Search Results

Search found 6881 results on 276 pages for 'storage spaces'.

Page 60/276 | < Previous Page | 56 57 58 59 60 61 62 63 64 65 66 67  | Next Page >

  • How can I build something like Amazon S3 in Perl?

    - by Joel G
    I am looking to code a file storage application in perl similar to amazon s3. I already have a amazon s3 clone that I found online called parkplace but its in ruby and is old also isn't built for high loads. I am not really sure what modules and programs I should use so id like some help picking them out. My requirements are listed below (yes I know there are lots but I could start simple then add more once I get it going): Easy API implementation for client side apps. (maybe REST (?) Centralized database server for the USERDB (maybe PostgreSQL (?). Logging of all connections, bandwidth used, well pretty much everything to a centralized server (maybe PostgreSQL again (?). Easy server side configuration (config file(s) stored on the servers). Web based control panel for admin(s) and user(s) to show logs. (could work just running queries from the databases) Fast High Uptime Low memory usage Some sort of load distribution/load balancer (maybe a dns based or pound or perlbal or something else (?). Maybe a cache of some sort (memcached or parlbal or something else (?). Thanks in advance

    Read the article

  • Is it possible to read data that has been separately copied to the Android sd card without having ro

    - by icecream
    I am developing an application that needs to access data on the sd card. When I run on my development device (an odroid with Android 2.1) I have root access and can construct the path using: File sdcard = Environment.getExternalStorageDirectory(); String path = sdcard.getAbsolutePath() + File.separator + "mydata" File data = new File(path); File[] files = data.listFiles(new FilenameFilter() { @Override public boolean accept(File dir, String filename) { return filename.toLowerCase().endsWith(".xyz"); }}); However, when I install this on a phone (2.1) where I do not have root access I get files == null. I assume this is because I do not have the right permissions to read the data from the sd card. I also get files == null when just trying to list files on /sdcard. So the same applies without my constructed path. Also, this app is not intended to be distributed through the app store and is needs to use data copied separately to the sd card so this is a real use-case. It is too much data to put in res/raw (I have tried, it did not work). I have also tried adding: <uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" /> to the manifest, even though I only want to read the sd card, but it did not help. I have not found a permission type for reading the storage. There is probably a correct way to do this, but I haven't been able to find it. Any hints would be useful.

    Read the article

  • StorageClientException: The specified message does not exist?

    - by Aaron
    I have a simple video encoding worker role that pulls messages from a queue encodes a video then uploads the video to storage. Everything seems to be working but occasionally when deleting the message after I am done encoding and uploading I get a "StorageClientException: The specified message does not exist." Although the video is processed, I believe the message is reappearing in the queue because it's not being deleted correctly. Is it possible that another instance of the Worker role is processing and deleting the message? Doesn't the GetMessage() prevent other worker roles from picking up the same message? Am I doing something wrong in the setup of my queue? What could be causing this message to not be found on delete? some code... //onStart() queue setup var queueStorage = _storageAccount.CreateCloudQueueClient(); _queue = queueStorage.GetQueueReference(QueueReference); queueStorage.RetryPolicy = RetryPolicies.Retry(5, new TimeSpan(0, 5, 0)); _queue.CreateIfNotExist(); public override void Run() { while (true) { try { var msg = _queue.GetMessage(new TimeSpan(0, 5, 0)); if (msg != null) { EncodeIt(msg); PostIt(msg); _queue.DeleteMessage(msg); } else { Thread.Sleep(WaitTime); } } catch (StorageClientException exception) { BlobTrace.Write(exception.ToString()); Thread.Sleep(WaitTime); } } }

    Read the article

  • Architecture for data layer that uses both localStorage and a REST remote server

    - by Zack
    Anybody has any ideas or references on how to implement a data persistence layer that uses both a localStorage and a REST remote storage: The data of a certain client is stored with localStorage (using an ember-data indexedDB adapter). The locally stored data is synced with the remote server (using ember-data RESTadapter). The server gathers all data from clients. Using mathematical sets notation: Server = Client1 ? Client2 ? ... ? ClientN where, in general, a record may not be unique to a certain client. Here are some scenarios: A client creates a record. The id of the record can not set on the client, since it may conflict with a record stored on the server. Therefore a newly created record needs to be committed to the server - receive the id - create the record in localStorage. A record is updated on the server, and as a consequence the data in localStorage and in the server go out of sync. Only the server knows that, so the architecture needs to implement a push architecture (?) Would you use 2 stores (one for localStorage, one for REST) and sync between them, or use a hybrid indexedDB/REST adapter and write the sync code within the adapter? Can you see any way to avoid implementing push (Web Sockets, ...)?

