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  • Daemon with Clojure/JVM

    - by Isaac Copper
    I'd like to have a small (not doing too damn much) daemon running on a little server, watching a directory for new files being added to it (and any directories in the main one), and calling another Clojure program to deal with that new file. Ideally, each file would be added to a queue (a list represented by a ref in Clojure?) and the main process would take care of those files in the queue on a FIFO basis. My question is: is having a JVM up running this little program all the time too much a resource hog? And do you have any suggestions as to how go about doing this? Thank you very much!

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  • Last in First out UDP structure in MatLab.

    - by D Zondervan
    I am using MatLabs UDP function in their instrument control toolbox to send data packets from one computer to another. The first computer is constantly updating data values and sending them to the other computer, and I want that computer to be able to query the first one for the most recent values whenever it needs them. However, the default implementation of the UDP send and receive in MatLab is a FIFO structure- the first packet I send is the first the other computer receives when they execute the "fscanf" function. I want the last packet I sent to be the one the fscanf function returns. Is this possible or do I need to use a different protocol?

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  • Java/swing: console component?

    - by Jason S
    I am looking for a component I can use in Swing that acts as a GUI console which has a text area with scrollbars that can be set to a particular font has an InputStream and an OutputStream that a host application can obtain accepts keyboard input, prints it onto the end of the console text, and sends that input to the InputStream prints the OutputStream text to the end of the console has some kind of FIFO-ish property whereby the amount of text displayed in the console can be limited by automatically discarding the oldest text, when appropriate allows copy (but not cut or paste or any other editing) of the console text to the system clipboard This is kind of like the Console tab in Eclipse. Are there any good libraries that provide this?

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  • Strange behavior of for loop in scheduler_tick

    - by EpsilonVector
    I'm working on Linux kernel 2.4 (homework) and I inserted the following code into the scheduler_tick function: if (unlikely(rt_task(p)) || (p->policy==SCHED_PROD && p->time_ran>=p->process_expected_time)) { /* * RR tasks need a special form of timeslice management. * FIFO tasks have no timeslices. */ if ((p->policy == SCHED_RR || /*change*/p->policy==SCHED_PROD) && !--p->time_slice) { /*changes*/ if (p->policy == SCHED_PROD){ for (i=0; i<5000; i++){ printk("I'm leeching off SCHED_RR code! %d\n", i); } } /*end changes*/ The addition was added for debugging purposes. For some reason this causes very weird behavior: when a SCHED_PROD process triggers this code (and consequently the loop that follows) the loop counts to about 4600 normally, but then goes back to 4600 each time it counts to 4800, and gets stuck in an infinite loop. What's going on?? EDIT: The i variable is my own.

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  • Problem with "write" function in linux

    - by Dumitru Catalin
    I am trying to write 2 server/client programs under Linux, in which they communicate through named pipes. The problem is that sometimes when I try to write from the server into a pipe that doesn't exist anymore (the client has stopped), I get a "Resource temporarily unavailable" error and the server stops completely. I understand that this is caused by using a O_NONBLOCK parameter when opening the fifo chanel, indicating the point where the program would usually wait until it could write again in the file, but is there a way to stop this behavior, and not halt the entire program if a problem occurs (shouldn't the write command return -1 ad the program continue normally)? And another strange thing is that this error only occurs when running the programs outside the ide (eclipse). If I run both programs inside eclipse, on error the write function just returns -1 and the programs continues normally.

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  • Solution for distributing MANY simple network tasks?

    - by EmpireJones
    I would like to create some sort of a distributed setup for running a ton of small/simple REST web queries in a production environment. For each 5-10 related queries which are executed from a node, I will generate a very small amount of derived data, which will need to be stored in a standard relational database (such as PostgreSQL). What platforms are built for this type of problem set? The nature, data sizes, and quantities seem to contradict the mindset of Hadoop. There are also more grid based architectures such as Condor and Sun Grid Engine, which I have seen mentioned. I'm not sure if these platforms have any recovery from errors though (checking if a job succeeds). What I would really like is a FIFO type queue that I could add jobs to, with the end result of my database getting updated. Any suggestions on the best tool for the job?

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  • Go - Concurrent method

    - by nevalu
    How to get a concurrent method? In my case, the library would be called from a program to get a value to each argument str --in method Get()--. When it's used Get() then it assigns a variable from type bytes.Buffer which it will have the value to return. The returned values --when it been concurrently called-- will be stored into a database or a file and it doesn't matter that its output been of FIFO way (from method). type test struct { foo uint8 bar uint8 } func NewTest(arg1 string) (*test, os.Error) {...} func (self *test) Get(str string) ([]byte, os.Error) { var format bytes.Buffer ... } I think that all code inner of method Get() should be put inner of go func() {...}(), and then to use a channel. Would there be a problem if it's called another method from Get()? Or would it also has to be concurrent?

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  • jQuery jqXHR - cancel chained calls, trigger error chain

    - by m0sa
    I am creating a ajax utility for interfacing with my server methods. I would like to leverage jQuery 1.5+ deferred methods from the object returned from the jQuery.ajax() call. The situation is following. The serverside method always returns a JSON object: { success: true|false, data: ... } The client-side utility initiates the ajax call like this var jqxhr = $.ajax({ ... }); And the problem area: jqxhr.success(function(data, textStatus, xhr) { if(!data || !data.success) { ???? // abort processing, trigger error } }); return jqxhr; // return to caller so he can attach his own handlers So the question is how to cancel invocation of all the callers appended success callbacks an trigger his error handler in the place mentioned with ???? ? The documentation says the deferred function invocation lists are FIFO, so my success handler is definitely the first one.

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  • Program quits if pipe is closed

    - by givemelight
    I am trying to write to a pipe using C++. The following code gets called in an extra thread: void writeToPipe() { int outfifo; char buf[100]; char outfile[] = "out"; mknod(outfile, S_IFIFO | 0666, 0); if ((outfifo = open(outfile, O_WRONLY)) < 0) { perror("Opening output fifo failed"); return false; } int currentTimestamp = (int)time(0); int bufLen = sprintf(bug, "Time is %d.", currentTimestamp); write(outfifo, buf, bufLen); } The thread is called in main using: thread writeThread(writeToPipe); writeThread.detach(); If the pipe is not opened by another process, the C++ program just quits without an error. I don't know how to check if the pipe is opened.

