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  • How to use most of memory available on MySQL

    - by Zilvinas
    I've got a MySQL server which has both InnoDB and MyISAM tables. InnoDB tablespace is quite small under 4 GB. MyISAM is big ~250 GB in total of which 50 GB is for indexes. Our server has 32 GB of RAM but it usually uses only ~8GB. Our key_buffer_size is only 2GB. But our key cache hit ratio is ~95%. I find it hard to believe.. Here's our key statistics: | Key_blocks_not_flushed | 1868 | | Key_blocks_unused | 109806 | | Key_blocks_used | 1714736 | | Key_read_requests | 19224818713 | | Key_reads | 60742294 | | Key_write_requests | 1607946768 | | Key_writes | 64788819 | key_cache_block_size is default at 1024. We have 52 GB's of index data and 2GB key cache is enough to get a 95% hit ratio. Is that possible? On the other side data set is 200GB and since MyISAM uses OS (Centos) caching I would expect it to use a lot more memory to cache accessed myisam data. But at this stage I see that key_buffer is completely used, our buffer pool size for innodb is 4gb and is also completely used that adds up to 6GB. Which means data is cached using just 1 GB? My question is how could I check where all the free memory could be used? How could I check if MyISAM hits OS cache for data reads instead of disk?

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  • where is memory gone (no, not buffers or cache)

    - by Marki
    can anyone tell me where the memory is gone: (no, this time neither buffers nor cache) # free total used free shared buffers cached Mem: 3928200 3868560 59640 0 2888 92924 -/+ buffers/cache: 3772748 155452 Swap: 4192956 226352 3966604 top, sorted by memory, descending: top - 13:42:06 up 1 day, 3:47, 2 users, load average: 0.08, 0.12, 0.36 Tasks: 228 total, 1 running, 227 sleeping, 0 stopped, 0 zombie Cpu0 : 2.0%us, 4.0%sy, 0.0%ni, 90.1%id, 0.0%wa, 0.0%hi, 4.0%si, 0.0%st Cpu1 : 0.0%us, 0.0%sy, 0.0%ni, 0.0%id,100.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 3928200k total, 3868020k used, 60180k free, 2896k buffers Swap: 4192956k total, 226048k used, 3966908k free, 82068k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 3863 root 20 0 902m 199m 3296 S 7 5.2 99:08.77 ndsd 21906 root 20 0 138m 9076 2988 S 0 0.2 0:00.02 sfcbd 2332 root 20 0 126m 4660 1332 S 0 0.1 0:17.72 mono 4243 wwwrun 20 0 683m 4468 668 S 0 0.1 0:07.38 java 2994 root 20 0 202m 2288 1660 S 0 0.1 6:10.02 httpstkd 4338 root 20 0 184m 2240 1112 S 0 0.1 0:00.52 namcd 21898 root 20 0 32368 1832 1256 R 1 0.0 0:00.08 top In fact, some time ago oom kicked in and crashed the system (kernel panic), and I'm afraid we're again not far from that point.... UPDATE # cat /proc/meminfo MemTotal: 3928200 kB MemFree: 51336 kB Buffers: 2964 kB Cached: 72876 kB SwapCached: 29128 kB Active: 233440 kB Inactive: 88040 kB Active(anon): 188920 kB Inactive(anon): 56752 kB Active(file): 44520 kB Inactive(file): 31288 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4192956 kB SwapFree: 3966824 kB Dirty: 32 kB Writeback: 0 kB AnonPages: 225112 kB Mapped: 11356 kB Shmem: 32 kB Slab: 1624080 kB SReclaimable: 13740 kB SUnreclaim: 1610340 kB KernelStack: 4176 kB PageTables: 10500 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 6157056 kB Committed_AS: 2397684 kB VmallocTotal: 34359738367 kB VmallocUsed: 441372 kB VmallocChunk: 34359246755 kB HardwareCorrupted: 0 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 10240 kB DirectMap2M: 4184064 kB slabtop Active / Total Objects (% used) : 9041019 / 9207548 (98.2%) Active / Total Slabs (% used) : 401132 / 401156 (100.0%) Active / Total Caches (% used) : 91 / 159 (57.2%) Active / Total Size (% used) : 1491537.88K / 1519791.56K (98.1%) Minimum / Average / Maximum Object : 0.02K / 0.17K / 4096.00K OBJS ACTIVE USE OBJ SIZE SLABS OBJ/SLAB CACHE SIZE NAME 4240470 4240319 99% 0.12K 141349 30 565396K pid 2245140 2219675 98% 0.25K 149676 15 598704K size-256 2238090 2210087 98% 0.12K 74603 30 298412K size-128 ...

