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  • Storage for large gridded datasets

    - by nullglob
    I am looking for a good storage format for large, gridded datasets. The application is meteorology, and we would prefer a format that is common within this field (to help exchange data with others). I don't need to deal with special data structures, and there should be a Fortran API. I am currently considering HDF5, GRIB2 and NetCDF4. How do these formats compare in terms of data compression? What are their main limitations? How steep is the learning curve? Are there any other storage formats worth investigating? I have not found a great deal of material outlining the differences and pros/cons of these formats (there is one relevant SO thread, and a presentation comparing GRIB and NetCDF).

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  • Nexenta storage metro cluster - what are components involved?

    - by Jiri Xichtkniha
    I'm quite imporesses that Nexenta can build storage metro cluster (site to site storage mirroring). As Nexenta is built on Illumos (successor of OpenSolaris) I was thinking what kind of components are involved in their storage metro cluster. Could anybody enlight me what components are doing this site-site mirroring and if these components are open source so one can build similar storage metro cluster on his own? ZFS is local filesystem so what takes care of clustering?

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  • Check to see if file transfer is complete

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

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  • Sensitive Data Storage - Best Practices

    - by Kenneth
    I recently started working on a personal project where I was connecting to a database using Java. This got me thinking. I have to provide the login information for a database account on the DB server in order to access the database. But if I hard code it in then it would be possible for someone to decompile the program and extract that login info. If I store it in an external setup file then the same problem exists only it would be even easier for them to get it. I could encrypt the data before storing it in either place but it seems like that's not really a fail safe either and I'm no encryption expert by any means. So what are some best practices for storing sensitive setup data for a program?

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  • iOS persistant storage with update function

    - by jernej
    im developing a game which has different levels and i need to store all levels and its elements (position, image, sounds,..) into a file/database. The levels will be updated so i need a function that checks online for a update and downloads a database dump and additional files. I was planing to store all the persistent data into a SQLLite database, but not quite sure how to do the update part - to pack the database dump and the files together (in a .zip or with a xml). Can this be done any other way (as secure as possible)? thanks!

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  • Product Launch: Oracle Optimized Storage: Solutions for Simplifying IT

    - by swalker
    On July 18, 2012 at 10am PT 17pm UK Time, Oracle is hosting an online storage launch event featuring Mark Hurd, John Fowler, and several other Oracle executives.  This event will consist of 3 different webcasts, all detailing our latest messaging, momentum, and product innovations. Highlights include: Even in the most advanced data centers, outdated and inefficient storage management techniques are stifling business innovation. But now you can deploy Oracle’s optimized storage, the industry’s most advanced, easy-to-use, and cost-effective enterprise storage solutions. Learn about the benefits of Oracle’s latest storage innovations, including: How you can take on the biggest enterprise storage infrastructure challenges—including reducing costs and increasing data management efficiency A deep-dive discussion into Oracle’s storage innovations, featuring the leaders of Oracle’s storage development organizations A first look at Oracle’s newest scalable storage solution for midsize businesses Join Mark Hurd and John Fowler for this important online launch event. Register NOW

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  • PHP File Downloading Questions

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

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  • Using Multiple File Handles for Single File

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

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  • what do you use for storage discovery / storage management?

    - by lysdexic
    I am looking for some ideas on what would be the best way to discover and manage network storage. Discovery: Any good tools that will scan hosts and storage devices and report back their findings? Maybe using SNMP or WMI? Management: I'm currently looking at Storage Manager by Solar Winds, but it is a bit pricey. Any good open source projects like this? Just looking for ideas of how to get better visibility into the storage infrastructure on this network. It includes a HP Lefthand Iscsi san and EC VNX san. As well as individual hosts with local storage. Thanks for reading and thanks for any input.

