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• Postgresql Output column from another table

  - by muffin

  i'm using Postgresql, my question is specifically about querying from a table that's in another table and i'm really having trouble with this one. In fact, i'm absolutely mentally blocked. I'll try to define the relations of the tables as much as I can. I have a table entry which is like this: Each of the entries has a group_id; when they are 'advanced' to the next stage, the old entries are marked is_active = false, and a new assignment is done, so C & D are advanced stages of A & B. I have another table (which acts as a record keeper) , in which the storage_log_id refers to, this is the storage_log table : But then I have another table, to really find out where the entries are actually stored - storage table : To define my problem properly. Each entry has a storage_log_id (but some doesn't have yet), and a storage_log has a storage_id to refer to the actual table and find the storage label. The sql query i'm trying to do should output this one: Where The actual storage label is shown instead of the log id. This is so far what i've done: select e.id, e.group_id, e.name, e.stage, s.label from operational.entry e, operational.storage_log sl, operational.storage s where e.storage_log_id = sl.id and sl.storage_id = s.id But this just returns 3 rows, showing only the ones that have the seed_storage_log_id set; I should be able to see even those without logs, and especially the active ones. adding e.is_active = true to the condition makes the results empty. So, yeah i'm stuck. Need help, Thanks guys!

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• How can I exclude LEFT JOINed tables from TOP in SQL Server?

  - by Kalessin

  Let's say I have two tables of books and two tables of their corresponding editions. I have a query as follows: SELECT TOP 10 * FROM (SELECT hbID, hbTitle, hbPublisherID, hbPublishDate, hbedID, hbedDate FROM hardback LEFT JOIN hardbackEdition on hbID = hbedID UNION SELECT pbID, pbTitle, pbPublisher, pbPublishDate, pbedID, pbedDate FROM paperback Left JOIN paperbackEdition on pbID = pbedID ) books WHERE hbPublisherID = 7 ORDER BY hbPublishDate DESC If there are 5 editions of the first two hardback and/or paperback books, this query only returns two books. However, I want the TOP 10 to apply only to the number of actual book records returned. Is there a way I can select 10 actual books, and still get all of their associated edition records? In case it's relevant, I do not have database permissions to CREATE and DROP temporary tables. Thanks for reading! Update To clarify: The paperback table has an associated table of paperback editions. The hardback table has an associated table of hardback editions. The hardback and paperback tables are not related to each other except to the user who will (hopefully!) see them displayed together.

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• Turn based synchronization between threads

  - by Amarus

  I'm trying to find a way to synchronize multiple threads having the following conditions: * There are two types of threads: 1. A single "cyclic" thread executing an infinite loop to do cyclic calculations 2. Multiple short-lived threads not started by the main thread * The cyclic thread has a sleep duration between each cycle/loop iteration * The other threads are allowed execute during the inter-cycle sleep of the cyclic thread: - Any other thread that attempts to execute during an active cycle should be blocked - The cyclic thread will wait until all other threads that are already executing to be finished Here's a basic example of what I was thinking of doing: // Somewhere in the code: ManualResetEvent manualResetEvent = new ManualResetEvent(true); // Allow Externally call CountdownEvent countdownEvent = new CountdownEvent(1); // Can't AddCount a CountdownEvent with CurrentCount = 0 void ExternallyCalled() { manualResetEvent.WaitOne(); // Wait until CyclicCalculations is having its beauty sleep countdownEvent.AddCount(); // Notify CyclicCalculations that it should wait for this method call to finish before starting the next cycle Thread.Sleep(1000); // TODO: Replace with actual method logic countdownEvent.Signal(); // Notify CyclicCalculations that this call is finished } void CyclicCalculations() { while (!stopCyclicCalculations) { manualResetEvent.Reset(); // Block all incoming calls to ExternallyCalled from this point forward countdownEvent.Signal(); // Dirty workaround for the issue with AddCount and CurrentCount = 0 countdownEvent.Wait(); // Wait until all of the already executing calls to ExternallyCalled are finished countdownEvent.Reset(); // Reset the CountdownEvent for next cycle. Thread.Sleep(2000); // TODO: Replace with actual method logic manualResetEvent.Set(); // Unblock all threads executing ExternallyCalled Thread.Sleep(1000); // Inter-cycles delay } } Obviously, this doesn't work. There's no guarantee that there won't be any threads executing ExternallyCalled that are in between manualResetEvent.WaitOne(); and countdownEvent.AddCount(); at the time the main thread gets released by the CountdownEvent. I can't figure out a simple way of doing what I'm after, and almost everything that I've found after a lengthy search is related to producer/consumer synchronization which I can't apply here.

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• How important is it that models be consistent across project components?

  - by RonLugge

  I have a project with two components, a server-side component and a client-side component. For various reasons, the client-side device doesn't carry a fully copy of the database around. How important is it that my models have a 1:1 correlation between the two sides? And, to extend the question to my bigger concern, are there any time-bombs I'm going to run into down the line if they don't? I'm not talking about having different information on each side, but rather the way the information is encapsulated will vary. (Obviously, storage mechanisms will also vary) The server side will store each user, each review, each 'item' with seperate tables, and create links between them to gather data as necessary. The client side shouldn't have a complete user database, however, so rather than link against the user for gathering things like 'name', I'd store that on the review. In other words... --- Server Side --- Item: +id //Store stuff about the item User: +id +Name -Password Review: +id +itemId +rating +text +userId --- Device Side --- Item: +id +AverageRating Review: +id +rating +text +userId +name User: +id +Name //Stuff The basic idea is that certain 'critical' information gets moved one level 'up'. A user gets the list of 'items' relevant to their query, with certain review-orientation moved up (i. e. average rating). If they want more info, they query the detail view for the item, and the actual reviews get queried and added to the dataset (and displayed). If they query the actual review, the review gets queried and they pick up some additional user info along the way (maybe; I'm not sure if the user would have any use for any of the additional user information). My basic concern is that I don't wan't to glut the user's bandwidth or local storage with a huge variety of information that they just don't need, even if proper database normalizations suggests that information REALLY should be stored at a 'lower' level. I've phrased this as a fairly low-level conceptual issue because that's the level I'm trying to think / worry over, but if it matters I'm creating a PHP / MySQL server that provides data for a iOS / CoreData client.

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• C++ const-reference semantics?

  - by Kristoffer

  Consider the sample application below. It demonstrates what I would call a flawed class design. #include <iostream> using namespace std; struct B { B() : m_value(1) {} long m_value; }; struct A { const B& GetB() const { return m_B; } void Foo(const B &b) { // assert(this != &b); m_B.m_value += b.m_value; m_B.m_value += b.m_value; } protected: B m_B; }; int main(int argc, char* argv[]) { A a; cout << "Original value: " << a.GetB().m_value << endl; cout << "Expected value: 3" << endl; a.Foo(a.GetB()); cout << "Actual value: " << a.GetB().m_value << endl; return 0; } Output: Original value: 1 Expected value: 3 Actual value: 4 Obviously, the programmer is fooled by the constness of b. By mistake b points to this, which yields the undesired behavior. My question: What const-rules should you follow when designing getters/setters? My suggestion: Never return a reference to a member variable if it can be set by reference through a member function. Hence, either return by value or pass parameters by value. (Modern compilers will optimize away the extra copy anyway.)

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• Disable a form and all contained elements until an ajax query completes (or another solution to prev

  - by Max Williams

  I have a search form with inputs and selects, and when any input/select is changed i run some js and then make an ajax query with jquery. I want to stop the user from making further changes to the form while the request is in progress, as at the moment they can initiate several remote searches at once, effectively causing a race between the different searches. It seems like the best solution to this is to prevent the user from interacting with the form while waiting for the request to come back. At the moment i'm doing this in the dumbest way possible by hiding the form before making the ajax query and then showing it again on success/error. This solves the problem but looks horrible and isn't really acceptable. Is there another, better way to prevent interaction with the form? To make things more complicated, to allow nice-looking selects, the user actually interacts with spans which have js hooked up to them to tie them to the actual, hidden, selects. So, even though the spans aren't inputs, they are contained in the form and represent the actual interactive elements of the form. Grateful for any advice - max. Here's what i'm doing now: function submitQuestionSearchForm(){ //bunch of irrelevant stuff var questionSearchForm = jQuery("#searchForm"); questionSearchForm.addClass("searching"); jQuery.ajax({ async: true, data: jQuery.param(questionSearchForm.serializeArray()), dataType: 'script', type: 'get', url: "/questions", success: function(msg){ //more irrelevant stuff questionSearchForm.removeClass("searching"); }, error: function(msg){ questionSearchForm.removeClass("searching"); } }); return true; }

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• Hive performance increase

  - by Sagar Nikam

  I am dealing with a database (2.5 GB) having some tables only 40 row to some having 9 million rows data. when I am doing any query for large table it takes more time. I want results in less time small query on table which have 90 rows only-- hive> select count(*) from cidade; Time taken: 50.172 seconds hdfs-site.xml <configuration> <property> <name>dfs.replication</name> <value>3</value> <description>Default block replication. The actual number of replications can be specified when the file is created. The default is used if replication is not specified in create time. </description> </property> <property> <name>dfs.block.size</name> <value>131072</value> <description>Default block replication. The actual number of replications can be specified when the file is created. The default is used if replication is not specified in create time. </description> </property> </configuration> does these setting affects performance of hive? dfs.replication=3 dfs.block.size=131072 can i set it from hive prompt as hive>set dfs.replication=5 Is this value remains for a perticular session only ? or Is it better to change it in .xml file ?

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• C non-trivial constants

  - by user525869

  I want to make several constants in C with #define to speed up computation. Two of them are not simply trivial numbers, where one is a right shift, the other is a power. math.h in C gives the function pow() for doubles, whereas I need powers for integers, so I wrote my own function, ipow, so I wouldn't need to be casting everytime. My question is this: One of the #define constants I want to make is a power, say ipow(M, T), where M and T were also #define constants. ipow is a function in the actual code, so this actually seems to slows things down when I run the code (is it running ipow everytime the constant is mentioned?). However, when I ues the built in pow function and just do (int)pow(M,T), the code is sped up. I'm confused as to why this is, since the ipow and pow functions are just as fast. On a more general note, can I define constants using #define using functions inside the actual code? The above example has me confused on whether this speeds things up or actually slows things down.

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• Fake ISAPI Handler to serve static files with extention that are rewritted by url rewriter

  - by developerit

  Introduction I often map html extention to the asp.net dll in order to use url rewritter with .html extentions. Recently, in the new version of www.nouvelair.ca, we renamed all urls to end with .html. This works great, but failed when we used FCK Editor. Static html files would not get serve because we mapped the html extension to the .NET Framework. We can we do to to use .html extension with our rewritter but still want to use IIS behavior with static html files. Analysis I thought that this could be resolve with a simple HTTP handler. We would map urls of static files in our rewriter to this handler that would read the static file and serve it, just as IIS would do. Implementation This is how I coded the class. Note that this may not be bullet proof. I only tested it once and I am sure that the logic behind IIS is more complicated that this. If you find errors or think of possible improvements, let me know. Imports System.Web Imports System.Web.Services ' Author: Nicolas Brassard ' For: Solutions Nitriques inc. http://www.nitriques.com ' Date Created: April 18, 2009 ' Last Modified: April 18, 2009 ' License: CPOL (http://www.codeproject.com/info/cpol10.aspx) ' Files: ISAPIDotNetHandler.ashx ' ISAPIDotNetHandler.ashx.vb ' Class: ISAPIDotNetHandler ' Description: Fake ISAPI handler to serve static files. ' Usefull when you want to serve static file that has a rewrited extention. ' Example: It often map html extention to the asp.net dll in order to use url rewritter with .html. ' If you want to still serve static html file, add a rewritter rule to redirect html files to this handler Public Class ISAPIDotNetHandler Implements System.Web.IHttpHandler Sub ProcessRequest(ByVal context As HttpContext) Implements IHttpHandler.ProcessRequest ' Since we are doing the job IIS normally does with html files, ' we set the content type to match html. ' You may want to customize this with your own logic, if you want to serve ' txt or xml or any other text file context.Response.ContentType = "text/html" ' We begin a try here. Any error that occurs will result in a 404 Page Not Found error. ' We replicate the behavior of IIS when it doesn't find the correspoding file. Try ' Declare a local variable containing the value of the query string Dim uri As String = context.Request("fileUri") ' If the value in the query string is null, ' throw an error to generate a 404 If String.IsNullOrEmpty(uri) Then Throw New ApplicationException("No fileUri") End If ' If the value in the query string doesn't end with .html, then block the acces ' This is a HUGE security hole since it could permit full read access to .aspx, .config, etc. If Not uri.ToLower.EndsWith(".html") Then ' throw an error to generate a 404 Throw New ApplicationException("Extention not allowed") End If ' Map the file on the server. ' If the file doesn't exists on the server, it will throw an exception and generate a 404. Dim fullPath As String = context.Server.MapPath(uri) ' Read the actual file Dim stream As IO.StreamReader = FileIO.FileSystem.OpenTextFileReader(fullPath) ' Write the file into the response context.Response.Output.Write(stream.ReadToEnd) ' Close and Dipose the stream stream.Close() stream.Dispose() stream = Nothing Catch ex As Exception ' Set the Status Code of the response context.Response.StatusCode = 404 'Page not found ' For testing and bebugging only ! This may cause a security leak ' context.Response.Output.Write(ex.Message) Finally ' In all cases, flush and end the response context.Response.Flush() context.Response.End() End Try End Sub ' Automaticly generated by Visual Studio ReadOnly Property IsReusable() As Boolean Implements IHttpHandler.IsReusable Get Return False End Get End Property End Class Conclusion As you see, with our static files map to this handler using query string (ex.: /ISAPIDotNetHandler.ashx?fileUri=index.html) you will have the same behavior as if you ask for the uri /index.html. Finally, test this only in IIS with the html extension map to aspnet_isapi.dll. Url rewritting will work in Casini (Internal Web Server shipped with Visual Studio) but it’s not the same as with IIS since EVERY request is handle by .NET. Versions First release