    Read the article

  • Windows Azure - Automatic Load Balancing - partitioning

    - by veda
    I was going through some videos. I found that Windows Azure will group the blobs into partitions based on the partition key and will Automatically Load Balance these partitions on their servers. The partition key for a blob is blob name. Using the blob name, azure will automatically do partitions. Now, My question is that Can I able to make the azure to do partitions based on the Container Name. I wanted my partition key to be container name. For example, I have a storage account. In that I have 2 containers named container1 and container2. In container1, I have 1000 files named 1.txt, 2.txt, 3.txt, ......., 501.txt, 502.txt, ..... 999.txt, 1000.txt and in container2, I have another 1000 files named 1001.txt, 1002.txt, 1003.txt, ......., 1501.txt, 1502.txt, ..... 1999.txt, 2000.txt Now, Will Windows Azure will generate 2000 partitions based on the blob name and serve me through several servers??? Won't it be better if Azure partitions based on the Container name? container1 on one server and conatiner2 on another.

    Read the article

  • How do I use HTML5's localStorage in a Google Chrome extension?

    - by davidkennedy85
    I am trying to develop an extension that will work with Awesome New Tab Page. I've followed the author's advice to the letter, but it doesn't seem like any of the script I add to my background page is being executed at all. Here's my background page: <script> var info = { poke: 1, width: 1, height: 1, path: "widget.html" } chrome.extension.onRequestExternal.addListener(function(request, sender, sendResponse) { if (request === "mgmiemnjjchgkmgbeljfocdjjnpjnmcg-poke") { chrome.extension.sendRequest( sender.id, { head: "mgmiemnjjchgkmgbeljfocdjjnpjnmcg-pokeback", body: info, } ); } }); function initSelectedTab() { localStorage.setItem("selectedTab", "Something"); } initSelectedTab(); </script> Here is manifest.json: { "update_url": "http://clients2.google.com/service/update2/crx", "background_page": "background.html", "name": "Test Widget", "description": "Test widget for mgmiemnjjchgkmgbeljfocdjjnpjnmcg.", "icons": { "128": "icon.png" }, "version": "0.0.1" } Here is the relevant part of widget.html: <script> var selectedTab = localStorage.getItem("selectedTab"); document.write(selectedTab); </script> Every time, the browser just displays null. The local storage isn't being set at all, which makes me think the background page is completely disconnected. Do I have something wired up incorrectly?

    Read the article

  • How to use dd to make splitted ISO images from an storage device?

    - by Gustavo Bandeira
    This is a double question, I just hope it's valid. I need to know how to use dd to make splitted ISO images from some storage device, I'm doing it through SSH: the process is slow and the risk of faling at the mid of the operation (1) is high then I need to know how to make these splitted ISO images from my storage device. (2) I'm searching for some reference on dd, it could be a book or a good website about it for when any doubt arises. 1 - I'm doing it on a ~60GB storage device, it took me a whole day to copy ~10GB from this disk. 2 - For curious people, I'm trying to recover an accidentaly deleted file from an iPod, until now I've been able to make the whole process, I just need to improve it beucase I left it copying the disk yesterday: Today it gave me an error when it was at ~10GB.

    Read the article

  • make a folder/partition on one computer appear as a mass storage device to another?

    - by user137560
    Is there anyway to make a folder or a partition on a computer (Linux or Windows) act like a mass storage device to other computers or devices when connected with a Male-Male USB cable? For example, I have a Windows 7 computer with 2 partitions, C and D. I would then connect that computer to another computer or a Smart TV using a Male-Male USB cable, and the other computer or device recognizes a folder/partition on current computer as a mass storage device. Is this possible? If not, is there any USB switch that can connect an external hard drive or flash drive to both a computer and TV without the need to manually switch them? (I know about some USB switches, but they only support automatic switching with some certain types of printers, not with mass storage)

    Read the article

  • Autocommands for Matlab in vim?

    - by Benjamin Oakes
    I use several different programming languages every day, and I'd like to have different tab widths (in spaces) for each. For example: I use the "standard" 2 spaces for Ruby, but all our existing Matlab code uses 4 spaces. I have this from my personal ~/.vimrc: augroup lang_perl au! set tabstop=4 " tabstop length N in spaces set shiftwidth=4 " make >> and friends (<<, ^T, ^D) shift N, not the default 8 set expandtab " Use spaces instead of tabs augroup END augroup lang_ruby au! set tabstop=2 " tabstop length N in spaces set shiftwidth=2 " make >> and friends (<<, ^T, ^D) shift N, not the default 8 set expandtab " Use spaces instead of tabs augroup END Those work, but the following doesn't: augroup lang_matlab au! set tabstop=4 " tabstop length N in spaces set shiftwidth=4 " make >> and friends (<<, ^T, ^D) shift N, not the default 8 set expandtab " Use spaces instead of tabs augroup END I really don't understand how augroup lang_ruby figures out that I'm editing a Ruby file. (My searches brought up ftdetect, but the solution wasn't obvious.) It doesn't seem like vim knows that I'm editing Matlab using augroup lang_matlab. What do I change to make this work?

