byte order - Page 82 - Developer IT

Java to JavaScript (Encryptation related)

- by balexandre

Hi guys, I'm having dificulties to get the same string in Javascript and I'm thinking that I'm doing something wrong... Java code: import java.io.UnsupportedEncodingException; import java.security.MessageDigest; import java.security.NoSuchAlgorithmException; import java.util.Date; import java.util.GregorianCalendar; import sun.misc.BASE64Encoder; private static String getBase64Code(String input) throws UnsupportedEncodingException, NoSuchAlgorithmException { String base64 = ""; byte[] txt = input.getBytes("UTF8"); byte[] text = new byte[txt.length+3]; text[0] = (byte)239; text[1] = (byte)187; text[2] = (byte)191; for(int i=0; i<txt.length; i++) text[i+3] = txt[i]; MessageDigest md = MessageDigest.getInstance("MD5"); md.update(text); byte digest[] = md.digest(); BASE64Encoder encoder = new BASE64Encoder(); base64 = encoder.encode(digest); return base64; } I'm trying this using Paj's MD5 script as well Farhadi Base 64 Encode script but my tests fail completly :( my code: function CalculateCredentialsSecret(type, user, pwd) { var days = days_between(new Date(), new Date(2000, 1, 1)); var str = type.toUpperCase() + user.toUpperCase() + pwd.toUpperCase() + days; var md5 = any_md5('', str); var b64 = base64Encode(md5); return encodeURIComponent(b64); } Does anyone know how can I convert this Java method into a Javascript one? Thank you

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SOA Suite 11g Native Format Builder Complex Format Example

- by bob.webster

This rather long posting details the steps required to process a grouping of fixed length records using Format Builder. If it’s 10 pm and you’re feeling beat you might want to leave this until tomorrow. But if it’s 10 pm and you need to get a Format Builder Complex template done, read on… The goal is to process individual orders from a file using the 11g File Adapter and Format Builder Sample Data =========== 001Square Widget 0245.98 102Triagular Widget 1120.00 403Circular Widget 0099.45 ORD8898302/01/2011 301Hexagon Widget 1150.98 ORD6735502/01/2011 The records are fixed length records representing a number of logical Order records. Each order record consists of a number of item records starting with a 3 digit number, followed by a single Summary Record which starts with the constant ORD. How can this file be processed so that the first poll returns the first order? 001Square Widget 0245.98 102Triagular Widget 1120.00 403Circular Widget 0099.45 ORD8898302/01/2011 And the second poll returns the second order? 301Hexagon Widget 1150.98 ORD6735502/01/2011 Note: if you need more than one order per poll, that’s also possible, see the “Multiple Messages” field in the “File Adapter Step 6 of 9” snapshot further down. To follow along with this example you will need - Studio Edition Version 11.1.1.4.0 with the - SOA Extension for JDeveloper 11.1.1.4.0 installed Both can be downloaded from here: http://www.oracle.com/technetwork/middleware/soasuite/downloads/index.html You will not need a running WebLogic Server domain to complete the steps and Format Builder tests in this article. Start with a SOA Composite containing a File Adapter The Format Builder is part of the File Adapter so start by creating a new SOA Project and Composite. Here is a quick summary for those not familiar with these steps - Start JDeveloper - From the Main Menu choose File->New - In the New Gallery window that opens Expand the “General” category and Select the Applications node. Then choose SOA Application from the Items section on the right. Finally press the OK button. - In Step 1 of the “Create SOA Application wizard” that appears enter an Application Name and an Directory of your choice, then press the Next button. - In Step 2 of the “Create SOA Application wizard”, press the Next button leaving all entries as defaulted. - In Step 3 of the “Create SOA Application wizard”, Enter a composite name of your choice and Press the Finish Button These steps result in a new Application and SOA Project. The SOA Project contains a composite.xml file which is opened and shown below. For our example we have not defined a Mediator or a BPEL process to minimize the steps, but one or the other would eventually be needed to use the File Adapter we are about to create. Drag and drop the File Adapter icon from the Component Pallette onto either the LEFT side of the diagram under “Exposed Services” or the right side under “External References”. (See the Green Circle in the image below). Placing the adapter on the left side would indicate the file being processed is inbound to the composite, if the adapter is placed on the right side then the data is outbound to a file. Note that the same Format Builder definition can be used in both directions. For example we could use the format with a File Adapter on the left side of the composite to parse fixed data into XML, modify the data in our Composite or BPEL process and then use the same Format Builder definition with a File adapter on the right side of the composite to write the data back out in the same fixed data format When the File Adapter is dropped on the Composite the File Adapter Wizard Appears. Skip Past the first page, Step 1 of 9 by pressing the Next button. In Step 2 enter a service name of your choice as shown below, then press Next When the Native Format Builder appears, skip the welcome page by pressing next. Also press the Next button to accept the settings on Step 3 of 9 On Step 4, select Read File and press the Next button as shown below. On Step 5 enter a directory that will contain a file with the input data, then Press the Next button as shown below. In step 6, enter *.txt or another file format to select input files from the input directory mentioned in step 5. ALSO check the “Files contain Multiple Messages” checkbox and set the “Publish Messages in Batches of” field to 1. The value can be set higher to increase the number of logical order group records returned on each poll of the file adapter. In other words, it determines the number of Orders that will be sent to each instance of a Mediator or Composite processing using the File Adapter. Skip Step 7 by pressing the Next button In Step 8 press the Gear Icon on the right side to load the Native Format Builder. Native Format Builder appears Before diving into the format, here is an overview of the process. Approach - Bottom up Assuming an Order is a grouping of item records and a summary record…. - Define a separate Complex Type for each Record Type found in the group. (One for itemRecord and one for summaryRecord) - Define a Complex Type to contain the Group of Record types defined above (LogicalOrderRecord) - Define a top level element to represent an order. (order) The order element will be of type LogicalOrderRecord Defining the Format In Step 1 select “Create new” and “Complex Type” and “Next” In Step two browse to and select a file containing the test data shown at the start of this article. A link is provided at the end of this article to download a file containing the test data. Press the Next button In Step 3 Complex types must be define for each type of input record. Select the Root-Element and Click on the Add Complex Type icon This creates a new empty complex type definition shown below. The fastest way to create the definition is to highlight the first line of the Sample File data and drag the line onto the <new_complex_type> Format Builder introspects the data and provides a grid to define additional fields. Change the “Complex Type Name” to “itemRecord” Then click on the ruler to indicate the position of fixed columns. Drag the red triangle icons to the exact columns if necessary. Double click on an existing red triangle to remove an unwanted entry. In the case below fields are define in columns 0-3, 4-28, 29-eol When the field definitions are correct, press the “Generate Fields” button. Field entries named C1, C2 and C3 will be created as shown below. Click on the field names and rename them from C1->itemNum, C2->itemDesc and C3->itemCost When all the fields are correctly defined press OK to save the complex type. Next, the process is repeated to define a Complex Type for the SummaryRecord. Select the Root-Element in the schema tree and press the new complex type icon Then highlight and drag the Summary Record from the sample data onto the <new_complex_type> Change the complex type name to “summaryRecord” Mark the fixed fields for Order Number and Order Date. Press the Generate Fields button and rename C1 and C2 to itemNum and orderDate respectively. The last complex type to be defined is a type to hold the group of items and the summary record. Select the Root-Element in the schema tree and click the new complex type icon Select the “<new_complex_type>” entry and click the pencil icon On the Complex Type Details page change the name and type of each input field. Change line 1 to be named item and set the Type to “itemRecord” Change line 2 to be named summary and set the Type to “summaryRecord” We also need to indicate that itemRecords repeat in the input file. Click the pencil icon at the right side of the item line. On the Edit Details page change the “Max Occurs” entry from 1 to UNBOUNDED. We also need to indicate how to identify an itemRecord. Since each item record has “.” in column 32 we can use this fact to differentiate an item record from a summary record. Change the “Look Ahead” field to value 32 and enter a period in the “Look For” field Press the OK button to save entry. Finally, its time to create a top level element to represent an order. Select the “Root-Element” in the schema tree and press the New element icon Click on the <new_element> and press the pencil icon. Set the Element Name to “order” and change the Data Type to “logicalOrderRecord” Press the OK button to save the element definition. The final definition should match the screenshot below. Press the Next Button to view the definition source. Press the Test Button to test the definition Press the Green Triangle Icon to run the test. And we are presented with an unwelcome error. The error states that the processor ran out of data while working through the definition. The processor was unable to differentiate between itemRecords and summaryRecords and therefore treated the entire file as a list of itemRecords. At end of file, the “summary” portion of the logicalOrderRecord remained unprocessed but mandatory. This root cause of this error is the loss of our “lookAhead” definition used to identify itemRecords. This appears to be a bug in the Native Format Builder 11.1.1.4.0 Luckily, a simple workaround exists. Press the Cancel button and return to the “Step 4 of 4” Window. Manually add nxsd:lookAhead="32" nxsd:lookFor="." attributes after the maxOccurs attribute of the item element. as shown in the highlighted text below. When the lookAhead and lookFor attributes have been added Press the Test button and on the Test page press the Green Triangle. The test is now successful, the first order in the file is returned by the File Adapter. Below is a complete listing of the Result XML from the right column of the screen above Try running it The downloaded input test file and completed schema file can be used for testing without following all the Native Format Builder steps in this example. Use the following link to download a file containing the sample data. Download Sample Input Data This is the best approach rather than cutting and pasting the input data at the top of the article. Since the data is fixed length it’s very important to watch out for trailing spaces in the data and to ensure an eol character at the end of every line. The download file is correctly formatted. The final schema definition can be downloaded at the following link Download Completed Schema Definition - Save the inputData.txt file to a known location like the xsd folder in your project. - Save the inputData_6.xsd file to the xsd folder in your project. - At step 1 in the Native Format Builder wizard (as shown above) check the “Edit existing” radio button, then browse and select the inputData_6.xsd file - At step 2 of the Format Builder configuration Wizard (as shown above) supply the path and filename for the inputData.txt file. - You can then proceed to the test page and run a test. - Remember the wizard bug will drop the lookAhead and lookFor attributes, you will need to manually add nxsd:lookAhead="32" nxsd:lookFor="." after the maxOccurs attribute of the item element in the LogicalOrderRecord Complex Type. (as shown above) Good Luck with your Format Project

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Adding Unobtrusive Validation To MVCContrib Fluent Html

- by srkirkland

ASP.NET MVC 3 includes a new unobtrusive validation strategy that utilizes HTML5 data-* attributes to decorate form elements. Using a combination of jQuery validation and an unobtrusive validation adapter script that comes with MVC 3, those attributes are then turned into client side validation rules. A Quick Introduction to Unobtrusive Validation To quickly show how this works in practice, assume you have the following Order.cs class (think Northwind) [If you are familiar with unobtrusive validation in MVC 3 you can skip to the next section]: public class Order : DomainObject { [DataType(DataType.Date)] public virtual DateTime OrderDate { get; set; } [Required] [StringLength(12)] public virtual string ShipAddress { get; set; } [Required] public virtual Customer OrderedBy { get; set; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Note the System.ComponentModel.DataAnnotations attributes, which provide the validation and metadata information used by ASP.NET MVC 3 to determine how to render out these properties. Now let’s assume we have a form which can edit this Order class, specifically let’s look at the ShipAddress property: @Html.LabelFor(x => x.Order.ShipAddress) @Html.EditorFor(x => x.Order.ShipAddress) @Html.ValidationMessageFor(x => x.Order.ShipAddress) .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Now the Html.EditorFor() method is smart enough to look at the ShipAddress attributes and write out the necessary unobtrusive validation html attributes. Note we could have used Html.TextBoxFor() or even Html.TextBox() and still retained the same results. If we view source on the input box generated by the Html.EditorFor() call, we get the following: <input type="text" value="Rua do Paço, 67" name="Order.ShipAddress" id="Order_ShipAddress" data-val-required="The ShipAddress field is required." data-val-length-max="12" data-val-length="The field ShipAddress must be a string with a maximum length of 12." data-val="true" class="text-box single-line input-validation-error"> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } As you can see, we have data-val-* attributes for both required and length, along with the proper error messages and additional data as necessary (in this case, we have the length-max=”12”). And of course, if we try to submit the form with an invalid value, we get an error on the client: Working with MvcContrib’s Fluent Html The MvcContrib project offers a fluent interface for creating Html elements which I find very expressive and useful, especially when it comes to creating select lists. Let’s look at a few quick examples: @this.TextBox(x => x.FirstName).Class("required").Label("First Name:") @this.MultiSelect(x => x.UserId).Options(ViewModel.Users) @this.CheckBox("enabled").LabelAfter("Enabled").Title("Click to enable.").Styles(vertical_align => "middle") @(this.Select("Order.OrderedBy").Options(Model.Customers, x => x.Id, x => x.CompanyName) .Selected(Model.Order.OrderedBy != null ? Model.Order.OrderedBy.Id : "") .FirstOption(null, "--Select A Company--") .HideFirstOptionWhen(Model.Order.OrderedBy != null) .Label("Ordered By:")) .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } These fluent html helpers create the normal html you would expect, and I think they make life a lot easier and more readable when dealing with complex markup or select list data models (look ma: no anonymous objects for creating class names!). Of course, the problem we have now is that MvcContrib’s fluent html helpers don’t know about ASP.NET MVC 3’s unobtrusive validation attributes and thus don’t take part in client validation on your page. This is not ideal, so I wrote a quick helper method to extend fluent html with the knowledge of what unobtrusive validation attributes to include when they are rendered. Extending MvcContrib’s Fluent Html Before posting the code, there are just a few things you need to know. The first is that all Fluent Html elements implement the IElement interface (MvcContrib.FluentHtml.Elements.IElement), and the second is that the base System.Web.Mvc.HtmlHelper has been extended with a method called GetUnobtrusiveValidationAttributes which we can use to determine the necessary attributes to include. With this knowledge we can make quick work of extending fluent html: public static class FluentHtmlExtensions { public static T IncludeUnobtrusiveValidationAttributes<T>(this T element, HtmlHelper htmlHelper) where T : MvcContrib.FluentHtml.Elements.IElement { IDictionary<string, object> validationAttributes = htmlHelper .GetUnobtrusiveValidationAttributes(element.GetAttr("name")); foreach (var validationAttribute in validationAttributes) { element.SetAttr(validationAttribute.Key, validationAttribute.Value); } return element; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } The code is pretty straight forward – basically we use a passed HtmlHelper to get a list of validation attributes for the current element and then add each of the returned attributes to the element to be rendered. The Extension In Action Now let’s get back to the earlier ShipAddress example and see what we’ve accomplished. First we will use a fluent html helper to render out the ship address text input (this is the ‘before’ case): @this.TextBox("Order.ShipAddress").Label("Ship Address:").Class("class-name") .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } And the resulting HTML: <label id="Order_ShipAddress_Label" for="Order_ShipAddress">Ship Address:</label> <input type="text" value="Rua do Paço, 67" name="Order.ShipAddress" id="Order_ShipAddress" class="class-name"> Now let’s do the same thing except here we’ll use the newly written extension method: @this.TextBox("Order.ShipAddress").Label("Ship Address:") .Class("class-name").IncludeUnobtrusiveValidationAttributes(Html) .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } And the resulting HTML: <label id="Order_ShipAddress_Label" for="Order_ShipAddress">Ship Address:</label> <input type="text" value="Rua do Paço, 67" name="Order.ShipAddress" id="Order_ShipAddress" data-val-required="The ShipAddress field is required." data-val-length-max="12" data-val-length="The field ShipAddress must be a string with a maximum length of 12." data-val="true" class="class-name"> .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Excellent! Now we can continue to use unobtrusive validation and have the flexibility to use ASP.NET MVC’s Html helpers or MvcContrib’s fluent html helpers interchangeably, and every element will participate in client side validation. Wrap Up Overall I’m happy with this solution, although in the best case scenario MvcContrib would know about unobtrusive validation attributes and include them automatically (of course if it is enabled in the web.config file). I know that MvcContrib allows you to author global behaviors, but that requires changing the base class of your views, which I am not willing to do. Enjoy!

