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  • Opening a file opens the folder the file is in, not the file itself

    - by Pepe Lebuntu
    Whenever I try to open a file (such as an .odt, or .doc) from say, the Dash or the Firefox Downloads, Ubuntu 11.10 opens Nautilus to the the folder where the file is, rather than just going to the application and loading the file straight away. In previous releases, when I clicked on a downloaded file, it just went straight to LibreOffice, and it was fine. This is adding a superfluous step in the process. How do I associate the correct extensions?

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  • URL blocked in robots.txt but still showing up on Google search [closed]

    - by Ahmad Alfy
    Possible Duplicate: Why do Google search results include pages disallowed in robots.txt? In my robots.txt I am disallowing a lot of URLs. Google webmaster tools says there're +750 URL blocked. The problem is the URLs are still showing on Google search. For example I have the following rule: Disallow: /entity/child-health/ But when I search some-keyword + child health the following URL shows up : http://www.sitename.com/entity/child-health/ Am I doing anything wrong? Is is possible for a URL to be blocked using robots.txt and still show up on search results?

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  • Odd Search resaults

    - by Alex
    It was brought to my attention that if you search for the name of one of our directors (with the intent to find there profile page on our site) They come up as the first link in most search engines as you would expect but the link text is just pure spam. the three search string I have tested on Google, Bing, Ask, and Yahoo have all returned similar results. Here is a list of the search strings: Paolo rossi futex Mark rossi futex Marco rossi futex Dan Goldberg futex Any idea what might be causing this I have searched through as much of the sites code as I can and cant find anything wrong with it.

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  • Website Stopped Showing From Google Search Results Sunddenly

    - by Aman Virk
    I have a design and development blog http://www.thetutlage.com (1.5 years old), which was doing really well in Google search as I was getting over 70% of my traffic from Google. Now suddenly from last two days it reduced the amount of traffic from 70% to 20% and also when I am trying to search for the exact posts that I can created even after appending my website name to it does not show any results for that. Sample Search Text: JQuery Game Programming Creating A Ping Pong Game Part 1 I have post with exact same title and it does not show it on Google search anywhere. I am totally shocked, I write my own unique content and follow Google guide lines like bible. Also there is no message under my webmasters account stating any problem or error.

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  • Configure Unity Lenses and what they search

    - by Sindre
    I'm using Ubuntu 12.10. I've read about a lense (ppa:pydave/unity-lenses) that you can replace with the original files and folders lense, so you can search all your files. Instead of the current which only search used/recently used files and programs. I couldn't get this to work with 12.10, got a bunch of errors when I tried adding the ppa. I would like to set up a lens that can search all my files and folders (from all of my 3 hdd's), one that search through my videos (ability to specify which folders) and the same for music. So basically I would like to set up three specific lenses that each get a set of specified folders that they search through. If this is not possible, is there atleast a way to configure the current Files and Folders lense to ignore certain folders? I don't like when my dash shows files that I don't want to be shown. I should add that I'm completely new to Ubuntu and I apologize beforehand if this information could easily be found. But I wasn't able to find something like this. Edit: I found out how I can use the Privacy application to ignore what I want, so that's sorted now. Sorry for not researching it more. But my question regarding the lenses still stand. All help is greatly appreciated.

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  • Conventions for search result scoring

    - by DeaconDesperado
    I assume this type of question is more on-topic here than on regular SO. I have been working on a search feature for my team's web application and have had a lot of success building a multithreaded, "divide and conquer" processing system to work through a large amount of fulltext. Our problem domain is pretty specific. Users of the app generate posts, and as a general rule, posts that are more recent are considered to be of greater relevance. Some of the data we are trying to extract from search is very specific (user's feelings about specific items or things) and we are using python nltk to do named-entity extraction to find interesting likely query terms. Essentially we look for descriptive adjective-noun pairs and generate a general picture of a user's expressed sentiment as a list of tokens. This search is intended as an internal tool for our team to draw out a local picture of sentiments like "soggy pizza." There's some machine learning in there too to do entity resolution on terms like "soggy" to all manner of adjectives expressing nastiness. My problem is I am at a loss for how to go about scoring these results. The text being searched is split up into tokens in a list, so my initial approach would be to normalize a float score between 0.0-1.0 generated off of how far into the list the terms appear and how often they are repeated (a later mention of the term being worth less, earlier more, greater frequency-greater score, etc.) A certain amount of weight could be given to the timestamp as well, though I am not certain how to calculate this. I am curious if anyone has had to solve a similar problem in a search relevance grading between appreciable metrics (frequency, term location/colocation, recency) and if there are and guidelines for how to weight each. I should mention as well that the final fallback procedure in the search is to pipe the query to Sphinx, which has its own scoring practices. Sphinx operates as the last resort in case our application specific processing can't find any eligible candidates.