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  • Scaling-out Your Services by Message Bus based WCF Transport Extension &ndash; Part 1 &ndash; Background

    - by Shaun
    Cloud computing gives us more flexibility on the computing resource, we can provision and deploy an application or service with multiple instances over multiple machines. With the increment of the service instances, how to balance the incoming message and workload would become a new challenge. Currently there are two approaches we can use to pass the incoming messages to the service instances, I would like call them dispatcher mode and pulling mode.   Dispatcher Mode The dispatcher mode introduces a role which takes the responsible to find the best service instance to process the request. The image below describes the sharp of this mode. There are four clients communicate with the service through the underlying transportation. For example, if we are using HTTP the clients might be connecting to the same service URL. On the server side there’s a dispatcher listening on this URL and try to retrieve all messages. When a message came in, the dispatcher will find a proper service instance to process it. There are three mechanism to find the instance: Round-robin: Dispatcher will always send the message to the next instance. For example, if the dispatcher sent the message to instance 2, then the next message will be sent to instance 3, regardless if instance 3 is busy or not at that moment. Random: Dispatcher will find a service instance randomly, and same as the round-robin mode it regardless if the instance is busy or not. Sticky: Dispatcher will send all related messages to the same service instance. This approach always being used if the service methods are state-ful or session-ful. But as you can see, all of these approaches are not really load balanced. The clients will send messages at any time, and each message might take different process duration on the server side. This means in some cases, some of the service instances are very busy while others are almost idle. For example, if we were using round-robin mode, it could be happened that most of the simple task messages were passed to instance 1 while the complex ones were sent to instance 3, even though instance 1 should be idle. This brings some problem in our architecture. The first one is that, the response to the clients might be longer than it should be. As it’s shown in the figure above, message 6 and 9 can be processed by instance 1 or instance 2, but in reality they were dispatched to the busy instance 3 since the dispatcher and round-robin mode. Secondly, if there are many requests came from the clients in a very short period, service instances might be filled by tons of pending tasks and some instances might be crashed. Third, if we are using some cloud platform to host our service instances, for example the Windows Azure, the computing resource is billed by service deployment period instead of the actual CPU usage. This means if any service instance is idle it is wasting our money! Last one, the dispatcher would be the bottleneck of our system since all incoming messages must be routed by the dispatcher. If we are using HTTP or TCP as the transport, the dispatcher would be a network load balance. If we wants more capacity, we have to scale-up, or buy a hardware load balance which is very expensive, as well as scaling-out the service instances. Pulling Mode Pulling mode doesn’t need a dispatcher to route the messages. All service instances are listening to the same transport and try to retrieve the next proper message to process if they are idle. Since there is no dispatcher in pulling mode, it requires some features on the transportation. The transportation must support multiple client connection and server listening. HTTP and TCP doesn’t allow multiple clients are listening on the same address and port, so it cannot be used in pulling mode directly. All messages in the transportation must be FIFO, which means the old message must be received before the new one. Message selection would be a plus on the transportation. This means both service and client can specify some selection criteria and just receive some specified kinds of messages. This feature is not mandatory but would be very useful when implementing the request reply and duplex WCF channel modes. Otherwise we must have a memory dictionary to store the reply messages. I will explain more about this in the following articles. Message bus, or the message queue would be best candidate as the transportation when using the pulling mode. First, it allows multiple application to listen on the same queue, and it’s FIFO. Some of the message bus also support the message selection, such as TIBCO EMS, RabbitMQ. Some others provide in memory dictionary which can store the reply messages, for example the Redis. The principle of pulling mode is to let the service instances self-managed. This means each instance will try to retrieve the next pending incoming message if they finished the current task. This gives us more benefit and can solve the problems we met with in the dispatcher mode. The incoming message will be received to the best instance to process, which means this will be very balanced. And it will not happen that some instances are busy while other are idle, since the idle one will retrieve more tasks to make them busy. Since all instances are try their best to be busy we can use less instances than dispatcher mode, which more cost effective. Since there’s no dispatcher in the system, there is no bottleneck. When we introduced more service instances, in dispatcher mode we have to change something to let the dispatcher know the new instances. But in pulling mode since all service instance are self-managed, there no extra change at all. If there are many incoming messages, since the message bus can queue them in the transportation, service instances would not be crashed. All above are the benefits using the pulling mode, but it will introduce some problem as well. The process tracking and debugging become more difficult. Since the service instances are self-managed, we cannot know which instance will process the message. So we need more information to support debug and track. Real-time response may not be supported. All service instances will process the next message after the current one has done, if we have some real-time request this may not be a good solution. Compare with the Pros and Cons above, the pulling mode would a better solution for the distributed system architecture. Because what we need more is the scalability, cost-effect and the self-management.   WCF and WCF Transport Extensibility Windows Communication Foundation (WCF) is a framework for building service-oriented applications. In the .NET world WCF is the best way to implement the service. In this series I’m going to demonstrate how to implement the pulling mode on top of a message bus by extending the WCF. I don’t want to deep into every related field in WCF but will highlight its transport extensibility. When we implemented an RPC foundation there are many aspects we need to deal with, for example the message encoding, encryption, authentication and message sending and receiving. In WCF, each aspect is represented by a channel. A message will be passed through all necessary channels and finally send to the underlying transportation. And on the other side the message will be received from the transport and though the same channels until the business logic. This mode is called “Channel Stack” in WCF, and the last channel in the channel stack must always be a transport channel, which takes the responsible for sending and receiving the messages. As we are going to implement the WCF over message bus and implement the pulling mode scaling-out solution, we need to create our own transport channel so that the client and service can exchange messages over our bus. Before we deep into the transport channel, let’s have a look on the message exchange patterns that WCF defines. Message exchange pattern (MEP) defines how client and service exchange the messages over the transportation. WCF defines 3 basic MEPs which are datagram, Request-Reply and Duplex. Datagram: Also known as one-way, or fire-forgot mode. The message sent from the client to the service, and no need any reply from the service. The client doesn’t care about the message result at all. Request-Reply: Very common used pattern. The client send the request