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  • Azure - Part 4 - Table Storage Service in Windows Azure

    - by Shaun
    In Windows Azure platform there are 3 storage we can use to save our data on the cloud. They are the Table, Blob and Queue. Before the Chinese New Year Microsoft announced that Azure SDK 1.1 had been released and it supports a new type of storage – Drive, which allows us to operate NTFS files on the cloud. I will cover it in the coming few posts but now I would like to talk a bit about the Table Storage.   Concept of Table Storage Service The most common development scenario is to retrieve, create, update and remove data from the data storage. In the normal way we communicate with database. When we attempt to move our application over to the cloud the most common requirement should be have a storage service. Windows Azure provides a in-build service that allow us to storage the structured data, which is called Windows Azure Table Storage Service. The data stored in the table service are like the collection of entities. And the entities are similar to rows or records in the tradtional database. An entity should had a partition key, a row key, a timestamp and set of properties. You can treat the partition key as a group name, the row key as a primary key and the timestamp as the identifer for solving the concurrency problem. Different with a table in a database, the table service does not enforce the schema for tables, which means you can have 2 entities in the same table with different property sets. The partition key is being used for the load balance of the Azure OS and the group entity transaction. As you know in the cloud you will never know which machine is hosting your application and your data. It could be moving based on the transaction weight and the number of the requests. If the Azure OS found that there are many requests connect to your Book entities with the partition key equals “Novel” it will move them to another idle machine to increase the performance. So when choosing the partition key for your entities you need to make sure they indecate the category or gourp information so that the Azure OS can perform the load balance as you wish.   Consuming the Table Although the table service looks like a database, you cannot access it through the way you are using now, neither ADO.NET nor ODBC. The table service exposed itself by ADO.NET Data Service protocol, which allows you can consume it through the RESTful style by Http requests. The Azure SDK provides a sets of classes for us to connect it. There are 2 classes we might need: TableServiceContext and TableServiceEntity. The TableServiceContext inherited from the DataServiceContext, which represents the runtime context of the ADO.NET data service. It provides 4 methods mainly used by us: CreateQuery: It will create a IQueryable instance from a given type of entity. AddObject: Add the specified entity into Table Service. UpdateObject: Update an existing entity in the Table Service. DeleteObject: Delete an entity from the Table Service. Beofre you operate the table service you need to provide the valid account information. It’s something like the connect string of the database but with your account name and the account key when you created the storage service on the Windows Azure Development Portal. After getting the CloudStorageAccount you can create the CloudTableClient instance which provides a set of methods for using the table service. A very useful method would be CreateTableIfNotExist. It will create the table container for you if it’s not exsited. And then you can operate the eneities to that table through the methods I mentioned above. Let me explain a bit more through an exmaple. We always like code rather than sentence.   Straightforward Accessing to the Table Here I would like to build a WCF service on the Windows Azure platform, and for now just one requirement: it would allow the client to create an account entity on the table service. The WCF service would have a method named Register and accept an instance of the account which the client wants to create. After perform some validation it will add the entity into the table service. So the first thing I should do is to create a Cloud Application on my VIstial Studio 2010 RC. (The Azure SDK 1.1 only supports VS2008 and VS2010 RC.) The solution should be like this below. Then I added a configuration items for the storage account through the Settings section under the cloud project. (Double click the Services file under Roles folder and navigate to the Setting section.) This setting will be used when to retrieve my storage account information. Since for now I just in the development phase I will select “UseDevelopmentStorage=true”. And then I navigated to the WebRole.cs file under my WCF project. If you have read my previous posts you would know that this file defines the process when the application start, and terminate on the cloud. What I need to do is to when the application start, set the configuration publisher to load my config file with the config name I specified. So the code would be like below. I removed the original service and contract created by the VS template and add my IAccountService contract and its implementation class - AccountService. And I add the service method Register with the parameters: email, password and it will return a boolean value to indicates the result which is very simple. At this moment if I press F5 the application will be established on my local development fabric and I can see my service runs well through the browser. Let’s implement the service method Rigister, add a new entity to the table service. As I said before the entities you want to store in the table service must have 3 properties: partition key, row key and timespan. You can create a class with these 3 properties. The Azure SDK provides us a base class for that named TableServiceEntity in Microsoft.WindowsAzure.StorageClient namespace. So what we need to do is more simply, create a class named Account and let it derived from the TableServiceEntity. And I need to add my own properties: Email, Password, DateCreated and DateDeleted. The DateDeleted is a nullable date time value to indecate whether this entity had been deleted and when. Do you notice that I missed something here? Yes it’s the partition key and row key I didn’t assigned. The TableServiceEntity base class defined 2 constructors one was a parameter-less constructor which will be used to fill values into the properties from the table service when retrieving data. The other was one with 2 parameters: partition key and row key. As I said below the partition key may affect the load balance and the row key must be unique so here I would like to use the email as the parition key and the email plus a Guid as the row key. OK now we finished the entity class we need to store onto the table service. The next step is to create a data access class for us to add it. Azure SDK gives us a base class for it named TableServiceContext as I mentioned below. So let’s create a class for operate the Account entities. The TableServiceContext need the storage account information for its constructor. It’s the combination of the storage service URI that we will create on Windows Azure platform, and the relevant account name and key. The TableServiceContext will use this information to find the related address and verify the account to operate the storage entities. Hence in my AccountDataContext class I need to override this constructor and pass the storage account into it. All entities will be saved in the table storage with one or many tables which we call them “table containers”. Before we operate an entity we need to make sure that the table container had been created on the storage. There’s a method we can use for that: CloudTableClient.CreateTableIfNotExist. So in the constructor I will perform it firstly to make sure all method will be invoked after the table had been created. Notice that I passed the storage account enpoint URI and the credentials to specify where my storage is located and who am I. Another advise is that, make your entity class name as the same as the table name when create the table. It will increase the performance when you operate it over the cloud especially querying. Since the Register WCF method will add a new account into the table service, here I will create a relevant method to add the account entity. Before implement, I should add a reference - System.Data.Services.Client to the project. This reference provides some common method within the ADO.NET Data Service which can be used in the Windows Azure Table Service. I will use its AddObject method to create my account entity. Since the table service are not fully implemented the ADO.NET Data Service, there are some methods in the System.Data.Services.Client that TableServiceContext doesn’t support, such as AddLinks, etc. Then I implemented the serivce method to add the account entity through the AccountDataContext. You can see in the service implmentation I load the storage account information through my configuration file and created the account table entity from the parameters. Then I created the AccountDataContext. If it’s my first time to invoke this method the constructor of the AccountDataContext will create a table container for me. Then I use Add method to add the account entity into the table. Next, let’s create a farely simple client application to test this service. I created a windows console application and added a service reference to my WCF service. The metadata information of the WCF service cannot be retrieved if it’s deployed on the Windows Azure even though the <serviceMetadata httpGetEnabled="true"/> had been set. If we need to get its metadata we can deploy it on the local development service and then changed the endpoint to the address which is on the cloud. In the client side app.config file I specified the endpoint to the local development fabric address. And the just implement the client to let me input an email and a password then invoke the WCF service to add my acocunt. Let’s run my application and see the result. Of course it should return TRUE to me. And in the local SQL Express I can see the data had been saved in the table.   Summary In this post I explained more about the Windows Azure Table Storage Service. I also created a small application for demostration of how to connect and consume it through the ADO.NET Data Service Managed Library provided within the Azure SDK. I only show how to create an eneity in the storage service. In the next post I would like to explain about how to query the entities with conditions thruogh LINQ. I also would like to refactor my AccountDataContext class to make it dyamic for any kinds of entities.   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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  • 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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  • Home Server: storage virtualisation, what to choose?

