Search Results

Search found 3641 results on 146 pages for 'threads'.

Page 40/146 | < Previous Page | 36 37 38 39 40 41 42 43 44 45 46 47  | Next Page >

  • Creating sitemap for Googlebot - how to mark dynamic content / dynamic subpages?

    - by ojek
    I have a website that is an Internet forum. This forum has many categories, and a single category page that contains a lot of subpages with listed threads. This Internet forum is brand new, and about a week ago I filled it with a few hundred thousand threads. I then looked at my Google Webmasters Tools page to see any changes in indexing, but the index went up from 300 to about 1200, so that means it did not index my added threads (although it added something). The following is what my sitemap.xml contains, which I uploaded to their website. Of course there is a lot more code, this is just a snippet for a single category. In my real sitemap file I have all the categories listed as below: <url> <loc>http://mysite.com/Forums/Physics</loc> <changefreq>hourly</changefreq> </url> Now, I would expect Googlebot to go into mysite.com/Forums/Physics, and crawl through all the subpages with thread links, and then crawl inside of each thread and index its content. How can I achieve this? Also if this is unclear, I will add a real link to my website.

    Read the article

  • The Importance of Fully Specifying a Problem

    - by Alan
    I had a customer call this week where we were provided a forced crashdump and asked to determine why the system was hung. Normally when you are looking at a hung system, you will find a lot of threads blocked on various locks, and most likely very little actually running on the system (unless it's threads spinning on busy wait type locks). This vmcore showed none of that. In fact we were seeing hundreds of threads actively on cpu in the second before the dump was forced. This prompted the question back to the customer: What exactly were you seeing that made you believe that the system was hung? It took a few days to get a response, but the response that I got back was that they were not able to ssh into the system and when they tried to login to the console, they got the login prompt, but after typing "root" and hitting return, the console was no longer responsive. This description puts a whole new light on the "hang". You immediately start thinking "name services". Looking at the crashdump, yes the sshds are all in door calls to nscd, and nscd is idle waiting on responses from the network. Looking at the connections I see a lot of connections to the secure ldap port in CLOSE_WAIT, but more interestingly I am seeing a few connections over the non-secure ldap port to a different LDAP server just sitting open. My feeling at this point is that we have an either non-responding LDAP server, or one that is responding slowly, the resolution being to investigate that server. Moral When you log a service ticket for a "system hang", it's great to get the forced crashdump first up, but it's even better to get a description of what you observed to make to believe that the system was hung.

    Read the article

  • Uses of persistent data structures in non-functional languages

    - by Ray Toal
    Languages that are purely functional or near-purely functional benefit from persistent data structures because they are immutable and fit well with the stateless style of functional programming. But from time to time we see libraries of persistent data structures for (state-based, OOP) languages like Java. A claim often heard in favor of persistent data structures is that because they are immutable, they are thread-safe. However, the reason that persistent data structures are thread-safe is that if one thread were to "add" an element to a persistent collection, the operation returns a new collection like the original but with the element added. Other threads therefore see the original collection. The two collections share a lot of internal state, of course -- that's why these persistent structures are efficient. But since different threads see different states of data, it would seem that persistent data structures are not in themselves sufficient to handle scenarios where one thread makes a change that is visible to other threads. For this, it seems we must use devices such as atoms, references, software transactional memory, or even classic locks and synchronization mechanisms. Why then, is the immutability of PDSs touted as something beneficial for "thread safety"? Are there any real examples where PDSs help in synchronization, or solving concurrency problems? Or are PDSs simply a way to provide a stateless interface to an object in support of a functional programming style?

    Read the article

  • Concurrency pattern of logger in multithreaded application

    - by Dipan Mehta
    The context: We are working on a multi-threaded (Linux-C) application that follows a pipeline model. Each module has a private thread and encapsulated objects which do processing of data; and each stage has a standard form of exchanging data with next unit. The application is free from memory leak and is threadsafe using locks at the point where they exchange data. Total number of threads is about 15- and each thread can have from 1 to 4 objects. Making about 25 - 30 odd objects which all have some critical logging to do. Most discussion I have seen about different levels as in Log4J and it's other translations. The real big questions is about how the overall logging should really happen? One approach is all local logging does fprintf to stderr. The stderr is redirected to some file. This approach is very bad when logs become too big. If all object instantiate their individual loggers - (about 30-40 of them) there will be too many files. And unlike above, one won't have the idea of true order of events. Timestamping is one possibility - but it is still a mess to collate. If there is a single global logger (singleton) pattern - it indirectly blocks so many threads while one is busy putting up logs. This is unacceptable when processing of the threads are heavy. So what should be the ideal way to structure the logging objects? What are some of the best practices in actual large scale applications? I would also love to learn from some of the real designs of large scale applications to get inspirations from!

    Read the article

  • Creating sitemap for google bot - how to mark dynamic content / dynamic subpages?

    - by ojek
    I have a website that is internet forum. This forum has many categories, and single category page contains alot of subpages with listed threads. This internet forum is brand new, and about a week ago I filled it with few hundred thousands threads. I then looked at google webmasters page to see any changes in indexing, but the index went up from 300 to about 1200, so that means it did not index my added threads (although it added something). This is what my sitemap.xml contains which I uploaded on their website (of course there is a lot more of the code, this is just a snipped for a single category, in my real sitemap file I have all the categories listed as below): <url> <loc>http://mysite.com/Forums/Physics</loc> <changefreq>hourly</changefreq> </url> Now, I would expect google bot to go into http://mysite.com/Forums/Physics, and move through all the subpages with thread links, and then get inside of each thread and index it's content. How can I do this? Also if this will be unclear, I will add a real link to my website.

    Read the article

  • Marking Discussions as Answered

    As a contributor to a number of projects on CodePlex I really like the fact that the discussions feature exists but also I need ways to help me sort the discussions threads so I can make sure no-one is getting forgotten about. Seems like a lot of you agreed as the feature request Provide feature to allow Coordinators to mark Discussions threads as 'Answered' is our number 2 voted feature right now with 178 votes.  Today we rolled out the first iteration of “answer” support to discussions. In this first iteration we wanted to keep it simple and lightweight. The original poster of the thread along with project owners, developers or editors can mark any post to the thread as an answer. You can have any number of answers marked in a thread and it’s very quick to mark or unmark a post as an answer.  We deliberately keep the answers in the originally posted order so that you can see them in context with the discussion thread. When viewing discussions the default view is still to see everything, but you can easily filter by “Unanswered”.  You can even save that as a bookmark so as someone interested in the project can quickly jump to the unanswered discussion threads to go help out on. As I mention, we kept this first pass of the answering feature as simple and as lightweight as possible so that we can get some feedback on it. Head on over to the issue tracking this feature if you have any thoughts once you have used it for a bit or feel free to respond in the comments. I already have a couple of things I think we want to do such as a refresh of the look and feel of discussions in general along, make it easier to navigate to posts that are marked an answered and surface posts that you do that were marked as answered in your profile page - but if you have ideas then please let us know.