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C#/.NET Fundamentals: Choosing the Right Collection Class

- by James Michael Hare

The .NET Base Class Library (BCL) has a wide array of collection classes at your disposal which make it easy to manage collections of objects. While it's great to have so many classes available, it can be daunting to choose the right collection to use for any given situation. As hard as it may be, choosing the right collection can be absolutely key to the performance and maintainability of your application! This post will look at breaking down any confusion between each collection and the situations in which they excel. We will be spending most of our time looking at the System.Collections.Generic namespace, which is the recommended set of collections. The Generic Collections: System.Collections.Generic namespace The generic collections were introduced in .NET 2.0 in the System.Collections.Generic namespace. This is the main body of collections you should tend to focus on first, as they will tend to suit 99% of your needs right up front. It is important to note that the generic collections are unsynchronized. This decision was made for performance reasons because depending on how you are using the collections its completely possible that synchronization may not be required or may be needed on a higher level than simple method-level synchronization. Furthermore, concurrent read access (all writes done at beginning and never again) is always safe, but for concurrent mixed access you should either synchronize the collection or use one of the concurrent collections. So let's look at each of the collections in turn and its various pros and cons, at the end we'll summarize with a table to help make it easier to compare and contrast the different collections. The Associative Collection Classes Associative collections store a value in the collection by providing a key that is used to add/remove/lookup the item. Hence, the container associates the value with the key. These collections are most useful when you need to lookup/manipulate a collection using a key value. For example, if you wanted to look up an order in a collection of orders by an order id, you might have an associative collection where they key is the order id and the value is the order. The Dictionary<TKey,TVale> is probably the most used associative container class. The Dictionary<TKey,TValue> is the fastest class for associative lookups/inserts/deletes because it uses a hash table under the covers. Because the keys are hashed, the key type should correctly implement GetHashCode() and Equals() appropriately or you should provide an external IEqualityComparer to the dictionary on construction. The insert/delete/lookup time of items in the dictionary is amortized constant time - O(1) - which means no matter how big the dictionary gets, the time it takes to find something remains relatively constant. This is highly desirable for high-speed lookups. The only downside is that the dictionary, by nature of using a hash table, is unordered, so you cannot easily traverse the items in a Dictionary in order. The SortedDictionary<TKey,TValue> is similar to the Dictionary<TKey,TValue> in usage but very different in implementation. The SortedDictionary<TKey,TValye> uses a binary tree under the covers to maintain the items in order by the key. As a consequence of sorting, the type used for the key must correctly implement IComparable<TKey> so that the keys can be correctly sorted. The sorted dictionary trades a little bit of lookup time for the ability to maintain the items in order, thus insert/delete/lookup times in a sorted dictionary are logarithmic - O(log n). Generally speaking, with logarithmic time, you can double the size of the collection and it only has to perform one extra comparison to find the item. Use the SortedDictionary<TKey,TValue> when you want fast lookups but also want to be able to maintain the collection in order by the key. The SortedList<TKey,TValue> is the other ordered associative container class in the generic containers. Once again SortedList<TKey,TValue>, like SortedDictionary<TKey,TValue>, uses a key to sort key-value pairs. Unlike SortedDictionary, however, items in a SortedList are stored as an ordered array of items. This means that insertions and deletions are linear - O(n) - because deleting or adding an item may involve shifting all items up or down in the list. Lookup time, however is O(log n) because the SortedList can use a binary search to find any item in the list by its key. So why would you ever want to do this? Well, the answer is that if you are going to load the SortedList up-front, the insertions will be slower, but because array indexing is faster than following object links, lookups are marginally faster than a SortedDictionary. Once again I'd use this in situations where you want fast lookups and want to maintain the collection in order by the key, and where insertions and deletions are rare. The Non-Associative Containers The other container classes are non-associative. They don't use keys to manipulate the collection but rely on the object itself being stored or some other means (such as index) to manipulate the collection. The List<T> is a basic contiguous storage container. Some people may call this a vector or dynamic array. Essentially it is an array of items that grow once its current capacity is exceeded. Because the items are stored contiguously as an array, you can access items in the List<T> by index very quickly. However inserting and removing in the beginning or middle of the List<T> are very costly because you must shift all the items up or down as you delete or insert respectively. However, adding and removing at the end of a List<T> is an amortized constant operation - O(1). Typically List<T> is the standard go-to collection when you don't have any other constraints, and typically we favor a List<T> even over arrays unless we are sure the size will remain absolutely fixed. The LinkedList<T> is a basic implementation of a doubly-linked list. This means that you can add or remove items in the middle of a linked list very quickly (because there's no items to move up or down in contiguous memory), but you also lose the ability to index items by position quickly. Most of the time we tend to favor List<T> over LinkedList<T> unless you are doing a lot of adding and removing from the collection, in which case a LinkedList<T> may make more sense. The HashSet<T> is an unordered collection of unique items. This means that the collection cannot have duplicates and no order is maintained. Logically, this is very similar to having a Dictionary<TKey,TValue> where the TKey and TValue both refer to the same object. This collection is very useful for maintaining a collection of items you wish to check membership against. For example, if you receive an order for a given vendor code, you may want to check to make sure the vendor code belongs to the set of vendor codes you handle. In these cases a HashSet<T> is useful for super-quick lookups where order is not important. Once again, like in Dictionary, the type T should have a valid implementation of GetHashCode() and Equals(), or you should provide an appropriate IEqualityComparer<T> to the HashSet<T> on construction. The SortedSet<T> is to HashSet<T> what the SortedDictionary<TKey,TValue> is to Dictionary<TKey,TValue>. That is, the SortedSet<T> is a binary tree where the key and value are the same object. This once again means that adding/removing/lookups are logarithmic - O(log n) - but you gain the ability to iterate over the items in order. For this collection to be effective, type T must implement IComparable<T> or you need to supply an external IComparer<T>. Finally, the Stack<T> and Queue<T> are two very specific collections that allow you to handle a sequential collection of objects in very specific ways. The Stack<T> is a last-in-first-out (LIFO) container where items are added and removed from the top of the stack. Typically this is useful in situations where you want to stack actions and then be able to undo those actions in reverse order as needed. The Queue<T> on the other hand is a first-in-first-out container which adds items at the end of the queue and removes items from the front. This is useful for situations where you need to process items in the order in which they came, such as a print spooler or waiting lines. So that's the basic collections. Let's summarize what we've learned in a quick reference table. Collection Ordered? Contiguous Storage? Direct Access? Lookup Efficiency Manipulate Efficiency Notes Dictionary No Yes Via Key Key: O(1) O(1) Best for high performance lookups. SortedDictionary Yes No Via Key Key: O(log n) O(log n) Compromise of Dictionary speed and ordering, uses binary search tree. SortedList Yes Yes Via Key Key: O(log n) O(n) Very similar to SortedDictionary, except tree is implemented in an array, so has faster lookup on preloaded data, but slower loads. List No Yes Via Index Index: O(1) Value: O(n) O(n) Best for smaller lists where direct access required and no ordering. LinkedList No No No Value: O(n) O(1) Best for lists where inserting/deleting in middle is common and no direct access required. HashSet No Yes Via Key Key: O(1) O(1) Unique unordered collection, like a Dictionary except key and value are same object. SortedSet Yes No Via Key Key: O(log n) O(log n) Unique ordered collection, like SortedDictionary except key and value are same object. Stack No Yes Only Top Top: O(1) O(1)* Essentially same as List<T> except only process as LIFO Queue No Yes Only Front Front: O(1) O(1) Essentially same as List<T> except only process as FIFO The Original Collections: System.Collections namespace The original collection classes are largely considered deprecated by developers and by Microsoft itself. In fact they indicate that for the most part you should always favor the generic or concurrent collections, and only use the original collections when you are dealing with legacy .NET code. Because these collections are out of vogue, let's just briefly mention the original collection and their generic equivalents: ArrayList A dynamic, contiguous collection of objects. Favor the generic collection List<T> instead. Hashtable Associative, unordered collection of key-value pairs of objects. Favor the generic collection Dictionary<TKey,TValue> instead. Queue First-in-first-out (FIFO) collection of objects. Favor the generic collection Queue<T> instead. SortedList Associative, ordered collection of key-value pairs of objects. Favor the generic collection SortedList<T> instead. Stack Last-in-first-out (LIFO) collection of objects. Favor the generic collection Stack<T> instead. In general, the older collections are non-type-safe and in some cases less performant than their generic counterparts. Once again, the only reason you should fall back on these older collections is for backward compatibility with legacy code and libraries only. The Concurrent Collections: System.Collections.Concurrent namespace The concurrent collections are new as of .NET 4.0 and are included in the System.Collections.Concurrent namespace. These collections are optimized for use in situations where multi-threaded read and write access of a collection is desired. The concurrent queue, stack, and dictionary work much as you'd expect. The bag and blocking collection are more unique. Below is the summary of each with a link to a blog post I did on each of them. ConcurrentQueue Thread-safe version of a queue (FIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentStack Thread-safe version of a stack (LIFO). For more information see: C#/.NET Little Wonders: The ConcurrentStack and ConcurrentQueue ConcurrentBag Thread-safe unordered collection of objects. Optimized for situations where a thread may be bother reader and writer. For more information see: C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection ConcurrentDictionary Thread-safe version of a dictionary. Optimized for multiple readers (allows multiple readers under same lock). For more information see C#/.NET Little Wonders: The ConcurrentDictionary BlockingCollection Wrapper collection that implement producers & consumers paradigm. Readers can block until items are available to read. Writers can block until space is available to write (if bounded). For more information see C#/.NET Little Wonders: The ConcurrentBag and BlockingCollection Summary The .NET BCL has lots of collections built in to help you store and manipulate collections of data. Understanding how these collections work and knowing in which situations each container is best is one of the key skills necessary to build more performant code. Choosing the wrong collection for the job can make your code much slower or even harder to maintain if you choose one that doesn’t perform as well or otherwise doesn’t exactly fit the situation. Remember to avoid the original collections and stick with the generic collections. If you need concurrent access, you can use the generic collections if the data is read-only, or consider the concurrent collections for mixed-access if you are running on .NET 4.0 or higher. Tweet Technorati Tags: C#,.NET,Collecitons,Generic,Concurrent,Dictionary,List,Stack,Queue,SortedList,SortedDictionary,HashSet,SortedSet

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How do I use Java to sort surnames in alphabetical order from file to file?

