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  • Given an array of arguments, how do I send those arguments to a particular function in Ruby?

    - by Steven Xu
    Forgive the beginner question, but say I have an array: a = [1,2,3] And a function somewhere; let's say it's an instance function: class Ilike def turtles(*args) puts args.inspect end end How do I invoke Ilike.turtles with a as if I were calling (Ilike.new).turtles(1,2,3). I'm familiar with send, but this doesn't seem to translate an array into an argument list. A parallel of what I'm looking for is the Javascript apply, which is equivalent to call but converts the array into an argument list.

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  • SEHException External component has thrown exception in VS2005

    - by sdz
    Hello! I imported inpout32.dll to the program and tried to do the parallel port interfacing for outputting and inputting through the port. But when the execution reaches the statement PortAccess.Output(888,0); it throws the above exception. The PortAccess class is defined in the inpout32.dll file which i downloaded from www.logix4u.net. Can anyone help me with this?

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  • How can I have a Foo* iterator to a vector of Foo?

    - by mghie
    If I have a class that contains a std::list<Foo>, how can I implement iterators to a Foo* collection, preferably without using boost? I'd rather not maintain a parallel collection of pointers. For now I have std::list<Foo>, mostly so that removing or inserting an element does not invalidate all other iterators, but would it be possible to implement other iterators too, so that the collection type used in the implementation is opaque to the user of the class?

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  • Check if a connection is in a transaction

    - by acidzombie24
    I am getting a SqlConnection does not support parallel transactions. exception and this answer mentions its when a connection tries to open two transactions. This is exactly what i am doing. I thought nested transactions were ok (i was using sqlite for the prototype). How do i check if the connection is already in a transaction? I am using Microsoft SQL Server Database File.

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  • Concurrent processes do not utilize all available CPU

    - by metdos
    I run some processes on an EC2 cc2.8xlarge instance which has 32 virtual processors. For some type of processes, when I run 16 processes on parallel, all of them use 100% of CPU cycles. But for other type of processes, they are not using 100% CPU and they finish considerably slower than a single thread. There is no time spend on IO and all data is served from memory. Do you have any idea about the reason of this problem?

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  • Multiple reference in SQL

    - by AGarofoli
    Hi! I'm working on a db but i'm kinda new to this so i've bumped into a problem today. I've got some tables: OFFICE, ROOM, EMPLOYEE and DOCUMENT. Document must specify the sender, which can be a single employee, an entire room or an entire office so it must have a reference to the primary keys of those tables. Should I do a "parallel" table for handle it (for example i've done one for handle the multiple recipients documents) or there is another way? Thank you

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  • java Thread class run() method

    - by JavaUser
    Hi, Thread class has run method to implement the business logic that could be executed in parallel.But I want implement different business logics in a single run method and to run simultaneously.How to get this feature. thanks

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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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  • Linux software RAID6: rebuild slow

    - by Ole Tange
    I am trying to find the bottleneck in the rebuilding of a software raid6. ## Pause rebuilding when measuring raw I/O performance # echo 1 > /proc/sys/dev/raid/speed_limit_min # echo 1 > /proc/sys/dev/raid/speed_limit_max ## Drop caches so that does not interfere with measuring # sync ; echo 3 | tee /proc/sys/vm/drop_caches >/dev/null # time parallel -j0 "dd if=/dev/{} bs=256k count=4000 | cat >/dev/null" ::: sdbd sdbc sdbf sdbm sdbl sdbk sdbe sdbj sdbh sdbg 4000+0 records in 4000+0 records out 1048576000 bytes (1.0 GB) copied, 7.30336 s, 144 MB/s [... similar for each disk ...] # time parallel -j0 "dd if=/dev/{} skip=15000000 bs=256k count=4000 | cat >/dev/null" ::: sdbd sdbc sdbf sdbm sdbl sdbk sdbe sdbj sdbh sdbg 4000+0 records in 4000+0 records out 1048576000 bytes (1.0 GB) copied, 12.7991 s, 81.9 MB/s [... similar for each disk ...] So we can read sequentially at 140 MB/s in the outer tracks and 82 MB/s in the inner tracks on all the drives simultaneously. Sequential write performance is similar. This would lead me to expect a rebuild speed of 82 MB/s or more. # echo 800000 > /proc/sys/dev/raid/speed_limit_min # echo 800000 > /proc/sys/dev/raid/speed_limit_max # cat /proc/mdstat md2 : active raid6 sdbd[10](S) sdbc[9] sdbf[0] sdbm[8] sdbl[7] sdbk[6] sdbe[11] sdbj[4] sdbi[3](F) sdbh[2] sdbg[1] 27349121408 blocks super 1.2 level 6, 128k chunk, algorithm 2 [9/8] [UUU_UUUUU] [=========>...........] recovery = 47.3% (1849905884/3907017344) finish=855.9min speed=40054K/sec But we only get 40 MB/s. And often this drops to 30 MB/s. # iostat -dkx 1 sdbc 0.00 8023.00 0.00 329.00 0.00 33408.00 203.09 0.70 2.12 1.06 34.80 sdbd 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sdbe 13.00 0.00 8334.00 0.00 33388.00 0.00 8.01 0.65 0.08 0.06 47.20 sdbf 0.00 0.00 8348.00 0.00 33388.00 0.00 8.00 0.58 0.07 0.06 48.00 sdbg 16.00 0.00 8331.00 0.00 33388.00 0.00 8.02 0.71 0.09 0.06 48.80 sdbh 961.00 0.00 8314.00 0.00 37100.00 0.00 8.92 0.93 0.11 0.07 54.80 sdbj 70.00 0.00 8276.00 0.00 33384.00 0.00 8.07 0.78 0.10 0.06 48.40 sdbk 124.00 0.00 8221.00 0.00 33380.00 0.00 8.12 0.88 0.11 0.06 47.20 sdbl 83.00 0.00 8262.00 0.00 33380.00 0.00 8.08 0.96 0.12 0.06 47.60 sdbm 0.00 0.00 8344.00 0.00 33376.00 0.00 8.00 0.56 0.07 0.06 47.60 iostat says the disks are not 100% busy (but only 40-50%). This fits with the hypothesis that the max is around 80 MB/s. Since this is software raid the limiting factor could be CPU. top says: PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 38520 root 20 0 0 0 0 R 64 0.0 2947:50 md2_raid6 6117 root 20 0 0 0 0 D 53 0.0 473:25.96 md2_resync So md2_raid6 and md2_resync are clearly busy taking up 64% and 53% of a CPU respectively, but not near 100%. The chunk size (128k) of the RAID was chosen after measuring which chunksize gave the least CPU penalty. If this speed is normal: What is the limiting factor? Can I measure that? If this speed is not normal: How can I find the limiting factor? Can I change that?

