Search Results

Search found 45804 results on 1833 pages for 'large files'.

Page 35/1833 | < Previous Page | 31 32 33 34 35 36 37 38 39 40 41 42  | Next Page >

  • Chunking large rsync transfers?

    - by Gabe Martin-Dempesy
    We use rsync to update a mirror of our primary file server to an off-site colocated backup server. One of the issues we currently have is that our file server has 1TB of mostly smaller files (in the 10-100kb range), and when we're transferring this much data, we often end up with the connection being dropped several hours into the transfer. Rsync doesn't have a resume/retry feature that simply reconnects to the server to pickup where it left off -- you need to go through the file comparison process, which ends up being very length with the amount of files we have. The solution that's recommended to get around is to split up your large rsync transfer into a series of smaller transfers. I've figured the best way to do this is by first letter of the top-level directory names, which doesn't give us a perfectly even distribution, but is good enough. I'd like to confirm if my methodology for doing this is sane, or if there's a more simple way to accomplish the goal. To do this, I iterate through A-Z, a-z, 0-9 to pick a one character $prefix. Initially I was thinking of just running rsync -av --delete --delete-excluded --exclude "*.mp3" "src/$prefix*" dest/ (--exclude "*.mp3" is just an example, as we have a more lengthy exclude list for removing things like temporary files) The problem with this is that any top-level directories in dest/ that are no longer present present on src will not get picked up by --delete. To get around this, I'm instead trying the following: rsync \ --filter 'S /$prefix*' \ --filter 'R /$prefix*' \ --filter 'H /*' \ --filter 'P /*' \ -av --delete --delete-excluded --exclude "*.mp3" src/ dest/ I'm using the show and hide over include and exclude, because otherwise the --delete-excluded will delete anything that doesn't match $prefix. Is this the most effective way of splitting the rsync into smaller chunks? Is there a more effective tool, or a flag that I've missed, that might make this more simple?

    Read the article

  • Sharing large (multi-Gb) files with clients

    - by Tim Long
    I wasn't sure if this was the best place for this question, but I think it is squarely in the realm of the IT admin so that's the reason I put it here. We need to share large files (several Gigabytes) with external clients. We need a simple way of reliably and automatically publishing these files so that clients can then download them. Our organization has Windows desktops and a Windows SBS 2011 server. Sharing from our server is probably suboptimal from the client's perspective, because of the low upstream bandwidth of typical ADSL (around 1 Mbps) - it would take all day (9 hours for a 4Gb file) for the client to download the file. Uploading to a 3rd party sever is good for the client but painful for us, because we then have to deal with a multi-hour upload. Uploading to a third-part server would be less problematic if it could be made reliable and automatic, e.g. something like a Groove/SharePoint Workspace, simply drop the file in and wait for it to synchronize - but Groove has a 2Gb limit which is not big enough. So ideally I'd like a service with the following attributes: Must work for files of at least 5Gb, preferably 10Gb Once the transfer is started, it must be reliable (i.e. not sensitive to disconnections and service outages) and completely automatic Ideally, the sender would get a notification when the transfer completes. Has to work with Windows based systems. Any suggestions?

    Read the article

  • PostgreSQL lots of large Arrays and Writes

    - by strife911
    Hi, I am running a python program that spawns 8 threads and as each thread launch its own postmaster process via psycopg2. This is to maximize the use of my CPU-cores (8). Each thread call a series of SQL Functions. Most of these functions go through many thousands of rows each associated to a large FLOAT8[] Array (250-300) values by using unnest() and multiplying each FLOAT8 by an another FLOAT8 associated to each row. This Array approach minimized the size of the Indexes and the Tables. The Function ends with an Insert into another Table of a row of the same form (pk INT4, array FLOAT8[]). Some SQL Functions called by python will Update a row of these kind of Tables (with large Arrays). Now I currently have configured PostgreSQL to use most of the memory for cache (effective_cache_size of 57 GB I think) and only a small amount of it for shared memory (1GB I think). First, I was wondering what the difference between Cache and Shared memory was in regards to PostgreSQL (and my application). What I have noticed is that only about 20-40% of my total CPU processing power is used during the most Read intensive parts of the application (Select unnest(array) etc). So secondly, I was wondering what I could do to improve this so that 100% of the CPU is used. Based on my observations, it does not seem to have anything to do with python or its GIL. Thanks

