyond that because, if you delete and re-create your entire database when the schema changes, you lose all of your operational data. This is the void that Migrations are meant to fill. For example, if you add a column to your model, Migrations will alter the database to add the column rather than blowing away the entire database and re-creating it from scratch. Azure is becoming increasingly easier to use – especially with features like Azure Web Sites. Being able to use Entity Framework Migrations in Azure makes deployment easier than ever. In this blog post, I’ll walk through enabling Automatic Code First Migrations on Azure. I’ll use the Simple Membership provider for my example. First, we’ll create a new Azure Web site called “migrationstest” including creating a new SQL Database along with it:   Next we’ll go to the web site and download the publish profile:   In the meantime, we’ve created a new MVC 4 website in Visual Studio 2012 using the “Internet Application” template. This template is automatically configured to use the Simple Membership provider. We’ll do our initial Publish to Azure by right-clicking our project and selecting “Publish…”. From the “Publish Web” dialog, we’ll import the publish profile that we downloaded in the previous step:   Once the site is published, we’ll just click the “Register” link from the default site. Since the AccountController is decorated with the [InitializeSimpleMembership] attribute, the initializer will be called and the initial database is created.   We can verify this by connecting to our SQL Database on Azure with SQL Management Studio (after making sure that our local IP address is added to the list of Allowed IP Addresses in Azure): One interesting note is that these tables got created with the default Entity Framework initializer – which is to create the database if it doesn’t already exist. However, our database did already exist! This is because there is a new feature of Entity Framework 5 where Code First will add tables to an existing database as long as the target database doesn’t contain any of the tables from the model. At this point, it’s time to enable Migrations. We’ll open the Package Manger Console and execute the command: PM> Enable-Migrations -EnableAutomaticMigrations This will enable automatic migrations for our project. Because we used the "-EnableAutomaticMigrations” switch, it will create our Configuration class with a constructor that sets the AutomaticMigrationsEnabled property set to true: 1: public Configuration() 2: { 3: AutomaticMigrationsEnabled = true; 4: } We’ll now add our initial migration: PM> Add-Migration Initial This will create a migration class call “Initial” that contains the entire model. But we need to remove all of this code because our database already exists so we are just left with empty Up() and Down() methods. 1: public partial class Initial : DbMigration 2: { 3: public override void Up() 4: { 5: } 6: 7: public override void Down() 8: { 9: } 10: } If we don’t remove this code, we’ll get an exception the first time we attempt to run migrations that tells us: “There is already an object named 'UserProfile' in the database”. This blog post by Julie Lerman fully describes this scenario (i.e., enabling migrations on an existing database). Our next step is to add the Entity Framework initializer that will automatically use Migrations to update the database to the latest version. We will add these 2 lines of code to the Application_Start of the Global.asax: 1: Database.SetInitializer(new MigrateDatabaseToLatestVersion<UsersContext, Configuration>()); 2: new UsersContext().Database.Initialize(false); Note the Initialize() call will force the initializer to run if it has not been run before. At this point, we can publish again to make sure everything is still working as we are expecting. This time we’re going to specify in our publish profile that Code First Migrations should be executed:   Once we have re-published we can once again navigate to the Register page. At this point the database has not been changed but Migrations is now enabled on our SQL Database in Azure. We can now customize our model. Let’s add 2 new properties to the UserProfile class – Email and DateOfBirth: 1: [Table("UserProfile")] 2: public class UserProfile 3: { 4: [Key] 5: [DatabaseGeneratedAttribute(DatabaseGeneratedOption.Identity)] 6: public int UserId { get; set; } 7: public string UserName { get; set; } 8: public string Email { get; set; } 9: public DateTime DateOfBirth { get; set; } 10: } At this point all we need to do is simply re-publish. We’ll once again navigate to the Registration page and, because we had Automatic Migrations enabled, the database has been altered (*not* recreated) to add our 2 new columns. We can verify this by once again looking at SQL Management Studio:   Automatic Migrations provide a quick and easy way to keep your database in sync with your model without the worry of having to re-create your entire database and lose data. With Azure Web Sites you can set up automatic deployment with Git or TFS and automate the entire process to make it dead simple.

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• Migration from Exchange to BPOS - Microsoft Assessment and Planning (MAP) Toolkit Link

  - by Harish Pavithran

  The Microsoft Assessment and Planning (MAP) Toolkit is an agentless toolkit that finds computers on a network and performs a detailed inventory of the computers using Windows Management Instrumentation (WMI) and the Remote Registry Service. The data and analysis provided by this toolkit can significantly simplify the planning process for migrating to Windows® 7, Windows Vista®, Microsoft Office 2007, Windows Server® 2008 R2, Windows Server 2008, Hyper-V, Microsoft Application Virtualization, Microsoft SQL Server 2008, and Forefront® Client Security and Network Access Protection. Assessments for Windows Server 2008 R2, Windows Server 2008, Windows 7, and Windows Vista include device driver availability as well as recommendations for hardware upgrades. If you are interested in server virtualization planning, MAP provides the ability to gather performance metrics from computers you are considering for virtualization and a feature to model a library of potential host hardware and storage configurations. This information can be used to quickly perform "what-if" analysis using Hyper-V and Microsoft Virtual Server 2005 R2 as virtualization platforms. http://www.microsoft.com/downloads/details.aspx?displaylang=en&FamilyID=67240b76-3148-4e49-943d-4d9ea7f77730