    - by Huygens
    I'm looking for virtualisation solutions for storage and OS for a home server. A sort of private cloud where I manage the storage space independently of the VM one. This question focus on storage management. (I have another question related to the VM/compute instance management). Here my environement and wishes. Server: HP Proliant MicroServer with 8 GB RAM (AMD Turion dual core with AMD-V technology) with 1 250GB system disk and up to 4 HDD (2 TB) for "data" OS types: only Linux (perhaps a *BSD VM in the future) Linux distributions do not matter, I'm familiar with RHEL, Fedora, Suse, Ubuntu, but any other recommandation will be fine The 4 HDD is going to be a software RAID array, probably RAID 5. storage should be "virtualised/cloudified": easy to extend: if I add a NAS on the network, I can include the NAS space capacity within this storage space as one virtual disk. This can be a NAS, an external HDD or another server. cluster FS or S3 style space or OpenStack block storage? Whatever is easier to manage/maintain and easy to integrate/plug to VM/compute instance. I would prefer free (libre, as in a free speach) and open source tools. But it does not have to be free as in a free beer. Note: the VMs I intend to run on top of this server are one dedicated to backup, one for a "owncloud/dropbox"-like service and perhaps one for media server (hosting video and photos). I'm not sure if traditional VMs or compute instance are the most suitable for this.

