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  • check if a tree is a binary search tree

    - by TimeToCodeTheRoad
    I have written the following code to check if a tree is a Binary search tree. Please help me check the code: Pair p{ boolean isTrue; int min; int max; } public boo lean isBst(BNode v){ return isBST1(v).isTrue; } public Pair isBST1(BNode v){ if(v==null) return new Pair(true, INTEGER.MIN,INTEGER.MAX); if(v.left==null && v.right==null) return new Pair(true, v.data, v.data); Pair pLeft=isBST1(v.left); Pair pRight=isBST1(v.right); boolean check=pLeft.max<v.data && v.data<= pRight.min; Pair p=new Pair(); p.isTrue=check&&pLeft.isTrue&&pRight.isTrue; p.min=pLeft.min; p.max=pRight.max; return p; } Note: This function checks if a tree is a binary search tree

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  • Convert a post-order binary tree traversal index to an level-order (breadth-first) index

    - by strfry
    Assuming a complete binary tree, each node can be adressed with the position it appears in a given tree traversal algorithm. For example, the node indices of a simple complete tree with height 3 would look like this: breadth first (aka level-order): 0 / \ 1 2 / \ / \ 3 4 5 6 post-order dept first: 6 / \ 2 5 / \ / \ 0 1 3 4 The height of the tree and an index in the post-order traversal is given. How can i calculate the breadth first index from this information?

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  • Which non-clustered index should I use?

    - by Junior Mayhé
    Here I am studying nonclustered indexes on SQL Server Management Studio. I've created a table with more than 1 million records. This table has a primary key. CREATE TABLE [dbo].[Customers]( [CustomerId] [int] IDENTITY(1,1) NOT NULL, [CustomerName] [varchar](100) NOT NULL, [Deleted] [bit] NOT NULL, [Active] [bit] NOT NULL, CONSTRAINT [PK_Customers] PRIMARY KEY CLUSTERED ( [CustomerId] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, IGNORE_DUP_KEY = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] ) ON [PRIMARY] This is the query I'll be using to see what execution plan is showing: SELECT CustomerName FROM Customers Well, executing this command with no additional non-clustered index, it leads the execution plan to show me: I/O cost = 3.45646 Operator cost = 4.57715 Now I'm trying to see if it's possible to improve performance, so I've created a non-clustered index for this table: 1) First non-clustered index CREATE NONCLUSTERED INDEX [IX_CustomerID_CustomerName] ON [dbo].[Customers] ( [CustomerId] ASC, [CustomerName] ASC )WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] GO Executing again the select against Customers table, the execution plan shows me: I/O cost = 2.79942 Operator cost = 3.92001 It seems better. Now I've deleted this just created non-clustered index, in order to create a new one: 2) First non-clustered index CREATE NONCLUSTERED INDEX [IX_CustomerIDIncludeCustomerName] ON [dbo].[Customers] ( [CustomerId] ASC ) INCLUDE ( [CustomerName]) WITH (PAD_INDEX = OFF, STATISTICS_NORECOMPUTE = OFF, SORT_IN_TEMPDB = OFF, IGNORE_DUP_KEY = OFF, DROP_EXISTING = OFF, ONLINE = OFF, ALLOW_ROW_LOCKS = ON, ALLOW_PAGE_LOCKS = ON) ON [PRIMARY] GO With this new non-clustered index, I've executed the select statement again and the execution plan shows me the same result: I/O cost = 2.79942 Operator cost = 3.92001 So, which non-clustered index should I use? Why the costs are the same on execution plan for I/O and Operator? Am I doing something wrong or this is expected? thank you

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  • how does NTFS actually work with B-tree ?

    - by bakra
    To improve performance, NTFS directories use a special data management structure called a B-tree. "B-tree" concept here refers to a "tree of storage units" that hold the contents of an individual directory. What I don't understand is where on the disk is this tree stored? Its surely not created every-time we reboot...that would take lots of time. and since its a tree(dynamic Data structure) unlike arrays it will grow. so space needs to be allocated every-time it grows. so how is this "dynamic meta-data" stored ?