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• ARM TechCon 2013: Oracle, ARM expand collaboration on servers, Internet of Things

  - by terrencebarr

  Over the years, Oracle has been making big investments in Java for ARM-based devices. This week, Oracle and ARM announced further expanding their collaboration on a number of fronts, from additional hardware platforms, porting layers, and optimized communication protocols, to 64-bit ARMv8 support, and IoT architectures. Henrik Stahl, VP of Product Management in the Java Platform Group at Oracle, just posted an excellent summary: “ARM TechCon 2013: Oracle, ARM expand collaboration on servers, Internet of Things”. Highly recommended reading. Cheers, – TerrenceFiled under: Embedded Tagged: 6LoWPAN, ARM, CoAP, Freescale, Gemalto, iot, Java Embedded, Java ME Embedded, Java SE Embedded, Lego Mindstorms, OpenJDK, Qualcomm, Raspberry Pi, TechCon

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• EXALYTICS - Oracle® Essbase 11.1.2.1.000 Patch Set (PS): 11.1.2.2.000

  - by Ahmed Awan

  Who should apply this patch: This PS contains defect fixes and changes that are specific to the Oracle Exalytics In-Memory box. You should install this PS only in the following circumstances: You are installing Essbase on the Exalytics In-Memory Machine, or There is an urgent need for a defect fix that is included in this PS Customers considering this PS for a platform other than the Exalytics In-Memory Machine should carefully review the list of fixed defects. If there is not a truly urgent need for a defect fix included in this PS, Oracle recommends customers install the upcoming Enterprise Performance Management (EPM) 11.1.2.2.000 release, which will contain an update, instead of this patch set. Reference: http://docs.oracle.com/cd/E26232_01/doc.11122/readme/esb_11122000_readme.html

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• Microsoft Presss Free E-Book - 12/April/2012 - Introducing Microsoft® SQL Server® 2012

  - by TATWORTH

  At http://shop.oreilly.com/product/0790145342201.do, I have spotted a free e-book "Introducing Microsoft® SQL Server® 2012 ". There is no indication as to how long this will be available for free, so I suggest get it ASAP. It is available in a number of other electronic formats besides PDF."Introducing Microsoft® SQL Server® 2012 explores the exciting enhancements and new capabilities engineered into SQL Server, ranging from improvements in operation to those in reporting and management. This book is for anyone who has an interest in SQL Server 2012 and wants to understand its capabilities, including database administrators, application developers, and technical decision makers."

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• James Atkinson - New Blog Home

  - by jatkinson

  I'm migrating my blog that is currently hosted over at vbCity.com (which is an outstanding developer community!) to a new home at geekswithblogs.net. I truly appreciate the comradery of Serge B, Ged Mead, and the other team members at the "City". What you can expect to find here (my interests): Most .NET programming topics General computing Language examples in C#, VB.NET, and Boo WCF WPF Mathematical / GPS solutions F# (in progress... if you can say that much) Obsessed with code performance (speed) Some photography My background: Kansas State University Grad (Agriculture Technology Management) From Richmond, VA Self taught programmer (started with C# in VS2002) NOT a professional programmer (enables free thinking?!)  I'm no Jeff Atwood or Beth Massi, but you should expect to see some interesting stuff to follow.

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• Commercial Drupal Modules & Themes

  - by Ravish

  A discussion at Drupal.org forums prompted me to give my input about commercial ecosystem around Open Source Content Management Systems. WordPress and Joomla have been growing rapidly since past few years. But, growth rate of Drupal seems to be almost flat. Despite being the most powerful CMS around, Drupal is still not being adopted by masses. Many people will argue that Drupal is not targeted towards masses, but developers. I agree, Drupal is more of a development platform than a consumer CMS. Drupal is ‘many things to many people’, and I can build almost any type of website with it. Drupal is being used for building blogs, corporate websites, Intranet portals, social networking and even a project management system. Looking at the wide array of Drupal implementations, it deserves to be the most widely adopted CMS. I believe there are few challenges that Drupal community needs to overcome. To understand these challenges, I surveyed some webmasters who use Joomla or WordPress but not Drupal. I asked them why they don’t want to use Drupal, following are the responses I got from them: Drupal is too complicated, takes time to learn. Drupal is great, but its admin panel is overwhelming. I couldn’t find any nice themes for Drupal. There is no WYSIWYG editor in Drupal. Most Drupal modules do not work out of the box. There aren’t enough modules like Ubercart which provides any out of the box functionality. I tried modules like CCK, Views and Panels. After wasting several hours struggling with them, I decided to give up on Drupal. I don’t use Drupal because of pushbutton and Garland theme. I had hard time trying to customize Garland and it messed up the whole layout. There are no premium modules and themes for Drupal. Joomla has tons of awesome themes and modules. I don’t want a million hacks like CCK, Views, Tokens, Pathauto, ImageCache and CTools just to run a simple website. Most of the complaints from users are related to the learning and development curve involved with Drupal, and the lack of ecosystem. While most of the problems will be gone in Drupal 7, ecosystem is something that needs to be built by the Drupal community. Drupal distributions are a great step forward. There are few awesome Drupal distributions available like Open Publish, Open Atrium and Drupal Commons. I predict, there will be a wave of many powerful Drupal distributions after Drupal 7 release. Many of them will be user-friendly and commercial supported. Following is my post at Drupal.org forums: Quote from: http://drupal.org/node/863776#comment-3313836 Brian Gardner (StudioPress) and Woo Themes launched premium WordPress themes in 2007, the developer community did not accept it at first. Moreover, they were not even GPL licensed. There was an outcry in WordPress community against them. Following that, most premium theme providers switched to GPL licensing. Despite controversies, users voted for premium theme and plugins by buying them. Inspired by their success, hundreds of other developers started to sell premium themes and plugins. It is now the acceptable and in fact most popular business model among WordPress community. Matt Mullenweg once told me, they would not support premium themes. If he supported, developers would no more give out free GPL themes & plugins. He pointed me towards Joomla, there were hardly any nice free themes & modules available. Now two years forward, premium products are not just accepted but embraced by the WordPress community – http://wordpress.org/extend/themes/commercial/ The quality and number of themes & modules has increased, even the free ones. This also helped to boost the adoption and ecosystem of WordPress. Today, state of Drupal is like WordPress was in 2007. There are hardly any out of the box solutions available for Drupal. Ubercart, Open Publish and Open Atrium are the only ones I can think of. Many of the popular Drupal modules are patches and hole-fillers. Thankfully, these hole-filler modules are going to be in Drupal 7 core. Drupal 7 and distributions will spawn a new array of solutions built upon Drupal. Soon, we will have more like Ubercarts and Open Atriums. If commercial solutions can help fuel this ecosystem and growth, Drupal community will accept them eventually. This debate will not stop your customers from buying your product. If your product is awesome, they will vote for you by buying your product.