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  • This task is currently locked by a running workflow and cannot be edited. Limitation to both Nintex and SPD workflow

    - by ybbest
    Note, this post is from Nintex Forum here. These limitations apply to both SharePoint designer Workflow and Nintex Workflow as Nintex using the SharePoint workflow engine. The common cause that I experience is that ‘parent’ workflow is generating more than one task at once. This is common as you can have multiple approvers for certain approval process. You could also have workflow running when the task is created, one of the common scenario is you would like to set a custom column value in your approval task. For me this is huge limitation, as Nintex lover I really hope Nintex could solve this problem with Microsoft going forward. Introduction “This task is currently locked by a running workflow and cannot be edited” is a common message that is seen when an error occurs while the SharePoint workflow engine is processing a task item associated with a workflow. When a workflow processes a task normally, the following sequence of events is expected to occur: 1.       The process begins. 2.       The workflow places a ‘lock’ on the task so nothing else can change the values while the workflow is processing. 3.       The workflow processes the task. 4.       The lock is released when the task processing is finished. When the message is encountered, it usually indicates that an error occurred between step 2 and 4. As a result, the lock is never released. Therefore, the ‘task locked’ message is not an error itself, rather a symptom of another error – the ‘task locked’ message does not indicate what went wrong. In most cases, once this message is encountered, the workflow cannot be made to continue and must be terminated and started again. The following is a guide that can help troubleshoot the cause of these messages.  Some initial observations to narrow down the potential causes are: Is the error consistent or intermittent? When the error is consistent, it will happen every time the workflow is run. When it is intermittent, it may happen regularly, but not every time. Does the error occur the first time the user tries to respond to a task, or do they respond and notice the workflow does not continue, and when they respond again the error occurs? If the message is present when the user first responds to the task, the issue would have occurred when the task was created. Otherwise, it would have occurred when the user attempted to respond to the task. Causes Modifying the task list A cause of this error appearing consistently the first time a user tries to respond to a task is a modification to the default task list schema. For example, changing the ‘Assigned to’ field in a task list to be a multiple selection will cause the behaviour. Deleting the workflow task then restoring it from the Recycle bin If you start a workflow, delete the workflow task then restore it from the Recycle Bin in SharePoint, the workflow will fail with the ‘task locked’ error.  This is confirmed behaviour whether using a SharePoint Designer or a Nintex workflow.  You will need to terminate the workflow and start it again. Parallel simultaneous responses A cause of this error appearing inconsistently is multiple users responding to tasks in parallel at the same time. In this scenario, one task will complete correctly and the other will not process. When the user tries again, the ‘task locked’ message will display. Nintex included a workaround for this issue in build 11000. In build 11000 and later, one of the users will receive a message on the task form when they attempt to respond, stating that they need to try again in a few moments. Additional processing on the task A cause of this error appearing consistently and inconsistently is having an additional system running on the items in the task list. Some examples include: a workflow running on the task list, an event receiver running on the task list or another automated process querying and updating workflow tasks. Note: This Microsoft help article (http://office.microsoft.com/en-us/sharepointdesigner/HA102376561033.aspx#5) explains creating a workflow that runs on the task list to update a field on the task. Our experience shows that this causes the ‘Task Locked’ issues when the ‘parent’ workflow is generating more than one task at once. Isolated system error If the error is a rare event, or a ‘one off’ event, then an isolated system error may have occurred. For example, if there is a database connectivity issue while the workflow is processing the task response, the task will lock. In this case, the user will respond to a task but the workflow will not continue. When they respond again, the ‘task locked’ message will display. In this case, there will be an error in the SharePoint ULS Logs at the time that the user originally responded. Temporary delay while workflow processes If the workflow is taking a long time to process after a user submits a task, they may notice and try to respond to the task again. They will see the task locked error, but after a number of attempts (or after waiting some time) the task response page eventually indicates the task has been responded to. In this case, nothing actually went wrong, and the error message gives an accurate indication of what is happening – the workflow temporarily locked the task while it was processing. This scenario may occur in a very large workflow, or after the SharePoint application pool has just started. Modifying the task via a web service with an invalid url If the Nintex Workflow web service is used to respond to or delegate a task, the site context part of the url must be a valid alternative access mapping url. For example, if you access the web service via the IP address of the SharePoint server, and the IP address is not a valid AAM, the task can become locked. The workflow has become stuck without any apparent errors This behaviour can occur as a result of a bug in the SharePoint 2010 workflow engine.  If you do not have the August 2010 Cumulative Update (or later) for SharePoint, and your workflow uses delays, “Flexi-task”, State machine”, “Task Reminder” actions or variables, you could be affected. Check the SharePoint 2010 Updates site here: http://technet.microsoft.com/en-us/sharepoint/ff800847.  The October CU is recommended http://support.microsoft.com/kb/2553031.   The fix is described as “Consider the following scenario. You add a Delay activity to a workflow. Then, you set the duration for the Delay activity. You deploy the workflow in SharePoint Foundation 2010. In this scenario, the workflow is not resumed after the duration of the Delay activity”. If you find this is occurring in your environment, install the October CU, terminate all the running workflows affected and run them afresh. Investigative steps The first step to isolate the issue is to create a new task list on the site and configure the workflow to use it.  Any customizations that were made to the original task list should not be made to the new task list. If the new task list eliminates the issue, then the cause can be attributed to the original task list or a change that was made to it. To change the task list that the workflow uses: In Workflow Designer select Settings -> Startup Options Then configure the task list as required If any of the scenarios above do not help, check the SharePoint logs for any messages with a category of ‘Workflow Infrastructure’. Conclusion The information in this article has been gathered from observations and investigations by Nintex. The sources of these issues are the underlying SharePoint workflow engine. This article will be updated if further causes are discovered. From <http://connect.nintex.com/forums/thread/6503.aspx>

