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  • Web browsing through SSH tunnel gets stuck/clogged

    - by endolith
    I use tools like Tunnelier to log into my home Tomato router through SSH, and then use it as a proxy for web browsing, tunnel for Remote Desktop/VNC, etc. Most days it works great, but some days every page I try to view gets stuck, like the tunnel is clogged. I load a web page and it seems to be loading, then stops, with the little loading icon spinning and nothing happening. I refresh the page, I reboot the router, I reboot the other computers on my home network and turn off any bandwidth-hogging services on them, I've turned on QoS on the router to prioritize SSH. I don't understand what's getting stuck. Rebooting or disconnecting/reconnecting the SSH tunnel improves responsiveness for a minute, but then it gets clogged again. It also seems to help if I don't do anything on the tunnel for a few minutes, then it will be responsive for a bit and then get clogged again. Trying to open a terminal console from Tunnelier is also unresponsive, so it's not just a web browsing problem. Likewise, connecting to http://192.168.1.1 in the browser (to the router's web config through its own tunnel) is also slow/laggy/halting. The realtime bandwidth reported by the router is nowhere near my DSL connection's limits, though it does show big spikes during the laggy times, and the connection is responsive when it shows low bandwidths. How do I troubleshoot something like this?

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  • openvpn port 53 bypasses allows restrictions ( find similar ports)

    - by user181216
    scenario of wifi : i'm using wifi in hostel which having cyberoam firewall and all the computer which uses that access point. that access point have following configuration default gateway : 192.168.100.1 primary dns server : 192.168.100.1 here, when i try to open a website the cyberoam firewall redirects the page to a login page (with correct login information, we can browse internet else not), and also website access and bandwidth limitations. once i've heard about pd-proxy which finds open port and tunnels through a port ( usually udp 53). using pd-proxy with UDP 53 port, i can browse internet without login, even bandwidth limit is bypassed !!! and another software called openvpn with connecting openvpn server through udp port 53 i can browse internet without even login into the cyberoam. both of softwares uses port 53, specially openvpn with port 53, now i've a VPS server in which i can install openvpn server and connect through the VPS server to browse internet. i know why that is happening because with pinging on some website(eb. google.com) it returns it's ip address that means it allows dns queries without login. but the problem is there is already DNS service is running on the VPS server on port 53. and i can only use 53 port to bypass the limitations as i think. and i can not run openvpn service on my VPS server on port 53. so how to scan the wifi for vulnerable ports like 53 so that i can figure out the magic port and start a openvpn service on VPS on the same port. ( i want to scan similar vulnerable ports like 53 on cyberoam in which the traffic can be tunneled, not want to scan services running on ports). improvement of the question with retags and edits are always welcomed... NOTE : all these are for Educational purpose only, i'm curious about network related knowledge.....

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  • openvpn port 53 bypasses allows restrictions ( find similar ports)

    - by user181216
    scenario of wifi : i'm using wifi in hostel which having cyberoam firewall and all the computer which uses that access point. that access point have following configuration default gateway : 192.168.100.1 primary dns server : 192.168.100.1 here, when i try to open a website the cyberoam firewall redirects the page to a login page (with correct login information, we can browse internet else not), and also website access and bandwidth limitations. once i've heard about pd-proxy which finds open port and tunnels through a port ( usually udp 53). using pd-proxy with UDP 53 port, i can browse internet without login, even bandwidth limit is bypassed !!! and another software called openvpn with connecting openvpn server through udp port 53 i can browse internet without even login into the cyberoam. both of softwares uses port 53, specially openvpn with port 53, now i've a VPS server in which i can install openvpn server and connect through the VPS server to browse internet. i know why that is happening because with pinging on some website(eb. google.com) it returns it's ip address that means it allows dns queries without login. but the problem is there is already DNS service is running on the VPS server on port 53. and i can only use 53 port to bypass the limitations as i think. and i can not run openvpn service on my VPS server on port 53. so how to scan the wifi for vulnerable ports like 53 so that i can figure out the magic port and start a openvpn service on VPS on the same port. ( i want to scan similar vulnerable ports like 53 on cyberoam in which the traffic can be tunneled, not want to scan services running on ports). improvement of the question with retags and edits are always welcomed... NOTE : all these are for Educational purpose only, i'm curious about network related knowledge.....

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  • torrent downloads not showing on Squid log

    - by noobroot
    hello, i have just a few months working as sysadmin, hence i still have lots to learn, first thing id like to do is as follows: We have an OpenBSD 4.5 box acting like firewall,dns,cache etc, the box has 2 network cards, one conected directly to the internet and the other to our switch, i used to work with sarg for the log analysis but then changed to the much faster free-sa. I use a daily free-sa report to check the bandwidth usage and report our top 5 bandwidth consumers (3 days a week being #1 and you will be buying the pizzas :D, we are a small company ~20 so we are very familiar). this was working really good until recently, one of us required to download some stuff via torrent (~3GB) and since the pizza rule is active for non-work related downloads, he told me (verified) that his download was indeed work related so i would dismiss that 3GB off his quota, but to my surprise the log didnt showed that 3GB, since his ip consumption was only around 290MB. More recently, since the FIFA world cup started, we know that some of the employees are watching the match's streaming, we know it and we dont care about it since, like already stated, we are a small company so we dont have restrictive policies, we all can chat, watch youtube, download anything we want BUT we are only allowed 300MB a day otherwise you'll get in the top5-pizza-board, anyway, that streaming consumption is also not showing in the free-sa reports. So my question is, why is these data being excluded from the reports? im thinking that the free-sa reports list only certain types of things but im also thinking if are the squid logs the ones that are not erm... logging these conections. Any help, guide, advice or clarification is appreciated.

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  • What is the best hosting option for Flash web-widget?

