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  • linux is runing slow

    - by karan
    I am using open suse 11.3 .my laptop is running to slow and dmesg is showing following error: 733.162161] psmouse.c: TouchPad at isa0060/serio4/input0 lost synchronization, throwing 5 bytes away. [ 774.230841] psmouse.c: TouchPad at isa0060/serio4/input0 lost synchronization, throwing 2 bytes away. [ 856.344570] psmouse.c: TouchPad at isa0060/serio4/input0 lost synchronization, throwing 1 bytes away. [ 898.451626] psmouse.c: TouchPad at isa0060/serio4/input0 lost synchronization, throwing 1 bytes away. is there any way i could see the problem and solve it....

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  • SQL SERVER – Extending SQL Azure with Azure worker role – Guest Post by Paras Doshi

    - by pinaldave
    This is guest post by Paras Doshi. Paras Doshi is a research Intern at SolidQ.com and a Microsoft student partner. He is currently working in the domain of SQL Azure. SQL Azure is nothing but a SQL server in the cloud. SQL Azure provides benefits such as on demand rapid provisioning, cost-effective scalability, high availability and reduced management overhead. To see an introduction on SQL Azure, check out the post by Pinal here In this article, we are going to discuss how to extend SQL Azure with the Azure worker role. In other words, we will attempt to write a custom code and host it in the Azure worker role; the aim is to add some features that are not available with SQL Azure currently or features that need to be customized for flexibility. This way we extend the SQL Azure capability by building some solutions that run on Azure as worker roles. To understand Azure worker role, think of it as a windows service in cloud. Azure worker role can perform background processes, and to handle processes such as synchronization and backup, it becomes our ideal tool. First, we will focus on writing a worker role code that synchronizes SQL Azure databases. Before we do so, let’s see some scenarios in which synchronization between SQL Azure databases is beneficial: scaling out access over multiple databases enables us to handle workload efficiently As of now, SQL Azure database can be hosted in one of any six datacenters. By synchronizing databases located in different data centers, one can extend the data by enabling access to geographically distributed data Let us see some scenarios in which SQL server to SQL Azure database synchronization is beneficial To backup SQL Azure database on local infrastructure Rather than investing in local infrastructure for increased workloads, such workloads could be handled by cloud Ability to extend data to different datacenters located across the world to enable efficient data access from remote locations Now, let us develop cloud-based app that synchronizes SQL Azure databases. For an Introduction to developing cloud based apps, click here Now, in this article, I aim to provide a bird’s eye view of how a code that synchronizes SQL Azure databases look like and then list resources that can help you develop the solution from scratch. Now, if you newly add a worker role to the cloud-based project, this is how the code will look like. (Note: I have added comments to the skeleton code to point out the modifications that will be required in the code to carry out the SQL Azure synchronization. Note the placement of Setup() and Sync() function.) Click here (http://parasdoshi1989.files.wordpress.com/2011/06/code-snippet-1-for-extending-sql-azure-with-azure-worker-role1.pdf ) Enabling SQL Azure databases synchronization through sync framework is a two-step process. In the first step, the database is provisioned and sync framework creates tracking tables, stored procedures, triggers, and tables to store metadata to enable synchronization. This is one time step. The code for the same is put in the setup() function which is called once when the worker role starts. Now, the second step is continuous (or on demand) synchronization of SQL Azure databases by propagating changes between databases. This is done on a continuous basis by calling the sync() function in the while loop. The code logic to synchronize changes between SQL Azure databases should be put in the sync() function. Discussing the coding part step by step is out of the scope of this article. Therefore, let me suggest you a resource, which is given here. Also, note that before you start developing the code, you will need to install SYNC framework 2.1 SDK (download here). Further, you will reference some libraries before you start coding. Details regarding the same are available in the article that I just pointed to. You will be charged for data transfers if the databases are not in the same datacenter. For pricing information, go here Currently, a tool named DATA SYNC, which is built on top of sync framework, is available in CTP that allows SQL Azure <-> SQL server and SQL Azure <-> SQL Azure synchronization (without writing single line of code); however, in some cases, the custom code shown in this blogpost provides flexibility that is not available with Data SYNC. For instance, filtering is not supported in the SQL Azure DATA SYNC CTP2; if you wish to have such a functionality now, then you have the option of developing a custom code using SYNC Framework. Now, this code can be easily extended to synchronize at some schedule. Let us say we want the databases to get synchronized every day at 10:00 pm. This is what the code will look like now: (http://parasdoshi1989.files.wordpress.com/2011/06/code-snippet-2-for-extending-sql-azure-with-azure-worker-role.pdf) Don’t you think that by writing such a code, we are imitating the functionality provided by the SQL server agent for a SQL server? Think about it. We are scheduling our administrative task by writing custom code – in other words, we have developed a “Light weight SQL server agent for SQL Azure!” Since the SQL server agent is not currently available in cloud, we have developed a solution that enables us to schedule tasks, and thus we have extended SQL Azure with the Azure worker role! Now if you wish to track jobs, you can do so by storing this data in SQL Azure (or Azure tables). The reason is that Windows Azure is a stateless platform, and we will need to store the state of the job ourselves and the choice that you have is SQL Azure or Azure tables. Note that this solution requires custom code and also it is not UI driven; however, for now, it can act as a temporary solution until SQL server agent is made available in the cloud. Moreover, this solution does not encompass functionalities that a SQL server agent provides, but it does open up an interesting avenue to schedule some of the tasks such as backup and synchronization of SQL Azure databases by writing some custom code in the Azure worker role. Now, let us see one more possibility – i.e., running BCP through a worker role in Azure-hosted services and then uploading the backup files either locally or on blobs. If you upload it locally, then consider the data transfer cost. If you upload it to blobs residing in the same datacenter, then no transfer cost applies but the cost on blob size applies. So, before choosing the option, you need to evaluate your preferences keeping the cost associated with each option in mind. In this article, I have shown that Azure worker role solution could be developed to synchronize SQL Azure databases. Moreover, a light-weight SQL server agent for SQL Azure can be developed. Also we discussed the possibility of running BCP through a worker role in Azure-hosted services for backing up our precious SQL Azure data. Thus, we can extend SQL Azure with the Azure worker role. But remember: you will be charged for running Azure worker roles. So at the end of the day, you need to ask – am I willing to build a custom code and pay money to achieve this functionality? I hope you found this blog post interesting. If you have any questions/feedback, you can comment below or you can mail me at Paras[at]student-partners[dot]com Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Azure, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Change AccountName/LoginName for a SharePoint User (SPUser)

    - by Rohit Gupta
    Consider the following: We have an account named MYDOMAIN\eholz. This accounts Active Directory Login Name changes to MYDOMAIN\eburrell Now this user was a active user in a Sharepoint 2010 team Site, and had a userProfile using the Account name MYDOMAIN\eholz. Since the AD LoginName changed to eburrell hence we need to update the Sharepoint User (SPUser object) as well update the userprofile to reflect the new account name. To update the Sharepoint User LoginName we can run the following stsadm command on the Server: STSADM –o migrateuser –oldlogin MYDOMAIN\eholz –newlogin MYDOMAIN\eburrell –ignoresidhistory However to update the Sharepoint 2010 UserProfile, i first tried running a Incremental/Full Synchronization using the User Profile Synchronization service… this did not work. To enable me to update the AccountName field (which is a read only field) of the UserProfile, I had to first delete the User Profile for MYDOMAIN\eholz and then run a FULL Synchronization using the User Profile Synchronization service which synchronizes the Sharepoint User Profiles with the AD profiles.

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  • What can be done to improve time synchronization on networks with sporadic internet access?

    - by anregen
    I'm looking for advice setting up time servers for a very non-typical network. I support many closed networks that have occasional access to the internet. A network would get access most days for a few hours, but would frequently go 1-3 weeks blacked-out. The computers/servers on this network are mostly *nix-based, but not all the same flavor. The entire network is mobile, so when it connects, it will have very different hops/latency to internet time servers. The servers on the closed network are powered-off frequently (at least daily). Right now, my gut tells me to use NTP (because I hate re-learning all the stuff that someone else already got working pretty well). But I have several issues, and am looking for someone with experience in this type of strange situation. I currently have no solution in place, I'm simply letting the internal clocks drift. This results in errors of ~600s in a majority of networks. I have seen mismatch worse than 10,000s. Is there something "better" than NTP in this situation? I know NTP likes to have very frequent, consistent access to servers that give nearly identical answers. I won't have that. How many internal NTP servers should I configure, so that during periods of internet blackout, I have internal time that is consistent within the closed network? There is no human access. No matter how large the mismatch, the server(s) must attempt to correct itself. Discrete steps are very bad. No matter how large the mismatch, the correction must be "slewed", not "stepped". I understand that this could take many hours to correct.

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  • Can getAttribute() method of Tomcat ServletContext implementation be called without synchronization?

    - by oo_olo_oo
    I would like to read some parameters during servlet initializtion (in init() method), and store them among servlet context attributes (using getServletContext().setAttribute()). I would like to read these parameters later - during some request processing (using getServletContext().getAttribute()). So, the multiple threads could do this simultaneously. My question is if such an attempt is safe? Could I be sure that multi threaded calls to the getAttribute() don't mess up any internal state of the servlet context? Please take into account that I'm not going to call the setAttribute() anywhere besides the initialization. So, only calls to the getAttribute() are going to be done from multiple threads. But depending on the internal implementation, this also could be dangerous. So, any information about Tomcat's implementation would be appreciated.

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  • How to implement this .NET client and PHP server synchronization scenario?

