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  • How do you detach an array of strings from shared memory? C

    - by Tim
    I have: int array_id; char* records[10]; // get the shared segment if ((array_id = shmget(IPC_PRIVATE, 1, 0666)) == -1) { perror("Array Creating"); } // attach records[0] = (char*) shmat(array_id, (void*)0, 0); if ((int) *records == -1) { perror("Array Attachment"); } which works fine, but when i try and detach i get an "invalid argument" error. // detach int error; if( (error = shmdt((void*) records[0])) == -1) { perror(array detachment); } any ideas? thank you

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  • Running out of memory when getting a bitmap from a server?

    - by ikky
    Hi! I'm making an application which uses MANY images. The application gets the images from a server, and downloads them one at a time. After many images the creation of a bitmap returns an exception, but i don't know how to solve this. Here is my function for downloading the images: public static Bitmap getImageFromWholeURL(String sURL) { HttpWebRequest myRequest = (HttpWebRequest)WebRequest.Create(sURL); myRequest.Method = "GET"; // If it does not exist anything on the url, then return null try { HttpWebResponse myResponse = (HttpWebResponse)myRequest.GetResponse(); System.Drawing.Bitmap bmp = new System.Drawing.Bitmap(myResponse.GetResponseStream()); myResponse.Close(); return bmp; } catch (Exception e) { return null; } } Can anyone help me out here? Thanks in advance!

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  • pointer to preallocated memory as an input parameter and have the function fill it

    - by djones2010
    test code: void modify_it(char * mystuff) { char test[7] = "123456"; //last element is null i presume for c style strings here. //static char test[] = "123123"; //when i do this i thought i should be able to gain access to this bit of memory when the function is destroyed but that does not seem to be the case. //char * test = new char[7]; //this is also creating memory on stack and not the heap i reckon and gets destroyed once the function is done with. strcpy_s(mystuff,7,test); //this does the job as long as memory for mystuff has been allocated outside the function. mystuff = test; //this does not work. I know with c style strings you can't just do string assignments they have to be actually copied. in this case I was using this in conjunction with static char test thinking by having it as static the memory would not get destroyed and i can then simply point mystuff to test and be done with it. i would later have address the memory cleanup in the main function. but anyway this never worked. } int main(void) { char * mystuff = new char [7]; //allocate memory on heap where the pointer will point cool(mystuff); std::string test_case(mystuff); std::cout<<test_case.c_str(); //this is the only way i know how to use cout by making it into a string c++ string. delete [] mystuff; return 0; } in the case, of a static array in the function why would it not work. in the case, when i allocated memory using new in the function does it get created on the stack or heap? in the case, i have string which needs to be copied into a char * form. everything i see usually requires const char* instead of just char*. I know i could use reference to take care of this easy. Or char ** to send in the pointer and do it that way. But i just wanted to know if I could do it with just char *. Anyway your thoughts and comments plus any examples would be very helpful.

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  • What's in-memory database technology that do realtime materialized view?

    - by KA100
    What I'm looking for is something like materialized views in front-end that shows my data in diffident ways without full recalculation. let's say I have stock watcher with many front-end views and dashborads some based on aggregation, order by or just filter with different criteria defined realtime by user. Now, I receive online record updates from some webservice and it's not like "data warehouse" every single record can be updated any time and it actually happens every second. Is there any technology can help me in such I create something like materialized view and it's update it without doing full recalculation every time data changed. Thank you.

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  • Iterating over a large data set in long running Python process - memory issues?

    - by user1094786
    I am working on a long running Python program (a part of it is a Flask API, and the other realtime data fetcher). Both my long running processes iterate, quite often (the API one might even do so hundreds of times a second) over large data sets (second by second observations of certain economic series, for example 1-5MB worth of data or even more). They also interpolate, compare and do calculations between series etc. What techniques, for the sake of keeping my processes alive, can I practice when iterating / passing as parameters / processing these large data sets? For instance, should I use the gc module and collect manually? Any advice would be appreciated. Thanks!