    Read the article

  • How can I tell if I am overusing multi-threading?

    - by exhuma
    NOTE: This is a complete re-write of the question. The text before was way too lengthy and did not get to the point! If you're interested in the original question, you can look it up in the edit history. I currently feel like I am over-using multi-threading. I have 3 types of data, A, B and C. Each A can be converted to multiple Bs and each B can be converted to multiple Cs. I am only interested in treating Cs. I could write this fairly easily with a couple of conversion functions. But I caught myself implementing it with threads, three queues (queue_a, queue_b and queue_c). There are two threads doing the different conversions, and one worker: ConverterA reads from queue_a and writes to queue_b ConverterB reads from queue_b and writes to queue_c Worker handles each element from queue_c The conversions are fairly mundane, and I don't know if this model is too convoluted. But it seems extremely robust to me. Each "converter" can start working even before data has arrived on the queues, and at any time in the code I can just "submit" new As or Bs and it will trigger the conversion pipeline which in turn will trigger a job by the worker thread. Even the resulting code looks simpler. But I still am unsure if I am abusing threads for something simple.

    Read the article

  • multi-thread in mmorpg server

    - by jean
    For MMORPG, there is a tick function to update every object's state in a map. The function was triggered by a timer in fixed interval. So each map's update can be dispatch to different thread. At other side, server handle player incoming package have its own threads also: I/O threads. Generally, the handler of the corresponding incoming package run in I/O threads. So there is a problem: thread synchronization. I have consider two methods: Synchronize with mutex. I/O thread lock a mutex before execute handler function and map thread lock same mutex before it execute map's update. Execute all handler functions in map's thread, I/O thread only queue the incoming handler and let map thread to pop the queue then call handler function. These two have a disadvantage: delay. For method 1, if the map's tick function is running, then all clients' request need to waiting the lock release. For method 2, if map's tick function is running, all clients' request need to waiting for next tick to be handle. Of course, there is another method: add lock to functions that use data which will be accessed both in I/O thread & map thread. But this is hard to maintain and easy to goes incorrect. It needs carefully check all variables whether or not accessed by both two kinds thread. My problem is: is there better way to do this? Notice that I said map is logic concept means no interactions can happen between two map except transport. I/O thread means thread in 3rd part network lib which used to handle client request.

    Read the article

  • Context switches much slower in new linux kernels

    - by Michael Goldshteyn
    We are looking to upgrade the OS on our servers from Ubuntu 10.04 LTS to Ubuntu 12.04 LTS. Unfortunately, it seems that the latency to run a thread that has become runnable has significantly increased from the 2.6 kernel to the 3.2 kernel. In fact the latency numbers we are getting are hard to believe. Let me be more specific about the test. We have a program that has two threads. The first thread gets the current time (in ticks using RDTSC) and then signals a condition variable once a second. The second thread waits on the condition variable and wakes up when it is signaled. It then gets the current time (in ticks using RDTSC). The difference between the time in the second thread and the time in the first thread is computed and displayed on the console. After this the second thread waits on the condition variable once more. So, we get a thread to thread signaling latency measurement once a second as a result. In linux 2.6.32, this latency is somewhere on the order of 2.8-3.5 us, which is reasonable. In linux 3.2.0, this latency is somewhere on the order of 40-100 us. I have excluded any differences in hardware between the two host hosts. They run on identical hardware (dual socket X5687 {Westmere-EP} processors running at 3.6 GHz with hyperthreading, speedstep and all C states turned off). We are changing the affinity to run both threads on physical cores of the same socket (i.e., the first thread is run on Core 0 and the second thread is run on Core 1), so there is no bouncing of threads on cores or bouncing/communication between sockets. The only difference between the two hosts is that one is running Ubuntu 10.04 LTS with kernel 2.6.32-28 (the fast context switch box) and the other is running the latest Ubuntu 12.04 LTS with kernel 3.2.0-23 (the slow context switch box). Have there been any changes in the kernel that could account for this ridiculous slow down in how long it takes for a thread to be scheduled to run?