    Read the article

  • Generic class for performing mass-parallel queries. Feedback?

    - by Aaron
    I don't understand why, but there appears to be no mechanism in the client library for performing many queries in parallel for Windows Azure Table Storage. I've created a template class that can be used to save considerable time, and you're welcome to use it however you wish. I would appreciate however, if you could pick it apart, and provide feedback on how to improve this class. public class AsyncDataQuery<T> where T: new() { public AsyncDataQuery(bool preserve_order) { m_preserve_order = preserve_order; this.Queries = new List<CloudTableQuery<T>>(1000); } public void AddQuery(IQueryable<T> query) { var data_query = (DataServiceQuery<T>)query; var uri = data_query.RequestUri; // required this.Queries.Add(new CloudTableQuery<T>(data_query)); } /// <summary> /// Blocking but still optimized. /// </summary> public List<T> Execute() { this.BeginAsync(); return this.EndAsync(); } public void BeginAsync() { if (m_preserve_order == true) { this.Items = new List<T>(Queries.Count); for (var i = 0; i < Queries.Count; i++) { this.Items.Add(new T()); } } else { this.Items = new List<T>(Queries.Count * 2); } m_wait = new ManualResetEvent(false); for (var i = 0; i < Queries.Count; i++) { var query = Queries[i]; query.BeginExecuteSegmented(callback, i); } } public List<T> EndAsync() { m_wait.WaitOne(); return this.Items; } private List<T> Items { get; set; } private List<CloudTableQuery<T>> Queries { get; set; } private bool m_preserve_order; private ManualResetEvent m_wait; private int m_completed = 0; private void callback(IAsyncResult ar) { int i = (int)ar.AsyncState; CloudTableQuery<T> query = Queries[i]; var response = query.EndExecuteSegmented(ar); if (m_preserve_order == true) { // preserve ordering only supports one result per query this.Items[i] = response.Results.First(); } else { // add any number of items this.Items.AddRange(response.Results); } if (response.HasMoreResults == true) { // more data to pull query.BeginExecuteSegmented(response.ContinuationToken, callback, i); return; } m_completed = Interlocked.Increment(ref m_completed); if (m_completed == Queries.Count) { m_wait.Set(); } } }

    Read the article

  • Objective-C memory management issue

    - by Toby Wilson
    I've created a graphing application that calls a web service. The user can zoom & move around the graph, and the program occasionally makes a decision to call the web service for more data accordingly. This is achieved by the following process: The graph has a render loop which constantly renders the graph, and some decision logic which adds web service call information to a stack. A seperate thread takes the most recent web service call information from the stack, and uses it to make the web service call. The other objects on the stack get binned. The idea of this is to reduce the number of web service calls to only those appropriate, and only one at a time. Right, with the long story out of the way (for which I apologise), here is my memory management problem: The graph has persistant (and suitably locked) NSDate* objects for the currently displayed start & end times of the graph. These are passed into the initialisers for my web service request objects. The web service call objects then retain the dates. After the web service calls have been made (or binned if they were out of date), they release the NSDate*. The graph itself releases and reallocates new NSDates* on the 'touches ended' event. If there is only one web service call object on the stack when removeAllObjects is called, EXC_BAD_ACCESS occurs in the web service call object's deallocation method when it attempts to release the date objects (even though they appear to exist and are in scope in the debugger). If, however, I comment out the release messages from the destructor, no memory leak occurs for one object on the stack being released, but memory leaks occur if there are more than one object on the stack. I have absolutely no idea what is going wrong. It doesn't make a difference what storage symantics I use for the web service call objects dates as they are assigned in the initialiser and then only read (so for correctness' sake are set to readonly). It also doesn't seem to make a difference if I retain or copy the dates in the initialiser (though anything else obviously falls out of scope or is unwantedly released elsewhere and causes a crash). I'm sorry this explanation is long winded, I hope it's sufficiently clear but I'm not gambling on that either I'm afraid. Major big thanks to anyone that can help, even suggest anything I may have missed?

    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

  • Persistance JDO - How to query a property of a collection with JDOQL?