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  • Code Camp 2011 – Summary

    - by hajan
    Waiting whole twelve months to come this year’s Code Camp 2011 event was something which all Microsoft technologies (and even non-Microsoft techs.) developers were doing in the past year. Last year’s success was enough big to be heard and to influence everything around our developer community and beyond. Code Camp 2011 was nothing else but a invincible success which will remain in our memory for a long time from now. Darko Milevski (president of MKDOT.NET UG and SharePoint MVP) said something interesting at the event keynote that up to now we were looking at the past by saying what we did… now we will focus on the future and how to develop our community more and more in the future days, weeks, months and I hope so for many years… Even though it was held only two days ago (26th of November 2011), I already feel the nostalgia for everything that happened there and for the excellent time we have spent all together. ORGANIZED BY ENTHUSIASTS AND EXPERTS Code Camp 2011 was organized by number of community enthusiasts and experts who have unselfishly contributed with all their free time to make the best of this event. The event was organized by a known community group called MKDOT.NET User Group, name of a user group which is known not only in Macedonia, but also in many countries abroad. Organization mainly consists of software developers, technical leaders, team leaders in several known companies in Macedonia, as well as Microsoft MVPs. SPEAKERS There were 24 speakers at five parallel tracks. At Code Camp 2011 we had two groups of speakers: Professional Experts in various technologies and Student Speakers. The new interesting thing here is the Student Speakers, which draw attention a lot, especially to other students who were interested to see what their colleagues are going to speak about and how do they use Microsoft technologies in different coding scenarios and practices, in different topics. From the rest of the professional speakers, there were 7 Microsoft MVPs: Two ASP.NET/IIS MVPs, Two C# MVPs, and One MVP in SharePoint, SQL Server and Exchange Server. I must say that besides the MVP Speakers, who definitely did a great job as always… there were other excellent speakers as well, which were speaking on various technologies, such as: Web Development, Windows Phone Development, XNA, Windows 8, Games Development, Entity Framework, Event-driven programming, SOLID, SQLCLR, T-SQL, e.t.c. SESSIONS There were 25 sessions mainly all related to Microsoft technologies, but ranging from Windows 8, WP7, ASP.NET till Games Development, XNA and Event-driven programming. Sessions were going in five parallel tracks named as Red, Yellow, Green, Blue and Student track. Five presentations in each track, each with level 300 or 400. More info MY SESSION (ASP.NET MVC Best Practices) I must say that from the big number of speaking engagements I have had, this was one of my best performances and definitely I have set new records of attendees at my sessions and probably overall. I spoke on topic ASP.NET MVC Best Practices, where I have shown tips, tricks, guidelines and best practices on what to use and what to avoid by developing with one of the best web development frameworks nowadays, ASP.NET MVC. I had approximately 350+ attendees, the hall was full so that there was no room for staying at feet. Besides .NET developers, there were a lot of other technology oriented developers, who has also received the presentation very well and I really hope I gave them reason to think about ASP.NET as one of the best options for web development nowadays (if you ask me, it’s the best one ;-)). I have included 10 tips in using ASP.NET MVC each of them followed by a demo. Besides these 10 tips, I have briefly introduced the concept of ASP.NET MVC for those that haven’t been working with the framework and at the end some bonus tips. I must say there was lot of laugh for some funny sentences I have stated, like “If you code ASP.NET MVC, girls will love you more” – same goes for girls, only replace girls with boys :). [LINK TO SESSION WILL GO HERE, ONCE SESSIONS ARE AVAILABLE ON MK CODECAMP WEBSITE] VOLUNTEERS Without strong organization, such events wouldn’t be able to gather hundreds of attendees at one place and still stay perfectly organized to the smallest details, without dedicated organization and volunteers. I would like to dedicate this space in my blog to them and to say one big THANK YOU for supporting us before the event and during the whole day in the event. With such young and dedicated volunteers, we couldn’t achieve anything but great results. THANK YOU EVERYONE FOR YOUR CONTRIBUTION! NETWORKING One of the main reasons why we do such events is to gather all professionals in one place. Networking is what everyone wants because through this way of networking, we can meet incredible people in one place. It is amazing feeling to share your knowledge with others and exchange thoughts on various topics. Meet and talk to interesting people. I have had very special moments with many attendees especially after my presentation. Special Thank You to all of them who come to meet me in person, whether to ask a question, say congrats for my session or simply meet me and just smile :)… everything counts! Thank You! TWITTER During the event, twitter was one of the most useful event-wide communication tool where everyone could tweet with hash tag #mkcodecamp or #mkdotnet and say what he/she wants to say about the current state and happenings at that moment… In my next blog post I will list the top craziest tweets that were posted at this event… FUTURE OF MKDOT.NET Having such strong community around MKDOT.NET, the future seems very bright. The initial plans are to have sub-groups in several technologies, however all these sub-groups will belong to the MKDOT.NET UG which will be, somehow, the HEAD of these sub-groups. We are doing this to provide better divisions by technologies and organize ourselves better since our community is very big, around 500 members in MKDOT.NET.We will have five sub-groups:- Web User Group (Lead:Hajan Selmani - me)- Mobile User Group (Lead: Filip Kerazovski)- Visual C# User Group (Lead: Vekoslav Stefanovski)- SharePoint User Group (Lead: Darko Milevski)- Dynamics User Group (Lead: Vladimir Senih) SUMMARY Online registered attendees: ~1.200 Event attendees: ~800 Number of members in organization: 40+ Organized by: MKDOT.NET User Group Number of tracks: 5 Number of speakers: 24 Number of sessions: 25 Event official website: http://codecamp.mkdot.net Total number of sponsors: 20 Platinum Sponsors: Microsoft, INETA, Telerik Place held: FON University City and Country: Skopje, Macedonia THANK YOU FOR BEING PART OF THE BEST EVENT IN MACEDONIA, CODE CAMP 2011. Regards, Hajan