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• Using JSON.NET for dynamic JSON parsing

  - by Rick Strahl

  With the release of ASP.NET Web API as part of .NET 4.5 and MVC 4.0, JSON.NET has effectively pushed out the .NET native serializers to become the default serializer for Web API. JSON.NET is vastly more flexible than the built in DataContractJsonSerializer or the older JavaScript serializer. The DataContractSerializer in particular has been very problematic in the past because it can't deal with untyped objects for serialization - like values of type object, or anonymous types which are quite common these days. The JavaScript Serializer that came before it actually does support non-typed objects for serialization but it can't do anything with untyped data coming in from JavaScript and it's overall model of extensibility was pretty limited (JavaScript Serializer is what MVC uses for JSON responses). JSON.NET provides a robust JSON serializer that has both high level and low level components, supports binary JSON, JSON contracts, Xml to JSON conversion, LINQ to JSON and many, many more features than either of the built in serializers. ASP.NET Web API now uses JSON.NET as its default serializer and is now pulled in as a NuGet dependency into Web API projects, which is great. Dynamic JSON Parsing One of the features that I think is getting ever more important is the ability to serialize and deserialize arbitrary JSON content dynamically - that is without mapping the JSON captured directly into a .NET type as DataContractSerializer or the JavaScript Serializers do. Sometimes it isn't possible to map types due to the differences in languages (think collections, dictionaries etc), and other times you simply don't have the structures in place or don't want to create them to actually import the data. If this topic sounds familiar - you're right! I wrote about dynamic JSON parsing a few months back before JSON.NET was added to Web API and when Web API and the System.Net HttpClient libraries included the System.Json classes like JsonObject and JsonArray. With the inclusion of JSON.NET in Web API these classes are now obsolete and didn't ship with Web API or the client libraries. I re-linked my original post to this one. In this post I'll discus JToken, JObject and JArray which are the dynamic JSON objects that make it very easy to create and retrieve JSON content on the fly without underlying types. Why Dynamic JSON? So, why Dynamic JSON parsing rather than strongly typed parsing? Since applications are interacting more and more with third party services it becomes ever more important to have easy access to those services with easy JSON parsing. Sometimes it just makes lot of sense to pull just a small amount of data out of large JSON document received from a service, because the third party service isn't directly related to your application's logic most of the time - and it makes little sense to map the entire service structure in your application. For example, recently I worked with the Google Maps Places API to return information about businesses close to me (or rather the app's) location. The Google API returns a ton of information that my application had no interest in - all I needed was few values out of the data. Dynamic JSON parsing makes it possible to map this data, without having to map the entire API to a C# data structure. Instead I could pull out the three or four values I needed from the API and directly store it on my business entities that needed to receive the data - no need to map the entire Maps API structure. Getting JSON.NET The easiest way to use JSON.NET is to grab it via NuGet and add it as a reference to your project. You can add it to your project with: PM> Install-Package Newtonsoft.Json From the Package Manager Console or by using Manage NuGet Packages in your project References. As mentioned if you're using ASP.NET Web API or MVC 4 JSON.NET will be automatically added to your project. Alternately you can also go to the CodePlex site and download the latest version including source code: http://json.codeplex.com/ Creating JSON on the fly with JObject and JArray Let's start with creating some JSON on the fly. It's super easy to create a dynamic object structure with any of the JToken derived JSON.NET objects. The most common JToken derived classes you are likely to use are JObject and JArray. JToken implements IDynamicMetaProvider and so uses the dynamic  keyword extensively to make it intuitive to create object structures and turn them into JSON via dynamic object syntax. Here's an example of creating a music album structure with child songs using JObject for the base object and songs and JArray for the actual collection of songs:[TestMethod] public void JObjectOutputTest() { // strong typed instance var jsonObject = new JObject(); // you can explicitly add values here using class interface jsonObject.Add("Entered", DateTime.Now); // or cast to dynamic to dynamically add/read properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; album.Artist = "AC/DC"; album.YearReleased = 1976; album.Songs = new JArray() as dynamic; dynamic song = new JObject(); song.SongName = "Dirty Deeds Done Dirt Cheap"; song.SongLength = "4:11"; album.Songs.Add(song); song = new JObject(); song.SongName = "Love at First Feel"; song.SongLength = "3:10"; album.Songs.Add(song); Console.WriteLine(album.ToString()); } This produces a complete JSON structure: { "Entered": "2012-08-18T13:26:37.7137482-10:00", "AlbumName": "Dirty Deeds Done Dirt Cheap", "Artist": "AC/DC", "YearReleased": 1976, "Songs": [ { "SongName": "Dirty Deeds Done Dirt Cheap", "SongLength": "4:11" }, { "SongName": "Love at First Feel", "SongLength": "3:10" } ] } Notice that JSON.NET does a nice job formatting the JSON, so it's easy to read and paste into blog posts :-). JSON.NET includes a bunch of configuration options that control how JSON is generated. Typically the defaults are just fine, but you can override with the JsonSettings object for most operations. The important thing about this code is that there's no explicit type used for holding the values to serialize to JSON. Rather the JSON.NET objects are the containers that receive the data as I build up my JSON structure dynamically, simply by adding properties. This means this code can be entirely driven at runtime without compile time restraints of structure for the JSON output. Here I use JObject to create a album 'object' and immediately cast it to dynamic. JObject() is kind of similar in behavior to ExpandoObject in that it allows you to add properties by simply assigning to them. Internally, JObject values are stored in pseudo collections of key value pairs that are exposed as properties through the IDynamicMetaObject interface exposed in JSON.NET's JToken base class. For objects the syntax is very clean - you add simple typed values as properties. For objects and arrays you have to explicitly create new JObject or JArray, cast them to dynamic and then add properties and items to them. Always remember though these values are dynamic - which means no Intellisense and no compiler type checking. It's up to you to ensure that the names and values you create are accessed consistently and without typos in your code. Note that you can also access the JObject instance directly (not as dynamic) and get access to the underlying JObject type. This means you can assign properties by string, which can be useful for fully data driven JSON generation from other structures. Below you can see both styles of access next to each other:// strong type instance var jsonObject = new JObject(); // you can explicitly add values here jsonObject.Add("Entered", DateTime.Now); // expando style instance you can just 'use' properties dynamic album = jsonObject; album.AlbumName = "Dirty Deeds Done Dirt Cheap"; JContainer (the base class for JObject and JArray) is a collection so you can also iterate over the properties at runtime easily:foreach (var item in jsonObject) { Console.WriteLine(item.Key + " " + item.Value.ToString()); } The functionality of the JSON objects are very similar to .NET's ExpandObject and if you used it before, you're already familiar with how the dynamic interfaces to the JSON objects works. Importing JSON with JObject.Parse() and JArray.Parse() The JValue structure supports importing JSON via the Parse() and Load() methods which can read JSON data from a string or various streams respectively. Essentially JValue includes the core JSON parsing to turn a JSON string into a collection of JsonValue objects that can be then referenced using familiar dynamic object syntax. Here's a simple example:public void JValueParsingTest() { var jsonString = @"{""Name"":""Rick"",""Company"":""West Wind"", ""Entered"":""2012-03-16T00:03:33.245-10:00""}"; dynamic json = JValue.Parse(jsonString); // values require casting string name = json.Name; string company = json.Company; DateTime entered = json.Entered; Assert.AreEqual(name, "Rick"); Assert.AreEqual(company, "West Wind"); } The JSON string represents an object with three properties which is parsed into a JObject class and cast to dynamic. Once cast to dynamic I can then go ahead and access the object using familiar object syntax. Note that the actual values - json.Name, json.Company, json.Entered - are actually of type JToken and I have to cast them to their appropriate types first before I can do type comparisons as in the Asserts at the end of the test method. This is required because of the way that dynamic types work which can't determine the type based on the method signature of the Assert.AreEqual(object,object) method. I have to either assign the dynamic value to a variable as I did above, or explicitly cast ( (string) json.Name) in the actual method call. The JSON structure can be much more complex than this simple example. Here's another example of an array of albums serialized to JSON and then parsed through with JsonValue():[TestMethod] public void JsonArrayParsingTest() { var jsonString = @"[ { ""Id"": ""b3ec4e5c"", ""AlbumName"": ""Dirty Deeds Done Dirt Cheap"", ""Artist"": ""AC/DC"", ""YearReleased"": 1976, ""Entered"": ""2012-03-16T00:13:12.2810521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/61kTaH-uZBL._AA115_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/gp/product/…ASIN=B00008BXJ4"", ""Songs"": [ { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Dirty Deeds Done Dirt Cheap"", ""SongLength"": ""4:11"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Love at First Feel"", ""SongLength"": ""3:10"" }, { ""AlbumId"": ""b3ec4e5c"", ""SongName"": ""Big Balls"", ""SongLength"": ""2:38"" } ] }, { ""Id"": ""7b919432"", ""AlbumName"": ""End of the Silence"", ""Artist"": ""Henry Rollins Band"", ""YearReleased"": 1992, ""Entered"": ""2012-03-16T00:13:12.2800521-10:00"", ""AlbumImageUrl"": ""http://ecx.images-amazon.com/images/I/51FO3rb1tuL._SL160_AA160_.jpg"", ""AmazonUrl"": ""http://www.amazon.com/End-Silence-Rollins-Band/dp/B0000040OX/ref=sr_1_5?ie=UTF8&qid=1302232195&sr=8-5"", ""Songs"": [ { ""AlbumId"": ""7b919432"", ""SongName"": ""Low Self Opinion"", ""SongLength"": ""5:24"" }, { ""AlbumId"": ""7b919432"", ""SongName"": ""Grip"", ""SongLength"": ""4:51"" } ] } ]"; JArray jsonVal = JArray.Parse(jsonString) as JArray; dynamic albums = jsonVal; foreach (dynamic album in albums) { Console.WriteLine(album.AlbumName + " (" + album.YearReleased.ToString() + ")"); foreach (dynamic song in album.Songs) { Console.WriteLine("\t" + song.SongName); } } Console.WriteLine(albums[0].AlbumName); Console.WriteLine(albums[0].Songs[1].SongName); } JObject and JArray in ASP.NET Web API Of course these types also work in ASP.NET Web API controller methods. If you want you can accept parameters using these object or return them back to the server. The following contrived example receives dynamic JSON input, and then creates a new dynamic JSON object and returns it based on data from the first:[HttpPost] public JObject PostAlbumJObject(JObject jAlbum) { // dynamic input from inbound JSON dynamic album = jAlbum; // create a new JSON object to write out dynamic newAlbum = new JObject(); // Create properties on the new instance // with values from the first newAlbum.AlbumName = album.AlbumName + " New"; newAlbum.NewProperty = "something new"; newAlbum.Songs = new JArray(); foreach (dynamic song in album.Songs) { song.SongName = song.SongName + " New"; newAlbum.Songs.Add(song); } return newAlbum; } The raw POST request to the server looks something like this: POST http://localhost/aspnetwebapi/samples/PostAlbumJObject HTTP/1.1User-Agent: FiddlerContent-type: application/jsonHost: localhostContent-Length: 88 {AlbumName: "Dirty Deeds",Songs:[ { SongName: "Problem Child"},{ SongName: "Squealer"}]} and the output that comes back looks like this: {  "AlbumName": "Dirty Deeds New",  "NewProperty": "something new",  "Songs": [    {      "SongName": "Problem Child New"    },    {      "SongName": "Squealer New"    }  ]} The original values are echoed back with something extra appended to demonstrate that we're working with a new object. When you receive or return a JObject, JValue, JToken or JArray instance in a Web API method, Web API ignores normal content negotiation and assumes your content is going to be received and returned as JSON, so effectively the parameter and result type explicitly determines the input and output format which is nice. Dynamic to Strong Type Mapping You can also map JObject and JArray instances to a strongly typed object, so you can mix dynamic and static typing in the same piece of code. Using the 2 Album jsonString shown earlier, the code below takes an array of albums and picks out only a single album and casts that album to a static Album instance.[TestMethod] public void JsonParseToStrongTypeTest() { JArray albums = JArray.Parse(jsonString) as JArray; // pick out one album JObject jalbum = albums[0] as JObject; // Copy to a static Album instance Album album = jalbum.ToObject<Album>(); Assert.IsNotNull(album); Assert.AreEqual(album.AlbumName,jalbum.Value<string>("AlbumName")); Assert.IsTrue(album.Songs.Count > 0); } This is pretty damn useful for the scenario I mentioned earlier - you can read a large chunk of JSON and dynamically walk the property hierarchy down to the item you want to access, and then either access the specific item dynamically (as shown earlier) or map a part of the JSON to a strongly typed object. That's very powerful if you think about it - it leaves you in total control to decide what's dynamic and what's static. Strongly typed JSON Parsing With all this talk of dynamic let's not forget that JSON.NET of course also does strongly typed serialization which is drop dead easy. Here's a simple example on how to serialize and deserialize an object with JSON.NET:[TestMethod] public void StronglyTypedSerializationTest() { // Demonstrate deserialization from a raw string var album = new Album() { AlbumName = "Dirty Deeds Done Dirt Cheap", Artist = "AC/DC", Entered = DateTime.Now, YearReleased = 1976, Songs = new List<Song>() { new Song() { SongName = "Dirty Deeds Done Dirt Cheap", SongLength = "4:11" }, new Song() { SongName = "Love at First Feel", SongLength = "3:10" } } }; // serialize to string string json2 = JsonConvert.SerializeObject(album,Formatting.Indented); Console.WriteLine(json2); // make sure we can serialize back var album2 = JsonConvert.DeserializeObject<Album>(json2); Assert.IsNotNull(album2); Assert.IsTrue(album2.AlbumName == "Dirty Deeds Done Dirt Cheap"); Assert.IsTrue(album2.Songs.Count == 2); } JsonConvert is a high level static class that wraps lower level functionality, but you can also use the JsonSerializer class, which allows you to serialize/parse to and from streams. It's a little more work, but gives you a bit more control. The functionality available is easy to discover with Intellisense, and that's good because there's not a lot in the way of documentation that's actually useful. Summary JSON.NET is a pretty complete JSON implementation with lots of different choices for JSON parsing from dynamic parsing to static serialization, to complex querying of JSON objects using LINQ. It's good to see this open source library getting integrated into .NET, and pushing out the old and tired stock .NET parsers so that we finally have a bit more flexibility - and extensibility - in our JSON parsing. Good to go! Resources Sample Test Project http://json.codeplex.com/© Rick Strahl, West Wind Technologies, 2005-2012Posted in .NET  Web Api  AJAX   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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• HTG Reviews the CODE Keyboard: Old School Construction Meets Modern Amenities