    - by pbean
    I have a PHP webserver and a .NET mobile application. The .NET application needs data from a database, which is provided (for now) by the php webserver. I'm fairly new to this kind of scenario so I'm not sure what the best practices are. I ran into a couple of problems and I am not certain how to overcome them. For now, I have the following setup. I run a PHP SOAP server which has a couple of operations which simply retrieve data from the database. For this web service I have created a WSDL file. In Visual Studio I added a web reference to my project using the WSDL file and it generated some classes for it. I simply call something like "MyWebService.GetItems();" and I get an array of items in my .NET application, which come straight from the database. Next I also serialize all these retrieved objects to local (permanent) storage. I face a couple of challenges which I don't know how to resolve properly. The idea is for the mobile client to synchronize the data once (at the start of the day), before working, and then use the local storage throughout the day, and synchronize it back at the end of the day. At the moment all data is downloaded through SOAP, and not a subset (only what is needed). How would I know which new information should be sent to the client? Only the server knows what is new, but only the client knows for sure which data it already has. I seem to be doing double work now. The data which is transferred with SOAP basically already are serialized objects. But at the moment I first retrieve all objects through SOAP and the .NET framework automatically deserializes it. Then I serialize all data again myself. It would be more efficient to simply download it to storage, and then deserialize it. The mobile device does not have a lot of memory. In my test data this is not really a problem, but with potentially tenths of thousands of records I can imagine this will become a problem. Currently when I call the SOAP method, it loads all data into memory (as an array) but as described above perhaps it would be better to have it stored into storage directly, and only retrieve from storage the objects that are needed. But how would I store this? An array would serialize to one big XML (or binary) file from which I cannot choose which objects to load. Would I make (possible tenths of thousands) separate files? Also at the end of the day when I want to send the changes back to the server, how would I know which objects to send... since they're not in memory? I hope my troubles are clear and I hope you are able to help me figure out how to implement this the best way. :) Some things are already fixed (like using .NET on the mobile device, using PHP and having a MySQL database server) but other things can most certainly be changed (like using SOAP).

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  • tile_static, tile_barrier, and tiled matrix multiplication with C++ AMP

    - by Daniel Moth
    We ended the previous post with a mechanical transformation of the C++ AMP matrix multiplication example to the tiled model and in the process introduced tiled_index and tiled_grid. This is part 2. tile_static memory You all know that in regular CPU code, static variables have the same value regardless of which thread accesses the static variable. This is in contrast with non-static local variables, where each thread has its own copy. Back to C++ AMP, the same rules apply and each thread has its own value for local variables in your lambda, whereas all threads see the same global memory, which is the data they have access to via the array and array_view. In addition, on an accelerator like the GPU, there is a programmable cache, a third kind of memory type if you'd like to think of it that way (some call it shared memory, others call it scratchpad memory). Variables stored in that memory share the same value for every thread in the same tile. So, when you use the tiled model, you can have variables where each thread in the same tile sees the same value for that variable, that threads from other tiles do not. The new storage class for local variables introduced for this purpose is called tile_static. You can only use tile_static in restrict(direct3d) functions, and only when explicitly using the tiled model. What this looks like in code should be no surprise, but here is a snippet to confirm your mental image, using a good old regular C array // each tile of threads has its own copy of locA, // shared among the threads of the tile tile_static float locA[16][16]; Note that tile_static variables are scoped and have the lifetime of the tile, and they cannot have constructors or destructors. tile_barrier In amp.h one of the types introduced is tile_barrier. You cannot construct this object yourself (although if you had one, you could use a copy constructor to create another one). So how do you get one of these? You get it, from a tiled_index object. Beyond the 4 properties returning index objects, tiled_index has another property, barrier, that returns a tile_barrier object. The tile_barrier class exposes a single member, the method wait. 15: // Given a tiled_index object named t_idx 16: t_idx.barrier.wait(); 17: // more code …in the code above, all threads in the tile will reach line 16 before a single one progresses to line 17. Note that all threads must be able to reach the barrier, i.e. if you had branchy code in such a way which meant that there is a chance that not all threads could reach line 16, then the code above would be illegal. Tiled Matrix Multiplication Example – part 2 So now that we added to our understanding the concepts of tile_static and tile_barrier, let me obfuscate rewrite the matrix multiplication code so that it takes advantage of tiling. Before you start reading this, I suggest you get a cup of your favorite non-alcoholic beverage to enjoy while you try to fully understand the code. 01: void MatrixMultiplyTiled(vector<float>& vC, const vector<float>& vA, const vector<float>& vB, int M, int N, int W) 02: { 03: static const int TS = 16; 04: array_view<const float,2> a(M, W, vA); 05: array_view<const float,2> b(W, N, vB); 06: array_view<writeonly<float>,2> c(M,N,vC); 07: parallel_for_each(c.grid.tile< TS, TS >(), 08: [=] (tiled_index< TS, TS> t_idx) restrict(direct3d) 09: { 10: int row = t_idx.local[0]; int col = t_idx.local[1]; 11: float sum = 0.0f; 12: for (int i = 0; i < W; i += TS) { 13: tile_static float locA[TS][TS], locB[TS][TS]; 14: locA[row][col] = a(t_idx.global[0], col + i); 15: locB[row][col] = b(row + i, t_idx.global[1]); 16: t_idx.barrier.wait(); 17: for (int k = 0; k < TS; k++) 18: sum += locA[row][k] * locB[k][col]; 19: t_idx.barrier.wait(); 20: } 21: c[t_idx.global] = sum; 22: }); 23: } Notice that all the code up to line 9 is the same as per the changes we made in part 1 of tiling introduction. If you squint, the body of the lambda itself preserves the original algorithm on lines 10, 11, and 17, 18, and 21. The difference being that those lines use new indexing and the tile_static arrays; the tile_static arrays are declared and initialized on the brand new lines 13-15. On those lines we copy from the global memory represented by the array_view objects (a and b), to the tile_static vanilla arrays (locA and locB) – we are copying enough to fit a tile. Because in the code that follows on line 18 we expect the data for this tile to be in the tile_static storage, we need to synchronize the threads within each tile with a barrier, which we do on line 16 (to avoid accessing uninitialized memory on line 18). We also need to synchronize the threads within a tile on line 19, again to avoid the race between lines 14, 15 (retrieving the next set of data for each tile and overwriting the previous set) and line 18 (not being done processing the previous set of data). Luckily, as part of the awesome C++ AMP debugger in Visual Studio there is an option that helps you find such races, but that is a story for another blog post another time. May I suggest reading the next section, and then coming back to re-read and walk through this code with pen and paper to really grok what is going on, if you haven't already? Cool. Why would I introduce this tiling complexity into my code? Funny you should ask that, I was just about to tell you. There is only one reason we tiled our extent, had to deal with finding a good tile size, ensure the number of threads we schedule are correctly divisible with the tile size, had to use a tiled_index instead of a normal index, and had to understand tile_barrier and to figure out where we need to use it, and double the size of our lambda in terms of lines of code: the reason is to be able to use tile_static memory. Why do we want to use tile_static memory? Because accessing tile_static memory is around 10 times faster than accessing the global memory on an accelerator like the GPU, e.g. in the code above, if you can get 150GB/second accessing data from the array_view a, you can get 1500GB/second accessing the tile_static array locA. And since by definition you are dealing with really large data sets, the savings really pay off. We have seen tiled implementations being twice as fast as their non-tiled counterparts. Now, some algorithms will not have performance benefits from tiling (and in fact may deteriorate), e.g. algorithms that require you to go only once to global memory will not benefit from tiling, since with tiling you already have to fetch the data once from global memory! Other algorithms may benefit, but you may decide that you are happy with your code being 150 times faster than the serial-version you had, and you do not need to invest to make it 250 times faster. Also algorithms with more than 3 dimensions, which C++ AMP supports in the non-tiled model, cannot be tiled. Also note that in future releases, we may invest in making the non-tiled model, which already uses tiling under the covers, go the extra step and use tile_static memory on your behalf, but it is obviously way to early to commit to anything like that, and we certainly don't do any of that today. Comments about this post by Daniel Moth welcome at the original blog.

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  • Change AccountName/LoginName for a SharePoint User (SPUser)

    - by Rohit Gupta
    Consider the following: We have an account named MYDOMAIN\eholz. This accounts Active Directory Login Name changes to MYDOMAIN\eburrell Now this user was a active user in a Sharepoint 2010 team Site, and had a userProfile using the Account name MYDOMAIN\eholz. Since the AD LoginName changed to eburrell hence we need to update the Sharepoint User (SPUser object) as well update the userprofile to reflect the new account name. To update the Sharepoint User LoginName we can run the following stsadm command on the Server: STSADM –o migrateuser –oldlogin MYDOMAIN\eholz –newlogin MYDOMAIN\eburrell –ignoresidhistory However to update the Sharepoint 2010 UserProfile, i first tried running a Incremental/Full Synchronization using the User Profile Synchronization service… this did not work. To enable me to update the AccountName field (which is a read only field) of the UserProfile, I had to first delete the User Profile for MYDOMAIN\eholz and then run a FULL Synchronization using the User Profile Synchronization service which synchronizes the Sharepoint User Profiles with the AD profiles. Update: if you just run the STSADM –o migrateuser command… the profile also gets updated automatically. so all you need is to run the stsadm –o migrate user command and you dont need to delete and recreate the User Profile

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  • Getting a handle on mobile data