- by user577939

I have written this code and don't know how to sort surnames in alphabetical order from my file to another file. import java.io.*; import java.util.*; class Asmuo { String pavarde; String vardas; long buvLaikas; int atv1; int atv2; int atv3; } class Irasas { Asmuo duom; Irasas kitas; } class Sarasas { private Irasas p; Sarasas() { p = null; } Irasas itrauktiElementa(String pv, String v, long laikas, int d0, int d1, int d2) { String pvrd, vrd; int data0; int data1; int data2; long lks; lks = laikas; pvrd = pv; vrd = v; data0 = d0; data1 = d1; data2 = d2; Irasas r = new Irasas(); r.duom = new Asmuo(); uzpildymasDuomenimis(r, pvrd, vrd, lks, d0, d1, d2); r.kitas = p; p = r; return r; } void uzpildymasDuomenimis(Irasas r, String pv, String v, long laik, int d0, int d1, int d2) { r.duom.pavarde = pv; r.duom.vardas = v; r.duom.atv1 = d0; r.duom.buvLaikas = laik; r.duom.atv2 = d1; r.duom.atv3 = d2; } void spausdinti() { Irasas d = p; int i = 0; try { FileWriter fstream = new FileWriter("rez.txt"); BufferedWriter rez = new BufferedWriter(fstream); while (d != null) { System.out.println(d.duom.pavarde + " " + d.duom.vardas + " " + d.duom.buvLaikas + " " + d.duom.atv1 + " " + d.duom.atv2 + " " + d.duom.atv3); rez.write(d.duom.pavarde + " " + d.duom.vardas + " " + d.duom.buvLaikas + " " + d.duom.atv1 + " " + d.duom.atv2 + " " + d.duom.atv3 + "\n"); d = d.kitas; i++; } rez.close(); } catch (Exception e) { System.err.println("Error: " + e.getMessage()); } } } public class Gyventojai { public static void main(String args[]) { Sarasas sar = new Sarasas(); Calendar atv = Calendar.getInstance(); Calendar isv = Calendar.getInstance(); try { FileInputStream fstream = new FileInputStream("duom.txt"); DataInputStream in = new DataInputStream(fstream); BufferedReader br = new BufferedReader(new InputStreamReader(in)); String eil; while ((eil = br.readLine()) != null) { String[] cells = eil.split(" "); String pvrd = cells[0]; String vrd = cells[1]; atv.set(Integer.parseInt(cells[2]), Integer.parseInt(cells[3]), Integer.parseInt(cells[4])); isv.set(Integer.parseInt(cells[5]), Integer.parseInt(cells[6]), Integer.parseInt(cells[7])); long laik = (isv.getTimeInMillis() - atv.getTimeInMillis()) / (24 * 60 * 60 * 1000); int d0 = Integer.parseInt(cells[2]); int d1 = Integer.parseInt(cells[3]); int d2 = Integer.parseInt(cells[4]); sar.itrauktiElementa(pvrd, vrd, laik, d0, d1, d2); } in.close(); } catch (Exception e) { System.err.println("Error: " + e.getMessage()); } sar.spausdinti(); } }

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c++ to vb.net , problem with callback function

- by johan

I'm having a hard time here trying to find a solution for my problem. I'm trying to convert a client API funktion from C++ to VB.NET, and i think have some problems with the callback function. parts of the C++ code: typedef struct{ BYTE m_bRemoteChannel; BYTE m_bSendMode; BYTE m_nImgFormat; // =0 cif ; = 1 qcif char *m_sIPAddress; char *m_sUserName; char *m_sUserPassword; BOOL m_bUserCheck; HWND m_hShowVideo; }CLIENT_VIDEOINFO, *PCLIENT_VIDEOINFO; CPLAYER_API LONG __stdcall MP4_ClientStart(PCLIENT_VIDEOINFO pClientinfo,void(CALLBACK *ReadDataCallBack)(DWORD nPort,UCHAR *pPacketBuffer,DWORD nPacketSize)); void CALLBACK ReadDataCallBack(DWORD nPort,UCHAR *pPacketBuffer,DWORD nPacketSize) { TRACE("%d\n",nPacketSize); } ..... aa5.m_sUserName = "123"; aa5.m_sUserPassword="w"; aa5.m_bUserCheck = TRUE; MP4_ClientSetTTL(64); nn1 = MP4_ClientStart(&aa5,ReadDataCallBack); if (nn1 == -1) { MessageBox("error"); return; } SDK description: MP4_ClientStart This function starts a connection. The format of the call is: LONG __stdcall MP4_ClientStart(PCLIENT_VIDEOINFO pClientinfo, void(*ReadDataCallBack)(DWORD nChannel,UCHAR *pPacketBuffer,DWORD nPacketSize)) Parameters pClientinfo holds the information. of this connection. nChannel holds the channel of card. pPacketBuffer holds the pointer to the receive buffer. nPacketSize holds the length of the receive buffer. Return Values If the function succeeds the return value is the context of this connection. If the function fails the return value is -1. Remarks typedef struct{ BYTE m_bRemoteChannel; BYTE m_bSendMode; BYTE m_bImgFormat; char *m_sIPAddress; char *m_sUserName; char *m_sUserPassword; BOOL m_bUserCheck; HWND m_hShowVideo; } CLIENT_VIDEOINFO, * PCLIENT_VIDEOINFO; m_bRemoteChannel holds the channel which the client wants to connect to. m_bSendMode holds the network mode of the connection. m_bImgFormat : Image format, 0 is main channel video, 1 is sub channel video m_sIPAddress holds the IP address of the server. m_sUserName holds the user’s name. m_sUserPassword holds the user’s password. m_bUserCheck holds the value whether sends the user’s name and password or not. m_hShowVideo holds Handle for this video window. If m_hShowVideo holds NULL, the client can be record only without decoder. If m_bUserCheck is FALSE, we will send m_sUserName and m_sUserPassword as NULL, else we will send each 50 bytes. The length of m_sIPAddress and m_sUserName must be more than 50 bytes. ReadDataCallBack: When the library receives a packet from a server, this callback is called. My VB.Net code: Imports System.Runtime.InteropServices Public Class Form1 Const WM_USER = &H400 Public Structure CLIENT_VIDEOINFO Public m_bRemoteChannel As Byte Public m_bSendMode As Byte Public m_bImgFormat As Byte Public m_sIPAddress As String Public m_sUserName As String Public m_sUserPassword As String Public m_bUserCheck As Boolean Public m_hShowVideo As Long 'hWnd End Structure Public Declare Function MP4_ClientSetNetPort Lib "hikclient.dll" (ByVal dServerPort As Integer, ByVal dClientPort As Integer) As Boolean Public Declare Function MP4_ClientStartup Lib "hikclient.dll" (ByVal nMessage As UInteger, ByVal hWnd As System.IntPtr) As Boolean <DllImport("hikclient.dll")> Public Shared Function MP4_ClientStart(ByVal Clientinfo As CLIENT_VIDEOINFO, ByRef ReadDataCallBack As CALLBACKdel) As Long End Function Public Delegate Sub CALLBACKdel(ByVal nPort As Long, <MarshalAs(UnmanagedType.LPArray)> ByRef pPacketBuffer As Byte(), ByVal nPacketSize As Long) Public Sub CALLBACK(ByVal nPort As Long, <MarshalAs(UnmanagedType.LPArray)> ByRef pPacketBuffer As Byte(), ByVal nPacketSize As Long) End Sub Public mydel As New CALLBACKdel(AddressOf CALLBACK) Private Sub Form1_Load(ByVal sender As System.Object, ByVal e As System.EventArgs) Handles MyBase.Load Dim Clientinfo As New CLIENT_VIDEOINFO() Clientinfo.m_bRemoteChannel = 0 Clientinfo.m_bSendMode = 0 Clientinfo.m_bImgFormat = 0 Clientinfo.m_sIPAddress = "193.168.1.100" Clientinfo.m_sUserName = "1" Clientinfo.m_sUserPassword = "a" Clientinfo.m_bUserCheck = False Clientinfo.m_hShowVideo = Me.Handle 'Nothing MP4_ClientSetNetPort(850, 850) MP4_ClientStartup(WM_USER + 1, Me.Handle) MP4_ClientStart(Clientinfo, mydel) End Sub End Class here is some other examples of the code in: C# http://blog.csdn.net/nenith1981/archive/2007/09/17/1787692.aspx VB ://read.pudn.com/downloads70/sourcecode/graph/250633/MD%E5%AE%A2%E6%88%B7%E7%AB%AF%28VB%29/hikclient.bas__.htm ://read.pudn.com/downloads70/sourcecode/graph/250633/MD%E5%AE%A2%E6%88%B7%E7%AB%AF%28VB%29/Form1.frm__.htm Delphi ://read.pudn.com/downloads91/sourcecode/multimedia/streaming/349759/Delphi_client/Unit1.pas__.htm

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HTML, CSS: how can I merge these divs in order to use float:left property on their children ?

- by Patrick

hi, I've 2 sets of thumbnails and in each set I'm displaying them one nearby each other in 4 columns using float:left. I would like to "merge" the 2 sets (but I cannot change the html code) because I want the thumbnails of the second set floating right after the last thumbnail of the first set. In other terms, if in the last row there are only 2 thumbnails and the last 2 columns are empty, the thumbnails of the second set should fill the empty columns of the last row of the first set. This is the code... <div class="field field-type-filefield field-field-image"> <div class="field-items"> <div class="field-item odd"> <a rel="lightbox[field_image][First image<br /><br /><a href="/lancelmaat/content/stalkshow" id="node_link_text" class="active">View Image Details</a>]" href="http://localhost/lancelmaat/sites/default/files/files/projects/Stalkshow/images/LPrisPetjong.jpeg" class="lightbox-processed"><img width="89" height="89" title="" alt="First image" src="http://localhost/lancelmaat/sites/default/files/imagecache/galleryImage/files/projects/Stalkshow/images/LPrisPetjong.jpeg"></a> </div> <div class="field-item even"> <a rel="lightbox[field_image][Second image<br /><br /><a href="/lancelmaat/content/stalkshow" id="node_link_text" class="active">View Image Details</a>]" href="http://localhost/lancelmaat/sites/default/files/files/projects/Stalkshow/images/SeoulLEDScreen2a.jpeg" class="lightbox-processed"><img width="89" height="89" title="" alt="Second image" src="http://localhost/lancelmaat/sites/default/files/imagecache/galleryImage/files/projects/Stalkshow/images/SeoulLEDScreen2a.jpeg"></a> </div> <div class="field-item odd"> <a rel="lightbox[field_image][Third image<br /><br /><a href="/lancelmaat/content/stalkshow" id="node_link_text" class="active">View Image Details</a>]" href="http://localhost/lancelmaat/sites/default/files/files/projects/Stalkshow/images/SeoulSKT6.jpeg" class="lightbox-processed"><img width="89" height="89" title="" alt="Third image" src="http://localhost/lancelmaat/sites/default/files/imagecache/galleryImage/files/projects/Stalkshow/images/SeoulSKT6.jpeg"></a> </div> </div>  <div class="field field-type-filefield field-field-video"> <div class="field-items"> <div class="field-item odd"> <a rel="lightbox[field_video][Video Number 1<br /><br /><a href="/lancelmaat/content/stalkshow" id="node_link_text" class="active">View Image Details</a>]" href="http://localhost/lancelmaat/sites/default/files/files/projects/Stalkshow/videos/StalkSeoul8d1Mbps.flv" class="lightbox-processed"><img title="" alt="Video Number 1" src="http://localhost/lancelmaat/sites/default/files/imagecache/galleryVideo/files/projects/Stalkshow/videos/StalkSeoul8d1Mbps.flv"></a> </div> <div class="field-item even"> <a rel="lightbox[field_video][Video Number 2<br /><br /><a href="/lancelmaat/content/stalkshow" id="node_link_text" class="active">View Image Details</a>]" href="http://localhost/lancelmaat/sites/default/files/files/projects/Stalkshow/videos/stalkshowdvd21Mbps.flv" class="lightbox-processed"><img title="" alt="Video Number 2" src="http://localhost/lancelmaat/sites/default/files/imagecache/galleryVideo/files/projects/Stalkshow/videos/stalkshowdvd21Mbps.flv"></a> </div> <div class="field-item odd"> <a rel="lightbox[field_video][Video Number 3<br /><br /><a href="/lancelmaat/content/stalkshow" id="node_link_text" class="active">View Image Details</a>]" href="http://localhost/lancelmaat/sites/default/files/files/projects/Stalkshow/videos/StalkShowMoscow1Mbps.flv" class="lightbox-processed"><img title="" alt="Video Number 3" src="http://localhost/lancelmaat/sites/default/files/imagecache/galleryVideo/files/projects/Stalkshow/videos/StalkShowMoscow1Mbps.flv"></a> </div> </div> </div> How can I merge these divs in order to use float:left property on their children ? thanks

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snort analysis of wireshark capture

- by Ben Voigt

I'm trying to identify trouble users on our network. ntop identifies high traffic and high connection users, but malware doesn't always need high bandwidth to really mess things up. So I am trying to do offline analysis with snort (don't want to burden the router with inline analysis of 20 Mbps traffic). Apparently snort provides a -r option for this purpose, but I can't get the analysis to run. The analysis system is gentoo, amd64, in case that makes any difference. I've already used oinkmaster to download the latest IDS signatures. But when I try to run snort, I keep getting the following error: % snort -V ,,_ -*> Snort! <*- o" )~ Version 2.9.0.3 IPv6 GRE (Build 98) x86_64-linux '''' By Martin Roesch & The Snort Team: http://www.snort.org/snort/snort-team Copyright (C) 1998-2010 Sourcefire, Inc., et al. Using libpcap version 1.1.1 Using PCRE version: 8.11 2010-12-10 Using ZLIB version: 1.2.5 %> snort -v -r jan21-for-snort.cap -c /etc/snort/snort.conf -l ~/snortlog/ (snip) 273 out of 1024 flowbits in use. [ Port Based Pattern Matching Memory ] +- [ Aho-Corasick Summary ] ------------------------------------- | Storage Format : Full-Q | Finite Automaton : DFA | Alphabet Size : 256 Chars | Sizeof State : Variable (1,2,4 bytes) | Instances : 314 | 1 byte states : 304 | 2 byte states : 10 | 4 byte states : 0 | Characters : 69371 | States : 58631 | Transitions : 3471623 | State Density : 23.1% | Patterns : 3020 | Match States : 2934 | Memory (MB) : 29.66 | Patterns : 0.36 | Match Lists : 0.77 | DFA | 1 byte states : 1.37 | 2 byte states : 26.59 | 4 byte states : 0.00 +---------------------------------------------------------------- [ Number of patterns truncated to 20 bytes: 563 ] ERROR: Can't find pcap DAQ! Fatal Error, Quitting.. net-libs/daq is installed, but I don't even want to capture traffic, I just want to process the capture file. What configuration options should I be setting/unsetting in order to do offline analysis instead of real-time capture?

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In Wireshark's Protocol Hierarchy Statistics screen, is the total byte count of a capture the sum of the Bytes column or just the top line (Frame)?