  - by Jason Fitzpatrick

  There’s nothing quite as satisfying as the smooth and crisp action of a well built keyboard. If you’re tired of  mushy keys and cheap feeling keyboards, a well-constructed mechanical keyboard is a welcome respite from the $10 keyboard that came with your computer. Read on as we put the CODE mechanical keyboard through the paces. What is the CODE Keyboard? The CODE keyboard is a collaboration between manufacturer WASD Keyboards and Jeff Atwood of Coding Horror (the guy behind the Stack Exchange network and Discourse forum software). Atwood’s focus was incorporating the best of traditional mechanical keyboards and the best of modern keyboard usability improvements. In his own words: The world is awash in terrible, crappy, no name how-cheap-can-we-make-it keyboards. There are a few dozen better mechanical keyboard options out there. I’ve owned and used at least six different expensive mechanical keyboards, but I wasn’t satisfied with any of them, either: they didn’t have backlighting, were ugly, had terrible design, or were missing basic functions like media keys. That’s why I originally contacted Weyman Kwong of WASD Keyboards way back in early 2012. I told him that the state of keyboards was unacceptable to me as a geek, and I proposed a partnership wherein I was willing to work with him to do whatever it takes to produce a truly great mechanical keyboard. Even the ardent skeptic who questions whether Atwood has indeed created a truly great mechanical keyboard certainly can’t argue with the position he starts from: there are so many agonizingly crappy keyboards out there. Even worse, in our opinion, is that unless you’re a typist of a certain vintage there’s a good chance you’ve never actually typed on a really nice keyboard. Those that didn’t start using computers until the mid-to-late 1990s most likely have always typed on modern mushy-key keyboards and never known the joy of typing on a really responsive and crisp mechanical keyboard. Is our preference for and love of mechanical keyboards shining through here? Good. We’re not even going to try and hide it. So where does the CODE keyboard stack up in pantheon of keyboards? Read on as we walk you through the simple setup and our experience using the CODE. Setting Up the CODE Keyboard Although the setup of the CODE keyboard is essentially plug and play, there are two distinct setup steps that you likely haven’t had to perform on a previous keyboard. Both highlight the degree of care put into the keyboard and the amount of customization available. Inside the box you’ll find the keyboard, a micro USB cable, a USB-to-PS2 adapter, and a tool which you may be unfamiliar with: a key puller. We’ll return to the key puller in a moment. Unlike the majority of keyboards on the market, the cord isn’t permanently affixed to the keyboard. What does this mean for you? Aside from the obvious need to plug it in yourself, it makes it dead simple to repair your own keyboard cord if it gets attacked by a pet, mangled in a mechanism on your desk, or otherwise damaged. It also makes it easy to take advantage of the cable routing channels in on the underside of the keyboard to  route your cable exactly where you want it. While we’re staring at the underside of the keyboard, check out those beefy rubber feet. By peripherals standards they’re huge (and there is six instead of the usual four). Once you plunk the keyboard down where you want it, it might as well be glued down the rubber feet work so well. After you’ve secured the cable and adjusted it to your liking, there is one more task  before plug the keyboard into the computer. On the bottom left-hand side of the keyboard, you’ll find a small recess in the plastic with some dip switches inside: The dip switches are there to switch hardware functions for various operating systems, keyboard layouts, and to enable/disable function keys. By toggling the dip switches you can change the keyboard from QWERTY mode to Dvorak mode and Colemak mode, the two most popular alternative keyboard configurations. You can also use the switches to enable Mac-functionality (for Command/Option keys). One of our favorite little toggles is the SW3 dip switch: you can disable the Caps Lock key; goodbye accidentally pressing Caps when you mean to press Shift. You can review the entire dip switch configuration chart here. The quick-start for Windows users is simple: double check that all the switches are in the off position (as seen in the photo above) and then simply toggle SW6 on to enable the media and backlighting function keys (this turns the menu key on the keyboard into a function key as typically found on laptop keyboards). After adjusting the dip switches to your liking, plug the keyboard into an open USB port on your computer (or into your PS/2 port using the included adapter). Design, Layout, and Backlighting The CODE keyboard comes in two flavors, a traditional 87-key layout (no number pad) and a traditional 104-key layout (number pad on the right hand side). We identify the layout as traditional because, despite some modern trapping and sneaky shortcuts, the actual form factor of the keyboard from the shape of the keys to the spacing and position is as classic as it comes. You won’t have to learn a new keyboard layout and spend weeks conditioning yourself to a smaller than normal backspace key or a PgUp/PgDn pair in an unconventional location. Just because the keyboard is very conventional in layout, however, doesn’t mean you’ll be missing modern amenities like media-control keys. The following additional functions are hidden in the F11, F12, Pause button, and the 2×6 grid formed by the Insert and Delete rows: keyboard illumination brightness, keyboard illumination on/off, mute, and then the typical play/pause, forward/backward, stop, and volume +/- in Insert and Delete rows, respectively. While we weren’t sure what we’d think of the function-key system at first (especially after retiring a Microsoft Sidewinder keyboard with a huge and easily accessible volume knob on it), it took less than a day for us to adapt to using the Fn key, located next to the right Ctrl key, to adjust our media playback on the fly. Keyboard backlighting is a largely hit-or-miss undertaking but the CODE keyboard nails it. Not only does it have pleasant and easily adjustable through-the-keys lighting but the key switches the keys themselves are attached to are mounted to a steel plate with white paint. Enough of the light reflects off the interior cavity of the keys and then diffuses across the white plate to provide nice even illumination in between the keys. Highlighting the steel plate beneath the keys brings us to the actual construction of the keyboard. It’s rock solid. The 87-key model, the one we tested, is 2.0 pounds. The 104-key is nearly a half pound heavier at 2.42 pounds. Between the steel plate, the extra-thick PCB board beneath the steel plate, and the thick ABS plastic housing, the keyboard has very solid feel to it. Combine that heft with the previously mentioned thick rubber feet and you have a tank-like keyboard that won’t budge a millimeter during normal use. Examining The Keys This is the section of the review the hardcore typists and keyboard ninjas have been waiting for. We’ve looked at the layout of the keyboard, we’ve looked at the general construction of it, but what about the actual keys? There are a wide variety of keyboard construction techniques but the vast majority of modern keyboards use a rubber-dome construction. The key is floated in a plastic frame over a rubber membrane that has a little rubber dome for each key. The press of the physical key compresses the rubber dome downwards and a little bit of conductive material on the inside of the dome’s apex connects with the circuit board. Despite the near ubiquity of the design, many people dislike it. The principal complaint is that dome keyboards require a complete compression to register a keystroke; keyboard designers and enthusiasts refer to this as “bottoming out”. In other words, the register the “b” key, you need to completely press that key down. As such it slows you down and requires additional pressure and movement that, over the course of tens of thousands of keystrokes, adds up to a whole lot of wasted time and fatigue. The CODE keyboard features key switches manufactured by Cherry, a company that has manufactured key switches since the 1960s. Specifically the CODE features Cherry MX Clear switches. These switches feature the same classic design of the other Cherry switches (such as the MX Blue and Brown switch lineups) but they are significantly quieter (yes this is a mechanical keyboard, but no, your neighbors won’t think you’re firing off a machine gun) as they lack the audible click found in most Cherry switches. This isn’t to say that they keyboard doesn’t have a nice audible key press sound when the key is fully depressed, but that the key mechanism isn’t doesn’t create a loud click sound when triggered. One of the great features of the Cherry MX clear is a tactile “bump” that indicates the key has been compressed enough to register the stroke. For touch typists the very subtle tactile feedback is a great indicator that you can move on to the next stroke and provides a welcome speed boost. Even if you’re not trying to break any word-per-minute records, that little bump when pressing the key is satisfying. The Cherry key switches, in addition to providing a much more pleasant typing experience, are also significantly more durable than dome-style key switch. Rubber dome switch membrane keyboards are typically rated for 5-10 million contacts whereas the Cherry mechanical switches are rated for 50 million contacts. You’d have to write the next War and Peace  and follow that up with A Tale of Two Cities: Zombie Edition, and then turn around and transcribe them both into a dozen different languages to even begin putting a tiny dent in the lifecycle of this keyboard. So what do the switches look like under the classicly styled keys? You can take a look yourself with the included key puller. Slide the loop between the keys and then gently beneath the key you wish to remove: Wiggle the key puller gently back and forth while exerting a gentle upward pressure to pop the key off; You can repeat the process for every key, if you ever find yourself needing to extract piles of cat hair, Cheeto dust, or other foreign objects from your keyboard. There it is, the naked switch, the source of that wonderful crisp action with the tactile bump on each keystroke. The last feature worthy of a mention is the N-key rollover functionality of the keyboard. This is a feature you simply won’t find on non-mechanical keyboards and even gaming keyboards typically only have any sort of key roller on the high-frequency keys like WASD. So what is N-key rollover and why do you care? On a typical mass-produced rubber-dome keyboard you cannot simultaneously press more than two keys as the third one doesn’t register. PS/2 keyboards allow for unlimited rollover (in other words you can’t out type the keyboard as all of your keystrokes, no matter how fast, will register); if you use the CODE keyboard with the PS/2 adapter you gain this ability. If you don’t use the PS/2 adapter and use the native USB, you still get 6-key rollover (and the CTRL, ALT, and SHIFT don’t count towards the 6) so realistically you still won’t be able to out type the computer as even the more finger twisting keyboard combos and high speed typing will still fall well within the 6-key rollover. The rollover absolutely doesn’t matter if you’re a slow hunt-and-peck typist, but if you’ve read this far into a keyboard review there’s a good chance that you’re a serious typist and that kind of quality construction and high-number key rollover is a fantastic feature.  The Good, The Bad, and the Verdict We’ve put the CODE keyboard through the paces, we’ve played games with it, typed articles with it, left lengthy comments on Reddit, and otherwise used and abused it like we would any other keyboard. The Good: The construction is rock solid. In an emergency, we’re confident we could use the keyboard as a blunt weapon (and then resume using it later in the day with no ill effect on the keyboard). The Cherry switches are an absolute pleasure to type on; the Clear variety found in the CODE keyboard offer a really nice middle-ground between the gun-shot clack of a louder mechanical switch and the quietness of a lesser-quality dome keyboard without sacrificing quality. Touch typists will love the subtle tactile bump feedback. Dip switch system makes it very easy for users on different systems and with different keyboard layout needs to switch between operating system and keyboard layouts. If you’re investing a chunk of change in a keyboard it’s nice to know you can take it with you to a different operating system or “upgrade” it to a new layout if you decide to take up Dvorak-style typing. The backlighting is perfect. You can adjust it from a barely-visible glow to a blazing light-up-the-room brightness. Whatever your intesity preference, the white-coated steel backplate does a great job diffusing the light between the keys. You can easily remove the keys for cleaning (or to rearrange the letters to support a new keyboard layout). The weight of the unit combined with the extra thick rubber feet keep it planted exactly where you place it on the desk. The Bad: While you’re getting your money’s worth, the $150 price tag is a shock when compared to the $20-60 price tags you find on lower-end keyboards. People used to large dedicated media keys independent of the traditional key layout (such as the large buttons and volume controls found on many modern keyboards) might be off put by the Fn-key style media controls on the CODE. The Verdict: The keyboard is clearly and heavily influenced by the needs of serious typists. Whether you’re a programmer, transcriptionist, or just somebody that wants to leave the lengthiest article comments the Internet has ever seen, the CODE keyboard offers a rock solid typing experience. Yes, $150 isn’t pocket change, but the quality of the CODE keyboard is so high and the typing experience is so enjoyable, you’re easily getting ten times the value you’d get out of purchasing a lesser keyboard. Even compared to other mechanical keyboards on the market, like the Das Keyboard, you’re still getting more for your money as other mechanical keyboards don’t come with the lovely-to-type-on Cherry MX Clear switches, back lighting, and hardware-based operating system keyboard layout switching. If it’s in your budget to upgrade your keyboard (especially if you’ve been slogging along with a low-end rubber-dome keyboard) there’s no good reason to not pickup a CODE keyboard. Key animation courtesy of Geekhack.org user Lethal Squirrel.       