    - by Eric Jensen
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} written by Ashok Joshi The proliferation of mobile devices in the corporate world is both a blessing as well as a challenge.  Mobile devices improve productivity and the velocity of business for the end users; on the other hand, IT departments need to manage the corporate data and applications that run on these devices. Oracle Database Mobile Server (DMS for short) provides a simple and effective way to deal with the management challenge.  DMS supports data synchronization between a central Oracle database server and data on mobile devices.  It also provides authentication, encryption and application and device management.  Finally, DMS is a highly scalable solution that can be used to manage hundreds of thousands of devices.   Here’s a simplified outline of how such a solution might work. Each device runs local sync and mgmt agents that handle bidirectional data flow with an Oracle enterprise backend, run remote commands, and provide status to the management console. For example, mobile admins could monitor multiple networks of mobile devices, upgrade their software remotely, and even destroy the local database on a compromised device. DMS supports either Oracle Berkeley DB or SQLite for device-local storage, and runs on a wide variety of mobile platforms. The schema for the device-local database is pretty simple – it contains the name of the application that’s installed on the device as well as details such as product name, version number, time of last access etc. Each mobile user has an account on the monitoring system.  DMS supports authentication via the Oracle database authentication mechanisms or alternately, via an external authentication server such as Oracle Identity Management. DMS also provides the option of encrypting the data on disk as well as while it is being synchronized. Whenever a device connects with DMS, it sends the list of all local application changes to the server; the server updates the central repository with this information.  Synchronization can be triggered on-demand, whenever there’s a change on the device (e.g. new application installed or an existing application removed) or via a rule-based schedule (e.g. every Saturday). Synchronization is very fast and efficient, since only the changes are propagated.  This includes resume capability; should synchronization be interrupted for any reason, the next synchronization will resume where the previous synchronization was interrupted. If the device should be lost or stolen, DMS has the capability to remove the applications and/or data from the device. This ability to control access to sensitive data and applications is critical in the corporate environment. The central repository also allows the IT manager to track the kinds of applications that mobile users use and recommend patches and upgrades, while still allowing the mobile user full control over what applications s/he downloads and uses on the device.  This is useful since most devices are used for corporate as well as personal information. In certain restricted use scenarios, the IT manager can also control whether a certain application can be installed on a mobile device.  Should an unapproved application be installed, it can easily be removed the next time the device connects with the central server. Oracle Database mobile server provides a simple, effective and highly secure and scalable solution for managing the data and applications for the mobile workforce.

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  • SQL SERVER – Integrate Your Data with Skyvia – Cloud ETL Solution

    - by Pinal Dave
    In our days data integration often becomes a key aspect of business success. For business analysts it’s very important to get integrated data from various sources, such as relational databases, cloud CRMs, etc. to make correct and successful decisions. There are various data integration solutions on market, and today I will tell about one of them – Skyvia. Skyvia is a cloud data integration service, which allows integrating data in cloud CRMs and different relational databases. It is a completely online solution and does not require anything except for a browser. Skyvia provides powerful etl tools for data import, export, replication, and synchronization for SQL Server and other databases and cloud CRMs. You can use Skyvia data import tools to load data from various sources to SQL Server (and SQL Azure). Skyvia supports such cloud CRMs as Salesforce and Microsoft Dynamics CRM and such databases as MySQL and PostgreSQL. You even can migrate data from SQL Server to SQL Server, or from SQL Server to other databases and cloud CRMs. Additionally Skyvia supports import of CSV files, either uploaded manually or stored on cloud file storage services, such as Dropbox, Box, Google Drive, or FTP servers. When data import is not enough, Skyvia offers bidirectional data synchronization. With this tool, you can synchronize SQL Server data with other databases and cloud CRMs. After performing the first synchronization, Skyvia tracks data changes in the synchronized data storages. In SQL Server databases (and other relational databases) it creates additional tracking tables and triggers. This allows synchronizing only the changed data. Skyvia also maps records by their primary key values to each other, so it does not require different sources to have the same primary key structure. It still can match the corresponding records without having to add any additional columns or changing data structure. The only requirement for synchronization is that primary keys must be autogenerated. With Skyvia it’s not necessary for data to have the same structure in integrated data storages. Skyvia supports powerful mapping mechanisms that allow synchronizing data with completely different structure. It provides support for complex mathematical and string expressions when mapping data, using lookups, etc. You may use data splitting – loading data from a single CSV file or source table to multiple related target tables. Or you may load data from several source CSV files or tables to several related target tables. In each case Skyvia preserves data relations. It builds corresponding relations between the target data automatically. When you often work with cloud CRM data, native CRM data reporting and analysis tools may be not enough for you. And there is a vast set of professional data analysis and reporting tools available for SQL Server. With Skyvia you can quickly copy your cloud CRM data to an SQL Server database and apply corresponding SQL Server tools to the data. In such case you can use Skyvia data replication tools. It allows you to quickly copy cloud CRM data to SQL Server or other databases without customizing any mapping. You need just to specify columns to copy data from. Target database tables will be created automatically. Skyvia offers powerful filtering settings to replicate only the records you need. Skyvia also provides capability to export data from SQL Server (including SQL Azure) and other databases and cloud CRMs to CSV files. These files can be either downloadable manually or loaded to cloud file storages or FTP server. You can use export, for example, to backup SQL Azure data to Dropbox. Any data integration operation can be scheduled for automatic execution. Thus, you can automate your SQL Azure data backup or data synchronization – just configure it once, then schedule it, and benefit from automatic data integration with Skyvia. Currently registration and using Skyvia is completely free, so you can try it yourself and find out whether its data migration and integration tools suits for you. Visit this link to register on Skyvia: https://app.skyvia.com/register Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Cloud Computing

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  • BizTalk: History of one project architecture

    - by Leonid Ganeline
    "In the beginning God made heaven and earth. Then he started to integrate." At the very start was the requirement: integrate two working systems. Small digging up: It was one system. It was good but IT guys want to change it to the new one, much better, chipper, more flexible, and more progressive in technologies, more suitable for the future, for the faster world and hungry competitors. One thing. One small, little thing. We cannot turn off the old system (call it A, because it was the first), turn on the new one (call it B, because it is second but not the last one). The A has a hundreds users all across a country, they must study B. A still has a lot nice custom features, home-made features that cannot disappear. These features have to be moved to the B and it is a long process, months and months of redevelopment. So, the decision was simple. Let’s move not jump, let’s both systems working side-by-side several months. In this time we could teach the users and move all custom A’s special functionality to B. That automatically means both systems should work side-by-side all these months and use the same data. Data in A and B must be in sync. That’s how the integration projects get birth. Moreover, the specific of the user tasks requires the both systems must be in sync in real-time. Nightly synchronization is not working, absolutely.   First draft The first draft seems simple. Both systems keep data in SQL databases. When data changes, the Create, Update, Delete operations performed on the data, and the sync process could be started. The obvious decision is to use triggers on tables. When we are talking about data, we are talking about several entities. For example, Orders and Items [in Orders]. We decided to use the BizTalk Server to synchronize systems. Why it was chosen is another story. Second draft   Let’s take an example how it works in more details. 1.       User creates a new entity in the A system. This fires an insert trigger on the entity table. Trigger has to pass the message “Entity created”. This message includes all attributes of the new entity, but I focused on the Id of this entity in the A system. Notation for this message is id.A. System A sends id.A to the BizTalk Server. 2.       BizTalk transforms id.A to the format of the system B. This is easiest part and I will not focus on this kind of transformations in the following text. The message on the picture is still id.A but it is in slightly different format, that’s why it is changing in color. BizTalk sends id.A to the system B. 3.       The system B creates the entity on its side. But it uses different id-s for entities, these id-s are id.B. System B saves id.A+id.B. System B sends the message id.A+id.B back to the BizTalk. 4.       BizTalk sends the message id.A+id.B to the system A. 5.       System A saves id.A+id.B. Why both id-s should be saved on both systems? It was one of the next requirements. Users of both systems have to know the systems are in sync or not in sync. Users working with the entity on the system A can see the id.B and use it to switch to the system B and work there with the copy of the same entity. The decision was to store the pairs of entity id-s on both sides. If there is only one id, the entities are not in sync yet (for the Create operation). Third draft Next problem was the reliability of the synchronization. The synchronizing process can be interrupted on each step, when message goes through the wires. It can be communication problem, timeout, temporary shutdown one of the systems, the second system cannot be synchronized by some internal reason. There were several potential problems that prevented from enclosing the whole synchronization process in one transaction. Decision was to restart the whole sync process if it was not finished (in case of the error). For this purpose was created an additional service. Let’s call it the Resync service. We still keep the id pairs in both systems, but only for the fast access not for the synchronization process. For the synchronizing these id-s now are kept in one main place, in the Resync service database. The Resync service keeps record as: ·       Id.A ·       Id.B ·       Entity.Type ·       Operation (Create, Update, Delete) ·       IsSyncStarted (true/false) ·       IsSyncFinished (true/false0 The example now looks like: 1.       System A creates id.A. id.A is saved on the A. Id.A is sent to the BizTalk. 2.       BizTalk sends id.A to the Resync and to the B. id.A is saved on the Resync. 3.       System B creates id.B. id.A+id.B are saved on the B. id.A+id.B are sent to the BizTalk. 4.       BizTalk sends id.A+id.B to the Resync and to the A. id.A+id.B are saved on the Resync. 5.       id.A+id.B are saved on the B. Resync changes the IsSyncStarted and IsSyncFinished flags accordingly. The Resync service implements three main methods: ·       Save (id.A, Entity.Type, Operation) ·       Save (id.A, id.B, Entity.Type, Operation) ·       Resync () Two Save() are used to save id-s to the service storage. See in the above example, in 2 and 4 steps. What about the Resync()? It is the method that finishes the interrupted synchronization processes. If Save() is started by the trigger event, the Resync() is working as an independent process. It periodically scans the Resync storage to find out “unfinished” records. Then it restarts the synchronization processes. It tries to synchronize them several times then gives up.     One more thing, both systems A and B must tolerate duplicates of one synchronizing process. Say on the step 3 the system B was not able to send id.A+id.B back. The Resync service must restart the synchronization process that will send the id.A to B second time. In this case system B must just send back again also created id.A+id.B pair without errors. That means “tolerate duplicates”. Fourth draft Next draft was created only because of the aesthetics. As it always happens, aesthetics gave significant performance gain to the whole system. First was the stupid question. Why do we need this additional service with special database? Can we just master the BizTalk to do something like this Resync() does? So the Resync orchestration is doing the same thing as the Resync service. It is started by the Id.A and finished by the id.A+id.B message. The first works as a Start message, the second works as a Finish message.     Here is a diagram the whole process without errors. It is pretty straightforward. The Resync orchestration is waiting for the Finish message specific period of time then resubmits the Id.A message. It resubmits the Id.A message specific number of times then gives up and gets suspended. It can be resubmitted then it starts the whole process again: waiting [, resubmitting [, get suspended]], finishing. Tuning up The Resync orchestration resubmits the id.A message with special “Resubmitted” flag. The subscription filter on the Resync orchestration includes predicate as (Resubmit_Flag != “Resubmitted”). That means only the first Sync orchestration starts the Resync orchestration. Other Sync orchestration instantiated by the resubmitting can finish this Resync orchestration but cannot start another instance of the Resync   Here is a diagram where system B was inaccessible for some period of time. The Resync orchestration resubmitted the id.A two times. Then system B got the response the id.A+id.B and this finished the Resync service execution. What is interesting about this, there were submitted several identical id.A messages and only one id.A+id.B message. Because of this, the system B and the Resync must tolerate the duplicate messages. We also told about this requirement for the system B. Now the same requirement is for the Resunc. Let’s assume the system B was very slow in the first response and the Resync service had time to resubmit two id.A messages. System B responded not, as it was in previous case, with one id.A+id.B but with two id.A+id.B messages. First of them finished the Resync execution for the id.A. What about the second id.A+id.B? Where it goes? So, we have to add one more internal requirement. The whole solution must tolerate many identical id.A+id.B messages. It is easy task with the BizTalk. I added the “SinkExtraMessages” subscriber (orchestration with one receive shape), that just get these messages and do nothing. Real design Real architecture is much more complex and interesting. In reality each system can submit several id.A almost simultaneously and completely unordered. There are not only the “Create entity” operation but the Update and Delete operations. And these operations relate each other. Say the Update operation after Delete means not the same as Update after Create. In reality there are entities related each other. Say the Order and Order Items. Change on one of it could start the series of the operations on another. Moreover, the system internals are the “black boxes” and we cannot predict the exact content and order of the operation series. It worth to say, I had to spend a time to manage the zombie message problems. The zombies are still here, but this is not a problem now. And this is another story. What is interesting in the last design? One orchestration works to help another to be more reliable. Why two orchestration design is more reliable, isn’t it something strange? The Synch orchestration takes all the message exchange between systems, here is the area where most of the errors could happen. The Resync orchestration sends and receives messages only within the BizTalk server. Is there another design? Sure. All Resync functionality could be implemented inside the Sync orchestration. Hey guys, some other ideas?