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  • Create an index only on certain rows in mysql

    - by dhruvbird
    So, I have this funny requirement of creating an index on a table only on a certain set of rows. This is what my table looks like: USER: userid, friendid, created, blah0, blah1, ..., blahN Now, I'd like to create an index on: (userid, friendid, created) but only on those rows where userid = friendid. The reason being that this index is only going to be used to satisfy queries where the WHERE clause contains "userid = friendid". There will be many rows where this is NOT the case, and I really don't want to waste all that extra space on the index. Another option would be to create a table (query table) which is populated on insert/update of this table and create a trigger to do so, but again I am guessing an index on that table would mean that the data would be stored twice. How does mysql store Primary Keys? I mean is the table ordered on the Primary Key or is it ordered by insert order and the PK is like a normal unique index? I checked up on clustered indexes (http://dev.mysql.com/doc/refman/5.0/en/innodb-index-types.html), but it seems only InnoDB supports them. I am using MyISAM (I mention this because then I could have created a clustered index on these 3 fields in the query table). I am basically looking for something like this: ALTER TABLE USERS ADD INDEX (userid, friendid, created) WHERE userid=friendid

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  • Html index page and files in that directory

    - by Frank
    On my web site, there is an index page, but if I take out that index page, users will see the files in that directory, for instance my site is : XYZ.com and I have a directory called "My_Dir", so when a user typed in "XYZ.com/My_Dir" he will see the index.html if there is one, but if it's not there, he will see a list of all my files inside "My_Dir", so is it safe to assume that with an index page in any of my sub directories, I can hide all the files in those directories from users, in other words if I have "123.txt, abc.html and index.html" in "My_Dir", users won't be able to see "123.txt, abc.html" because of the existence of "index.html" [ unless of course I mention those two files inside index.html ] ? Frank

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  • Accessing selected node of richfaces tree from Javascript

    - by kazanaki
    Hello This should be a very simple question. I have a richfaces tree that is rendered using JSF. When the user clicks on a node I want a javascript function to run. Nothing more nothing less. No redirects, no re-submit, no-rerender, no Ajax. Just plain old Javascript. I have seen the onselected attribute of the tree and it indeed fires a Javascript method. But of course I want to know which node was clicked. Here is what I have so far <head> <script type="text/javascript"> function documentClicked(nodeRef) { alert("Node is "+nodeRef); } </script> </head> <rich:tree switchType="client" value="#{ajaxDocumentTree.rootNode}" var="document" onselected="documentClicked()" > <rich:treeNode iconLeaf="../images/tree/doc.gif" icon="../images/tree/doc.gif"> <h:outputText value="#{doc.friendlyName}" /> </rich:treeNode> But this does not work because nodeRef is undefined. I expected that the first argument of the callback would be the selected node but this is not the case. So the question is this: How do I fire a Javascript function with the selected node from a richfaces tree?

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  • JQGrid tree - passing additional parameters when tree is expanded

    - by PHP thinker
    I have a JQGRid tree. It loads data click by click, not all at once. Typically, JQGRid passes 4 standard tree parameters with each call - row (level, parent, is leaf, is expanded). How can I pass more parameters that I will take from the row being expanded? E.g. data from Name column should be passed in AJAX call too. There doesn't seem to be OnExpand event or similar.

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  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • SQL Server Index cost