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  • Oracle Database In-Memory Launch Featuring Larry Ellison – June 10

    - by Roxana Babiciu
    For more than three-and-a-half decades, Oracle has defined database innovation. With our market-leading technologies, customers have been able to out-think and out-perform their competition. Soon they will be able to do that even faster. At a live launch event and simultaneous webcast, Larry Ellison will reveal the future of the database. Promote this strategic event to customers. Registration for the live event begins at 9am PT.

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  • Oracle Database In-Memory Launch Featuring Larry Ellison – June 10

    - by Cinzia Mascanzoni
    For more than three-and-a-half decades, Oracle has defined database innovation. With our market-leading technologies, customers have been able to out-think and out-perform their competition. Soon they will be able to do that even faster. At a live launch event and simultaneous webcast, Larry Ellison will reveal the future of the database. Promote this strategic event to partners and customers. Registration for the live event begins at 5pm GMT, 6pm CET.

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  • rTorrent, too low memory usage !?

    - by Claudiu
    I want to know from more experienced rTorrent users how to tweak the .rtorrent.rc so that rTorrent will cache disk reading and writing (same as uTorrent does). I have set the max_memory_usage = 1GB but this amount is not used. I run 6 rTorrent instances on a Quad Core, 8 GB Ram machine and total used memory reported by htop is only ~500MB. I need to use memory buffers cause disk IO activity is very high.

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  • Amazon EC2 High-Memory Extra Large Instance

    - by Simpanoz
    I am new to Mongodb and EC2. If I use following single MongoDb server : High-Memory Extra Large Instance 17.1 GiB memory, 6.5 ECU (2 virtual cores with 3.25 EC2 Compute Units each), 420 GB of local instance storage, 64-bit platform As a layman, if we quantify I/O, data in MB/sec. How much I/O transactions mongodb server can handle easily, without being burnt out. Consider default settings of EC2 server with Ubuntu and MongoDb version available in AWS marketplace. Thanks in advance

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  • Apache strace to hunt down a memory leak

    - by Zipp
    We have a server with a memory issue: the server keeps allocating itself memory and doesn't release it. We're running Apache. I set MaxReqsPerClient to a really low value just so the threads don't hold a lot of memory, but has anyone seen calls like this? Am I wrong in thinking that it's probably Drupal pulling too much data back from the cache in DB? read(52, "h_index\";a:2:{s:6:\"weight\";i:1;s"..., 6171) = 1368 read(52, "\";a:2:{s:6:\"author\";a:3:{s:5:\"la"..., 4803) = 1368 read(52, ":\"description\";s:19:\"Term name t"..., 3435) = 1368 read(52, "abel\";s:4:\"Name\";s:11:\"descripti"..., 2067) = 1368 read(52, "ions\";a:2:{s:4:\"form\";a:3:{s:4:\""..., 16384) = 708 brk(0x2ab554396000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55f653000 brk(0x2ab554356000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55f753000 brk(0x2ab554356000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55f853000 brk(0x2ab554356000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55f953000 brk(0x2ab554356000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55fa53000 brk(0x2ab554356000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55fb53000 brk(0x2ab554356000) = 0x2ab5542f5000 mmap(NULL, 1048576, PROT_READ|PROT_WRITE, MAP_PRIVATE|MAP_ANONYMOUS, -1, 0) = 0x2ab55fc53000 poll([{fd=52, events=POLLIN|POLLPRI}], 1, 0) = 0 (Timeout) write(52, "d\0\0\0\3SELECT cid, data, created, "..., 104) = 104 read(52, "\1\0\0\1\5E\0\0\2\3def\23drupal_database_nam"..., 16384) = 1368 read(52, ";s:11:\"granularity\";a:5:{s:4:\"ye"..., 34783) = 1368 read(52, ":4:\"date\";}s:9:\"datestamp\";a:9:{"..., 33415) = 1368 read(52, "\";i:0;s:15:\"display_default\";i:0"..., 32047) = 1368 read(52, "e as an integer value.\";s:8:\"set"..., 30679) = 1368 read(52, "label' pairs, i.e. 'Fraction': 0"..., 29311) = 1368 top (the procs just keep growing in memory..): 12845 apache 15 0 581m 246m 37m S 0.0 4.1 0:17.39 httpd 12846 apache 15 0 571m 235m 37m S 0.0 4.0 0:12.13 httpd 12833 apache 15 0 420m 117m 37m S 0.0 2.0 0:06.04 httpd 12851 apache 15 0 412m 113m 37m S 0.0 1.9 0:05.32 httpd 13871 apache 15 0 409m 109m 37m S 0.0 1.8 0:04.90 httpd 12844 apache 15 0 407m 108m 37m S 0.0 1.8 0:04.50 httpd 13870 apache 15 0 407m 108m 37m S 0.3 1.8 0:03.50 httpd 14903 apache 15 0 402m 103m 37m S 0.3 1.7 0:01.29 httpd 14850 apache 15 0 397m 100m 37m S 0.0 1.7 0:02.08 httpd 14907 apache 15 0 390m 93m 36m S 0.0 1.6 0:01.32 httpd 13872 apache 15 0 386m 91m 37m S 0.0 1.5 0:03.13 httpd 12843 apache 15 0 373m 81m 37m S 0.0 1.4 0:02.51 httpd 14901 apache 15 0 370m 75m 33m S 0.0 1.3 0:00.78 httpd 14904 apache 15 0 335m 29m 15m S 0.0 0.5 0:00.26 httpd