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  • global static boolean pointer causes segmentation fault using pthread

    - by asksw0rder
    New to pthread programming, and stuck on this error when working on a C++&C mixed code. What I have done is to call the c code in the thread created by the c++ code. There is a static boolean pointer used in the thread and should got free when the thread finishes. However I noticed that every time when the program processed into the c function, the value of the boolean pointer would be changed and the segmentation fault then happened due to the free(). Detail code is as follows: static bool *is_center; // omit other codes in between ... void streamCluster( PStream* stream) { // some code here ... while(1){ // some code here ... is_center = (bool*)calloc(points.num,sizeof(bool)); // start the parallel thread here. // the c code is invoked in this function. localSearch(&points,kmin, kmax,&kfinal); // parallel free(is_center); } And the function using parallel is as follows (my c code is invoked in each thread): void localSearch( Points* points, long kmin, long kmax, long* kfinal ) { pthread_barrier_t barrier; pthread_t* threads = new pthread_t[nproc]; pkmedian_arg_t* arg = new pkmedian_arg_t[nproc]; pthread_barrier_init(&barrier,NULL,nproc); for( int i = 0; i < nproc; i++ ) { arg[i].points = points; arg[i].kmin = kmin; arg[i].kmax = kmax; arg[i].pid = i; arg[i].kfinal = kfinal; arg[i].barrier = &barrier; pthread_create(threads+i,NULL,localSearchSub,(void*)&arg[i]); } for ( int i = 0; i < nproc; i++) { pthread_join(threads[i],NULL); } delete[] threads; delete[] arg; pthread_barrier_destroy(&barrier); } Finally the function calling my c code: void* localSearchSub(void* arg_) { // omit some initialize code... // my code begin_papi_thread(&eventSet); // Processing k-means, omit codes. // is_center value will be updated correctly // my code end_papi_thread(&eventSet); // when jumping into this, error happens return NULL; } And from gdb, what I have got for the is_center is: Breakpoint 2, localSearchSub (arg_=0x600000000000bc40) at streamcluster.cpp:1711 1711 end_papi_thread(&eventSet); (gdb) s Hardware watchpoint 1: is_center Old value = (bool *) 0x600000000000bba0 New value = (bool *) 0xa93f3 0x400000000000d8d1 in localSearchSub (arg_=0x600000000000bc40) at streamcluster.cpp:1711 1711 end_papi_thread(&eventSet); Any suggestions? Thanks in advance!

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  • Using shared_ptr to implement RCU (read-copy-update)?

    - by yongsun
    I'm very interested in the user-space RCU (read-copy-update), and trying to simulate one via tr1::shared_ptr, here is the code, while I'm really a newbie in concurrent programming, would some experts help me to review? The basic idea is, reader calls get_reading_copy() to gain the pointer of current protected data (let's say it's generation one, or G1). writer calls get_updating_copy() to gain a copy of the G1 (let's say it's G2), and only one writer is allowed to enter the critical section. After the updating is done, writer calls update() to do a swap, and make the m_data_ptr pointing to data G2. The ongoing readers and the writer now hold the shared_ptr of G1, and either a reader or a writer will eventually deallocate the G1 data. Any new readers would get the pointer to G2, and a new writer would get the copy of G2 (let's say G3). It's possible the G1 is not released yet, so multiple generations of data my co-exists. template <typename T> class rcu_protected { public: typedef T type; typedef std::tr1::shared_ptr<type> rcu_pointer; rcu_protected() : m_data_ptr (new type()) {} rcu_pointer get_reading_copy () { spin_until_eq (m_is_swapping, 0); return m_data_ptr; } rcu_pointer get_updating_copy () { spin_until_eq (m_is_swapping, 0); while (!CAS (m_is_writing, 0, 1)) {/* do sleep for back-off when exceeding maximum retry times */} rcu_pointer new_data_ptr(new type(*m_data_ptr)); // as spin_until_eq does not have memory barrier protection, // we need to place a read barrier to protect the loading of // new_data_ptr not to be re-ordered before its construction _ReadBarrier(); return new_data_ptr; } void update (rcu_pointer new_data_ptr) { while (!CAS (m_is_swapping, 0, 1)) {} m_data_ptr.swap (new_data_ptr); // as spin_until_eq does not have memory barrier protection, // we need to place a write barrier to protect the assignments of // m_is_writing/m_is_swapping be re-ordered bofore the swapping _WriteBarrier(); m_is_writing = 0; m_is_swapping = 0; } private: volatile long m_is_writing; volatile long m_is_swapping; rcu_pointer m_data_ptr; };

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  • Parallelism in .NET – Part 4, Imperative Data Parallelism: Aggregation