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• SQL Monitor’s data repository: Alerts

  - by Chris Lambrou

  In my previous post, I introduced the SQL Monitor data repository, and described how the monitored objects are stored in a hierarchy in the data schema, in a series of tables with a _Keys suffix. In this post I had planned to describe how the actual data for the monitored objects is stored in corresponding tables with _StableSamples and _UnstableSamples suffixes. However, I’m going to postpone that until my next post, as I’ve had a request from a SQL Monitor user to explain how alerts are stored. In the SQL Monitor data repository, alerts are stored in tables belonging to the alert schema, which contains the following five tables: alert.Alert alert.Alert_Cleared alert.Alert_Comment alert.Alert_Severity alert.Alert_Type In this post, I’m only going to cover the alert.Alert and alert.Alert_Type tables. I may cover the other three tables in a later post. The most important table in this schema is alert.Alert, as each row in this table corresponds to a single alert. So let’s have a look at it. SELECT TOP 100 AlertId, AlertType, TargetObject, [Read], SubType FROM alert.Alert ORDER BY AlertId DESC;  AlertIdAlertTypeTargetObjectReadSubType 165550397:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,9:SqlServer,1,4:Name,s0:,10 265549387:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,7:Machine,1,4:Name,s0:,10 365548187:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 465547157:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 565546147:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 665545187:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 765544157:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 865543147:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 965542187:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 1065541147:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 11…     So what are we seeing here, then? Well, AlertId is an auto-incrementing identity column, so ORDER BY AlertId DESC ensures that we see the most recent alerts first. AlertType indicates the type of each alert, such as Job failed (6), Backup overdue (14) or Long-running query (12). The TargetObject column indicates which monitored object the alert is associated with. The Read column acts as a flag to indicate whether or not the alert has been read. And finally the SubType column is used in the case of a Custom metric (40) alert, to indicate which custom metric the alert pertains to. Okay, now lets look at some of those columns in more detail. The AlertType column is an easy one to start with, and it brings use nicely to the next table, data.Alert_Type. Let’s have a look at what’s in this table: SELECT AlertType, Event, Monitoring, Name, Description FROM alert.Alert_Type ORDER BY AlertType;  AlertTypeEventMonitoringNameDescription 1100Processor utilizationProcessor utilization (CPU) on a host machine stays above a threshold percentage for longer than a specified duration 2210SQL Server error log entryAn error is written to the SQL Server error log with a severity level above a specified value. 3310Cluster failoverThe active cluster node fails, causing the SQL Server instance to switch nodes. 4410DeadlockSQL deadlock occurs. 5500Processor under-utilizationProcessor utilization (CPU) on a host machine remains below a threshold percentage for longer than a specified duration 6610Job failedA job does not complete successfully (the job returns an error code). 7700Machine unreachableHost machine (Windows server) cannot be contacted on the network. 8800SQL Server instance unreachableThe SQL Server instance is not running or cannot be contacted on the network. 9900Disk spaceDisk space used on a logical disk drive is above a defined threshold for longer than a specified duration. 101000Physical memoryPhysical memory (RAM) used on the host machine stays above a threshold percentage for longer than a specified duration. 111100Blocked processSQL process is blocked for longer than a specified duration. 121200Long-running queryA SQL query runs for longer than a specified duration. 131400Backup overdueNo full backup exists, or the last full backup is older than a specified time. 141500Log backup overdueNo log backup exists, or the last log backup is older than a specified time. 151600Database unavailableDatabase changes from Online to any other state. 161700Page verificationTorn Page Detection or Page Checksum is not enabled for a database. 171800Integrity check overdueNo entry for an integrity check (DBCC DBINFO returns no date for dbi_dbccLastKnownGood field), or the last check is older than a specified time. 181900Fragmented indexesFragmentation level of one or more indexes is above a threshold percentage. 192400Job duration unusualThe duration of a SQL job duration deviates from its baseline duration by more than a threshold percentage. 202501Clock skewSystem clock time on the Base Monitor computer differs from the system clock time on a monitored SQL Server host machine by a specified number of seconds. 212700SQL Server Agent Service statusThe SQL Server Agent Service status matches the status specified. 222800SQL Server Reporting Service statusThe SQL Server Reporting Service status matches the status specified. 232900SQL Server Full Text Search Service statusThe SQL Server Full Text Search Service status matches the status specified. 243000SQL Server Analysis Service statusThe SQL Server Analysis Service status matches the status specified. 253100SQL Server Integration Service statusThe SQL Server Integration Service status matches the status specified. 263300SQL Server Browser Service statusThe SQL Server Browser Service status matches the status specified. 273400SQL Server VSS Writer Service statusThe SQL Server VSS Writer status matches the status specified. 283501Deadlock trace flag disabledThe monitored SQL Server’s trace flag cannot be enabled. 293600Monitoring stopped (host machine credentials)SQL Monitor cannot contact the host machine because authentication failed. 303700Monitoring stopped (SQL Server credentials)SQL Monitor cannot contact the SQL Server instance because authentication failed. 313800Monitoring error (host machine data collection)SQL Monitor cannot collect data from the host machine. 323900Monitoring error (SQL Server data collection)SQL Monitor cannot collect data from the SQL Server instance. 334000Custom metricThe custom metric value has passed an alert threshold. 344100Custom metric collection errorSQL Monitor cannot collect custom metric data from the target object. Basically, alert.Alert_Type is just a big reference table containing information about the 34 different alert types supported by SQL Monitor (note that the largest id is 41, not 34 – some alert types have been retired since SQL Monitor was first developed). The Name and Description columns are self evident, and I’m going to skip over the Event and Monitoring columns as they’re not very interesting. The AlertId column is the primary key, and is referenced by AlertId in the alert.Alert table. As such, we can rewrite our earlier query to join these two tables, in order to provide a more readable view of the alerts: SELECT TOP 100 AlertId, Name, TargetObject, [Read], SubType FROM alert.Alert a JOIN alert.Alert_Type at ON a.AlertType = at.AlertType ORDER BY AlertId DESC;  AlertIdNameTargetObjectReadSubType 165550Monitoring error (SQL Server data collection)7:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,9:SqlServer,1,4:Name,s0:,00 265549Monitoring error (host machine data collection)7:Cluster,1,4:Name,s29:srp-mr03.testnet.red-gate.com,7:Machine,1,4:Name,s0:,00 365548Integrity check overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 465547Log backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 565546Backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s15:FavouriteThings,00 665545Integrity check overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 765544Log backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 865543Backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,00 965542Integrity check overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 1065541Backup overdue7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s4:msdb,00 Okay, the next column to discuss in the alert.Alert table is TargetObject. Oh boy, this one’s a bit tricky! The TargetObject of an alert is a serialized string representation of the position in the monitored object hierarchy of the object to which the alert pertains. The serialization format is somewhat convenient for parsing in the C# source code of SQL Monitor, and has some helpful characteristics, but it’s probably very awkward to manipulate in T-SQL. I could document the serialization format here, but it would be very dry reading, so perhaps it’s best to consider an example from the table above. Have a look at the alert with an AlertID of 65543. It’s a Backup overdue alert for the SqlMonitorData database running on the default instance of granger, my laptop. Each different alert type is associated with a specific type of monitored object in the object hierarchy (I described the hierarchy in my previous post). The Backup overdue alert is associated with databases, whose position in the object hierarchy is root → Cluster → SqlServer → Database. The TargetObject value identifies the target object by specifying the key properties at each level in the hierarchy, thus: Cluster: Name = "granger" SqlServer: Name = "" (an empty string, denoting the default instance) Database: Name = "SqlMonitorData" Well, look at the actual TargetObject value for this alert: "7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s14:SqlMonitorData,". It is indeed composed of three parts, one for each level in the hierarchy: Cluster: "7:Cluster,1,4:Name,s7:granger," SqlServer: "9:SqlServer,1,4:Name,s0:," Database: "8:Database,1,4:Name,s14:SqlMonitorData," Each part is handled in exactly the same way, so let’s concentrate on the first part, "7:Cluster,1,4:Name,s7:granger,". It comprises the following: "7:Cluster," – This identifies the level in the hierarchy. "1," – This indicates how many different key properties there are to uniquely identify a cluster (we saw in my last post that each cluster is identified by a single property, its Name). "4:Name,s14:SqlMonitorData," – This represents the Name property, and its corresponding value, SqlMonitorData. It’s split up like this: "4:Name," – Indicates the name of the key property. "s" – Indicates the type of the key property, in this case, it’s a string. "14:SqlMonitorData," – Indicates the value of the property. At this point, you might be wondering about the format of some of these strings. Why is the string "Cluster" stored as "7:Cluster,"? Well an encoding scheme is used, which consists of the following: "7" – This is the length of the string "Cluster" ":" – This is a delimiter between the length of the string and the actual string’s contents. "Cluster" – This is the string itself. 7 characters. "," – This is a final terminating character that indicates the end of the encoded string. You can see that "4:Name,", "8:Database," and "14:SqlMonitorData," also conform to the same encoding scheme. In the example above, the "s" character is used to indicate that the value of the Name property is a string. If you explore the TargetObject property of alerts in your own SQL Monitor data repository, you might find other characters used for other non-string key property values. The different value types you might possibly encounter are as follows: "I" – Denotes a bigint value. For example, "I65432,". "g" – Denotes a GUID value. For example, "g32116732-63ae-4ab5-bd34-7dfdfb084c18,". "d" – Denotes a datetime value. For example, "d634815384796832438,". The value is stored as a bigint, rather than a native SQL datetime value. I’ll describe how datetime values are handled in the SQL Monitor data repostory in a future post. I suggest you have a look at the alerts in your own SQL Monitor data repository for further examples, so you can see how the TargetObject values are composed for each of the different types of alert. Let me give one further example, though, that represents a Custom metric alert, as this will help in describing the final column of interest in the alert.Alert table, SubType. Let me show you the alert I’m interested in: SELECT AlertId, a.AlertType, Name, TargetObject, [Read], SubType FROM alert.Alert a JOIN alert.Alert_Type at ON a.AlertType = at.AlertType WHERE AlertId = 65769;  AlertIdAlertTypeNameTargetObjectReadSubType 16576940Custom metric7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s6:master,12:CustomMetric,1,8:MetricId,I2,02 An AlertType value of 40 corresponds to the Custom metric alert type. The Name taken from the alert.Alert_Type table is simply Custom metric, but this doesn’t tell us anything about the specific custom metric that this alert pertains to. That’s where the SubType value comes in. For custom metric alerts, this provides us with the Id of the specific custom alert definition that can be found in the settings.CustomAlertDefinitions table. I don’t really want to delve into custom alert definitions yet (maybe in a later post), but an extra join in the previous query shows us that this alert pertains to the CPU pressure (avg runnable task count) custom metric alert. SELECT AlertId, a.AlertType, at.Name, cad.Name AS CustomAlertName, TargetObject, [Read], SubType FROM alert.Alert a JOIN alert.Alert_Type at ON a.AlertType = at.AlertType JOIN settings.CustomAlertDefinitions cad ON a.SubType = cad.Id WHERE AlertId = 65769;  AlertIdAlertTypeNameCustomAlertNameTargetObjectReadSubType 16576940Custom metricCPU pressure (avg runnable task count)7:Cluster,1,4:Name,s7:granger,9:SqlServer,1,4:Name,s0:,8:Database,1,4:Name,s6:master,12:CustomMetric,1,8:MetricId,I2,02 The TargetObject value in this case breaks down like this: "7:Cluster,1,4:Name,s7:granger," – Cluster named "granger". "9:SqlServer,1,4:Name,s0:," – SqlServer named "" (the default instance). "8:Database,1,4:Name,s6:master," – Database named "master". "12:CustomMetric,1,8:MetricId,I2," – Custom metric with an Id of 2. Note that the hierarchy for a custom metric is slightly different compared to the earlier Backup overdue alert. It’s root → Cluster → SqlServer → Database → CustomMetric. Also notice that, unlike Cluster, SqlServer and Database, the key property for CustomMetric is called MetricId (not Name), and the value is a bigint (not a string). Finally, delving into the custom metric tables is beyond the scope of this post, but for the sake of avoiding any future confusion, I’d like to point out that whilst the SubType references a custom alert definition, the MetricID value embedded in the TargetObject value references a custom metric definition. Although in this case both the custom metric definition and custom alert definition share the same Id value of 2, this is not generally the case. Okay, that’s enough for now, not least because as I’m typing this, it’s almost 2am, I have to go to work tomorrow, and my alarm is set for 6am – eek! In my next post, I’ll either cover the remaining three tables in the alert schema, or I’ll delve into the way SQL Monitor stores its monitoring data, as I’d originally planned to cover in this post.

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• When is a SQL function not a function?