message to the service and wait until the reply message comes from the service. Duplex: The client sent message to the service, when the service processing the message it can callback to the client. When callback the service would be like a client while the client would be like a service. In WCF, each MEP represent some channels associated. MEP Channels Datagram IInputChannel, IOutputChannel Request-Reply IRequestChannel, IReplyChannel Duplex IDuplexChannel And the channels are created by ChannelListener on the server side, and ChannelFactory on the client side. The ChannelListener and ChannelFactory are created by the TransportBindingElement. The TransportBindingElement is created by the Binding, which can be defined as a new binding or from a custom binding. For more information about the transport channel mode, please refer to the MSDN document. The figure below shows the transport channel objects when using the request-reply MEP. And this is the datagram MEP. And this is the duplex MEP. After investigated the WCF transport architecture, channel mode and MEP, we finally identified what we should do to extend our message bus based transport layer. They are: Binding: (Optional) Defines the channel elements in the channel stack and added our transport binding element at the bottom of the stack. But we can use the build-in CustomBinding as well. TransportBindingElement: Defines which MEP is supported in our transport and create the related ChannelListener and ChannelFactory. This also defines the scheme of the endpoint if using this transport. ChannelListener: Create the server side channel based on the MEP it’s. We can have one ChannelListener to create channels for all supported MEPs, or we can have ChannelListener for each MEP. In this series I will use the second approach. ChannelFactory: Create the client side channel based on the MEP it’s. We can have one ChannelFactory to create channels for all supported MEPs, or we can have ChannelFactory for each MEP. In this series I will use the second approach. Channels: Based on the MEPs we want to support, we need to implement the channels accordingly. For example, if we want our transport support Request-Reply mode we should implement IRequestChannel and IReplyChannel. In this series I will implement all 3 MEPs listed above one by one. Scaffold: In order to make our transport extension works we also need to implement some scaffold stuff. For example we need some classes to send and receive message though out message bus. We also need some codes to read and write the WCF message, etc.. These are not necessary but would be very useful in our example.   Message Bus There is only one thing remained before we can begin to implement our scaling-out support WCF transport, which is the message bus. As I mentioned above, the message bus must have some features to fulfill all the WCF MEPs. In my company we will be using TIBCO EMS, which is an enterprise message bus product. And I have said before we can use any message bus production if it’s satisfied with our requests. Here I would like to introduce an interface to separate the message bus from the WCF. This allows us to implement the bus operations by any kinds bus we are going to use. The interface would be like this. 1: public interface IBus : IDisposable 2: { 3: string SendRequest(string message, bool fromClient, string from, string to = null); 4:  5: void SendReply(string message, bool fromClient, string replyTo); 6:  7: BusMessage Receive(bool fromClient, string replyTo); 8: } There are only three methods for the bus interface. Let me explain one by one. The SendRequest method takes the responsible for sending the request message into the bus. The parameters description are: message: The WCF message content. fromClient: Indicates if this message was came from the client. from: The channel ID that this message was sent from. The channel ID will be generated when any kinds of channel was created, which will be explained in the following articles. to: The channel ID that this message should be received. In Request-Reply and Duplex MEP this is necessary since the reply message must be received by the channel which sent the related request message. The SendReply method takes the responsible for sending the reply message. It’s very similar as the previous one but no “from” parameter. This is because it’s no need to reply a reply message again in any MEPs. The Receive method takes the responsible for waiting for a incoming message, includes the request message and specified reply message. It returned a BusMessage object, which contains some information about the channel information. The code of the BusMessage class is 1: public class BusMessage 2: { 3: public string MessageID { get; private set; } 4: public string From { get; private set; } 5: public string ReplyTo { get; private set; } 6: public string Content { get; private set; } 7:  8: public BusMessage(string messageId, string fromChannelId, string replyToChannelId, string content) 9: { 10: MessageID = messageId; 11: From = fromChannelId; 12: ReplyTo = replyToChannelId; 13: Content = content; 14: } 15: } Now let’s implement a message bus based on the IBus interface. Since I don’t want you to buy and install the TIBCO EMS or any other message bus products, I will implement an in process memory bus. This bus is only for test and sample purpose. It can only be used if the service and client are in the same process. Very straightforward. 1: public class InProcMessageBus : IBus 2: { 3: private readonly ConcurrentDictionary<Guid, InProcMessageEntity> _queue; 4: private readonly object _lock; 5:  6: public InProcMessageBus() 7: { 8: _queue = new ConcurrentDictionary<Guid, InProcMessageEntity>(); 9: _lock = new object(); 10: } 11:  12: public string SendRequest(string message, bool fromClient, string from, string to = null) 13: { 14: var entity = new InProcMessageEntity(message, fromClient, from, to); 15: _queue.TryAdd(entity.ID, entity); 16: return entity.ID.ToString(); 17: } 18:  19: public void SendReply(string message, bool fromClient, string replyTo) 20: { 21: var entity = new InProcMessageEntity(message, fromClient, null, replyTo); 22: _queue.TryAdd(entity.ID, entity); 23: } 24:  25: public BusMessage Receive(bool fromClient, string replyTo) 26: { 27: InProcMessageEntity e = null; 28: while (true) 29: { 30: lock (_lock) 31: { 32: var entity = _queue 33: .Where(kvp => kvp.Value.FromClient == fromClient && (kvp.Value.To == replyTo || string.IsNullOrWhiteSpace(kvp.Value.To))) 34: .FirstOrDefault(); 35: if (entity.Key != Guid.Empty && entity.Value != null) 36: { 37: _queue.TryRemove(entity.Key, out e); 38: } 39: } 40: if (e == null) 41: { 42: Thread.Sleep(100); 43: } 44: else 45: { 46: return new BusMessage(e.ID.ToString(), e.From, e.To, e.Content); 47: } 48: } 49: } 50:  51: public void Dispose() 52: { 53: } 54: } The InProcMessageBus stores the messages in the objects of InProcMessageEntity, which can take some extra information beside the WCF message itself. 1: public class InProcMessageEntity 2: { 3: public Guid ID { get; set; } 4: public string Content { get; set; } 5: public bool FromClient { get; set; } 6: public string From { get; set; } 7: public string To { get; set; } 8:  9: public InProcMessageEntity() 10: : this(string.Empty, false, string.Empty, string.Empty) 11: { 12: } 13:  14: public InProcMessageEntity(string content, bool fromClient, string from, string to) 15: { 16: ID = Guid.NewGuid(); 17: Content = content; 18: FromClient = fromClient; 19: From = from; 20: To = to; 21: } 22: }   Summary OK, now I have all necessary stuff ready. The next step would be implementing our WCF message bus transport extension. In this post I described two scaling-out approaches on the service side especially if we are using the cloud platform: dispatcher mode and pulling mode. And I compared the Pros and Cons of them. Then I introduced the WCF channel stack, channel mode and the transport extension part, and identified what we should do to create our own WCF transport extension, to let our WCF services using pulling mode based on a message bus. And finally I provided some classes that need to be used in the future posts that working against an in process memory message bus, for the demonstration purpose only. In the next post I will begin to implement the transport extension step by step.   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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  • MySQL Enterprise Backup 3.8.2 - Overview

