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  • Linqpad with Table Storage

    - by kaleidoscope
    LinqPad as we all know has been a wonderful tool for running ad-hoc queries. With Azure Table storage in picture LinqPad was no longer in picture and we shifted focus to Cloud Storage Studio only to realize the limited and strange querying capabilities of CSS. With some tweaking to Linqpad we can get the comfortable old shoe of ad-hoc queries with LinqPad in the Azure Table storage. Steps: 1. Start LinqPad 2. Right Click in the query window and select “Query Properties” 3. In The Additional References add reference to Microsoft.WindowsAzure.StorageClient, System.Data.Services.Client.dll and the assembly containing the implementation of the DataServiceContext class tied to the Azure table storage. 4. In the additional namespace imports import the same three namespaces mentioned above. 5. Then we need to provide following details. a. Table storage account name and shared key. b. DataServiceContext implementing class in your code. c. A LINQ query. e.x. var storageAccountName = "myStorageAccount";  // Enter valid storage account name var storageSharedKey = "mysharedKey"; // Enter valid storage account shared key var uri = new System.Uri("http://table.core.windows.net/"); var storageAccountInfo = new CloudStorageAccount(new StorageCredentialsAccountKey(storageAccountName, storageSharedKey), false); var serviceContext = new TweetPollDataServiceContext(storageAccountInfo); // Specify the DataServiceContext implementation // The query var query = from row in serviceContext.Table select row;         query.Dump(); Sarang, K

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  • PARTNER WEBCAST (June 4): Enhance Customer experience with Nimble Storage SmartStack for Oracle with Cisco

    - by Zeynep Koch
    Live Webcast: Enhance Customer experience with Nimble Storage SmartStack for Oracle with Cisco A webcast for resellers who sell Oracle workloads to customers  Wednesday, June 4, 2014, 8:00 AM PDT /11 AM EDT  Register today Nimble Storage SmartStack™ for Oracle provides pre-validated reference architecture that speed deployments and minimize risk.  IT and Oracle administrators and architects realize the importance of underlying Operating System, Virtualization software, and Storage in maintaining services levels and staying in budget.  In this webinar, you will learn how Nimble Storage SmartStack for Oracle provides a converged infrastructure for Oracle database online transaction processing (OLTP) and online analytical processing (OLAP) environments with Oracle Linux and Oracle VM. SmartStack delivers the performance and reliability needed for deploying Oracle on a single symmetric multiprocessing (SMP) server or if you are running Oracle Real Application Clusters (RAC) on multiple nodes. Nimble Storage SmartStack for Oracle with Cisco can help you provide: Improved Oracle performance Stress-free data protection and DR of your Oracle database Higher availability and uptime Accelerate Oracle development and improve testing All for dramatically less than what you’re paying now Presenters: Doan Nguyen, Senior Principal Product Marketing Director, Oracle Vanessa Scott , Business Development Manager, Cisco Ibrahim “Ibby” Rahmani, Product and Solutions Marketing, Nimble Storage Join this event to learn from our Nimble Storage and Oracle experts on how to optimize your customers' Oracle environments. Register today to learn more!

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  • PARTNER WEBCAST (June 4): Enhance Customer experience with Nimble Storage SmartStack for Oracle with Cisco

    - by Zeynep Koch
    Live Webcast: Enhance Customer experience with Nimble Storage SmartStack for Oracle with Cisco A webcast for resellers who sell Oracle workloads to customers  Wednesday, June 4, 2014, 8:00 AM PDT /11 AM EDT  Register today Nimble Storage SmartStack™ for Oracle provides pre-validated reference architecture that speed deployments and minimize risk.  IT and Oracle administrators and architects realize the importance of underlying Operating System, Virtualization software, and Storage in maintaining services levels and staying in budget.  In this webinar, you will learn how Nimble Storage SmartStack for Oracle provides a converged infrastructure for Oracle database online transaction processing (OLTP) and online analytical processing (OLAP) environments with Oracle Linux and Oracle VM. SmartStack delivers the performance and reliability needed for deploying Oracle on a single symmetric multiprocessing (SMP) server or if you are running Oracle Real Application Clusters (RAC) on multiple nodes. Nimble Storage SmartStack for Oracle with Cisco can help you provide: Improved Oracle performance Stress-free data protection and DR of your Oracle database Higher availability and uptime Accelerate Oracle development and improve testing All for dramatically less than what you’re paying now Presenters: Doan Nguyen, Senior Principal Product Marketing Director, Oracle Vanessa Scott , Business Development Manager, Cisco Ibrahim “Ibby” Rahmani, Product and Solutions Marketing, Nimble Storage Join this event to learn from our Nimble Storage and Oracle experts on how to optimize your customers' Oracle environments. Register today to learn more!

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  • Node.js Adventure - Storage Services and Service Runtime