    Read the article

  • Two large, linked Excel files take 30 minutes to save, except in VMWare environment

    - by Gerald L
    I support some tax consultants who love to use Excel when they should probably be using Access. Anyway, they have created two Excel files, A and B. File B has cells linked to file A. File A is 27 MB and file B is 16 MB. One worksheet has roughly 1 million rows and there is another worksheet doing a whole bunch of SUMIF on the 1 million rows. Not the best idea, but whatever. Both Excel files open and recalculate within a reasonable amount of time (1-2 minutes). For a files that large, this is acceptable. Here is the problem: Once you change a cell, and save the file B, it takes a solid 30 minutes to save the file, and the processors are going full speed. I've tried this on 6 different machines, all running Windows XP SP3 with Office 2007 SP2 and all patches. The specs vary from one machine with 512 MB or RAM to a machine with 4 GB of RAM and quad processors. Same result every time. Here is the clincher: If I do this same save operation on a VMWare virtual machine, the file gets saved in 1 minute. I've tried this with my ESX servers at the office, my Mac Fusion at home, and VMWare workstation at the office. It does not matter how much RAM the virtual machine has... it saves in about 1 minute every time. Does anybody have any idea why this is happening and how to fix?

    Read the article

  • osx bash grep - finding search terms in a large file with one single line

    - by unsynchronized
    Is there simple unix command line i can enter which lets me isolate say 512 bytes either side of a search term, even if there is only one "line" in a very large text file? Ok, this should be easy. Famous last words. I'm not that familiar with grep, but it seems it is mainly used to filter out lines in the input that contain search terms. I have a very large json file that I downloaded that i want to search for a particular term. before you click the link - it's over 244MB so be warned - it is from the internet wayback machine and contains lists of zip files of archived photos. i am trying to find mine. Their web interface is broken, so i found the json file that they make public here - it's the last one on the list. when i grep looking for my username, it finds it, but proceeds to dump that line to the console. the problem is that line is 244MB long, and it's the only line in the file. i tried using less, but could not get that to do much - it's very slow, and seems to have the same issue. is there simple unix command line i can enter which lets me isolate say 512 bytes either side of a search term?

    Read the article

  • iis7 large worker process request queue creating process blocking aspnet.config & machine.config amended (bottleneck)

    - by scott_lotus
    ASP.net 2.0 app .net 2.0 framework IIS7 I am seeing a large queue of "requests" appear under the "worker process" option. State recorded appear to be Authenticate Request and Execute Request Handles more than anything else. I have amended aspnet.config in C:\Windows\Microsoft.NET\Framework64\v2.0.50727 (32 bit path and 64 bit path) to include: maxConcurrentRequestsPerCPU="50000" maxConcurrentThreadsPerCPU="0" requestQueueLimit="50000" I have amended machine.config in C:\Windows\Microsoft.NET\Framework64\v2.0.50727\CONFIG (32 bit and 64 bit path) to include: autoConfig="true" maxIoThreads="100" maxWorkerThreads="100" minIoThreads="50" minWorkerThreads="50" minFreeThreads="176" minLocalRequestFreeThreads="152" Still i get the issue. The issue manifestes itself as a large number of processes in the Worker Process queue. Number of current connections to the website display 500 when this issue occurs. I dont think i have seen concurrent connections over 500 without this issue occurring. Web application slows as the request block. Refreshing the app pool resolves for a while (as expected) as the load is spread between the two pools. Application pool in question FIXED REQUEST have been set to refresh on 50000. Thank you for any help. Scott quick edit to say hmm, my develeopers are telling me the project was built with .net 3.5 framework. Looking at C:\Windows\Microsoft.NET\Framework64\v3.5 there does not appear to be a ASPNET.CONFIG or a MACHINE.CONFIG .... is there a 3.5 equivalent ? after a little searching apparenetly 3.5 uses the 2.0 framework files that 3.5 is missing. So back to the original question , where is my bottleneck ?