    - by yellowstar
    I have read that one of the tradeoffs for adding table indexes in SQL Server is the increased cost of insert/update/delete queries to benefit the performance of select queries. I can conceptually understand what happens in the case of an insert because SQL Server has to write entries into each index matching the new rows, but update and delete are a little more murky to me because I can't quite wrap my head around what the database engine has to do. Let's take DELETE as an example and assume I have the following schema (pardon the pseudo-SQL) TABLE Foo col1 int ,col2 int ,col3 int ,col4 int PRIMARY KEY (col1,col2) INDEX IX_1 col3 INCLUDE col4 Now, if I issue the statement DELETE FROM Foo WHERE col1=12 AND col2 > 34 I understand what the engine must do to update the table (or clustered index if you prefer). The index is set up to make it easy to find the range of rows to be removed and do so. However, at this point it also needs to update IX_1 and the query that I gave it gives no obvious efficient way for the database engine to find the rows to update. Is it forced to do a full index scan at this point? Does the engine read the rows from the clustered index first and generate a smarter internal delete against the index? It might help me to wrap my head around this if I understood better what is going on under the hood, but I guess my real question is this. I have a database that is spending a significant amount of time in delete and I'm trying to figure out what I can do about it. When I display the execution plan for the deletion, it just shows an entry for "Clustered Index Delete" on table Foo which lists in the details section the other indices that need to be updated but I don't get any indication of the relative cost of these other indices. Are they all equal in this case? Is there some way that I can estimate the impact of removing one or more of these indices without having to actually try it?

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  • k-d tree implementation [closed]

    - by user466441
    when i run my code and debugged,i got this error - this 0x00093584 {_Myproxy=0x00000000 _Mynextiter=0x00000000 } std::_Iterator_base12 * const - _Myproxy 0x00000000 {_Mycont=??? _Myfirstiter=??? } std::_Container_proxy * _Mycont CXX0017: Error: symbol "" not found _Myfirstiter CXX0030: Error: expression cannot be evaluated + _Mynextiter 0x00000000 {_Myproxy=??? _Mynextiter=??? } std::_Iterator_base12 * but i dont know what does it means,code is this #include<iostream> #include<vector> #include<algorithm> using namespace std; struct point { float x,y; }; vector<point>pointleft(4); vector<point>pointright(4); //we are going to implement two comparison function for x and y coordinates,we need it in calculation of median (we should sort vector //by x or y according to depth informaton,is depth even or odd. bool sortby_X(point &a,point &b) { return a.x<b.x; } bool sortby_Y(point &a,point &b) { return a.y<b.y; } //so i am going to implement to median finding algorithm,one for finding median by x and another find median by y point medianx(vector<point>points) { point temp; sort(points.begin(),points.end(),sortby_X); temp=points[(points.size()/2)]; return temp; } point mediany(vector<point>points) { point temp; sort(points.begin(),points.end(),sortby_Y); temp=points[(points.size()/2)]; return temp; } //now construct basic tree structure struct Tree { float x,y; Tree(point a) { x=a.x; y=a.y; } Tree *left; Tree *right; }; Tree * build_kd( Tree *root,vector<point>points,int depth) { point temp; if(points.size()==1)// that point is as a leaf { if(root==NULL) root=new Tree(points[0]); return root; } if(depth%2==0) { temp=medianx(points); root=new Tree(temp); for(int i=0;i<points.size();i++) { if (points[i].x<temp.x) pointleft[i]=points[i]; else pointright[i]=points[i]; } } else { temp=mediany(points); root=new Tree(temp); for(int i=0;i<points.size();i++) { if(points[i].y<temp.y) pointleft[i]=points[i]; else pointright[i]=points[i]; } } return build_kd(root->left,pointleft,depth+1); return build_kd(root->right,pointright,depth+1); } void print(Tree *root) { while(root!=NULL) { cout<<root->x<<" " <<root->y; print(root->left); print(root->right); } } int main() { int depth=0; Tree *root=NULL; vector<point>points(4); float x,y; int n=4; for(int i=0;i<n;i++) { cin>>x>>y; points[i].x=x; points[i].y=y; } root=build_kd(root,points,depth); print(root); return 0; } i am trying ti implement in c++ this pseudo code tuple function build_kd_tree(int depth, set points): if points contains only one point: return that point as a leaf. if depth is even: Calculate the median x-value. Create a set of points (pointsLeft) that have x-values less than the median. Create a set of points (pointsRight) that have x-values greater than or equal to the median. else: Calculate the median y-value. Create a set of points (pointsLeft) that have y-values less than the median. Create a set of points (pointsRight) that have y-values greater than or equal to the median. treeLeft = build_kd_tree(depth + 1, pointsLeft) treeRight = build_kd_tree(depth + 1, pointsRight) return(median, treeLeft, treeRight) please help me what this error means?