    - by Shaun
    When I described on how to host a Node.js application on Windows Azure, one of questions might be raised about how to consume the vary Windows Azure services, such as the storage, service bus, access control, etc.. Interact with windows azure services is available in Node.js through the Windows Azure Node.js SDK, which is a module available in NPM. In this post I would like to describe on how to use Windows Azure Storage (a.k.a. WAS) as well as the service runtime.   Consume Windows Azure Storage Let’s firstly have a look on how to consume WAS through Node.js. As we know in the previous post we can host Node.js application on Windows Azure Web Site (a.k.a. WAWS) as well as Windows Azure Cloud Service (a.k.a. WACS). In theory, WAWS is also built on top of WACS worker roles with some more features. Hence in this post I will only demonstrate for hosting in WACS worker role. The Node.js code can be used when consuming WAS when hosted on WAWS. But since there’s no roles in WAWS, the code for consuming service runtime mentioned in the next section cannot be used for WAWS node application. We can use the solution that I created in my last post. Alternatively we can create a new windows azure project in Visual Studio with a worker role, add the “node.exe” and “index.js” and install “express” and “node-sqlserver” modules, make all files as “Copy always”. In order to use windows azure services we need to have Windows Azure Node.js SDK, as knows as a module named “azure” which can be installed through NPM. Once we downloaded and installed, we need to include them in our worker role project and make them as “Copy always”. You can use my “Copy all always” tool mentioned in my last post to update the currently worker role project file. You can also find the source code of this tool here. The source code of Windows Azure SDK for Node.js can be found in its GitHub page. It contains two parts. One is a CLI tool which provides a cross platform command line package for Mac and Linux to manage WAWS and Windows Azure Virtual Machines (a.k.a. WAVM). The other is a library for managing and consuming vary windows azure services includes tables, blobs, queues, service bus and the service runtime. I will not cover all of them but will only demonstrate on how to use tables and service runtime information in this post. You can find the full document of this SDK here. Back to Visual Studio and open the “index.js”, let’s continue our application from the last post, which was working against Windows Azure SQL Database (a.k.a. WASD). The code should looks like this. 1: var express = require("express"); 2: var sql = require("node-sqlserver"); 3:  4: var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd={PASSWORD};Encrypt=yes;Connection Timeout=30;"; 5: var port = 80; 6:  7: var app = express(); 8:  9: app.configure(function () { 10: app.use(express.bodyParser()); 11: }); 12:  13: app.get("/", function (req, res) { 14: sql.open(connectionString, function (err, conn) { 15: if (err) { 16: console.log(err); 17: res.send(500, "Cannot open connection."); 18: } 19: else { 20: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 21: if (err) { 22: console.log(err); 23: res.send(500, "Cannot retrieve records."); 24: } 25: else { 26: res.json(results); 27: } 28: }); 29: } 30: }); 31: }); 32:  33: app.get("/text/:key/:culture", function (req, res) { 34: sql.open(connectionString, function (err, conn) { 35: if (err) { 36: console.log(err); 37: res.send(500, "Cannot open connection."); 38: } 39: else { 40: var key = req.params.key; 41: var culture = req.params.culture; 42: var command = "SELECT * FROM [Resource] WHERE [Key] = '" + key + "' AND [Culture] = '" + culture + "'"; 43: conn.queryRaw(command, function (err, results) { 44: if (err) { 45: console.log(err); 46: res.send(500, "Cannot retrieve records."); 47: } 48: else { 49: res.json(results); 50: } 51: }); 52: } 53: }); 54: }); 55:  56: app.get("/sproc/:key/:culture", function (req, res) { 57: sql.open(connectionString, function (err, conn) { 58: if (err) { 59: console.log(err); 60: res.send(500, "Cannot open connection."); 61: } 62: else { 63: var key = req.params.key; 64: var culture = req.params.culture; 65: var command = "EXEC GetItem '" + key + "', '" + culture + "'"; 66: conn.queryRaw(command, function (err, results) { 67: if (err) { 68: console.log(err); 69: res.send(500, "Cannot retrieve records."); 70: } 71: else { 72: res.json(results); 73: } 74: }); 75: } 76: }); 77: }); 78:  79: app.post("/new", function (req, res) { 80: var key = req.body.key; 81: var culture = req.body.culture; 82: var val = req.body.val; 83:  84: sql.open(connectionString, function (err, conn) { 85: if (err) { 86: console.log(err); 87: res.send(500, "Cannot open connection."); 88: } 89: else { 90: var command = "INSERT INTO [Resource] VALUES ('" + key + "', '" + culture + "', N'" + val + "')"; 91: conn.queryRaw(command, function (err, results) { 92: if (err) { 93: console.log(err); 94: res.send(500, "Cannot retrieve records."); 95: } 96: else { 97: res.send(200, "Inserted Successful"); 98: } 99: }); 100: } 101: }); 102: }); 103:  104: app.listen(port); Now let’s create a new function, copy the records from WASD to table service. 1. Delete the table named “resource”. 2. Create a new table named “resource”. These 2 steps ensures that we have an empty table. 3. Load all records from the “resource” table in WASD. 4. For each records loaded from WASD, insert them into the table one by one. 5. Prompt to user when finished. In order to use table service we need the storage account and key, which can be found from the developer portal. Just select the storage account and click the Manage Keys button. Then create two local variants in our Node.js application for the storage account name and key. Since we need to use WAS we need to import the azure module. Also I created another variant stored the table name. In order to work with table service I need to create the storage client for table service. This is very similar as the Windows Azure SDK for .NET. As the code below I created a new variant named “client” and use “createTableService”, specified my storage account name and key. 1: var azure = require("azure"); 2: var storageAccountName = "synctile"; 3: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 4: var tableName = "resource"; 5: var client = azure.createTableService(storageAccountName, storageAccountKey); Now create a new function for URL “/was/init” so that we can trigger it through browser. Then in this function we will firstly load all records from WASD. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: } 18: } 19: }); 20: } 21: }); 22: }); When we succeed loaded all records we can start to transform them into table service. First I need to recreate the table in table service. This can be done by deleting and creating the table through table client I had just created previously. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: } 27: }); 28: }); 29: } 30: } 31: }); 32: } 33: }); 34: }); As you can see, the azure SDK provide its methods in callback pattern. In fact, almost all modules in Node.js use the callback pattern. For example, when I deleted a table I invoked “deleteTable” method, provided the name of the table and a callback function which will be performed when the table had been deleted or failed. Underlying, the azure module will perform the table deletion operation in POSIX async threads pool asynchronously. And once it’s done the callback function will be performed. This is the reason we need to nest the table creation code inside the deletion function. If we perform the table creation code after the deletion code then they will be invoked in parallel. Next, for each records in WASD I created an entity and then insert into the table service. Finally I send the response to the browser. Can you find a bug in the code below? I will describe it later in this post. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: // transform the records 26: for (var i = 0; i < results.rows.length; i++) { 27: var entity = { 28: "PartitionKey": results.rows[i][1], 29: "RowKey": results.rows[i][0], 30: "Value": results.rows[i][2] 31: }; 32: client.insertEntity(tableName, entity, function (error) { 33: if (error) { 34: error["target"] = "insertEntity"; 35: res.send(500, error); 36: } 37: else { 38: console.log("entity inserted"); 39: } 40: }); 41: } 42: // send the 43: console.log("all done"); 44: res.send(200, "All done!"); 45: } 46: }); 47: }); 48: } 49: } 50: }); 51: } 52: }); 53: }); Now we can publish it to the cloud and have a try. But normally we’d better test it at the local emulator first. In Node.js SDK there are three build-in properties which provides the account name, key and host address for local storage emulator. We can use them to initialize our table service client. We also need to change the SQL connection string to let it use my local database. The code will be changed as below. 1: // windows azure sql database 2: //var connectionString = "Driver={SQL Server Native Client 10.0};Server=tcp:ac6271ya9e.database.windows.net,1433;Database=synctile;Uid=shaunxu@ac6271ya9e;Pwd=eszqu94XZY;Encrypt=yes;Connection Timeout=30;"; 3: // sql server 4: var connectionString = "Driver={SQL Server Native Client 11.0};Server={.};Database={Caspar};Trusted_Connection={Yes};"; 5:  6: var azure = require("azure"); 7: var storageAccountName = "synctile"; 8: var storageAccountKey = "/cOy9L7xysXOgPYU9FjDvjrRAhaMX/5tnOpcjqloPNDJYucbgTy7MOrAW7CbUg6PjaDdmyl+6pkwUnKETsPVNw=="; 9: var tableName = "resource"; 10: // windows azure storage 11: //var client = azure.createTableService(storageAccountName, storageAccountKey); 12: // local storage emulator 13: var client = azure.createTableService(azure.ServiceClient.DEVSTORE_STORAGE_ACCOUNT, azure.ServiceClient.DEVSTORE_STORAGE_ACCESS_KEY, azure.ServiceClient.DEVSTORE_TABLE_HOST); Now let’s run the application and navigate to “localhost:12345/was/init” as I hosted it on port 12345. We can find it transformed the data from my local database to local table service. Everything looks fine. But there is a bug in my code. If we have a look on the Node.js command window we will find that it sent response before all records had been inserted, which is not what I expected. The reason is that, as I mentioned before, Node.js perform all IO operations in non-blocking model. When we inserted the records we executed the table service insert method in parallel, and the operation of sending response was also executed in parallel, even though I wrote it at the end of my logic. The correct logic should be, when all entities had been copied to table service with no error, then I will send response to the browser, otherwise I should send error message to the browser. To do so I need to import another module named “async”, which helps us to coordinate our asynchronous code. Install the module and import it at the beginning of the code. Then we can use its “forEach” method for the asynchronous code of inserting table entities. The first argument of “forEach” is the array that will be performed. The second argument is the operation for each items in the array. And the third argument will be invoked then all items had been performed or any errors occurred. Here we can send our response to browser. 1: app.get("/was/init", function (req, res) { 2: // load all records from windows azure sql database 3: sql.open(connectionString, function (err, conn) { 4: if (err) { 5: console.log(err); 6: res.send(500, "Cannot open connection."); 7: } 8: else { 9: conn.queryRaw("SELECT * FROM [Resource]", function (err, results) { 10: if (err) { 11: console.log(err); 12: res.send(500, "Cannot retrieve records."); 13: } 14: else { 15: if (results.rows.length > 0) { 16: // begin to transform the records into table service 17: // recreate the table named 'resource' 18: client.deleteTable(tableName, function (error) { 19: client.createTableIfNotExists(tableName, function (error) { 20: if (error) { 21: error["target"] = "createTableIfNotExists"; 22: res.send(500, error); 23: } 24: else { 25: async.forEach(results.rows, 26: // transform the records 27: function (row, callback) { 28: var entity = { 29: "PartitionKey": row[1], 30: "RowKey": row[0], 31: "Value": row[2] 32: }; 33: client.insertEntity(tableName, entity, function (error) { 34: if (error) { 35: callback(error); 36: } 37: else { 38: console.log("entity inserted."); 39: callback(null); 40: } 41: }); 42: }, 43: // send reponse 44: function (error) { 45: if (error) { 46: error["target"] = "insertEntity"; 47: res.send(500, error); 48: } 49: else { 50: console.log("all done"); 51: res.send(200, "All done!"); 52: } 53: } 54: ); 55: } 56: }); 57: }); 58: } 59: } 60: }); 61: } 62: }); 63: }); Run it locally and now we can find the response was sent after all entities had been inserted. Query entities against table service is simple as well. Just use the “queryEntity” method from the table service client and providing the partition key and row key. We can also provide a complex query criteria as well, for example the code here. In the code below I queried an entity by the partition key and row key, and return the proper localization value in response. 1: app.get("/was/:key/:culture", function (req, res) { 2: var key = req.params.key; 3: var culture = req.params.culture; 4: client.queryEntity(tableName, culture, key, function (error, entity) { 5: if (error) { 6: res.send(500, error); 7: } 8: else { 9: res.json(entity); 10: } 11: }); 12: }); And then tested it on local emulator. Finally if we want to publish this application to the cloud we should change the database connection string and storage account. For more information about how to consume blob and queue service, as well as the service bus please refer to the MSDN page.   Consume Service Runtime As I mentioned above, before we published our application to the cloud we need to change the connection string and account information in our code. But if you had played with WACS you should have known that the service runtime provides the ability to retrieve configuration settings, endpoints and local resource information at runtime. Which means we can have these values defined in CSCFG and CSDEF files and then the runtime should be able to retrieve the proper values. For example we can add some role settings though the property window of the role, specify the connection string and storage account for cloud and local. And the can also use the endpoint which defined in role environment to our Node.js application. In Node.js SDK we can get an object from “azure.RoleEnvironment”, which provides the functionalities to retrieve the configuration settings and endpoints, etc.. In the code below I defined the connection string variants and then use the SDK to retrieve and initialize the table client. 1: var connectionString = ""; 2: var storageAccountName = ""; 3: var storageAccountKey = ""; 4: var tableName = ""; 5: var client; 6:  7: azure.RoleEnvironment.getConfigurationSettings(function (error, settings) { 8: if (error) { 9: console.log("ERROR: getConfigurationSettings"); 10: console.log(JSON.stringify(error)); 11: } 12: else { 13: console.log(JSON.stringify(settings)); 14: connectionString = settings["SqlConnectionString"]; 15: storageAccountName = settings["StorageAccountName"]; 16: storageAccountKey = settings["StorageAccountKey"]; 17: tableName = settings["TableName"]; 18:  19: console.log("connectionString = %s", connectionString); 20: console.log("storageAccountName = %s", storageAccountName); 21: console.log("storageAccountKey = %s", storageAccountKey); 22: console.log("tableName = %s", tableName); 23:  24: client = azure.createTableService(storageAccountName, storageAccountKey); 25: } 26: }); In this way we don’t need to amend the code for the configurations between local and cloud environment since the service runtime will take care of it. At the end of the code we will listen the application on the port retrieved from SDK as well. 1: azure.RoleEnvironment.getCurrentRoleInstance(function (error, instance) { 2: if (error) { 3: console.log("ERROR: getCurrentRoleInstance"); 4: console.log(JSON.stringify(error)); 5: } 6: else { 7: console.log(JSON.stringify(instance)); 8: if (instance["endpoints"] && instance["endpoints"]["nodejs"]) { 9: var endpoint = instance["endpoints"]["nodejs"]; 10: app.listen(endpoint["port"]); 11: } 12: else { 13: app.listen(8080); 14: } 15: } 16: }); But if we tested the application right now we will find that it cannot retrieve any values from service runtime. This is because by default, the entry point of this role was defined to the worker role class. In windows azure environment the service runtime will open a named pipeline to the entry point instance, so that it can connect to the runtime and retrieve values. But in this case, since the entry point was worker role and the Node.js was opened inside the role, the named pipeline was established between our worker role class and service runtime, so our Node.js application cannot use it. To fix this problem we need to open the CSDEF file under the azure project, add a new element named Runtime. Then add an element named EntryPoint which specify the Node.js command line. So that the Node.js application will have the connection to service runtime, then it’s able to read the configurations. Start the Node.js at local emulator we can find it retrieved the connections, storage account for local. And if we publish our application to azure then it works with WASD and storage service through the configurations for cloud.   Summary In this post I demonstrated how to use Windows Azure SDK for Node.js to interact with storage service, especially the table service. I also demonstrated on how to use WACS service runtime, how to retrieve the configuration settings and the endpoint information. And in order to make the service runtime available to my Node.js application I need to create an entry point element in CSDEF file and set “node.exe” as the entry point. I used five posts to introduce and demonstrate on how to run a Node.js application on Windows platform, how to use Windows Azure Web Site and Windows Azure Cloud Service worker role to host our Node.js application. I also described how to work with other services provided by Windows Azure platform through Windows Azure SDK for Node.js. Node.js is a very new and young network application platform. But since it’s very simple and easy to learn and deploy, as well as, it utilizes single thread non-blocking IO model, Node.js became more and more popular on web application and web service development especially for those IO sensitive projects. And as Node.js is very good at scaling-out, it’s more useful on cloud computing platform. Use Node.js on Windows platform is new, too. The modules for SQL database and Windows Azure SDK are still under development and enhancement. It doesn’t support SQL parameter in “node-sqlserver”. It does support using storage connection string to create the storage client in “azure”. But Microsoft is working on make them easier to use, working on add more features and functionalities.   PS, you can download the source code here. You can download the source code of my “Copy all always” tool here.   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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  • USB drives not recognized all of a sudden