    - by Priya Jayakumar
      MySQL Enterprise Backup (MEB) is the ideal solution for backing up MySQL databases. MEB 3.8.2 is released in June 2013. MySQL Enterprise Backup 3.8.2 release’s main goal is to improve usability. With this release, users can know the progress of backup completed both in terms of size and as a percentage of the total. This release also offers options to be able to manage the behavior of MEB in case the space on the secondary storage is completely exhausted during backup. The progress indicator is a (short) string that indicates how far the execution of a time-consuming MEB command has progressed. It consists of one or more "meters" that measures the progress of the command. There are two options introduced to control the progress reporting function of mysqlbackup command (1) –show-progress (2) –progress-interval. The user can control the progress indicator by using “--show-progress” option in any of the MEB operations. This option instructs MEB to output periodically short reports on the progress of time-consuming commands. The argument of this option instructs where the output could be sent. For example it could be stderr, stdout, file, fifo and table. With the “--show-progress” option both the total size of the backup to be copied and the size that’s already copied will be shown. Along with this, the state of the operation for example data or meta-data being copied or tables being locked and other such operations will also be reported. This gives more clear information to the DBA on the progress of the backup that’s happening. Interval between progress report in seconds is controlled by “--progress-interval” option. For more information on this please refer progress-report-options. MEB can also be accessed through GUI from MySQL WorkBench’s next version. This can be used as the front end interface for MEB users to perform backup operations at the click of a button. This feature was highly requested by DBAs and will be very useful. Refer http://insidemysql.com/mysql-workbench-6-0-a-sneak-preview/ for WorkBench upcoming release info. Along with the progress report feature some of the important issues like below are also addressed in MEB 3.8.2. In MEB 3.8.2 a new command line option “--on-disk-full” is introduced to abort or warn the user when a backup process encounters a full disk condition. When no option is given, by default it would abort. A few issues related to “incremental-backup” are also addressed in this release. Please refer 3.8.2 documentation for more details. It would be good for MEB users to move to 3.8.2 to take incremental backups. Overall the added usability and the important defects fixed in this release makes MySQL Enterprise Backup 3.8.2 a promising release.  

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  • How can I make a universal construction more efficient?

    - by VF1
    A "universal construction" is a wrapper class for a sequential object that enables it to be linearized (a strong consistency condition for concurrent objects). For instance, here's an adapted wait-free construction, in Java, from [1], which presumes the existence of a wait-free queue that satisfies the interface WFQ (which only requires one-time consensus between threads) and assumes a Sequential interface: public interface WFQ<T> // "FIFO" iteration { int enqueue(T t); // returns the sequence number of t Iterable<T> iterateUntil(int max); // iterates until sequence max } public interface Sequential { // Apply an invocation (method + arguments) // and get a response (return value + state) Response apply(Invocation i); } public interface Factory<T> { T generate(); } // generate new default object public interface Universal extends Sequential {} public class SlowUniversal implements Universal { Factory<? extends Sequential> generator; WFQ<Invocation> wfq = new WFQ<Invocation>(); Universal(Factory<? extends Sequential> g) { generator = g; } public Response apply(Invocation i) { int max = wfq.enqueue(i); Sequential s = generator.generate(); for(Invocation invoc : wfq.iterateUntil(max)) s.apply(invoc); return s.apply(i); } } This implementation isn't very satisfying, however, since it presumes determinism of a Sequential and is really slow. I attempted to add memory recycling: public interface WFQD<T> extends WFQ<T> { T dequeue(int n); } // dequeues only when n is the tail, else assists other threads public interface CopyableSequential extends Sequential { CopyableSequential copy(); } public class RecyclingUniversal implements Universal { WFQD<CopyableSequential> wfqd = new WFQD<CopyableSequential>(); Universal(CopyableSequential init) { wfqd.enqueue(init); } public Response apply(Invocation i) { int max = wfqd.enqueue(i); CopyableSequential cs = null; int ctr = max; for(CopyableSequential csq : wfq.iterateUntil(max)) if(--max == 0) cs = csq.copy(); wfqd.dequeue(max); return cs.apply(i); } } Here are my specific questions regarding the extension: Does my implementation create a linearizable multi-threaded version of a CopyableSequential? Is it possible extend memory recycling without extending the interface (perhaps my new methods trivialize the problem)? My implementation only reduces memory when a thread returns, so can this be strengthened? [1] provided an implementation for WFQ<T>, not WFQD<T> - one does exist, though, correct? [1] Herlihy and Shavit, The Art of Multiprocessor Programming.