    Read the article

  • Understanding G1 GC Logs

    - by poonam
    The purpose of this post is to explain the meaning of GC logs generated with some tracing and diagnostic options for G1 GC. We will take a look at the output generated with PrintGCDetails which is a product flag and provides the most detailed level of information. Along with that, we will also look at the output of two diagnostic flags that get enabled with -XX:+UnlockDiagnosticVMOptions option - G1PrintRegionLivenessInfo that prints the occupancy and the amount of space used by live objects in each region at the end of the marking cycle and G1PrintHeapRegions that provides detailed information on the heap regions being allocated and reclaimed. We will be looking at the logs generated with JDK 1.7.0_04 using these options. Option -XX:+PrintGCDetails Here's a sample log of G1 collection generated with PrintGCDetails. 0.522: [GC pause (young), 0.15877971 secs] [Parallel Time: 157.1 ms] [GC Worker Start (ms): 522.1 522.2 522.2 522.2 Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] [Processed Buffers : 2 2 3 2 Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] [GC Worker Other (ms): 0.3 0.3 0.3 0.3 Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] [Clear CT: 0.1 ms] [Other: 1.5 ms] [Choose CSet: 0.0 ms] [Ref Proc: 0.3 ms] [Ref Enq: 0.0 ms] [Free CSet: 0.3 ms] [Eden: 12M(12M)->0B(10M) Survivors: 0B->2048K Heap: 13M(64M)->9739K(64M)] [Times: user=0.59 sys=0.02, real=0.16 secs] This is the typical log of an Evacuation Pause (G1 collection) in which live objects are copied from one set of regions (young OR young+old) to another set. It is a stop-the-world activity and all the application threads are stopped at a safepoint during this time. This pause is made up of several sub-tasks indicated by the indentation in the log entries. Here's is the top most line that gets printed for the Evacuation Pause. 0.522: [GC pause (young), 0.15877971 secs] This is the highest level information telling us that it is an Evacuation Pause that started at 0.522 secs from the start of the process, in which all the regions being evacuated are Young i.e. Eden and Survivor regions. This collection took 0.15877971 secs to finish. Evacuation Pauses can be mixed as well. In which case the set of regions selected include all of the young regions as well as some old regions. 1.730: [GC pause (mixed), 0.32714353 secs] Let's take a look at all the sub-tasks performed in this Evacuation Pause. [Parallel Time: 157.1 ms] Parallel Time is the total elapsed time spent by all the parallel GC worker threads. The following lines correspond to the parallel tasks performed by these worker threads in this total parallel time, which in this case is 157.1 ms. [GC Worker Start (ms): 522.1 522.2 522.2 522.2Avg: 522.2, Min: 522.1, Max: 522.2, Diff: 0.1] The first line tells us the start time of each of the worker thread in milliseconds. The start times are ordered with respect to the worker thread ids – thread 0 started at 522.1ms and thread 1 started at 522.2ms from the start of the process. The second line tells the Avg, Min, Max and Diff of the start times of all of the worker threads. [Ext Root Scanning (ms): 1.6 1.5 1.6 1.9 Avg: 1.7, Min: 1.5, Max: 1.9, Diff: 0.4] This gives us the time spent by each worker thread scanning the roots (globals, registers, thread stacks and VM data structures). Here, thread 0 took 1.6ms to perform the root scanning task and thread 1 took 1.5 ms. The second line clearly shows the Avg, Min, Max and Diff of the times spent by all the worker threads. [Update RS (ms): 38.7 38.8 50.6 37.3 Avg: 41.3, Min: 37.3, Max: 50.6, Diff: 13.3] Update RS gives us the time each thread spent in updating the Remembered Sets. Remembered Sets are the data structures that keep track of the references that point into a heap region. Mutator threads keep changing the object graph and thus the references that point into a particular region. We keep track of these changes in buffers called Update Buffers. The Update RS sub-task processes the update buffers that were not able to be processed concurrently, and updates the corresponding remembered sets of all regions. [Processed Buffers : 2 2 3 2Sum: 9, Avg: 2, Min: 2, Max: 3, Diff: 1] This tells us the number of Update Buffers (mentioned above) processed by each worker thread. [Scan RS (ms): 9.9 9.7 0.0 9.7 Avg: 7.3, Min: 0.0, Max: 9.9, Diff: 9.9] These are the times each worker thread had spent in scanning the Remembered Sets. Remembered Set of a region contains cards that correspond to the references pointing into that region. This phase scans those cards looking for the references pointing into all the regions of the collection set. [Object Copy (ms): 106.7 106.8 104.6 107.9 Avg: 106.5, Min: 104.6, Max: 107.9, Diff: 3.3] These are the times spent by each worker thread copying live objects from the regions in the Collection Set to the other regions. [Termination (ms): 0.0 0.0 0.0 0.0 Avg: 0.0, Min: 0.0, Max: 0.0, Diff: 0.0] Termination time is the time spent by the worker thread offering to terminate. But before terminating, it checks the work queues of other threads and if there are still object references in other work queues, it tries to steal object references, and if it succeeds in stealing a reference, it processes that and offers to terminate again. [Termination Attempts : 1 4 4 6 Sum: 15, Avg: 3, Min: 1, Max: 6, Diff: 5] This gives the number of times each thread has offered to terminate. [GC Worker End (ms): 679.1 679.1 679.1 679.1 Avg: 679.1, Min: 679.1, Max: 679.1, Diff: 0.1] These are the times in milliseconds at which each worker thread stopped. [GC Worker (ms): 156.9 157.0 156.9 156.9 Avg: 156.9, Min: 156.9, Max: 157.0, Diff: 0.1] These are the total lifetimes of each worker thread. [GC Worker Other (ms): 0.3 0.3 0.3 0.3Avg: 0.3, Min: 0.3, Max: 0.3, Diff: 0.0] These are the times that each worker thread spent in performing some other tasks that we have not accounted above for the total Parallel Time. [Clear CT: 0.1 ms] This is the time spent in clearing the Card Table. This task is performed in serial mode. [Other: 1.5 ms] Time spent in the some other tasks listed below. The following sub-tasks (which individually may be parallelized) are performed serially. [Choose CSet: 0.0 ms] Time spent in selecting the regions for the Collection Set. [Ref Proc: 0.3 ms] Total time spent in processing Reference objects. [Ref Enq: 0.0 ms] Time spent in enqueuing references to the ReferenceQueues. [Free CSet: 0.3 ms] Time spent in freeing the collection set data structure. [Eden: 12M(12M)->0B(13M) Survivors: 0B->2048K Heap: 14M(64M)->9739K(64M)] This line gives the details on the heap size changes with the Evacuation Pause. This shows that Eden had the occupancy of 12M and its capacity was also 12M before the collection. After the collection, its occupancy got reduced to 0 since everything is evacuated/promoted from Eden during a collection, and its target size grew to 13M. The new Eden capacity of 13M is not reserved at this point. This value is the target size of the Eden. Regions are added to Eden as the demand is made and when the added regions reach to the target size, we start the next collection. Similarly, Survivors had the occupancy of 0 bytes and it grew to 2048K after the collection. The total heap occupancy and capacity was 14M and 64M receptively before the collection and it became 9739K and 64M after the collection. Apart from the evacuation pauses, G1 also performs concurrent-marking to build the live data information of regions. 1.416: [GC pause (young) (initial-mark), 0.62417980 secs] ….... 2.042: [GC concurrent-root-region-scan-start] 2.067: [GC concurrent-root-region-scan-end, 0.0251507] 2.068: [GC concurrent-mark-start] 3.198: [GC concurrent-mark-reset-for-overflow] 4.053: [GC concurrent-mark-end, 1.9849672 sec] 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] [Times: user=0.00 sys=0.00, real=0.00 secs] 4.090: [GC concurrent-cleanup-start] 4.091: [GC concurrent-cleanup-end, 0.0002721] The first phase of a marking cycle is Initial Marking where all the objects directly reachable from the roots are marked and this phase is piggy-backed on a fully young Evacuation Pause. 2.042: [GC concurrent-root-region-scan-start] This marks the start of a concurrent phase that scans the set of root-regions which are directly reachable from the survivors of the initial marking phase. 2.067: [GC concurrent-root-region-scan-end, 0.0251507] End of the concurrent root region scan phase and it lasted for 0.0251507 seconds. 2.068: [GC concurrent-mark-start] Start of the concurrent marking at 2.068 secs from the start of the process. 3.198: [GC concurrent-mark-reset-for-overflow] This indicates that the global marking stack had became full and there was an overflow of the stack. Concurrent marking detected this overflow and had to reset the data structures to start the marking again. 4.053: [GC concurrent-mark-end, 1.9849672 sec] End of the concurrent marking phase and it lasted for 1.9849672 seconds. 4.055: [GC remark 4.055: [GC ref-proc, 0.0000254 secs], 0.0030184 secs] This corresponds to the remark phase which is a stop-the-world phase. It completes the left over marking work (SATB buffers processing) from the previous phase. In this case, this phase took 0.0030184 secs and out of which 0.0000254 secs were spent on Reference processing. 4.088: [GC cleanup 117M->106M(138M), 0.0015198 secs] Cleanup phase which is again a stop-the-world phase. It goes through the marking information of all the regions, computes the live data information of each region, resets the marking data structures and sorts the regions according to their gc-efficiency. In this example, the total heap size is 138M and after the live data counting it was found that the total live data size dropped down from 117M to 106M. 4.090: [GC concurrent-cleanup-start] This concurrent cleanup phase frees up the regions that were found to be empty (didn't contain any live data) during the previous stop-the-world phase. 