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  • Apache httpd processes and PHP out of memory

    - by Ofri
    I have a VPS running apache-php-mysql on centos and a single drupal website installed. The VPS has 256MB of RAM (could be the root cause of all my problems... maybe I just need more). Whenever I try to open my website from multiple browser tabs (about 8... not 800) all at once, apache crashes! I have this on the log: [Wed Oct 24 11:26:31 2012] [error] [client xxx] PHP Fatal error: Out of memory (allocated 28049408) (tried to allocate 201335 bytes) in xxx on line 2139, referer: xxx I have read many many posts here, but I think there is something fundamental that I'm missing - If I understand correctly some php script tried to allocate 200K after allocating 28MB, and fails to do so. First question is: should this cause the apache to crash??? Next, I tried to look at 'top' command while I do my little test. Indeed I see 7 httpd processes, each reserving about 30MB - which explains why my RAM runs out. How do I prevent apache from creating new processes until it's out of memory? I tried configuring /etc/httpd/conf/httpd.conf like this: <IfModule prefork.c> StartServers 1 MinSpareServers 1 MaxSpareServers 1 ServerLimit 1 MaxClients 1 MaxRequestsPerChild 100 </IfModule> But got the same exact result! What am I missing? Thanks a lot!

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  • Updated my WAMP Server and MySQL is eating up 580mB of memory

    - by Jon
    I updated my dev-box's WAMPSERVER, and along with updating PHP and Apache, MySQL updated to '5.6.12'. After doing that, I copied the data folder from my old (5.1.36) install to the new one and now MySQL takes up 580mB which is way too much, since I'm the only person using it (Locally) and there are only 20 or so databases on it, none of which have 'memory' tables. How can I get this down to a decent amount? My my.ini: # For advice on how to change settings please see # http://dev.mysql.com/doc/refman/5.6/en/server-configuration-defaults.html # *** DO NOT EDIT THIS FILE. It's a template which will be copied to the # *** default location during install, and will be replaced if you # *** upgrade to a newer version of MySQL. [mysqld] # Remove leading # and set to the amount of RAM for the most important data # cache in MySQL. Start at 70% of total RAM for dedicated server, else 10%. # innodb_buffer_pool_size = 128M # Remove leading # to turn on a very important data integrity option: logging # changes to the binary log between backups. # log_bin # These are commonly set, remove the # and set as required. # basedir = ..... # datadir = ..... # port = ..... # server_id = ..... # Remove leading # to set options mainly useful for reporting servers. # The server defaults are faster for transactions and fast SELECTs. # Adjust sizes as needed, experiment to find the optimal values. # join_buffer_size = 128M # sort_buffer_size = 2M # read_rnd_buffer_size = 2M sql_mode=NO_ENGINE_SUBSTITUTION,STRICT_TRANS_TABLES Database info: Storage Engine Data Size Index Size Total Size InnoDB 48.00 KB 0.00 B 48.00 KB MEMORY 0.00 B 0.00 B 0.00 B MyISAM 163.64 MB 122.49 MB 286.13 MB Total 163.69 MB 122.49 MB 286.18 MB

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  • Memory overcommitment on VmWare ESXi 5.0

    - by Tibor
    I would like to understand better the possibilities of VmWare ESXi memory overcommitment. I've read this paper from VmWare, so I am familiar with general concepts, such as hypervisor swapping, memory balooning and page sharing. It seems that a combination of these techniques allows for quite a large degree of overcommitment. However, I am not sure. I am deploying a virtual test lab comprising of 4 identical sets of virtual servers and workstations and a couple of virtual router instances. Overall, I expect to be running around 20 virtual machines with Windows XP, Windows 7 and Ubuntu for workstation hosts as well as CentOS and Windows 2008 Server instances for servers. The problem is, however, that the host machine only has 12GB of RAM and I don't have an option to stuff in some more. I would like to know what is the best option to configure hosts in order to achieve reasonable performance within the constrains. I have these two options: Allocate as little as possible of RAM to each virtual machine. Allocate an extraordinary amount (such as 4 GB per instance) and let the baloon driver do the rest. Something else? Which would work better? Machines will mostly be idle, so I don't have any major performance expectations, but they should run reasonably smoothly nevertheless.