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• Scrum in 5 Minutes

  - by Stephen.Walther

  The goal of this blog entry is to explain the basic concepts of Scrum in less than five minutes. You learn how Scrum can help a team of developers to successfully complete a complex software project. Product Backlog and the Product Owner Imagine that you are part of a team which needs to create a new website – for example, an e-commerce website. You have an overwhelming amount of work to do. You need to build (or possibly buy) a shopping cart, install an SSL certificate, create a product catalog, create a Facebook page, and at least a hundred other things that you have not thought of yet. According to Scrum, the first thing you should do is create a list. Place the highest priority items at the top of the list and the lower priority items lower in the list. For example, creating the shopping cart and buying the domain name might be high priority items and creating a Facebook page might be a lower priority item. In Scrum, this list is called the Product Backlog. How do you prioritize the items in the Product Backlog? Different stakeholders in the project might have different priorities. Gary, your division VP, thinks that it is crucial that the e-commerce site has a mobile app. Sally, your direct manager, thinks taking advantage of new HTML5 features is much more important. Multiple people are pulling you in different directions. According to Scrum, it is important that you always designate one person, and only one person, as the Product Owner. The Product Owner is the person who decides what items should be added to the Product Backlog and the priority of the items in the Product Backlog. The Product Owner could be the customer who is paying the bills, the project manager who is responsible for delivering the project, or a customer representative. The critical point is that the Product Owner must always be a single person and that single person has absolute authority over the Product Backlog. Sprints and the Sprint Backlog So now the developer team has a prioritized list of items and they can start work. The team starts implementing the first item in the Backlog — the shopping cart — and the team is making good progress. Unfortunately, however, half-way through the work of implementing the shopping cart, the Product Owner changes his mind. The Product Owner decides that it is much more important to create the product catalog before the shopping cart. With some frustration, the team switches their developmental efforts to focus on implementing the product catalog. However, part way through completing this work, once again the Product Owner changes his mind about the highest priority item. Getting work done when priorities are constantly shifting is frustrating for the developer team and it results in lower productivity. At the same time, however, the Product Owner needs to have absolute authority over the priority of the items which need to get done. Scrum solves this conflict with the concept of Sprints. In Scrum, a developer team works in Sprints. At the beginning of a Sprint the developers and the Product Owner agree on the items from the backlog which they will complete during the Sprint. This subset of items from the Product Backlog becomes the Sprint Backlog. During the Sprint, the Product Owner is not allowed to change the items in the Sprint Backlog. In other words, the Product Owner cannot shift priorities on the developer team during the Sprint. Different teams use Sprints of different lengths such as one month Sprints, two-week Sprints, and one week Sprints. For high-stress, time critical projects, teams typically choose shorter sprints such as one week sprints. For more mature projects, longer one month sprints might be more appropriate. A team can pick whatever Sprint length makes sense for them just as long as the team is consistent. You should pick a Sprint length and stick with it. Daily Scrum During a Sprint, the developer team needs to have meetings to coordinate their work on completing the items in the Sprint Backlog. For example, the team needs to discuss who is working on what and whether any blocking issues have been discovered. Developers hate meetings (well, sane developers hate meetings). Meetings take developers away from their work of actually implementing stuff as opposed to talking about implementing stuff. However, a developer team which never has meetings and never coordinates their work also has problems. For example, Fred might get stuck on a programming problem for days and never reach out for help even though Tom (who sits in the cubicle next to him) has already solved the very same problem. Or, both Ted and Fred might have started working on the same item from the Sprint Backlog at the same time. In Scrum, these conflicting needs – limiting meetings but enabling team coordination – are resolved with the idea of the Daily Scrum. The Daily Scrum is a meeting for coordinating the work of the developer team which happens once a day. To keep the meeting short, each developer answers only the following three questions: 1. What have you done since yesterday? 2. What do you plan to do today? 