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  • crunchbang: it takes up *how* much memory?!?!

    - by Theo Moore
    I've been trying many distros of Linux lately, trying to find something I like for my netbook. I started out with Ubuntu, and I can tell you I am a big fan. Ubuntu is now fast to install, much simpler to administer, and pretty light resource-wise. My original install was the standard 32 bit version of 9.04. I tried the netbook remix version of this release, but it was very, very slow. Even the full-blown version used only about 200mb. Much better than the almost 800 that the recommended Windows y version took. Once the newest release of Ubuntu was released, I decided to try the netbook remx of 10.04. It used even less RAM; only about 150mb. I thought I'd found my OS. I certainly settled in and prepared to use it forever. Then, someone I know suggested I try cunchbang. It is the most minimalistic UI I've ever seen, using Openbox rather than Gnome or KDE. Very slick, simple and clean. Since I am using the alpha of the most recent version (using Debian Squeeze), the apps provided for you are few...although more will be provided soon. You do have a word processor, etc., although not the OpenOffice you would normally get in Ubuntu. But the best part? 48MB. That's it. 48mb fully loaded, supporting what I can "hotel services". It's fast, boots quick, and believe it or not, I can even do Java-based development....on my netbook! Pretty slick.   More on it as I use it.

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  • PHP-FPM Pool, Child Processes and Memory Consumption