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  • Extjs: Tree, Selecting node after creating the tree

    - by Natkeeran
    I have a simple TreePanel. I would like to select a particular node upon loading it. The nodes are from a remote file (json). The tree is loading as expected. However, the node is not being selected. Firebug shows node as undefined. This perhaps because of the async property. But, I an unable to configure this other wise, or specify the node be selected. Any suggestions welcomed, and thank you. LeftMenuTree = new Ext.tree.TreePanel({ renderTo: 'TreeMenu', collapsible: false, height: 450, border: false, userArrows: true, animate: true, autoScroll: true, id: 'testtest', dataUrl: fileName, root: { nodeType: 'async', iconCls:'home-icon', expanded:true, text: rootText }, listeners: { "click": { fn: onPoseClick, scope: this } }, "afterrender": { fn: setNode, scope: this } }); function setNode(){ alert (SelectedNode); if (SelectedNode == "Orders"){ var treepanel = Ext.getCmp('testtest'); var node = treepanel.getNodeById("PendingItems"); node.select(); } }

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  • SVN project folder tree structure vs production folder tree structure

    - by Marco Demaio
    While developing a PHP+JS web application we always try to separate big blocks of code into small modules/components, in order to make these last ones as much reusable as possible in other applications. Let's say we now have: the EcommerceApp (an ecommerce main application) a Server-file-mgr component (a component to view/manage file on server) a Mylib (a library of useful functions) a MailistApp (another main application to handle mail lists) ... EcommerceApp needs both Server-file-mgr component and Mylib to work Server-file-mgr needs Mylib to work MaillistApp needs both Server-file-mgr component and Mylib to work too. My idea is to simply structure the SVN project folder tree putting everything at the same level: trunk/EcommerceApp trunk/Server-file-mgr trunk/Mylib trunk/MaillistApp But in real life to make these apps to work the folder tree structure must be the following: EcommerceApp |_ Mylib |_ Server-file-mgr MaillistApp |_ Mylib |_ Server-file-mgr I mean Mylib and Server-file-mgr needs to be inside the EcommerceApp/MaillistApp folder. How would you then structure the SVN folder, as I did or in a different/better/smarter way???

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  • Insert element into a tree from a list in Standard ML

    - by vichet
    I have just started to learn SML on my own and get stuck with a question from the tutorial. Let say I have: tree data type datatype node of (tree*int*tree) | null insert function fun insert (newItem, null) = node (null, newItem, null) | insert (newItem, node (left, oldItem, right)) = if (newItem <= oldItem) then node (insert(newItem,left),oldItem, right) else node (left, oldItem, insert(newItem, right) an integer list val intList = [19,23,21,100,2]; my question is how can I add write a function to loop through each element in the list and add to a tree? Your answer is really appreciated.

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  • Family Tree :- myheritage.com

    - by Nitesh Panchal
    Hello, The other day i just accidently visited the site myheritage.com. I was just wondering, how they must have created one? Can anybody tell me what can be their database design? and if possible, algorithm that we can use to generate such a tree? Generating simple binary tree is very easy using recursion. But if you have a look at the site(if you have time please make account on it and add few nodes to feel) when we add son to a father, it's mother is automatically added(if you don't add explicitly). Mother's family tree is also generated side by side and many such fancy things are happening. In a simple binary tree we have a root node and then many nodes below it. Thus we cannot show wife and husband in the tree and then show a line from wife and husband to child. In spare time, can anybody discuss what can be it's database design and the recursive algorithm that we can follow to generate it? I hope i am not asking too much from you :).

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  • Maximum depth of a B-tree

    - by Phenom
    How do you figure out the maximum depth of a B-tree? Say you had a B-tree of order 1625, meaning each node has 1625 pointers and 1624 elements. What is the maximum depth of the tree if it contains 85,000,000 keys?