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  • VS 2010 Debugger Improvements (BreakPoints, DataTips, Import/Export)

    - by ScottGu
    This is the twenty-first in a series of blog posts I’m doing on the VS 2010 and .NET 4 release.  Today’s blog post covers a few of the nice usability improvements coming with the VS 2010 debugger.  The VS 2010 debugger has a ton of great new capabilities.  Features like Intellitrace (aka historical debugging), the new parallel/multithreaded debugging capabilities, and dump debuging support typically get a ton of (well deserved) buzz and attention when people talk about the debugging improvements with this release.  I’ll be doing blog posts in the future that demonstrate how to take advantage of them as well.  With today’s post, though, I thought I’d start off by covering a few small, but nice, debugger usability improvements that were also included with the VS 2010 release, and which I think you’ll find useful. Breakpoint Labels VS 2010 includes new support for better managing debugger breakpoints.  One particularly useful feature is called “Breakpoint Labels” – it enables much better grouping and filtering of breakpoints within a project or across a solution.  With previous releases of Visual Studio you had to manage each debugger breakpoint as a separate item. Managing each breakpoint separately can be a pain with large projects and for cases when you want to maintain “logical groups” of breakpoints that you turn on/off depending on what you are debugging.  Using the new VS 2010 “breakpoint labeling” feature you can now name these “groups” of breakpoints and manage them as a unit. Grouping Multiple Breakpoints Together using a Label Below is a screen-shot of the breakpoints window within Visual Studio 2010.  This lists all of the breakpoints defined within my solution (which in this case is the ASP.NET MVC 2 code base): The first and last breakpoint in the list above breaks into the debugger when a Controller instance is created or released by the ASP.NET MVC Framework. Using VS 2010, I can now select these two breakpoints, right-click, and then select the new “Edit labels…” menu command to give them a common label/name (making them easier to find and manage): Below is the dialog that appears when I select the “Edit labels” command.  We can use it to create a new string label for our breakpoints or select an existing one we have already defined.  In this case we’ll create a new label called “Lifetime Management” to describe what these two breakpoints cover: When we press the OK button our two selected breakpoints will be grouped under the newly created “Lifetime Management” label: Filtering/Sorting Breakpoints by Label We can use the “Search” combobox to quickly filter/sort breakpoints by label.  Below we are only showing those breakpoints with the “Lifetime Management” label: Toggling Breakpoints On/Off by Label We can also toggle sets of breakpoints on/off by label group.  We can simply filter by the label group, do a Ctrl-A to select all the breakpoints, and then enable/disable all of them with a single click: Importing/Exporting Breakpoints VS 2010 now supports importing/exporting breakpoints to XML files – which you can then pass off to another developer, attach to a bug report, or simply re-load later.  To export only a subset of breakpoints, you can filter by a particular label and then click the “Export breakpoint” button in the Breakpoints window: Above I’ve filtered my breakpoint list to only export two particular breakpoints (specific to a bug that I’m chasing down).  I can export these breakpoints to an XML file and then attach it to a bug report or email – which will enable another developer to easily setup the debugger in the correct state to investigate it on a separate machine.  Pinned DataTips Visual Studio 2010 also includes some nice new “DataTip pinning” features that enable you to better see and track variable and expression values when in the debugger.  Simply hover over a variable or expression within the debugger to expose its DataTip (which is a tooltip that displays its value)  – and then click the new “pin” button on it to make the DataTip always visible: You can “pin” any number of DataTips you want onto the screen.  In addition to pinning top-level variables, you can also drill into the sub-properties on variables and pin them as well.  Below I’ve “pinned” three variables: “category”, “Request.RawUrl” and “Request.LogonUserIdentity.Name”.  Note that these last two variable are sub-properties of the “Request” object.   Associating Comments with Pinned DataTips Hovering over a pinned DataTip exposes some additional UI within the debugger: Clicking the comment button at the bottom of this UI expands the DataTip - and allows you to optionally add a comment with it: This makes it really easy to attach and track debugging notes: Pinned DataTips are usable across both Debug Sessions and Visual Studio Sessions Pinned DataTips can be used across multiple debugger sessions.  This means that if you stop the debugger, make a code change, and then recompile and start a new debug session - any pinned DataTips will still be there, along with any comments you associate with them.  Pinned DataTips can also be used across multiple Visual Studio sessions.  This means that if you close your project, shutdown Visual Studio, and then later open the project up again – any pinned DataTips will still be there, along with any comments you associate with them. See the Value from Last Debug Session (Great Code Editor Feature) How many times have you ever stopped the debugger only to go back to your code and say: $#@! – what was the value of that variable again??? One of the nice things about pinned DataTips is that they keep track of their “last value from debug session” – and you can look these values up within the VB/C# code editor even when the debugger is no longer running.  DataTips are by default hidden when you are in the code editor and the debugger isn’t running.  On the left-hand margin of the code editor, though, you’ll find a push-pin for each pinned DataTip that you’ve previously setup: Hovering your mouse over a pinned DataTip will cause it to display on the screen.  Below you can see what happens when I hover over the first pin in the editor - it displays our debug session’s last values for the “Request” object DataTip along with the comment we associated with them: This makes it much easier to keep track of state and conditions as you toggle between code editing mode and debugging mode on your projects. Importing/Exporting Pinned DataTips As I mentioned earlier in this post, pinned DataTips are by default saved across Visual Studio sessions (you don’t need to do anything to enable this). VS 2010 also now supports importing/exporting pinned DataTips to XML files – which you can then pass off to other developers, attach to a bug report, or simply re-load later. Combined with the new support for importing/exporting breakpoints, this makes it much easier for multiple developers to share debugger configurations and collaborate across debug sessions. Summary Visual Studio 2010 includes a bunch of great new debugger features – both big and small.  Today’s post shared some of the nice debugger usability improvements. All of the features above are supported with the Visual Studio 2010 Professional edition (the Pinned DataTip features are also supported in the free Visual Studio 2010 Express Editions)  I’ll be covering some of the “big big” new debugging features like Intellitrace, parallel/multithreaded debugging, and dump file analysis in future blog posts.  Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • Building dynamic OLAP data marts on-the-fly