    Read the article

  • Load Sharing Regarding Large Websites

    - by JHarley1
    Hello, I have a question regarding Load Sharing for large websites. My Understanding: So if you have a website that has millions of fits a day you will need to have an architecture that can support this sort of pressure. You can either do one or two things: Invest in a single large server that has huge amounts of processing power, memory and storage (such as Microsoft's TerraServer). Spread the load of your website across a number of machines. Let me tackle the second approach, so you have a collection of machines all running Web Server Software and all having access to identical copies of the websites pages. You can either spread the load across these machines using a cyclic pattern in a DNS or you can use a Load Ballancing Switch. The advantages of this approach is: - Redundancy - servers can fail and the others would "pick up the slack" - Incremental - the ability to easily add new machines to this set-up. My Question's Is there a Virtual approach to this issue of load balancing now? If the website runs from a database - is there still only a single copy of the database? If a user had a session running on one Server (e.g. they had gone to www.example.org and had been assigned to Server 2 - were they had created a session) if they refreshed the website (and were allocated Server 3) would they still have their session? What are the other disadvantages associated with Load Balancing? Many Thanks, J

    Read the article

  • Better approach to archiving large amounts of original video footage using optical media (DVD/Blu-ra

    - by Rob
    This question is to share my experience as well as ask for suggestions for better methods. Along with 2 friends, I completed the making of a short documentary film in 2006. Clip is at: http://www.youtube.com/mediamotioninvision The film was edited in Adobe Premiere Pro 1.5 on Windows XP. More details and screenshot here: http://www.flickr.com/photos/smilingrobbie/1350235514/ ( note this is not intended to be a plug, we've moved on from this initial learning curve project ;) ) The film is in 4:3 standard definition 720x576 PAL format. As well as retaining the final 30minute film, I wanted to keep all original files that assembled together to make the film. The footage was 83.5Gb So I archived them to over 20 4.7Gb DVD recordables in the original .avi format (i.e. data DVD-ROM format, NOT DVD-Video Mpeg2) Some .avi DV video files were larger than 4.7Gb so I used 7-zip to split them ( here is a guide as to how to do that: http://www.linglom.com/2008/10/12/how-to-split-a-large-file-using-7-zip/ ) To recombine them, a dos shell command like this would do that: copy /b file.avi.* file.avi would do the job, where .* is a wild card to include all the split parts e.g. 001, 002...00n assuming they are all in the same directory path folder. file.avi is the recombined file identical to the original. Later on, I bought a LG BE06 LU10 USB 2.0 Super-multi Blu-ray burner and archived the footage to 2 (two) x 50Gb BD-R DL discs. Again in the original format, written as files to a BD-R in the BD-R BD-ROM UDF format readable by PC/Mac etc, NOT Blu-ray video/film format. This seems to be a good solution for me, because: the archive is in a robust, reasonably permanent, non-volatile medium, i.e. DVD recordable / Blu-ray (debates about stability of optical media organic chemical dye compounds/substrates aside) the format of the archive is accessible by open source tools or just plain Windows Explorer and it's not in a proprietary format I just thought I'd ask folks for their experience on better methods, if such exist.