    - by Sergio del Amo
    I want to build an application where a user identified by an email address can have several application accounts. Each account can have one o more users. I am trying to use the JDO Storage capabilities with Google App Engine Java. Here is my attempt: @PersistenceCapable @Inheritance(strategy = InheritanceStrategy.NEW_TABLE) public class AppAccount { @PrimaryKey @Persistent(valueStrategy = IdGeneratorStrategy.IDENTITY) private Long id; @Persistent private String companyName; @Persistent List<Invoices> invoices = new ArrayList<Invoices>(); @Persistent List<AppUser> users = new ArrayList<AppUser>(); // Getter Setters and Other Fields } @PersistenceCapable @EmbeddedOnly public class AppUser { @Persistent private String username; @Persistent private String firstName; @Persistent private String lastName; // Getter Setters and Other Fields } When a user logs in, I want to check how many accounts does he belongs to. If he belongs to more than one he will be presented with a dashboard where he can click which account he wants to load. This is my code to retrieve a list of app accounts where he is registered. public static List<AppAccount> getUserAppAccounts(String username) { PersistenceManager pm = JdoUtil.getPm(); Query q = pm.newQuery(AppAccount.class); q.setFilter("users.username == usernameParam"); q.declareParameters("String usernameParam"); return (List<AppAccount>) q.execute(username); } But I get the next error: SELECT FROM invoices.server.AppAccount WHERE users.username == usernameParam PARAMETERS String usernameParam: Encountered a variable expression that isn't part of a join. Maybe you're referencing a non-existent field of an embedded class. org.datanucleus.store.appengine.FatalNucleusUserException: SELECT FROM com.softamo.pelicamo.invoices.server.AppAccount WHERE users.username == usernameParam PARAMETERS String usernameParam: Encountered a variable expression that isn't part of a join. Maybe you're referencing a non-existent field of an embedded class. at org.datanucleus.store.appengine.query.DatastoreQuery.getJoinClassMetaData(DatastoreQuery.java:1154) at org.datanucleus.store.appengine.query.DatastoreQuery.addLeftPrimaryExpression(DatastoreQuery.java:1066) at org.datanucleus.store.appengine.query.DatastoreQuery.addExpression(DatastoreQuery.java:846) at org.datanucleus.store.appengine.query.DatastoreQuery.addFilters(DatastoreQuery.java:807) at org.datanucleus.store.appengine.query.DatastoreQuery.performExecute(DatastoreQuery.java:226) at org.datanucleus.store.appengine.query.JDOQLQuery.performExecute(JDOQLQuery.java:85) at org.datanucleus.store.query.Query.executeQuery(Query.java:1489) at org.datanucleus.store.query.Query.executeWithArray(Query.java:1371) at org.datanucleus.jdo.JDOQuery.execute(JDOQuery.java:243) at com.softamo.pelicamo.invoices.server.Store.getUserAppAccounts(Store.java:82) at com.softamo.pelicamo.invoices.test.server.StoreTest.testgetUserAppAccounts(StoreTest.java:39) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25) at java.lang.reflect.Method.invoke(Method.java:597) at org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:44) at org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:15) at org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:41) at org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:20) at org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:28) at org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:31) at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:76) at org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:50) at org.junit.runners.ParentRunner$3.run(ParentRunner.java:193) at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:52) at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:191) at org.junit.runners.ParentRunner.access$000(ParentRunner.java:42) at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:184) at org.junit.runners.ParentRunner.run(ParentRunner.java:236) at org.eclipse.jdt.internal.junit4.runner.JUnit4TestReference.run(JUnit4TestReference.java:46) at org.eclipse.jdt.internal.junit.runner.TestExecution.run(TestExecution.java:38) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.runTests(RemoteTestRunner.java:467) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.runTests(RemoteTestRunner.java:683) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.run(RemoteTestRunner.java:390) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.main(RemoteTestRunner.java:197) Any idea? I am getting JDO persistance totally wrong?

    Read the article

  • Fast distributed filesystem for a large amounts of data with metadata in database

    - by undefined hero
    My project uses several processing machines and one storage machine. Currently storage organized with a MSSQL filetable shared folder. Every file in storage have some metadata in database. Processing machines executes tasks for which they needed files from storage and their metadata. After completing task, processing machine puts resulting data back in storage. From there its taken by another processing machine, which also generates some file and put it back in storage. And etc. Everything was fine, but as number of processing machines increases, I found myself bottlenecked myself with storage machines hard drive performance. So I want processing machines to put files in distributed FS. to lift load from storage machines, from which they can take data from each other, not only storage machine. Can You suggest a particular distributed FS which meets my needs? Or there is another way to solve this problem, without it? Amounts of data in FS in one time are like several terabytes. (storage can handle this, but processors cannot). Data consistence is critical. Read write policy is: once file is written - its constant and may be only removed, but not modified. My current platform is Windows, but I'm ready to switch it, if there is a substantially more convenient solution on another one.

    Read the article

  • How do I escape spaces in command line in Windows without using quotation marks?