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  • windows 2008 r2 iis worker proccess memory usage increase

    - by nLL
    I have this web site written in c#. around 400-500 users online at any time. it was on windows 2008 32 bit machine before and never ever locked/slowed down due to increased memory consumption up until i upgraded it's server to win 2008 r2 64 bit. Old server had only 4 gig ram and quad core cpu at 2ghz. site was working just fine. since i've upgraded the server i noticed (2 times with in 10 days) it started to eat ram. last night it went up to 4 gb ram. with ram increase response slows down quite a lot. recycling app pool doesn't help. I have to restart it's worker process to recover. i've noticed this usually happens if there are continuous errors. as i didn't change anything in the code am i safe to assume it is not related to memory leak in the code? did anyone came across something like that? same thing happens if i create continuous errors with classic asp. thanks

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  • 4GB Memory Upgrade for Acer Aspire 5102WLMi

    - by Richard Slater
    I have bought a 4GB memory upgrade (2x 2GB PC2-5300 SODIMM) for my Acer Aspire 5102WLMi (Aspire 5100 Series) laptop, I installed the two memory modules correctly however with 4GB installed the laptop refuses to POST. I have tried the following: Tried both 2GB SODIMMs without the other (Worked Fine) Tried the original 512MB SODIMMs (Worked Fine) Tried with original 512MB SODIMM and new 2GB SODIMM (Worked Fine) Tried swapping over the 2GB SODIMs (Didn't Boot) Left the computer for 10 minutes with both 2GB SODIMMs installed (Didn't Boot) Checked latest BIOS installed (No Change) The Crucial website said that the laptop supported 4GB of RAM as do several other sites through found through Google, up until now I was fairly confident this would work. Couple of questions that would be good to have answered: Question: Has anyone got an Acer Aspire 5100 Series running with 4GB RAM? Answer: Yes, I have now got one working with 3.75GB Usable, the rest is occupied utilized by the Graphics Card. Question: Any tips on getting this to work; is there a CMOS reset switch? Answer: Yes there is, if both SODIMMs are removed two very small interlocking PCB tracks are revealed. If these are shorted together with a screwdriver the BIOS will be reset. Thanks.

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  • Allocating More Than 4 GB Of Memory

    - by TPatti
    I am facing an issue with memory allocation. I have: Host OS: Microsoft Windows XP - Professional x64 Edition - Version 2003 - Service Pack 2. Host Physical Memory: 8 GB Guest OS: Red Hat Enterprise Linux WS release 4 (Nahant Update 5). I am not sure if it is 32 or 64 bits. The lsb_release -a command says that argument LSB Version: core-3.0-ia32, so I guess that would be 32 bits... VMware Player Version: 2.5.2 build-156735 I would like that VMware Player could allocate more that 4 GB, but when I go to the setting, it only lists 4 GB. If I choose the "About" option, it actually says that I have 8 GB installed in the host machine. This VMware image created by someone else and provided to me, apparently done with VMware Workstation 5. Why can't I allocate 8 GB? Where is the problem? In the WMware Player Version, Guest OS or Host OS? How can I solve this? I understand that for this version of player there isn't one version for 32 and another for 64 bits.

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  • How to solve QPixmap::fromImage memory leak?