    - by par
    Our Flash web-widget has got highly popular. It is downloaded around 100,000 times per day. And that is the problem. Our server bandwidth is too narrow to deliver the widget to the clients fast. The widget is loaded very slow. Probably 20 times slower than before (at peak times). Probably I have choosen not the right hoster for my task - delivering 1 MB Flash widget to 100,000 users per day. What is the best hosting solution in my case? I'm not good at server administration so forgive me if I sound naive. The details are the following. Our hoster options: -Dedicated server, Ubuntu -10 Mbit Connection -monthly bandwidth limit: 2000 GB Widget size is 1 MB. The widget consists of the main SWF and a number of loaded SWF and data files. This is a part of Apache Status report taken right now ---- Server uptime: 1 hour 2 minutes 38 seconds Total accesses: 74865 - Total Traffic: 5.8 GB CPU Usage: u28 s7.78 cu0 cs0 - .952% CPU load 19.9 requests/sec - 1.6 MB/second - 81.1 kB/request 200 requests currently being processed, 0 idle workers WWWWWWWWWWWWWWWWWWWWWWWWCWWWWWWWWWWWWWWWWWWWWWWWWWWCWWWWWWWCWWWW WWWWWCWWWWWWWWWWWWWWCWWWWWWWWWWWWCWWWWWWWWCWWCWWWWWWWWWWWWWWWWWW WWWWWWWWWWWWWWWWCWWWWWWWWWWWWWWWWWWWWWWWWWWWCWCWWWWWWWWWWWWWWWCW WWWWWWWW........................................................ ----

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  • Simple Distributed Disconnected way to sync a directory

    - by Rory
    I want to start regularly backup my home directory on my ubuntu laptop, machine X. Suppose I have access to 2 different remote (linux) servers that I can backup to, machines A & B. Machine X will be the master, and should be synced to A and B. I could just regularly run rsync from X to A and then from X to B. That's all I need. However I'm curious if there's a more bandwidth effecient, and hence faster way to do it. Assuming X is going to be on residential style broadband lines, and since I don't want to soak up the bandwidth, I would limit the transfer from X. A and B will be on all the time, however X, will not be, so I'd also like to reduce the amount of time that X is transfering, potentially allowing A and B to spend more time transfering. Also, X won't be connected all the time. What's the best way to do this? rsync from X to A, then from A to B? Timing that right could be troublesome. I don't want to keep old files around, so if I was to rsync, then the --del option would be used. Could that mean something might get tranfered from A to B, then deleted from B, then transfered from A to B again? That's suboptimal. I know there are fancy distributed filesystems like gluster, but I think that's overkill in this case, and might not fit with the disconnected nature.

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  • Centralized backup method recommendation for SMEs with various OSes

    - by Akinator
    Hi I was wondering what in your opinion is the "best" method for having "everything" backed-up in the following situation. We are a SMEs with 10 computers in total. Three of those computers are MACs The rest are windows (1 vista, 4 win7 and 2 XPs) I'm very open to what the method should be but you should also consider the follwing: Very limited resources Quite "small" bandwidth (4 MBs for all (download) 0.4 MBs (upload, yep, thats it)- though this might get, a little bit better) One of the main thing to back up would be the mails, considerations: All windows computers use outlook, mainly 2003 There is one mac that uses outlook too (for mac of course - not 2011 yet) We also have to backup the files: Not a huge amount Very few very big files Very organizes (by machine) What I would like is to hear your opinions as to which would be the best method (or combination of methods - preferably one of course) considering. We are not sure what do we need and I'm open to suggestions, though an online (cloud based applications) would be great, remember the the bandwidth is unbearable. Last think to consider, it that we would like to do weekly updates (unless the method is very easy of course). Thanks in advance!! I tried to be as specific as possible, but if anything is needed I'll gladly update, please ask for any clarification needed! Please avoid any answers like upgrade all to windows 7 and throw away your macs :) our's may not be an ideal situation, but it is what it is, and right now, it would be impossible for us to change it for a lot of circumstances.

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  • moving files and directories between two machine, via a third, preserving permissions and usernames

    - by Jarmund
    The situation is as follows: Machine A has a file repository accessible via rsync Machine B needs the above mentioned files with all permissions and ownerships intact (including groups etc) Machine C has access to both A and B, but has a completely different set of users. Normally, i would just rsync everything over, directly between A and B, but due to severely limited bandwidth at the moment, i need something different, as rsync times out after building the list of the 430 files (49Mb uncompressed... can be compressed down to ~7Mb). What i've tried so far: rsync everything over from A to C, tar it, copy the tarball over, and then untar it, however, this messes up the ownership and/or the permissions. To rsync it from A to C, i run this command: rsync --numeric-ids --password-file=/root/rsync_pwd_file -oaPvu rsync://[email protected]/portal_2/ ./portal_2/ ...and from the looks of things, they do end up on C with the correct ownerships/permissions/flags/everything (not 100% sure, though.. are there any more switches i can throw in there? did i miss something?) copying the tarball over is simple enough (slow as a one-legged turtle due to the bandwidth, but it checksums out alright) What i'm unsure of is the flags and switches for creating and extracting the tarball, so could someone please provide the full commands for creating a tarball from /root/portal_2 on machine C (with everything intact) and extracting the tarball into /var/ex/portal_2 on machine B? ? Also, are there any other approaches worth mentioning that could allow me to perform this? I have root access to A and C, whereas i only have rsync access to B. PS: I'm running rsync v2.6.9 on machine B, and unfortunately i do not have the oportunity to upgrade to v3

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  • Centralized backup method recommendation for SMEs with various OSes

    - by Akinator
    Hi I was wondering what in your opinion is the "best" method for having "everything" backed-up in the following situation. We are a SMEs with 10 computers in total. Three of those computers are MACs The rest are windows (1 vista, 4 win7 and 2 XPs) I'm very open to what the method should be but you should also consider the follwing: Very limited resources Quite "small" bandwidth (4 MBs for all (download) 0.4 MBs (upload, yep, thats it)- though this might get, a little bit better) One of the main thing to back up would be the mails, considerations: All windows computers use outlook, mainly 2003 There is one mac that uses outlook too (for mac of course - not 2011 yet) We also have to backup the files: Not a huge amount Very few very big files Very organizes (by machine) What I would like is to hear your opinions as to which would be the best method (or combination of methods - preferably one of course) considering. We are not sure what do we need and I'm open to suggestions, though an online (cloud based applications) would be great, remember the the bandwidth is unbearable. Last think to consider, it that we would like to do weekly updates (unless the method is very easy of course). Thanks in advance!! I tried to be as specific as possible, but if anything is needed I'll gladly update, please ask for any clarification needed! Please avoid any answers like upgrade all to windows 7 and throw away your macs :) our's may not be an ideal situation, but it is what it is, and right now, it would be impossible for us to change it for a lot of circumstances.

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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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  • If Nvidia Shield can stream a game via WiFi (~150-300Mbps), where is the 1-10Gbps wired streaming?