    - by David
    For example what is the alternative to this command without quotation marks: CD "c:\Documents and Settings" The full reason I don't want to use quotation marks is that this command DOES work: SVN add mypathname\*.* but this command DOES NOT work : SVN add "mypathname\*.*" The problem being when I change mypathname for a path with spaces in it I need to quote the whole thing. For example: SVN add "c:\Documents and Settings\username\svn\*.*" But when I try this I get the following error message: svn: warning: 'c:\Documents and Settings\username\svn\*.*' not found

    Read the article

  • How can I set paperclip's storage mechanism based on the current Rails environment?

    - by John Reilly
    I have a rails application that has multiple models with paperclip attachments that are all uploaded to S3. This app also has a large test suite that is run quite often. The downside with this is that a ton of files are uploaded to our S3 account on every test run, making the test suite run slowly. It also slows down development a bit, and requires you to have an internet connection in order to work on the code. Is there a reasonable way to set the paperclip storage mechanism based on the Rails environment? Ideally, our test and development environments would use the local filesystem storage, and the production environment would use S3 storage. I'd also like to extract this logic into a shared module of some kind, since we have several models that will need this behavior. I'd like to avoid a solution like this inside of every model: ### We don't want to do this in our models... if Rails.env.production? has_attached_file :image, :styles => {...}, :storage => :s3, # ...etc... else has_attached_file :image, :styles => {...}, :storage => :filesystem, # ...etc... end Any advice or suggestions would be greatly appreciated! :-)

    Read the article

  • Story of success: MySQL Enterprise Backup (MEB) was successfully integrated with IBM Tivoli Storage Manager (TSM) via System Backup to Tape (SBT) interface.