  - by Rob Farley

  Should SQL Server even have functions? (Oh yeah – this is a T-SQL Tuesday post, hosted this month by Brad Schulz) Functions serve an important part of programming, in almost any language. A function is a piece of code that is designed to return something, as opposed to a piece of code which isn’t designed to return anything (which is known as a procedure). SQL Server is no different. You can call stored procedures, even from within other stored procedures, and you can call functions and use these in other queries. Stored procedures might query something, and therefore ‘return data’, but a function in SQL is considered to have the type of the thing returned, and can be used accordingly in queries. Consider the internal GETDATE() function. SELECT GETDATE(), SomeDatetimeColumn FROM dbo.SomeTable; There’s no logical difference between the field that is being returned by the function and the field that’s being returned by the table column. Both are the datetime field – if you didn’t have inside knowledge, you wouldn’t necessarily be able to tell which was which. And so as developers, we find ourselves wanting to create functions that return all kinds of things – functions which look up values based on codes, functions which do string manipulation, and so on. But it’s rubbish. Ok, it’s not all rubbish, but it mostly is. And this isn’t even considering the SARGability impact. It’s far more significant than that. (When I say the SARGability aspect, I mean “because you’re unlikely to have an index on the result of some function that’s applied to a column, so try to invert the function and query the column in an unchanged manner”) I’m going to consider the three main types of user-defined functions in SQL Server: Scalar Inline Table-Valued Multi-statement Table-Valued I could also look at user-defined CLR functions, including aggregate functions, but not today. I figure that most people don’t tend to get around to doing CLR functions, and I’m going to focus on the T-SQL-based user-defined functions. Most people split these types of function up into two types. So do I. Except that most people pick them based on ‘scalar or table-valued’. I’d rather go with ‘inline or not’. If it’s not inline, it’s rubbish. It really is. Let’s start by considering the two kinds of table-valued function, and compare them. These functions are going to return the sales for a particular salesperson in a particular year, from the AdventureWorks database. CREATE FUNCTION dbo.FetchSales_inline(@salespersonid int, @orderyear int) RETURNS TABLE AS  RETURN (     SELECT e.LoginID as EmployeeLogin, o.OrderDate, o.SalesOrderID     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101') ) ; GO CREATE FUNCTION dbo.FetchSales_multi(@salespersonid int, @orderyear int) RETURNS @results TABLE (     EmployeeLogin nvarchar(512),     OrderDate datetime,     SalesOrderID int     ) AS BEGIN     INSERT @results (EmployeeLogin, OrderDate, SalesOrderID)     SELECT e.LoginID, o.OrderDate, o.SalesOrderID     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101')     ;     RETURN END ; GO You’ll notice that I’m being nice and responsible with the use of the DATEADD function, so that I have SARGability on the OrderDate filter. Regular readers will be hoping I’ll show what’s going on in the execution plans here. Here I’ve run two SELECT * queries with the “Show Actual Execution Plan” option turned on. Notice that the ‘Query cost’ of the multi-statement version is just 2% of the ‘Batch cost’. But also notice there’s trickery going on. And it’s nothing to do with that extra index that I have on the OrderDate column. Trickery. Look at it – clearly, the first plan is showing us what’s going on inside the function, but the second one isn’t. The second one is blindly running the function, and then scanning the results. There’s a Sequence operator which is calling the TVF operator, and then calling a Table Scan to get the results of that function for the SELECT operator. But surely it still has to do all the work that the first one is doing... To see what’s actually going on, let’s look at the Estimated plan. Now, we see the same plans (almost) that we saw in the Actuals, but we have an extra one – the one that was used for the TVF. Here’s where we see the inner workings of it. You’ll probably recognise the right-hand side of the TVF’s plan as looking very similar to the first plan – but it’s now being called by a stack of other operators, including an INSERT statement to be able to populate the table variable that the multi-statement TVF requires. And the cost of the TVF is 57% of the batch! But it gets worse. Let’s consider what happens if we don’t need all the columns. We’ll leave out the EmployeeLogin column. Here, we see that the inline function call has been simplified down. It doesn’t need the Employee table. The join is redundant and has been eliminated from the plan, making it even cheaper. But the multi-statement plan runs the whole thing as before, only removing the extra column when the Table Scan is performed. A multi-statement function is a lot more powerful than an inline one. An inline function can only be the result of a single sub-query. It’s essentially the same as a parameterised view, because views demonstrate this same behaviour of extracting the definition of the view and using it in the outer query. A multi-statement function is clearly more powerful because it can contain far more complex logic. But a multi-statement function isn’t really a function at all. It’s a stored procedure. It’s wrapped up like a function, but behaves like a stored procedure. It would be completely unreasonable to expect that a stored procedure could be simplified down to recognise that not all the columns might be needed, but yet this is part of the pain associated with this procedural function situation. The biggest clue that a multi-statement function is more like a stored procedure than a function is the “BEGIN” and “END” statements that surround the code. If you try to create a multi-statement function without these statements, you’ll get an error – they are very much required. When I used to present on this kind of thing, I even used to call it “The Dangers of BEGIN and END”, and yes, I’ve written about this type of thing before in a similarly-named post over at my old blog. Now how about scalar functions... Suppose we wanted a scalar function to return the count of these. CREATE FUNCTION dbo.FetchSales_scalar(@salespersonid int, @orderyear int) RETURNS int AS BEGIN     RETURN (         SELECT COUNT(*)         FROM Sales.SalesOrderHeader AS o         LEFT JOIN HumanResources.Employee AS e         ON e.EmployeeID = o.SalesPersonID         WHERE o.SalesPersonID = @salespersonid         AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')         AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101')     ); END ; GO Notice the evil words? They’re required. Try to remove them, you just get an error. That’s right – any scalar function is procedural, despite the fact that you wrap up a sub-query inside that RETURN statement. It’s as ugly as anything. Hopefully this will change in future versions. Let’s have a look at how this is reflected in an execution plan. Here’s a query, its Actual plan, and its Estimated plan: SELECT e.LoginID, y.year, dbo.FetchSales_scalar(p.SalesPersonID, y.year) AS NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID; We see here that the cost of the scalar function is about twice that of the outer query. Nicely, the query optimizer has worked out that it doesn’t need the Employee table, but that’s a bit of a red herring here. There’s actually something way more significant going on. If I look at the properties of that UDF operator, it tells me that the Estimated Subtree Cost is 0.337999. If I just run the query SELECT dbo.FetchSales_scalar(281,2003); we see that the UDF cost is still unchanged. You see, this 0.0337999 is the cost of running the scalar function ONCE. But when we ran that query with the CROSS JOIN in it, we returned quite a few rows. 68 in fact. Could’ve been a lot more, if we’d had more salespeople or more years. And so we come to the biggest problem. This procedure (I don’t want to call it a function) is getting called 68 times – each one between twice as expensive as the outer query. And because it’s calling it in a separate context, there is even more overhead that I haven’t considered here. The cheek of it, to say that the Compute Scalar operator here costs 0%! I know a number of IT projects that could’ve used that kind of costing method, but that’s another story that I’m not going to go into here. Let’s look at a better way. Suppose our scalar function had been implemented as an inline one. Then it could have been expanded out like a sub-query. It could’ve run something like this: SELECT e.LoginID, y.year, (SELECT COUNT(*)     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = p.SalesPersonID     AND o.OrderDate >= DATEADD(year,y.year-2000,'20000101')     AND o.OrderDate < DATEADD(year,y.year-2000+1,'20000101')     ) AS NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID; Don’t worry too much about the Scan of the SalesOrderHeader underneath a Nested Loop. If you remember from plenty of other posts on the matter, execution plans don’t push the data through. That Scan only runs once. The Index Spool sucks the data out of it and populates a structure that is used to feed the Stream Aggregate. The Index Spool operator gets called 68 times, but the Scan only once (the Number of Executions property demonstrates this). Here, the Query Optimizer has a full picture of what’s being asked, and can make the appropriate decision about how it accesses the data. It can simplify it down properly. To get this kind of behaviour from a function, we need it to be inline. But without inline scalar functions, we need to make our function be table-valued. Luckily, that’s ok. CREATE FUNCTION dbo.FetchSales_inline2(@salespersonid int, @orderyear int) RETURNS table AS RETURN (SELECT COUNT(*) as NumSales     FROM Sales.SalesOrderHeader AS o     LEFT JOIN HumanResources.Employee AS e     ON e.EmployeeID = o.SalesPersonID     WHERE o.SalesPersonID = @salespersonid     AND o.OrderDate >= DATEADD(year,@orderyear-2000,'20000101')     AND o.OrderDate < DATEADD(year,@orderyear-2000+1,'20000101') ); GO But we can’t use this as a scalar. Instead, we need to use it with the APPLY operator. SELECT e.LoginID, y.year, n.NumSales FROM (VALUES (2001),(2002),(2003),(2004)) AS y (year) CROSS JOIN Sales.SalesPerson AS p LEFT JOIN HumanResources.Employee AS e ON e.EmployeeID = p.SalesPersonID OUTER APPLY dbo.FetchSales_inline2(p.SalesPersonID, y.year) AS n; And now, we get the plan that we want for this query. All we’ve done is tell the function that it’s returning a table instead of a single value, and removed the BEGIN and END statements. We’ve had to name the column being returned, but what we’ve gained is an actual inline simplifiable function. And if we wanted it to return multiple columns, it could do that too. I really consider this function to be superior to the scalar function in every way. It does need to be handled differently in the outer query, but in many ways it’s a more elegant method there too. The function calls can be put amongst the FROM clause, where they can then be used in the WHERE or GROUP BY clauses without fear of calling the function multiple times (another horrible side effect of functions). So please. If you see BEGIN and END in a function, remember it’s not really a function, it’s a procedure. And then fix it. @rob_farley

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• The case of the phantom ADF developer (and other yarns)