- by Howiecamp

Part 1 - I'm looking at Wireshark's Protocol Hierarchy Statistics screen (sample below), is the total byte count of the capture the sum of the Bytes column or just the top line (Frame)? I'm 99% that it's the latter because of protocol rollup but I wanted to conform. Part 2 - From Wireshark documentation on this screen, "Protocol layers can consist of packets that won't contain any higher layer protocol, so the sum of all higher layer packets may not sum up to the protocols packet count. Example: In the screenshot TCP has 85,83% but the sum of the subprotocols (HTTP, ...) is much less. This may be caused by TCP protocol overhead, e.g. TCP ACK packets won't be counted as packets of the higher layer)." Can you explain this?

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Efficient mapping of game entity positions in Java

- by byte

In Java (Swing), say I've got a 2D game where I have various types of entities on the screen, such as a player, bad guys, powerups, etc. When the player moves across the screen, in order to do efficient checking of what is in the immediate vicinity of the player, I would think I'd want indexed access to the things that are near the character based on their position. For example, if player 'P' steps onto element 'E' in the following example... | | | | | | | | | |P| | | | |E| | | | | | | | | ... would be to do something like: if(player.getPosition().x == entity.getPosition().x && entity.getPosition.y == thing.getPosition().y) { //do something } And thats fine, but that implies that the entities hold their positions, and therefor if I had MANY entities on the screen I would have to loop through all possible entities available and check each ones position against the player position. This seems really inefficient especially if you start getting tons of entities. So, I would suspect I'd want some sort of map like Map<Point, Entity> map = new HashMap<Point, Entity>(); And store my point information there, so that I could access these entities in constant time. The only problem with that approach is that, if I want to move an entity to a different point on the screen, I'd have to search through the values of the HashMap for the entity I want to move (inefficient since I dont know its Point position ahead of time), and then once I've found it remove it from the HashMap, and re-insert it with the new position information. Any suggestions or advice on what sort of data structure / storage format I ought to be using here in order to have efficient access to Entities based on their position, as well as Position's based on the Entity?

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Advanced TSQL Tuning: Why Internals Knowledge Matters

- by Paul White

There is much more to query tuning than reducing logical reads and adding covering nonclustered indexes. Query tuning is not complete as soon as the query returns results quickly in the development or test environments. In production, your query will compete for memory, CPU, locks, I/O and other resources on the server. Today’s entry looks at some tuning considerations that are often overlooked, and shows how deep internals knowledge can help you write better TSQL. As always, we’ll need some example data. In fact, we are going to use three tables today, each of which is structured like this: Each table has 50,000 rows made up of an INTEGER id column and a padding column containing 3,999 characters in every row. The only difference between the three tables is in the type of the padding column: the first table uses CHAR(3999), the second uses VARCHAR(MAX), and the third uses the deprecated TEXT type. A script to create a database with the three tables and load the sample data follows: USE master; GO IF DB_ID('SortTest') IS NOT NULL DROP DATABASE SortTest; GO CREATE DATABASE SortTest COLLATE LATIN1_GENERAL_BIN; GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest', SIZE = 3GB, MAXSIZE = 3GB ); GO ALTER DATABASE SortTest MODIFY FILE ( NAME = 'SortTest_log', SIZE = 256MB, MAXSIZE = 1GB, FILEGROWTH = 128MB ); GO ALTER DATABASE SortTest SET ALLOW_SNAPSHOT_ISOLATION OFF ; ALTER DATABASE SortTest SET AUTO_CLOSE OFF ; ALTER DATABASE SortTest SET AUTO_CREATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_SHRINK OFF ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS ON ; ALTER DATABASE SortTest SET AUTO_UPDATE_STATISTICS_ASYNC ON ; ALTER DATABASE SortTest SET PARAMETERIZATION SIMPLE ; ALTER DATABASE SortTest SET READ_COMMITTED_SNAPSHOT OFF ; ALTER DATABASE SortTest SET MULTI_USER ; ALTER DATABASE SortTest SET RECOVERY SIMPLE ; USE SortTest; GO CREATE TABLE dbo.TestCHAR ( id INTEGER IDENTITY (1,1) NOT NULL, padding CHAR(3999) NOT NULL, CONSTRAINT [PK dbo.TestCHAR (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestMAX ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL, CONSTRAINT [PK dbo.TestMAX (id)] PRIMARY KEY CLUSTERED (id), ) ; CREATE TABLE dbo.TestTEXT ( id INTEGER IDENTITY (1,1) NOT NULL, padding TEXT NOT NULL, CONSTRAINT [PK dbo.TestTEXT (id)] PRIMARY KEY CLUSTERED (id), ) ; -- ============= -- Load TestCHAR (about 3s) -- ============= INSERT INTO dbo.TestCHAR WITH (TABLOCKX) ( padding ) SELECT padding = REPLICATE(CHAR(65 + (Data.n % 26)), 3999) FROM ( SELECT TOP (50000) n = ROW_NUMBER() OVER (ORDER BY (SELECT 0)) - 1 FROM master.sys.columns C1, master.sys.columns C2, master.sys.columns C3 ORDER BY n ASC ) AS Data ORDER BY Data.n ASC ; -- ============ -- Load TestMAX (about 3s) -- ============ INSERT INTO dbo.TestMAX WITH (TABLOCKX) ( padding ) SELECT CONVERT(VARCHAR(MAX), padding) FROM dbo.TestCHAR ORDER BY id ; -- ============= -- Load TestTEXT (about 5s) -- ============= INSERT INTO dbo.TestTEXT WITH (TABLOCKX) ( padding ) SELECT CONVERT(TEXT, padding) FROM dbo.TestCHAR ORDER BY id ; -- ========== -- Space used -- ========== -- EXECUTE sys.sp_spaceused @objname = 'dbo.TestCHAR'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAX'; EXECUTE sys.sp_spaceused @objname = 'dbo.TestTEXT'; ; CHECKPOINT ; That takes around 15 seconds to run, and shows the space allocated to each table in its output: To illustrate the points I want to make today, the example task we are going to set ourselves is to return a random set of 150 rows from each table. The basic shape of the test query is the same for each of the three test tables: SELECT TOP (150) T.id, T.padding FROM dbo.Test AS T ORDER BY NEWID() OPTION (MAXDOP 1) ; Test 1 – CHAR(3999) Running the template query shown above using the TestCHAR table as the target, we find that the query takes around 5 seconds to return its results. This seems slow, considering that the table only has 50,000 rows. Working on the assumption that generating a GUID for each row is a CPU-intensive operation, we might try enabling parallelism to see if that speeds up the response time. Running the query again (but without the MAXDOP 1 hint) on a machine with eight logical processors, the query now takes 10 seconds to execute – twice as long as when run serially. Rather than attempting further guesses at the cause of the slowness, let’s go back to serial execution and add some monitoring. The script below monitors STATISTICS IO output and the amount of tempdb used by the test query. We will also run a Profiler trace to capture any warnings generated during query execution. DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TC.id, TC.padding FROM dbo.TestCHAR AS TC ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; Let’s take a closer look at the statistics and query plan generated from this: Following the flow of the data from right to left, we see the expected 50,000 rows emerging from the Clustered Index Scan, with a total estimated size of around 191MB. The Compute Scalar adds a column containing a random GUID (generated from the NEWID() function call) for each row. With this extra column in place, the size of the data arriving at the Sort operator is estimated to be 192MB. Sort is a blocking operator – it has to examine all of the rows on its input before it can produce its first row of output (the last row received might sort first). This characteristic means that Sort requires a memory grant – memory allocated for the query’s use by SQL Server just before execution starts. In this case, the Sort is the only memory-consuming operator in the plan, so it has access to the full 243MB (248,696KB) of memory reserved by SQL Server for this query execution. Notice that the memory grant is significantly larger than the expected size of the data to be sorted. SQL Server uses a number of techniques to speed up sorting, some of which sacrifice size for comparison speed. Sorts typically require a very large number of comparisons, so this is usually a very effective optimization. One of the drawbacks is that it is not possible to exactly predict the sort space needed, as it depends on the data itself. SQL Server takes an educated guess based on data types, sizes, and the number of rows expected, but the algorithm is not perfect. In spite of the large memory grant, the Profiler trace shows a Sort Warning event (indicating that the sort ran out of memory), and the tempdb usage monitor shows that 195MB of tempdb space was used – all of that for system use. The 195MB represents physical write activity on tempdb, because SQL Server strictly enforces memory grants – a query cannot ‘cheat’ and effectively gain extra memory by spilling to tempdb pages that reside in memory. Anyway, the key point here is that it takes a while to write 195MB to disk, and this is the main reason that the query takes 5 seconds overall. If you are wondering why using parallelism made the problem worse, consider that eight threads of execution result in eight concurrent partial sorts, each receiving one eighth of the memory grant. The eight sorts all spilled to tempdb, resulting in inefficiencies as the spilled sorts competed for disk resources. More importantly, there are specific problems at the point where the eight partial results are combined, but I’ll cover that in a future post. CHAR(3999) Performance Summary: 5 seconds elapsed time 243MB memory grant 195MB tempdb usage 192MB estimated sort set 25,043 logical reads Sort Warning Test 2 – VARCHAR(MAX) We’ll now run exactly the same test (with the additional monitoring) on the table using a VARCHAR(MAX) padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TM.id, TM.padding FROM dbo.TestMAX AS TM ORDER BY NEWID() OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query takes around 8 seconds to complete (3 seconds longer than Test 1). Notice that the estimated row and data sizes are very slightly larger, and the overall memory grant has also increased very slightly to 245MB. The most marked difference is in the amount of tempdb space used – this query wrote almost 391MB of sort run data to the physical tempdb file. Don’t draw any general conclusions about VARCHAR(MAX) versus CHAR from this – I chose the length of the data specifically to expose this edge case. In most cases, VARCHAR(MAX) performs very similarly to CHAR – I just wanted to make test 2 a bit more exciting. MAX Performance Summary: 8 seconds elapsed time 245MB memory grant 391MB tempdb usage 193MB estimated sort set 25,043 logical reads Sort warning Test 3 – TEXT The same test again, but using the deprecated TEXT data type for the padding column: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) TT.id, TT.padding FROM dbo.TestTEXT AS TT ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; This time the query runs in 500ms. If you look at the metrics we have been checking so far, it’s not hard to understand why: TEXT Performance Summary: 0.5 seconds elapsed time 9MB memory grant 5MB tempdb usage 5MB estimated sort set 207 logical reads 596 LOB logical reads Sort warning SQL Server’s memory grant algorithm still underestimates the memory needed to perform the sorting operation, but the size of the data to sort is so much smaller (5MB versus 193MB previously) that the spilled sort doesn’t matter very much. Why is the data size so much smaller? The query still produces the correct results – including the large amount of data held in the padding column – so what magic is being performed here? TEXT versus MAX Storage The answer lies in how columns of the TEXT data type are stored. By default, TEXT data is stored off-row in separate LOB pages – which explains why this is the first query we have seen that records LOB logical reads in its STATISTICS IO output. You may recall from my last post that LOB data leaves an in-row pointer to the separate storage structure holding the LOB data. SQL Server can see that the full LOB value is not required by the query plan until results are returned, so instead of passing the full LOB value down the plan from the Clustered Index Scan, it passes the small in-row structure instead. SQL Server estimates that each row coming from the scan will be 79 bytes long – 11 bytes for row overhead, 4 bytes for the integer id column, and 64 bytes for the LOB pointer (in fact the pointer is rather smaller – usually 16 bytes – but the details of that don’t really matter right now). OK, so this query is much more efficient because it is sorting a very much smaller data set – SQL Server delays retrieving the LOB data itself until after the Sort starts producing its 150 rows. The question that normally arises at this point is: Why doesn’t SQL Server use the same trick when the padding column is defined as VARCHAR(MAX)? The answer is connected with the fact that if the actual size of the VARCHAR(MAX) data is 8000 bytes or less, it is usually stored in-row in exactly the same way as for a VARCHAR(8000) column – MAX data only moves off-row into LOB storage when it exceeds 8000 bytes. The default behaviour of the TEXT type is to be stored off-row by default, unless the ‘text in row’ table option is set suitably and there is room on the page. There is an analogous (but opposite) setting to control the storage of MAX data – the ‘large value types out of row’ table option. By enabling this option for a table, MAX data will be stored off-row (in a LOB structure) instead of in-row. SQL Server Books Online has good coverage of both options in the topic In Row Data. The MAXOOR Table The essential difference, then, is that MAX defaults to in-row storage, and TEXT defaults to off-row (LOB) storage. You might be thinking that we could get the same benefits seen for the TEXT data type by storing the VARCHAR(MAX) values off row – so let’s look at that option now. This script creates a fourth table, with the VARCHAR(MAX) data stored off-row in LOB pages: CREATE TABLE dbo.TestMAXOOR ( id INTEGER IDENTITY (1,1) NOT NULL, padding VARCHAR(MAX) NOT NULL, CONSTRAINT [PK dbo.TestMAXOOR (id)] PRIMARY KEY CLUSTERED (id), ) ; EXECUTE sys.sp_tableoption @TableNamePattern = N'dbo.TestMAXOOR', @OptionName = 'large value types out of row', @OptionValue = 'true' ; SELECT large_value_types_out_of_row FROM sys.tables WHERE [schema_id] = SCHEMA_ID(N'dbo') AND name = N'TestMAXOOR' ; INSERT INTO dbo.TestMAXOOR WITH (TABLOCKX) ( padding ) SELECT SPACE(0) FROM dbo.TestCHAR ORDER BY id ; UPDATE TM WITH (TABLOCK) SET padding.WRITE (TC.padding, NULL, NULL) FROM dbo.TestMAXOOR AS TM JOIN dbo.TestCHAR AS TC ON TC.id = TM.id ; EXECUTE sys.sp_spaceused @objname = 'dbo.TestMAXOOR' ; CHECKPOINT ; Test 4 – MAXOOR We can now re-run our test on the MAXOOR (MAX out of row) table: DECLARE @read BIGINT, @write BIGINT ; SELECT @read = SUM(num_of_bytes_read), @write = SUM(num_of_bytes_written) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; SET STATISTICS IO ON ; SELECT TOP (150) MO.id, MO.padding FROM dbo.TestMAXOOR AS MO ORDER BY NEWID() OPTION (MAXDOP 1, RECOMPILE) ; SET STATISTICS IO OFF ; SELECT tempdb_read_MB = (SUM(num_of_bytes_read) - @read) / 1024. / 1024., tempdb_write_MB = (SUM(num_of_bytes_written) - @write) / 1024. / 1024., internal_use_MB = ( SELECT internal_objects_alloc_page_count / 128.0 FROM sys.dm_db_task_space_usage WHERE session_id = @@SPID ) FROM tempdb.sys.database_files AS DBF JOIN sys.dm_io_virtual_file_stats(2, NULL) AS FS ON FS.file_id = DBF.file_id WHERE DBF.type_desc = 'ROWS' ; TEXT Performance Summary: 0.3 seconds elapsed time 245MB memory grant 0MB tempdb usage 193MB estimated sort set 207 logical reads 446 LOB logical reads No sort warning The query runs very quickly – slightly faster than Test 3, and without spilling the sort to tempdb (there is no sort warning in the trace, and the monitoring query shows zero tempdb usage by this query). SQL Server is passing the in-row pointer structure down the plan and only looking up the LOB value on the output side of the sort. The Hidden Problem There is still a huge problem with this query though – it requires a 245MB memory grant. No wonder the sort doesn’t spill to tempdb now – 245MB is about 20 times more memory than this query actually requires to sort 50,000 records containing LOB data pointers. Notice that the estimated row and data sizes in the plan are the same as in test 2 (where the MAX data was stored in-row). The optimizer assumes that MAX data is stored in-row, regardless of the sp_tableoption setting ‘large value types out of row’. Why? Because this option is dynamic – changing it does not immediately force all MAX data in the table in-row or off-row, only when data is added or actually changed. SQL Server does not keep statistics to show how much MAX or TEXT data is currently in-row, and how much is stored in LOB pages. This is an annoying limitation, and one which I hope will be addressed in a future version of the product. So why should we worry about this? Excessive memory grants reduce concurrency and may result in queries waiting on the RESOURCE_SEMAPHORE wait type while they wait for memory they do not need. 245MB is an awful lot of memory, especially on 32-bit versions where memory grants cannot use AWE-mapped memory. Even on a 64-bit server with plenty of memory, do you really want a single query to consume 0.25GB of memory unnecessarily? That’s 32,000 8KB pages that might be put to much better use. The Solution The answer is not to use the TEXT data type for the padding column. That solution happens to have better performance characteristics for this specific query, but it still results in a spilled sort, and it is hard to recommend the use of a data type which is scheduled for removal. I hope it is clear to you that the fundamental problem here is that SQL Server sorts the whole set arriving at a Sort operator. Clearly, it is not efficient to sort the whole table in memory just to return 150 rows in a random order. The TEXT example was more efficient because it dramatically reduced the size of the set that needed to be sorted. We can do the same thing by selecting 150 unique keys from the table at random (sorting by NEWID() for example) and only then retrieving the large padding column values for just the 150 rows we need. The following script implements that idea for all four tables: SET STATISTICS IO ON ; WITH TestTable AS ( SELECT * FROM dbo.TestCHAR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id = ANY (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAX ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestTEXT ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; WITH TestTable AS ( SELECT * FROM dbo.TestMAXOOR ), TopKeys AS ( SELECT TOP (150) id FROM TestTable ORDER BY NEWID() ) SELECT T1.id, T1.padding FROM TestTable AS T1 WHERE T1.id IN (SELECT id FROM TopKeys) OPTION (MAXDOP 1) ; SET STATISTICS IO OFF ; All four queries now return results in much less than a second, with memory grants between 6 and 12MB, and without spilling to tempdb. The small remaining inefficiency is in reading the id column values from the clustered primary key index. As a clustered index, it contains all the in-row data at its leaf. The CHAR and VARCHAR(MAX) tables store the padding column in-row, so id values are separated by a 3999-character column, plus row overhead. The TEXT and MAXOOR tables store the padding values off-row, so id values in the clustered index leaf are separated by the much-smaller off-row pointer structure. This difference is reflected in the number of logical page reads performed by the four queries: Table 'TestCHAR' logical reads 25511 lob logical reads 000 Table 'TestMAX'. logical reads 25511 lob logical reads 000 Table 'TestTEXT' logical reads 00412 lob logical reads 597 Table 'TestMAXOOR' logical reads 00413 lob logical reads 446 We can increase the density of the id values by creating a separate nonclustered index on the id column only. This is the same key as the clustered index, of course, but the nonclustered index will not include the rest of the in-row column data. CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestCHAR (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAX (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestTEXT (id); CREATE UNIQUE NONCLUSTERED INDEX uq1 ON dbo.TestMAXOOR (id); The four queries can now use the very dense nonclustered index to quickly scan the id values, sort them by NEWID(), select the 150 ids we want, and then look up the padding data. The logical reads with the new indexes in place are: Table 'TestCHAR' logical reads 835 lob logical reads 0 Table 'TestMAX' logical reads 835 lob logical reads 0 Table 'TestTEXT' logical reads 686 lob logical reads 597 Table 'TestMAXOOR' logical reads 686 lob logical reads 448 With the new index, all four queries use the same query plan (click to enlarge): Performance Summary: 0.3 seconds elapsed time 6MB memory grant 0MB tempdb usage 1MB sort set 835 logical reads (CHAR, MAX) 686 logical reads (TEXT, MAXOOR) 597 LOB logical reads (TEXT) 448 LOB logical reads (MAXOOR) No sort warning I’ll leave it as an exercise for the reader to work out why trying to eliminate the Key Lookup by adding the padding column to the new nonclustered indexes would be a daft idea Conclusion This post is not about tuning queries that access columns containing big strings. It isn’t about the internal differences between TEXT and MAX data types either. It isn’t even about the cool use of UPDATE .WRITE used in the MAXOOR table load. No, this post is about something else: Many developers might not have tuned our starting example query at all – 5 seconds isn’t that bad, and the original query plan looks reasonable at first glance. Perhaps the NEWID() function would have been blamed for ‘just being slow’ – who knows. 5 seconds isn’t awful – unless your users expect sub-second responses – but using 250MB of memory and writing 200MB to tempdb certainly is! If ten sessions ran that query at the same time in production that’s 2.5GB of memory usage and 2GB hitting tempdb. Of course, not all queries can be rewritten to avoid large memory grants and sort spills using the key-lookup technique in this post, but that’s not the point either. The point of this post is that a basic understanding of execution plans is not enough. Tuning for logical reads and adding covering indexes is not enough. If you want to produce high-quality, scalable TSQL that won’t get you paged as soon as it hits production, you need a deep understanding of execution plans, and as much accurate, deep knowledge about SQL Server as you can lay your hands on. The advanced database developer has a wide range of tools to use in writing queries that perform well in a range of circumstances. By the way, the examples in this post were written for SQL Server 2008. They will run on 2005 and demonstrate the same principles, but you won’t get the same figures I did because 2005 had a rather nasty bug in the Top N Sort operator. Fair warning: if you do decide to run the scripts on a 2005 instance (particularly the parallel query) do it before you head out for lunch… This post is dedicated to the people of Christchurch, New Zealand. © 2011 Paul White email: @[email protected] twitter: @SQL_Kiwi