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  • Google search preview shows content not on the website

    - by SDG
    My website google search entry is messed up. In the preview in google search results, I get things like cracks, serials, random ip addresses. I scanned all files and my computer for viruses and malware and could not find anything. I also tried to download and reupload all content from a friend's computer and still that content persists. I also scanned the source code of all files, but the content does not appear in any file. Google also does not detect any malware on the website, as seen in their webmaster tools. I have searched using the same keywords in other search engines such as bing and yahoo and the search results there are fine. I am quite clueless as to what the causes would be for this and what would be a possible remedy.

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  • How can I search files on ubuntu?

    - by asdffdg
    How can I search files on ubuntu ??? The usual search tool does not find anything . I have installed tracker search tool and it too does not find anything .I tried to follow the instructions found to enable this tool by going to systempreferencessearching and indexing but Where the hell is systempreferencessearching and indexing? I found a program called searching and indexing but it does not contain anything that is described in the instructions .

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  • CONVERT(int, (datepart(month, @search)), (datepart(day, @search)), DateAdd(year, Years.Year - (datepart(year, @search)))

    - by MyHeadHurts
    In the query the top part is getting all the years that will run in the stored procedure. Works fine But at first i just wanted to run the queries for yesterdays date for all the years, but now i realized i want the user to select a date that will be in a parameter @search Booked <= CONVERT(int,DateAdd(year, Years.Year - Year(getdate()), DateAdd(day, DateDiff(day, 2, getdate()), 1))) this should be easy because normally it would just be Booked <= CONVERT(int,@search) but the problem is i want to do something like a Booked <= CONVERT(int, (datepart(month, @search)), (datepart(day, @search)), DateAdd(year, Years.Year - (datepart(year, @search))) would something like that work i dont need to worry about subtracting days but i still need to worry about the years WITH Years AS ( SELECT DATEPART(year, GETDATE()) [Year] UNION ALL SELECT [Year]-1 FROM Years WHERE [Year]>@YearToGet ), q_00 as ( select DIVISION , DYYYY , sum(PARTY) as asofPAX , sum(APRICE) as asofSales from dbo.B101BookingsDetails INNER JOIN Years ON B101BookingsDetails.DYYYY = Years.Year where Booked <= CONVERT(int,DateAdd(year, Years.Year - Year(getdate()), DateAdd(day, DateDiff(day, 2, getdate()), 1))) and DYYYY = Years.Year group by DIVISION, DYYYY, years.year having DYYYY = years.year ),

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  • Check to see if file transfer is complete

    - by Cymon
    We have a daily job that processes files delivered from an external source. The process usually runs fine without any issues but every once in a while we have an issue of attempting to process a file that is not completely transferred. The external source SCPs these files from a UNIX server to our Windows server. From there we try to process the files. Is there a way to check to see if a file is still being transferred? Does UNIX put a lock on a file while SCPing it that we could check on the Windows side?

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  • Indexing File Contents

    - by Rafid K. Abdullah
    People seem to have already asked about indexing file system: What options are there for indexing my filesystem? Alternatives to OS X's Spotlight? but I want to actually just index a certain working directory and be able to do that manually (so that I make sure my search is correct). Basically, I am on working a project and I need be able to search in contents quickly. I already use 'locate' and 'updatedb' commands, but those search for file names only. I am looking for similar commands but file contents. Just in case you are wondering why I don't use tracker also like answered in the two posts, tracker have a set of prespecified folders to search in them, and whenever you make a search, you search in all of them. What I want is to be able to search in every project separately.

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  • Windows 7 search doesn’t find text strings

    - by Hugh Tash
    I’m not able to find any text strings starting not from the beginning of word in filename or in file content using Windows 7 search. My Windows 7 search configuration: Let’s say I’m searching for a documents containing word “content”. I’m able to find those documents when searching for “content”, “conte”, “con” (as long as the string includes the beginning of the word). "content" "con" But if I search for “ontent”, “tent” or any other combination that doesn’t include the beginning of the word, Windows search won't find it. I've tried other indexing/searching software such as Copernic Desktop search, Google desktop search. Those programs also weren’t able to find part of the word starting from the middle of the word. For instance, it finds “conte”, but doesn’t find “onte”. Finds “conte” Doesn’t find “onte” I got the same problem using Copernic desktop search. On the other hand, when I use non-indexing content search software such as Agent Ransack or FileSeek, I get the same results when searching for “conte” or “onte”: “conte” “onte” Why do all pre-indexing content search applications (Windows search, Google desktop, Copernic desktop search) fail to search for a string inside the words? Why do non-indexing applications find text strings wherever they are: in the beginning, middle or end of the word? I’ve tried wildcards and other constructions with no luck. *onte onte “onte” content:onte content:onte content:~onte All these searched doesn’t find the word “content”. How can I make Windows search find strings from any part of words? Could you try these searches and see if they work for you? Or is this normal behavior? Thank you. Update: Using wildcards before or after "onte" doesn't find any results. content:~=onte doesn't find any results.