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  • Parallel Port Problem in 12.04

    - by Frank Oberle
    I have a “dumb” printer attached to a parallel port in my machine which works fine under the “other” resident operating system (from Redmond) on the same machine. I recently added Ubuntu 12.04 as a dual boot on the machine, but Ubuntu doesn't seem to recognize the parallel port at all. All I need to set up a printer is a really plain-vanilla fixed pitch text-only generic driver, which is present, but no parallel ports show up. (The other printers, all on USB ports, seem to work just fine). Following what appeared to me to be the most reasonable of the many conflicting pieces of advice on the web, here's what I did: I added the following lines to /etc/modules parport_pc ppdev parport Then, after rebooting, I checked to see that the lines were still present, and they were. I ran dmesg | grep par and got the following references in the output that seemed like they might have to do with the parallel port: [ 14.169511] parport_pc 0000:03:07.0: PCI INT A -> GSI 21 (level, low) -> IRQ 21 [ 14.169516] PCI parallel port detected: 9710:9805, I/O at 0xce00(0xcd00), IRQ 21 [ 14.169577] parport0: PC-style at 0xce00 (0xcd00), irq 21, using FIFO [PCSPP,TRISTATE,COMPAT,ECP] [ 14.354254] lp0: using parport0 (interrupt-driven). [ 14.571358] ppdev: user-space parallel port driver [ 16.588304] type=1400 audit(1347226670.386:5): apparmor="STATUS" operation="profile_load" name="/usr/lib/cups/backend/cups-pdf" pid=964 comm="apparmor_parser" [ 16.588756] type=1400 audit(1347226670.386:6): apparmor="STATUS" operation="profile_load" name="/usr/sbin/cupsd" pid=964 comm="apparmor_parser" [ 16.673679] type=1400 audit(1347226670.470:7): apparmor="STATUS" operation="profile_load" name="/usr/lib/lightdm/lightdm/lightdm-guest-session-wrapper" pid=1010 comm="apparmor_parser" [ 16.675252] type=1400 audit(1347226670.470:8): apparmor="STATUS" operation="profile_load" name="/usr/lib/telepathy/mission-control-5" pid=1014 comm="apparmor_parser" [ 16.675716] type=1400 audit(1347226670.470:9): apparmor="STATUS" operation="profile_load" name="/usr/lib/telepathy/telepathy-*" pid=1014 comm="apparmor_parser" [ 16.676636] type=1400 audit(1347226670.474:10): apparmor="STATUS" operation="profile_replace" name="/usr/lib/cups/backend/cups-pdf" pid=1015 comm="apparmor_parser" [ 16.677124] type=1400 audit(1347226670.474:11): apparmor="STATUS" operation="profile_replace" name="/usr/sbin/cupsd" pid=1015 comm="apparmor_parser" [ 1545.725328] parport0: ppdev0 forgot to release port I have no idea what any of that means, but the line “parport0: ppdev0 forgot to release port ” seems unusual. I was still unable to add a printer for my old clunker, so I tried the direct approach, typing echo “Hello” > /dev/lp0 and received a Permission denied message. I then tried echo “Hello” > /dev/parport0 which didn't give me any message at all, but still didn't print anything. Running the command sudo /usr/lib/cups/backend/parallel gives the following: direct parallel:/dev/lp0 "unknown" "LPT #1" "" "" Checking the permissions for /dev/parport0, Owner, Group, and Other are all set to read and write. crw-rw---- 1 root lp 6, 0 Sep 9 16:37 /dev/lp0 crw-rw-rw- 1 root lp 99, 0 Sep 9 16:37 /dev/parport0 The output of the command lpinfo -v includes the following line: direct parallel:/dev/lp0 I've read several web postings that seem to suggest this has been a problem for several years, but the bug reports were closed because there wasn't enough information to address the issue (shades of Microsoft!). Any suggestions as to what I might be missing here?

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  • Event Driven Behavior Tree: deterministic traversal order with parallel

    - by Heisenbug
    I've studied several articles and listen some talks about behavior trees (mostly the resources available on AIGameDev by Alex J. Champandard). I'm particularly interested on event driven behavior trees, but I have still some doubts on how to implement them correctly using a scheduler. Just a quick recap: Standard Behavior Tree Each execution tick the tree is traversed from the root in depth-first order The execution order is implicitly expressed by the tree structure. So in the case of behaviors parented to a parallel node, even if both children are executed during the same traversing, the first leaf is always evaluated first. Event Driven BT During the first traversal the nodes (tasks) are enqueued using a scheduler which is responsible for updating only running ones every update The first traversal implicitly produce a depth-first ordered queue in the scheduler Non leaf nodes stays suspended mostly of the time. When a leaf node terminate(either with success or fail status) the parent (observer) is waked up allowing the tree traversing to continue and new tasks will be enqueued in the scheduler Without parallel nodes in the tree there will be up to 1 task running in the scheduler Without parallel nodes, the tasks in the queue(excluding dynamic priority implementation) will be always ordered in a depth-first order (is this right?) Now, from what is my understanding of a possible implementation, there are 2 requirements I think must be respected(I'm not sure though): Now, some requirements I think needs to be guaranteed by a correct implementation are: The result of the traversing should be independent from which implementation strategy is used. The traversing result must be deterministic. I'm struggling trying to guarantee both in the case of parallel nodes. Here's an example: Parallel_1 -->Sequence_1 ---->leaf_A ---->leaf_B -->leaf_C Considering a FIFO policy of the scheduler, before leaf_A node terminates the tasks in the scheduler are: P1(suspended),S1(suspended),leaf_A(running),leaf_C(running) When leaf_A terminate leaf_B will be scheduled (at the end of the queue), so the queue will become: P1(suspended),S1(suspended),leaf_C(running),leaf_B(running) In this case leaf_B will be executed after leaf_C at every update, meanwhile with a non event-driven traversing from the root node, the leaf_B will always be evaluated before leaf_A. So I have a couple of question: do I have understand correctly how event driven BT work? How can I guarantee the depth first order is respected with such an implementation? is this a common issue or am I missing something?