    - by Enigma
    Facts: It is surprising and uncharacteristic that a wireless game streaming solution is the *first to hit the market when a 1000mbps+ Ethernet connection would accomplish the same feat with roughly 6x the available bandwidth. 150-300mbps WiFi is in no way superior to a 1000mbps+ LAN connection aside from well wireless mobility. Throughout time, (since the internet was created) wired services have **always come first yet in this particular case, the opposite seems to be true. We had wired internet first, wired audio streaming, and wired video streaming all before their wireless counterparts. Why? Largely because the wireless bandwidth was and is inferior. Even today despite being significantly better and capable of a lot more, it is still inferior to a wired connection. Situation: Chief among these is that NVIDIA’s Shield handheld game console will be getting a microconsole-like mode, dubbed “Shield Console Mode”, that will allow the handheld to be converted into a more traditional TV-connected console. In console mode Shield can be controlled with a Bluetooth controller, and in accordance with the higher resolution of TVs will accept 1080p game streaming from a suitably equipped PC, versus 720p in handheld mode. With that said 1080p streaming will require additional bandwidth, and while 720p can be done over WiFi NVIDIA will be requiring a hardline GigE connection for 1080p streaming (note that Shield doesn’t have Ethernet, so this is presumably being done over USB). Streaming aside, in console mode Shield will also support its traditional local gaming/application functionality. - http://www.anandtech.com/show/7435/nvidia-consolidates-game-streaming-tech-under-gamestream-brand-announces-shield-console-mode ^ This is not acceptable to me for a number of reasons not to mention the ridiculousness of having a little screen+controller unit sitting there while using a secondary controller and screen instead. That kind of redundant absurdity exemplifies how wrong of a solution that is. They need a second product for this solution without the screen or controller for it to make sense... at which point your just buying a little computer that does what most other larger computers do better. While this secondary project will provide a wired connection, it still shouldn't be necessary to purchase a Shield to have this benefit. Not only this but Intel's WiDi claims game streaming support as well - wirelessly. Where is the wired streaming? All that is required, by my understanding, is the ability to decode H.264 video compression and transmit control/feedback so by any logical comparison, one (Nvidia especially) should have no difficulty in creating an application for PC's (win32/64 environment) that does the exact same thing their android app does. I have 2 video cards capable of streaming (encoding) H.264 so by right they must be capable of decoding it I would think. I should be able to stream to my second desktop or my laptop both of which by hardware comparison are superior to the Shield. I haven't found anything stating plans to allow non-shield owners to do this. Can a third party create this software or does it hinge on some limitation that only Nvidia can overcome? Reiteration of questions: Is there a technical reason (non marketing) for why Nvidia opted to bottleneck the streaming service with a wireless connection limiting the resolution to 720p and introducing intermittent video choppiness when on a wired connection one could achieve, presumably, 1080p with significantly less or zero choppiness? Is there anything limiting developers from creating a PC/Desktop application emulating the same H.264 decoding functionality that circumvents the need to get an Nvidia Shield altogether? (It is not a matter of being too cheap to support Nvidia - I have many Nvidia cards that aren't being used. One should not have to purchase specialty hardware when = hardware already exists) Same questions go for Intel Widi also. I am just utterly perplexed that there are wireless live streaming solution and yet no wired. How on earth can wireless be the goto transmission medium? Is there another solution that takes advantage of H.264 video compression allowing live streaming over a wired connection? (*) - Perhaps this isn't the first but afaik it is the first complete package. (**) - I cant back that up with hard evidence/links but someone probably could. Edit: Maybe this will be the solution I am looking for but I still find it hard to believe that they would be the first and after wireless solutions already exist. In-home Streaming You can play all your Windows and Mac games on your SteamOS machine, too. Just turn on your existing computer and run Steam as you always have - then your SteamOS machine can stream those games over your home network straight to your TV! - http://store.steampowered.com/livingroom/SteamOS/

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  • Weighted round robins via TTL - possible?

    - by Joe Hopfgartner
    I currently use DNS round robin for load balancing, which works great. The records look like this (I have a ttl of 120 seconds) ;; ANSWER SECTION: orion.2x.to. 116 IN A 80.237.201.41 orion.2x.to. 116 IN A 87.230.54.12 orion.2x.to. 116 IN A 87.230.100.10 orion.2x.to. 116 IN A 87.230.51.65 I learned that not every ISP / device treats such a response the same way. For example some DNS servers rotate the addresses randomly or always cycle them through. Some just propagate the first entry, others try to determine which is best (regionally near) by looking at the ip address. However if the userbase is big enough (spreads over multiple ISPs etc) it balances pretty well. The discrepancies from highest to lowest loaded server hardly every exceeds 15%. However now I have the problem that I am introducing more servers into the systems, that not all have the same capacities. I currently only have 1gbps servers, but I want to work with 100mbit and also 10gbps servers too. So what I want is I want to introduce a server with 10 GBps with a weight of 100, a 1 gbps server with a weight of 10 and a 100 mbit server with a weight of 1. I used to add servers twice to bring more traffic to them (which worked nice. the bandwidth doubled almost.) But adding a 10gbit server 100 times to DNS is a bit rediculous. So I thought about using the TTL. If I give server A 240 seconds ttl and server B only 120 seconds (which is about about the minimum to use for round robin, as a lot of dns servers set to 120 if a lower ttl is specified.. so i have heard) I think something like this should occour in an ideal scenario: first 120 seconds 50% of requests get server A -> keep it for 240 seconds. 50% of requests get server B -> keep it for 120 seconds second 120 seconds 50% of requests still have server A cached -> keep it for another 120 seconds. 25% of requests get server A -> keep it for 240 seconds 25% of requests get server B -> keep it for 120 seconds third 120 seconds 25% will get server A (from the 50% of Server A that now expired) -> cache 240 sec 25% will get server B (from the 50% of Server A that now expired) -> cache 120 sec 25% will have server A cached for another 120 seconds 12.5% will get server B (from the 25% of server B that now expired) -> cache 120sec 12.5% will get server A (from the 25% of server B that now expired) -> cache 240 sec fourth 120 seconds 25% will have server A cached -> cache for another 120 secs 12.5% will get server A (from the 25% of b that now expired) -> cache 240 secs 12.5% will get server B (from the 25% of b that now expired) -> cache 120 secs 12.5% will get server A (from the 25% of a that now expired) -> cache 240 secs 12.5% will get server B (from the 25% of a that now expired) -> cache 120 secs 6.25% will get server A (from the 12.5% of b that now expired) -> cache 240 secs 6.25% will get server B (from the 12.5% of b that now expired) -> cache 120 secs 12.5% will have server A cached -> cache another 120 secs ... i think i lost something at this point but i think you get the idea.... As you can see this gets pretty complicated to predict and it will for sure not work out like this in practice. But it should definitely have an effect on the distribution! I know that weighted round robin exists and is just controlled by the root server. It just cycles through dns records when responding and returns dns records with a set propability that corresponds to the weighting. My DNS server does not support this, and my requirements are not that precise. If it doesnt weight perfectly its okay, but it should go into the right direction. I think using the TTL field could be a more elegant and easier solution - and it deosnt require a dns server that controls this dynamically, which saves resources - which is in my opinion the whole point of dns load balancing vs hardware load balancers. My question now is... are there any best prectices / methos / rules of thumb to weight round robin distribution using the TTL attribute of DNS records? Edit: The system is a forward proxy server system. The amount of Bandwidth (not requests) exceeds what one single server with ethernet can handle. So I need a balancing solution that distributes the bandwidth to several servers. Are there any alternative methods than using DNS? Of course I can use a load balancer with fibre channel etc, but the costs are rediciulous and it also increases only the width of the bottleneck and does not eliminate it. The only thing i can think of are anycast (is it anycast or multicast?) ip addresses, but I don't have the means to set up such a system.