3. Any impediments in your way? During the Daily Scrum, developers are not allowed to talk about issues with their cat, do demos of their latest work, or tell heroic stories of programming problems overcome. The meeting must be kept short — typically about 15 minutes. Issues which come up during the Daily Scrum should be discussed in separate meetings which do not involve the whole developer team. Stories and Tasks Items in the Product or Sprint Backlog – such as building a shopping cart or creating a Facebook page – are often referred to as User Stories or Stories. The Stories are created by the Product Owner and should represent some business need. Unlike the Product Owner, the developer team needs to think about how a Story should be implemented. At the beginning of a Sprint, the developer team takes the Stories from the Sprint Backlog and breaks the stories into tasks. For example, the developer team might take the Create a Shopping Cart story and break it into the following tasks: · Enable users to add and remote items from shopping cart · Persist the shopping cart to database between visits · Redirect user to checkout page when Checkout button is clicked During the Daily Scrum, members of the developer team volunteer to complete the tasks required to implement the next Story in the Sprint Backlog. When a developer talks about what he did yesterday or plans to do tomorrow then the developer should be referring to a task. Stories are owned by the Product Owner and a story is all about business value. In contrast, the tasks are owned by the developer team and a task is all about implementation details. A story might take several days or weeks to complete. A task is something which a developer can complete in less than a day. Some teams get lazy about breaking stories into tasks. Neglecting to break stories into tasks can lead to “Never Ending Stories” If you don’t break a story into tasks, then you can’t know how much of a story has actually been completed because you don’t have a clear idea about the implementation steps required to complete the story. Scrumboard During the Daily Scrum, the developer team uses a Scrumboard to coordinate their work. A Scrumboard contains a list of the stories for the current Sprint, the tasks associated with each Story, and the state of each task. The developer team uses the Scrumboard so everyone on the team can see, at a glance, what everyone is working on. As a developer works on a task, the task moves from state to state and the state of the task is updated on the Scrumboard. Common task states are ToDo, In Progress, and Done. Some teams include additional task states such as Needs Review or Needs Testing. Some teams use a physical Scrumboard. In that case, you use index cards to represent the stories and the tasks and you tack the index cards onto a physical board. Using a physical Scrumboard has several disadvantages. A physical Scrumboard does not work well with a distributed team – for example, it is hard to share the same physical Scrumboard between Boston and Seattle. Also, generating reports from a physical Scrumboard is more difficult than generating reports from an online Scrumboard. Estimating Stories and Tasks Stakeholders in a project, the people investing in a project, need to have an idea of how a project is progressing and when the project will be completed. For example, if you are investing in creating an e-commerce site, you need to know when the site can be launched. It is not enough to just say that “the project will be done when it is done” because the stakeholders almost certainly have a limited budget to devote to the project. The people investing in the project cannot determine the business value of the project unless they can have an estimate of how long it will take to complete the project. Developers hate to give estimates. The reason that developers hate to give estimates is that the estimates are almost always completely made up. For example, you really don’t know how long it takes to build a shopping cart until you finish building a shopping cart, and at that point, the estimate is no longer useful. The problem is that writing code is much more like Finding a Cure for Cancer than Building a Brick Wall. Building a brick wall is very straightforward. After you learn how to add one brick to a wall, you understand everything that is involved in adding a brick to a wall. There is no additional research required and no surprises. If, on the other hand, I assembled a team of scientists and asked them to find a cure for cancer, and estimate exactly how long it will take, they would have no idea. The problem is that there are too many unknowns. I don’t know how to cure cancer, I need to do a lot of research here, so I cannot even begin to estimate how long it will take. So developers hate to provide estimates, but the Product Owner and other product stakeholders, have a legitimate need for estimates. Scrum resolves this conflict by using the idea of Story Points. Different teams use different units to represent Story Points. For example, some teams use shirt sizes such as Small, Medium, Large, and X-Large. Some teams prefer to use Coffee Cup sizes such as Tall, Short, and Grande. Finally, some teams like to use numbers from the Fibonacci series. These alternative units are converted into a Story Point value. Regardless of the type of unit which you use to represent Story Points, the goal is the same. Instead of attempting to estimate a Story in hours (which is doomed to failure), you use a much less fine-grained measure of work. A developer team is much more likely to be able to estimate that a Story is Small or X-Large than the exact number of hours required to complete the story. So you can think of Story Points as a compromise between the needs of the Product Owner and the developer team. When a Sprint starts, the developer team devotes more time to thinking about the Stories in a Sprint and the developer team breaks the Stories into Tasks. In Scrum, you estimate the work required to complete a Story by using Story Points and you estimate the work required to complete a task by using hours. The difference between Stories and Tasks is that you don’t create a task until you are just about ready to start working on a task. A task is something that you should be able to create within a day, so you have a much better chance of providing an accurate estimate of the work required to complete a task than a story. Burndown Charts In Scrum, you use Burndown charts to represent the remaining work on a project. You use Release Burndown charts to represent the overall remaining work for a project and you