4.091: [GC concurrent-cleanup-end, 0.0002721] Concurrent cleanup phase took 0.0002721 secs to free up the empty regions. Option -XX:G1PrintRegionLivenessInfo Now, let's look at the output generated with the flag G1PrintRegionLivenessInfo. This is a diagnostic option and gets enabled with -XX:+UnlockDiagnosticVMOptions. G1PrintRegionLivenessInfo prints the live data information of each region during the Cleanup phase of the concurrent-marking cycle. 26.896: [GC cleanup ### PHASE Post-Marking @ 26.896### HEAP committed: 0x02e00000-0x0fe00000 reserved: 0x02e00000-0x12e00000 region-size: 1048576 Cleanup phase of the concurrent-marking cycle started at 26.896 secs from the start of the process and this live data information is being printed after the marking phase. Committed G1 heap ranges from 0x02e00000 to 0x0fe00000 and the total G1 heap reserved by JVM is from 0x02e00000 to 0x12e00000. Each region in the G1 heap is of size 1048576 bytes. ### type address-range used prev-live next-live gc-eff### (bytes) (bytes) (bytes) (bytes/ms) This is the header of the output that tells us about the type of the region, address-range of the region, used space in the region, live bytes in the region with respect to the previous marking cycle, live bytes in the region with respect to the current marking cycle and the GC efficiency of that region. ### FREE 0x02e00000-0x02f00000 0 0 0 0.0 This is a Free region. ### OLD 0x02f00000-0x03000000 1048576 1038592 1038592 0.0 Old region with address-range from 0x02f00000 to 0x03000000. Total used space in the region is 1048576 bytes, live bytes as per the previous marking cycle are 1038592 and live bytes with respect to the current marking cycle are also 1038592. The GC efficiency has been computed as 0. ### EDEN 0x03400000-0x03500000 20992 20992 20992 0.0 This is an Eden region. ### HUMS 0x0ae00000-0x0af00000 1048576 1048576 1048576 0.0### HUMC 0x0af00000-0x0b000000 1048576 1048576 1048576 0.0### HUMC 0x0b000000-0x0b100000 1048576 1048576 1048576 0.0### HUMC 0x0b100000-0x0b200000 1048576 1048576 1048576 0.0### HUMC 0x0b200000-0x0b300000 1048576 1048576 1048576 0.0### HUMC 0x0b300000-0x0b400000 1048576 1048576 1048576 0.0### HUMC 0x0b400000-0x0b500000 1001480 1001480 1001480 0.0 These are the continuous set of regions called Humongous regions for storing a large object. HUMS (Humongous starts) marks the start of the set of humongous regions and HUMC (Humongous continues) tags the subsequent regions of the humongous regions set. ### SURV 0x09300000-0x09400000 16384 16384 16384 0.0 This is a Survivor region. ### SUMMARY capacity: 208.00 MB used: 150.16 MB / 72.19 % prev-live: 149.78 MB / 72.01 % next-live: 142.82 MB / 68.66 % At the end, a summary is printed listing the capacity, the used space and the change in the liveness after the completion of concurrent marking. In this case, G1 heap capacity is 208MB, total used space is 150.16MB which is 72.19% of the total heap size, live data in the previous marking was 149.78MB which was 72.01% of the total heap size and the live data as per the current marking is 142.82MB which is 68.66% of the total heap size. Option -XX:+G1PrintHeapRegions G1PrintHeapRegions option logs the regions related events when regions are committed, allocated into or are reclaimed. COMMIT/UNCOMMIT events G1HR COMMIT [0x6e900000,0x6ea00000]G1HR COMMIT [0x6ea00000,0x6eb00000] Here, the heap is being initialized or expanded and the region (with bottom: 0x6eb00000 and end: 0x6ec00000) is being freshly committed. COMMIT events are always generated in order i.e. the next COMMIT event will always be for the uncommitted region with the lowest address. G1HR UNCOMMIT [0x72700000,0x72800000]G1HR UNCOMMIT [0x72600000,0x72700000] Opposite to COMMIT. The heap got shrunk at the end of a Full GC and the regions are being uncommitted. Like COMMIT, UNCOMMIT events are also generated in order i.e. the next UNCOMMIT event will always be for the committed region with the highest address. GC Cycle events G1HR #StartGC 7G1HR CSET 0x6e900000G1HR REUSE 0x70500000G1HR ALLOC(Old) 0x6f800000G1HR RETIRE 0x6f800000 0x6f821b20G1HR #EndGC 7 This shows start and end of an Evacuation pause. This event is followed by a GC counter tracking both evacuation pauses and Full GCs. Here, this is the 7th GC since the start of the process. G1HR #StartFullGC 17G1HR UNCOMMIT [0x6ed00000,0x6ee00000]G1HR POST-COMPACTION(Old) 0x6e800000 0x6e854f58G1HR #EndFullGC 17 Shows start and end of a Full GC. This event is also followed by the same GC counter as above. This is the 17th GC since the start of the process. ALLOC events G1HR ALLOC(Eden) 0x6e800000 The region with bottom 0x6e800000 just started being used for allocation. In this case it is an Eden region and allocated into by a mutator thread. G1HR ALLOC(StartsH) 0x6ec00000 0x6ed00000G1HR ALLOC(ContinuesH) 0x6ed00000 0x6e000000 Regions being used for the allocation of Humongous object. The object spans over two regions. G1HR ALLOC(SingleH) 0x6f900000 0x6f9eb010 Single region being used for the allocation of Humongous object. G1HR COMMIT [0x6ee00000,0x6ef00000]G1HR COMMIT [0x6ef00000,0x6f000000]G1HR COMMIT [0x6f000000,0x6f100000]G1HR COMMIT [0x6f100000,0x6f200000]G1HR ALLOC(StartsH) 0x6ee00000 0x6ef00000G1HR ALLOC(ContinuesH) 0x6ef00000 0x6f000000G1HR ALLOC(ContinuesH) 0x6f000000 0x6f100000G1HR ALLOC(ContinuesH) 0x6f100000 0x6f102010 Here, Humongous object allocation request could not be satisfied by the free committed regions that existed in the heap, so the heap needed to be expanded. Thus new regions are committed and then allocated into for the Humongous object. G1HR ALLOC(Old) 0x6f800000 Old region started being used for allocation during GC. G1HR ALLOC(Survivor) 0x6fa00000 Region being used for copying old objects into during a GC. Note that Eden and Humongous ALLOC events are generated outside the GC boundaries and Old and Survivor ALLOC events are generated inside the GC boundaries. Other Events G1HR RETIRE 0x6e800000 0x6e87bd98 Retire and stop using the region having bottom 0x6e800000 and top 0x6e87bd98 for allocation. Note that most regions are full when they are retired and we omit those events to reduce the output volume. A region is retired when another region of the same type is allocated or we reach the start or end of a GC(depending on the region). So for Eden regions: For example: 1. ALLOC(Eden) Foo2. ALLOC(Eden) Bar3. StartGC At point 2, Foo has just been retired and it was full. At point 3, Bar was retired and it was full. If they were not full when they were retired, we will have a RETIRE event: 1. ALLOC(Eden) Foo2. RETIRE Foo top3. ALLOC(Eden) Bar4. StartGC G1HR CSET 0x6e900000 Region (bottom: 0x6e900000) is selected for the Collection Set. The region might have been selected for the collection set earlier (i.e. when it was allocated). However, we generate the CSET events for all regions in the CSet at the start of a GC to make sure there's no confusion about which regions are part of the CSet. G1HR POST-COMPACTION(Old) 0x6e800000 0x6e839858 POST-COMPACTION event is generated for each non-empty region in the heap after a full compaction. A full compaction moves objects around, so we don't know what the resulting shape of the heap is (which regions were written to, which were emptied, etc.). To deal with this, we generate a POST-COMPACTION event for each non-empty region with its type (old/humongous) and the heap boundaries. At this point we should only have Old and Humongous regions, as we have collapsed the young generation, so we should not have eden and survivors. POST-COMPACTION events are generated within the Full GC boundary. G1HR CLEANUP 0x6f400000G1HR CLEANUP 0x6f300000G1HR CLEANUP 0x6f200000 These regions were found empty after remark phase of Concurrent Marking and are reclaimed shortly afterwards. G1HR #StartGC 5G1HR CSET 0x6f400000G1HR CSET 0x6e900000G1HR REUSE 0x6f800000 At the end of a GC we retire the old region we are allocating into. Given that its not full, we will carry on allocating into it during the next GC. This is what REUSE means. In the above case 0x6f800000 should have been the last region with an ALLOC(Old) event during the previous GC and should have been retired before the end of the previous GC. G1HR ALLOC-FORCE(Eden) 0x6f800000 A specialization of ALLOC which indicates that we have reached the max desired number of the particular region type (in this case: Eden), but we decided to allocate one more. Currently it's only used for Eden regions when we extend the young generation because we cannot do a GC as the GC-Locker is active. G1HR EVAC-FAILURE 0x6f800000 During a GC, we have failed to evacuate an object from the given region as the heap is full and there is no space left to copy the object. This event is generated within GC boundaries and exactly once for each region from which we failed to evacuate objects. When Heap Regions are reclaimed ? It is also worth mentioning when the heap regions in the G1 heap are reclaimed. All regions that are in the CSet (the ones that appear in CSET events) are reclaimed at the end of a GC. The exception to that are regions with EVAC-FAILURE events. All regions with CLEANUP events are reclaimed. After a Full GC some regions get reclaimed (the ones from which we moved the objects out). But that is not shown explicitly, instead the non-empty regions that are left in the heap are printed out with the POST-COMPACTION events.