  - by Chris Muir

  A few years of ADF experience means I see common mistakes made by different developers, some I regularly make myself.  This post is designed to assist beginners to Oracle JDeveloper Application Development Framework (ADF) avoid a common ADF pitfall, the case of the phantom ADF developer [add Scooby-Doo music here]. ADF Business Components - triggers, default table values and instead of views. Oracle's JDeveloper tutorials help with the A-B-Cs of ADF development, typically built on the nice 'n safe demo schema provided by with the Oracle database such as the HR demo schema. However it's not too long until ADF beginners, having built up some confidence from learning with the tutorials and vanilla demo schemas, start building ADF Business Components based upon their own existing database schema objects.  This is where unexpected problems can sneak in. The crime Developers may encounter a surprising error at runtime when editing a record they just created or updated and committed to the database, based on their own existing tables, namely the error: JBO-25014: Another user has changed the row with primary key oracle.jbo.Key[x] ...where X is the primary key value of the row at hand.  In a production environment with multiple users this error may be legit, one of the other users has updated the row since you queried it.  Yet in a development environment this error is just plain confusing.  If developers are isolated in their own database, creating and editing records they know other users can't possibly be working with, or all the other developers have gone home for the day, how is this error possible? There are no other users?  It must be the phantom ADF developer! [insert dramatic music here] The following picture is what you'll see in the Business Component Browser, and you'll receive a similar error message via an ADF Faces page: A false conclusion What can possibly cause this issue if it isn't our phantom ADF developer?  Doesn't ADF BC implement record locking, locking database records when the row is modified in the ADF middle-tier by a user?  How can our phantom ADF developer even take out a lock if this is the case?  Maybe ADF has a bug, maybe ADF isn't implementing record locking at all?  Shouldn't we see the error "JBO-26030: Failed to lock the record, another user holds the lock" as we attempt to modify the record, why do we see JBO-25014? : Let's verify that ADF is in fact issuing the correct SQL LOCK-FOR-UPDATE statement to the database. First we need to verify ADF's locking strategy.  It is determined by the Application Module's jbo.locking.mode property.  The default (as of JDev 11.1.1.4.0 if memory serves me correct) and recommended value is optimistic, and the other valid value is pessimistic. Next we need a mechanism to check that ADF is issuing the LOCK statements to the database.  We could ask DBAs to monitor locks with OEM, but optimally we'd rather not involve overworked DBAs in this process, so instead we can use the ADF runtime setting –Djbo.debugoutput=console.  At runtime this options turns on instrumentation within the ADF BC layer, which among a lot of extra detail displayed in the log window, will show the actual SQL statement issued to the database, including the LOCK statement we're looking to confirm. Setting our locking mode to pessimistic, opening the Business Components Browser of a JSF page allowing us to edit a record, say the CHARGEABLE field within a BOOKINGS record where BOOKING_NO = 1206, upon editing the record see among others the following log entries: [421] Built select: 'SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings'[422] Executing LOCK...SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings WHERE BOOKING_NO=:1 FOR UPDATE NOWAIT[423] Where binding param 1: 1206  As can be seen on line 422, in fact a LOCK-FOR-UPDATE is indeed issued to the database.  Later when we commit the record we see: [441] OracleSQLBuilder: SAVEPOINT 'BO_SP'[442] OracleSQLBuilder Executing, Lock 1 DML on: BOOKINGS (Update)[443] UPDATE buf Bookings>#u SQLStmtBufLen: 210, actual=62[444] UPDATE BOOKINGS Bookings SET CHARGEABLE=:1 WHERE BOOKING_NO=:2[445] Update binding param 1: N[446] Where binding param 2: 1206[447] BookingsView1 notify COMMIT ... [448] _LOCAL_VIEW_USAGE_model_Bookings_ResourceTypesView1 notify COMMIT ... [449] EntityCache close prepared statement ....and as a result the changes are saved to the database, and the lock is released. Let's see what happens when we use the optimistic locking mode, this time to change the same BOOKINGS record CHARGEABLE column again.  As soon as we edit the record we see little activity in the logs, nothing to indicate any SQL statement, let alone a LOCK has been taken out on the row. However when we save our records by issuing a commit, the following is recorded in the logs: [509] OracleSQLBuilder: SAVEPOINT 'BO_SP'[510] OracleSQLBuilder Executing doEntitySelect on: BOOKINGS (true)[511] Built select: 'SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings'[512] Executing LOCK...SELECT BOOKING_NO, EVENT_NO, RESOURCE_CODE, CHARGEABLE, MADE_BY, QUANTITY, COST, STATUS, COMMENTS FROM BOOKINGS Bookings WHERE BOOKING_NO=:1 FOR UPDATE NOWAIT[513] Where binding param 1: 1205[514] OracleSQLBuilder Executing, Lock 2 DML on: BOOKINGS (Update)[515] UPDATE buf Bookings>#u SQLStmtBufLen: 210, actual=62[516] UPDATE BOOKINGS Bookings SET CHARGEABLE=:1 WHERE BOOKING_NO=:2[517] Update binding param 1: Y[518] Where binding param 2: 1205[519] BookingsView1 notify COMMIT ... [520] _LOCAL_VIEW_USAGE_model_Bookings_ResourceTypesView1 notify COMMIT ... [521] EntityCache close prepared statement Again even though we're seeing the midtier delay the LOCK statement until commit time, it is in fact occurring on line 412, and released as part of the commit issued on line 419.  Therefore with either optimistic or pessimistic locking a lock is indeed issued. Our conclusion at this point must be, unless there's the unlikely cause the LOCK statement is never really hitting the database, or the even less likely cause the database has a bug, then ADF does in fact take out a lock on the record before allowing the current user to update it.  So there's no way our phantom ADF developer could even modify the record if he tried without at least someone receiving a lock error. Hmm, we can only conclude the locking mode is a red herring and not the true cause of our problem.  Who is the phantom? At this point we'll need to conclude that the error message "JBO-25014: Another user has changed" is somehow legit, even though we don't understand yet what's causing it. This leads onto two further questions, how does ADF know another user has changed the row, and what's been changed anyway? To answer the first question, how does ADF know another user has changed the row, the Fusion Guide's section 4.10.11 How to Protect Against Losing Simultaneous Updated Data , that details the Entity Object Change-Indicator property, gives us the answer: At runtime the framework provides automatic "lost update" detection for entity objects to ensure that a user cannot unknowingly modify data that another user has updated and committed in the meantime. Typically, this check is performed by comparing the original values of each persistent entity attribute against the corresponding current column values in the database at the time the underlying row is locked. Before updating a row, the entity object verifies that the row to be updated is still consistent with the current state of the database.  The guide further suggests to make this solution more efficient: You can make the lost update detection more efficient by identifying any attributes of your entity whose values you know will be updated whenever the entity is modified. Typical candidates include a version number column or an updated date column in the row.....To detect whether the row has been modified since the user queried it in the most efficient way, select the Change Indicator option to compare only the change-indicator attribute values. We now know that ADF BC doesn't use the locking mechanism at all to protect the current user against updates, but rather it keeps a copy of the original record fetched, separate to the user changed version of the record, and it compares the original record against the one in the database when the lock is taken out.  If values don't match, be it the default compare-all-columns behaviour, or the more efficient Change Indicator mechanism, ADF BC will throw the JBO-25014 error. This leaves one last question.  Now we know the mechanism under which ADF identifies a changed row, what we don't know is what's changed and who changed it? The real culprit What's changed?  We know the record in the mid-tier has been changed by the user, however ADF doesn't use the changed record in the mid-tier to compare to the database record, but rather a copy of the original record before it was changed.  This leaves us to conclude the database record has changed, but how and by who? There are three potential causes: Database triggers The database trigger among other uses, can be configured to fire PLSQL code on a database table insert, update or delete.  In particular in an insert or update the trigger can override the value assigned to a particular column.  The trigger execution is actioned by the database on behalf of the user initiating the insert or update action. Why this causes the issue specific to our ADF use, is when we insert or update a record in the database via ADF, ADF keeps a copy of the record written to the database.  However the cached record is instantly out of date as the database triggers have modified the record that was actually written to the database.  Thus when we update the record we just inserted or updated for a second time to the database, ADF compares its original copy of the record to that in the database, and it detects the record has been changed – giving us JBO-25014. This is probably the most common cause of this problem. Default values A second reason this issue can occur is another database feature, default column values.  When creating a database table the schema designer can define default values for specific columns.  For example a CREATED_BY column could be set to SYSDATE, or a flag column to Y or N.  Default values are only used by the database when a user inserts a new record and the specific column is assigned NULL.  The database in this case will overwrite the column with the default value. As per the database trigger section, it then becomes apparent why ADF chokes on this feature, though it can only specifically occur in an insert-commit-update-commit scenario, not the update-commit-update-commit scenario. Instead of trigger views I must admit I haven't double checked this scenario but it seems plausible, that of the Oracle database's instead of trigger view (sometimes referred to as instead of views).  A view in the database is based on a query, and dependent on the queries complexity, may support insert, update and delete functionality to a limited degree.  In order to support fully insertable, updateable and deletable views, Oracle introduced the instead of view, that gives the view designer the ability to not only define the view query, but a set of programmatic PLSQL triggers where the developer can define their own logic for inserts, updates and deletes. While this provides the database programmer a very powerful feature, it can cause issues for our ADF application.  On inserting or updating a record in the instead of view, the record and it's data that goes in is not necessarily the data that comes out when ADF compares the records, as the view developer has the option to practically do anything with the incoming data, including throwing it away or pushing it to tables which aren't used by the view underlying query for fetching the data. Readers are at this point reminded that this article is specifically about how the JBO-25014 error occurs in the context of 1 developer on an isolated database.  The article is not considering how the error occurs in a production environment where there are multiple users who can cause this error in a legitimate fashion.  Assuming none of the above features are the cause of the problem, and optimistic locking is turned on (this error is not possible if pessimistic locking is the default mode *and* none of the previous causes are possible), JBO-25014 is quite feasible in a production ADF application if 2 users modify the same record. At this point under project timelines pressure, the obvious fix for developers is to drop both database triggers and default values from the underlying tables.  However we must be careful that these legacy constructs aren't used and assumed to be in place by other legacy systems.  Dropping the database triggers or default value that the existing Oracle Forms  applications assumes and requires to be in place could cause unexpected behaviour and bugs in the Forms application.  Proficient software engineers would recognize such a change may require a partial or full regression test of the existing legacy system, a potentially costly and timely exercise, not ideal. Solving the mystery once and for all Luckily ADF has built in functionality to deal with this issue, though it's not a surprise, as Oracle as the author of ADF also built the database, and are fully aware of the Oracle database's feature set.  At the Entity Object attribute level, the Refresh After Insert and Refresh After Update properties.  Simply selecting these instructs ADF BC after inserting or updating a record to the database, to expect the database to modify the said attributes, and read a copy of the changed attributes back into its cached mid-tier record.  Thus next time the developer modifies the current record, the comparison between the mid-tier record and the database record match, and JBO-25014: Another user has changed" is no longer an issue. [Post edit - as per the comment from Oracle's Steven Davelaar below, as he correctly points out the above solution will not work for instead-of-triggers views as it relies on SQL RETURNING clause which is incompatible with this type of view] Alternatively you can set the Change Indicator on one of the attributes.  This will work as long as the relating column for the attribute in the database itself isn't inadvertently updated.  In turn you're possibly just masking the issue rather than solving it, because if another developer turns the Change Indicator back on the original issue will return.

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• Pain Comes Instantly

  - by user701213

  When I look back at recent blog entries – many of which are not all that current (more on where my available writing time is going later) – I am struck by how many of them focus on public policy or legislative issues instead of, say, the latest nefarious cyberattack or exploit (or everyone’s favorite new pastime: coining terms for the Coming Cyberpocalypse: “digital Pearl Harbor” is so 1941). Speaking of which, I personally hope evil hackers from Malefactoria will someday hack into my bathroom scale – which in a future time will be connected to the Internet because, gosh, wouldn’t it be great to have absolutely everything in your life Internet-enabled? – and recalibrate it so I’m 10 pounds thinner. The horror. In part, my focus on public policy is due to an admitted limitation of my skill set. I enjoy reading technical articles about exploits and cybersecurity trends, but writing a blog entry on those topics would take more research than I have time for and, quite honestly, doesn’t play to my strengths. The first rule of writing is “write what you know.” The bigger contributing factor to my recent paucity of blog entries is that more and more of my waking hours are spent engaging in “thrust and parry” activity involving emerging regulations of some sort or other. I’ve opined in earlier blogs about what constitutes good and reasonable public policy so nobody can accuse me of being reflexively anti-regulation. That said, you have so many cycles in the day, and most of us would rather spend it slaying actual dragons than participating in focus groups on whether dragons are really a problem, whether lassoing them (with organic, sustainable and recyclable lassos) is preferable to slaying them – after all, dragons are people, too - and whether we need lasso compliance auditors to make sure lassos are being used correctly and humanely. (A point that seems to evade many rule makers: slaying dragons actually accomplishes something, whereas talking about “approved dragon slaying procedures and requirements” wastes the time of those who are competent to dispatch actual dragons and who were doing so very well without the input of “dragon-slaying theorists.”) Unfortunately for so many of us who would just get on with doing our day jobs, cybersecurity is rapidly devolving into the “focus groups on dragon dispatching” realm, which actual dragons slayers have little choice but to participate in. The general trend in cybersecurity is that powers-that-be – which encompasses groups other than just legislators – are often increasingly concerned and therefore feel they need to Do Something About Cybersecurity. Many seem to believe that if only we had the right amount of regulation and oversight, there would be no data breaches: a breach simply must mean Someone Is At Fault and Needs Supervision. (Leaving aside the fact that we have lots of home invasions despite a) guard dogs b) liberal carry permits c) alarm systems d) etc.) Also note that many well-managed and security-aware organizations, like the US Department of Defense, still get hacked. More specifically, many powers-that-be feel they must direct industry in a multiplicity of ways, up to and including how we actually build and deploy information technology systems. The more prescriptive the requirement, the more regulators or overseers a) can be seen to be doing something b) feel as if they are doing something regardless of whether they are actually doing something useful or cost effective. Note: an unfortunate concomitant of Doing Something is that often the cure is worse than the ailment. That is, doing what overseers want creates unfortunate byproducts that they either didn’t foresee or worse, don’t care about. After all, the logic goes, we Did Something. Prescriptive practice in the IT industry is problematic for a number of reasons. For a start, prescriptive guidance is really only appropriate if: • It is cost effective• It is “current” (meaning, the guidance doesn’t require the use of the technical equivalent of buggy whips long after horse-drawn transportation has become passé)*• It is practical (that is, pragmatic, proven and effective in the real world, not theoretical and unproven)• It solves the right problem With the above in mind, heading up the list of “you must be joking” regulations are recent disturbing developments in the Payment Card Industry (PCI) world. I’d like to give PCI kahunas the benefit of the doubt about their intentions, except that efforts by Oracle among others to make them aware of “unfortunate side effects of your requirements” – which is as tactful I can be for reasons that I believe will become obvious below - have gone, to-date, unanswered and more importantly, unchanged. A little background on PCI before I get too wound up. In 2008, the Payment Card Industry (PCI) Security Standards Council (SSC) introduced the Payment Application Data Security Standard (PA-DSS). That standard requires vendors of payment applications to ensure that their products implement specific requirements and undergo security assessment procedures. In order to have an application listed as a Validated Payment Application (VPA) and available for use by merchants, software vendors are required to execute the PCI Payment Application Vendor Release Agreement (VRA). (Are you still with me through all the acronyms?) Beginning in August 2010, the VRA imposed new obligations on vendors that are extraordinary and extraordinarily bad, short-sighted and unworkable. Specifically, PCI requires vendors to disclose (dare we say “tell all?”) to PCI any known security vulnerabilities and associated security breaches involving VPAs. ASAP. Think about the impact of that. PCI is asking a vendor to disclose to them: • Specific details of security vulnerabilities • Including exploit information or technical details of the vulnerability • Whether or not there is any mitigation available (as in a patch) PCI, in turn, has the right to blab about any and all of the above – specifically, to distribute all the gory details of what is disclosed - to the PCI SSC, qualified security assessors (QSAs), and any affiliate or agent or adviser of those entities, who are in turn permitted to share it with their respective affiliates, agents, employees, contractors, merchants, processors, service providers and other business partners. This assorted crew can’t be more than, oh, hundreds of thousands of entities. Does anybody believe that several hundred thousand people can keep a secret? Or that several hundred thousand people are all equally trustworthy? Or that not one of the people getting all that information would blab vulnerability details to a bad guy, even by accident? Or be a bad guy who uses the information to break into systems? (Wait, was that the Easter Bunny that just hopped by? Bringing world peace, no doubt.) Sarcasm aside, common sense tells us that telling lots of people a secret is guaranteed to “unsecret” the secret. Notably, being provided details of a vulnerability (without a patch) is of little or no use to companies running the affected application. Few users have the technological sophistication to create a workaround, and even if they do, most workarounds break some other functionality in the application or surrounding environment. Also, given the differences among corporate implementations of any application, it is highly unlikely that a single workaround is going to work for all corporate users. So until a patch is developed by the vendor, users remain at risk of exploit: even more so if the details of vulnerability have been widely shared. Sharing that information widely before a patch is available therefore does not help users, and instead helps only those wanting to exploit known security bugs. There’s a shocker for you. Furthermore, we already know that insider information about security vulnerabilities inevitably leaks, which is why most vendors closely hold such information and limit dissemination until a patch is available (and frequently limit dissemination of technical details even with the release of a patch). That’s the industry norm, not that PCI seems to realize or acknowledge that. Why would anybody release a bunch of highly technical exploit information to a cast of thousands, whose only “vetting” is that they are members of a PCI consortium? Oracle has had personal experience with this problem, which is one reason why information on security vulnerabilities at Oracle is “need to know” (we use our own row level access control to limit access to security bugs in our bug database, and thus less than 1% of development has access to this information), and we don’t provide some customers with more information than others or with vulnerability information and/or patches earlier than others. Failure to remember “insider information always leaks” creates problems in the general case, and has created problems for us specifically. A number of years ago, one of the UK intelligence agencies had information about a non-public security vulnerability in an Oracle product that they circulated among other UK and Commonwealth defense and intelligence entities. Nobody, it should be pointed out, bothered to report the problem to Oracle, even though only Oracle could produce a patch. The vulnerability was finally reported to Oracle by (drum roll) a US-based commercial company, to whom the information had leaked. (Note: every time I tell this story, the MI-whatever agency that created the problem gets a bit shirty with us. I know they meant well and have improved their vulnerability handling/sharing processes but, dudes, next time you find an Oracle vulnerability, try reporting it to us first before blabbing to lots of people who can’t actually fix the problem. Thank you!) Getting back to PCI: clearly, these new disclosure obligations increase the risk of exploitation of a vulnerability in a VPA and thus, of misappropriation of payment card data and customer information that a VPA processes, stores or transmits. It stands to reason that VRA’s current requirement for the widespread distribution of security vulnerability exploit details -- at any time, but particularly before a vendor can issue a patch or a workaround -- is very poor public policy. It effectively publicizes information of great value to potential attackers while not providing compensating benefits - actually, any benefits - to payment card merchants or consumers. In fact, it magnifies the risk to payment card merchants and consumers. The risk is most prominent in the time before a patch has been released, since customers often have little option but to continue using an application or system despite the risks. However, the risk is not limited to the time before a patch is issued: customers often need days, or weeks, to apply patches to systems, based upon the complexity of the issue and dependence on surrounding programs. Rather than decreasing the available window of exploit, this requirement increases the available window of exploit, both as to time available to exploit a vulnerability and the ease with which it can be exploited. Also, why would hackers focus on finding new vulnerabilities to exploit if they can get “EZHack” handed to them in such a manner: a) a vulnerability b) in a payment application c) with exploit code: the “Hacking Trifecta!“ It’s fair to say that this is probably the exact opposite of what PCI – or any of us – would want. Established industry practice concerning vulnerability handling avoids the risks created by the VRA’s vulnerability disclosure requirements. Specifically, the norm is not to release information about a security bug until the associated patch (or a pretty darn good workaround) has been issued. Once a patch is available, the notice to the user community is a high-level communication discussing the product at issue, the level of risk associated with the vulnerability, and how to apply the patch. The notices do not include either the specific customers affected by the vulnerability or forensic reports with maps of the exploit (both of which are required by the current VRA). In this way, customers have the tools they need to prioritize patching and to help prevent an attack, and the information released does not increase the risk of exploit. Furthermore, many vendors already use industry standards for vulnerability description: Common Vulnerability Enumeration (CVE) and Common Vulnerability Scoring System (CVSS). CVE helps ensure that customers know which particular issues a patch addresses and CVSS helps customers determine how severe a vulnerability is on a relative scale. Industry already provides the tools customers need to know what the patch contains and how bad the problem is that the patch remediates. So, what’s a poor vendor to do? Oracle is reaching out to other vendors subject to PCI and attempting to enlist then in a broad effort to engage PCI in rethinking (that is, eradicating) these requirements. I would therefore urge all who care about this issue, but especially those in the vendor community whose applications are subject to PCI and who may not have know they were being asked to tell-all to PCI and put their customers at risk, to do one of the following: • Contact PCI with your concerns• Contact Oracle (we are looking for vendors to sign our statement of concern)• And make sure you tell your customers that you have to rat them out to PCI if there is a breach involving the payment application I like to be charitable and say “PCI meant well” but in as important a public policy issue as what you disclose about vulnerabilities, to whom and when, meaning well isn’t enough. We need to do well. PCI, as regards this particular issue, has not done well, and has compounded the error by thus far being nonresponsive to those of us who have labored mightily to try to explain why they might want to rethink telling the entire planet about security problems with no solutions. By Way of Explanation… Non-related to PCI whatsoever, and the explanation for why I have not been blogging a lot recently, I have been working on Other Writing Venues with my sister Diane (who has also worked in the tech sector, inflicting upgrades on unsuspecting and largely ungrateful end users). I am pleased to note that we have recently (self-)published the first in the Miss Information Technology Murder Mystery series, Outsourcing Murder. The genre might best be described as “chick lit meets geek scene.” Our sisterly nom de plume is Maddi Davidson and (shameless plug follows): you can order the paper version of the book on Amazon, or the Kindle or Nook versions on www.amazon.com or www.bn.com, respectively. From our book jacket: Emma Jones, a 20-something IT consultant, is working on an outsourcing project at Tahiti Tacos, a restaurant chain offering Polynexican cuisine: refried poi, anyone? Emma despises her boss Padmanabh, a brilliant but arrogant partner in GD Consulting. When Emma discovers His-Royal-Padness’s body (verdict: death by cricket bat), she becomes a suspect.With her overprotective family and her best friend Stacey providing endless support and advice, Emma stumbles her way through an investigation of Padmanabh’s murder, bolstered by fusion food feeding frenzies, endless cups of frou-frou coffee and serious surfing sessions. While Stacey knows a PI who owes her a favor, landlady Magda urges Emma to tart up her underwear drawer before the next cute cop with a search warrant arrives. Emma’s mother offers to fix her up with a PhD student at Berkeley and showers her with self-defense gizmos while her old lover Keoni beckons from Hawai’i. And everyone, even Shaun the barista, knows a good lawyer. Book 2, Denial of Service, is coming out this summer. * Given the rate of change in technology, today’s “thou shalts” are easily next year’s “buggy whip guidance.”