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  • Sorting by custom field and fetching whole tree from DB

    - by Niaxon
    Hello everyone, I am trying to do file browser in a tree form and have a problem to sort it somehow. I use PHP and MySQL for that. I've created mixed (nested set + adjacency) table 'element' with the following fields: element_id, left_key, right_key, level, parent_id, element_name, element_type (enum: 'folder','file'), element_size. Let's not discuss right now that it is better to move information about element (name, type, size) into other table. Function to scan specified directory and fill table work correctly. Noteworthy, i am adding elements to tree in specific order: folders first and then files. After that i can easily fetch and display whole table on the page using simple query: SELECT * FROM element WHERE 1=1 ORDER BY left_key With the result of that query and another function i can generate correct html code (<ul><li>... and so on). to display tree. Now back to the question (finally, huh?). I am struggling to add sorting functionality. For example i want to order my result by size. Here i need to keep in my mind whole hierarchy of tree and rule: folders first, files later. I believe i can do that by generating in PHP recursive query: SELECT * FROM element WHERE parent_id = {$parentId} ORDER BY element_type (so folders would be first), size (or name for example) asc/desc After that for each result which has type = 'folder' i will send another query to get it's content. Also it's possible to fetch whole tree by left_key and after that sort it in PHP as array but i guess that would be worse :) I wonder if there is better and more efficient way to do such a thing?

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  • How to Populate a 'Tree' structure 'Declaratively'

    - by mackenir
    I want to define a 'node' class/struct and then declare a tree of these nodes in code in such a way that the way the code is formatted reflects the tree structure, and there's not 'too much' boiler plate in the way. Note that this isn't a question about data structures, but rather about what features of C++ I could use to arrive at a similar style of declarative code to the example below. Possibly with C++0X this would be easier as it has more capabilities in the area of constructing objects and collections, but I'm using Visual Studio 2008. Example tree node type: struct node { string name; node* children; node(const char* name, node* children); node(const char* name); }; What I want to do: Declare a tree so its structure is reflected in the source code node root = node("foo", [ node("child1"), node("child2", [ node("grand_child1"), node("grand_child2"), node("grand_child3" ]), node("child3") ]); NB: what I don't want to do: Declare a whole bunch of temporary objects/colls and construct the tree 'backwards' node grandkids[] = node[3] { node("grand_child1"), node("grand_child2"), node("grand_child3" }; node kids[] = node[3] { node("child1"), node("child2", grandkids) node("child3") }; node root = node("foo", kids);

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  • unique substrings using suffix tree

    - by user1708762
    For a given string S of length n- Optimal algorithm for finding all unique substrings of S can't be less than O(n^2). So, the best algorithm will give us the complexity of O(n^2). As per what I have read, this can be implemented by creating suffix tree for S. The suffix tree for S can be created in O(n) time. Now, my question is- How can we use the suffix tree for S to get all the unique substrings of S in O(n^2)?

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  • Index files for Subdomains

    - by user358994
    I was finally able to setup subdomains but now I have a problem when I try and access the subdomain by itself. For instance, when I visit sub.domain.com, I get a page not found error. However, when I visit sub.domain.com/index.php, I see my page. My theory is that when I visit sub.domain.com, the index file it searches for is not in the sub/ folder but instead in the root folder. I have directoryindex to look for index.html before index.php. There is a index.html in the root directory that is needed. So when I go to sub.domain.com, it thinks that sub.domain.com/index.html exists but then finds out it doesnt and sends me a 404. That is my theory. How would I fix this? Any ideas? Thanks.

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  • Thinking Sphinx index rebuild error on windows xp: searchd is already running

    - by Voldy
    I have Sphinx installed on windows xp system. A I use Thinking Sphinx plug-in within my rails application. I can't rebuild index with Thinking Sphinx rake task after application server starting up even if I stop it: Stopped search daemon (pid 4492). ... bla bla bla ... total 3 reads, 0.000 sec, 1.3 kb/call avg, 0.0 msec/call avg total 9 writes, 0.000 sec, 1.2 kb/call avg, 0.0 msec/call avg WARNING: could not open pipe (GetLastError()=2) rake aborted! searchd is already running. If I reload system, I can rebuild index. What do you think about? p.s: Does this question suited for serverfault.com?

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