    Read the article

  • Oracle TimesTen In-Memory Database Performance on SPARC T4-2

    - by Brian
    The Oracle TimesTen In-Memory Database is optimized to run on Oracle's SPARC T4 processor platforms running Oracle Solaris 11 providing unsurpassed scalability, performance, upgradability, protection of investment and return on investment. The following demonstrate the value of combining Oracle TimesTen In-Memory Database with SPARC T4 servers and Oracle Solaris 11: On a Mobile Call Processing test, the 2-socket SPARC T4-2 server outperforms: Oracle's SPARC Enterprise M4000 server (4 x 2.66 GHz SPARC64 VII+) by 34%. Oracle's SPARC T3-4 (4 x 1.65 GHz SPARC T3) by 2.7x, or 5.4x per processor. Utilizing the TimesTen Performance Throughput Benchmark (TPTBM), the SPARC T4-2 server protects investments with: 2.1x the overall performance of a 4-socket SPARC Enterprise M4000 server in read-only mode and 1.5x the performance in update-only testing. This is 4.2x more performance per processor than the SPARC64 VII+ 2.66 GHz based system. 10x more performance per processor than the SPARC T2+ 1.4 GHz server. 1.6x better performance per processor than the SPARC T3 1.65 GHz based server. In replication testing, the two socket SPARC T4-2 server is over 3x faster than the performance of a four socket SPARC Enterprise T5440 server in both asynchronous replication environment and the highly available 2-Safe replication. This testing emphasizes parallel replication between systems. Performance Landscape Mobile Call Processing Test Performance System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 218,400 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 162,900 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 80,400 TimesTen Performance Throughput Benchmark (TPTBM) Read-Only System Processor Sockets/Cores/Threads Tps SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 7.9M SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 6.5M M4000 SPARC64 VII+, 2.66 GHz 4 16 32 3.1M T5440 SPARC T2+, 1.4 GHz 4 32 256 3.1M TimesTen Performance Throughput Benchmark (TPTBM) Update-Only System Processor Sockets/Cores/Threads Tps SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 547,800 M4000 SPARC64 VII+, 2.66 GHz 4 16 32 363,800 SPARC T3-4 SPARC T3, 1.65 GHz 4 64 512 240,500 TimesTen Replication Tests System Processor Sockets/Cores/Threads Asynchronous 2-Safe SPARC T4-2 SPARC T4, 2.85 GHz 2 16 128 38,024 13,701 SPARC T5440 SPARC T2+, 1.4 GHz 4 32 256 11,621 4,615 Configuration Summary Hardware Configurations: SPARC T4-2 server 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 4 x 300 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head SPARC T3-4 server 4 x SPARC T3 processors, 1.6 GHz 512 GB memory 1 x 8 Gbs FC Qlogic HBA 8 x 146 GB internal disks 1 x Sun Fire X4275 server configured as COMSTAR head SPARC Enterprise M4000 server 4 x SPARC64 VII+ processors, 2.66 GHz 128 GB memory 1 x 8 Gbs FC Qlogic HBA 1 x 6 Gbs SAS HBA 2 x 146 GB internal disks Sun Storage F5100 Flash Array (40 x 24 GB flash modules) 1 x Sun Fire X4275 server configured as COMSTAR head Software Configuration: Oracle Solaris 11 11/11 Oracle TimesTen 11.2.2.4 Benchmark Descriptions TimesTen Performance Throughput BenchMark (TPTBM) is shipped with TimesTen and measures the total throughput of the system. The workload can test read-only, update-only, delete and insert operations as required. Mobile Call Processing is a customer-based workload for processing calls made by mobile phone subscribers. The workload has a mixture of read-only, update, and insert-only transactions. The peak throughput performance is measured from multiple concurrent processes executing the transactions until a peak performance is reached via saturation of the available resources. Parallel Replication tests using both asynchronous and 2-Safe replication methods. For asynchronous replication, transactions are processed in batches to maximize the throughput capabilities of the replication server and network. In 2-Safe replication, also known as no data-loss or high availability, transactions are replicated between servers immediately emphasizing low latency. For both environments, performance is measured in the number of parallel replication servers and the maximum transactions-per-second for all concurrent processes. See Also SPARC T4-2 Server oracle.com OTN Oracle TimesTen In-Memory Database oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 1 October 2012.