use Sprint Burndown charts to represent the overall remaining work for a particular Sprint. You create a Release Burndown chart by calculating the remaining number of uncompleted Story Points for the entire Product Backlog every day. The vertical axis represents Story Points and the horizontal axis represents time. A Sprint Burndown chart is similar to a Release Burndown chart, but it focuses on the remaining work for a particular Sprint. There are two different types of Sprint Burndown charts. You can either represent the remaining work in a Sprint with Story Points or with task hours (the following image, taken from Wikipedia, uses hours). When each Product Backlog Story is completed, the Release Burndown chart slopes down. When each Story or task is completed, the Sprint Burndown chart slopes down. Burndown charts typically do not always slope down over time. As new work is added to the Product Backlog, the Release Burndown chart slopes up. If new tasks are discovered during a Sprint, the Sprint Burndown chart will also slope up. The purpose of a Burndown chart is to give you a way to track team progress over time. If, halfway through a Sprint, the Sprint Burndown chart is still climbing a hill then you know that you are in trouble. Team Velocity Stakeholders in a project always want more work done faster. For example, the Product Owner for the e-commerce site wants the website to launch before tomorrow. Developers tend to be overly optimistic. Rarely do developers acknowledge the physical limitations of reality. So Project stakeholders and the developer team often collude to delude themselves about how much work can be done and how quickly. Too many software projects begin in a state of optimism and end in frustration as deadlines zoom by. In Scrum, this problem is overcome by calculating a number called the Team Velocity. The Team Velocity is a measure of the average number of Story Points which a team has completed in previous Sprints. Knowing the Team Velocity is important during the Sprint Planning meeting when the Product Owner and the developer team work together to determine the number of stories which can be completed in the next Sprint. If you know the Team Velocity then you can avoid committing to do more work than the team has been able to accomplish in the past, and your team is much more likely to complete all of the work required for the next Sprint. Scrum Master There are three roles in Scrum: the Product Owner, the developer team, and the Scrum Master. I’v e already discussed the Product Owner. The Product Owner is the one and only person who maintains the Product Backlog and prioritizes the stories. I’ve also described the role of the developer team. The members of the developer team do the work of implementing the stories by breaking the stories into tasks. The final role, which I have not discussed, is the role of the Scrum Master. The Scrum Master is responsible for ensuring that the team is following the Scrum process. For example, the Scrum Master is responsible for making sure that there is a Daily Scrum meeting and that everyone answers the standard three questions. The Scrum Master is also responsible for removing (non-technical) impediments which the team might encounter. For example, if the team cannot start work until everyone installs the latest version of Microsoft Visual Studio then the Scrum Master has the responsibility of working with management to get the latest version of Visual Studio as quickly as possible. The Scrum Master can be a member of the developer team. Furthermore, different people can take on the role of the Scrum Master over time. The Scrum Master, however, cannot be the same person as the Product Owner. Using SonicAgile SonicAgile (SonicAgile.com) is an online tool which you can use to manage your projects using Scrum. You can use the SonicAgile Product Backlog to create a prioritized list of stories. You can estimate the size of the Stories using different Story Point units such as Shirt Sizes and Coffee Cup sizes. You can use SonicAgile during the Sprint Planning meeting to select the Stories that you want to complete during a particular Sprint. You can configure Sprints to be any length of time. SonicAgile calculates Team Velocity automatically and displays a warning when you add too many stories to a Sprint. In other words, it warns you when it thinks you are overcommitting in a Sprint. SonicAgile also includes a Scrumboard which displays the list of Stories selected for a Sprint and the tasks associated with each story. You can drag tasks from one task state to another. Finally, SonicAgile enables you to generate Release Burndown and Sprint Burndown charts. You can use these charts to view the progress of your team. To learn more about SonicAgile, visit SonicAgile.com. Summary In this post, I described many of the basic concepts of Scrum. You learned how a Product Owner uses a Product Backlog to create a prioritized list of tasks. I explained why work is completed in Sprints so the developer team can be more productive. I also explained how a developer team uses the daily scrum to coordinate their work. You learned how the developer team uses a Scrumboard to see, at a glance, who is working on what and the state of each task. I also discussed Burndown charts. You learned how you can use both Release and Sprint Burndown charts to track team progress in completing a project. Finally, I described the crucial role of the Scrum Master – the person who is responsible for ensuring that the rules of Scrum are being followed. My goal was not to describe all of the concepts of Scrum. This post was intended to be an introductory overview. For a comprehensive explanation of Scrum, I recommend reading Ken Schwaber’s book Agile Project Management with Scrum: http://www.amazon.com/Agile-Project-Management-Microsoft-Professional/dp/073561993X/ref=la_B001H6ODMC_1_1?ie=UTF8&qid=1345224000&sr=1-1