    - by Reed
    In the article on simple data parallelism, I described how to perform an operation on an entire collection of elements in parallel.  Often, this is not adequate, as the parallel operation is going to be performing some form of aggregation. Simple examples of this might include taking the sum of the results of processing a function on each element in the collection, or finding the minimum of the collection given some criteria.  This can be done using the techniques described in simple data parallelism, however, special care needs to be taken into account to synchronize the shared data appropriately.  The Task Parallel Library has tools to assist in this synchronization. The main issue with aggregation when parallelizing a routine is that you need to handle synchronization of data.  Since multiple threads will need to write to a shared portion of data.  Suppose, for example, that we wanted to parallelize a simple loop that looked for the minimum value within a dataset: double min = double.MaxValue; foreach(var item in collection) { double value = item.PerformComputation(); min = System.Math.Min(min, value); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This seems like a good candidate for parallelization, but there is a problem here.  If we just wrap this into a call to Parallel.ForEach, we’ll introduce a critical race condition, and get the wrong answer.  Let’s look at what happens here: // Buggy code! Do not use! double min = double.MaxValue; Parallel.ForEach(collection, item => { double value = item.PerformComputation(); min = System.Math.Min(min, value); }); This code has a fatal flaw: min will be checked, then set, by multiple threads simultaneously.  Two threads may perform the check at the same time, and set the wrong value for min.  Say we get a value of 1 in thread 1, and a value of 2 in thread 2, and these two elements are the first two to run.  If both hit the min check line at the same time, both will determine that min should change, to 1 and 2 respectively.  If element 1 happens to set the variable first, then element 2 sets the min variable, we’ll detect a min value of 2 instead of 1.  This can lead to wrong answers. Unfortunately, fixing this, with the Parallel.ForEach call we’re using, would require adding locking.  We would need to rewrite this like: // Safe, but slow double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach(collection, item => { double value = item.PerformComputation(); lock(syncObject) min = System.Math.Min(min, value); }); This will potentially add a huge amount of overhead to our calculation.  Since we can potentially block while waiting on the lock for every single iteration, we will most likely slow this down to where it is actually quite a bit slower than our serial implementation.  The problem is the lock statement – any time you use lock(object), you’re almost assuring reduced performance in a parallel situation.  This leads to two observations I’ll make: When parallelizing a routine, try to avoid locks. That being said: Always add any and all required synchronization to avoid race conditions. These two observations tend to be opposing forces – we often need to synchronize our algorithms, but we also want to avoid the synchronization when possible.  Looking at our routine, there is no way to directly avoid this lock, since each element is potentially being run on a separate thread, and this lock is necessary in order for our routine to function correctly every time. However, this isn’t the only way to design this routine to implement this algorithm.  Realize that, although our collection may have thousands or even millions of elements, we have a limited number of Processing Elements (PE).  Processing Element is the standard term for a hardware element which can process and execute instructions.  This typically is a core in your processor, but many modern systems have multiple hardware execution threads per core.  The Task Parallel Library will not execute the work for each item in the collection as a separate work item. Instead, when Parallel.ForEach executes, it will partition the collection into larger “chunks” which get processed on different threads via the ThreadPool.  This helps reduce the threading overhead, and help the overall speed.  In general, the Parallel class will only use one thread per PE in the system. Given the fact that there are typically fewer threads than work items, we can rethink our algorithm design.  We can parallelize our algorithm more effectively by approaching it differently.  Because the basic aggregation we are doing here (Min) is communitive, we do not need to perform this in a given order.  We knew this to be true already – otherwise, we wouldn’t have been able to parallelize this routine in the first place.  With this in mind, we can treat each thread’s work independently, allowing each thread to serially process many elements with no locking, then, after all the threads are complete, “merge” together the results. This can be accomplished via a different set of overloads in the Parallel class: Parallel.ForEach<TSource,TLocal>.  The idea behind these overloads is to allow each thread to begin by initializing some local state (TLocal).  The thread will then process an entire set of items in the source collection, providing that state to the delegate which processes an individual item.  Finally, at the end, a separate delegate is run which allows you to handle merging that local state into your final results. To rewriting our routine using Parallel.ForEach<TSource,TLocal>, we need to provide three delegates instead of one.  The most basic version of this function is declared as: public static ParallelLoopResult ForEach<TSource, TLocal>( IEnumerable<TSource> source, Func<TLocal> localInit, Func<TSource, ParallelLoopState, TLocal, TLocal> body, Action<TLocal> localFinally ) The first delegate (the localInit argument) is defined as Func<TLocal>.  This delegate initializes our local state.  It should return some object we can use to track the results of a single thread’s operations. The second delegate (the body argument) is where our main processing occurs, although now, instead of being an Action<T>, we actually provide a Func<TSource, ParallelLoopState, TLocal, TLocal> delegate.  This delegate will receive three arguments: our original element from the collection (TSource), a ParallelLoopState which we can use for early termination, and the instance of our local state we created (TLocal).  It should do whatever processing you wish to occur per element, then return the value of the local state after processing is completed. The third delegate (the localFinally argument) is defined as Action<TLocal>.  This delegate is passed our local state after it’s been processed by all of the elements this thread will handle.  This is where you can merge your final results together.  This may require synchronization, but now, instead of synchronizing once per element (potentially millions of times), you’ll only have to synchronize once per thread, which is an ideal situation. Now that I’ve explained how this works, lets look at the code: // Safe, and fast! double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach( collection, // First, we provide a local state initialization delegate. () => double.MaxValue, // Next, we supply the body, which takes the original item, loop state, // and local state, and returns a new local state (item, loopState, localState) => { double value = item.PerformComputation(); return System.Math.Min(localState, value); }, // Finally, we provide an Action<TLocal>, to "merge" results together localState => { // This requires locking, but it's only once per used thread lock(syncObj) min = System.Math.Min(min, localState); } ); Although this is a bit more complicated than the previous version, it is now both thread-safe, and has minimal locking.  This same approach can be used by Parallel.For, although now, it’s Parallel.For<TLocal>.  When working with Parallel.For<TLocal>, you use the same triplet of delegates, with the same purpose and results. Also, many times, you can completely avoid locking by using a method of the Interlocked class to perform the final aggregation in an atomic operation.  The MSDN example demonstrating this same technique using Parallel.For uses the Interlocked class instead of a lock, since they are doing a sum operation on a long variable, which is possible via Interlocked.Add. By taking advantage of local state, we can use the Parallel class methods to parallelize algorithms such as aggregation, which, at first, may seem like poor candidates for parallelization.  Doing so requires careful consideration, and often requires a slight redesign of the algorithm, but the performance gains can be significant if handled in a way to avoid excessive synchronization.

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  • Sync custom AD properties to SharePoint Profile

    - by KunaalKapoor
    Here are some step-by-step instructions regarding configuring SharePoint to sync with custom AD attributes:Add the custom attribute in Active DirectoryThis part will have to be your doing; here is some documentation regarding creating customattributes in AD:http://msdn.microsoft.com/en-us/library/ms675085(VS.85).aspxhttp://technet.microsoft.com/en-us/magazine/2008.05.schema.aspxhttp://blogs.technet.com/b/isingh/archive/2007/02/18/adding-custom-attributes-in-active-directory.aspx2. Open up the miisclient.exe (C:\Program Files\Microsoft Office Servers\14.0\Synchronization Service\UIShell\miisclient.exe)a. This will have to be opened up with the farm admin account3. Click on "Management Agents" in the ribbon4. Right-click the Active Directory Management Agent ("MOSS-<name of sync connection>") and click "Refresh Schema"a. When prompted, enter the credentials for the farm account5. Once complete, close out of miisclient.exe6. Go into Central Admin --> Application Management --> Manage Service Applications --> Go into the User Profile Service Application7. Click on "Manage User Properties"8. Click on "New Property"9. Put in the correct information regarding the attribute that was created10. At the bottom of this page, under the "Source Data Connection" drop down, select the AD synchronization connection you have already configured11. For the "Attribute" drop down, select the new attribute you have created12. For the "Direction" drop down, select "Import"13. Click "OK"14. Run a full synchronization for the user profile service application and the custom property will get synced (as long as the attribute is set in Active Directory for the desired users)

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  • DropSpace Syncs Android Files to Dropbox

    - by ETC
    DropSpace is a free Android application that fixes the primary issue that plagues the official Dropbox app for Android–the lack of true file synchronization. Grab a copy of DropSpace and start enjoying true file syncing on the go. The official Dropbox app is limited to grabbing files from your Dropbox account or pushing files from your phone to your Dropbox account. Actual file synchronization, this manual push/pull model aside, is nowhere to be found. DropSpace fills that gap by enabling file synchronization between your SD card directories and your Dropbox directories. It’s packed with handy features including restricting file syncing to Wi-Fi connection only (great if you don’t want to chew up your very limited data plan) as well as numerous toggles for various settings like whether it should delete remote files if the local file is deleted, how often it should run the sync service, and more. Hit up the link below to grab a copy and take it for a test drive. DropSpace is free and works wherever Android does; Dropbox account required. DropSpace [via Addictive Tips] Latest Features How-To Geek ETC Have You Ever Wondered How Your Operating System Got Its Name? Should You Delete Windows 7 Service Pack Backup Files to Save Space? What Can Super Mario Teach Us About Graphics Technology? Windows 7 Service Pack 1 is Released: But Should You Install It? How To Make Hundreds of Complex Photo Edits in Seconds With Photoshop Actions How to Enable User-Specific Wireless Networks in Windows 7 Access the Options for Your Favorite Extensions Easier in Firefox Don’t Sleep Keeps Your Windows Machine Awake DropSpace Syncs Android Files to Dropbox Field of Poppies Wallpaper The History Of Operating Systems [Infographic] DriveSafe.ly Reads Your Text Messages Aloud

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  • usb wifi dongle on ubuntu server, cannot install realtek driver RTL 8188cus