    Read the article

  • Error importing large MySQL dump file which includes binary BLOBs in Windows

    - by Daniel Magliola
    I'm trying to import a MySQL dump file, which I got from my hosting company, into my Windows dev machine, and i'm running into problems. I'm importing this from the command line, and i'm getting a very weird error: ERROR 2005 (HY000) at line 3118: Unknown MySQL server host '+?*á±dÆ-N+Æ·h^ye"p-i+ Z+-$?P+Y.8+|?+l8/l¦¦î7æ¦X¦XE.ºG[ ;-ï?éµ?º+¦¦].?+f9d릦'+ÿG?-0à¡úè?-?ù??¥'+NÑ' (11004) I'm attaching the screenshot because i'm assuming the binary data will get lost... I'm not exactly sure what the problem is, but two potential issues are the size of the file (2 Gb) which is not insanely large, but it's not trivially small either, and the other is the fact that many of these tables have JPG images in them (which is why the file is 2Gb large, for the most part). Also, the dump was taken in a Linux machine and I'm importing this into Windows, not sure if that could add to the problems (I understand it shouldn't) Now, that binary garbage is why I think the images in the file might be a problem, but i've been able to import similar dumps from the same hosting company in the past, so i'm not sure what might be the issue. Also, trying to look into this file (and line 3118 in particular) is kind of impossible given its size (i'm not really handy with Linux command line tools like grep, sed, etc). The file might be corrupted, but i'm not exactly sure how to check it. What I downloaded was a .gz file, which I "tested" with WinRar and it says it looks OK (i'm assuming gz has some kind of CRC). If you can think of a better way to test it, I'd love to try that. Any ideas what could be going on / how to get past this error? I'm not very attached to the data in particular, since I just want this as a copy for dev, so if I have to lose a few records, i'm fine with that, as long as the schema remains perfectly sound. Thanks! Daniel

    Read the article

  • Backing up large network (~200 clients) -- Enough Bandwidth?

    - by mtkoan
    My company wants to institute a backup plan for all of the clients on our network, which is about 200. We back up our servers and SQL databases regularly, but its been our policy to not backup individuals. What is most critical for people is their Documents and PST files in Outlook. PST files can be very large, and most people's are ~1-1.5 GB around here. So with PST files alone that is 200-300 GB of data needing to be transferred daily to a sever for backup. Or compressing first, then transferring, but many of the machines are VERY old and such a task would grind their computer to a halt. Isn't this the reason networks use things like VMware -- to reduce network traffic and streamline backups? Or is this only to reduce hardware costs? Would this much network traffic everyday drastically slow down our network? Enough to the point we'd have to mandate it to be done at night only? Or could we stagger then through out the day? Really appreciate any input, thank you.

    Read the article

  • How to configure a large mtu (linux)

    - by Somejan
    I have a gigabit ethernet connection from my laptop to my router, and a working ipv6 connection to the internet. I can receive very large packets from sites on the internet, with sizes up to at least 10000 bytes (according to wireshark). (edit: turns out to be linux's 'generic receive offload') However, when trying to send anything, my local computer fragments at just below 1500 bytes for ipv6. (On ipv4, I can send tcp packets to the internet of at least 1514 bytes, I can ping with packets up to the configured mtu of 6128 but they are blackholed.) I'm on ubuntu 12.04. I have configured an mtu for my eth0 of 6128 (the maximum it accepts), both using ip link set dev eth0 mtu 6128 and in the NetworkManager applet gui, and restarted the connection. ip link show eth0 shows the 6128 mtu is indeed set. ip -6 route shows that none of the paths the kernel knows about have an mtu set. I can ping over ipv4 with packets up to 6128 bytes (though I don't get responses), but when I do ping6 myrouter -c3 -s1500 -Mdo I get error replies from my own computer saying that the packets are too large and the mtu is 1480. I have confirmed with Wireshark that nothing is put on the wire, and the replies are indeed generated by my own computer. So, how do I get my computer to use the larger mtu?