    - by DrJohn
    At the forthcoming SQLBits conference, I will be presenting a session on how to dynamically build an OLAP data mart on-the-fly. This blog entry is intended to clarify exactly what I mean by an OLAP data mart, why you may need to build them on-the-fly and finally outline the steps needed to build them dynamically. In subsequent blog entries, I will present exactly how to implement some of the techniques involved. What is an OLAP data mart? In data warehousing parlance, a data mart is a subset of the overall corporate data provided to business users to meet specific business needs. Of course, the term does not specify the technology involved, so I coined the term "OLAP data mart" to identify a subset of data which is delivered in the form of an OLAP cube which may be accompanied by the relational database upon which it was built. To clarify, the relational database is specifically create and loaded with the subset of data and then the OLAP cube is built and processed to make the data available to the end-users via standard OLAP client tools. Why build OLAP data marts? Market research companies sell data to their clients to make money. To gain competitive advantage, market research providers like to "add value" to their data by providing systems that enhance analytics, thereby allowing clients to make best use of the data. As such, OLAP cubes have become a standard way of delivering added value to clients. They can be built on-the-fly to hold specific data sets and meet particular needs and then hosted on a secure intranet site for remote access, or shipped to clients' own infrastructure for hosting. Even better, they support a wide range of different tools for analytical purposes, including the ever popular Microsoft Excel. Extension Attributes: The Challenge One of the key challenges in building multiple OLAP data marts based on the same 'template' is handling extension attributes. These are attributes that meet the client's specific reporting needs, but do not form part of the standard template. Now clearly, these extension attributes have to come into the system via additional files and ultimately be added to relational tables so they can end up in the OLAP cube. However, processing these files and filling dynamically altered tables with SSIS is a challenge as SSIS packages tend to break as soon as the database schema changes. There are two approaches to this: (1) dynamically build an SSIS package in memory to match the new database schema using C#, or (2) have the extension attributes provided as name/value pairs so the file's schema does not change and can easily be loaded using SSIS. The problem with the first approach is the complexity of writing an awful lot of complex C# code. The problem of the second approach is that name/value pairs are useless to an OLAP cube; so they have to be pivoted back into a proper relational table somewhere in the data load process WITHOUT breaking SSIS. How this can be done will be part of future blog entry. What is involved in building an OLAP data mart? There are a great many steps involved in building OLAP data marts on-the-fly. The key point is that all the steps must be automated to allow for the production of multiple OLAP data marts per day (i.e. many thousands, each with its own specific data set and attributes). Now most of these steps have a great deal in common with standard data warehouse practices. The key difference is that the databases are all built to order. The only permanent database is the metadata database (shown in orange) which holds all the metadata needed to build everything else (i.e. client orders, configuration information, connection strings, client specific requirements and attributes etc.). The staging database (shown in red) has a short life: it is built, populated and then ripped down as soon as the OLAP Data Mart has been populated. In the diagram below, the OLAP data mart comprises the two blue components: the Data Mart which is a relational database and the OLAP Cube which is an OLAP database implemented using Microsoft Analysis Services (SSAS). The client may receive just the OLAP cube or both components together depending on their reporting requirements.  So, in broad terms the steps required to fulfil a client order are as follows: Step 1: Prepare metadata Create a set of database names unique to the client's order Modify all package connection strings to be used by SSIS to point to new databases and file locations. Step 2: Create relational databases Create the staging and data mart relational databases using dynamic SQL and set the database recovery mode to SIMPLE as we do not need the overhead of logging anything Execute SQL scripts to build all database objects (tables, views, functions and stored procedures) in the two databases Step 3: Load staging database Use SSIS to load all data files into the staging database in a parallel operation Load extension files containing name/value pairs. These will provide client-specific attributes in the OLAP cube. Step 4: Load data mart relational database Load the data from staging into the data mart relational database, again in parallel where possible Allocate surrogate keys and use SSIS to perform surrogate key lookup during the load of fact tables Step 5: Load extension tables & attributes Pivot the extension attributes from their native name/value pairs into proper relational tables Add the extension attributes to the views used by OLAP cube Step 6: Deploy & Process OLAP cube Deploy the OLAP database directly to the server using a C# script task in SSIS Modify the connection string used by the OLAP cube to point to the data mart relational database Modify the cube structure to add the extension attributes to both the data source view and the relevant dimensions Remove any standard attributes that not required Process the OLAP cube Step 7: Backup and drop databases Drop staging database as it is no longer required Backup data mart relational and OLAP database and ship these to the client's infrastructure Drop data mart relational and OLAP database from the build server Mark order complete Start processing the next order, ad infinitum. So my future blog posts and my forthcoming session at the SQLBits conference will all focus on some of the more interesting aspects of building OLAP data marts on-the-fly such as handling the load of extension attributes and how to dynamically alter the structure of an OLAP cube using C#.

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  • RiverTrail - JavaScript GPPGU Data Parallelism