    - by Sandro Dzneladze
    I got cheap Ebay wifi dongle from HongKong, Im trying to set it up on my ubuntu server. Occasionally need to move server, so it cannot always be connected to router via lan. Anyhow, usb wifi came with a driver cd. I uploaded files to my home directory and tried to run install script (RTL 8188cus): sudo bash install.sh But I get error: Authentication requested [root] for make driver: make ARCH=x86_64 CROSS_COMPILE= -C /lib/modules/2.6.38-8-server/build M=/home/minime/RTL 8188cus/Linux/driver/rtl8192CU_linux_v2.0.1324.20110126 modules make[1]: Entering directory `/usr/src/linux-headers-2.6.38-8-server' make[1]: *** No rule to make target `8188cus/Linux/driver/rtl8192CU_linux_v2.0.1324.20110126'. Stop. make[1]: Leaving directory `/usr/src/linux-headers-2.6.38-8-server' make: *** [modules] Error 2 Compile make driver error: 2, Please check error Mesg Any ideas what Im doing wrong? There is another driver folder for linux called: RTL 81XX, which doesn't have install.sh at all! I tried to use make command, but I get: make: *** No targets specified and no makefile found. Stop. Any help? this is first time I'm installing driver from source. Im on Ubuntu 11.04 server. lsusb Bus 001 Device 002: ID 0bda:8176 Realtek Semiconductor Corp. lspci -nn 00:00.0 Host bridge [0600]: Intel Corporation N10 Family DMI Bridge [8086:a000] (rev 02) 00:02.0 VGA compatible controller [0300]: Intel Corporation N10 Family Integrated Graphics Controller [8086:a001] (rev 02) 00:1b.0 Audio device [0403]: Intel Corporation N10/ICH 7 Family High Definition Audio Controller [8086:27d8] (rev 02) 00:1c.0 PCI bridge [0604]: Intel Corporation N10/ICH 7 Family PCI Express Port 1 [8086:27d0] (rev 02) 00:1d.0 USB Controller [0c03]: Intel Corporation N10/ICH 7 Family USB UHCI Controller #1 [8086:27c8] (rev 02) 00:1d.1 USB Controller [0c03]: Intel Corporation N10/ICH 7 Family USB UHCI Controller #2 [8086:27c9] (rev 02) 00:1d.2 USB Controller [0c03]: Intel Corporation N10/ICH 7 Family USB UHCI Controller #3 [8086:27ca] (rev 02) 00:1d.3 USB Controller [0c03]: Intel Corporation N10/ICH 7 Family USB UHCI Controller #4 [8086:27cb] (rev 02) 00:1d.7 USB Controller [0c03]: Intel Corporation N10/ICH 7 Family USB2 EHCI Controller [8086:27cc] (rev 02) 00:1e.0 PCI bridge [0604]: Intel Corporation 82801 Mobile PCI Bridge [8086:2448] (rev e2) 00:1f.0 ISA bridge [0601]: Intel Corporation NM10 Family LPC Controller [8086:27bc] (rev 02) 00:1f.2 IDE interface [0101]: Intel Corporation N10/ICH7 Family SATA IDE Controller [8086:27c0] (rev 02) 00:1f.3 SMBus [0c05]: Intel Corporation N10/ICH 7 Family SMBus Controller [8086:27da] (rev 02) 01:00.0 Ethernet controller [0200]: Atheros Communications Device [1969:1083] (rev c0) sudo lshw description: Desktop Computer product: To Be Filled By O.E.M. (To Be Filled By O.E.M.) vendor: To Be Filled By O.E.M. version: To Be Filled By O.E.M. serial: To Be Filled By O.E.M. width: 64 bits capabilities: smbios-2.6 dmi-2.6 vsyscall64 vsyscall32 configuration: boot=normal chassis=desktop family=To Be Filled By O.E.M. sku=To Be Filled By O.E.M. uuid=00020003-0004-0005-0006-000700080009 *-core description: Motherboard product: AD525PV3 vendor: ASRock physical id: 0 *-firmware description: BIOS vendor: American Megatrends Inc. physical id: 0 version: P1.20 date: 04/01/2011 size: 64KiB capacity: 448KiB capabilities: pci upgrade shadowing cdboot bootselect socketedrom edd int13floppy1200 int13floppy720 int13floppy2880 int5printscreen int9keyboard int14serial int17printer int10video acpi usb ls120boot zipboot biosbootspecification netboot *-cpu description: CPU product: Intel(R) Atom(TM) CPU D525 @ 1.80GHz vendor: Intel Corp. physical id: 4 bus info: cpu@0 version: Intel(R) Atom(TM) CPU D525 @ 1.80GHz serial: To Be Filled By O.E.M. slot: CPUSocket size: 1800MHz capacity: 1800MHz width: 64 bits clock: 200MHz capabilities: x86-64 fpu fpu_exception wp vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx constant_tsc arch_perfmon pebs bts rep_good nopl aperfmperf pni dtes64 monitor ds_cpl tm2 ssse3 cx16 xtpr pdcm movbe lahf_lm configuration: cores=2 enabledcores=2 threads=4 *-cache:0 description: L1 cache physical id: 5 slot: L1-Cache size: 48KiB capacity: 48KiB capabilities: internal write-back data *-cache:1 description: L2 cache physical id: 6 slot: L2-Cache size: 1MiB capacity: 1MiB capabilities: internal write-back unified *-memory description: System Memory physical id: c slot: System board or motherboard size: 2GiB *-bank:0 description: SODIMM DDR2 Synchronous 800 MHz (1.2 ns) product: ModulePartNumber00 vendor: Manufacturer00 physical id: 0 serial: SerNum00 slot: DIMM0 size: 2GiB width: 64 bits clock: 800MHz (1.2ns) *-bank:1 description: DIMM [empty] product: ModulePartNumber01 vendor: Manufacturer01 physical id: 1 serial: SerNum01 slot: DIMM1 *-pci description: Host bridge product: N10 Family DMI Bridge vendor: Intel Corporation physical id: 100 bus info: pci@0000:00:00.0 version: 02 width: 32 bits clock: 33MHz configuration: driver=agpgart-intel resources: irq:0 *-display description: VGA compatible controller product: N10 Family Integrated Graphics Controller vendor: Intel Corporation physical id: 2 bus info: pci@0000:00:02.0 version: 02 width: 32 bits clock: 33MHz capabilities: msi pm vga_controller bus_master cap_list rom configuration: driver=i915 latency=0 resources: irq:41 memory:fea80000-feafffff ioport:dc00(size=8) memory:e0000000-efffffff memory:fe900000-fe9fffff *-multimedia description: Audio device product: N10/ICH 7 Family High Definition Audio Controller vendor: Intel Corporation physical id: 1b bus info: pci@0000:00:1b.0 version: 02 width: 64 bits clock: 33MHz capabilities: pm msi pciexpress bus_master cap_list configuration: driver=HDA Intel latency=0 resources: irq:43 memory:fea78000-fea7bfff *-pci:0 description: PCI bridge product: N10/ICH 7 Family PCI Express Port 1 vendor: Intel Corporation physical id: 1c bus info: pci@0000:00:1c.0 version: 02 width: 32 bits clock: 33MHz capabilities: pci pciexpress msi pm normal_decode bus_master cap_list configuration: driver=pcieport resources: irq:40 ioport:e000(size=4096) memory:feb00000-febfffff ioport:80000000(size=2097152) *-network description: Ethernet interface product: Atheros Communications vendor: Atheros Communications physical id: 0 bus info: pci@0000:01:00.0 logical name: eth0 version: c0 serial: XX size: 100Mbit/s capacity: 1Gbit/s width: 64 bits clock: 33MHz capabilities: pm msi pciexpress vpd bus_master cap_list ethernet physical tp 10bt 10bt-fd 100bt 100bt-fd 1000bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=atl1c driverversion=1.0.1.0-NAPI duplex=full firmware=N/A ip=192.168.1.99 latency=0 link=yes multicast=yes port=twisted pair speed=100Mbit/s resources: irq:42 memory:febc0000-febfffff ioport:ec00(size=128) *-usb:0 description: USB Controller product: N10/ICH 7 Family USB UHCI Controller #1 vendor: Intel Corporation physical id: 1d bus info: pci@0000:00:1d.0 version: 02 width: 32 bits clock: 33MHz capabilities: uhci bus_master configuration: driver=uhci_hcd latency=0 resources: irq:23 ioport:d880(size=32) *-usb:1 description: USB Controller product: N10/ICH 7 Family USB UHCI Controller #2 vendor: Intel Corporation physical id: 1d.1 bus info: pci@0000:00:1d.1 version: 02 width: 32 bits clock: 33MHz capabilities: uhci bus_master configuration: driver=uhci_hcd latency=0 resources: irq:19 ioport:d800(size=32) *-usb:2 description: USB Controller product: N10/ICH 7 Family USB UHCI Controller #3 vendor: Intel Corporation physical id: 1d.2 bus info: pci@0000:00:1d.2 version: 02 width: 32 bits clock: 33MHz capabilities: uhci bus_master configuration: driver=uhci_hcd latency=0 resources: irq:18 ioport:d480(size=32) *-usb:3 description: USB Controller product: N10/ICH 7 Family USB UHCI Controller #4 vendor: Intel Corporation physical id: 1d.3 bus info: pci@0000:00:1d.3 version: 02 width: 32 bits clock: 33MHz capabilities: uhci bus_master configuration: driver=uhci_hcd latency=0 resources: irq:16 ioport:d400(size=32) *-usb:4 description: USB Controller product: N10/ICH 7 Family USB2 EHCI Controller vendor: Intel Corporation physical id: 1d.7 bus info: pci@0000:00:1d.7 version: 02 width: 32 bits clock: 33MHz capabilities: pm debug ehci bus_master cap_list configuration: driver=ehci_hcd latency=0 resources: irq:23 memory:fea77c00-fea77fff *-pci:1 description: PCI bridge product: 82801 Mobile PCI Bridge vendor: Intel Corporation physical id: 1e bus info: pci@0000:00:1e.0 version: e2 width: 32 bits clock: 33MHz capabilities: pci subtractive_decode bus_master cap_list *-isa description: ISA bridge product: NM10 Family LPC Controller vendor: Intel Corporation physical id: 1f bus info: pci@0000:00:1f.0 version: 02 width: 32 bits clock: 33MHz capabilities: isa bus_master cap_list configuration: latency=0 *-ide description: IDE interface product: N10/ICH7 Family SATA IDE Controller vendor: Intel Corporation physical id: 1f.2 bus info: pci@0000:00:1f.2 logical name: scsi0 version: 02 width: 32 bits clock: 66MHz capabilities: ide pm bus_master cap_list emulated configuration: driver=ata_piix latency=0 resources: irq:19 ioport:1f0(size=8) ioport:3f6 ioport:170(size=8) ioport:376 ioport:ff90(size=16) memory:80200000-802003ff *-disk description: ATA Disk product: WDC WD10TPVT-11U vendor: Western Digital physical id: 0.0.0 bus info: scsi@0:0.0.0 logical name: /dev/sda version: 01.0 serial: WD-WXC1A80P0314 size: 931GiB (1TB) capabilities: partitioned partitioned:dos configuration: ansiversion=5 signature=00088c47 *-volume:0 description: EXT4 volume vendor: Linux physical id: 1 bus info: scsi@0:0.0.0,1 logical name: /dev/sda1 logical name: /media/private version: 1.0 serial: 042daf2d-350c-4640-a76a-4554c9d98c59 size: 300GiB capacity: 300GiB capabilities: primary journaled extended_attributes large_files huge_files dir_nlink recover extents ext4 ext2 initialized configuration: created=2011-11-06 11:05:03 filesystem=ext4 label=Private lastmountpoint=/media/private modified=2012-04-13 20:01:16 mount.fstype=ext4 mount.options=rw,relatime,barrier=1,stripe=1,data=ordered mounted=2012-04-13 20:01:16 state=mounted *-volume:1 description: Extended partition physical id: 2 bus info: scsi@0:0.0.0,2 logical name: /dev/sda2 size: 625GiB capacity: 625GiB capabilities: primary extended partitioned partitioned:extended *-logicalvolume:0 description: Linux filesystem partition physical id: 5 logical name: /dev/sda5 logical name: /media/storage capacity: 600GiB configuration: mount.fstype=ext4 mount.options=rw,relatime,barrier=1,stripe=1,data=ordered state=mounted *-logicalvolume:1 description: Linux filesystem partition physical id: 6 logical name: /dev/sda6 logical name: /media/dropbox capacity: 24GiB configuration: mount.fstype=ext4 mount.options=rw,relatime,barrier=1,stripe=1,data=ordered state=mounted *-volume:2 description: EXT4 volume vendor: Linux physical id: 3 bus info: scsi@0:0.0.0,3 logical name: /dev/sda3 logical name: /media/www version: 1.0 serial: 9b0a27b4-05d8-40d5-bfc7-4aeba198db7b size: 2570MiB capacity: 2570MiB capabilities: primary journaled extended_attributes large_files huge_files dir_nlink recover extents ext4 ext2 initialized configuration: created=2011-11-06 11:05:11 filesystem=ext4 label=www lastmountpoint=/media/www modified=2012-04-15 11:31:12 mount.fstype=ext4 mount.options=rw,relatime,barrier=1,stripe=1,data=ordered mounted=2012-04-15 11:31:12 state=mounted *-volume:3 description: Linux swap volume physical id: 4 bus info: scsi@0:0.0.0,4 logical name: /dev/sda4 version: 1 serial: 6ed1130e-3aad-4fa6-890b-77e729121e3b size: 4098MiB capacity: 4098MiB capabilities: primary nofs swap initialized configuration: filesystem=swap pagesize=4096 *-serial UNCLAIMED description: SMBus product: N10/ICH 7 Family SMBus Controller vendor: Intel Corporation physical id: 1f.3 bus info: pci@0000:00:1f.3 version: 02 width: 32 bits clock: 33MHz configuration: latency=0 resources: ioport:400(size=32) *-scsi physical id: 1 bus info: usb@1:4 logical name: scsi2 capabilities: emulated scsi-host configuration: driver=usb-storage *-disk description: SCSI Disk physical id: 0.0.0 bus info: scsi@2:0.0.0 logical name: /dev/sdb size: 3864MiB (4051MB) capabilities: partitioned partitioned:dos configuration: signature=000b4c55 *-volume description: EXT4 volume vendor: Linux physical id: 1 bus info: scsi@2:0.0.0,1 logical name: /dev/sdb1 logical name: / version: 1.0 serial: 33926e39-4685-4f63-b83c-f2a67824b69a size: 3862MiB capacity: 3862MiB capabilities: primary bootable journaled extended_attributes large_files huge_files dir_nlink recover extents ext4 ext2 initialized configuration: created=2011-10-11 14:03:46 filesystem=ext4 lastmountpoint=/ modified=2012-03-19 11:47:29 mount.fstype=ext4 mount.options=rw,noatime,errors=remount-ro,barrier=1,data=ordered mounted=2012-04-15 11:31:11 state=mounted rfkill list all Doesnt show anything! dmesg | grep -i firmware [ 0.715481] pci 0000:00:1f.0: [Firmware Bug]: TigerPoint LPC.BM_STS cleared