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  • Delphi-5 single-file storage solution?

    - by pastacool
    Hi! Is there a Delphi-5 solution to easily integrate single-file storage into existing code? I would like to have files like Java *.jar or Openoffice document files which are zipped/compressed files and folders but with their own file extension. Edit: I know some ZIP capable components but in a nutshell I want to access files within the "container" and use normal file handling routines on them (eg. TStringList.SaveToFile). Any overhead about compress/uncompress should be handled by the component.

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  • On Server Disk Storage VS SAN Storage

    - by Justin
    Hello, I am looking at buying three servers, and trying to figure out which storage solution makes the most sense in terms of performance and cost. Total budget is around: $10,000. OPTION 1: Dell servers with RAID 10 (4 Drives) each 7200RPM SAS 500GB, for a total capacity of 1TB. Each server is approx: $3000. Total storage then across all three servers is 3TB. OPTION 2: Same Dell servers with a cheap single drive no RAID for $2000 and go with a centralized SAN solution. The biggest problem is that I haven't been able to even find a SAN solution that is a reasonable price. Dell entry level storage servers are like $15,000. I am thinking just iSCSI, not fiber (too expensive). What do you guys recommend?

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  • SIMD Extensions for the Database Storage Engine

    - by jchang
    For the last 15 years, Intel and AMD have been progressively adding special purpose extensions to their processor architectures. The extensions mostly pertain to vector operations with Single Instruction, Multiple Data (SIMD) concept. The reasoning was that achieving significant performance improvement over each successive generation for the general purpose elements had become extraordinarily difficult. On the other hand, SIMD performance could be significantly improved with special purpose registers...(read more)

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  • Off-site Cardholder Data Storage

    - by LinuxGnut
    Is there a service or site out there that will store cardholder data for me? I don't need any kind of transaction processing or recurring billing... I just need somewhere that I can store data on until someone in my company is able to look at it. The specific need is allowing customers to input data that will be used for credit checks. Name, Address, Credit Card(s), and the such. Google Checkout, PayPal, NetSuite, and Authorize.net seem to be what everyone suggests to me, but they don't offer what I need -- they're just payment gateways.

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  • update manager - insufficient storage space (false alarm)

    - by itsols
    I'm trying to run Update Manager but it keeps reporting that there's not enough space. Here's the screenshot: I ran sudo apt-get update && sudo apt-get upgrade from the terminal but still update manager says that there are updates and I cannot seem to get pass this message. I have even removed many programs from my system and there is supposed to be at least 6GB of disk space free. What can I do?

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  • SIMD Extensions for the Database Storage Engine

    - by jchang
    For the last 15 years, Intel and AMD have been progressively adding special purpose extensions to their processor architectures. The extensions mostly pertain to vector operations with Single Instruction, Multiple Data (SIMD) concept. The motivation was that achieving significant performance improvement over each successive generation for the general purpose elements had become extraordinarily difficult. On the other hand, SIMD performance could be significantly improved with special purpose registers...(read more)

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  • USB Storage Device Automount

    - by matto1990
    Under Ubuntu 10.04 one of the problems which appeared is that USB devices would no longer automatically mount when plugged in. Normally I would get a pop up message asking what application I wanted to open the newly plugged in device with, however now that doesn't happen. This happens regardless of the way the device is formatted (NTFS or FAT32) and all other USB devices (printer, keyboard and mouse) work perfectly. My current solution is the mount them manually using sudo mount dev/... /medai/... however to be honest I'm just getting tired of having to do this. I'm happy to post any extra information you are likely to need. I know there will be lots of places I could look to find out what's going wrong but I have no idea where to start really.

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  • Can't access any storage devices on 12.10

    - by Trigger
    Hi I've just started using Ubuntu 12.10 (today!) my first time with any non-windows OS. I wanted to retrieve some files after windows stopped working. I boot Ubuntu from a USB and it seems to work fine - I can access the internet etc. But I can't access any of my drives or even a USB drive. The error I get is "Adding read ACL for uid 999 to `/media/ubuntu' failed: Operation not supported" Any help much appreciated:)

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  • Windows Phone 7 development: Using isolated storage