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Python regex to parse text file, get the items in list and count the list

- by Nemo

I have a text file which contains some data. I m particularly interested in finding the count of the number of items in v_dims v_dims pattern in my text file looks like this : v_dims={ "Sales", "Product Family", "Sales Organization", "Region", "Sales Area", "Sales office", "Sales Division", "Sales Person", "Sales Channel", "Sales Order Type", "Sales Number", "Sales Person", "Sales Quantity", "Sales Amount" } So I m thinking of getting all the elements in v_dims and dumping them out in a Python list. Then compute the len(mylist) to get the count of the items. The challenge is in getting all the elements of v_dims from my text file and putting them in an empty list. I m particularly interested in items in v_dims in my text file. The text file has data in the form of v_dims pattern i showed in my original post. Some data has nested patterns of v_dims. Thanks. Here's what I have tried and failed. Any help is appreciated. TIA. import re fname = "C:\Users\XXXX\Test.mrk" with open(fname, "r") as fo: content_as_string = fo.read() match = re.findall(r'v_dims={\"(.+?)\"}',content_as_string) Though I have a big text file, Here's a snippet of what's the structure of my text file version "1"; // Computer generated object language file object 'MRKR' "Main" { Data_Type=2, HeaderBlock={ Version_String="6.3 (25)" }, Printer_Info={ Orientation=0, Page_Width=8.50000000, Page_Height=11.00000000, Page_Header="", Page_Footer="", Margin_type=0, Top_Margin=0.50000000, Left_Margin=0.50000000, Bottom_Margin=0.50000000, Right_Margin=0.50000000 }, Marker_Options={ Close_All="TRUE", Hide_Console="FALSE", Console_Left="FALSE", Console_Width=217, Main_Style="Maximized", MDI_Rect={ 0, 0, 892, 1063 } }, Dives={ { Dive="A", Windows={ { View_Index=0, Window_Info={ Window_Rect={ 0, -288, 400, 1008 }, Window_Style="Maximized Front", Window_Name="Theater [Previous Qtr Diveplan-Dive A]" }, Dependent_bool="FALSE", Colset={ Dive_Type="Normal", Dimension_Name="Theater", Action_List={ Actions={ { Action_Type="Select", select_type=5 }, { Action_Type="Select", select_type=0, Key_Names={ "Theater" }, Key_Indexes={ { "AMERICAS" } } }, { Action_Type="Focus", Focus_Rows="True" }, { Action_Type="Dimensions", v_dims={ "Theater", "Product Family", "Division", "Region", "Install at Country Name", "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "PS Flag", "Avalanche Flag", "Product Item Family" }, Xtab_Bool="False", Xtab_Flip="False" }, { Action_Type="Select", select_type=5 }, { Action_Type="Select", select_type=0, Key_Names={ "Theater", "Product Family", "Division", "Region", "Install at Country Name", "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "PS Flag", "Avalanche Flag" }, Key_Indexes={ { "AMERICAS", "ATMOS", "Latin America CS Division", "37000 CS Region", "Mexico", "", "", "", "", "DIRECT", "EMC", "N", "0" } } } } }, Num_Palette_cols=0, Num_Palette_rows=0 }, Format={ Window_Type="Tabular", Tabular={ Num_row_labels=8 } } } } } }, Widget_Set={ Widget_Layout="Vertical", Go_Button=1, Picklist_Width=0, Sort_Subset_Dimensions="TRUE", Order={ } }, Views={ { Data_Type=1, dbname="Previous Qtr Diveplan", diveline_dbname="Current Qtr Diveplan", logical_name="Current Qtr Diveplan", cols={ { name="Total TSS installs", column_type="Calc[Total TSS installs]", output_type="Number", format_string="." }, { name="TSS Valid Connectivity Records", column_type="Calc[TSS Valid Connectivity Records]", output_type="Number", format_string="." }, { name="% TSS Connectivity Record", column_type="Calc[% TSS Connectivity Record]", output_type="Number" }, { name="TSS Not Applicable", column_type="Calc[TSS Not Applicable]", output_type="Number", format_string="." }, { name="TSS Customer Refusals", column_type="Calc[TSS Customer Refusals]", output_type="Number", format_string="." }, { name="% TSS Refusals", column_type="Calc[% TSS Refusals]", output_type="Number" }, { name="TSS Eligible for Physical Connectivity", column_type="Calc[TSS Eligible for Physical Connectivity]", output_type="Number", format_string="." }, { name="TSS Boxes with Physical Connectivty", column_type="Calc[TSS Boxes with Physical Connectivty]", output_type="Number", format_string="." }, { name="% TSS Physical Connectivity", column_type="Calc[% TSS Physical Connectivity]", output_type="Number" } }, dim_cols={ { name="Model", column_type="Dimension[Model]", output_type="None" }, { name="Model", column_type="Dimension[Model]", output_type="None" }, { name="Connect In Type", column_type="Dimension[Connect In Type]", output_type="None" }, { name="Connect Home Type", column_type="Dimension[Connect Home Type]", output_type="None" }, { name="SymmConnect Enabled", column_type="Dimension[SymmConnect Enabled]", output_type="None" }, { name="Theater", column_type="Dimension[Theater]", output_type="None" }, { name="Division", column_type="Dimension[Division]", output_type="None" }, { name="Region", column_type="Dimension[Region]", output_type="None" }, { name="Sales Order Number", column_type="Dimension[Sales Order Number]", output_type="None" }, { name="Product Item Family", column_type="Dimension[Product Item Family]", output_type="None" }, { name="Item Serial Number", column_type="Dimension[Item Serial Number]", output_type="None" }, { name="Sales Order Deal Number", column_type="Dimension[Sales Order Deal Number]", output_type="None" }, { name="Item Install Date", column_type="Dimension[Item Install Date]", output_type="None" }, { name="SYR Last Dial Home Date", column_type="Dimension[SYR Last Dial Home Date]", output_type="None" }, { name="Maintained By Group", column_type="Dimension[Maintained By Group]", output_type="None" }, { name="PS Flag", column_type="Dimension[PS Flag]", output_type="None" }, { name="Connect Home Refusal Reason", column_type="Dimension[Connect Home Refusal Reason]", output_type="None", col_width=177 }, { name="Cust Name", column_type="Dimension[Cust Name]", output_type="None" }, { name="Sales Order Channel Type", column_type="Dimension[Sales Order Channel Type]", output_type="None" }, { name="Sales Order Type", column_type="Dimension[Sales Order Type]", output_type="None" }, { name="Part Model Key", column_type="Dimension[Part Model Key]", output_type="None" }, { name="Ship Date", column_type="Dimension[Ship Date]", output_type="None" }, { name="Model Number", column_type="Dimension[Model Number]", output_type="None" }, { name="Item Description", column_type="Dimension[Item Description]", output_type="None" }, { name="Customer Classification", column_type="Dimension[Customer Classification]", output_type="None" }, { name="CS Customer Name", column_type="Dimension[CS Customer Name]", output_type="None" }, { name="Install At Customer Number", column_type="Dimension[Install At Customer Number]", output_type="None" }, { name="Install at Country Name", column_type="Dimension[Install at Country Name]", output_type="None" }, { name="TLA Serial Number", column_type="Dimension[TLA Serial Number]", output_type="None" }, { name="Product Version", column_type="Dimension[Product Version]", output_type="None" }, { name="Avalanche Flag", column_type="Dimension[Avalanche Flag]", output_type="None" }, { name="Product Family", column_type="Dimension[Product Family]", output_type="None" }, { name="Project Number", column_type="Dimension[Project Number]", output_type="None" }, { name="PROJECT_STATUS", column_type="Dimension[PROJECT_STATUS]", output_type="None" } }, Available_Columns={ "Total TSS installs", "TSS Valid Connectivity Records", "% TSS Connectivity Record", "TSS Not Applicable", "TSS Customer Refusals", "% TSS Refusals", "TSS Eligible for Physical Connectivity", "TSS Boxes with Physical Connectivty", "% TSS Physical Connectivity", "Total Installs", "All Boxes with Valid Connectivty Record", "% All Connectivity Record", "Overall Refusals", "Overall Refusals %", "All Eligible for Physical Connectivty", "Boxes with Physical Connectivity", "% All with Physical Conectivity" }, Remaining_columns={ { name="Total Installs", column_type="Calc[Total Installs]", output_type="Number", format_string="." }, { name="All Boxes with Valid Connectivty Record", column_type="Calc[All Boxes with Valid Connectivty Record]", output_type="Number", format_string="." }, { name="% All Connectivity Record", column_type="Calc[% All Connectivity Record]", output_type="Number" }, { name="Overall Refusals", column_type="Calc[Overall Refusals]", output_type="Number", format_string="." }, { name="Overall Refusals %", column_type="Calc[Overall Refusals %]", output_type="Number" }, { name="All Eligible for Physical Connectivty", column_type="Calc[All Eligible for Physical Connectivty]", output_type="Number" }, { name="Boxes with Physical Connectivity", column_type="Calc[Boxes with Physical Connectivity]", output_type="Number" }, { name="% All with Physical Conectivity", column_type="Calc[% All with Physical Conectivity]", output_type="Number" } }, calcs={ { name="Total TSS installs", definition="Total[Total TSS installs]", ts_flag="Not TS Calc" }, { name="TSS Valid Connectivity Records", definition="Total[PS Boxes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="% TSS Connectivity Record", definition="Total[PS Boxes w/ valid connectivity record (1=yes)] /Total[Total TSS installs]", ts_flag="Not TS Calc" }, { name="TSS Not Applicable", definition="Total[Bozes w/ valid connectivity record (1=yes)]-Total[Boxes Eligible (1=yes)]-Total[TSS Refusals]", ts_flag="Not TS Calc" }, { name="TSS Customer Refusals", definition="Total[TSS Refusals]", ts_flag="Not TS Calc" }, { name="% TSS Refusals", definition="Total[TSS Refusals]/Total[PS Boxes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="TSS Eligible for Physical Connectivity", definition="Total[TSS Eligible]-Total[Exception]", ts_flag="Not TS Calc" }, { name="TSS Boxes with Physical Connectivty", definition="Total[PS Physical Connectivity] - Total[PS Physical Connectivity, SymmConnect Enabled=\"Capable not enabled\"]", ts_flag="Not TS Calc" }, { name="% TSS Physical Connectivity", definition="Total[Boxes w/ phys conn]/Total[Boxes Eligible (1=yes)]", ts_flag="Not TS Calc" }, { name="Total Installs", definition="Total[Total Installs]", ts_flag="Not TS Calc" }, { name="All Boxes with Valid Connectivty Record", definition="Total[Bozes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="% All Connectivity Record", definition="Total[Bozes w/ valid connectivity record (1=yes)]/Total[Total Installs]", ts_flag="Not TS Calc" }, { name="Overall Refusals", definition="Total[Overall Refusals]", ts_flag="Not TS Calc" }, { name="Overall Refusals %", definition="Total[Overall Refusals]/Total[Bozes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="All Eligible for Physical Connectivty", definition="Total[Boxes Eligible (1=yes)]-Total[Exception]", ts_flag="Not TS Calc" }, { name="Boxes with Physical Connectivity", definition="Total[Boxes w/ phys conn]-Total[Boxes w/ phys conn,SymmConnect Enabled=\"Capable not enabled\"]", ts_flag="Not TS Calc" }, { name="% All with Physical Conectivity", definition="Total[Boxes w/ phys conn]/Total[Boxes Eligible (1=yes)]", ts_flag="Not TS Calc" } }, merge_type="consolidate", merge_dbs={ { dbname="connectivityallproducts.mdl", diveline_dbname="/DI_PSREPORTING/connectivityallproducts.mdl" } }, skip_constant_columns="FALSE", categories={ { name="Geography", dimensions={ "Theater", "Division", "Region", "Install at Country Name" } }, { name="Mappings and Flags", dimensions={ "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "Customer Installable", "PS Flag", "Top Level Flag", "Avalanche Flag" } }, { name="Product Information", dimensions={ "Product Family", "Product Item Family", "Product Version", "Item Description" } }, { name="Sales Order Info", dimensions={ "Sales Order Deal Number", "Sales Order Number", "Sales Order Type" } }, { name="Dates", dimensions={ "Item Install Date", "Ship Date", "SYR Last Dial Home Date" } }, { name="Details", dimensions={ "Item Serial Number", "TLA Serial Number", "Part Model Key", "Model Number" } }, { name="Customer Infor", dimensions={ "CS Customer Name", "Install At Customer Number", "Customer Classification", "Cust Name" } }, { name="Other Dimensions", dimensions={ "Model" } } }, Maintain_Category_Order="FALSE", popup_info="false" } } };