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  • How do I find a file that begins with a phraze in Windows Search?

    - by plasmuska
    Hi Guys, What is the syntax for searching a file with file name that STARTS with a certain phrase? Example: I have two files: 60933 blahblah.xls PZ 60933 blahblah.xls I would like to search only for the first one but Windows Search always returns two results. I have tried these but none of them seem to work: filename:60933 filename:^60933* filename:60933..xls My setup: Windows XP Pro CZ, Windows Search 4, files are located on indexed network share.

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  • How do I find a file that begins with a phrase in Windows Search?

    - by plasmuska
    Hi Guys, What is the syntax for searching a file with file name that STARTS with a certain phrase? Example: I have two files: 60933 blahblah.xls PZ 60933 blahblah.xls I would like to search only for the first one but Windows Search always returns two results. I have tried these but none of them seem to work: filename:60933 filename:^60933* filename:60933..xls My setup: Windows XP Pro CZ, Windows Search 4, files are located on indexed network share.

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  • Scalable Full Text Search With Per User Result Ordering

    - by jeremy
    What options exist for creating a scalable, full text search with results that need to be sorted on a per user basis? This is for PHP/MySQL (Symfony/Doctrine as well, if relevant). In our case, we have a database of workouts that have been performed by users. The workouts that the user has done before should appear at the top of the results. The more frequently they've done the workout, the higher it should appear in search matches. If it helps, you can assume we know the number of times a user has done a workout in advance. Possible Solutions Sphinx - Use Sphinx to implement full text search, do all the querying and sorting in MySQL. This seems promising (and there's a Symfony Plugin!) but I don't know much about it. Lucene - Use Lucene to perform full text search and put the users' completions into the query. As is suggested in this Stack Overflow thread. Alternatively, use Lucene to retrieve the results, then reorder them in PHP. However, both solutions seem clunky and potentially unscalable as a user may have completed hundreds of workouts. Mysql - No native full text support (InnoDB), so we'd have use LIKE or REGEX, which isn't scalable.

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  • PHP File Downloading Questions

    - by nsearle
    Hey All! I am currently running into some problems with user's downloading a file stored on my server. I have code set up to auto download a file once the user hits the download button. It is working for all files, but when the size get's larger than 30 MB it is having issues. Is there a limit on user download? Also, I have supplied my example code and am wondering if there is a better practice than using the PHP function 'file_get_contents'. Thank You all for the help! $path = $_SERVER['DOCUMENT_ROOT'] . '../path/to/file/'; $filename = 'filename.zip'; $filesize = filesize($path . $filename); @header("Content-type: application/zip"); @header("Content-Disposition: attachment; filename=$filename"); @header("Content-Length: $filesize") echo file_get_contents($path . $filename);

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  • Delphi Search Edit Component

    - by Reber
    Hi, I need a delphi component for Delphi 2007 win32 that have features like Google search text box. ** While User writing search key it should fill/refresh the list with values, and user can select one of them. **User can go up and down list and can select one of them. **List should contain codes and text pair, so user can select text and I can get code for database operations. (Google can highlight the search text in List but I think it is not possible with Delphi 2007, so it is not excepted.) I tried Dev Express TcxMRUEdit, however it doesn't meet my needs

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  • Using Multiple File Handles for Single File

    - by Ryan Rosario
    I have an O(n^2) operation that requires me to read line i from a file, and then compare line i to every line in the file. This repeats for all i. I wrote the following code to do this with 2 file handles, but it does not yield the result I am looking for. I imagine this is a simple error on my part. IN1 = open("myfile.dat","r") IN2 = open("myfile.dat","r") for line1 in IN1: for line2 in IN2: print line1.strip(), line2.strip() IN1.close() IN2.close() The result: Hello Hello Hello World Hello This Hello is Hello an Hello Example Hello of Hello Using Hello Two Hello File Hello Pointers Hello to Hello Read Hello One Hello File The output should contain 15^2 lines.

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  • Google Search API - Only returning 4 results

    - by user353829
    After much experimenting and googling, the following Python code successfully calls Google's Search APi - but only returns 4 results: after reading the Google Search API docs, I thought the 'start=' would return additional results: but this not happen. Can anyone give pointers? Thanks. Python code: /usr/bin/python import urllib import simplejson query = urllib.urlencode({'q' : 'site:example.com'}) url = 'http://ajax.googleapis.com/ajax/services/search/web?v=1.0&%s&start=50' \ % (query) search_results = urllib.urlopen(url) json = simplejson.loads(search_results.read()) results = json['responseData']['results'] for i in results: print i['title'] + ": " + i['url']

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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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