    Read the article

  • Export-Mailbox - fails with large folders

    - by grojo
    I am trying to move messages from a rather large mailbox to an archive mailbox. However I run into errors all the time. the command I am executing is Export-Mailbox -Identity MAILBOX_FROM -TargetMailbox ARCHIVE -TargetFolder ARCHIVE_FOLDER -StartDate 2009-02-01 -EndDate 2009-02-28 -DeleteContent -Confirm:$false I can copy/move some messages, but run into frequent "an unknown error has occurred" (statuscode -1056749164) I run the console as administrative user, and all permissions are set right, as far as I can tell. I've restricted the start and end dates in case the number of messages moved/deleted should create problems. Anything I am missing in my setup? Corrupted messages? Over-limit message sizes? Update: What I've learnt so far, is that folder with more than approx 3000 messages will generate errors. If mail retention is set (default 30 days), Export-Mailbox will scan all messages whether these were deleted in previous runs or not, and date restriction to limit number of messages will not work. To avoid errors, I've switched off deleted message retention for the mailbox, and moved the messages from one large folder to multiple folders, and moved these one by one...

    Read the article

  • Large, high performance object or key/value store for HTTP serving on Linux

    - by Tommy
    I have a service that serves images to end users at a very high rate using plain HTTP. The images vary between 4 and 64kbytes, and there are 1.300.000.000 of them in total. The dataset is about 30TiB in size and changes (new objects, updates, deletes) make out less than 1% of the requests. The number of requests pr. second vary from 240 to 9000 and is dispersed pretty much all over, with few objects being especially "hot". As of now, these images are files on a ext3 filesystem distributed read only across a large amount of mid range servers. This poses several problems: Using a fileysystem is very inefficient since the metadata size is large, the inode/dentry cache is volatile on linux and some daemons tend to stat()/readdir() it's way through the directory structure, which in my case becomes very expensive. Updating the dataset is very time consuming and requires remounting between set A and B. The only reasonable handling is operating on the block device for backup, copying, etc. What I would like is a deamon that: speaks HTTP (get, put, delete and perhaps update) stores data it in an efficient structure. The index should remain in memory, and considering the amount of objects, the overhead must be small. The software should be able to handle massive connections with slow (if any) time needed to ramp up. Index should be read in memory at startup. Statistics would be nice, but not mandatory. I have experimented a bit with riak, redis, mongodb, kyoto and varnish with persistent storage, but I haven't had the chance to dig in really deep yet.

    Read the article

  • File corruption (bad checksums) in large files copied to VMware guest

    - by AllanA
    In setting up a development lab, I've got a desktop system running ESXi 4.1.0 (free license) on SATA RAID 0 (already purchased and configured when I started this job; I'm open to hardware input as it pertains to my problem.) Its guests so far include two Win2008 Server R2 64-bit VMs and on Ubuntu 10.04 64-bit VM. I'm installing onto the Windows servers. We've been copying off some fairly large files (over a gigabyte) for an installation, hoping to install more quickly from a (virtual) hard drive than from the network for from BD-ROM. The problem is that they keep coming up with different checksums from the originals. The file sizes are the same, but md5sum reports different numbers (and so does the installer, as it refuses to continue when the checksums don't match.) I've tried copying directly from the BD-ROM (attaching the OS drive to the host system's physical drive). I've tried copying the large files onto a co-worker's Windows machine from his Blu-Ray drive; when I do that, the checksums match. But when I copy from his machine to the VM guest over a network share, the checksums no longer match. Thinking this meant a corrupt destination drive, I deleted it in vSphere and added another freshly created drive. The problem persists. I'm not sure what to try next.

    Read the article

  • 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.