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Is this way of storing typed objects in memory good?

- by Pindatjuh

This is an "is this okay, or can it be done better" question. Topic: Storing typed objects in memory. Background information: I'm building a compiler for the x86-32 platform for my language. My goal includes typed objects. Idea: Every primitive is a semi-class (it can be used as if it was a normal class, but it's stored more compact). Every class is represented by primitives and some meta-data (containing class-properties, inheritance stuff, etc.). The meta-data is complex: it doesn't use fields but instead context-switches. For primitives, the meta-data is very small, compared to a "real" class, which is alot bigger. This enables another idea that "primitives are objects", in my language, which I found nessecairy. Example: If I have an array of 32 booleans, then the pure content of this array is exactly 4 byte (32 bits of booleans). The meta-data will contain flags that the type is an array of booleans, which contains 32 entries. The meta-data is very compacted, on bit-level: using a sort of "packing" mechanism, which is read by a FSM at runtime, when doing inspection of the type (like when passing the object to methods for checking, etc.) For instance (read from left to right, top to bottom, remember vertical possition when going to the right, and check nearest column header for meaning of switch): Primitive? Array? Type-Meta 1 Byte? || Size (1 byte) 1 1 [...] 1 [...] done 0 2 Bytes? || Size (2 bytes) 1 [...] done || Size (4 bytes) 0 [...] done Integer? 1 Byte? 2 Bytes? 0 1 0 1 done 1 done 0 done Boolean? Byte? 0 1 0 done 1 done More-Primitives 0 .... Class-Stuff (Huge) 0 ... (After reaching done the data is inserted. || = byte alignement. [...] is variable sized. ... is not described here, for simplicity. And let's call them cost-based-data-structures.) For an array of 32 booleans containing all true values, the memory for this type would be (read top-down): 1 Primitive 1 Array 1 ArrayType: Primitive 0 Not-Array 0 Not-Integer 1 Boolean 0 Not-Byte (thus bit) 1 Integer Size: 1 Byte 00100000 Array size 11111111 11111111 11111111 11111111 Data Thus, 8 bytes represent 32 booleans in an array: 11100101 00100000 11111111 11111111 11111111 11111111 Is this okay, or can it be done better?

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SQL Server 2008 Filestream Impersonation Access Denied error

- by Adi

I've been trying to upload a file to the database using SQL SERVER 2008 Filestream and Impersonation technique to save the file in the file system, but i keep getting Access Denied error; even though i've set the permissions for the impersonating user to the Filestream folder(C:\SQLFILESTREAM\Dev_DB). when i debugged the code, i found the server return a unc path(\Server_Name\MSSQLSERVER\v1\Dev_LMDB\dbo\FileData\File_Data\13C39AB1-8B91-4F5A-81A1-940B58504C17), which was not accessible through windows explorer. I've my web application hosted on local maching(Windows 7). SQL Server is located on a remote server(Windows Server 2008 R2). Sql authentication was used to call the stored procedure. Following is the code i've used to do the above operations. SqlCommand sqlCmd = new SqlCommand("AddFile"); sqlCmd.CommandType = CommandType.StoredProcedure; sqlCmd.Parameters.Add("@File_Name", SqlDbType.VarChar, 512).Value = filename; sqlCmd.Parameters.Add("@File_Type", SqlDbType.VarChar, 5).Value = Path.GetExtension(filename); sqlCmd.Parameters.Add("@Username", SqlDbType.VarChar, 20).Value = username; sqlCmd.Parameters.Add("@Output_File_Path", SqlDbType.VarChar, -1).Direction = ParameterDirection.Output; DAManager PDAM = new DAManager(DAManager.getConnectionString()); using (SqlConnection connection = (SqlConnection)PDAM.CreateConnection()) { connection.Open(); SqlTransaction transaction = connection.BeginTransaction(); WindowsImpersonationContext wImpersonationCtx; NetworkSecurity ns = null; try { PDAM.ExecuteNonQuery(sqlCmd, transaction); string filepath = sqlCmd.Parameters["@Output_File_Path"].Value.ToString(); sqlCmd = new SqlCommand("SELECT GET_FILESTREAM_TRANSACTION_CONTEXT()"); sqlCmd.CommandType = CommandType.Text; byte[] Context = (byte[])PDAM.ExecuteScalar(sqlCmd, transaction); byte[] buffer = new byte[4096]; int bytedRead; ns = new NetworkSecurity(); wImpersonationCtx = ns.ImpersonateUser(IMP_Domain, IMP_Username, IMP_Password, LogonType.LOGON32_LOGON_INTERACTIVE, LogonProvider.LOGON32_PROVIDER_DEFAULT); SqlFileStream sfs = new SqlFileStream(filepath, Context, System.IO.FileAccess.Write); while ((bytedRead = inFS.Read(buffer, 0, buffer.Length)) != 0) { sfs.Write(buffer, 0, bytedRead); } sfs.Close(); transaction.Commit(); } catch (Exception ex) { transaction.Rollback(); } finally { sqlCmd.Dispose(); connection.Close(); connection.Dispose(); ns.undoImpersonation(); wImpersonationCtx = null; ns = null; } } Can someone help me with this issue. Reference Exception: Type : System.ComponentModel.Win32Exception, System, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 Message : Access is denied Source : System.Data Help link : NativeErrorCode : 5 ErrorCode : -2147467259 Data : System.Collections.ListDictionaryInternal TargetSite : Void OpenSqlFileStream(System.String, Byte[], System.IO.FileAccess, System.IO.FileOptions, Int64) Stack Trace : at System.Data.SqlTypes.SqlFileStream.OpenSqlFileStream(String path, Byte[] transactionContext, FileAccess access, FileOptions options, Int64 allocationSize) at System.Data.SqlTypes.SqlFileStream..ctor(String path, Byte[] transactionContext, FileAccess access, FileOptions options, Int64 allocationSize) at System.Data.SqlTypes.SqlFileStream..ctor(String path, Byte[] transactionContext, FileAccess access) Thanks

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Is there any way that an export-to-Excel function can be scalable?