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  • Abnormally high amount of Transmit discards reported by Solarwinds for multiple switches

    - by Jared
    I have several 3750X Cisco switches that, according to our Solarwinds NPM, are producing billions of transmit discards per day. I'm not sure why it's reporting these discards. Many of the ports on the 3750X's have 2960's connected to them and are hardcoded as trunk ports. Solarwinds NPM version 10.3 Cisco IOS version 12.2(58)SE2 Total output drops: 29139431: GigabitEthernet1/0/43 is up, line protocol is up (connected) Hardware is Gigabit Ethernet, address is XXXX (bia XXXX) Description: XXXX MTU 1500 bytes, BW 100000 Kbit/sec, DLY 100 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full-duplex, 100Mb/s, media type is 10/100/1000BaseTX input flow-control is off, output flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input 00:00:47, output 00:00:50, output hang never Last clearing of "show interface" counters 1w4d Input queue: 0/75/0/0 (size/max/drops/flushes); Total output drops: 29139431 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 35000 bits/sec, 56 packets/sec 51376 packets input, 9967594 bytes, 0 no buffer Received 51376 broadcasts (51376 multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 51376 multicast, 0 pause input 0 input packets with dribble condition detected 115672302 packets output, 8673778028 bytes, 0 underruns 0 output errors, 0 collisions, 0 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out sh controllers gigabitEthernet 1/0/43 utilization: Receive Bandwidth Percentage Utilization : 0 Transmit Bandwidth Percentage Utilization : 0

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  • Immediately tell which output was sent to stderr

    - by Clinton Blackmore
    When automating a task, it is sensible to test it first manually. It would be helpful, though, if any data going to stderr was immediately recognizeable as such, and distinguishable from the data going to stdout, and to have all the output together so it is obvious what the sequence of events is. One last touch that would be nice is if, at program exit, it printed its return code. All of these things would aid in automating. Yes, I can echo the return code when a program finishes, and yes, I can redirect stdout and stderr; what I'd really like it some shell, script, or easy-to-use redirector that shows stdout in black, shows stderr interleaved with it in red, and prints the exit code at the end. Is there such a beast? [If it matters, I'm using Bash 3.2 on Mac OS X]. Update: Sorry it has been months since I've looked at this. I've come up with a simple test script: #!/usr/bin/env python import sys print "this is stdout" print >> sys.stderr, "this is stderr" print "this is stdout again" In my testing (and probably due to the way things are buffered), rse and hilite display everything from stdout and then everything from stderr. The fifo method gets the order right but appears to colourize everything following the stderr line. ind complained about my stdin and stderr lines, and then put the output from stderr last. Most of these solutions are workable, as it is not atypical for only the last output to go to stderr, but still, it'd be nice to have something that worked slightly better.

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  • How can I "filter" postfix-generated bounce messages?

    - by Flimzy
    We are using postfix 2.7 and custom SMTPD (based on qpsmtpd) in highly customized configuration for spam filtering. We have a new requirement to filter postfix-generated bounces through our custom qpsmtpd process (not so much for content filtering, but to process these bounces accordingly). Our current configuration looks (in part) like this: main.cf (only customizations shown): 2526 inet n - - - 0 cleanup pickup fifo n - - 60 1 pickup -o content_filter=smtp:127.0.0.2 Our smtpd injects messages to postfix on port 2526, by speaking directly to the cleanup daemon. And the custom pickup command instructs postfix to hand off all locally-generated mail (from cron, nagios, or other custom scripts) to our custom smtpd. The problem is that this configuration does not affect postfix generated bounce messages, since they do not go through the pickup daemon. I have tried adding the same content_filter option to the bounce daemon commands, but it does not seem to have any effect: bounce unix - - - - 0 bounce -o content_filter=smtp:127.0.0.2 defer unix - - - - 0 bounce -o content_filter=smtp:127.0.0.2 trace unix - - - - 0 bounce -o content_filter=smtp:127.0.0.2 For reference, here is my main.cf file, as well: biff = no # TLS parameters smtpd_tls_loglevel = 0 smtpd_tls_cert_file=/etc/ssl/certs/ssl-cert-snakeoil.pem smtpd_tls_key_file=/etc/ssl/private/ssl-cert-snakeoil.key smtpd_use_tls=yes smtpd_tls_session_cache_database = btree:${queue_directory}/smtpd_scache smtp_tls_session_cache_database = btree:${queue_directory}/smtp_scache smtp_tls_security_level = may mydestination = $myhostname alias_maps = proxy:pgsql:/etc/postfix/dc-aliases.cf transport_maps = proxy:pgsql:/etc/postfix/dc-transport.cf # This is enforced on incoming mail by QPSMTPD, so this is simply # the upper possible bound (also enforced in defaults.pl) message_size_limit = 262144000 mailbox_size_limit = 0 # We do our own message expiration, but if we set this to 0, then postfix # will try each mail delivery only once, so instead we set it to 100 days # (which is the max postfix seems to support) maximal_queue_lifetime = 100d hash_queue_depth = 1 hash_queue_names = deferred, defer, hold I also tried adding the internal_mail_filter_classes option to main.cf, but also tono affect: internal_mail_filter_classes = bounce,notify I am open to any suggestions, including handling our current content-filtering-loop in a different way. If it's not clear what I'm asking, please let me know, and I can try to clarify.

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  • cpusets not working - threads aren't running in the cpuset I specified?