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  • Apache on Win32: Slow Transfers of single, static files in HTTP, fast in HTTPS

    - by Michael Lackner
    I have a weird problem with Apache 2.2.15 on Windows 2000 Server SP4. Basically, I am trying to serve larger static files, images, videos etc. The download seems to be capped at around 550kB/s even over 100Mbit LAN. I tried other protocols (FTP/FTPS/FTP+ES/SCP/SMB), and they are all in the multi-megabyte range. The strangest thing is that, when using Apache with HTTPS instead of HTTP, it serves very fast, around 2.7MByte/s! I also tried the AnalogX SimpleWWW server just to test the plain HTTP speed of it, and it gave me a healthy 3.3Mbyte/s. I am at a total loss here. I searched the web, and tried to change the following Apache configuration directives in httpd.conf, one at a time, mostly to no avail at all: SendBufferSize 1048576 #(tried multiples of that too, up to 100Mbytes) EnableSendfile Off #(minor performance boost) EnableMMAP Off Win32DisableAcceptEx HostnameLookups Off #(default) I also tried to tune the following registry parameters, setting their values to 4194304 in decimal (they are REG_DWORD), and rebooting afterwards: HKLM\SYSTEM\CurrentControlSet\Services\AFD\Parameters\DefaultReceiveWindow HKLM\SYSTEM\CurrentControlSet\Services\AFD\Parameters\DefaultSendWindow Additionally, I tried to install mod_bw, which sets the event timer precision to 1ms, and allows for bandwidth throttling. According to some people it boosts static file serving performance when set to unlimited bandwidth for everybody. Unfortunately, it did nothing for me. So: AnalogX HTTP: 3300kB/s Gene6 FTPD, plain: 3500kB/s Gene6 FTPD, Implicit and Explicit SSL, AES256 Cipher: 1800-2000kB/s freeSSHD: 1100kB/s SMB shared folder: about 3000kB/s Apache HTTP, plain: 550kB/s Apache HTTPS: 2700kB/s Clients that were used in the bandwidth testing: Internet Explorer 8 (HTTP, HTTPS) Firefox 8 (HTTP, HTTPS) Chrome 13 (HTTP, HTTPS) Opera 11.60 (HTTP, HTTPS) wget under CygWin (HTTP, HTTPS) FileZilla (FTP, FTPS, FTP+ES, SFTP) Windows Explorer (SMB) Generally, transfer speeds are not too high, but that's because the server machine is an old quad Pentium Pro 200MHz machine with 2GB RAM. However, I would like Apache to serve at at least 2Mbyte/s instead of 550kB/s, and that already works with HTTPS easily, so I fail to see why plain HTTP is so crippled. I am using a Kerio Winroute Firewall, but no Throttling and no special filters peeking into HTTP traffic, just the plain Firewall functionality for blocking/allowing connections. The Apache error.log (Loglevel info) shows no warnings, no errors. Also nothing strange to be seen in access.log. I have already stripped down my httpd.conf to the bare minimum just to make sure nothing is interfering, but that didn't help either. If you have any idea, help would be greatly appreciated, since I am totally out of ideas! Thanks! Edit: I have now tried a newer Apache 2.2.21 to see if it makes any difference. However, the behaviour is exactly the same. Edit 2: KM01 has requested a sniff on the HTTP headers, so here comes the LiveHTTPHeaders output (an extension to Firefox). The Output is generated on downloading a single file called "elephantsdream_source.264", which is an H.264/AVC elementary video stream under an Open Source license. I have taken the freedom to edit the URL, removing folders and changing the actual servers domain name to www.mydomain.com. Here it is: LiveHTTPHeaders, Plain HTTP: http://www.mydomain.com/elephantsdream_source.264 GET /elephantsdream_source.264 HTTP/1.1 Host: www.mydomain.com User-Agent: Mozilla/5.0 (Windows NT 5.2; WOW64; rv:6.0.2) Gecko/20100101 Firefox/6.0.2 Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8 Accept-Language: de-de,de;q=0.8,en-us;q=0.5,en;q=0.3 Accept-Encoding: gzip, deflate Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.7 Connection: keep-alive HTTP/1.1 200 OK Date: Wed, 21 Dec 2011 20:55:16 GMT Server: Apache/2.2.21 (Win32) mod_ssl/2.2.21 OpenSSL/0.9.8r PHP/5.2.17 Last-Modified: Thu, 28 Oct 2010 20:20:09 GMT Etag: "c000000013fa5-29cf10e9-493b311889d3c" Accept-Ranges: bytes Content-Length: 701436137 Keep-Alive: timeout=15, max=100 Connection: Keep-Alive Content-Type: text/plain LiveHTTPHeaders, HTTPS: https://www.mydomain.com/elephantsdream_source.264 GET /elephantsdream_source.264 HTTP/1.1 Host: www.mydomain.com User-Agent: Mozilla/5.0 (Windows NT 5.2; WOW64; rv:6.0.2) Gecko/20100101 Firefox/6.0.2 Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8 Accept-Language: de-de,de;q=0.8,en-us;q=0.5,en;q=0.3 Accept-Encoding: gzip, deflate Accept-Charset: ISO-8859-1,utf-8;q=0.7,*;q=0.7 Connection: keep-alive HTTP/1.1 200 OK Date: Wed, 21 Dec 2011 20:56:57 GMT Server: Apache/2.2.21 (Win32) mod_ssl/2.2.21 OpenSSL/0.9.8r PHP/5.2.17 Last-Modified: Thu, 28 Oct 2010 20:20:09 GMT Etag: "c000000013fa5-29cf10e9-493b311889d3c" Accept-Ranges: bytes Content-Length: 701436137 Keep-Alive: timeout=15, max=100 Connection: Keep-Alive Content-Type: text/plain

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  • Intel Dual Band Wireless-AC 7260 keeps dropping wifi