    - by user13334359
    Since version 3.6 MEB supports backups to tape through the SBT interface.The officially supported tool for such backups to tape is Oracle Secure Backup (OSB).But there are a lot of other Storage Managers. MEB allows to use them through the SBT interface. Since version 3.7 it also has option --sbt-environment which allows to pass environment variables, not needed by OSB, to third-party managers. At the same time MEB can not guarantee it would work with all of them.This month we were contacted by a customer who wanted to use IBM Tivoli Storage Manager (TSM) with MEB. We could only say them same thing I wrote in previous paragraph: this solution is supposed to work, but you have to be pioneers of this technology. And they agreed. They agreed to be the pioneers and so the story begins.MEB requires following options to be specified by those who want to connect it to SBT interface:--sbt-database-name: a name which should be handed over to SBT interface. This can be any name. Default, MySQL, works for most cases, so user is not required to specify this option.--sbt-lib-path: path to SBT library. For TSM this library comes with "Data Protection for Oracle", which, in its turn, interfaces with Oracle Recovery Manager (RMAN), which uses SBT interface. So you need to install it even if you don't use Oracle.--sbt-environment: environment for third-party manager. This option is not needed when you use OSB, but almost always necessary for third-party SBT managers. TSM requires variable TDPO_OPTFILE to be set and point to the TSM configuration file.--backup-image=sbt:: path to the image. Prefix "sbt:" indicates that image should be sent through SBT interfaceSo full command in our case would look like: ./mysqlbackup --port=3307 --protocol=tcp --user=backup_user --password=foobar \ --backup-image=sbt:my-first-backup --sbt-lib-path=/usr/lib/libobk.so \ --sbt-environment="TDPO_OPTFILE=/path/to/my/tdpo.opt" --backup-dir=/path/to/my/dir backup-to-imageAnd this command results in the following output log: MySQL Enterprise Backup version 3.7.1 [2012/02/16] Copyright (c) 2003, 2012, Oracle and/or its affiliates. All Rights Reserved. INFO: Starting with following command line ...  ./mysqlbackup --port=3307 --protocol=tcp --user=backup_user         --password=foobar --backup-image=sbt:my-first-backup         --sbt-lib-path=/usr/lib/libobk.so         --sbt-environment="TDPO_OPTFILE=/path/to/my/tdpo.opt"         --backup-dir=/path/to/my/dir backup-to-image sbt-environment: 'TDPO_OPTFILE=/path/to/my/tdpo.opt' INFO: Got some server configuration information from running server. IMPORTANT: Please check that mysqlbackup run completes successfully.             At the end of a successful 'backup-to-image' run mysqlbackup             prints "mysqlbackup completed OK!". --------------------------------------------------------------------                        Server Repository Options: --------------------------------------------------------------------   datadir                          =  /path/to/data   innodb_data_home_dir             =  /path/to/data   innodb_data_file_path            =  ibdata1:2048M;ibdata2:2048M;ibdata3:64M:autoextend:max:2048M   innodb_log_group_home_dir        =  /path/to/data   innodb_log_files_in_group        =  2   innodb_log_file_size             =  268435456 --------------------------------------------------------------------                        Backup Config Options: --------------------------------------------------------------------   datadir                          =  /path/to/my/dir/datadir   innodb_data_home_dir             =  /path/to/my/dir/datadir   innodb_data_file_path            =  ibdata1:2048M;ibdata2:2048M;ibdata3:64M:autoextend:max:2048M   innodb_log_group_home_dir        =  /path/to/my/dir/datadir   innodb_log_files_in_group        =  2   innodb_log_file_size             =  268435456 Backup Image Path= sbt:my-first-backup mysqlbackup: INFO: Unique generated backup id for this is 13297406400663200 120220 08:54:00 mysqlbackup: INFO: meb_sbt_session_open: MMS is 'Data Protection for Oracle: version 5.5.1.0' 120220 08:54:00 mysqlbackup: INFO: meb_sbt_session_open: MMS version '5.5.1.0' mysqlbackup: INFO: Uses posix_fadvise() for performance optimization. mysqlbackup: INFO: System tablespace file format is Antelope. mysqlbackup: INFO: Found checkpoint at lsn 31668381. mysqlbackup: INFO: Starting log scan from lsn 31668224. 120220  8:54:00 mysqlbackup: INFO: Copying log... 120220  8:54:00 mysqlbackup: INFO: Log copied, lsn 31668381.           We wait 1 second before starting copying the data files... 120220  8:54:01 mysqlbackup: INFO: Copying /path/to/ibdata/ibdata1 (Antelope file format). mysqlbackup: Progress in MB: 200 400 600 800 1000 1200 1400 1600 1800 2000 120220  8:55:30 mysqlbackup: INFO: Copying /path/to/ibdata/ibdata2 (Antelope file format). mysqlbackup: Progress in MB: 200 400 600 800 1000 1200 1400 1600 1800 2000 120220  8:57:18 mysqlbackup: INFO: Copying /path/to/ibdata/ibdata3 (Antelope file format). mysqlbackup: INFO: Preparing to lock tables: Connected to mysqld server. 120220 08:57:22 mysqlbackup: INFO: Starting to lock all the tables.... 120220 08:57:22 mysqlbackup: INFO: All tables are locked and flushed to disk mysqlbackup: INFO: Opening backup source directory '/path/to/data/' 120220 08:57:22 mysqlbackup: INFO: Starting to backup all files in subdirectories of '/path/to/data/' mysqlbackup: INFO: Backing up the database directory 'mysql' mysqlbackup: INFO: Backing up the database directory 'test' mysqlbackup: INFO: Copying innodb data and logs during final stage ... mysqlbackup: INFO: A copied database page was modified at 31668381.           (This is the highest lsn found on page)           Scanned log up to lsn 31670396.           Was able to parse the log up to lsn 31670396.           Maximum page number for a log record 328 120220 08:57:23 mysqlbackup: INFO: All tables unlocked mysqlbackup: INFO: All MySQL tables were locked for 0.000 seconds 120220 08:59:01 mysqlbackup: INFO: meb_sbt_backup_close: blocks: 4162  size: 1048576  bytes: 4363985063 120220  8:59:01 mysqlbackup: INFO: Full backup completed! mysqlbackup: INFO: MySQL binlog position: filename bin_mysql.001453, position 2105 mysqlbackup: WARNING: backup-image already closed mysqlbackup: INFO: Backup image created successfully.:            Image Path: 'sbt:my-first-backup' -------------------------------------------------------------    Parameters Summary -------------------------------------------------------------    Start LSN                  : 31668224    End LSN                    : 31670396 ------------------------------------------------------------- mysqlbackup completed OK!Backup successfully completed.To restore it you should use same commands like you do for any other MEB image, but need to provide sbt* options as well: $./mysqlbackup --backup-image=sbt:my-first-backup --sbt-lib-path=/usr/lib/libobk.so \ --sbt-environment="TDPO_OPTFILE=/path/to/my/tdpo.opt" --backup-dir=/path/to/my/dir image-to-backup-dirThen apply log as usual: $./mysqlbackup --backup-dir=/path/to/my/dir apply-logThen stop mysqld and finally copy-back: $./mysqlbackup --defaults-file=path/to/my.cnf --backup-dir=/path/to/my/dir copy-back  Disclaimer. This is only story of one success which can be useful for someone else. MEB is not regularly tested and not guaranteed to work with IBM TSM or any other third-party storage manager.

    Read the article

  • PHP Line Indentation

    - by Tower
    Hi, I'm curious to know, how many spaces of indentation do you prefer in PHP code? function one() { $one; function space() { $space; } } function two() { $two; function spaces() { $spaces; } } function three() { $three; function spaces() { $spaces; } } function four() { $four; function spaces() { $spaces; } } Let's not make multiple answers for same identation, but use the +1 for answers that fit your preferences.

    Read the article

  • Converting to and from local and world 3D coordinate spaces?