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  • barriers in SMP linux kernel

    - by osgx
    Hello Is there smth like pthread_barrier in SMP Linux kernel? When kernel works simultaneously on 2 and more CPUs with the same structure, the barrier (like pthread_barrier) can be useful. It will stop all CPUs entering to it until last CPU will run the barrier. From this moment all CPUs again works.

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  • ItemUpdating called twice after ItemAdded in event receiver

    - by Jason
    I've created an event receiver to handle the ItemAdded and ItemUpdating events on a document library in SharePoint 2010. I've encountered a problem where when I add a document to the library (e.g. by saving it back from Word) the ItemAdded method is correctly called however this is then followed by two calls to ItemUpdating. I have removed all code from my handlers to ensure that it's not something I'm doing inside that is causing the problem. They literally look like: public override void ItemUpdating(SPItemEventProperties properties) { } public override void ItemAdded(SPItemEventProperties properties) { } Does anyone have a solution to this issue? Here is my elements.xml file for the event receiver: <Elements xmlns="http://schemas.microsoft.com/sharepoint/"> <Receivers ListTemplateId="101"> <Receiver> <Name>DocumentsEventReceiverItemUpdating</Name> <Type>ItemUpdating</Type> <Assembly>$SharePoint.Project.AssemblyFullName$</Assembly> <Class>My.Namespace.DocumentsEventReceiver</Class> <SequenceNumber>10000</SequenceNumber> <Synchronization>Synchronous</Synchronization> </Receiver> <Receiver> <Name>DocumentsEventReceiverItemAdded</Name> <Type>ItemAdded</Type> <Assembly>$SharePoint.Project.AssemblyFullName$</Assembly> <Class>My.Namespace.DocumentsEventReceiver</Class> <SequenceNumber>10000</SequenceNumber> <Synchronization>Synchronous</Synchronization> </Receiver> </Receivers> </Elements>

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  • C#/.NET Little Wonders: ConcurrentBag and BlockingCollection