    - by Siddharth
    I have tried most of the advice on askubuntu and other sites, usb_storage enable to fdisk -l. But I am unable to find steps to get it working again. lsusb results Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub Bus 002 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 003 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 004 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 005 Device 001: ID 1d6b:0001 Linux Foundation 1.1 root hub Bus 004 Device 002: ID 413c:3012 Dell Computer Corp. Optical Wheel Mouse Bus 005 Device 002: ID 413c:2105 Dell Computer Corp. Model L100 Keyboard Bus 001 Device 005: ID 8564:1000 dmseg | tail reports [ 69.567948] usb 1-4: USB disconnect, device number 4 [ 74.084041] usb 1-6: new high-speed USB device number 5 using ehci_hcd [ 74.240484] Initializing USB Mass Storage driver... [ 74.256033] scsi5 : usb-storage 1-6:1.0 [ 74.256145] usbcore: registered new interface driver usb-storage [ 74.256147] USB Mass Storage support registered. [ 74.257290] usbcore: deregistering interface driver usb-storage fdisk -l reports Device Boot Start End Blocks Id System /dev/sda1 * 2048 972656639 486327296 83 Linux /dev/sda2 972658686 976771071 2056193 5 Extended /dev/sda5 972658688 976771071 2056192 82 Linux swap / Solaris I think I need steps to install and get usb_storage module working. Edit : I tried sudo modprobe -v usb-storage reports sudo modprobe -v usb-storage insmod /lib/modules/3.2.0-48-generic-pae/kernel/drivers/usb/storage/usb-storage.ko Still no usb driver mounted. Nor does a device show up in /dev. Any step by step process to debug and fix this will be really helpful. Thanks.