    - by Rick T
    My wifi Intel Dual Band Wireless-AC 7260 keeps dropping wificonnection drops and the network to which I was connected disappears from the list of available networks in network manager. The only way to fix it is to disable wifi and re-enable it How can I fix this. I'm using ubuntu 14.04 64bit. It mostly drops connections on the 5ghz network. My other devices don't drop connections over wifi. see logs and versions rt@simon:~$ uname -a Linux simon 3.13.0-34-generic #60-Ubuntu SMP Wed Aug 13 15:45:27 UTC 2014 x86_64 x86_64 x86_64 GNU/Linux rt@simon:~$ rt@simon:~$ dmesg | grep iwl [ 3.370777] iwlwifi 0000:03:00.0: irq 46 for MSI/MSI-X [ 3.381089] iwlwifi 0000:03:00.0: loaded firmware version 22.24.8.0 op_mode iwlmvm [ 3.414637] iwlwifi 0000:03:00.0: Detected Intel(R) Dual Band Wireless AC 7260, REV=0x144 [ 3.414695] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 3.414913] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 3.630208] ieee80211 phy0: Selected rate control algorithm 'iwl-mvm-rs' [ 9.304838] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 9.305068] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 605.483174] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S [ 605.483396] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S rt@simon:~$ cat /var/log/syslog | grep -e iwl -e 80211 | tail -n25 Aug 14 08:13:02 simon kernel: [ 3.452780] cfg80211: (5735000 KHz - 5835000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:13:02 simon kernel: [ 3.630208] ieee80211 phy0: Selected rate control algorithm 'iwl-mvm-rs' Aug 14 08:13:06 simon NetworkManager[1125]: <info> rfkill1: found WiFi radio killswitch (at /sys/devices/pci0000:00/0000:00:1c.2/0000:03:00.0/ieee80211/phy0/rfkill1) (driver iwlwifi) Aug 14 08:13:06 simon NetworkManager[1125]: <info> (wlan0): using nl80211 for WiFi device control Aug 14 08:13:06 simon NetworkManager[1125]: <info> (wlan0): new 802.11 WiFi device (driver: 'iwlwifi' ifindex: 3) Aug 14 08:13:06 simon kernel: [ 9.304838] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S Aug 14 08:13:06 simon kernel: [ 9.305068] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S Aug 14 08:14:18 simon kernel: [ 81.230162] cfg80211: Calling CRDA to update world regulatory domain Aug 14 08:14:18 simon kernel: [ 81.232330] cfg80211: World regulatory domain updated: Aug 14 08:14:18 simon kernel: [ 81.232332] cfg80211: (start_freq - end_freq @ bandwidth), (max_antenna_gain, max_eirp) Aug 14 08:14:18 simon kernel: [ 81.232333] cfg80211: (2402000 KHz - 2472000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:14:18 simon kernel: [ 81.232334] cfg80211: (2457000 KHz - 2482000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:14:18 simon kernel: [ 81.232335] cfg80211: (2474000 KHz - 2494000 KHz @ 20000 KHz), (300 mBi, 2000 mBm) Aug 14 08:14:18 simon kernel: [ 81.232336] cfg80211: (5170000 KHz - 5250000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:14:18 simon kernel: [ 81.232337] cfg80211: (5735000 KHz - 5835000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:23:02 simon kernel: [ 605.483174] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S Aug 14 08:23:02 simon kernel: [ 605.483396] iwlwifi 0000:03:00.0: L1 Disabled; Enabling L0S Aug 14 08:23:18 simon kernel: [ 621.223905] cfg80211: Calling CRDA to update world regulatory domain Aug 14 08:23:18 simon kernel: [ 621.228945] cfg80211: World regulatory domain updated: Aug 14 08:23:18 simon kernel: [ 621.228950] cfg80211: (start_freq - end_freq @ bandwidth), (max_antenna_gain, max_eirp) Aug 14 08:23:18 simon kernel: [ 621.228954] cfg80211: (2402000 KHz - 2472000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:23:18 simon kernel: [ 621.228956] cfg80211: (2457000 KHz - 2482000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:23:18 simon kernel: [ 621.228959] cfg80211: (2474000 KHz - 2494000 KHz @ 20000 KHz), (300 mBi, 2000 mBm) Aug 14 08:23:18 simon kernel: [ 621.228961] cfg80211: (5170000 KHz - 5250000 KHz @ 40000 KHz), (300 mBi, 2000 mBm) Aug 14 08:23:18 simon kernel: [ 621.228963] cfg80211: (5735000 KHz - 5835000 KHz @ 40000 KHz), (300 mBi, 2000 mBm)

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  • Java Script – Content delivery networks (CDN) can bit you in the butt.

    - by Ryan Ternier
    As much as I love the new CDN’s that Google, Microsoft and a few others have publically released, there are some strong gotchas that could come up and bite you in the ass if you’re not careful. But before we jump into that, for those that are not 100% sure what a CDN is (besides Canadian).   Content Delivery Network. A way of distributing your static content across various servers in different physical locations.  Because this static content is stored on many servers around the world, whenever a user needs to access this content, they are given the closest server to their location for this data. Already you can probably see the immediate bonuses to a system like this: Lower bandwidth Even small script files downloaded thousands of times will start to take a noticeable hit on your bandwidth meter. Less connections/hits to your web server which gives better latency If you manage many servers, you don’t need to manually update each server with scripts. A user will download a script for each website they visit. If a user is redirected to many domains/sub-domains within your web site, they might download many copies of the same file. When a system sees multiple requests from the same  domain, they will ignore the download   Those are just a handful of the many bonuses a CDN will give you. And for the average website, a CDN is great choice. Check out the following CDN links for their solutions: Google AJAX Library: http://code.google.com/apis/ajaxlibs/ Microsoft Ajax library: http://www.asp.net/ajaxlibrary/cdn.ashx The Gotcha There is always a catch. Here are some issues I found with using CDN’s that hopefully can help you make your decision. HTTP / HTTPS If you are running a website behind SSL, make sure that when you reference your CDN data that you use https:// vs. http://. If you forget this users will get a very nice message telling them that their secure connection is trying to access unsecure data. For a developer this is fairly simple, but general users will get a bit anxious when seeing this. Trusted Sites Internet Explorer has this really nifty feature that allows users to specify what sites they trust, and by some defaults IE7 only allows trusted sites to be viewed.  No problem, they set your website as trusted. But what about your CDN? If a user sets your websites to trusted, but not the CDN, they will not download those static files. This has the potential to totally break your web site. Pedantic Network Admins This alone is sometimes the killer of projects. However, always be careful when you are going to use a CDN for a professional project. If a network / security admin sees that you’re referencing an outside source, or that a call from a website might hit an outside domain.. panties will be bunched, emails will be spewed out and well, no one wants that.