    - by James Bedford
    Hey guys, I've been following a guide I found here (http://knol.google.com/k/matrices-for-3d-applications-view-transformation) on constructing a matrix that will allow me to 3D coordinates to an object's local coordinate space, and back again. I've tried to implement these two matrices using my object's look, side, up and location vectors and it seems to be working for the first three coordinates. I'm a little confused as to what I should expect for the w coordinate. Here are couple of examples from the print outs I've made of the matricies that are constructed. I'm passing a test vector of [9, 8, 14, 1] each time to see if I can convert both ways: Basic example: localize matrix: Matrix: 0.000000 -0.000000 1.000000 0.000000 0.000000 1.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 5.237297 -45.530716 11.021271 1.000000 globalize matrix: Matrix: 0.000000 0.000000 1.000000 0.000000 -0.000000 1.000000 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 -11.021271 -45.530716 -5.237297 1.000000 test: Vector4f(9.000000, 8.000000, 14.000000, 1.000000) localTest: Vector4f(14.000000, 8.000000, 9.000000, -161.812256) worldTest: Vector4f(9.000000, 8.000000, 14.000000, -727.491455) More complicated example: localize matrix: Matrix: 0.052504 -0.000689 -0.998258 0.000000 0.052431 0.998260 0.002068 0.000000 0.997241 -0.052486 0.052486 0.000000 58.806095 2.979346 -39.396252 1.000000 globalize matrix: Matrix: 0.052504 0.052431 0.997241 0.000000 -0.000689 0.998260 -0.052486 0.000000 -0.998258 0.002068 0.052486 0.000000 -42.413120 5.975957 -56.419727 1.000000 test: Vector4f(9.000000, 8.000000, 14.000000, 1.000000) localTest: Vector4f(-13.508600, 8.486917, 9.290090, 2.542114) worldTest: Vector4f(9.000190, 7.993863, 13.990230, 102.057129) As you can see in the more complicated example, the coordinates after converting both ways loose some precision, but this isn't a problem. I'm just wondering how I should deal with the last (w) coordinate? Should I just set it to 1 after performing the matrix multiplication, or does it look like I've done something wrong? Thanks in advance for your help!

    Read the article

  • How to turn a folder into USB drive / mass storage?

    - by FernandoSBS
    I have a plasma TV with USB input (can play divx and etc) but what I would like to do is use a software to turn a folder in my notebook HD (windows 7) into a USB Mass Storage device, so that I can connect the TV to the PC using a USB cable so that the TV recognize the PC folder as a flash drive / usb mass storage. is seems MAC has something like what I need: http://support.apple.com/kb/ht1661 So there must be a similar to windows!