    Read the article

  • Jersey non blocking client

    - by Pavel Bucek
    Although Jersey already have support for making asynchronous requests, it is implemented by standard blocking way - every asynchronous request is handled by one thread and that thread is released only after request is completely processed. That is OK for lots of cases, but imagine how that will work when you need to do lots of parallel requests. Of course you can limit (and its really wise thing to do, you do want control your resources) number of threads used for asynchronous requests, but you'll get another maybe not pleasant consequence - obviously processing time will incerase. There are few projects which are trying to deal with that problem, commonly named as async http clients. I didn't want to "re-implement a wheel" and I decided I'll use AHC - Async Http Client made by Jeanfrancois Arcand. There is also interesting implementation from Apache - HttpAsyncClient, but it is still in "very early stages of development" and others haven't been in similar or better shape as AHC. How this works? Non-blocking clients allow users to make same asynchronous requests as we can do with standard approach but implementation is different - threads are better utilized, they don't spend most of time in idle state. Simply described - when you make a request (send it over the network), you are waiting for reply from other side. And there comes main advantage of non-blocking approach - it uses these threads for further work, like making other requests or processing responses etc.. Idle time is minimized and your resources (threads) will be far better used. Who should consider using this? Everyone who is making lots of asynchronous requests. I haven't done proper benchmark yet, but some simple dumb tests are showing huge improvement in cases where lots of concurrent asynchronous requests are made in short period. Last but not least - this module is still experimental, so if you don't like something or if you have ideas for improvements/any feedback, feel free to comment this blog post, send mail to [email protected] or contact me personally. All feedback is greatly appreciated! maven dependency (will be present in java.net maven 2 repo by the end of the day): link: http://download.java.net/maven/2/com/sun/jersey/experimental/jersey-non-blocking-client <dependency> <groupId>com.sun.jersey.experimental</groupId> <artifactId>jersey-non-blocking-client</artifactId> <version>1.9-SNAPSHOT</version> </dependency> code snippet: ClientConfig cc = new DefaultNonBlockingClientConfig(); cc.getProperties().put(NonBlockingClientConfig.PROPERTY_THREADPOOL_SIZE, 10); // default value, feel free to change Client c = NonBlockingClient.create(cc); AsyncWebResource awr = c.asyncResource("http://oracle.com"); Future<ClientResponse> responseFuture = awr.get(ClientResponse.class); // or awr.get(new TypeListener<ClientResponse>(ClientResponse.class) { @Override public void onComplete(Future<ClientResponse> f) throws InterruptedException { ... } }); javadoc (temporary location, won't be updated): http://anise.cz/~paja/jersey-non-blocking-client/

    Read the article

  • Socket Read In Multi-Threaded Application Returns Zero Bytes or EINTR (104)

    - by user309670
    Hi. Am a c-coder for a while now - neither a newbie nor an expert. Now, I have a certain daemoned application in C on a PPC Linux. I use PHP's socket_connect as a client to connect to this service locally. The server uses epoll for multiplexing connections via a Unix socket. A user submitted string is parsed for certain characters/words using strstr() and if found, spawns 4 joinable threads to different websites simultaneously. I use socket, connect, write and read, to interact with the said webservers via TCP on their port 80 in each thread. All connections and writes seems successful. Reads to the webserver sockets fail however, with either (A) all 3 threads seem to hang, and only one thread returns -1 and errno is set to 104. The responding thread takes like 10 minutes - an eternity long:-(. *I read somewhere that the 104 (is EINTR?), which in the network context suggests that ...'the connection was reset by peer'; or (B) 0 bytes from 3 threads, and only 1 of the 4 threads actually returns some data. Isn't the socket read/write thread-safe? I use thread-safe (and reentrant) libc functions such as strtok_r, gethostbyname_r, etc. *I doubt that the said webhosts are actually resetting the connection, because when I run a single-threaded standalone (everything else equal) all things works perfectly right, but of course in series not parallel. There's a second problem too (oops), I can't write back to the client who connect to my epoll-ed Unix socket. My daemon application will hang and hog CPU 100% for ever. Yet nothing is written to the clients end. Am sure the client (a very typical PHP socket application) hasn't closed the connection whenever this is happening - no error(s) detected either. Any ideas? I cannot figure-out whatever is wrong even with Valgrind, GDB or much logging. Kindly help where you can.

    Read the article

  • ScrollView content async downloading problem

    - by Newbee
    Hi! I have UIScrollView with lots of UIImageView inside. In the loadView method I assign some temporary image for each of subview UIImageView images and starts several threads to async download images from internet. Each thread downloads and assign images as follows: NSData *data = [NSData dataWithContentsOfURL:URL]; UIImage *img = [UIImage imageWithData:data]; img_view.image = img; Here is the problem - I expects picture will changed after each image downloaded by I can see only temporary images until all images will downloads. UIScrollView still interact while images downloads - I can scroll temporary images inside it and see scrollers and nothing blocks run loop, but downloaded images doesn't updates.. What I tried to do: Call sleep() in the download thread -- not helps. Call setNeedsDisplay for each ImageView inside ScrollView and for ScrollView -- not helps. What's wrong ? Thanks. Update. I tried some experiments with number of threads and number of images to download. Now I'm sure -- images redraws only when thread finished. For example - if I load 100 images with one thread -- picture updates one time after all images downloads. If I increase number of threads to 10 -- picture updates 10 times -- 10 images appears per update. One more update. I fixed problem by staring new thread from the downloading threads each time one image downloaded and exit current thread (instead of download several images in one thread in the cycle and exit thread only when all downloaded). Obviously it's not a good solution and there must be right approach.

    Read the article

  • Socket.Recieve Failing When Multithreaded

    - by Qua
    The following piece of code runs fine when parallelized to 4-5 threads, but starts to fail as the number of threads increase somewhere beyond 10 concurrentthreads int totalRecieved = 0; int recieved; StringBuilder contentSB = new StringBuilder(4000); while ((recieved = socket.Receive(buffer, SocketFlags.None)) > 0) { contentSB.Append(Encoding.ASCII.GetString(buffer, 0, recieved)); totalRecieved += recieved; } The Recieve method returns with zero bytes read, and if I continue calling the recieve method then I eventually get a 'An established connection was aborted by the software in your host machine'-exception. So I'm assuming that the host actually sent data and then closed the connection, but for some reason I never recieved it. I'm curious as to why this problem arises when there are a lot of threads. I'm thinking it must have something to do with the fact that each thread doesn't get as much execution time and therefore there are some idle time for the threads which causes this error. Just can't figure out why idle time would cause the socket not to recieve any data.

    Read the article

  • Multi-threaded library calls in ASP.NET page request.

    - by ProfK
    I have an ASP.NET app, very basic, but right now too much code to post if we're lucky and I don't have to. We have a class called ReportGenerator. On a button click, method GenerateReports is called. It makes an async call to InternalGenerateReports using ThreadPool.QueueUserWorkItem and returns, ending the ASP.NET response. It doesn't provide any completion callback or anything. InternalGenerateReports creates and maintains five threads in the threadpool, one report per thread, also using QueueUserWorkItem, by 'creating' five threads, also with and waiting until calls on all of them complete, in a loop. Each thread uses an ASP.NET ReportViewer control to render a report to HTML. That is, for 200 reports, InternalGenerateReports should create 5 threads 40 times. As threads complete, report data is queued, and when all five have completed, report data is flushed to disk. My biggest problems are that after running for just one report, the aspnet process is 'hung', and also that at around 200 reports, the app just hangs. I just simplified this code to run in a single thread, and this works fine. Before we get into details like my code, is there anything obvious in the above scendario that might be wrong?