    - by JoshReuben
    Where is WebCL ? The Khronos WebCL working group is working on a JavaScript binding to the OpenCL standard so that HTML 5 compliant browsers can host GPGPU web apps – e.g. for image processing or physics for WebGL games - http://www.khronos.org/webcl/ . While Nokia & Samsung have some protype WebCL APIs, Intel has one-upped them with a higher level of abstraction: RiverTrail. Intro to RiverTrail Intel Labs JavaScript RiverTrail provides GPU accelerated SIMD data-parallelism in web applications via a familiar JavaScript programming paradigm. It extends JavaScript with simple deterministic data-parallel constructs that are translated at runtime into a low-level hardware abstraction layer. With its high-level JS API, programmers do not have to learn a new language or explicitly manage threads, orchestrate shared data synchronization or scheduling. It has been proposed as a draft specification to ECMA a (known as ECMA strawman). RiverTrail runs in all popular browsers (except I.E. of course). To get started, download a prebuilt version https://github.com/downloads/RiverTrail/RiverTrail/rivertrail-0.17.xpi , install Intel's OpenCL SDK http://www.intel.com/go/opencl and try out the interactive River Trail shell http://rivertrail.github.com/interactive For a video overview, see  http://www.youtube.com/watch?v=jueg6zB5XaM . ParallelArray the ParallelArray type is the central component of this API & is a JS object that contains ordered collections of scalars – i.e. multidimensional uniform arrays. A shape property describes the dimensionality and size– e.g. a 2D RGBA image will have shape [height, width, 4]. ParallelArrays are immutable & fluent – they are manipulated by invoking methods on them which produce new ParallelArray objects. ParallelArray supports several constructors over arrays, functions & even the canvas. // Create an empty Parallel Array var pa = new ParallelArray(); // pa0 = <>   // Create a ParallelArray out of a nested JS array. // Note that the inner arrays are also ParallelArrays var pa = new ParallelArray([ [0,1], [2,3], [4,5] ]); // pa1 = <<0,1>, <2,3>, <4.5>>   // Create a two-dimensional ParallelArray with shape [3, 2] using the comprehension constructor var pa = new ParallelArray([3, 2], function(iv){return iv[0] * iv[1];}); // pa7 = <<0,0>, <0,1>, <0,2>>   // Create a ParallelArray from canvas.  This creates a PA with shape [w, h, 4], var pa = new ParallelArray(canvas); // pa8 = CanvasPixelArray   ParallelArray exposes fluent API functions that take an elemental JS function for data manipulation: map, combine, scan, filter, and scatter that return a new ParallelArray. Other functions are scalar - reduce  returns a scalar value & get returns the value located at a given index. The onus is on the developer to ensure that the elemental function does not defeat data parallelization optimization (avoid global var manipulation, recursion). For reduce & scan, order is not guaranteed - the onus is on the dev to provide an elemental function that is commutative and associative so that scan will be deterministic – E.g. Sum is associative, but Avg is not. map Applies a provided elemental function to each element of the source array and stores the result in the corresponding position in the result array. The map method is shape preserving & index free - can not inspect neighboring values. // Adding one to each element. var source = new ParallelArray([1,2,3,4,5]); var plusOne = source.map(function inc(v) {     return v+1; }); //<2,3,4,5,6> combine Combine is similar to map, except an index is provided. This allows elemental functions to access elements from the source array relative to the one at the current index position. While the map method operates on the outermost dimension only, combine, can choose how deep to traverse - it provides a depth argument to specify the number of dimensions it iterates over. The elemental function of combine accesses the source array & the current index within it - element is computed by calling the get method of the source ParallelArray object with index i as argument. It requires more code but is more expressive. var source = new ParallelArray([1,2,3,4,5]); var plusOne = source.combine(function inc(i) { return this.get(i)+1; }); reduce reduces the elements from an array to a single scalar result – e.g. Sum. // Calculate the sum of the elements var source = new ParallelArray([1,2,3,4,5]); var sum = source.reduce(function plus(a,b) { return a+b; }); scan Like reduce, but stores the intermediate results – return a ParallelArray whose ith elements is the results of using the elemental function to reduce the elements between 0 and I in the original ParallelArray. // do a partial sum var source = new ParallelArray([1,2,3,4,5]); var psum = source.scan(function plus(a,b) { return a+b; }); //<1, 3, 6, 10, 15> scatter a reordering function - specify for a certain source index where it should be stored in the result array. An optional conflict function can prevent an exception if two source values are assigned the same position of the result: var source = new ParallelArray([1,2,3,4,5]); var reorder = source.scatter([4,0,3,1,2]); // <2, 4, 5, 3, 1> // if there is a conflict use the max. use 33 as a default value. var reorder = source.scatter([4,0,3,4,2], 33, function max(a, b) {return a>b?a:b; }); //<2, 33, 5, 3, 4> filter // filter out values that are not even var source = new ParallelArray([1,2,3,4,5]); var even = source.filter(function even(iv) { return (this.get(iv) % 2) == 0; }); // <2,4> Flatten used to collapse the outer dimensions of an array into a single dimension. pa = new ParallelArray([ [1,2], [3,4] ]); // <<1,2>,<3,4>> pa.flatten(); // <1,2,3,4> Partition used to restore the original shape of the array. var pa = new ParallelArray([1,2,3,4]); // <1,2,3,4> pa.partition(2); // <<1,2>,<3,4>> Get return value found at the indices or undefined if no such value exists. var pa = new ParallelArray([0,1,2,3,4], [10,11,12,13,14], [20,21,22,23,24]) pa.get([1,1]); // 11 pa.get([1]); // <10,11,12,13,14>

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  • parallel_for_each from amp.h – part 1