    - by Jhilke Dai
    In my PHP-FPM configuration I have 3 Pools, the eg: Config is: ;;;;;;;;;;;;;;;;;;;;;;; ; Pool 1 ; ;;;;;;;;;;;;;;;;;;;;;;; [www1] user = www group = www listen = /tmp/php-fpm1.sock; listen.backlog = -1 listen.owner = www listen.group = www listen.mode = 0666 pm = dynamic pm.max_children = 40 pm.start_servers = 6 pm.min_spare_servers = 6 pm.max_spare_servers = 12 pm.max_requests = 250 slowlog = /var/log/php/$pool.log.slow request_slowlog_timeout = 5s request_terminate_timeout = 120s rlimit_files = 131072 ;;;;;;;;;;;;;;;;;;;;;;; ; Pool 2 ; ;;;;;;;;;;;;;;;;;;;;;;; [www2] user = www group = www listen = /tmp/php-fpm2.sock; listen.backlog = -1 listen.owner = www listen.group = www listen.mode = 0666 pm = dynamic pm.max_children = 40 pm.start_servers = 6 pm.min_spare_servers = 6 pm.max_spare_servers = 12 pm.max_requests = 250 slowlog = /var/log/php/$pool.log.slow request_slowlog_timeout = 5s request_terminate_timeout = 120s rlimit_files = 131072 ;;;;;;;;;;;;;;;;;;;;;;; ; Pool 3 ; ;;;;;;;;;;;;;;;;;;;;;;; [www3] user = www group = www listen = /tmp/php-fpm3.sock; listen.backlog = -1 listen.owner = www listen.group = www listen.mode = 0666 pm = dynamic pm.max_children = 40 pm.start_servers = 6 pm.min_spare_servers = 6 pm.max_spare_servers = 12 pm.max_requests = 250 slowlog = /var/log/php/$pool.log.slow request_slowlog_timeout = 5s request_terminate_timeout = 120s rlimit_files = 131072 I calculated the pm.max_children processes according to some example calculations on the web like 40 x 40 Mb = 1600 Mb. I have separated 4 GB of RAM for PHP, now according to the calculations 40 Child Processes via one socket, and I have total of 3 sockets in my Nginx and FPM configuration. My doubt is about the amount of memory consumption by those child processes. I tried to create high load in the server via httperf hog and siege but I could not calculate the accurate memory usage by all the PHP processes (other processes like MySQL and Nginx were also running). And all the sockets were in use, So, I seek guidance from anyone who have done this before or know how exactly the pm.max_children in PHP Works. Since I have 3 Pools/sockets with 40 child processes does that count to 3 x 40 x 40 Mb of Memory usage ? or it is just like 40 Max. Child processes sharing 3 sockets (and the total memory usage is just 40 x 40 Mb) ?

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  • Out of memory error when enabling openX Market plugin

    - by Jeremy Pippin
    We're trying to enable the openX Market plugin on openX 2.8.9. Enabling the plugin results in an "Allowed memory exceeded" error: Fatal error: Allowed memory size of 201326592 bytes exhausted (tried to allocate 76 bytes) in /home/openx/lib/pear/PEAR.php on line 868 no matter what we have our php memory_limit set to. It even exceeded 512MB. We're running RHEL 5.6 and PEAR 1.9.4 Has anybody else come across this problem?

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  • How to memory test in Linux?

    - by sasayins
    Hi, I'm planning to test my Linux box and I want to start in memory testing. But my problem is what should I need to test the memory in my linux box? Should I need a tool? Or there are some APIs to use to build some scripts? Thanks

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  • XNA Shader Texture Memory

    - by Alex
    I was wondering about texture optimization in XNA 4.0. Will the the contentmanager send the texturedata to the GPU directly when the texture gets loaded or do I send the texture data to the GPU when I declare a texture in my shader. If that's the case, what happens if I have 5 shaders all using the same texture, does that mean that I send 5 instances of that texture data to the gpu or am I simply telling the GPU what preloaded texture to use? Or does XNA do the heavy lifting in the background?

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  • Why Hekaton In-Memory OLTP Truly is Revolutionary

    - by merrillaldrich
    I just returned from the PASS Summit in Charlotte, NC – which was excellent, among the best I have attended – and I have had Dr. David DeWitt’s talk rolling around in my head since he gave it on Thursday. (Dr. DeWitt starts at 27:00 at that link.) I probably cannot do it justice, but I wanted to recap why Hekaton really is revolutionary, and not just a marketing buzzword. I am normally skeptical of product announcements, and I find too often that real technical innovation can be overwhelmed by the...(read more)

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  • Learning about BIOS memory, instructions and code origins

    - by m3taspl0it
    I'm learning about the BIOS and have a few questions. What is meant by, "This is the last 16 bytes of memory at the end of the first megabyte of memory"? The first instruction of BIOS is jump, which jumps to the main BIOS program, but where does it jump? Where does the original BIOS code originate? I'm also interested in POST? How are POST signals executed by the processor?