    Read the article

  • More Great Improvements to the Windows Azure Management Portal

    - by ScottGu
    Over the last 3 weeks we’ve released a number of enhancements to the new Windows Azure Management Portal.  These new capabilities include: Localization Support for 6 languages Operation Log Support Support for SQL Database Metrics Virtual Machine Enhancements (quick create Windows + Linux VMs) Web Site Enhancements (support for creating sites in all regions, private github repo deployment) Cloud Service Improvements (deploy from storage account, configuration support of dedicated cache) Media Service Enhancements (upload, encode, publish, stream all from within the portal) Virtual Networking Usability Enhancements Custom CNAME support with Storage Accounts All of these improvements are now live in production and available to start using immediately.  Below are more details on them: Localization Support The Windows Azure Portal now supports 6 languages – English, German, Spanish, French, Italian and Japanese. You can easily switch between languages by clicking on the Avatar bar on the top right corner of the Portal: Selecting a different language will automatically refresh the UI within the portal in the selected language: Operation Log Support The Windows Azure Portal now supports the ability for administrators to review the “operation logs” of the services they manage – making it easy to see exactly what management operations were performed on them.  You can query for these by selecting the “Settings” tab within the Portal and then choosing the “Operation Logs” tab within it.  This displays a filter UI that enables you to query for operations by date and time: As of the most recent release we now show logs for all operations performed on Cloud Services and Storage Accounts.  You can click on any operation in the list and click the “Details” button in the command bar to retrieve detailed status about it.  This now makes it possible to retrieve details about every management operation performed. In future updates you’ll see us extend the operation log capability to apply to all Windows Azure Services – which will enable great post-mortem and audit support. Support for SQL Database Metrics You can now monitor the number of successful connections, failed connections and deadlocks in your SQL databases using the new “Dashboard” view provided on each SQL Database resource: Additionally, if the database is added as a “linked resource” to a Web Site or Cloud Service, monitoring metrics for the linked SQL database are shown along with the Web Site or Cloud Service metrics in the dashboard. This helps with viewing and managing aggregated information across both resources in your application. Enhancements to Virtual Machines The most recent Windows Azure Portal release brings with it some nice usability improvements to Virtual Machines: Integrated Quick Create experience for Windows and Linux VMs Creating a new Windows or Linux VM is now easy using the new “Quick Create” experience in the Portal: In addition to Windows VM templates you can also now select Linux image templates in the quick create UI: This makes it incredibly easy to create a new Virtual Machine in only a few seconds. Enhancements to Web Sites Prior to this past month’s release, users were forced to choose a single geographical region when creating their first site.  After that, subsequent sites could only be created in that same region.  This restriction has now been removed, and you can now create sites in any region at any time and have up to 10 free sites in each supported region: One of the new regions we’ve recently opened up is the “East Asia” region.  This allows you to now deploy sites to North America, Europe and Asia simultaneously.  Private GitHub Repository Support This past week we also enabled Git based continuous deployment support for Web Sites from private GitHub and BitBucket repositories (previous to this you could only enable this with public repositories).  Enhancements to Cloud Services Experience The most recent Windows Azure Portal release brings with it some nice usability improvements to Cloud Services: Deploy a Cloud Service from a Windows Azure Storage Account The Windows Azure Portal now supports deploying an application package and configuration file stored in a blob container in Windows Azure Storage. The ability to upload an application package from storage is available when you custom create, or upload to, or update a cloud service deployment. To upload an application package and configuration, create a Cloud Service, then select the file upload dialog, and choose to upload from a Windows Azure Storage Account: To upload an application package from storage, click the “FROM STORAGE” button and select the application package and configuration file to use from the new blob storage explorer in the portal. Configure Windows Azure Caching in a caching enabled cloud service If you have deployed the new dedicated cache within a cloud service role, you can also now configure the cache settings in the portal by navigating to the configuration tab of for your Cloud Service deployment. The configuration experience is similar to the one in Visual Studio when you create a cloud service and add a caching role.  The portal now allows you to add or remove named caches and change the settings for the named caches – all from within the Portal and without needing to redeploy your application. Enhancements to Media Services You can now upload, encode, publish, and play your video content directly from within the Windows Azure Portal.  This makes it incredibly easy to get started with Windows Azure Media Services and perform common tasks without having to write any code. Simply navigate to your media service and then click on the “Content” tab.  All of the media content within your media service account will be listed here: Clicking the “upload” button within the portal now allows you to upload a media file directly from your computer: This will cause the video file you chose from your local file-system to be uploaded into Windows Azure.  Once uploaded, you can select the file within the content tab of the Portal and click the “Encode” button to transcode it into different streaming formats: The portal includes a number of pre-set encoding formats that you can easily convert media content into: Once you select an encoding and click the ok button, Windows Azure Media Services will kick off an encoding job that will happen in the cloud (no need for you to stand-up or configure a custom encoding server).  When it’s finished, you can select the video in the “Content” tab and then click PUBLISH in the command bar to setup an origin streaming end-point to it: Once the media file is published you can point apps against the public URL and play the content using Windows Azure Media Services – no need to setup or run your own streaming server.  You can also now select the file and click the “Play” button in the command bar to play it using the streaming endpoint directly within the Portal: This makes it incredibly easy to try out and use Windows Azure Media Services and test out an end-to-end workflow without having to write any code.  Once you test things out you can of course automate it using script or code – providing you with an incredibly powerful Cloud Media platform that you can use. Enhancements to Virtual Network Experience Over the last few months, we have received feedback on the complexity of the Virtual Network creation experience. With these most recent Portal updates, we have added a Quick Create experience that makes the creation experience very simple. All that an administrator now needs to do is to provide a VNET name, choose an address space and the size of the VNET address space. They no longer need to understand the intricacies of the CIDR format or walk through a 4-page wizard or create a VNET / subnet. This makes creating virtual networks really simple: The portal also now has a “Register DNS Server” task that makes it easy to register DNS servers and associate them with a virtual network. Enhancements to Storage Experience The portal now lets you register custom domain names for your Windows Azure Storage Accounts.  To enable this, select a storage resource and then go to the CONFIGURE tab for a storage account, and then click MANAGE DOMAIN on the command bar: Clicking “Manage Domain” will bring up a dialog that allows you to register any CNAME you want: Summary The above features are all now live in production and available to use immediately.  If you don’t already have a Windows Azure account, you can sign-up for a free trial and start using them today.  Visit the Windows Azure Developer Center to learn more about how to build apps with it. One of the other cool features that is now live within the portal is our new Windows Azure Store – which makes it incredibly easy to try and purchase developer services from a variety of partners.  It is an incredibly awesome new capability – and something I’ll be doing a dedicated post about shortly. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

    Read the article

< Previous Page | 56 57 58 59 60 61 62 63 64 65 66 67  | Next Page >