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  • Intel Rapid Storage Technology (pre-OS) driver installation

    - by Nero theZero
    My desktop machine is built on Gigabyte GA-Z87-UD3H and Gigabyte provides the latest driver for Intel Rapid Storage Technology (IRST), which I installed after installing the OS. Same goes for my Lenovo Thinkpad-T420. And for both machine, checking the controller device under the IDE ATA/ATAPI Controllers section in Device Manager I see the driver has been updated to the latest version. I set the SATA controller to AHCI from BIOS On the desktop machine I have one WD 2TB BLACK & one WD 3TB Green I don’t use RAID, & no chance of using in near future, but according to Intel IRST improves performance in single disk scenario too. Now I have the following questions – What is the actual purpose of IRST (pre-OS install) driver that doesn’t get served with a post-OS driver that I installed? There must be some difference, otherwise there wouldn’t be a pre-OS version of the driver. Right? In the pre-OS procedure (loading the drivers at OS-installation time) after successfully completing the OS installation, do I need that post-OS driver? Because after installing from that one I got a quick launch icon that runs the IRST configuration application. Where do get that after installing the pre-OS driver? As it is “pre-OS”, when I load it at OS-installation time, does it updates anything at BIOS level or anywhere other than HDD? That’s because I’m going to dual boot Windows 7 with Windows 8.1, and after installing Windows 7 when I install Windows 8.1 & load the IRST driver for that, is there any chance of any “overwriting” or OS-incompatibility? In short, is there anything specific to follow while installing the second OS?

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  • Is basing storage requirements based on IOPS sufficient?