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• Mark Hurd and Balaji Yelamanchili present Oracle’s Business Analytics Strategy

  - by Mike.Hallett(at)Oracle-BI&EPM

  Join Mark Hurd and Balaji Yelamanchili as they unveil the latest advances in Oracle’s strategy for placing analytics into the hands of every decision-makers—so that they can see more, think smarter, and act faster. Wednesday, April 4, 2012   at 1.0 pm UK BST / 2.0 pm CET Register HERE today for this online event Agenda Keynote: Oracle’s Business Analytics StrategyMark Hurd, President, Oracle, and Balaji Yelamanchili, Senior Vice President, Analytics and Performance Management, Oracle Plus Breakout Sessions: Achieving Predictable Performance with Oracle Hyperion Enterprise Performance Managemen Explore All Relevant Data—Introducing Oracle Endeca Information Discovery Run Your Business Faster and Smarter with Oracle Business Intelligence Applications on Oracle Exalytics In-Memory Machine Analyzing and Deciding with Big Data

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• Webcast Replay Available: Performance Tuning E-Business Suite Concurrent Manager (Performance Series Part 2 of 3)

  - by BillSawyer

  I am pleased to release the replay and presentation for the latest ATG Live Webcast: Performance Tuning E-Business Suite Concurrent Manager (Performance Series Part 2 of 3) (Presentation)Andy Tremayne, Senior Architect, Applications Performance, and co-author of Oracle Applications Performance Tuning Handbook from Oracle Press, and Uday Moogala, Senior Principal Engineer, Applications Performance discussed two major components of E-Business Suite performance tuning:  concurrent management and tracing. They dispel some myths surrounding these topics, and shared with you the recommended best practices that you can use on your own E-Business Suite instance.Finding other recorded ATG webcastsThe catalog of ATG Live Webcast replays, presentations, and all ATG training materials is available in this blog's Webcasts and Training section.

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• Using CMS for App Configuration - Part 1, Deploying Umbraco

  - by Elton Stoneman

  Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2014/06/04/using-cms-for-app-configurationndashpart-1-deploy-umbraco.aspxSince my last post on using CMS for semi-static API content, How about a new platform for your next API… a CMS?, I’ve been using the idea for centralized app configuration, and this post is the first in a series that will walk through how to do that, step-by-step. The approach gives you a platform-independent, easily configurable way to specify your application configuration for different environments, with a built-in approval workflow, change auditing and the ability to easily rollback to previous settings. It’s like Azure Web and Worker Roles where you can specify settings that change at runtime, but it's not specific to Azure - you can use it for any app that needs changeable config, provided it can access the Internet. The series breaks down into four posts: Deploying Umbraco – the CMS that will store your configurable settings and the current values; Publishing your config – create a document type that encapsulates your settings and a template to expose them as JSON; Consuming your config – in .NET, a simple client that uses dynamic objects to access settings; Config lifecycle management – how to publish, audit, and rollback settings. Let’s get started. Deploying Umbraco There’s an Umbraco package on Azure Websites, so deploying your own instance is easy – but there are a couple of things to watch out for, so this step-by-step will put you in a good place. Create From Gallery The easiest way to get started is with an Azure subscription, navigate to add a new Website and then Create From Gallery. Under CMS, you’ll see an Umbraco package (currently at version 7.1.3): Configure Your App For high availability and scale, you’ll want your CMS on separate kit from anything else you have in Azure, so in the configuration of Umbraco I’d create a new SQL Azure database – which Umbraco will use to store all its content: You can use the free 20mb database option if you don’t have demanding NFRs, or if you’re just experimenting. You’ll need to specify a password for a SQL Server account which the Umbraco service will use, and changing from the default username umbracouser is probably wise. Specify Database Settings You can create a new database on an existing server if you have one, or create new. If you create a new server *do not* use the same username for the database server login as you used for the Umbraco account. If you do, the deployment will fail later. Think of this as the SQL Admin account that you can use for managing the db, the previous account was the service account Umbraco uses to connect. Make Tea If you have a fast kettle. It takes about two minutes for Azure to create and provision the website and the database. Install Umbraco So far we’ve deployed an empty instance of Umbraco using the Azure package, and now we need to browse to the site and complete installation. My Website was called my-app-config, so to complete installation I browse to http://my-app-config.azurewebsites.net:   Enter the credentials you want to use to login – this account will have full admin rights to the Umbraco instance. Note that between deploying your new Umbraco instance and completing installation in this step, anyone can browse to your website and complete the installation themselves with their own credentials, if they know the URL. Remote possibility, but it’s there. From this page *do not* click the big green Install button. If you do, Umbraco will configure itself with a local SQL Server CE database (.sdf file on the Web server), and ignore the SQL Azure database you’ve carefully provisioned and may be paying for. Instead, click on the Customize link and: Configure Your Database You need to enter your SQL Azure database details here, so you’ll have to get the server name from the Azure Management Console. You don’t need to explicitly grant access to your Umbraco website for the database though. Click Continue and you’ll be offered a “starter” website to install: If you don’t know Umbraco at all (but you are familiar with ASP.NET MVC) then a starter website is worthwhile to see how it all hangs together. But after a while you’ll have a bunch of artifacts in your CMS that you don’t want and you’ll have to work out which you can safely delete. So I’d click “No thanks, I do not want to install a starter website” and give yourself a clean Umbraco install. When it completes, the installation will log you in to the welcome screen for managing Umbraco – which you can access from http://my-app-config.azurewebsites.net/umbraco: That’s It Easy. Umbraco is installed, using a dedicated SQL Azure instance that you can separately scale, sync and backup, and ready for your content. In the next post, we’ll define what our app config looks like, and publish some settings for the dev environment.