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  • Security Access Control With Solaris Virtualization

    - by Thierry Manfe-Oracle
    Numerous Solaris customers consolidate multiple applications or servers on a single platform. The resulting configuration consists of many environments hosted on a single infrastructure and security constraints sometimes exist between these environments. Recently, a customer consolidated many virtual machines belonging to both their Intranet and Extranet on a pair of SPARC Solaris servers interconnected through Infiniband. Virtual Machines were mapped to Solaris Zones and one security constraint was to prevent SSH connections between the Intranet and the Extranet. This case study gives us the opportunity to understand how the Oracle Solaris Network Virtualization Technology —a.k.a. Project Crossbow— can be used to control outbound traffic from Solaris Zones. Solaris Zones from both the Intranet and Extranet use an Infiniband network to access a ZFS Storage Appliance that exports NFS shares. Solaris global zones on both SPARC servers mount iSCSI LU exported by the Storage Appliance.  Non-global zones are installed on these iSCSI LU. With no security hardening, if an Extranet zone gets compromised, the attacker could try to use the Storage Appliance as a gateway to the Intranet zones, or even worse, to the global zones as all the zones are reachable from this node. One solution consists in using Solaris Network Virtualization Technology to stop outbound SSH traffic from the Solaris Zones. The virtualized network stack provides per-network link flows. A flow classifies network traffic on a specific link. As an example, on the network link used by a Solaris Zone to connect to the Infiniband, a flow can be created for TCP traffic on port 22, thereby a flow for the ssh traffic. A bandwidth can be specified for that flow and, if set to zero, the traffic is blocked. Last but not least, flows are created from the global zone, which means that even with root privileges in a Solaris zone an attacker cannot disable or delete a flow. With the flow approach, the outbound traffic of a Solaris zone is controlled from outside the zone. Schema 1 describes the new network setting once the security has been put in place. Here are the instructions to create a Crossbow flow as used in Schema 1 : (GZ)# zoneadm -z zonename halt ...halts the Solaris Zone. (GZ)# flowadm add-flow -l iblink -a transport=TCP,remote_port=22 -p maxbw=0 sshFilter  ...creates a flow on the IB partition "iblink" used by the zone to connect to the Infiniband.  This IB partition can be identified by intersecting the output of the commands 'zonecfg -z zonename info net' and 'dladm show-part'.  The flow is created on port 22, for the TCP traffic with a zero maximum bandwidth.  The name given to the flow is "sshFilter". (GZ)# zoneadm -z zonename boot  ...restarts the Solaris zone now that the flow is in place.Solaris Zones and Solaris Network Virtualization enable SSH access control on Infiniband (and on Ethernet) without the extra cost of a firewall. With this approach, no change is required on the Infiniband switch. All the security enforcements are put in place at the Solaris level, minimizing the impact on the overall infrastructure. The Crossbow flows come in addition to many other security controls available with Oracle Solaris such as IPFilter and Role Based Access Control, and that can be used to tackle security challenges.

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  • The Growing Importance of Network Virtualization

    - by user12608550
    The Growing Importance of Network Virtualization We often focus on server virtualization when we discuss cloud computing, but just as often we neglect to consider some of the critical implications of that technology. The ability to create virtual environments (or VEs [1]) means that we can create, destroy, activate and deactivate, and more importantly, MOVE them around within the cloud infrastructure. This elasticity and mobility has profound implications for how network services are defined, managed, and used to provide cloud services. It's not just servers that benefit from virtualization, it's the network as well. Network virtualization is becoming a hot topic, and not just for discussion but for companies like Oracle and others who have recently acquired net virtualization companies [2,3]. But even before this topic became so prominent, Solaris engineers were working on technologies in Solaris 11 to virtualize network services, known as Project Crossbow [4]. And why is network virtualization so important? Because old assumptions about network devices, topology, and management must be re-examined in light of the self-service, elasticity, and resource sharing requirements of cloud computing infrastructures. Static, hierarchical network designs, and inter-system traffic flows, need to be reconsidered and quite likely re-architected to take advantage of new features like virtual NICs and switches, bandwidth control, load balancing, and traffic isolation. For example, traditional multi-tier Web services (Web server, App server, DB server) that share net traffic over Ethernet wires can now be virtualized and hosted on shared-resource systems that communicate within a larger server at system bus speeds, increasing performance and reducing wired network traffic. And virtualized traffic flows can be monitored and adjusted as needed to optimize network performance for dynamically changing cloud workloads. Additionally, as VEs come and go and move around in the cloud, static network configuration methods cannot easily accommodate the routing and addressing flexibility that VE mobility implies; virtualizing the network itself is a requirement. Oracle Solaris 11 [5] includes key network virtualization technologies needed to implement cloud computing infrastructures. It includes features for the creation and management of virtual NICs and switches, and for the allocation and control of the traffic flows among VEs [6]. Additionally it allows for both sharing and dedication of hardware components to network tasks, such as allocating specific CPUs and vNICs to VEs, and even protocol-specific management of traffic. So, have a look at your current network topology and management practices in view of evolving cloud computing technologies. And don't simply duplicate the physical architecture of servers and connections in a virtualized environment…rethink the traffic flows among VEs and how they can be optimized using Oracle Solaris 11 and other Oracle products and services. [1] I use the term "virtual environment" or VE here instead of the more commonly used "virtual machine" or VM, because not all virtualized operating system environments are full OS kernels under the control of a hypervisor…in other words, not all VEs are VMs. In particular, VEs include Oracle Solaris zones, as well as SPARC VMs (previously called LDoms), and x86-based Solaris and Linux VMs running under hypervisors such as OEL, Xen, KVM, or VMware. [2] Oracle follows VMware into network virtualization space with Xsigo purchase; http://www.mercurynews.com/business/ci_21191001/oracle-follows-vmware-into-network-virtualization-space-xsigo [3] Oracle Buys Xsigo; http://www.oracle.com/us/corporate/press/1721421 [4] Oracle Solaris 11 Networking Virtualization Technology, http://www.oracle.com/technetwork/server-storage/solaris11/technologies/networkvirtualization-312278.html [5] Oracle Solaris 11; http://www.oracle.com/us/products/servers-storage/solaris/solaris11/overview/index.html [6] For example, the Solaris 11 'dladm' command can be used to limit the bandwidth of a virtual NIC, as follows: dladm create-vnic -l net0 -p maxbw=100M vnic0

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  • Upgrade to Xubuntu 13.10 - Saucy Salamander