    - by DigiMortal
    In my previous posting about Windows Phone 7 development I showed how to use WebBrowser control in Windows Phone 7. In this posting I make some other improvements to my blog reader application and I will show you how to use isolated storage to store information to phone. Why isolated storage? Isolated storage is place where your application can save its data and settings. The image on right (that I stole from MSDN library) shows you how application data store is organized. You have no other options to keep your files besides isolated storage because Windows Phone 7 does not allow you to save data directly to other file system locations. From MSDN: “Isolated storage enables managed applications to create and maintain local storage. The mobile architecture is similar to the Silverlight-based applications on Windows. All I/O operations are restricted to isolated storage and do not have direct access to the underlying operating system file system. Ultimately, this helps to provide security and prevents unauthorized access and data corruption.” Saving files from web to isolated storage I updated my RSS-reader so it reads RSS from web only if there in no local file with RSS. User can update RSS-file by clicking a button. Also file is created when application starts and there is no RSS-file. Why I am doing this? I want my application to be able to work also offline. As my code needs some more refactoring I provide it with some next postings about Windows Phone 7. If you want it sooner then please leave me a comment here. Here is the code for my RSS-downloader that downloads RSS-feed and saves it to isolated storage file calles rss.xml. public class RssDownloader {     private string _url;     private string _fileName;       public delegate void DownloadCompleteDelegate();     public event DownloadCompleteDelegate DownloadComplete;       public RssDownloader(string url, string fileName)     {         _url = url;         _fileName = fileName;     }       public void Download()     {         var request = (HttpWebRequest)WebRequest.Create(_url);         var result = (IAsyncResult)request.BeginGetResponse(ResponseCallback, request);            }       private void ResponseCallback(IAsyncResult result)     {         var request = (HttpWebRequest)result.AsyncState;         var response = request.EndGetResponse(result);           using(var stream = response.GetResponseStream())         using(var reader = new StreamReader(stream))         using(var appStorage = IsolatedStorageFile.GetUserStoreForApplication())         using(var file = appStorage.OpenFile("rss.xml", FileMode.OpenOrCreate))         using(var writer = new StreamWriter(file))         {             writer.Write(reader.ReadToEnd());         }           if (DownloadComplete != null)             DownloadComplete();     } } Of course I modified RSS-source for my application to use rss.xml file from isolated storage. As isolated storage files also base on streams we can use them everywhere where streams are expected. Reading isolated storage files As isolated storage files are opened as streams you can read them like usual files in your usual applications. The next code fragment shows you how to open file from isolated storage and how to read it using XmlReader. Previously I used response stream in same place. using(var appStorage = IsolatedStorageFile.GetUserStoreForApplication()) using(var file = appStorage.OpenFile("rss.xml", FileMode.Open)) {     var reader = XmlReader.Create(file);                      // more code } As you can see there is nothing complex. If you have worked with System.IO namespace objects then you will find isolated storage classes and methods to be very similar to these. Also mention that application storage and isolated storage files must be disposed after you are not using them anymore.

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  • Looking for advice on Hyper-v storage replication