    Read the article

  • [C#][XNA] Draw() 20,000 32 by 32 Textures or 1 Large Texture 20,000 Times

    - by Rudi
    The title may be confusing - sorry about that, it's a poor summary. Here's my dilemma. I'm programming in C# using the .NET Framework 4, and aiming to make a tile-based game with XNA. I have one large texture (256 pixels by 4096 pixels). Remember this is a tile-based game, so this texture is so massive only because it contains many tiles, which are each 32 pixels by 32 pixels. I think the experts will definitely know what a tile-based game is like. The orientation is orthogonal (like a chess board), not isometric. In the Game.Draw() method, I have two choices, one of which will be incredibly more efficient than the other. Choice/Method #1: Semi-Pseudocode: public void Draw() { // map tiles are drawn left-to-right, top-to-bottom for (int x = 0; x < mapWidth; x++) { for (int y = 0; y < mapHeight; y++) { SpriteBatch.Draw( MyLargeTexture, // One large 256 x 4096 texture new Rectangle(x, y, 32, 32), // Destination rectangle - ignore this, its ok new Rectangle(x, y, 32, 32), // Notice the source rectangle 'cuts out' 32 by 32 squares from the texture corresponding to the loop Color.White); // No tint - ignore this, its ok } } } Caption: So, effectively, the first method is referencing one large texture many many times, each time using a small rectangle of this large texture to draw the appropriate tile image. Choice/Method #2: Semi-Pseudocode: public void Draw() { // map tiles are drawn left-to-right, top-to-bottom for (int x = 0; x < mapWidth; x++) { for (int y = 0; y < mapHeight; y++) { Texture2D tileTexture = map.GetTileTexture(x, y); // Getting a small 32 by 32 texture (different each iteration of the loop) SpriteBatch.Draw( tileTexture, new Rectangle(x, y, 32, 32), // Destination rectangle - ignore this, its ok new Rectangle(0, 0, tileTexture.Width, tileTexture.Height), // Notice the source rectangle uses the entire texture, because the entire texture IS 32 by 32 Color.White); // No tint - ignore this, its ok } } } Caption: So, effectively, the second method is drawing many small textures many times. The Question: Which method and why? Personally, I would think it would be incredibly more efficient to use the first method. If you think about what that means for the tile array in a map (think of a large map with 2000 by 2000 tiles, let's say), each Tile object would only have to contain 2 integers, for the X and Y positions of the source rectangle in the one large texture - 8 bytes. If you use method #2, however, each Tile object in the tile array of the map would have to store a 32by32 Texture - an image - which has to allocate memory for the R G B A pixels 32 by 32 times - is that 4096 bytes per tile then? So, which method and why? First priority is speed, then memory-load, then efficiency or whatever you experts believe.

    Read the article

  • Need to get .obj file names of Executable(which one is crrently executing) at runtime programaticall

    - by Usman
    Suppose I have a VC++ project contains no of(say e.g 5) Source files(.cpp files),it will generate 5 .obj files(obj files corresponding to my .cpp's files not all kernel and OS layers including .obj files) e.g my project includes xyz_1.cpp,xyz_2.cpp,xyz_3.cpp,xyz_4.cpp,it will corresponds 4 respective .objs. By programtaically HOW CAN I TAKE AND GET THE NAMES OF THESE 4 .OBJ files at runtime(On run time I need to check how many obj files & names of those objs). REMEMBER I DON'T NEED ALL KERNEL AND OS LAYER .OBJS I ONLY NEED OBJS OF MY .CPPs. Regards Usman

    Read the article

  • Playing around with Eclipse features - Project files are now hidden?

    - by Daddy Warbox
    I don't even remember how, but somehow I managed to make all of my project's source files hidden in Eclipse's Package and Project Explorer panels. Go figure. 'Show Filtered Children (alt+click)' temporarily reveals the files, and only in Package Explorer can I double-click to reopen them from this view. They go back into hiding after I select another item, though. Plus, now I'm getting other annoyances, such as all of the folded non-hidden trees altogether expanding when I click on any item, and the entire file folder tree of my project now being shown in these panels (including my .svn subversion folders... which shouldn't be any of Eclipse's business, presently). Long story short, my Package/Project Explorers' just blew up on me, and I want to know how to fix this. Thanks in advance. P.S. What's a good guide I can use to learn my way around this silly contraption, anyway?