    As a common 'fashion' it is possible to upgrade an existing installation of Ubuntu or one of its derivates every six months. Of course, you might opt-in for the adventure and directly keep your system always on the latest version (including alphas and betas), or you might like to play safe and stay on the long-term support (LTS) versions which are updated every two years only. As for me, I'd like to jump from release to release on my main desktop machine. And since 17th October Saucy Salamander or also known as Ubuntu 13.10 has been released for general use. The following paragraphs document the steps I went in order to upgrade my system to the recent version. Don't worry about the fact that I'm actually using Xubuntu. It's mainly a flavoured version of Ubuntu running Xfce 4.10 as default X Window manager. Well, I have Gnome and LXDE on the same system... just out of couriosity. Preparing the system Before you think about upgrading you have to ensure that your current system is running on the latest packages. This can be done easily via a terminal like so: $ sudo apt-get update && sudo apt-get -y dist-upgrade --fix-missing Next, we are going to initiate the upgrade itself: $ sudo update-manager As a result the graphical Software Updater should inform you that a newer version of Ubuntu is available for installation. Ubuntu's Software Updater informs you whether an upgrade is available Running the upgrade After clicking 'Upgrade...' you will be presented with information about the new version. Details about Ubuntu 13.10 (Saucy Salamander) Simply continue with the procedure and your system will be analysed for the next steps. Analysing the existing system and preparing the actual upgrade to 13.10 Next, we are at the point of no return. Last confirmation dialog before having a coffee break while your machine is occupied to download the necessary packages. Not the best bandwidth at hand after all... yours might be faster. Are you really sure that you want to start the upgrade? Let's go and have fun! Anyway, bye bye Raring Ringtail and Welcome Saucy Salamander! In case that you added any additional repositories like Medibuntu or PPAs you will be informed that they are going to be disabled during the upgrade and they might require some manual intervention after completion. Ubuntu is playing safe and third party repositories are disabled during the upgrade Well, depending on your internet bandwidth this might take something between a couple of minutes and some hours to download all the packages and then trigger the actual installation process. In my case I left my PC unattended during the night. Time to reboot Finally, it's time to restart your system and see what's going to happen... In my case absolutely nothing unexpected. The system booted the new kernel 3.11.0 as usual and I was greeted by a new login screen. Honestly, 'same' system as before - which is good and I love that fact of consistency - and I can continue to work productively. And also Software Updater confirms that we just had a painless upgrade: System is running Ubuntu 13.10 - Saucy Salamander - and up to date See you in six months again... ;-) Post-scriptum In case that you would to upgrade to the latest development version of Ubuntu, run the following command in a console: $ sudo update-manager -d And repeat all steps as described above.

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  • Is there an "embedded DBMS" to support multiple writer applications (processes) on the same db files

    - by Amir Moghimi
    I need to know if there is any embedded DBMS (preferably in Java and not necessarily relational) which supports multiple writer applications (processes) on the same set of db files. BerkeleyDB supports multiple readers but just one writer. I need multiple writers and multiple readers. UPDATE: It is not a multiple connection issue. I mean I do not need multiple connections to a running DBMS application (process) to write data. I need multiple DBMS applications (processes) to commit on the same storage files. HSQLDB, H2, JavaDB (Derby) and MongoDB do not support this feature. I think that there may be some File System limitations that prohibit this. If so, is there a File System that allows multiple writers on a single file? Use Case: The use case is a high-throughput clustered system that intends to store its high-volume business log entries into a SAN storage. Storing business logs in separate files for each server does not fit because query and indexing capabilities are needed on the whole biz logs. Because "a SAN typically is its own network of storage devices that are generally not accessible through the regular network by regular devices", I want to use SAN network bandwidth for logging while cluster LAN bandwidth is being used for other server to server and client to server communications.

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  • BITS client fails to specify HTTP Range header

    - by user256890
    Our system is designed to deploy to regions with unreliable and/or insufficient network connections. We build our own fault tolerating data replication services that uses BITS. Due to some security and maintenance requirements, we implemented our own ASP.NET file download service on the server side, instead of just letting IIS serving up the files. When BITS client makes an HTTP download request with the specified range of the file, our ASP.NET page pulls the demanded file segment into memory and serve that up as the HTTP response. That is the theory. ;) This theory fails in artificial lab scenarios but I would not let the system deploy in real life scenarios unless we can overcome that. Lab scenario: I have BITS client and the IIS on the same developer machine, so practically I have enormous network "bandwidth" and BITS is intelligent enough to detect that. As BITS client discovers the unlimited bandwidth, it gets more and more "greedy". At each HTTP request, BITS wants to grasp greater and greater file ranges (we are talking about downloading CD iso files, videos), demanding 20-40MB inside a single HTTP request, a size that I am not comfortable to pull into memory on the server side as one go. I can overcome that simply by giving less than demanded. It is OK. However, BITS gets really "confident" and "arrogant" demanding files WITHOUT specifying the download range, i.e., it wants the entire file in a single request, and this is where things go wrong. I do not know how to answer that response in the case of a 600MB file. If I just provide the starting 1MB range of the file, BITS client keeps sending HTTP requests for the same file without download range to continue, it hammers its point that it wants the entire file in one go. Since I am reluctant to provide the entire file, BITS gives up after several trials and reports error. Any thoughts?

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  • How are you taking advantage of Multicore?

    - by tgamblin
    As someone in the world of HPC who came from the world of enterprise web development, I'm always curious to see how developers back in the "real world" are taking advantage of parallel computing. This is much more relevant now that all chips are going multicore, and it'll be even more relevant when there are thousands of cores on a chip instead of just a few. My questions are: How does this affect your software roadmap? I'm particularly interested in real stories about how multicore is affecting different software domains, so specify what kind of development you do in your answer (e.g. server side, client-side apps, scientific computing, etc). What are you doing with your existing code to take advantage of multicore machines, and what challenges have you faced? Are you using OpenMP, Erlang, Haskell, CUDA, TBB, UPC or something else? What do you plan to do as concurrency levels continue to increase, and how will you deal with hundreds or thousands of cores? If your domain doesn't easily benefit from parallel computation, then explaining why is interesting, too. Finally, I've framed this as a multicore question, but feel free to talk about other types of parallel computing. If you're porting part of your app to use MapReduce, or if MPI on large clusters is the paradigm for you, then definitely mention that, too. Update: If you do answer #5, mention whether you think things will change if there get to be more cores (100, 1000, etc) than you can feed with available memory bandwidth (seeing as how bandwidth is getting smaller and smaller per core). Can you still use the remaining cores for your application?

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  • can load data(google app enngine) from http://localhost:8100/remote_api ..