- by MusiGenesis

Summary: ASP.Net website with a couple hundred users. Data is exported to Excel files which can be relatively large (~5 MB). In the pilot phase (just a few users), we are already seeing occasional errors on the server in the exporting method. Here's the stack trace: System.Web.HttpUnhandledException: Exception of type 'System.Web.HttpUnhandledException' was thrown. --- System.OutOfMemoryException: Exception of type 'System.OutOfMemoryException' was thrown. at System.IO.MemoryStream.set_Capacity(Int32 value) at System.IO.MemoryStream.EnsureCapacity(Int32 value) at System.IO.MemoryStream.Write(Byte[] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Packaging.TrackingMemoryStream.Write(Byte[] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Packaging.SparseMemoryStream.WriteAndCollapseBlocks(Byte[ ] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Packaging.SparseMemoryStream.Write(Byte[] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Packaging.CompressEmulationStream.Write(Byte[] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Packaging.CompressStream.Write(Byte[] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Zip.ProgressiveCrcCalculatingStream.Write(Byte[] buffer, Int32 offset, Int32 count) at MS.Internal.IO.Zip.ZipIOModeEnforcingStream.Write(Byte[] buffer, Int32 offset, Int32 count) at System.IO.StreamWriter.Flush(Boolean flushStream, Boolean flushEncoder) at System.IO.StreamWriter.Write(String value) at System.Xml.XmlTextEncoder.Write(String text) at System.Xml.XmlTextWriter.WriteString(String text) at System.Xml.XmlText.WriteTo(XmlWriter w) at System.Xml.XmlAttribute.WriteContentTo(XmlWriter w) at System.Xml.XmlAttribute.WriteTo(XmlWriter w) at System.Xml.XmlElement.WriteTo(XmlWriter w) at System.Xml.XmlElement.WriteContentTo(XmlWriter w) at System.Xml.XmlElement.WriteTo(XmlWriter w) at System.Xml.XmlElement.WriteContentTo(XmlWriter w) at System.Xml.XmlElement.WriteTo(XmlWriter w) at System.Xml.XmlElement.WriteContentTo(XmlWriter w) at System.Xml.XmlElement.WriteTo(XmlWriter w) at System.Xml.XmlDocument.WriteContentTo(XmlWriter xw) at System.Xml.XmlDocument.WriteTo(XmlWriter w) at System.Xml.XmlDocument.Save(Stream outStream) at OfficeOpenXml.ExcelWorksheet.Save() in C:\temp\XXXXXXXXXX\ExcelPackage\ExcelWorksheet.cs:line 605 at OfficeOpenXml.ExcelWorkbook.Save() in C:\temp\XXXXXXXXXX\ExcelPackage\ExcelWorkbook.cs:line 439 at OfficeOpenXml.ExcelPackage.Save() in C:\temp\XXXXXXXXXX\ExcelPackage\ExcelPackage.cs:line 348 at Framework.Exporting.Business.ExcelExport.BuildReport(HttpContext context) at WebUserControl.BtnXLS_Click(Object sender, EventArgs e) in C:\TEMP\XXXXXXXXXX\XXXXXXXXXX\OneList\UserControls\TicketReportExporter. ascx.cs:line 108 at System.Web.UI.WebControls.Button.OnClick(EventArgs e) at System.Web.UI.WebControls.Button.RaisePostBackEvent(String eventArgument) at System.Web.UI.WebControls.Button.System.Web.UI.IPostBackEventHandler.Rai sePostBackEvent(String eventArgument) at System.Web.UI.Page.RaisePostBackEvent(IPostBackEventHandler sourceControl, String eventArgument) at System.Web.UI.Page.RaisePostBackEvent(NameValueCollection postData) at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) --- End of inner exception stack trace --- at System.Web.UI.Page.HandleError(Exception e) at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) at System.Web.UI.Page.ProcessRequest(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) at System.Web.UI.Page.ProcessRequest() at System.Web.UI.Page.ProcessRequestWithNoAssert(HttpContext context) at System.Web.UI.Page.ProcessRequest(HttpContext context) at ASP.XXXXXXXXXXX_aspx.ProcessRequest(HttpContext context) in c:\WINDOWS\Microsoft.NET\Framework\v2.0.50727\Temporary ASP.NET Files\XXXX\cdf32a52\d1a5eabd\App_Web_enxdwlks.1.cs:line 0 at System.Web.HttpApplication.CallHandlerExecutionStep.System.Web.HttpAppli cation.IExecutionStep.Execute() at System.Web.HttpApplication.ExecuteStep(IExecutionStep step, Boolean& completedSynchronously) Even aside from this particular problem, in general exporting to Excel requires the instantiation of huge Excel objects on the server for each request, which I've always assumed to mean disqualifies Excel for "serious" work on a highly-loaded server. Is there any general way to export to Excel in a "light-weight" manner? Would simply streaming the data into a CSV file work for this?

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Printf in assembler doesn't print

- by Gaim

Hi there, I have got a homework to hack program using buffer overflow ( with disassambling, program was written in C++, I haven't got the source code ). I have already managed it but I have a problem. I have to print some message on the screen, so I found out address of printf function, pushed address of "HACKED" and address of "%s" on the stack ( in this order ) and called that function. Called code passed well but nothing had been printed. I have tried to simulate the environment like in other place in the program but there has to be something wrong. Do you have any idea what I am doing wrong that I have no output, please? Thanks a lot EDIT: This program is running on Windows XP SP3 32b, written in C++, Intel asm there is the "hack" code CPU Disasm Address Hex dump Command Comments 0012F9A3 90 NOP ;hack begins 0012F9A4 90 NOP 0012F9A5 90 NOP 0012F9A6 89E5 MOV EBP,ESP 0012F9A8 83EC 7F SUB ESP,7F ;creating a place for working data 0012F9AB 83EC 7F SUB ESP,7F 0012F9AE 31C0 XOR EAX,EAX 0012F9B0 50 PUSH EAX 0012F9B1 50 PUSH EAX 0012F9B2 50 PUSH EAX 0012F9B3 89E8 MOV EAX,EBP 0012F9B5 83E8 09 SUB EAX,9 0012F9B8 BA 1406EDFF MOV EDX,FFED0614 ;address to jump, it is negative because there mustn't be 00 bytes 0012F9BD F7DA NOT EDX 0012F9BF FFE2 JMP EDX ;I have to jump because there are some values overwritten by the program 0012F9C1 90 NOP 0012F9C2 0090 00000000 ADD BYTE PTR DS:[EAX],DL 0012F9C8 90 NOP 0012F9C9 90 NOP 0012F9CA 90 NOP 0012F9CB 90 NOP 0012F9CC 6C INS BYTE PTR ES:[EDI],DX ; I/O command 0012F9CD 65:6E OUTS DX,BYTE PTR GS:[ESI] ; I/O command 0012F9CF 67:74 68 JE SHORT 0012FA3A ; Superfluous address size prefix 0012F9D2 2069 73 AND BYTE PTR DS:[ECX+73],CH 0012F9D5 203439 AND BYTE PTR DS:[EDI+ECX],DH 0012F9D8 34 2C XOR AL,2C 0012F9DA 2066 69 AND BYTE PTR DS:[ESI+69],AH 0012F9DD 72 73 JB SHORT 0012FA52 0012F9DF 74 20 JE SHORT 0012FA01 0012F9E1 3120 XOR DWORD PTR DS:[EAX],ESP 0012F9E3 6C INS BYTE PTR ES:[EDI],DX ; I/O command 0012F9E4 696E 65 7300909 IMUL EBP,DWORD PTR DS:[ESI+65],-6F6FFF8D 0012F9EB 90 NOP 0012F9EC 90 NOP 0012F9ED 90 NOP 0012F9EE 31DB XOR EBX,EBX ; hack continues 0012F9F0 8818 MOV BYTE PTR DS:[EAX],BL ; writing 00 behind word "HACKED" 0012F9F2 83E8 06 SUB EAX,6 0012F9F5 50 PUSH EAX ; address of "HACKED" 0012F9F6 B8 3B8CBEFF MOV EAX,FFBE8C3B 0012F9FB F7D0 NOT EAX 0012F9FD 50 PUSH EAX ; address of "%s" 0012F9FE B8 FFE4BFFF MOV EAX,FFBFE4FF 0012FA03 F7D0 NOT EAX 0012FA05 FFD0 CALL EAX ;address of printf This code is really ugly because I am new in assembler and there mustn't be null bytes because of buffer-overflow bug

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A reference that is not to 'const' cannot be bound to a non-lvalue

- by Bert

Hello, Am struggling a bit with this. Am declaring: BYTE *pImage = NULL; Used in call: m_pMyInterface-GetImage(i, &imageSize, &pImage); Visual C++ 2003 compiler error: error C2664: 'CJrvdInterface::GetImage' : cannot convert parameter 3 from 'BYTE **__w64 ' to 'BYTE **& ' A reference that is not to 'const' cannot be bound to a non-lvalue The method called is defined as: void CMyInterface::GetImage(const int &a_iTileId, ULONG *a_pulImageSize, BYTE** &a_ppbImage) { (...) Any help much appreciated, Bert

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How to get compatibility between C# and SQL2k8 AES Encryption?

- by Victor Rodrigues

I have an AES encryption being made on two columns: one of these columns is stored at a SQL Server 2000 database; the other is stored at a SQL Server 2008 database. As the first column's database (2000) doesn't have native functionality for encryption / decryption, we've decided to do the cryptography logic at application level, with .NET classes, for both. But as the second column's database (2008) allow this kind of functionality, we'd like to make the data migration using the database functions to be faster, since the data migration in SQL 2k is much smaller than this second and it will last more than 50 hours because of being made at application level. My problem started at this point: using the same key, I didn't achieve the same result when encrypting a value, neither the same result size. Below we have the full logic in both sides.. Of course I'm not showing the key, but everything else is the same: private byte[] RijndaelEncrypt(byte[] clearData, byte[] Key) { var memoryStream = new MemoryStream(); Rijndael algorithm = Rijndael.Create(); algorithm.Key = Key; algorithm.IV = InitializationVector; var criptoStream = new CryptoStream(memoryStream, algorithm.CreateEncryptor(), CryptoStreamMode.Write); criptoStream.Write(clearData, 0, clearData.Length); criptoStream.Close(); byte[] encryptedData = memoryStream.ToArray(); return encryptedData; } private byte[] RijndaelDecrypt(byte[] cipherData, byte[] Key) { var memoryStream = new MemoryStream(); Rijndael algorithm = Rijndael.Create(); algorithm.Key = Key; algorithm.IV = InitializationVector; var criptoStream = new CryptoStream(memoryStream, algorithm.CreateDecryptor(), CryptoStreamMode.Write); criptoStream.Write(cipherData, 0, cipherData.Length); criptoStream.Close(); byte[] decryptedData = memoryStream.ToArray(); return decryptedData; } This is the SQL Code sample: open symmetric key columnKey decryption by password = N'{pwd!!i_ll_not_show_it_here}' declare @enc varchar(max) set @enc = dbo.VarBinarytoBase64(EncryptByKey(Key_GUID('columnKey'), 'blablabla')) select LEN(@enc), @enc This varbinaryToBase64 is a tested sql function we use to convert varbinary to the same format we use to store strings in the .net application. The result in C# is: eg0wgTeR3noWYgvdmpzTKijkdtTsdvnvKzh+uhyN3Lo= The same result in SQL2k8 is: AI0zI7D77EmqgTQrdgMBHAEAAACyACXb+P3HvctA0yBduAuwPS4Ah3AB4Dbdj2KBGC1Dk4b8GEbtXs5fINzvusp8FRBknF15Br2xI1CqP0Qb/M4w I just didn't get yet what I'm doing wrong. Do you have any ideas? EDIT: One point I think is crucial: I have one Initialization Vector at my C# code, 16 bytes. This IV is not set at SQL symmetric key, could I do this? But even not filling the IV in C#, I get very different results, both in content and length.

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Compilation error: casting.

- by Andrei Ciobanu

Can somebody explain me why the following piece of code fails to compile. The error is: "Possible loss of precision." : byte a = 50; byte b = 40; byte sum = (byte)a + b; System.out.println(sum); Thank you.

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Can this way of storing typed objects be improved?

- by Pindatjuh

This is an "can it be improved"-question. Topic: Storing typed objects in memory. Background information: I'm building a compiler for the x86-32 Windows platform for my language. My goal includes typed objects. Idea: Every primitive is a semi-class (it can be used as if it was a normal class, but it's stored more compact). Every class is represented by primitives and some meta-data (containing class-properties, inheritance stuff, etc.). The meta-data is complex: it doesn't use fields but instead context-switches. For primitives, the meta-data is very small, compared to a "real" class, which is alot bigger. This enables another idea that "primitives are objects", in my language, which I found nessecairy. Example: If I have an array of 32 booleans, then the pure content of this array is exactly 4 byte (32 bits of booleans). The meta-data will contain flags that the type is an array of booleans, which contains 32 entries. The meta-data is very compacted, on bit-level: using a sort of "packing" mechanism, which is read by a FSM at runtime, when doing inspection of the type (like when passing the object to methods for checking, etc.) For instance (read from left to right, top to bottom, remember vertical position when going to the right, and check nearest column header for meaning of switch): Primitive? Array? Type-Meta 1 Byte? || Size (1 byte) 1 1 [...] 1 [...] done 0 2 Bytes? || Size (2 bytes) 1 [...] done || Size (4 bytes) 0 [...] done Integer? 1 Byte? 2 Bytes? 0 1 0 1 done 1 done 0 done Boolean? Byte? 0 1 0 done 1 done More-Primitives 0 .... Class-Stuff (Huge) 0 ... (After reaching done the data is inserted. || = byte alignment. [...] is variable sized. ... is not described here, for simplicity. And let's call them cost-based-data-structures.) For an array of 32 booleans containing all true values, the memory for this type would be (read top-down): 1 Primitive 1 Array 1 ArrayType: Primitive 0 Not-Array 0 Not-Integer 1 Boolean 0 Not-Byte (thus bit) 1 Integer Size: 1 Byte 00100000 Array size 01010101 01010101 01010101 01010101 Data (user defined) Thus, 8 bytes represent 32 booleans in an array: 11100101 00100000 01010101 01010101 01010101 01010101 How can I improve this? (Both performance- and memory-consumption wise)

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Objective C - Parse NSData

- by EZFrag

I have the following data inside an NSData object: <00000000 6f2d840e 31504159 2e535953 2e444446 3031a51b 8801015f 2d02656e 9f110101 bf0c0cc5 0affff3f 00000003 ffff03 I'm having issues parsing this data. This data contains information which is marked by tags Tag 1 is from byte value 0x84 to 0xa5 Tag 2 is from byte value 0xa5 to 0x88 Tag 3 is from byte value 0x88 to 0x5f0x2d Tag 4 is from byte value 0x5f0x2d to 0x9f0x11 How would I go about to get those values from the NSData object? Regards, EZFrag

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bit ordering and endianess

- by Neeraj

I am reading a file byte-by-byte. Say for example i have this byte: 0x41 (0100 0001) represented in hex. Now, I want the first three bits of this byte, i.e (010). I can use bitwise logic to extract the first three bits, but my question is will the first three bits be independent of endianess of the machine.(i.e they can't be 001)? Thanks,

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Heaps of Trouble?