    Read the article

  • How can I download all files of a specific type from a website using PHP?

    - by CheeseConQueso
    I want to get all midi (*.mid) files from a site that's set up pretty simple in terms of directory tree structure. I wish we had wget installed here, but that's another party.... The site is VGMusic.com and the path containing all of the midi files is: http://www.vgmusic.com/music/console/nintendo/nes/ I tried glob'ing it out, but I suppose that glob only works locally? Here is what I wrote to try to make it happen (doesn't work.. obviously..): <?php echo 'not a blizzard<br>'; foreach(glob('http://www.vgmusic.com/music/console/nintendo/nes/*.mid') as $filename) { echo $filename.'<br>'; //$newfile = 'http://www.mydomain.com/nes/'.$filename; //copy($filename, $newfile) } ?> I tried it also without the http:// in there with no luck.

    Read the article

  • Is it a good idea to work on header files only, just at the start of the project?

    - by m4design
    To explain my point further, I'm a beginner in programming, and I'm working on a small project. Instead of separating the .cpp file from the header file, I'm implementing the code in the header files, and making one .cpp file for testing. I do this to have less files, hence easier navigation. Then later I'll separate the code as it should be. Will this cause any problems? should I continue doing that? Thanks.

    Read the article

  • What are the pro and cons of having localization files vs hard coded variables in source code?

    - by corgrath
    Definitions: Files: Having the localization phrases stored in a physical file that gets read at application start-up and the phrases are stored in the memory to be accessed via util-methods. The phrases are stored in key-value format. One file per language. Variables: The localization texts are stored as hard code variables in the application's source code. The variables are complex data types and depending on the current language, the appropriate phrase is returned. Background: The application is a Java Servlet and the developers use Eclipse as their primary IDE. Some brief pro and cons: Since Eclipse is use, tracking and finding unused localizations are easier when they are saved as variables, compared to having them in a file. However the application's source code becomes bigger and bloated. What are the pro and cons of having localization text in files versus hard coded varibles in source code? What do you do and why?

    Read the article

  • How to manage reports/files distribution to different destinations in Unix?

    - by mossie
    The reporting tools will generate a huge numbers of reports/files in the file system (a Unix directory). There's a list of destinations (email addresses and shared folders) where a different set of reports/files (can have overlap) are required to be distributed at each destinations. Would like to know if there's a way to efficiently manage this reports delivery using shell scripts so that the maintenance of the list of reports and destinations will not become a mess in future. It's quite an open ended question, the constraint however is that it should work within the boundaries of managing the reports in a Unix FS.