    - by Daniel Moth
    This posts assumes that you've read my other C++ AMP posts on index<N> and extent<N>, as well as about the restrict modifier. It also assumes you are familiar with C++ lambdas (if not, follow my links to C++ documentation). Basic structure and parameters Now we are ready for part 1 of the description of the new overload for the concurrency::parallel_for_each function. The basic new parallel_for_each method signature returns void and accepts two parameters: a grid<N> (think of it as an alias to extent) a restrict(direct3d) lambda, whose signature is such that it returns void and accepts an index of the same rank as the grid So it looks something like this (with generous returns for more palatable formatting) assuming we are dealing with a 2-dimensional space: // some_code_A parallel_for_each( g, // g is of type grid<2> [ ](index<2> idx) restrict(direct3d) { // kernel code } ); // some_code_B The parallel_for_each will execute the body of the lambda (which must have the restrict modifier), on the GPU. We also call the lambda body the "kernel". The kernel will be executed multiple times, once per scheduled GPU thread. The only difference in each execution is the value of the index object (aka as the GPU thread ID in this context) that gets passed to your kernel code. The number of GPU threads (and the values of each index) is determined by the grid object you pass, as described next. You know that grid is simply a wrapper on extent. In this context, one way to think about it is that the extent generates a number of index objects. So for the example above, if your grid was setup by some_code_A as follows: extent<2> e(2,3); grid<2> g(e); ...then given that: e.size()==6, e[0]==2, and e[1]=3 ...the six index<2> objects it generates (and hence the values that your lambda would receive) are:    (0,0) (1,0) (0,1) (1,1) (0,2) (1,2) So what the above means is that the lambda body with the algorithm that you wrote will get executed 6 times and the index<2> object you receive each time will have one of the values just listed above (of course, each one will only appear once, the order is indeterminate, and they are likely to call your code at the same exact time). Obviously, in real GPU programming, you'd typically be scheduling thousands if not millions of threads, not just 6. If you've been following along you should be thinking: "that is all fine and makes sense, but what can I do in the kernel since I passed nothing else meaningful to it, and it is not returning any values out to me?" Passing data in and out It is a good question, and in data parallel algorithms indeed you typically want to pass some data in, perform some operation, and then typically return some results out. The way you pass data into the kernel, is by capturing variables in the lambda (again, if you are not familiar with them, follow the links about C++ lambdas), and the way you use data after the kernel is done executing is simply by using those same variables. In the example above, the lambda was written in a fairly useless way with an empty capture list: [ ](index<2> idx) restrict(direct3d), where the empty square brackets means that no variables were captured. If instead I write it like this [&](index<2> idx) restrict(direct3d), then all variables in the some_code_A region are made available to the lambda by reference, but as soon as I try to use any of those variables in the lambda, I will receive a compiler error. This has to do with one of the direct3d restrictions, where only one type can be capture by reference: objects of the new concurrency::array class that I'll introduce in the next post (suffice for now to think of it as a container of data). If I write the lambda line like this [=](index<2> idx) restrict(direct3d), all variables in the some_code_A region are made available to the lambda by value. This works for some types (e.g. an integer), but not for all, as per the restrictions for direct3d. In particular, no useful data classes work except for one new type we introduce with C++ AMP: objects of the new concurrency::array_view class, that I'll introduce in the post after next. Also note that if you capture some variable by value, you could use it as input to your algorithm, but you wouldn’t be able to observe changes to it after the parallel_for_each call (e.g. in some_code_B region since it was passed by value) – the exception to this rule is the array_view since (as we'll see in a future post) it is a wrapper for data, not a container. Finally, for completeness, you can write your lambda, e.g. like this [av, &ar](index<2> idx) restrict(direct3d) where av is a variable of type array_view and ar is a variable of type array - the point being you can be very specific about what variables you capture and how. So it looks like from a large data perspective you can only capture array and array_view objects in the lambda (that is how you pass data to your kernel) and then use the many threads that call your code (each with a unique index) to perform some operation. You can also capture some limited types by value, as input only. When the last thread completes execution of your lambda, the data in the array_view or array are ready to be used in the some_code_B region. We'll talk more about all this in future posts… (a)synchronous Please note that the parallel_for_each executes as if synchronous to the calling code, but in reality, it is asynchronous. I.e. once the parallel_for_each call is made and the kernel has been passed to the runtime, the some_code_B region continues to execute immediately by the CPU thread, while in parallel the kernel is executed by the GPU threads. However, if you try to access the (array or array_view) data that you captured in the lambda in the some_code_B region, your code will block until the results become available. Hence the correct statement: the parallel_for_each is as-if synchronous in terms of visible side-effects, but asynchronous in reality.   That's all for now, we'll revisit the parallel_for_each description, once we introduce properly array and array_view – coming next. Comments about this post by Daniel Moth welcome at the original blog.

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  • BI Applications overview