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• New Supply Chain, S&OP, & TPM Analyst Reports from Gartner, IDC Now Available

  - by Mike Liebson

  Check out these analyst reports Oracle has recently made available for customers and partners on Oracle.com: Gartner:  MarketScope for Stage 3 Sales and Operations Planning  -  Gartner lead supply chain planning analyst, Tim Payne, discusses the evolving definition of S&OP, the Gartner S&OP maturity model, and recommendations for selecting S&OP technology solutions. Gartner: Vendor Panorama for Trade Promotion Management in Consumer Goods  -  Consumer goods analyst, Dale Hagemeyer, presents an overview of the TPM market, followed by an analysis of vendor offerings. IDC:  Perspective: Oracle OpenWorld 2012 — Supply Chain as a Focus  -  Supply chain analyst, Simon Ellis, discusses supply chain highlights from the October OpenWorld conference. Value Chain Planning highlights include the VCP product roadmap and demand sensing presentations by Electronic Arts (Demantra) and Sony (Demand Signal Repository). For a complete set of analyst reports, visit here.

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• Revisiting ANTS Performance Profiler 7.4

  - by James Michael Hare

  Last year, I did a small review on the ANTS Performance Profiler 6.3, now that it’s a year later and a major version number higher, I thought I’d revisit the review and revise my last post. This post will take the same examples as the original post and update them to show what’s new in version 7.4 of the profiler. Background A performance profiler’s main job is to keep track of how much time is typically spent in each unit of code. This helps when we have a program that is not running at the performance we expect, and we want to know where the program is experiencing issues. There are many profilers out there of varying capabilities. Red Gate’s typically seem to be the very easy to “jump in” and get started with very little training required. So let’s dig into the Performance Profiler. I’ve constructed a very crude program with some obvious inefficiencies. It’s a simple program that generates random order numbers (or really could be any unique identifier), adds it to a list, sorts the list, then finds the max and min number in the list. Ignore the fact it’s very contrived and obviously inefficient, we just want to use it as an example to show off the tool: 1: // our test program 2: public static class Program 3: { 4: // the number of iterations to perform 5: private static int _iterations = 1000000; 6: 7: // The main method that controls it all 8: public static void Main() 9: { 10: var list = new List<string>(); 11: 12: for (int i = 0; i < _iterations; i++) 13: { 14: var x = GetNextId(); 15: 16: AddToList(list, x); 17: 18: var highLow = GetHighLow(list); 19: 20: if ((i % 1000) == 0) 21: { 22: Console.WriteLine("{0} - High: {1}, Low: {2}", i, highLow.Item1, highLow.Item2); 23: Console.Out.Flush(); 24: } 25: } 26: } 27: 28: // gets the next order id to process (random for us) 29: public static string GetNextId() 30: { 31: var random = new Random(); 32: var num = random.Next(1000000, 9999999); 33: return num.ToString(); 34: } 35: 36: // add it to our list - very inefficiently! 37: public static void AddToList(List<string> list, string item) 38: { 39: list.Add(item); 40: list.Sort(); 41: } 42: 43: // get high and low of order id range - very inefficiently! 44: public static Tuple<int,int> GetHighLow(List<string> list) 45: { 46: return Tuple.Create(list.Max(s => Convert.ToInt32(s)), list.Min(s => Convert.ToInt32(s))); 47: } 48: } So let’s run it through the profiler and see what happens! Visual Studio Integration First, let’s look at how the ANTS profilers integrate with Visual Studio’s menu system. Once you install the ANTS profilers, you will get an ANTS menu item with several options: Notice that you can either Profile Performance or Launch ANTS Performance Profiler. These sound similar but achieve two slightly different actions: Profile Performance: this immediately launches the profiler with all defaults selected to profile the active project in Visual Studio. Launch ANTS Performance Profiler: this launches the profiler much the same way as starting it from the Start Menu. The profiler will pre-populate the application and path information, but allow you to change the settings before beginning the profile run. So really, the main difference is that Profile Performance immediately begins profiling with the default selections, where Launch ANTS Performance Profiler allows you to change the defaults and attach to an already-running application. Let’s Fire it Up! So when you fire up ANTS either via Start Menu or Launch ANTS Performance Profiler menu in Visual Studio, you are presented with a very simple dialog to get you started: Notice you can choose from many different options for application type. You can profile executables, services, web applications, or just attach to a running process. In fact, in version 7.4 we see two new options added: ASP.NET Web Application (IIS Express) SharePoint web application (IIS) So this gives us an additional way to profile ASP.NET applications and the ability to profile SharePoint applications as well. You can also choose your level of detail in the Profiling Mode drop down. If you choose Line-Level and method-level timings detail, you will get a lot more detail on the method durations, but this will also slow down profiling somewhat. If you really need the profiler to be as unintrusive as possible, you can change it to Sample method-level timings. This is performing very light profiling, where basically the profiler collects timings of a method by examining the call-stack at given intervals. Which method you choose depends a lot on how much detail you need to find the issue and how sensitive your program issues are to timing. So for our example, let’s just go with the line and method timing detail. So, we check that all the options are correct (if you launch from VS2010, the executable and path are filled in already), and fire it up by clicking the [Start Profiling] button. Profiling the Application Once you start profiling the application, you will see a real-time graph of CPU usage that will indicate how much your application is using the CPU(s) on your system. During this time, you can select segments of the graph and bookmark them, giving them mnemonic names. This can be useful if you want to compare performance in one part of the run to another part of the run. Notice that once you select a block, it will give you the call tree breakdown for that selection only, and the relative