- by Paul White NZ

If you’re not already a regular reader of Brad Schulz’s blog, you’re missing out on some great material. In his latest entry, he is tasked with optimizing a query run against tables that have no indexes at all. The problem is, predictably, that performance is not very good. The catch is that we are not allowed to create any indexes (or even new statistics) as part of our optimization efforts. In this post, I’m going to look at the problem from a slightly different angle, and present an alternative solution to the one Brad found. Inevitably, there’s going to be some overlap between our entries, and while you don’t necessarily need to read Brad’s post before this one, I do strongly recommend that you read it at some stage; he covers some important points that I won’t cover again here. The Example We’ll use data from the AdventureWorks database, copied to temporary unindexed tables. A script to create these structures is shown below: CREATE TABLE #Custs ( CustomerID INTEGER NOT NULL, TerritoryID INTEGER NULL, CustomerType NCHAR(1) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, ); GO CREATE TABLE #Prods ( ProductMainID INTEGER NOT NULL, ProductSubID INTEGER NOT NULL, ProductSubSubID INTEGER NOT NULL, Name NVARCHAR(50) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, ); GO CREATE TABLE #OrdHeader ( SalesOrderID INTEGER NOT NULL, OrderDate DATETIME NOT NULL, SalesOrderNumber NVARCHAR(25) COLLATE SQL_Latin1_General_CP1_CI_AI NOT NULL, CustomerID INTEGER NOT NULL, ); GO CREATE TABLE #OrdDetail ( SalesOrderID INTEGER NOT NULL, OrderQty SMALLINT NOT NULL, LineTotal NUMERIC(38,6) NOT NULL, ProductMainID INTEGER NOT NULL, ProductSubID INTEGER NOT NULL, ProductSubSubID INTEGER NOT NULL, ); GO INSERT #Custs ( CustomerID, TerritoryID, CustomerType ) SELECT C.CustomerID, C.TerritoryID, C.CustomerType FROM AdventureWorks.Sales.Customer C WITH (TABLOCK); GO INSERT #Prods ( ProductMainID, ProductSubID, ProductSubSubID, Name ) SELECT P.ProductID, P.ProductID, P.ProductID, P.Name FROM AdventureWorks.Production.Product P WITH (TABLOCK); GO INSERT #OrdHeader ( SalesOrderID, OrderDate, SalesOrderNumber, CustomerID ) SELECT H.SalesOrderID, H.OrderDate, H.SalesOrderNumber, H.CustomerID FROM AdventureWorks.Sales.SalesOrderHeader H WITH (TABLOCK); GO INSERT #OrdDetail ( SalesOrderID, OrderQty, LineTotal, ProductMainID, ProductSubID, ProductSubSubID ) SELECT D.SalesOrderID, D.OrderQty, D.LineTotal, D.ProductID, D.ProductID, D.ProductID FROM AdventureWorks.Sales.SalesOrderDetail D WITH (TABLOCK); The query itself is a simple join of the four tables: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #Prods P JOIN #OrdDetail D ON P.ProductMainID = D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID JOIN #OrdHeader H ON D.SalesOrderID = H.SalesOrderID JOIN #Custs C ON H.CustomerID = C.CustomerID ORDER BY P.ProductMainID ASC OPTION (RECOMPILE, MAXDOP 1); Remember that these tables have no indexes at all, and only the single-column sampled statistics SQL Server automatically creates (assuming default settings). The estimated query plan produced for the test query looks like this (click to enlarge): The Problem The problem here is one of cardinality estimation – the number of rows SQL Server expects to find at each step of the plan. The lack of indexes and useful statistical information means that SQL Server does not have the information it needs to make a good estimate. Every join in the plan shown above estimates that it will produce just a single row as output. Brad covers the factors that lead to the low estimates in his post. In reality, the join between the #Prods and #OrdDetail tables will produce 121,317 rows. It should not surprise you that this has rather dire consequences for the remainder of the query plan. In particular, it makes a nonsense of the optimizer’s decision to use Nested Loops to join to the two remaining tables. Instead of scanning the #OrdHeader and #Custs tables once (as it expected), it has to perform 121,317 full scans of each. The query takes somewhere in the region of twenty minutes to run to completion on my development machine. A Solution At this point, you may be thinking the same thing I was: if we really are stuck with no indexes, the best we can do is to use hash joins everywhere. We can force the exclusive use of hash joins in several ways, the two most common being join and query hints. A join hint means writing the query using the INNER HASH JOIN syntax; using a query hint involves adding OPTION (HASH JOIN) at the bottom of the query. The difference is that using join hints also forces the order of the join, whereas the query hint gives the optimizer freedom to reorder the joins at its discretion. Adding the OPTION (HASH JOIN) hint results in this estimated plan: That produces the correct output in around seven seconds, which is quite an improvement! As a purely practical matter, and given the rigid rules of the environment we find ourselves in, we might leave things there. (We can improve the hashing solution a bit – I’ll come back to that later on). Faster Nested Loops It might surprise you to hear that we can beat the performance of the hash join solution shown above using nested loops joins exclusively, and without breaking the rules we have been set. The key to this part is to realize that a condition like (A = B) can be expressed as (A <= B) AND (A >= B). Armed with this tremendous new insight, we can rewrite the join predicates like so: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #OrdDetail D JOIN #OrdHeader H ON D.SalesOrderID >= H.SalesOrderID AND D.SalesOrderID <= H.SalesOrderID JOIN #Custs C ON H.CustomerID >= C.CustomerID AND H.CustomerID <= C.CustomerID JOIN #Prods P ON P.ProductMainID >= D.ProductMainID AND P.ProductMainID <= D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID ORDER BY D.ProductMainID OPTION (RECOMPILE, LOOP JOIN, MAXDOP 1, FORCE ORDER); I’ve also added LOOP JOIN and FORCE ORDER query hints to ensure that only nested loops joins are used, and that the tables are joined in the order they appear. The new estimated execution plan is: This new query runs in under 2 seconds. Why Is It Faster? The main reason for the improvement is the appearance of the eager Index Spools, which are also known as index-on-the-fly spools. If you read my Inside The Optimiser series you might be interested to know that the rule responsible is called JoinToIndexOnTheFly. An eager index spool consumes all rows from the table it sits above, and builds a index suitable for the join to seek on. Taking the index spool above the #Custs table as an example, it reads all the CustomerID and TerritoryID values with a single scan of the table, and builds an index keyed on CustomerID. The term ‘eager’ means that the spool consumes all of its input rows when it starts up. The index is built in a work table in tempdb, has no associated statistics, and only exists until the query finishes executing. The result is that each unindexed table is only scanned once, and just for the columns necessary to build the temporary index. From that point on, every execution of the inner side of the join is answered by a seek on the temporary index – not the base table. A second optimization is that the sort on ProductMainID (required by the ORDER BY clause) is performed early, on just the rows coming from the #OrdDetail table. The optimizer has a good estimate for the number of rows it needs to sort at that stage – it is just the cardinality of the table itself. The accuracy of the estimate there is important because it helps determine the memory grant given to the sort operation. Nested loops join preserves the order of rows on its outer input, so sorting early is safe. (Hash joins do not preserve order in this way, of course). The extra lazy spool on the #Prods branch is a further optimization that avoids executing the seek on the temporary index if the value being joined (the ‘outer reference’) hasn’t changed from the last row received on the outer input. It takes advantage of the fact that rows are still sorted on ProductMainID, so if duplicates exist, they will arrive at the join operator one after the other. The optimizer is quite conservative about introducing index spools into a plan, because creating and dropping a temporary index is a relatively expensive operation. It’s presence in a plan is often an indication that a useful index is missing. I want to stress that I rewrote the query in this way primarily as an educational exercise – I can’t imagine having to do something so horrible to a production system. Improving the Hash Join I promised I would return to the solution that uses hash joins. You might be puzzled that SQL Server can create three new indexes (and perform all those nested loops iterations) faster than it can perform three hash joins. The answer, again, is down to the poor information available to the optimizer. Let’s look at the hash join plan again: Two of the hash joins have single-row estimates on their build inputs. SQL Server fixes the amount of memory available for the hash table based on this cardinality estimate, so at run time the hash join very quickly runs out of memory. This results in the join spilling hash buckets to disk, and any rows from the probe input that hash to the spilled buckets also get written to disk. The join process then continues, and may again run out of memory. This is a recursive process, which may eventually result in SQL Server resorting to a bailout join algorithm, which is guaranteed to complete eventually, but may be very slow. The data sizes in the example tables are not large enough to force a hash bailout, but it does result in multiple levels of hash recursion. You can see this for yourself by tracing the Hash Warning event using the Profiler tool. The final sort in the plan also suffers from a similar problem: it receives very little memory and has to perform multiple sort passes, saving intermediate runs to disk (the Sort Warnings Profiler event can be used to confirm this). Notice also that because hash joins don’t preserve sort order, the sort cannot be pushed down the plan toward the #OrdDetail table, as in the nested loops plan. Ok, so now we understand the problems, what can we do to fix it? We can address the hash spilling by forcing a different order for the joins: SELECT P.ProductMainID AS PID, P.Name, D.OrderQty, H.SalesOrderNumber, H.OrderDate, C.TerritoryID FROM #Prods P JOIN #Custs C JOIN #OrdHeader H ON H.CustomerID = C.CustomerID JOIN #OrdDetail D ON D.SalesOrderID = H.SalesOrderID ON P.ProductMainID = D.ProductMainID AND P.ProductSubID = D.ProductSubID AND P.ProductSubSubID = D.ProductSubSubID ORDER BY D.ProductMainID OPTION (MAXDOP 1, HASH JOIN, FORCE ORDER); With this plan, each of the inputs to the hash joins has a good estimate, and no hash recursion occurs. The final sort still suffers from the one-row estimate problem, and we get a single-pass sort warning as it writes rows to disk. Even so, the query runs to completion in three or four seconds. That’s around half the time of the previous hashing solution, but still not as fast as the nested loops trickery. Final Thoughts SQL Server’s optimizer makes cost-based decisions, so it is vital to provide it with accurate information. We can’t really blame the performance problems highlighted here on anything other than the decision to use completely unindexed tables, and not to allow the creation of additional statistics. I should probably stress that the nested loops solution shown above is not one I would normally contemplate in the real world. It’s there primarily for its educational and entertainment value. I might perhaps use it to demonstrate to the sceptical that SQL Server itself is crying out for an index. Be sure to read Brad’s original post for more details. My grateful thanks to him for granting permission to reuse some of his material. Paul White Email: [email protected] Twitter: @PaulWhiteNZ

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Uninitialized constant Item::Types

- by Rasmus

Hi! First of, im a newbie ruby programmer so please bare with me if this is a very dumb question. I get this uninitialized constant error when i submit my nested forms. order.rb class Order < ActiveRecord::Base has_many :items, :dependent => :destroy has_many :types, :through => :items accepts_nested_attributes_for :items accepts_nested_attributes_for :types validates_associated :items validates_associated :types end item.rb class Item < ActiveRecord::Base has_one :types belongs_to :order accepts_nested_attributes_for :types validates_associated :types end type.rb class Type < ActiveRecord::Base belongs_to :items belongs_to :orders end new.erb.html <% form_for @order do |f| %> <%= f.error_messages %> <% f.fields_for :items do |builder| %> <table border="0"> <th>Type</th> <th>Amount</th> <th>Text</th> <th>Price</th> <tr> <% f.fields_for :type do |m| %> <td> <%= m.collection_select :type, Type.find(:all, :order => "created_at DESC"), :id, :name, {:prompt => "Select a Type" }, {:id => "selector", :onchange => "type_change(this)"} %> </td> <% end %> <td> <%= f.text_field :amount, :id => "amountField", :onchange => "change_total_price()" %> </td> <td> <%= f.text_field :text, :id => "textField" %> </td> <td> <%= f.text_field :price, :class => "priceField", :onChange => "change_total_price()" %> </td> <td> <%= link_to_remove_fields "Remove Item", f %> </td> </tr> </table> <% end %> <p><%= link_to_add_fields "Add Item", f, :items %></p> <p> <%= f.label :total_price %><br /> <%= f.text_field :total_price, :class => "priceField", :id => "totalPrice" %> </p> <p><%= f.submit "Create"%></p> <% end %> <%= link_to 'Back', orders_path %> create method in orders_controller.rb def create @order = Order.new(params[:order]) respond_to do |format| if @order.save flash[:notice] = 'Post was successfully created.' format.html { redirect_to(@order) } format.xml { render :xml => @order, :status => :created, :location => @order } else format.html { render :action => "new" } format.xml { render :xml => @order.errors, :status => :unprocessable_entity } end end end Hopefully you can see what i cant

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h:dataTable alternating rows in JSF2

- by Benchik

Hello. I'm trying to make alternating rows in JSF2 h:dataTable (no richfaces or such) but i get an unexpected result. the table is built but it has a white grid shown (but i didn't specifiy any border) and there's no buttom line under each row. The CSS: .order-table{ border-collapse:collapse; } .order-table-header{ text-align:center; background:none repeat scroll 0 0 #E5E5E5; border-bottom:1px solid #95bce2; padding:16px; } .order-table-odd-row{ text-align:center; background:none repeat scroll 0 0 #FFFFFFF; border-top:1px solid #000000; } .order-table-even-row{ text-align:center; background:none repeat scroll 0 0 #ecf6fc; border-top:1px solid #BBBBBB; } table.order-table tr.over { background-color: #bcd4ec; } The table: <h:dataTable id="personsTable" value="#{personController.allPersons}" var="bean" styleClass="order-table" headerClass="order-table-header" rowClasses="order-table-odd-row,order-table-even-row"> <h:column> <f:facet name="header"> <h:outputText value="First Name" /> </f:facet> <h:outputText value="#{bean.firstName}"/> </h:column> <h:column> <f:facet name="header"> <h:outputText value="Last Name" /> </f:facet> <h:outputText value="#{bean.lastName}"/> </h:column> <h:column> <f:facet name="header"> <h:outputText value="Phone" /> </f:facet> <h:outputText value="#{bean.phone}"/> </h:column> </h:dataTable> and a small JQuery script: <script type="text/javascript"> $(document).ready(function(){ $(".order-table tr").mouseover(function(){ $(this).addClass("over"); }); $(".order-table tr").mouseout(function(){ $(this).removeClass("over"); }); }); </script> The result is (notice the white grid that came from i don't know where. And also no underline which should come from the CSS): http://imagebin.org/132574

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