    Read the article

  • How to Play FLAC Files in Windows 7 Media Center & Player

    - by Mysticgeek
    An annoyance for music lovers who enjoy FLAC format, is there’s no native support for WMP or WMC. If you’re a music enthusiast who prefers FLAC format, we’ll look at adding support to Windows 7 Media Center and Player. For the following article we are using Windows 7 Home Premium 32-bit edition. Download and Install madFLAC v1.8 The first thing we need to do is download and install the madFLAC v1.8 decoder (link below). Just unzip the file and run install.bat… You’ll get a message that it has been successfully registered, click Ok. To verify everything is working, open up one of your FLAC files with WMP, and you’ll get the following message. Check the box Don’t ask me again for this extension and click Yes. Now Media Player should play the track you’ve chosen.   Delete Current Music Library But what if you want to add your entire collection of FLAC files to the Library? If you already have it set up as your default music player, unfortunately we need to remove the current library and delete the database. The best way to manage the music library in Windows 7 is via WMP 12. Since we don’t want to delete songs from the computer we need to Open WMP, press “Alt+T” and navigate to Tools \ Options \ Library.   Now uncheck the box Delete files from computer when deleted from library and click Ok. Now in your Library click “Ctrl + A” to highlight all of the songs in the Library, then hit the “Delete” key. If you have a lot of songs in your library (like on our system) you’ll see the following dialog box while it collects all of the information.   After all of the data is collected, make sure the radio button next to Delete from library only is marked and click Ok. Again you’ll see the Working progress window while the songs are deleted. Deleting Current Database Now we need to make sure we’re starting out fresh. Close out of Media Player, then we’ll basically follow the same directions The Geek pointed out for fixing the WMP Library. Click on Start and type in services.msc into the search box and hit Enter. Now scroll down and stop the service named Windows Media Player Network Sharing Service. Now, navigate to the following directory and the main file to delete CurrentDatabase_372.wmdb %USERPROFILE%\Local Settings\Application Data\Microsoft\Media Player\ Again, the main file to delete is CurrentDatabase_372.wmdb, though if you want, you can delete them all. If you’re uneasy about deleting these files, make sure to back them up first. Now after you restart WMP you can begin adding your FLAC files. For those of us with large collections, it’s extremely annoying to see WMP try to pick up all of your media by default. To delete the other directories go to Organize \ Manage Libraries then open the directories you want to remove. For example here we’re removing the default libraries it tries to check for music. Remove the directories you don’t want it to gather contents from in each of the categories. We removed all of the other collections and only added the FLAC music directory from our home server. SoftPointer Tag Support Plugin Even though we were able to get FLAC files to play in WMP and WMC at this point, there’s another utility from SoftPointer to add. It enables FLAC (and other file formats) to be picked up in the library much easier. It has a long name but is effective –M4a/FLAC/Ogg/Ape/Mpc Tag Support Plugin for Media Player and Media Center (link below). Just install it by accepting the defaults, and you’ll be glad you did. After installing it, and re-launching Media Player, give it some time to collect all of the data from your FLAC directory…it can take a while. In fact, if your collection is huge, just walk away and let it do its thing. If you try to use it right away, WMP slows down considerably while updating the library.   Once the library is setup you’ll be able to play your FLAC tunes in Windows 7 Media Center as well and Windows Media Player 12.   Album Art One caveat is that some of our albums didn’t show any cover art. But we were usually able to get it by right-clicking the album and selecting Find album info.   Then confirming the album information is correct…   Conclusion Although this seems like several steps to go through to play FLAC files in Windows 7 Media Center and Player, it seems to work really well after it’s set up. We haven’t tried this with a 64-bit machine, but the process should be similar, but you might want to make sure the codecs you use are 64-bit. We’re sure there are other methods out there that some of you use, and if so leave us a comment and tell us about it. Download madFlac V1.8  M4a/FLAC/Ogg/Ape/Mpc Tag Support Plugin for Media Player and Media Center from SoftPointer Similar Articles Productive Geek Tips How to Play .OGM Video Files in Windows VistaFixing When Windows Media Player Library Won’t Let You Add FilesUsing Netflix Watchnow in Windows Vista Media Center (Gmedia)Kantaris is a Unique Media Player Based on VLCEasily Change Audio File Formats with XRECODE TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 PCmover Professional OutSync will Sync Photos of your Friends on Facebook and Outlook Windows 7 Easter Theme YoWindoW, a real time weather screensaver Optimize your computer the Microsoft way Stormpulse provides slick, real time weather data Geek Parents – Did you try Parental Controls in Windows 7?

    Read the article

  • Analyze your IIS Log Files - Favorite Log Parser Queries

    - by The Official Microsoft IIS Site
    The other day I was asked if I knew about a tool that would allow users to easily analyze the IIS Log Files, to process and look for specific data that could easily be automated. My recommendation was that if they were comfortable with using a SQL-like language that they should use Log Parser . Log Parser is a very powerful tool that provides a generic SQL-like language on top of many types of data like IIS Logs, Event Viewer entries, XML files, CSV files, File System and others; and it allows you...(read more)

    Read the article

< Previous Page | 31 32 33 34 35 36 37 38 39 40 41 42  | Next Page >