performance of those calls. Once you feel you have collected enough information, you can click [Stop Profiling] to stop the application run and information collection and begin a more thorough analysis. Analyzing Method Timings So now that we’ve halted the run, we can look around the GUI and see what we can see. By default, the times are shown in terms of percentage of time of the total run of the application, though you can change it in the View menu item to milliseconds, ticks, or seconds as well. This won’t affect the percentages of methods, it only affects what units the times are shown. Notice also that the major hotspot seems to be in a method without source, ANTS Profiler will filter these out by default, but you can right-click on the line and remove the filter to see more detail. This proves especially handy when a bottleneck is due to a method in the BCL. So now that we’ve removed the filter, we see a bit more detail: In addition, ANTS Performance Profiler gives you the ability to decompile the methods without source so that you can dive even deeper, though typically this isn’t necessary for our purposes. When looking at timings, there are generally two types of timings for each method call: Time: This is the time spent ONLY in this method, not including calls this method makes to other methods. Time With Children: This is the total of time spent in both this method AND including calls this method makes to other methods. In other words, the Time tells you how much work is being done exclusively in this method, and the Time With Children tells you how much work is being done inclusively in this method and everything it calls. You can also choose to display the methods in a tree or in a grid. The tree view is the default and it shows the method calls arranged in terms of the tree representing all method calls and the parent method that called them, etc. This is useful for when you find a hot-spot method, you can see who is calling it to determine if the problem is the method itself, or if it is being called too many times. The grid method represents each method only once with its totals and is useful for quickly seeing what method is the trouble spot. In addition, you can choose to display Methods with source which are generally the methods you wrote (as opposed to native or BCL code), or Any Method which shows not only your methods, but also native calls, JIT overhead, synchronization waits, etc. So these are just two ways of viewing the same data, and you’re free to choose the organization that best suits what information you are after. Analyzing Method Source If we look at the timings above, we see that our AddToList() method (and in particular, it’s call to the List<T>.Sort() method in the BCL) is the hot-spot in this analysis. If ANTS sees a method that is consuming the most time, it will flag it as a hot-spot to help call out potential areas of concern. This doesn’t mean the other statistics aren’t meaningful, but that the hot-spot is most likely going to be your biggest bang-for-the-buck to concentrate on. So let’s select the AddToList() method, and see what it shows in the source window below: Notice the source breakout in the bottom pane when you select a method (from either tree or grid view). This shows you the timings in this method per line of code. This gives you a major indicator of where the trouble-spot in this method is. So in this case, we see that performing a Sort() on the List<T> after every Add() is killing our performance! Of course, this was a very contrived, duh moment, but you’d be surprised how many performance issues become duh moments. Note that this one line is taking up 86% of the execution time of this application! If we eliminate this bottleneck, we should see drastic improvement in the performance. So to fix this, if we still wanted to maintain the List<T> we’d have many options, including: delay Sort() until after all Add() methods, using a SortedSet, SortedList, or SortedDictionary depending on which is most appropriate, or forgoing the sorting all together and using a Dictionary. Rinse, Repeat! So let’s just change all instances of List<string> to SortedSet<string> and run this again through the profiler: Now we see the AddToList() method is no longer our hot-spot, but now the Max() and Min() calls are! This is good because we’ve eliminated one hot-spot and now we can try to correct this one as well. As before, we can then optimize this part of the code (possibly by taking advantage of the fact the list is now sorted and returning the first and last elements). We can then rinse and repeat this process until we have eliminated as many bottlenecks as possible. Calls by Web Request Another feature that was added recently is the ability to view .NET methods grouped by the HTTP requests that caused them to run. This can be helpful in determining which pages, web services, etc. are causing hot spots in your web applications. Summary If you like the other ANTS tools, you’ll like the ANTS Performance Profiler as well. It is extremely easy to use with very little product knowledge required to get up and running. There are profilers built into the higher product lines of Visual Studio, of course, which are also powerful and easy to use. But for quickly jumping in and finding hot spots rapidly, Red Gate’s Performance Profiler 7.4 is an excellent choice. Technorati Tags: Influencers,ANTS,Performance Profiler,Profiler

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• Oracle Linux at Oracle Openworld 2011

  - by Zeynep Koch

  In the Oracle Linux track, you'll learn how organizations of all sizes, in all industries, worldwide, are realizing the true benefits of complete and integrated solutions with Oracle Linux and Oracle's world-class Linux support program. Find out what Oracle is doing to simplify the development, deployment, and management of Linux solutions via significant testing initiatives including the Oracle Validated Configurations program. Also discover how Oracle is driving the enterprise Linux technology roadmap with new features and enhancements, making Linux a faster, better operating system for all. Meet Oracle's Linux engineers, experts, customers, and partners, and get answers to all your Linux questions. Here are the Linux sessions and demos that you don't want to miss. · Oracle Linux Strategy and Roadmap · New Features in Oracle Linux · End-to-End Data Integrity Solution for Linux · Debugging and Configuration Best Practices for Oracle Linux · Demos · Hands-on-Labs Register by July 29 and get a $500 discount.http://bit.ly/kSjDMD

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