    - by Boden
    The current system in question is running SBS 2003, and is going to be migrated on new hardware to SBS 2008. Currently I'm seeing on average 200-300 disk transfers per second total across all the arrays in the system. The array seeing the bulk of activity is a 6 disk 7200RPM RAID 6 and it struggles to keep up during high traffic times (idle time often only 10-20%; response times peaking 20-50+ ms). Based on some rough calculations this makes sense (avg ~245 IOPS on this array at 70/30 read to write ratio). I'm considering using a much simpler disk configuration using a single RAID 10 array of 10K disks. Using the same parameters for my calculations above, I'm getting 583 average random IOPS / sec. Granted SBS 2008 is not the same beast as 2003, but I'd like to make the assumption that it'll be similar in terms of disk performance, if not better (Exchange 2007 is easier on the disk and there's no ISA server). Am I correct in believing that the proposed system will be sufficient in terms of performance, or am I missing something? I've read so much about recommended disk configurations for various products like Exchange, and they often mention things like dedicating spindles to logs, etc. I understand the reasoning behind this, but if I've got more than enough random I/O overhead, does it really matter? I've always at the very least had separate spindles for the OS, but I could really reduce cost and complexity if I just had a single, good performing array. So as not to make you guys do my job for me, the generic version of this question is: if I have a projected IOPS figure for a new system, is it sufficient to use this value alone to spec the storage, ignoring "best practice" configurations? (given similar technology, not going from DAS to SAN or anything)

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  • Enterprise class storage best practices

    - by churnd
    One thing that has always perplexed me is storage best practices. Filesystems brag about how they can be petabytes or exabytes in size. Yet, I do not know many sysadmins who are willing to let a single volume grow over several terrabytes. I do know the primary reason behind this is how long it would take to rebuild the array should a drive fail. The more drives in a single LUN, the longer this takes and the greater your risk of losing another drive while the rebuild is taking place. Then there's usage reasons. Admins will carve out a LUN based on how much space they think needs to be allocated to the project. It seems more practical to me for the LUN to be one large array and to use quotas. I understand this wouldn't satisfy every requirement (iSCSI), but I see a lot of NAS systems (NFS) managed this way. I also understand that the underlying volumes can be grown/shrunk as needed quite easily, but wouldn't it be less "risky" to use quotas rather than manipulating volumes and bringing possible data loss into the equation? There may be some other reasons I'm missing, so please enlighten me. Can we not expect filesystems to ever be so large? Are we waiting for the hardware to get faster to cut down on rebuild times?

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  • How to diagnose storage system scaling problems?

    - by Unknown
    We are currently testing the maximum sequential read throughput of a storage system (48 disks total behind two HP P2000 arrays) connected to HP DL580 G7 running RHEL 5 with 128 GB of memory. Initial testing has been mainly done by running DD-commands like this: dd if=/dev/mapper/mpath1 of=/dev/null bs=1M count=3000 In parallel for each disk. However, we have been unable to scale the results from one array (maximum throughput of 1.3 GB/s) to two (almost the same throughput). Each array is connected to a dedicated host bust adapter, so they should not be the bottleneck. The disks are currently in JBOD configuration, so each disk can be addressed directly. I have two questions: Is running multiple DD commands in parallel really a good way to test maximum read throughput? We have noticed very high SWAPIN-% numbers in iotop, which I find hard to explain because the target is /dev/null How shoud we proceed in trying to find the reason for the scaling problem? Do you thing the server itself is the bottleneck here, or could there be some linux parameters that we have overlooked?

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  • Coronal Mass Ejection Video Captures Stunning Views of the Sun’s Surface

    - by Jason Fitzpatrick
    This beautiful HD video, courtesy of NASA, captures the Sun’s August 31st Coronal Mass Ejection with multiple angles and techniques–the surface of the Sun can be quite a turbulent place. [via Boing Boing] HTG Explains: What The Windows Event Viewer Is and How You Can Use It HTG Explains: How Windows Uses The Task Scheduler for System Tasks HTG Explains: Why Do Hard Drives Show the Wrong Capacity in Windows?

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  • Thread-local storage segfaults on NetBSD only?

    - by bortzmeyer
    Trying to run a C++ program, I get segmentation faults which appear to be specific to NetBSD. Bert Hubert wrote the simple test program (at the end of this message) and, indeed, it crashes only on NetBSD. % uname -a NetBSD golgoth 5.0.1 NetBSD 5.0.1 (GENERIC) #0: Thu Oct 1 15:46:16 CEST 2009 +stephane@golgoth:/usr/obj/sys/arch/i386/compile/GENERIC i386 % g++ --version g++ (GCC) 4.1.3 20080704 prerelease (NetBSD nb2 20081120) Copyright (C) 2006 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. % gdb thread-local-storage-powerdns GNU gdb 6.5 Copyright (C) 2006 Free Software Foundation, Inc. GDB is free software, covered by the GNU General Public License, and you are welcome to change it and/or distribute copies of it under certain conditions. Type "show copying" to see the conditions. There is absolutely no warranty for GDB. Type "show warranty" for details. This GDB was configured as "i386--netbsdelf"... (gdb) run Starting program: /home/stephane/Programmation/C++/essais/thread-local-storage-powerdns Program received signal SIGSEGV, Segmentation fault. 0x0804881b in main () at thread-local-storage-powerdns.cc:20 20 t_a = new Bogo('a'); (gdb) On other Unix, it works fine. Is there a known issue in NetBSD with C++ thread-local storage? #include <stdio.h> class Bogo { public: explicit Bogo(char a) { d_a = a; } char d_a; }; __thread Bogo* t_a; int main() { t_a = new Bogo('a'); Bogo* b = t_a; printf("%c\n", b->d_a); }

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  • Google I/O 2010 - Google Storage for Developers

    Google I/O 2010 - Google Storage for Developers Google I/O 2010 - Google Storage for Developers App Engine, Enterprise 101 David Erb, Michael Schwartz Google is expanding our storage products by introducing Google Storage for Developers. It offers a RESTful API for storing and accessing data at Google. Developers can take advantage of the performance and reliability of Google's storage infrastructure, as well as the advanced security and sharing capabilities. We will demonstrate key functionality of the product as well as customer use cases. For all I/O 2010 sessions, please go to code.google.com From: GoogleDevelopers Views: 13 0 ratings Time: 52:14 More in Science & Technology

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  • The Shift: how Orchard painlessly shifted to document storage, and how it’ll affect you