    - by zjm1126
    i can download data from gae (http://zjm1126.appspot.com/remote_api), this is code: appcfg.py download_data --application=zjm1126 --url=http://zjm1126.appspot.com/remote_api --filename=a.csv and it successful : D:\zjm_demo\app>appcfg.py download_data --application=zjm1126 --url=http://zjm1 126.appspot.com/remote_api --filename=a.csv Downloading data records. [INFO ] Logging to bulkloader-log-20100618.162421 [INFO ] Throttling transfers: [INFO ] Bandwidth: 250000 bytes/second [INFO ] HTTP connections: 8/second [INFO ] Entities inserted/fetched/modified: 20/second [INFO ] Batch Size: 10 [INFO ] Opening database: bulkloader-progress-20100618.162421.sql3 [INFO ] Opening database: bulkloader-results-20100618.162421.sql3 [INFO ] Connecting to zjm1126.appspot.com/remote_api Please enter login credentials for zjm1126.appspot.com Email: [email protected] Password for [email protected]: [INFO ] Downloading kinds: [u'LogText', u'Greeting', u'Forum', u'Thread'] .... [INFO ] Have 0 entities, 0 previously transferred [INFO ] 0 entities (8804 bytes) transferred in 11.3 seconds so i want to know can load data from 127.0.0.1 , this is my code : appcfg.py download_data --application=zjm1126 --url=http://localhost:8100/remote_api --filename=a.csv and the error is : D:\zjm_demo\app>appcfg.py download_data --application=zjm1126 --url=http://loca lhost:8100/remote_api --filename=a.csv Downloading data records. [INFO ] Logging to bulkloader-log-20100618.162325 [INFO ] Throttling transfers: [INFO ] Bandwidth: 250000 bytes/second [INFO ] HTTP connections: 8/second [INFO ] Entities inserted/fetched/modified: 20/second [INFO ] Batch Size: 10 [INFO ] Opening database: bulkloader-progress-20100618.162325.sql3 [INFO ] Opening database: bulkloader-results-20100618.162325.sql3 Please enter login credentials for localhost Email: [email protected] Password for [email protected]: [INFO ] Connecting to localhost:8100/remote_api [ERROR ] Exception during authentication Traceback (most recent call last): File "d:\Program Files\Google\google_appengine\google\appengine\tools\bulkload er.py", line 3169, in Run self.request_manager.Authenticate() File "d:\Program Files\Google\google_appengine\google\appengine\tools\bulkload er.py", line 1178, in Authenticate remote_api_stub.MaybeInvokeAuthentication() File "d:\Program Files\Google\google_appengine\google\appengine\ext\remote_api \remote_api_stub.py", line 542, in MaybeInvokeAuthentication datastore_stub._server.Send(datastore_stub._path, payload=None) File "d:\Program Files\Google\google_appengine\google\appengine\tools\appengin e_rpc.py", line 346, in Send f = self.opener.open(req) File "D:\Python25\lib\urllib2.py", line 387, in open response = meth(req, response) File "D:\Python25\lib\urllib2.py", line 498, in http_response 'http', request, response, code, msg, hdrs) File "D:\Python25\lib\urllib2.py", line 425, in error return self._call_chain(*args) File "D:\Python25\lib\urllib2.py", line 360, in _call_chain result = func(*args) File "D:\Python25\lib\urllib2.py", line 506, in http_error_default raise HTTPError(req.get_full_url(), code, msg, hdrs, fp) HTTPError: HTTP Error 404: Not Found [INFO ] Authentication Failed so what should i do , thanks

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  • send message to a web service according to its schema

    - by hguser
    Hi: When I request a web servcie,it give me a response which show me the required parameters and its schema,for example: the response of the web service for the descriptin of the parameter Then I start to organize the next requset according to the parameter,for the parameter "bandWith" I set it as the following: <InputParameter parameterID="bandWidth"> <value> <commonData> <swe:Category> <swe:quality> <swe:Text> <swe:value>low</swe:value> </swe:Text> </swe:quality> </swe:Category> </commonData> </value> </InputParameter> However I got a exception : error information Also I tried the following format,things does not chage: <InputParameter parameterID="bandWidth"> <value> <commonData> <swe:Category> <swe:value>low</swe:value> </swe:Category> </commonData> </value> </InputParameter> So, I wonder how do define the parameter to match the format it defined? The schema can be found there: The schema

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  • What can I do to get Mozilla Firefox to preload the eventual image result?

    - by Dalal
    I am attempting to preload images using JavaScript. I have declared an array as follows with image links from different places: var imageArray = new Array(); imageArray[0] = new Image(); imageArray[1] = new Image(); imageArray[2] = new Image(); imageArray[3] = new Image(); imageArray[0].src = "http://www.bollywoodhott.com/wp-content/uploads/2008/12/arjun-rampal.jpg"; imageArray[1].src = "http://labelleetleblog.files.wordpress.com/2009/06/josie-maran.jpg"; imageArray[2].src = "http://1.bp.blogspot.com/_22EXDJCJp3s/SxbIcZHTHTI/AAAAAAAAIXc/fkaDiOKjd-I/s400/black-male-model.jpg"; imageArray[3].src = "http://www.iill.net/wp-content/uploads/images/hot-chick.jpg"; The image fade and transformation effects that I am doing using this array work properly for the first 3 images, but for the last one, imageArray[3], the actual image data of the image does not get preloaded and it completely ruins the effect, since the actual image data loads AFTERWARDS, only at the time it needs to be displayed, it seems. This happens because the last link http://www.iill.net/wp-content/uploads/images/hot-chick.jpg is not a direct link to the image. If you go to that link, your browser will redirect you to the ACTUAL location. Now, my image preloading code in Chrome works perfectly well, and the effects look great. Because it seems that Chrome preloads the actual data - the EVENTUAL image that is to be shown. This means that in Chrome if I preloaded an image that will redirect to 'stop stealing my bandwidth', then the image that gets preloaded is 'stop stealing my bandwidth'. How can I modify my code to get Firefox to behave the same way?

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  • How do I handle freeing unmanaged structures on application close?

    - by LostKaleb
    I have a C# project in which i use several unmanaged C++ functions. More so, I also have static IntPtr that I use as parameters for those functions. I know that whenever I use them, I should implement IDisposable in that class and use a destructor to invoke the Dispose method, where I free the used IntPtr, as is said in the MSDN page. public void Dispose() { Dispose(true); GC.SuppressFinalize(this); } private void Dispose(bool disposing) { // Check to see if Dispose has already been called. if (!this.disposed) { if (disposing) { component.Dispose(); } CloseHandle(m_InstanceHandle); m_InstanceHandle = IntPtr.Zero; disposed = true; } } [System.Runtime.InteropServices.DllImport("Kernel32")] private extern static Boolean CloseHandle(IntPtr handle); However, when I terminate the application, I'm still left with a hanging process in TaskManager. I believe that it must be related to the used of the MarshalAs instruction in my structures: [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Ansi)] public struct SipxAudioCodec { [MarshalAs(UnmanagedType.ByValTStr, SizeConst=32)] public string CodecName; public SipxAudioBandwidth Bandwidth; public int PayloadType; } When I create such a structure should I also be careful to free the space it allocs using a destructor? [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Ansi)] public struct SipxAudioCodec { [MarshalAs(UnmanagedType.ByValTStr, SizeConst=32)] public string CodecName; public SipxAudioBandwidth Bandwidth; public int PayloadType; ~SipxAudioCodec() { Marshal.FreeGlobal(something...); } }

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