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• Selling Federal Enterprise Architecture (EA)

  - by TedMcLaughlan

  Selling Federal Enterprise Architecture A taxonomy of subject areas, from which to develop a prioritized marketing and communications plan to evangelize EA activities within and among US Federal Government organizations and constituents. Any and all feedback is appreciated, particularly in developing and extending this discussion as a tool for use – more information and details are also available. "Selling" the discipline of Enterprise Architecture (EA) in the Federal Government (particularly in non-DoD agencies) is difficult, notwithstanding the general availability and use of the Federal Enterprise Architecture Framework (FEAF) for some time now, and the relatively mature use of the reference models in the OMB Capital Planning and Investment (CPIC) cycles. EA in the Federal Government also tends to be a very esoteric and hard to decipher conversation – early apologies to those who agree to continue reading this somewhat lengthy article. Alignment to the FEAF and OMB compliance mandates is long underway across the Federal Departments and Agencies (and visible via tools like PortfolioStat and ITDashboard.gov – but there is still a gap between the top-down compliance directives and enablement programs, and the bottom-up awareness and effective use of EA for either IT investment management or actual mission effectiveness. "EA isn't getting deep enough penetration into programs, components, sub-agencies, etc.", verified a panelist at the most recent EA Government Conference in DC. Newer guidance from OMB may be especially difficult to handle, where bottom-up input can't be accurately aligned, analyzed and reported via standardized EA discipline at the Agency level – for example in addressing the new (for FY13) Exhibit 53D "Agency IT Reductions and Reinvestments" and the information required for "Cloud Computing Alternatives Evaluation" (supporting the new Exhibit 53C, "Agency Cloud Computing Portfolio"). Therefore, EA must be "sold" directly to the communities that matter, from a coordinated, proactive messaging perspective that takes BOTH the Program-level value drivers AND the broader Agency mission and IT maturity context into consideration. Selling EA means persuading others to take additional time and possibly assign additional resources, for a mix of direct and indirect benefits – many of which aren't likely to be realized in the short-term. This means there's probably little current, allocated budget to work with; ergo the challenge of trying to sell an "unfunded mandate". Also, the concept of "Enterprise" in large Departments like Homeland Security tends to cross all kinds of organizational boundaries – as Richard Spires recently indicated by commenting that "...organizational boundaries still trump functional similarities. Most people understand what we're trying to do internally, and at a high level they get it. The problem, of course, is when you get down to them and their system and the fact that you're going to be touching them...there's always that fear factor," Spires said. It is quite clear to the Federal IT Investment community that for EA to meet its objective, understandable, relevant value must be measured and reported using a repeatable method – as described by GAO's recent report "Enterprise Architecture Value Needs To Be Measured and Reported". What's not clear is the method or guidance to sell this value. In fact, the current GAO "Framework for Assessing and Improving Enterprise Architecture Management (Version 2.0)", a.k.a. the "EAMMF", does not include words like "sell", "persuade", "market", etc., except in reference ("within Core Element 19: Organization business owner and CXO representatives are actively engaged in architecture development") to a brief section in the CIO Council's 2001 "Practical Guide to Federal Enterprise Architecture", entitled "3.3.1. Develop an EA Marketing Strategy and Communications Plan." Furthermore, Core Element 19 of the EAMMF is advised to be applied in "Stage 3: Developing Initial EA Versions". This kind of EA sales campaign truly should start much earlier in the maturity progress, i.e. in Stages 0 or 1. So, what are the understandable, relevant benefits (or value) to sell, that can find an agreeable, participatory audience, and can pave the way towards success of a longer-term, funded set of EA mechanisms that can be methodically measured and reported? Pragmatic benefits from a useful EA that can help overcome the fear of change? And how should they be sold? Following is a brief taxonomy (it's a taxonomy, to help organize SME support) of benefit-related subjects that might make the most sense, in creating the messages and organizing an initial "engagement plan" for evangelizing EA "from within". An EA "Sales Taxonomy" of sorts. We're not boiling the ocean here; the subjects that are included are ones that currently appear to be urgently relevant to the current Federal IT Investment landscape. Note that successful dialogue in these topics is directly usable as input or guidance for actually developing early-stage, "Fit-for-Purpose" (a DoDAF term) Enterprise Architecture artifacts, as prescribed by common methods found in most EA methodologies, including FEAF, TOGAF, DoDAF and our own Oracle Enterprise Architecture Framework (OEAF). The taxonomy below is organized by (1) Target Community, (2) Benefit or Value, and (3) EA Program Facet - as in: "Let's talk to (1: Community Member) about how and why (3: EA Facet) the EA program can help with (2: Benefit/Value)". Once the initial discussion targets and subjects are approved (that can be measured and reported), a "marketing and communications plan" can be created. A working example follows the Taxonomy. Enterprise Architecture Sales Taxonomy Draft, Summary Version 1. Community 1.1. Budgeted Programs or Portfolios Communities of Purpose (CoPR) 1.1.1. Program/System Owners (Senior Execs) Creating or Executing Acquisition Plans 1.1.2. Program/System Owners Facing Strategic Change 1.1.2.1. Mandated 1.1.2.2. Expected/Anticipated 1.1.3. Program Managers - Creating Employee Performance Plans 1.1.4. CO/COTRs – Creating Contractor Performance Plans, or evaluating Value Engineering Change Proposals (VECP) 1.2. Governance & Communications Communities of Practice (CoP) 1.2.1. Policy Owners 1.2.1.1. OCFO 1.2.1.1.1. Budget/Procurement Office 1.2.1.1.2. Strategic Planning 1.2.1.2. OCIO 1.2.1.2.1. IT Management 1.2.1.2.2. IT Operations 1.2.1.2.3. Information Assurance (Cyber Security) 1.2.1.2.4. IT Innovation 1.2.1.3. Information-Sharing/ Process Collaboration (i.e. policies and procedures regarding Partners, Agreements) 1.2.2. Governing IT Council/SME Peers (i.e. an "Architects Council") 1.2.2.1. Enterprise Architects (assumes others exist; also assumes EA participants aren't buried solely within the CIO shop) 1.2.2.2. Domain, Enclave, Segment Architects – i.e. the right affinity group for a "shared services" EA structure (per the EAMMF), which may be classified as Federated, Segmented, Service-Oriented, or Extended 1.2.2.3. External Oversight/Constraints 1.2.2.3.1. GAO/OIG & Legal 1.2.2.3.2. Industry Standards 1.2.2.3.3. Official public notification, response 1.2.3. Mission Constituents Participant & Analyst Community of Interest (CoI) 1.2.3.1. Mission Operators/Users 1.2.3.2. Public Constituents 1.2.3.3. Industry Advisory Groups, Stakeholders 1.2.3.4. Media 2. Benefit/Value (Note the actual benefits may not be discretely attributable to EA alone; EA is a very collaborative, cross-cutting discipline.) 2.1. Program Costs – EA enables sound decisions regarding... 2.1.1. Cost Avoidance – a TCO theme 2.1.2. Sequencing – alignment of capability delivery 2.1.3. Budget Instability – a Federal reality 2.2. Investment Capital – EA illuminates new investment resources via... 2.2.1. Value Engineering – contractor-driven cost savings on existing budgets, direct or collateral 2.2.2. Reuse – reuse of investments between programs can result in savings, chargeback models; avoiding duplication 2.2.3. License Refactoring – IT license & support models may not reflect actual or intended usage 2.3. Contextual Knowledge – EA enables informed decisions by revealing... 2.3.1. Common Operating Picture (COP) – i.e. cross-program impacts and synergy, relative to context 2.3.2. Expertise & Skill – who truly should be involved in architectural decisions, both business and IT 2.3.3. Influence – the impact of politics and relationships can be examined 2.3.4. Disruptive Technologies – new technologies may reduce costs or mitigate risk in unanticipated ways 2.3.5. What-If Scenarios – can become much more refined, current, verifiable; basis for Target Architectures 2.4. Mission Performance – EA enables beneficial decision results regarding... 2.4.1. IT Performance and Optimization – towards 100% effective, available resource utilization 2.4.2. IT Stability – towards 100%, real-time uptime 2.4.3. Agility – responding to rapid changes in mission 2.4.4. Outcomes –measures of mission success, KPIs – vs. only "Outputs" 2.4.5. Constraints – appropriate response to constraints 2.4.6. Personnel Performance – better line-of-sight through performance plans to mission outcome 2.5. Mission Risk Mitigation – EA mitigates decision risks in terms of... 2.5.1. Compliance – all the right boxes are checked 2.5.2. Dependencies –cross-agency, segment, government 2.5.3. Transparency – risks, impact and resource utilization are illuminated quickly, comprehensively 2.5.4. Threats and Vulnerabilities – current, realistic awareness and profiles 2.5.5. Consequences – realization of risk can be mapped as a series of consequences, from earlier decisions or new decisions required for current issues 2.5.5.1. Unanticipated – illuminating signals of future or non-symmetric risk; helping to "future-proof" 2.5.5.2. Anticipated – discovering the level of impact that matters 3. EA Program Facet (What parts of the EA can and should be communicated, using business or mission terms?) 3.1. Architecture Models – the visual tools to be created and used 3.1.1. Operating Architecture – the Business Operating Model/Architecture elements of the EA truly drive all other elements, plus expose communication channels 3.1.2. Use Of – how can the EA models be used, and how are they populated, from a reasonable, pragmatic yet compliant perspective? What are the core/minimal models required? What's the relationship of these models, with existing system models? 3.1.3. Scope – what level of granularity within the models, and what level of abstraction across the models, is likely to be most effective and useful? 3.2. Traceability – the maturity, status, completeness of the tools 3.2.1. Status – what in fact is the degree of maturity across the integrated EA model and other relevant governance models, and who may already be benefiting from it? 3.2.2. Visibility – how does the EA visibly and effectively prove IT investment performance goals are being reached, with positive mission outcome? 3.3. Governance – what's the interaction, participation method; how are the tools used? 3.3.1. Contributions – how is the EA program informed, accept submissions, collect data? Who are the experts? 3.3.2. Review – how is the EA validated, against what criteria?  Taxonomy Usage Example:   1. To speak with: a. ...a particular set of System Owners Facing Strategic Change, via mandate (like the "Cloud First" mandate); about... b. ...how the EA program's visible and easily accessible Infrastructure Reference Model (i.e. "IRM" or "TRM"), if updated more completely with current system data, can... c. ...help shed light on ways to mitigate risks and avoid future costs associated with NOT leveraging potentially-available shared services across the enterprise... 2. ....the following Marketing & Communications (Sales) Plan can be constructed: a. Create an easy-to-read "Consequence Model" that illustrates how adoption of a cloud capability (like elastic operational storage) can enable rapid and durable compliance with the mandate – using EA traceability. Traceability might be from the IRM to the ARM (that identifies reusable services invoking the elastic storage), and then to the PRM with performance measures (such as % utilization of purchased storage allocation) included in the OMB Exhibits; and b. Schedule a meeting with the Program Owners, timed during their Acquisition Strategy meetings in response to the mandate, to use the "Consequence Model" for advising them to organize a rapid and relevant RFI solicitation for this cloud capability (regarding alternatives for sourcing elastic operational storage); and c. Schedule a series of short "Discovery" meetings with the system architecture leads (as agreed by the Program Owners), to further populate/validate the "As-Is" models and frame the "To Be" models (via scenarios), to better inform the RFI, obtain the best feedback from the vendor community, and provide potential value for and avoid impact to all other programs and systems. --end example -- Note that communications with the intended audience should take a page out of the standard "Search Engine Optimization" (SEO) playbook, using keywords and phrases relating to "value" and "outcome" vs. "compliance" and "output". Searches in email boxes, internal and external search engines for phrases like "cost avoidance strategies", "mission performance metrics" and "innovation funding" should yield messages and content from the EA team. This targeted, informed, practical sales approach should result in additional buy-in and participation, additional EA information contribution and model validation, development of more SMEs and quick "proof points" (with real-life testing) to bolster the case for EA. The proof point here is a successful, timely procurement that satisfies not only the external mandate and external oversight review, but also meets internal EA compliance/conformance goals and therefore is more transparently useful across the community. In short, if sold effectively, the EA will perform and be recognized. EA won’t therefore be used only for compliance, but also (according to a validated, stated purpose) to directly influence decisions and outcomes. The opinions, views and analysis expressed in this document are those of the author and do not necessarily reflect the views of Oracle.