    - by Bertrand Le Roy
    We’ve known it all along. The storage for Orchard content items would be much more efficient using a document database than a relational one. Orchard content items are composed of parts that serialize naturally into infoset kinds of documents. Storing them as relational data like we’ve done so far was unnatural and requires the data for a single item to span multiple tables, related through 1-1 relationships. This means lots of joins in queries, and a great potential for Select N+1 problems. Document databases, unfortunately, are still a tough sell in many places that prefer the more familiar relational model. Being able to x-copy Orchard to hosters has also been a basic constraint in the design of Orchard. Combine those with the necessity at the time to run in medium trust, and with license compatibility issues, and you’ll find yourself with very few reasonable choices. So we went, a little reluctantly, for relational SQL stores, with the dream of one day transitioning to document storage. We have played for a while with the idea of building our own document storage on top of SQL databases, and Sébastien implemented something more than decent along those lines, but we had a better way all along that we didn’t notice until recently… In Orchard, there are fields, which are named properties that you can add dynamically to a content part. Because they are so dynamic, we have been storing them as XML into a column on the main content item table. This infoset storage and its associated API are fairly generic, but were only used for fields. The breakthrough was when Sébastien realized how this existing storage could give us the advantages of document storage with minimal changes, while continuing to use relational databases as the substrate. public bool CommercialPrices { get { return this.Retrieve(p => p.CommercialPrices); } set { this.Store(p => p.CommercialPrices, value); } } This code is very compact and efficient because the API can infer from the expression what the type and name of the property are. It is then able to do the proper conversions for you. For this code to work in a content part, there is no need for a record at all. This is particularly nice for site settings: one query on one table and you get everything you need. This shows how the existing infoset solves the data storage problem, but you still need to query. Well, for those properties that need to be filtered and sorted on, you can still use the current record-based relational system. This of course continues to work. We do however provide APIs that make it trivial to store into both record properties and the infoset storage in one operation: public double Price { get { return Retrieve(r => r.Price); } set { Store(r => r.Price, value); } } This code looks strikingly similar to the non-record case above. The difference is that it will manage both the infoset and the record-based storages. The call to the Store method will send the data in both places, keeping them in sync. The call to the Retrieve method does something even cooler: if the property you’re looking for exists in the infoset, it will return it, but if it doesn’t, it will automatically look into the record for it. And if that wasn’t cool enough, it will take that value from the record and store it into the infoset for the next time it’s required. This means that your data will start automagically migrating to infoset storage just by virtue of using the code above instead of the usual: public double Price { get { return Record.Price; } set { Record.Price = value; } } As your users browse the site, it will get faster and faster as Select N+1 issues will optimize themselves away. If you preferred, you could still have explicit migration code, but it really shouldn’t be necessary most of the time. If you do already have code using QueryHints to mitigate Select N+1 issues, you might want to reconsider those, as with the new system, you’ll want to avoid joins that you don’t need for filtering or sorting, further optimizing your queries. There are some rare cases where the storage of the property must be handled differently. Check out this string[] property on SearchSettingsPart for example: public string[] SearchedFields { get { return (Retrieve<string>("SearchedFields") ?? "") .Split(new[] {',', ' '}, StringSplitOptions.RemoveEmptyEntries); } set { Store("SearchedFields", String.Join(", ", value)); } } The array of strings is transformed by the property accessors into and from a comma-separated list stored in a string. The Retrieve and Store overloads used in this case are lower-level versions that explicitly specify the type and name of the attribute to retrieve or store. You may be wondering what this means for code or operations that look directly at the database tables instead of going through the new infoset APIs. Even if there is a record, the infoset version of the property will win if it exists, so it is necessary to keep the infoset up-to-date. It’s not very complicated, but definitely something to keep in mind. Here is what a product record looks like in Nwazet.Commerce for example: And here is the same data in the infoset: The infoset is stored in Orchard_Framework_ContentItemRecord or Orchard_Framework_ContentItemVersionRecord, depending on whether the content type is versionable or not. A good way to find what you’re looking for is to inspect the record table first, as it’s usually easier to read, and then get the item record of the same id. Here is the detailed XML document for this product: <Data> <ProductPart Inventory="40" Price="18" Sku="pi-camera-box" OutOfStockMessage="" AllowBackOrder="false" Weight="0.2" Size="" ShippingCost="null" IsDigital="false" /> <ProductAttributesPart Attributes="" /> <AutoroutePart DisplayAlias="camera-box" /> <TitlePart Title="Nwazet Pi Camera Box" /> <BodyPart Text="[...]" /> <CommonPart CreatedUtc="2013-09-10T00:39:00Z" PublishedUtc="2013-09-14T01:07:47Z" /> </Data> The data is neatly organized under each part. It is easy to see how that document is all you need to know about that content item, all in one table. If you want to modify that data directly in the database, you should be careful to do it in both the record table and the infoset in the content item record. In this configuration, the record is now nothing more than an index, and will only be used for sorting and filtering. Of course, it’s perfectly fine to mix record-backed properties and record-less properties on the same part. It really depends what you think must be sorted and filtered on. In turn, this potentially simplifies migrations considerably. So here it is, the great shift of Orchard to document storage, something that Orchard has been designed for all along, and that we were able to implement with a satisfying and surprising economy of resources. Expect this code to make its way into the 1.8 version of Orchard when that’s available.

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  • [Not in Vermont] IT Jobs: Sharepoint/ASP.NET Dev + Winforms C# Dev in Western Mass

    Two .NET jobs in Western Mass from a recruiter, contact info below Requirement #1: Our client is looking for the best engineers in the world, and then we give them the opportunity to excel. Our light, scrum-based process keeps you focused on delivering functionality that our customers need. We try to do things right (unit tests, continuous builds, bug tracking, etc) and were looking for others who work this way too. Primary Responsibilities Develop SharePoint applications in ASP.NET with a heavy...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Storage subsystem borking after server restart (all on a Parallel SCSI bus)

    - by Dat Chu
    I have a server (with a SCSI HBA) connected to two Promise VTrak M310p RAID enclosure on the same bus. Everything is working fine until I have to restart my server. Once restarted, the server can no longer communicate with the enclosures: lots of read errors and bus resets. I have to turn off both enclosure, then turn off the server, then turn on the enclosure, then turn on the server for things to work. I don't believe this is the normal behavior, what could I be missing?

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  • needing storage integrity (write/read) test - for BASH

    - by Mr. Bash
    In need of shell scripts / bash commands to verify data integrity of local harddrives, usb-drives, etc, ... Like the famous www.heise.de/download/h2testw; or something that is at least common within repositories. (h2testw writes a specific datastring over and over onto the medium, then reads it again to verify if it was written correctly and displays write/read time/speed.) please no dd if=/dev/random of=/dev/sdx bs=1k && dd if=/dev/sdx of=/dev/null bs=1k since it won't verify if everything was written correctly. It is only a test if read/write is successful to the device. So far, I'm not too happy with badblocks -w -v /dev/sdx1 either, since it seems rather slow and I don't know what it exactly writes, and if it considers wear-leveling on flash media. There is also a program named F3 http://oss.digirati.com.br/f3/ that needs to be compiled. Designed after h2testw, the concept sounds interesting, i'd just rather have it as a ready to go bash script.