    - by lori
    I have used cpuset to shield some cpus for exclusive use by some realtime threads. Displaying the cpuset config with the test app RealtimeTest1 running and its tasks moved into the cpusets: $ cset set --list -r cset: Name CPUs-X MEMs-X Tasks Subs Path ------------ ---------- - ------- - ----- ---- ---------- root 0-23 y 0-1 y 279 2 / system 0,2,4,6,8,10 n 0 n 202 0 /system shield 1,3,5,7,9,11 n 1 n 0 2 /shield RealtimeTest1 1,3,5,7 n 1 n 0 4 /shield/RealtimeTest1 thread1 3 n 1 n 1 0 /shield/RealtimeTest1/thread1 thread2 5 n 1 n 1 0 /shield/RealtimeTest1/thread2 main 1 n 1 n 1 0 /shield/RealtimeTest1/main I can interrogate the cpuset filesystem to show that my tasks are supposedly pinned to the cpus I requested: /cpusets/shield/RealtimeTest1 $ for i in `find -name tasks`; do echo $i; cat $i; echo "------------"; done ./thread1/tasks 17651 ------------ ./main/tasks 17649 ------------ ./thread2/tasks 17654 ------------ Further, if I use sched_getaffinity, it reports what cpuset does - that thread1 is on cpu 3 and thread2 is on cpu 5. However, if I run top -p 17649 -H with f,j to bring up the last used cpu, it shows that thread 1 is running on thread 2's cpu, and main thread is running on a cpu in the system cpuset (Note that thread 17654 is running FIFO, hence thread 17651 is blocked) PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ P COMMAND 17654 root -2 0 54080 35m 7064 R 100 0.4 5:00.77 3 RealtimeTest 17649 root 20 0 54080 35m 7064 S 0 0.4 0:00.05 2 RealtimeTest 17651 root 20 0 54080 35m 7064 R 0 0.4 0:00.00 3 RealtimeTest Also, looking at /proc/17649/task to find the last_cpu each of its tasks ran on: /proc/17649/task $ for i in `ls -1`; do cat $i/stat | awk '{print $1 " is on " $(NF - 5)}'; done 17649 is on 2 17651 is on 3 17654 is on 3 So cpuset and sched_getaffinity reports one thing, but reality is another I would say that cpuset is not working? My machine configuration is: $ cat /etc/SuSE-release SUSE Linux Enterprise Server 11 (x86_64) VERSION = 11 PATCHLEVEL = 1 $ uname -a Linux foobar 2.6.32.12-0.7-default #1 SMP 2010-05-20 11:14:20 +0200 x86_64 x86_64 x86_64 GNU/Linux

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  • C# Dev Challenge Part 1 of n &ndash; Beginner Edition

    - by mbcrump
    I developed this challenge to test one’s knowledge of C Sharp. I am planning on creating several challenges with different skill sets, so don’t get mad if this challenge doesn’t well challenge you... I noticed that most people like short quizzes so this one only contains 5 questions. All of the challenges are clear and concise of what I am asking you to do. No smoke and mirrors here, meaning that none of the code has syntax errors. The purpose of this exercise is to test several OOP concepts and see how much of the C# language you really know. Question #1 – Lets start off Easy… Will the following code snippet compile successfully? What does this question test? - Can this compile without a namespace? Do you have to have an entry point of “static void Main()”? class Test { static int Main() { System.Console.WriteLine("Developer Challenge"); return 0; } } Answer (select text in box below): Yes, it will compile successfully. Question #2 – What is the value of the Console.WriteLine statements? What does this question test? – Do I understand reference types/value types? If a variable is declared with the @ symbol and its not a reserved keyword does the application compile successfully? using System; internal struct MyStruct { public int Value; } internal class MyClass { public int Value; } class Test { static void Main() { MyStruct @struct1 = new MyStruct(); MyStruct @struct2 = @struct1; @struct2.Value = 100; MyClass @ref1 = new MyClass(); MyClass @ref2 = @ref1; @ref2.Value = 100; Console.WriteLine("Value Type: {0} {1}", @struct1.Value, @struct2.Value); Console.WriteLine("Reference Type: {0} {1}", @ref1.Value, @ref2.Value); } } Answer (select text in box below): Value Type: 0 100 Reference Type: 100 100 Question #3 – What is the value of the Console.WriteLine statements? What does this question test? – Can 2 objects reference the same point in memory? using System; class Test { static void Main() { string s1 = "Testing2"; string t1 = s1; Console.WriteLine(s1 == t1); Console.WriteLine((object)s1 == (object)t1); } } Answer (select text in box below): True True Question #4 – What is the value of the Console.WriteLine statements? What does this question test? – How does the “Stack” work – LIFO or FIFO?   using System; using System.Collections; class Test { static void Main() { Stack a = new Stack(5); a.Push("1"); a.Push("2"); a.Push("3"); a.Push("4"); a.Push("5"); foreach (var o in a) { Console.WriteLine(o); } } } Answer (select text in box below): 5 4 3 2 1 Question #5 – What is the value of the Console.WriteLine statements? What does this question test? – Array and General Looping Knowledge. using System; namespace ConsoleApplication5 { class Program { static void Main(string[] args) { int[] J_LIST = new int[5] { 1, 2, 3, 4, 5 }; int K = 10; int L = 5; foreach (var J in J_LIST) { K = K - J; L = K + 2 * J; Console.WriteLine("J = {0, 5} K = {1, 5} L = {2, 5}", J, K, L); } Console.ReadLine(); } } } Answer (select text in box below): J = 1 K = 9 L = 11 J = 2 K = 7 L = 11 J = 3 K = 4 L = 10 J = 4 K = 0 L = 8 J = 5 K = -5 L = 5 Stay Tuned for more challenges!

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  • Should business objects be able to create their own DTOs?

    - by Sam
    Suppose I have the following class: class Camera { public Camera( double exposure, double brightness, double contrast, RegionOfInterest regionOfInterest) { this.exposure = exposure; this.brightness = brightness; this.contrast = contrast; this.regionOfInterest = regionOfInterest; } public void ConfigureAcquisitionFifo(IAcquisitionFifo acquisitionFifo) { // do stuff to the acquisition FIFO } readonly double exposure; readonly double brightness; readonly double contrast; readonly RegionOfInterest regionOfInterest; } ... and a DTO to transport the camera info across a service boundary (WCF), say, for viewing in a WinForms/WPF/Web app: using System.Runtime.Serialization; [DataContract] public class CameraData { [DataMember] public double Exposure { get; set; } [DataMember] public double Brightness { get; set; } [DataMember] public double Contrast { get; set; } [DataMember] public RegionOfInterestData RegionOfInterest { get; set; } } Now I can add a method to Camera to expose its data: class Camera { // blah blah public CameraData ToData() { var regionOfInterestData = regionOfInterest.ToData(); return new CameraData() { Exposure = exposure, Brightness = brightness, Contrast = contrast, RegionOfInterestData = regionOfInterestData }; } } or, I can create a method that requires a special IReporter to be passed in for the Camera to expose its data to. This removes the dependency on the Contracts layer (Camera no longer has to know about CameraData): class Camera { // beep beep I'm a jeep public void ExposeToReporter(IReporter reporter) { reporter.GetCameraInfo(exposure, brightness, contrast, regionOfInterest); } } So which should I do? I prefer the second, but it requires the IReporter to have a CameraData field (which gets changed by GetCameraInfo()), which feels weird. Also, if there is any even better solution, please share with me! I'm still an object-oriented newb.