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• Excel trend line intercept

  - by Brian M.

  I have an Excel graph with a linear trend line to keep track of users who are updated with a newer version of software: I have 660 users, and the trend line predicts where the number updated reaches 660 to indicate updates complete. Is there a way for it to either give me an actual value for that intercept, or, more conveniently, draw a vertical intercept line where the trend line is projected to hit that number?

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• Add DNS suffixes to a Sonicwall PRO2040 firewall?

  - by eidylon

  I want to have our network pass out DNS suffixes with the DHCP assignments, so that we don't need to add them to the TCP/IP settings on each computer. Our DHCP is not being handled by an actual server box, but by our Sonicwall firewall, which is a PRO 2040. Can this firewall be set up to append DNS suffixes? Thanks!

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• Brightness controls not adjusting the brightness in ubuntu 10.10 64 bit on hp dm3t notebook

  - by user26768

  I picked up an hp dm3t laptop with intel HD graphics and installed ubuntu 10.10 64 bit on it. It works great -- the only problem is that the brightness controls don't work. The brightness is always at full. When I try to adjust it down, the indicator graphic indicates that it's going down but the actual brightness doesn't change. Is there anything that I can try to make this work? I'd really appreciate any help.

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• Default Text Color in Apple Mail.app

  - by Axeva

  Is there any way to set the default font color for new messages in Mail.app? It's trivial to set the actual font, and text size. I cannot seem to get the application to change the text color though. It always defaults to black. After 5 or 6 major revisions of OS X, surely someone has thought of this, right?

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• Inkscape: how to create inner border?

  - by Anton

  I create figure and set border width to 1px. My image actual size is 100px. But with border this is 102px. How to set inner border instead of o*uther border*? In Protoshop I can select type of border - inner, outer or center. But in Inkscape I not found this option. Please, help me. Thanks!

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• Is it possible to correct my GeoIP location

  - by brianegge

  Numerous services and advertising do GeoIP lookups. They get the country correct, but often the city is wrong. Are there places where I can go and correct this, letting people know the actual location of my IP address. I have a static IP, so it's not going to go to another user in a different location.

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• PSTN Trunk TDM400P Install on Asterisk / Trixbox

  - by Jona

  Hey All, I'm trying to get a TDM400P card with FXO module to connect to our PSTN line. The card is correctly detected by Linux: [trixbox1.localdomain asterisk]# lspci 00:09.0 Communication controller: Tiger Jet Network Inc. Tiger3XX Modem/ISDN interface And asterisk can see the channel: > trixbox1*CLI> dahdi show channel 1 > Channel: 1LI> File Descriptor: 14 > Span: 11*CLI> Extension: I> Dialing: > noI> Context: from-pstn Caller ID: I> > Calling TON: 0 Caller ID name: > Mailbox: none Destroy: 0LI> InAlarm: > 1LI> Signalling Type: FXS Kewlstart > Radio: 0*CLI> Owner: <None> Real: > <None>> Callwait: <None> Threeway: > <None> Confno: -1LI> Propagated > Conference: -1 Real in conference: 0 > DSP: no1*CLI> Busy Detection: no TDD: > no1*CLI> Relax DTMF: no > Dialing/CallwaitCAS: 0/0 Default law: > ulaw Fax Handled: no Pulse phone: no > DND: no1*CLI> Echo Cancellation: > trixbox1128 taps trixbox1(unless TDM > bridged) currently OFF Actual > Confinfo: Num/0, Mode/0x0000 Actual > Confmute: No > Hookstate (FXS only): Onhook I have configured a "ZAP Trunk (DAHDI compatibility Mode)" with the ZAP identifier 1 and an outbound route, but when ever I try to make an external call via it I get the "All Circuits are busy now, please try your call again later message". The FXO module is directly connected to our phone line from BT via a BT-RJ11 cable. I'm guessing I've missed a configuration step somewhere but no idea where, any help greatly appreciated.

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• Automating the choice between JPEG and PNG with a script

  - by MHC

  Choosing the right format to save your images in is crucial for preserving image quality and reducing artifacts. Different formats follow different compression methods and come with their own set of advantages and disadvantages. JPG, for instance is suited for real life photographs that are rich in color gradients. The lossless PNG, on the other hand, is far superior when it comes to schematic figures: Picking the right format can be a chore when working with a large number of files. That's why I would love to find a way to automate it. A little bit of background on my particular use case: I am working on a number of handouts for a series of lectures at my unversity. The handouts are rich in figures, which I have to extract from PDF-formatted slides. Extracting these images gives me lossless PNGs, which are needlessly large at times. Converting these particular files to JPEG can reduce their size to up to less than 20% of their original file size, while maintaining the same quality. This is important as working with hundreds of large images in word processors is pretty crash-prone. Batch converting all extracted PNGs to JPEGs is not an option I am willing to follow, as many if not most images are better suited to be formatted as PNGs. Converting these would result in insignificant size reductions and sometimes even increases in filesize - that's at least what my test runs showed. What we can take from this is that file size after compression can serve as an indicator on what format is suited best for a particular image. It's not a particularly accurate predictor, but works well enough. So why not use it in form of a script: I included inotifywait because I would prefer for the script be executed automatically as soon as I drag an extracted image into a folder. This is a simpler version of the script that I've been using for the last couple of weeks: #!/bin/bash inotifywait -m --format "%w%f" --exclude '.jpg' -r -e create -e moved_to --fromfile '/home/MHC/.scripts/Workflow/Conversion/include_inotifywait' | while read file; do mogrify -format jpg -quality 92 "$file" done The advanced version of the script would have to be able to handle spaces in file names and directory names preserve the original file names flatten PNG images if an alpha value is set compare the file size between the temporary converted image and its original determine if the difference is greater than a given precentage act accordingly The actual conversion could be done with imagemagick tools: convert -quality 92 -flatten -background white file.png file.jpg Unfortunately, my bash skills aren't even close to advanced enough to convert the scheme above into an actual script, but I am sure many of you can. My reputation points on here are pretty low, but I will gladly award the most helpful answer with the highest bounty I can set. References: http://www.formortals.com/introducing-cnb-imageguide/, http://www.turnkeylinux.org/blog/png-vs-jpg Edit: Also see my comments below for some more information on why I think this script would be the best solution to the problem I am facing.

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• ESXi 5.1 ghettoVCB stuck at Clone: 10% done

  - by stormdrain

  Trying to run ghettoVCB for the first time here. I am using a NAS that is set up as a datastore on the host. I did a dry run and it completed without error. The VM is ~500GB and there is only one on the host that I'm trying to backup. I proceeded to start the actual backup: ./ghettoVCB.sh -m vmname -g ghettoVCB.conf It goes though the config and looks like it's taking off: 2013-10-24 11:43:19 -- info: CONFIG - USING GLOBAL GHETTOVCB CONFIGURATION FILE = ghettoVCB.conf 2013-10-24 11:43:19 -- info: CONFIG - VERSION = 2013_01_11_0 2013-10-24 11:43:19 -- info: CONFIG - GHETTOVCB_PID = 17398616 2013-10-24 11:43:19 -- info: CONFIG - VM_BACKUP_VOLUME = /vmfs/volumes/nas2tb-001/esxi4 2013-10-24 11:43:19 -- info: CONFIG - VM_BACKUP_ROTATION_COUNT = 3 2013-10-24 11:43:19 -- info: CONFIG - VM_BACKUP_DIR_NAMING_CONVENTION = 2013-10-24_11-43-18 2013-10-24 11:43:19 -- info: CONFIG - DISK_BACKUP_FORMAT = thin 2013-10-24 11:43:19 -- info: CONFIG - POWER_VM_DOWN_BEFORE_BACKUP = 0 2013-10-24 11:43:19 -- info: CONFIG - ENABLE_HARD_POWER_OFF = 0 2013-10-24 11:43:19 -- info: CONFIG - ITER_TO_WAIT_SHUTDOWN = 4 2013-10-24 11:43:19 -- info: CONFIG - POWER_DOWN_TIMEOUT = 5 2013-10-24 11:43:19 -- info: CONFIG - SNAPSHOT_TIMEOUT = 15 2013-10-24 11:43:19 -- info: CONFIG - LOG_LEVEL = info 2013-10-24 11:43:19 -- info: CONFIG - BACKUP_LOG_OUTPUT = /tmp/ghettoVCB-2013-10-24_11-43-18-17398616.log 2013-10-24 11:43:19 -- info: CONFIG - ENABLE_COMPRESSION = 0 2013-10-24 11:43:19 -- info: CONFIG - VM_SNAPSHOT_MEMORY = 0 2013-10-24 11:43:19 -- info: CONFIG - VM_SNAPSHOT_QUIESCE = 0 2013-10-24 11:43:19 -- info: CONFIG - ALLOW_VMS_WITH_SNAPSHOTS_TO_BE_BACKEDUP = 0 2013-10-24 11:43:19 -- info: CONFIG - VMDK_FILES_TO_BACKUP = all 2013-10-24 11:43:19 -- info: CONFIG - VM_SHUTDOWN_ORDER = 2013-10-24 11:43:19 -- info: CONFIG - VM_STARTUP_ORDER = 2013-10-24 11:43:19 -- info: CONFIG - EMAIL_LOG = 0 2013-10-24 11:43:19 -- info: 2013-10-24 11:43:22 -- info: Initiate backup for vmname 2013-10-24 11:43:22 -- info: Creating Snapshot "ghettoVCB-snapshot-2013-10-24" for serv2 Destination disk format: VMFS thin-provisioned Cloning disk '/vmfs/volumes/esxi4-storage/vmname/vmname_1.vmdk'... Clone: 10% done. and it's been that way for over an hour now. Stuck at Clone: 10% done.. Thing is: I can see the vmdk on the NAS. And it looks like almost the whole thing is there. On the NAS it's showing ~430GB but on vSphere Client Summary is shows as 507GB. I don't see the vmdk on the NAS growing any more. The logfile mimics some of the above and is sitting at "Creating Snapshot..." and nothing else is coming in. Is the vmdk on the NAS showing all those GB because of the provisioning or something? i.e. is the size of the file not necessarily indicative of the amount of actual data that has been copied? Is there are reason it might be "Stuck" at 10%? i.e. could it really be taking this long? Any other tips? Thanks. Edit: as soon as I hit the Submit button, I glance over to see that it has incremented to 11% done. Good to know it'll be complete sometime around when the sun explodes.

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