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  • Windows Storage Server 2008 hangs at logon

    - by ErJab
    We have a Dell PowerVault NX-3000 server running Windows Server 2008. Every now and then, when I try to login, the server seems to hang at the Welcome screen after I type in the password. However, all other services on the server are running fine - users are able to print off the print server and access their files. It just won't let me login. Any idea why this is happening? P.S.: I can't look at the server logs, because it won't let me login in the first place. Remote administration is also disabled on the server, so I can't use Remote Administration tools to look at the logs.

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  • Home media storage solution

    - by Dan
    I record lots of personal HD film footage and am looking for a cheap way to store all of this. I take ~120 GB of footage each month, so something expandable would be nice... something that might be able to hold 6+ SATA drives. There is a low load requirement, as there is never more than a user or two... but it should be able to keep up with streaming 2 simultanious HD videos. I don't really want to spend more than $200-$300 on top of the $900 I am thinking of spending for 6X2GB SATA drives@ $150 apiece, but I am willing to pay extra for a quality solution. Should I get a cheap NAS server? a cheap multi-drive external enclosure? should I just get some used systems off craigslist? If it is an independent system I'll probably just throw ubuntu on it since I can maintain that well. Its easy to do a software raid from ubuntu too, if I choose to go that way. Thanks

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  • Temporary file storage - script for webserver

    - by Chris
    I'm looking for a script (preferably php) which I can use for to temporarily exchange files. I had such a script before (it was written in flash), but - damn - just can't find it anymore. Here the features I'm looking for: I have a logon, which allows me to create "upload spaces". for these "upload spaces" I define a time how long the space will be available for (until the files are deleted), and who can access it - in the means of typing in an email, and that user gets a link with the "online space", user ID and password. the other user then clicks on the link and uploads the file, and I get (preferably) an email should there be any file changes I get an email before the content gets deleted Now, 3 additional things: - it should be open- source - run on linux (preferably lamp) - no, I dont wanna use dropbox or similar :p Thanks in advance everybody, Cheers Chris

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  • Image storage social network (Host plan)

    - by Samir
    I'm wondering what the best way is to host images on a social network site. Let's say that I expect my social network to reach 500.000 users in 2 years time. That would mean that if every user uploaded about 100 images and every image is 1 MB that I will have to need: 500.000 * 100 * 1 MB = 50.000.000 MB which means 50 terabytes. I'm not sure how I can best setup my hosting plan in order to have a solid bases to store my images and eventually store video files as well. Which hosting plan would you recommend me to start with and how can I enhance the plan?

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  • media storage social network (Host plan)

    - by Samir
    I'm wondering what the best way is to host media for a social network site. Let's say that I expect my social network to reach 500.000 users in 2 years time. I'm not sure how I can best setup my hosting plan in order to have a solid bases to store media files. Which hosting plan would you recommend me to start with and how can I enhance the plan?

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  • Page allocation failures on iSCSI storage