    - by James Michael Hare
    In the first week of concurrent collections, began with a general introduction and discussed the ConcurrentStack<T> and ConcurrentQueue<T>.  The last post discussed the ConcurrentDictionary<T> .  Finally this week, we shall close with a discussion of the ConcurrentBag<T> and BlockingCollection<T>. For more of the "Little Wonders" posts, see C#/.NET Little Wonders: A Redux. Recap As you'll recall from the previous posts, the original collections were object-based containers that accomplished synchronization through a Synchronized member.  With the advent of .NET 2.0, the original collections were succeeded by the generic collections which are fully type-safe, but eschew automatic synchronization.  With .NET 4.0, a new breed of collections was born in the System.Collections.Concurrent namespace.  Of these, the final concurrent collection we will examine is the ConcurrentBag and a very useful wrapper class called the BlockingCollection. For some excellent information on the performance of the concurrent collections and how they perform compared to a traditional brute-force locking strategy, see this informative whitepaper by the Microsoft Parallel Computing Platform team here. ConcurrentBag<T> – Thread-safe unordered collection. Unlike the other concurrent collections, the ConcurrentBag<T> has no non-concurrent counterpart in the .NET collections libraries.  Items can be added and removed from a bag just like any other collection, but unlike the other collections, the items are not maintained in any order.  This makes the bag handy for those cases when all you care about is that the data be consumed eventually, without regard for order of consumption or even fairness – that is, it’s possible new items could be consumed before older items given the right circumstances for a period of time. So why would you ever want a container that can be unfair?  Well, to look at it another way, you can use a ConcurrentQueue and get the fairness, but it comes at a cost in that the ordering rules and synchronization required to maintain that ordering can affect scalability a bit.  Thus sometimes the bag is great when you want the fastest way to get the next item to process, and don’t care what item it is or how long its been waiting. The way that the ConcurrentBag works is to take advantage of the new ThreadLocal<T> type (new in System.Threading for .NET 4.0) so that each thread using the bag has a list local to just that thread.  This means that adding or removing to a thread-local list requires very low synchronization.  The problem comes in where a thread goes to consume an item but it’s local list is empty.  In this case the bag performs “work-stealing” where it will rob an item from another thread that has items in its list.  This requires a higher level of synchronization which adds a bit of overhead to the take operation. So, as you can imagine, this makes the ConcurrentBag good for situations where each thread both produces and consumes items from the bag, but it would be less-than-idea in situations where some threads are dedicated producers and the other threads are dedicated consumers because the work-stealing synchronization would outweigh the thread-local optimization for a thread taking its own items. Like the other concurrent collections, there are some curiosities to keep in mind: IsEmpty(), Count, ToArray(), and GetEnumerator() lock collection Each of these needs to take a snapshot of whole bag to determine if empty, thus they tend to be more expensive and cause Add() and Take() operations to block. ToArray() and GetEnumerator() are static snapshots Because it is based on a snapshot, will not show subsequent updates after snapshot. Add() is lightweight Since adding to the thread-local list, there is very little overhead on Add. TryTake() is lightweight if items in thread-local list As long as items are in the thread-local list, TryTake() is very lightweight, much more so than ConcurrentStack() and ConcurrentQueue(), however if the local thread list is empty, it must steal work from another thread, which is more expensive. Remember, a bag is not ideal for all situations, it is mainly ideal for situations where a process consumes an item and either decomposes it into more items to be processed, or handles the item partially and places it back to be processed again until some point when it will complete.  The main point is that the bag works best when each thread both takes and adds items. For example, we could create a totally contrived example where perhaps we want to see the largest power of a number before it crosses a certain threshold.  Yes, obviously we could easily do this with a log function, but bare with me while I use this contrived example for simplicity. So let’s say we have a work function that will take a Tuple out of a bag, this Tuple will contain two ints.  The first int is the original number, and the second int is the last multiple of that number.  So we could load our bag with the initial values (let’s say we want to know the last multiple of each of 2, 3, 5, and 7 under 100. 1: var bag = new ConcurrentBag<Tuple<int, int>> 2: { 3: Tuple.Create(2, 1), 4: Tuple.Create(3, 1), 5: Tuple.Create(5, 1), 6: Tuple.Create(7, 1) 7: }; Then we can create a method that given the bag, will take out an item, apply the multiplier again, 1: public static void FindHighestPowerUnder(ConcurrentBag<Tuple<int,int>> bag, int threshold) 2: { 3: Tuple<int,int> pair; 4:  5: // while there are items to take, this will prefer local first, then steal if no local 6: while (bag.TryTake(out pair)) 7: { 8: // look at next power 9: var result = Math.Pow(pair.Item1, pair.Item2 + 1); 10:  11: if (result < threshold) 12: { 13: // if smaller than threshold bump power by 1 14: bag.Add(Tuple.Create(pair.Item1, pair.Item2 + 1)); 15: } 16: else 17: { 18: // otherwise, we're done 19: Console.WriteLine("Highest power of {0} under {3} is {0}^{1} = {2}.", 20: pair.Item1, pair.Item2, Math.Pow(pair.Item1, pair.Item2), threshold); 21: } 22: } 23: } Now that we have this, we can load up this method as an Action into our Tasks and run it: 1: // create array of tasks, start all, wait for all 2: var tasks = new[] 3: { 4: new Task(() => FindHighestPowerUnder(bag, 100)), 5: new Task(() => FindHighestPowerUnder(bag, 100)), 6: }; 7:  8: Array.ForEach(tasks, t => t.Start()); 9:  10: Task.WaitAll(tasks); Totally contrived, I know, but keep in mind the main point!  When you have a thread or task that operates on an item, and then puts it back for further consumption – or decomposes an item into further sub-items to be processed – you should consider a ConcurrentBag as the thread-local lists will allow for quick processing.  However, if you need ordering or if your processes are dedicated producers or consumers, this collection is not ideal.  As with anything, you should performance test as your mileage will vary depending on your situation! BlockingCollection<T> – A producers & consumers pattern collection The BlockingCollection<T> can be treated like a collection in its own right, but in reality it adds a producers and consumers paradigm to any collection that implements the interface IProducerConsumerCollection<T>.  If you don’t specify one at the time of construction, it will use a ConcurrentQueue<T> as its underlying store. If you don’t want to use the ConcurrentQueue, the ConcurrentStack and ConcurrentBag also implement the interface (though ConcurrentDictionary does not).  In addition, you are of course free to create your own implementation of the interface. So, for those who don’t remember the producers and consumers classical computer-science problem, the gist of it is that you have one (or more) processes that are creating items (producers) and one (or more) processes that are consuming these items (consumers).  Now, the crux of the problem is that there is a bin (queue) where the produced items are placed, and typically that bin has a limited size.  Thus if a producer creates an item, but there is no space to store it, it must wait until an item is consumed.  Also if a consumer goes to consume an item and none exists, it must wait until an item is produced. The BlockingCollection makes it trivial to implement any standard producers/consumers process set by providing that “bin” where the items can be produced into and consumed from with the appropriate blocking operations.  In addition, you can specify whether the bin should have a limited size or can be (theoretically) unbounded, and you can specify timeouts on the blocking operations. As far as your choice of “bin”, for the most part the ConcurrentQueue is the right choice because it is fairly light and maximizes fairness by ordering items so that they are consumed in the same order they are produced.  You can use the concurrent bag or stack, of course, but your ordering would be random-ish in the case of the former and LIFO in the case of the latter. So let’s look at some of the methods of note in BlockingCollection: BoundedCapacity returns capacity of the “bin” If the bin is unbounded, the capacity is int.MaxValue. Count returns an internally-kept count of items This makes it O(1), but if you modify underlying collection directly (not recommended) it is unreliable. CompleteAdding() is used to cut off further adds. This sets IsAddingCompleted and begins to wind down consumers once empty. IsAddingCompleted is true when producers are “done”. Once you are done producing, should complete the add process to alert consumers. IsCompleted is true when producers are “done” and “bin” is empty. Once you mark the producers done, and all items removed, this will be true. Add() is a blocking add to collection. If bin is full, will wait till space frees up Take() is a blocking remove from collection. If bin is empty, will wait until item is produced or adding is completed. GetConsumingEnumerable() is used to iterate and consume items. Unlike the standard enumerator, this one consumes the items instead of iteration. TryAdd() attempts add but does not block completely If adding would block, returns false instead, can specify TimeSpan to wait before stopping. TryTake() attempts to take but does not block completely Like TryAdd(), if taking would block, returns false instead, can specify TimeSpan to wait. Note the use of CompleteAdding() to signal the BlockingCollection that nothing else should be added.  This means that any attempts to TryAdd() or Add() after marked completed will throw an InvalidOperationException.  In addition, once adding is complete you can still continue to TryTake() and Take() until the bin is empty, and then Take() will throw the InvalidOperationException and TryTake() will return false. So let’s create a simple program to try this out.  Let’s say that you have one process that will be producing items, but a slower consumer process that handles them.  This gives us a chance to peek inside what happens when the bin is bounded (by default, the bin is NOT bounded). 1: var bin = new BlockingCollection<int>(5); Now, we create a method to produce items: 1: public static void ProduceItems(BlockingCollection<int> bin, int numToProduce) 2: { 3: for (int i = 0; i < numToProduce; i++) 4: { 5: // try for 10 ms to add an item 6: while (!bin.TryAdd(i, TimeSpan.FromMilliseconds(10))) 7: { 8: Console.WriteLine("Bin is full, retrying..."); 9: } 10: } 11:  12: // once done producing, call CompleteAdding() 13: Console.WriteLine("Adding is completed."); 14: bin.CompleteAdding(); 15: } And one to consume them: 1: public static void ConsumeItems(BlockingCollection<int> bin) 2: { 3: // This will only be true if CompleteAdding() was called AND the bin is empty. 4: while (!bin.IsCompleted) 5: { 6: int item; 7:  8: if (!bin.TryTake(out item, TimeSpan.FromMilliseconds(10))) 9: { 10: Console.WriteLine("Bin is empty, retrying..."); 11: } 12: else 13: { 14: Console.WriteLine("Consuming item {0}.", item); 15: Thread.Sleep(TimeSpan.FromMilliseconds(20)); 16: } 17: } 18: } Then we can fire them off: 1: // create one producer and two consumers 2: var tasks = new[] 3: { 4: new Task(() => ProduceItems(bin, 20)), 5: new Task(() => ConsumeItems(bin)), 6: new Task(() => ConsumeItems(bin)), 7: }; 8:  9: Array.ForEach(tasks, t => t.Start()); 10:  11: Task.WaitAll(tasks); Notice that the producer is faster than the consumer, thus it should be hitting a full bin often and displaying the message after it times out on TryAdd(). 1: Consuming item 0. 2: Consuming item 1. 3: Bin is full, retrying... 4: Bin is full, retrying... 5: Consuming item 3. 6: Consuming item 2. 7: Bin is full, retrying... 8: Consuming item 4. 9: Consuming item 5. 10: Bin is full, retrying... 11: Consuming item 6. 12: Consuming item 7. 13: Bin is full, retrying... 14: Consuming item 8. 15: Consuming item 9. 16: Bin is full, retrying... 17: Consuming item 10. 18: Consuming item 11. 19: Bin is full, retrying... 20: Consuming item 12. 21: Consuming item 13. 22: Bin is full, retrying... 23: Bin is full, retrying... 24: Consuming item 14. 25: Adding is completed. 26: Consuming item 15. 27: Consuming item 16. 28: Consuming item 17. 29: Consuming item 19. 30: Consuming item 18. Also notice that once CompleteAdding() is called and the bin is empty, the IsCompleted property returns true, and the consumers will exit. Summary The ConcurrentBag is an interesting collection that can be used to optimize concurrency scenarios where tasks or threads both produce and consume items.  In this way, it will choose to consume its own work if available, and then steal if not.  However, in situations where you want fair consumption or ordering, or in situations where the producers and consumers are distinct processes, the bag is not optimal. The BlockingCollection is a great wrapper around all of the concurrent queue, stack, and bag that allows you to add producer and consumer semantics easily including waiting when the bin is full or empty. That’s the end of my dive into the concurrent collections.  I’d also strongly recommend, once again, you read this excellent Microsoft white paper that goes into much greater detail on the efficiencies you can gain using these collections judiciously (here). Tweet Technorati Tags: C#,.NET,Concurrent Collections,Little Wonders

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