    - by sv744
    Welcome to Oracle BI applications blog! This blog will talk about various features, general roadmap, description of functionality and implementation steps related to Oracle BI applications. In the first post we start with an overview of the BI apps and will delve deeper into some of the topics below in the upcoming weeks and months. If there are other topics you would like us to talk about, pl feel free to provide feedback on that. The Oracle BI applications are a set of pre-built applications that enable pervasive BI by providing role-based insight for each functional area, including sales, service, marketing, contact center, finance, supplier/supply chain, HR/workforce, and executive management. For example, Sales Analytics includes role-based applications for sales executives, sales management, as well as front-line sales reps, each of whom have different needs. The applications integrate and transform data from a range of enterprise sources—including Siebel, Oracle, PeopleSoft, SAP, and others—into actionable intelligence for each business function and user role. This blog  starts with the key benefits and characteristics of Oracle BI applications. In a series of subsequent blogs, each of these points will be explained in detail. Why BI apps? Demonstrate the value of BI to a business user, show reports / dashboards / model that can answer their business questions as part of the sales cycle. Demonstrate technical feasibility of BI project and significantly lower risk and improve success Build Vs Buy benefit Don’t have to start with a blank sheet of paper. Help consolidate disparate systems Data integration in M&A situations Insulate BI consumers from changes in the OLTP Present OLTP data and highlight issues of poor data / missing data – and improve data quality and accuracy Prebuilt Integrations BI apps support prebuilt integrations against leading ERP sources: Fusion Applications, E- Business Suite, Peoplesoft, JD Edwards, Siebel, SAP Co-developed with inputs from functional experts in BI and Applications teams. Out of the box dimensional model to source model mappings Multi source and Multi Instance support Rich Data Model    BI apps have a very rich dimensionsal data model built over 10 years that incorporates best practises from BI modeling perspective as well as reflect the source system complexities  Thanks for reading a long post, and be on the lookout for future posts.  We will look forward to your valuable feedback on these topics as well as suggestions on what other topics would you like us to cover. I Conformed dimensional model across all business subject areas allows cross functional reporting, e.g. customer / supplier 360 Over 360 fact tables across 7 product areas CRM – 145, SCM – 47, Financials – 28, Procurement – 20, HCM – 27, Projects – 18, Campus Solutions – 21, PLM - 56 Supported by 300 physical dimensions Support for extensive calendars; Gregorian, enterprise and ledger based Conformed data model and metrics for real time vs warehouse based reporting  Multi-tenant enabled Extensive BI related transformations BI apps ETL and data integration support various transformations required for dimensional models and reporting requirements. All these have been distilled into common patterns and abstracted logic which can be readily reused across different modules Slowly Changing Dimension support Hierarchy flattening support Row / Column Hybrid Hierarchy Flattening As Is vs. As Was hierarchy support Currency Conversion :-  Support for 3 corporate, CRM, ledger and transaction currencies UOM conversion Internationalization / Localization Dynamic Data translations Code standardization (Domains) Historical Snapshots Cycle and process lifecycle computations Balance Facts Equalization of GL accounting chartfields/segments Standardized values for categorizing GL accounts Reconciliation between GL and subledgers to track accounted/transferred/posted transactions to GL Materialization of data only available through costly and complex APIs e.g. Fusion Payroll, EBS / Fusion Accruals Complex event Interpretation of source data – E.g. o    What constitutes a transfer o    Deriving supervisors via position hierarchy o    Deriving primary assignment in PSFT o    Categorizing and transposition to measures of Payroll Balances to specific metrics to support side by side comparison of measures of for example Fixed Salary, Variable Salary, Tax, Bonus, Overtime Payments. o    Counting of Events – E.g. converting events to fact counters so that for example the number of hires can easily be added up and compared alongside the total transfers and terminations. Multi pass processing of multiple sources e.g. headcount, salary, promotion, performance to allow side to side comparison. Adding value to data to aid analysis through banding, additional domain classifications and groupings to allow higher level analytical reporting and data discovery Calculation of complex measures examples: o    COGs, DSO, DPO, Inventory turns  etc o    Transfers within a Hierarchy or out of / into a hierarchy relative to view point in hierarchy. Configurability and Extensibility support  BI apps offer support for extensibility for various entities as automated extensibility or part of extension methodology Key Flex fields and Descriptive Flex support  Extensible attribute support (JDE)  Conformed Domains ETL Architecture BI apps offer a modular adapter architecture which allows support of multiple product lines into a single conformed model Multi Source Multi Technology Orchestration – creates load plan taking into account task dependencies and customers deployment to generate a plan based on a customers of multiple complex etl tasks Plan optimization allowing parallel ETL tasks Oracle: Bit map indexes and partition management High availability support    Follow the sun support. TCO BI apps support several utilities / capabilities that help with overall total cost of ownership and ensure a rapid implementation Improved cost of ownership – lower cost to deploy On-going support for new versions of the source application Task based setups flows Data Lineage Functional setup performed in Web UI by Functional person Configuration Test to Production support Security BI apps support both data and object security enabling implementations to quickly configure the application as per the reporting security needs Fine grain object security at report / dashboard and presentation catalog level Data Security integration with source systems  Extensible to support external data security rules Extensive Set of KPIs Over 7000 base and derived metrics across all modules Time series calculations (YoY, % growth etc) Common Currency and UOM reporting Cross subject area KPIs (analyzing HR vs GL data, drill from GL to AP/AR, etc) Prebuilt reports and dashboards 3000+ prebuilt reports supporting a large number of industries Hundreds of role based dashboards Dynamic currency conversion at dashboard level Highly tuned Performance The BI apps have been tuned over the years for both a very performant ETL and dashboard performance. The applications use best practises and advanced database features to enable the best possible performance. Optimized data model for BI and analytic queries Prebuilt aggregates& the ability for customers to create their own aggregates easily on warehouse facts allows for scalable end user performance Incremental extracts and loads Incremental Aggregate build Automatic table index and statistics management Parallel ETL loads Source system deletes handling Low latency extract with Golden Gate Micro ETL support Bitmap Indexes Partitioning support Modularized deployment, start small and add other subject areas seamlessly Source Specfic Staging and Real Time Schema Support for source specific operational reporting schema for EBS, PSFT, Siebel and JDE Application Integrations The BI apps also allow for integration with source systems as well as other applications that provide value add through BI and enable BI consumption during operational decision making Embedded dashboards for Fusion, EBS and Siebel applications Action Link support Marketing Segmentation Sales Predictor Dashboard Territory Management External Integrations The BI apps data integration choices include support for loading extenral data External data enrichment choices : UNSPSC, Item class etc. Extensible Spend Classification Broad Deployment Choices Exalytics support Databases :  Oracle, Exadata, Teradata, DB2, MSSQL ETL tool of choice : ODI (coming), Informatica Extensible and Customizable Extensible architecture and Methodology to add custom and external content Upgradable across releases

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  • Installing OpenSSL that supports SNI along with previous version of OpenSSL

    - by gh0sT
    So I learned that to host multiple HTTPS websites on the same IP address you need an OpenSSL version that supports SNI (0.9.8f and higher). My RHEL5 box currently has 0.9.8e and Apache version httpd-2.2.26-2.el5. According to a same question here it's not a good idea to replace the original version of OpenSSL and instead to have a parallel installation. It however doesn't explicitly mention how to achieve this. So my questions are: How do I have an alternate installation of OpenSSL without breaking the system? How do I make Apache to use this version of OpenSSL and not the original one? A detailed guide would be extremely helpful.

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  • What is the difference between Windows RT and Windows Phone 8?

    - by Rakib Ansary
    From what I have read it seems there are more or less three versions(?) of Windows 8: Windows 8, Windows RT, and Windows Phone 8. While the difference between Windows 8 and Windows RT is clear, I don't understand the difference between Windows RT and Windows Phone 8. The Android parallel, Jelly Bean that runs on Tablets and on Phones doesn't have any differences. Are there any differences between Windows RT and Windows Phone 8 except for the fact that one is for Tablets (Windows RT) and the other is for Phones (Windows Phone 8)?

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  • WinXP How to Tunnel LPT over USB

    - by Michael Pruitt
    I have a windows program that accesses a device connected to a LPT (1-3) 25 pin port. The communication is bidirectional, and I suspected the control lines are also accessed directly. I would like to migrate the device to a machine that does not have a LPT port. I saw the dos2usb software, but that takes the output (from a DOS program) and 'prints' it formatted for a specific printer. I need a raw LPT connection, and a cable that provides access to all the control signals. I do have a USB to 36-pin Centronics that may have the extra signals. I use it with a vinyl cutter that doesn't like most of the USB dongles. It comes up as USB001. Would adding and sharing a generic printer, then mapping LPT1 to the share get me closer? Would that work for a parallel port scanner? My preferred solution is a USB cable with a driver that will map it to LPT1, LPT2, or LPT3.

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