    Read the article

  • Socket Read In Multi-Threaded Application Returns Zero Bytes or EINTR (-1)

    - by user309670
    Hi. Am a c-coder for a while now - neither a newbie nor an expert. Now, I have a certain daemoned application in C on a PPC Linux. I use PHP's socket_connect as a client to connect to this service locally. The server uses epoll for concurrent connections via a Unix socket. A user submitted string is parsed for certain characters/words using strstr() and if found, spawns 4 joinable threads to different websites simultaneously. I use socket, connect, write and read, to interact with the said webservers via TCP on port 80 in each thread. All connections and writes seems successful. Reads to the webserver sockets fail however, with either (A) all 3 threads seem to hang, and only one thread returns -1 and errno is set to 104. The responding thread takes like 10 minutes - an eternity long:-(. *I read somewhere that the 104 (is EINTR) suggests that ...'the connection was reset by peer', or (B) 0 bytes from 3 threads, and only 1 of the 4 threads actually returns some data. Isn't the socket read/write thread-safe? Otherwise, use thread-safe (and reentrant) libc functions such as strtok_r, gethostbyname_r, etc. *I doubt that the said webhosts are actually resetting the connection, because when I run a single-threaded standalone (everything else equal) all things works perfectly right. There's a second problem too (oops), I can't write back to the client who connect to my epoll-ed Unix socket. My daemon application will hang and hog CPU 100% for ever. Yet nothing is written to the clients end. Am sure the client (a very typical PHP socket application) hasn't closed the connection whenever this is happening - no error(s) detected either. I cannot figure-out whatever is wrong even with Valgrind or GDB

    Read the article

  • Java Concurrency in practice sample question

    - by andy boot
    I am reading "Java Concurrency in practice" and looking at the example code on page 51. This states that if a thread has references to a shared object then other threads may be able to access that object before the constructor has finished executing. I have tried to put this into practice and so I wrote this code thinking that if I ran it enough times a RuntimeException("World is f*cked") would occur. But it isn't doing. Is this a case of the Java spec not guaranting something but my particular implementation of java guaranteeing it for me? (java version: 1.5.0 on Ubuntu) Or have I misread something in the book? Code: (I expect an exception but it is never thrown) public class Threads { private Widgit w; public static void main(String[] s) throws Exception { while(true){ Threads t = new Threads(); t.runThreads(); } } private void runThreads() throws Exception{ new Checker().start(); w = new Widgit((int)(Math.random() * 100) + 1); } private class Checker extends Thread{ private static final int LOOP_TIMES = 1000; public void run() { int count = 0; for(int i = 0; i < LOOP_TIMES; i++){ try { w.checkMe(); count++; } catch(NullPointerException npe){ //ignore } } System.out.println("checked: "+count+" times out of "+LOOP_TIMES); } } private static class Widgit{ private int n; private int n2; Widgit(int n) throws InterruptedException{ this.n = n; Thread.sleep(2); this.n2 = n; } void checkMe(){ if (n != n2) { throw new RuntimeException("World is f*cked"); } } } }

    Read the article

  • Thread-safety of read-only memory access

    - by Edmund
    I've implemented the Barnes-Hut gravity algorithm in C as follows: Build a tree of clustered stars. For each star, traverse the tree and apply the gravitational forces from each applicable node. Update the star velocities and positions. Stage 2 is the most expensive stage, and so is implemented in parallel by dividing the set of stars. E.g. with 1000 stars and 2 threads, I have one thread processing the first 500 stars and the second thread processing the second 500. In practice this works: it speeds the computation by about 30% with two threads on a two-core machine, compared to the non-threaded version. Additionally, it yields the same numerical results as the original non-threaded version. My concern is that the two threads are accessing the same resource (namely, the tree) simultaneously. I have not added any synchronisation to the thread workers, so it's likely they will attempt to read from the same location at some point. Although access to the tree is strictly read-only I am not 100% sure it's safe. It has worked when I've tested it but I know this is no guarantee of correctness! Questions Do I need to make a private copy of the tree for each thread? Even if it is safe, are there performance problems of accessing the same memory from multiple threads?

    Read the article

  • Update multiple progress bar with gtk c++

    - by Yadira Suazo
    I need to output the i progress bars and update them all. But only the last one updates i times. This is the code: static void calculaPi (GtkButton * boton, Datos * dDatos){ const char * threads; GtkWidget * barra, *bot2, *button, *progress, *vbox; threads = gtk_entry_get_text(GTK_ENTRY(dDatos->dthreads )); gint ithreads = 1; ithreads = atoi(threads); barra = gtk_window_new(GTK_WINDOW_TOPLEVEL); gtk_window_set_title((GtkWindow *) barra, "Loteria de Threads"); gtk_window_set_default_size(GTK_WINDOW(barra), 300, ithreads*30); gtk_window_set_position(GTK_WINDOW(barra), GTK_WIN_POS_CENTER); button = gtk_button_new_with_label ("Click me!"); vbox = gtk_vbox_new (FALSE, 5); gtk_box_pack_start (GTK_BOX (vbox), button, FALSE, FALSE, 5); gtk_container_add (GTK_CONTAINER (barra), vbox); for (gint i = 1 ; i <= ithreads; i++) { progress = gtk_progress_bar_new (); gtk_box_pack_start (GTK_BOX (vbox), progress, FALSE, FALSE, 5); g_object_set_data (G_OBJECT (barra), "pbar", (gpointer) progress); g_signal_connect (G_OBJECT (button), "clicked", G_CALLBACK (button_clicked), (gpointer) barra); } bot2 = gtk_button_new_with_label("Salir"); gtk_box_pack_start (GTK_BOX (vbox), bot2, FALSE, FALSE, 5); gtk_widget_set_size_request(bot2, 100, 35); g_signal_connect (G_OBJECT (bot2), "clicked", G_CALLBACK (destroy), G_OBJECT (barra)); gtk_widget_show_all(barra); gtk_main(); } static void button_clicked (GtkButton *button, GtkWidget *barra) { GtkProgressBar *progress; gdouble percent = 0.0; gtk_widget_set_sensitive (GTK_WIDGET (button), FALSE); progress = GTK_PROGRESS_BAR (g_object_get_data (G_OBJECT (barra), "pbar")); while (percent <= 100.0) { gchar *message = g_strdup_printf ("%.0f%% Complete", percent); gtk_progress_bar_set_fraction (progress, percent / 100.0); gtk_progress_bar_set_text (progress, message); while (gtk_events_pending ()) gtk_main_iteration (); g_usleep (500000); percent += 5.0; } }