    - by Notre1
    I am designing a 2-host Hyper-V R2 cluster with 6-10 guests stored on a SMB iSCSI SAN device (probably Promise VessRAID). I will be getting at least two of the SAN devices and need to eliminate the storage a single point of failure. Ideally, that would involve real-time failover for the storage, like the Windows failover clustering does for the hosts. This design will be used at around six of our sites, and I would like to allow for us to eventually setup a cluster at colocation site and replicate each site's VMs there for DR. (Ideally a live multi-site cluster, but a manual import of the VMs would be fine for this sort of DR.) The tools that come with enterprise SANs, like EMC and NetApp, seem to be the most commonly used items for a Hyper-V cluster, but I can't afford their prices with my budget. Outside of them, the two tools that seem to be most common for Hyper-V storage replication are SteelEye (now SIOS) DataKeeper Cluster Edition and Double-Take Availability. Originally, I was planning on using Clustered Shared Volume(s) (CSV), but it seems like replication support for these is either not available or brand new in both these products. It looks like CSVs are supported in Double-Take 5.22, see this discussion, but I don't think I want to run something that new in production. Right now, it seems like the best option for me is not to implement CSVs, implement some sort of storage replication, and upgrade to CSVs at a later date once replicating them is more mature. I would love to have live migration, and CSVs are not required for live migration if you are using one LUN per VM, so I guess this is what I'll do. I would prefer to stick to the using the Microsoft Windows Server and Hyper-V tools and features as much as possible. From that standpoint, SteelEye looks more appealing than Double-Take because they make the DataKeeper volume(s) available to the Failover Clustering Manager and then failover clustering is all configured and managed through the native Microsoft tools. Double-Take says that "clustered Hyper-V hosts are not supported," and Double-Take Availability itself seems to be what is used for the actual clustering and failover. Does anyone know if any of these replication tools work with more than two hosts in the cluster? All the information I can find on the web only uses two hosts in their examples. Are there any better tools than SteelEye and Double-Take for doing what I am trying to do, which is eliminate the storage as as single point of failure? Neverfail, AppAssure, and DataCore all seem to offer similar functionality, but they don't seems to be as popular as SteelEye and Double-Take. I have seen a number of people suggest using Starwind iSCSI SAN software for the shared storage, which includes replication (and CSV replication at that). There are a couple of reasons I have not seriously considered this route: 1) The company I work for is exclusively a Dell shop and Dell does not have any servers with that I can pack with more than six 3.5" SATA drives. 2) In the future, it could be advantegous for us to not be locked into a particular brand or type of storage and third-party replication softwares all allow replication to heterogeneous storage devices. I am pretty new to iSCSI and clustering, so please let me know if it looks like I am planning something that goes against best practices or overlooking/missing something.

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  • Looking for advice on Hyper-v storage replication

    - by Notre1
    I am designing a 2-host Hyper-V R2 cluster with 6-10 guests stored on a SMB iSCSI SAN device (probably Promise VessRAID). I will be getting at least two of the SAN devices and need to eliminate the storage a single point of failure. Ideally, that would involve real-time failover for the storage, like the Windows failover clustering does for the hosts. This design will be used at around six of our sites, and I would like to allow for us to eventually setup a cluster at colocation site and replicate each site's VMs there for DR. (Ideally a live multi-site cluster, but a manual import of the VMs would be fine for this sort of DR.) The tools that come with enterprise SANs, like EMC and NetApp, seem to be the most commonly used items for a Hyper-V cluster, but I can't afford their prices with my budget. Outside of them, the two tools that seem to be most common for Hyper-V storage replication are SteelEye (now SIOS) DataKeeper Cluster Edition and Double-Take Availability. Originally, I was planning on using Clustered Shared Volume(s) (CSV), but it seems like replication support for these is either not available or brand new in both these products. It looks like CSVs are supported in Double-Take 5.22, see this discussion, but I don't think I want to run something that new in production. Right now, it seems like the best option for me is not to implement CSVs, implement some sort of storage replication, and upgrade to CSVs at a later date once replicating them is more mature. I would love to have live migration, and CSVs are not required for live migration if you are using one LUN per VM, so I guess this is what I'll do. I would prefer to stick to the using the Microsoft Windows Server and Hyper-V tools and features as much as possible. From that standpoint, SteelEye looks more appealing than Double-Take because they make the DataKeeper volume(s) available to the Failover Clustering Manager and then failover clustering is all configured and managed through the native Microsoft tools. Double-Take says that "clustered Hyper-V hosts are not supported," and Double-Take Availability itself seems to be what is used for the actual clustering and failover. Does anyone know if any of these replication tools work with more than two hosts in the cluster? All the information I can find on the web only uses two hosts in their examples. Are there any better tools than SteelEye and Double-Take for doing what I am trying to do, which is eliminate the storage as as single point of failure? Neverfail, AppAssure, and DataCore all seem to offer similar functionality, but they don't seems to be as popular as SteelEye and Double-Take. I have seen a number of people suggest using Starwind iSCSI SAN software for the shared storage, which includes replication (and CSV replication at that). There are a couple of reasons I have not seriously considered this route: 1) The company I work for is exclusively a Dell shop and Dell does not have any servers with that I can pack with more than six 3.5" SATA drives. 2) In the future, it could be advantegous for us to not be locked into a particular brand or type of storage and third-party replication softwares all allow replication to heterogeneous storage devices. I am pretty new to iSCSI and clustering, so please let me know if it looks like I am planning something that goes against best practices or overlooking/missing something.

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  • Online file storage similar to Amazon S3

    - 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 RESTful but extras like mkdir and cp (?) 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

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