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  • Memory allocation strategy for the vertex buffers (DirectX 10/11)

    - by Alex
    I have the following question. I write CAD system. So I have a 3D scene and there are many different objects (walls, doors, windows and so on). User can add or delete some objects. The question is: how can I organise the keeping of vertices for all my objects. I can create vertex buffer for every object. But I think drawing/switching from one buffer to another would have performance penalty. Another way - I can create several big buffers for every object type. But I don't understand how to update such buffers. It is too big to update whole buffer (for example buffer for all walls). What I need to do if I want to delete the object from the middle of the buffer? Actually I have the similar question: http://stackoverflow.com/questions/5515700/how-to-properly-update-vertex-buffers-in-directx-10 Most examples I've found work with very static models. Therefore, they tend to create a single vertex buffer with their list of points, and then are just manipulated by matrix transformations. I, on the other hand, will be updating the scene very often.

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  • How to tune system settings for mongoDB on Linux?

    - by jsh
    Trying to squeeze a lot out of one question here -- please bear with me. Although the MongoDB man pages make several useful recommendations about system settings like ulimit (http://docs.mongodb.org/manual/reference/ulimit/), and other production factors (http://docs.mongodb.org/manual/administration/production-notes/) they seem mysteriously silent on things like virtual memory and swap settings. The closest we get to a hint is that "...the operating system’s virtual memory subsystem manages MongoDB’s memory..." (http://docs.mongodb.org/manual/faq/fundamentals/#does-mongodb-require-a-lot-of-ram). Running the same job - high writes and high reads on about 10,000,000 records in a single collection -- on my 4-processor, 4GB RAM macbook and an 8-core ubuntu box with 64GB RAM I saw dramatically WORSE read performance on the linux box with factory settings, and could hear the disk constantly spinning, indicating high I/O and presumably swapping. Yes, other things were happening on the box, but there was plenty of free RAM, disk space, etc.; furthermore, I did not see evidence that Mongo was expanding to take advantage of all that free RAM as it is touted to do. Linux box default settings were as follows: vm.swappiness =60 vm.dirty_background_ratio = 10 vm.dirty_ratio = 20 vm.dirty_expire_centisecs =3000 vm.dirty_writeback_centisecs=500 I hazarded some guesses looking at docs and blogs for other types of databases (Oracle, MYSQL, etc.), experimented, and adjusted as below. vm.swappiness=10 vm.dirty_background_ratio=5 vm.dirty_ratio=5 vm.dirty_writeback_centisecs=250 vm.dirty_expire_centisecs=500 I saw some immediate apparent improvements in read time. However, when I ran my test jobs again, read performance continued to be painfully sluggish during heavy writes. Then, I REBUILT the collection from an available data source - and suddenly I can read at 1ms or less per record WHILE doing the write job! So the question is really two-fold: 1) What are appropriate VM settings for MongoDB on Linux? 2) (bonus) Does Mongo do some checking or optimization with the OS while data is being built? In other words, if I have built a large data set with suboptimal VM or I/O settings, does Mongo make assumptions during the memory-mapping process that will fail to take advantage of optimizations down the road? Obviously I don't fully grok memory mapping under the hood (I was hoping I wouldn't have to). Any help appreciated...thanks! -j

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  • Fail2ban memory usage

    - by ltsstar
    Since my server is under a sustain DNS amplification attack (DDOS), I configured fail2ban and initially my outgoing traffic dropped markedly. Anyway, after a few hours (mostly +10), fail2ban uses about 75% ram and seems to be crashed in some way, because the outgoing traffic raises imediatly after. When I searched the web for the memory problem, I found some people complaining about high fail2ban memory usages as well. But the recommended solution, to insert an ulimit command into a fail2ban config file, did not change that much for me.

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