    Read the article

  • Sequential access to asynchronous sockets

    - by Lars A. Brekken
    I have a server that has several clients C1...Cn to each of which there is a TCP connection established. There are less than 10,000 clients. The message protocol is request/response based, where the server sends a request to a client and then the client sends a response. The server has several threads, T1...Tm, and each of these may send requests to any of the clients. I want to make sure that only one of these threads can send a request to a specific client at any one time, while the other threads wanting to send a request to the same client will have to wait. I do not want to block threads from sending requests to different clients at the same time. E.g. If T1 is sending a request to C3, another thread T2 should not be able to send anything to C3 until T1 has received its response. I was thinking of using a simple lock statement on the socket: lock (c3Socket) { // Send request to C3 // Get response from C3 } I am using asynchronous sockets, so I may have to use Monitor instead: Monitor.Enter(c3Socket); // Before calling .BeginReceive() And Monitor.Exit(c3Socket); // In .EndReceive I am worried about stuff going wrong and not letting go of the monitor and therefore blocking all access to a client. I'm thinking that my heartbeat thread could use Monitor.TryEnter() with a timeout and throw out sockets that it cannot get the monitor for. Would it make sense for me to make the Begin and End calls synchronous in order to be able to use the lock() statement? I know that I would be sacrificing concurrency for simplicity in this case, but it may be worth it. Am I overlooking anything here? Any input appreciated.

    Read the article

  • tiemout for a function that waits indefiinitely (like listen())

    - by Fantastic Fourier
    Hello, I'm not quite sure if it's possible to do what I'm about to ask so I thought I'd ask. I have a multi-threaded program where threads share a memory block to communicate necessary information. One of the information is termination of threads where threads constantly check for this value and when the value is changed, they know it's time for pthread_exit(). One of the threads contains listen() function and it seems to wait indefinitely. This can be problematic if there are nobody who wants to make connection and the thread needs to exit but it can't check the value whether thread needs to terminate or not since it's stuck on listen() and can't move beyond. while(1) { listen(); ... if(value == 1) pthread_exit(NULL); } My logic is something like that if it helps illustrate my point better. What I thought would solve the problem is to allow listen() to wait for a duration of time and if nothing happens, it moves on to next statement. Unfortunately, none of two args of listen() involves time limit. I'm not even sure if I'm going about the right way with multi-threaded programming, I'm not much experienced at all. So is this a good approach? Perhaps there is a better way to go about it? Thanks for any insightful comments.

    Read the article

  • Debugging instance of another thread altering my data

    - by Mick
    I have a huge global array of structures. Some regions of the array are tied to individual threads and those threads can modify their regions of the array without having to use critical sections. But there is one special region of the array which all threads may have access to. The code that accesses these parts of the array needs to carefully use critical sections (each array element has its own critical section) to prevent any possibility of two threads writing to the structure simultaneously. Now I have a mysterious bug I am trying to chase, it is occurring unpredictably and very infrequently. It seems that one of the structures is being filled with some incorrect number. One obvious explanation is that another thread has accidentally been allowed to set this number when it should be excluded from doing so. Unfortunately it seems close to impossible to track this bug. The array element in which the bad data appears is different each time. What I would love to be able to do is set some kind of trap for the bug as follows: I would enter a critical section for array element N, then I know that no other thread should be able to touch the data, then (until I exit the critical section) set some kind of flag to a debugging tool saying "if any other thread attempts to change the data here please break and show me the offending patch of source code"... but I suspect no such tool exists... or does it? Or is there some completely different debugging methodology that I should be employing.

    Read the article

  • Thread mutex behaviour

    - by Alberteddu
    Hi there, I'm learning C. I'm writing an application with multiple threads; I know that when a variable is shared between two or more threads, it is better to lock/unlock using a mutex to avoid deadlock and inconsistency of variables. This is very clear when I want to change or view one variable. int i = 0; /** Global */ static pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER; /** Thread 1. */ pthread_mutex_lock(&mutex); i++; pthread_mutex_unlock(&mutex); /** Thread 2. */ pthread_mutex_lock(&mutex); i++; pthread_mutex_unlock(&mutex); This is correct, I think. The variable i, at the end of the executions, contains the integer 2. Anyway, there are some situations in which I don't know exactly where to put the two function calls. For example, suppose you have a function obtain(), which returns a global variable. I need to call that function from within the two threads. I have also two other threads that call the function set(), defined with a few arguments; this function will set the same global variable. The two functions are necessary when you need to do something before getting/setting the var. /** (0) */ /** Thread 1, or 2, or 3... */ if(obtain() == something) { if(obtain() == somethingElse) { // Do this, sometimes obtain() and sometimes set(random number) (1) } else { // Do that, just obtain(). (2) } } else { // Do this and do that (3) // If # of thread * 3 > 10, then set(3*10) For example. (4) } /** (5) */ Where I have to lock, and where I have to unlock? The situation can be, I think, even more complex. I will appreciate an exhaustive answer. Thank you in advance. —Alberto

    Read the article

  • How do I configure encodings (UTF-8) for code executed by Quartz scheduled Jobs in Spring framework

    - by Martin
    I wonder how to configure Quartz scheduled job threads to reflect proper encoding. Code which otherwise executes fine within Springframework injection loaded webapps (java) will get encoding issues when run in threads scheduled by quartz. Is there anyone who can help me out? All source is compiled using maven2 with source and file encodings configured as UTF-8. In the quartz threads any string will have encoding errors if outside ISO 8859-1 characters: Example config <bean name="jobDetail" class="org.springframework.scheduling.quartz.JobDetailBean"> <property name="jobClass" value="example.ExampleJob" /> </bean> <bean id="jobTrigger" class="org.springframework.scheduling.quartz.SimpleTriggerBean"> <property name="jobDetail" ref="jobDetail" /> <property name="startDelay" value="1000" /> <property name="repeatCount" value="0" /> <property name="repeatInterval" value="1" /> </bean> <bean class="org.springframework.scheduling.quartz.SchedulerFactoryBean"> <property name="triggers"> <list> <ref bean="jobTrigger"/> </list> </property> </bean> Example implementation public class ExampleJob extends QuartzJobBean { private Log log = LogFactory.getLog(ExampleJob.class); protected void executeInternal(JobExecutionContext ctx) throws JobExecutionException { log.info("ÅÄÖ"); log.info(Charset.defaultCharset()); } } Example output 2010-05-20 17:04:38,285 1342 INFO [QuartzScheduler_Worker-9] ExampleJob - vÖvÑvñ 2010-05-20 17:04:38,286 1343 INFO [QuartzScheduler_Worker-9] ExampleJob - UTF-8 The same lines of code executed within spring injected beans referenced by servlets in the web-container will output proper encoding. What is it that make Quartz threads encoding dependent?

    Read the article

< Previous Page | 36 37 38 39 40 41 42 43 44 45 46 47  | Next Page >