    - by Dave
    We have a CentOS 6.3 iscsi server (16GB RAM) running on Infiniband bus (ipoib). When the load is high I can see multiple errors: Sep 3 23:22:20 stor4 kernel: tgtd: page allocation failure. order:2, mode:0x20 Sep 3 23:22:20 stor4 kernel: Pid: 3637, comm: tgtd Not tainted 2.6.32 #1 Sep 3 23:22:20 stor4 kernel: Call Trace: Sep 3 23:22:20 stor4 kernel: [] ? __alloc_pages_nodemask+0x77f/0x940 Sep 3 23:22:20 stor4 kernel: [] ? kmem_getpages+0x62/0x170 Sep 3 23:22:20 stor4 kernel: [] ? fallback_alloc+0x1ba/0x270 Sep 3 23:22:20 stor4 kernel: [] ? cache_grow+0x2cf/0x320 Sep 3 23:22:20 stor4 kernel: [] ? ____cache_alloc_node+0x99/0x160 Sep 3 23:22:20 stor4 kernel: [] ? pskb_expand_head+0x64/0x270 Sep 3 23:22:20 stor4 kernel: [] ? __kmalloc+0x189/0x220 Sep 3 23:22:20 stor4 kernel: [] ? pskb_expand_head+0x64/0x270 Sep 3 23:22:20 stor4 kernel: [] ? __pskb_pull_tail+0x2aa/0x360 Sep 3 23:22:20 stor4 kernel: [] ? tcp_init_tso_segs+0x37/0x50 Sep 3 23:22:20 stor4 kernel: [] ? dev_queue_xmit+0x4bb/0x6f0 Sep 3 23:22:20 stor4 kernel: [] ? neigh_connected_output+0xbd/0x100 Sep 3 23:22:20 stor4 kernel: [] ? ip_finish_output+0x237/0x310 Sep 3 23:22:20 stor4 kernel: [] ? ip_output+0xb8/0xc0 Sep 3 23:22:20 stor4 kernel: [] ? __ip_local_out+0x9f/0xb0 Sep 3 23:22:20 stor4 kernel: [] ? ip_local_out+0x25/0x30 Sep 3 23:22:20 stor4 kernel: [] ? ip_queue_xmit+0x190/0x420 Sep 3 23:22:20 stor4 kernel: [] ? sock_aio_write+0x167/0x180 Sep 3 23:22:20 stor4 kernel: [] ? tcp_transmit_skb+0x3fe/0x7b0 Sep 3 23:22:20 stor4 kernel: [] ? tcp_write_xmit+0x1fb/0xa20 Sep 3 23:22:20 stor4 kernel: [] ? __tcp_push_pending_frames+0x30/0xe0 Sep 3 23:22:20 stor4 kernel: [] ? tcp_push_pending_frames+0x33/0x40 Sep 3 23:22:20 stor4 kernel: [] ? do_tcp_setsockopt+0x3d6/0x480 Sep 3 23:22:20 stor4 kernel: [] ? tcp_setsockopt+0x2a/0x30 Sep 3 23:22:20 stor4 kernel: [] ? sock_common_setsockopt+0x14/0x20 Sep 3 23:22:20 stor4 kernel: [] ? sys_setsockopt+0x7f/0xe0 Sep 3 23:22:20 stor4 kernel: [] ? system_call_fastpath+0x16/0x1b Sep 3 23:22:20 stor4 kernel: Mem-Info: Sep 3 23:22:20 stor4 kernel: Node 0 DMA per-cpu: Sep 3 23:22:20 stor4 kernel: CPU 0: hi: 0, btch: 1 usd: 0 Sep 3 23:22:20 stor4 kernel: CPU 1: hi: 0, btch: 1 usd: 0 Sep 3 23:22:20 stor4 kernel: CPU 2: hi: 0, btch: 1 usd: 0 Sep 3 23:22:20 stor4 kernel: CPU 3: hi: 0, btch: 1 usd: 0 Sep 3 23:22:20 stor4 kernel: Node 0 DMA32 per-cpu: Sep 3 23:22:20 stor4 kernel: CPU 0: hi: 186, btch: 31 usd: 183 Sep 3 23:22:20 stor4 kernel: CPU 1: hi: 186, btch: 31 usd: 23 Sep 3 23:22:20 stor4 kernel: CPU 2: hi: 186, btch: 31 usd: 183 Sep 3 23:22:20 stor4 kernel: CPU 3: hi: 186, btch: 31 usd: 181 Sep 3 23:22:20 stor4 kernel: Node 0 Normal per-cpu: Sep 3 23:22:20 stor4 kernel: CPU 0: hi: 186, btch: 31 usd: 171 Sep 3 23:22:20 stor4 kernel: CPU 1: hi: 186, btch: 31 usd: 29 Sep 3 23:22:20 stor4 kernel: CPU 2: hi: 186, btch: 31 usd: 32 Sep 3 23:22:20 stor4 kernel: CPU 3: hi: 186, btch: 31 usd: 32 Sep 3 23:22:20 stor4 kernel: active_anon:1875 inactive_anon:2473 isolated_anon:0 Sep 3 23:22:20 stor4 kernel: active_file:1243637 inactive_file:2505055 isolated_file:0 Sep 3 23:22:20 stor4 kernel: unevictable:0 dirty:268338 writeback:0 unstable:0 Sep 3 23:22:20 stor4 kernel: free:86050 slab_reclaimable:132377 slab_unreclaimable:23744 Sep 3 23:22:20 stor4 kernel: mapped:1293 shmem:222 pagetables:720 bounce:0 Sep 3 23:22:20 stor4 kernel: Node 0 DMA free:15732kB min:124kB low:152kB high:184kB active_anon:0kB inactive_anon:0kB active_file:0kB inactive_file:0kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15332kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? yes Sep 3 23:22:20 stor4 kernel: lowmem_reserve[]: 0 2172 16060 16060 Sep 3 23:22:20 stor4 kernel: Node 0 DMA32 free:107544kB min:18268kB low:22832kB high:27400kB active_anon:468kB inactive_anon:2364kB active_file:566208kB inactive_file:976112kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:2224900kB mlocked:0kB dirty:96816kB writeback:0kB mapped:908kB shmem:12kB slab_reclaimable:176940kB slab_unreclaimable:968kB kernel_stack:64kB pagetables:192kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Sep 3 23:22:20 stor4 kernel: lowmem_reserve[]: 0 0 13887 13887 Sep 3 23:22:20 stor4 kernel: Node 0 Normal free:220924kB min:116772kB low:145964kB high:175156kB active_anon:7032kB inactive_anon:7528kB active_file:4408340kB inactive_file:9044108kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:14220800kB mlocked:0kB dirty:976536kB writeback:0kB mapped:4264kB shmem:876kB slab_reclaimable:352568kB slab_unreclaimable:94008kB kernel_stack:2048kB pagetables:2688kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Sep 3 23:22:20 stor4 kernel: lowmem_reserve[]: 0 0 0 0 Sep 3 23:22:20 stor4 kernel: Node 0 DMA: 1*4kB 0*8kB 1*16kB 1*32kB 1*64kB 0*128kB 1*256kB 0*512kB 1*1024kB 1*2048kB 3*4096kB = 15732kB Sep 3 23:22:20 stor4 kernel: Node 0 DMA32: 16305*4kB 4381*8kB 353*16kB 8*32kB 1*64kB 1*128kB 0*256kB 1*512kB 1*1024kB 0*2048kB 0*4096kB = 107900kB Sep 3 23:22:20 stor4 kernel: Node 0 Normal: 14548*4kB 14808*8kB 2420*16kB 31*32kB 5*64kB 0*128kB 0*256kB 0*512kB 0*1024kB 0*2048kB 1*4096kB = 220784kB Sep 3 23:22:20 stor4 kernel: 3748822 total pagecache pages Sep 3 23:22:20 stor4 kernel: 0 pages in swap cache Sep 3 23:22:20 stor4 kernel: Swap cache stats: add 0, delete 0, find 0/0 Sep 3 23:22:20 stor4 kernel: Free swap = 975864kB Sep 3 23:22:20 stor4 kernel: Total swap = 975864kB Sep 3 23:22:20 stor4 kernel: 4194303 pages RAM Sep 3 23:22:20 stor4 kernel: 126915 pages reserved Sep 3 23:22:20 stor4 kernel: 3753534 pages shared Sep 3 23:22:20 stor4 kernel: 213500 pages non-shared TCP stack and VM config: net.core.rmem_max = 83886080 net.core.wmem_max = 83886080 net.core.rmem_default = 65536 net.core.wmem_default = 65536 net.ipv4.tcp_rmem = 40960 1048560 4194304 net.ipv4.tcp_wmem = 40960 196608 4194304 net.ipv4.tcp_mem = 16388608 16388608 16388608 vm.min_free_kbytes=135168 Additional tweaks: /sbin/blockdev --setra 16384 /dev/sdb echo 2048 /sys/block/sdb/queue/nr_requests Where might the problem be? Thank you.

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  • Can I get redundancy with a JBOD storage subsystem

    - by Dat Chu
    I have a Promise Technology J610S. This is a JBOD subsystem. Is it possible for me to buy a SAS hardware RAID controller and provide some type of redundancy for these drives? I am unsure whether I will use Linux or Windows yet so an answer with enumeration for both would be highly appreciated. One solution that I thought of was: if my J610s can export each drive as a target, my server will simply see 16 drives. The RAID controller can then perform the RAID5/RAID6 if I want.

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