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  • Three.js: texture to datatexture

    - by Alessandro Pezzato
    I'm trying to implement a delayed webcam viewer in javascript, using Three.js for WebGL capabilities. I need to store frames grabbed from webcam, so they can be shown after some time (some milliseconds to some seconds). I'm able to do this without Three.js, using canvas and getImageData(). You can find an example on jsfidle. I'm trying to find a way to do this without canvas, but using Three.js Texture or DataTexture object. Here an example of what I'm trying. The problem is that I cannot find how to copy the image from a Texture (image is of type HTMLVideoElement) to another. In rotateFrames() function the older frame should be lost and newer should replace, like in a FIFO. But the line frames[i].image = frames[i + 1].image; is just copying the reference, not the texture data. I guess DataTexture should do this, but I'm not able to get a DataTexture out of a Texture or HTMLVideoElement. Any idea?

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  • Threads, Sockets, and Designing Low-Latency, High Concurrency Servers

    - by lazyconfabulator
    I've been thinking a lot lately about low-latency, high concurrency servers. Specifically, http servers. http servers (fast ones, anyway) can serve thousands of users simultaneously, with very little latency. So how do they do it? As near as I can tell, they all use events. Cherokee and Lighttpd use libevent. Nginx uses it's own event library performing much the same function of libevent, that is, picking a platform optimal strategy for polling events (like kqueue on *bsd, epoll on linux, /dev/poll on Solaris, etc). They all also seem to employ a strategy of multiprocess or multithread once the connection is made - using worker threads to handle the more cpu intensive tasks while another thread continues to listen and handle connections (via events). This is the extent of my understanding and ability to grok the thousand line sources of these applications. What I really want are finer details about how this all works. In examples of using events I've seen (and written) the events are handling both input and output. To this end, do the workers employ some sort of input/output queue to the event handling thread? Or are these worker threads handling their own input and output? I imagine a fixed amount of worker threads are spawned, and connections are lined up and served on demand, but how does the event thread feed these connections to the workers? I've read about FIFO queues and circular buffers, but I've yet to see any implementations to work from. Are there any? Do any use compare-and-swap instructions to avoid locking or is locking less detrimental to event polling than I think? Or have I misread the design entirely? Ultimately, I'd like to take enough away to improve some of my own event-driven network services. Bonus points to anyone providing solid implementation details (especially for stuff like low-latency queues) in C, as that's the language my network services are written in.

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  • Pthread Queue System

    - by Wallace
    Hi. I'm working on my assignment on pthreads. I'm new and never touched on pthreads before. Is there any sample codes or resources out there that anyone of you have, that might aid me in my assignment? Here are my assignment details. A pthread program about queue system: Write a C/C++ Pthread program for a Dental clinic’s queuing system that declares an array of integers of size N, where N is the maximum number of queue for the day. The pthread program uses two threads. Whenever there is a new dental appointment, the first thread (the creator) puts the queue numbers in the array, one after the other. The second thread (the remover) removes the queue numbers from the array whenever the dentist has seen the patient. This is done in a FIFO fashion (First In First Out). The algorithm of the creator is as follows: • If the array is not full then put a new number in it (the numbers start at 1 and are incremented by one each time, so the creator create queue number 1, 2, 3 etc.) • sleep for 1 to 10 seconds, randomly • repeat The algorithm of the remover is as follows: • If the array is not empty then remove its smallest queue number • sleep for 1 to 10 seconds, randomly • repeat You should use mutex locks to protect things that must be protected. Each thread should print on the screen what it is doing (eg: "number 13 is added into the queue", "number 7 is removed from the queue", etc.). The program should run forever. Any help will be appreciated. Thanks.

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  • Linked List pop() function

    - by JKid314159
    Consider the following list: [LinkNode * head -- LinkNode * node1 -- LinkNode * node2] I'm creating a stack of FIFO. I Call pop() which I want to pop node1. LinkNode::LinkNode(int numIn) { this->numIn = numIn; next = null; } . . . int LinkNode::pop() { Link * temp = head->next; head = temp->next; int popped = head->nodeNum; delete temp; Return numOut; Question: 1) head should be a pointer or a LinkNode *? 2) Link * temp is created on the call stack and when pop finishes doesn't temp delete automatically? 3) My major confusion is on what is the value of temp-next? Does this point to node1.next which equals node2? Appreciate your help? My reference is C++ for Java Programmers by Weiss.

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  • Using pipes in Linux with C

    - by Dave
    Hi, I'm doing a course in Operating Systems and we're supposed to learn how to use pipes to transfer data between processes. We were given this simple piece of code which demonstrates how to use pipes,but I'm having difficulty understanding it. #include <stdio.h> #include <stdlib.h> #include <unistd.h> main() { int pipefd [2], n; char buff[100] ; if( pipe( pipefd) < 0) { printf("can not create pipe \n"); } printf("read fd = %d, write fd = %d \n", pipefd[0], pipefd[1]); if ( write (pipefd[1],"hello world\n", 12)!= 12) { printf("pipe write error \n"); } if( ( n = read ( pipefd[0] , buff, sizeof ( buff) ) ) <= 0 ) { printf("pipe read error \n"); } write ( 1, buff, n ) ; exit (0); } What does the write function do? It seems to send data to the pipe and also print it to the screen (at least it seems like the second time the write function is called it does this). Does anyone have any suggestions of good websites for learning about topics such as this, FIFO, signals, other basic linux commands used in C?

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