    - by dodoent
    Hello everyone! I have a problem with Qt. Here is a part of code that troubles me: void FullScreenImage::QImageIplImageCvt(IplImage *input) { help=cvCreateImage(cvGetSize(input), input->depth, input->nChannels); cvCvtColor(input, help, CV_BGR2RGB); QImage tmp((uchar *)help->imageData, help->width, help->height, help->widthStep, QImage::Format_RGB888); this->setPixmap(QPixmap::fromImage(tmp).scaled(this->size(), Qt::IgnoreAspectRatio, Qt::SmoothTransformation)); cvReleaseImage(&help); } void FullScreenImage::hideOnScreen() { this->hide(); this->clear(); } void FullScreenImage::showOnScreen(IplImage *slika, int delay) { QImageIplImageCvt(slika); this->showFullScreen(); if(delay>0) QTimer::singleShot(delay*1000, this, SLOT(hideOnScreen())); } So, the method showOnScreen uses private method QImageIplImageCvt to create QImage from IplImage (which is used by the openCV), which is then used to create QPixmap in order to show the image in full screen. FullScreenImage class inherits QLabel. After some delay, the fullscreen picture should be hidden, so I use QTimer to trigger an event after some delay. The event handler is the hideOnScreen method which hides the label and should clear the memory. The problem is the following: Whenever I call QPixmap::fromImage, it allocates the memory for the pixmap data and copies the data from QImage memory buffer to the QPixmap memory buffer. After the label is hidden, the QPixmap data still remains allocated, and even worse, after the new QPixmap::fromImage call the new chunk of memory is allocated for the new picture, and the old data is not freed from memory. This causes a memory leak (cca 10 MB per method call with my testing pictures). How can I solve that leak? I've even tried to create a private QPixmap variable, store pixmap created by the QPixmap::fromImage to it, and then tried to call its destructor in hideOnScreen method, but it didn't help. Is there a non-static way to create QPixmap from QImage? Or even better, is there a way to create QPixmap directly from IplImage* ? Thank you in advance for your answers.

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  • Does a CPU assigns a value atomically to memory?

    - by Poni
    Hi! A quick question I've been wondering about for some time; Does the CPU assign values atomically, or, is it bit by bit (say for example a 32bit integer). If it's bit by bit, could another thread accessing this exact location get a "part" of the to-be-assigned value? Think of this: I have two threads and one shared "unsigned int" variable (call it "g_uiVal"). Both threads loop. On is printing "g_uiVal" with printf("%u\n", g_uiVal). The second just increase this number. Will the printing thread ever print something that is totally not or part of "g_uiVal"'s value? In code: unsigned int g_uiVal; void thread_writer() { g_uiVal++; } void thread_reader() { while(1) printf("%u\n", g_uiVal); }

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  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Why does jquery leak memory so badly?

    - by Thomas Lane
    This is kind of a follow-up to a question I posted last week: http://stackoverflow.com/questions/2429056/simple-jquery-ajax-call-leaks-memory-in-ie I love the jquery syntax and all of its nice features, but I've been having trouble with a page that automatically updates table cells via ajax calls leaking memory. So I created two simple test pages for experimenting. Both pages do an ajax call every .1 seconds. After each successful ajax call, a counter is incremented and the DOM is updated. The script stops after 1000 cycles. One uses jquery for both the ajax call and to update the DOM. The other uses the Yahoo API for the ajax and does a document.getElementById(...).innerHTML to update the DOM. The jquery version leaks memory badly. Running in drip (on XP Home with IE7), it starts at 9MB and finishes at about 48MB, with memory growing linearly the whole time. If I comment out the line that updates the DOM, it still finishes at 32MB, suggesting that even simple DOM updates leak a significant amount of memory. The non-jquery version starts and finishes at about 9MB, regardless of whether it updates the DOM. Does anyone have a good explanation of what is causing jquery to leak so badly? Am I missing something obvious? Is there a circular reference that I'm not aware of? Or does jquery just have some serious memory issues? Here is the source for the leaky (jquery) version: <html> <head> <script type="text/javascript" src="http://www.google.com/jsapi"></script> <script type="text/javascript"> google.load('jquery', '1.4.2'); </script> <script type="text/javascript"> var counter = 0; leakTest(); function leakTest() { $.ajax({ url: '/html/delme.x', type: 'GET', success: incrementCounter }); } function incrementCounter(data) { if (counter<1000) { counter++; $('#counter').text(counter); setTimeout(leakTest,100); } else $('#counter').text('finished.'); } </script> </head> <body> <div>Why is memory usage going up?</div> <div id="counter"></div> </body> </html> And here is the non-leaky version: <html> <head> <script type="text/javascript" src="http://yui.yahooapis.com/2.8.0r4/build/yahoo/yahoo-min.js"></script> <script type="text/javascript" src="http://yui.yahooapis.com/2.8.0r4/build/event/event-min.js"></script> <script type="text/javascript" src="http://yui.yahooapis.com/2.8.0r4/build/connection/connection_core-min.js"></script> <script type="text/javascript"> var counter = 0; leakTest(); function leakTest() { YAHOO.util.Connect.asyncRequest('GET', '/html/delme.x', {success:incrementCounter}); } function incrementCounter(o) { if (counter<1000) { counter++; document.getElementById('counter').innerHTML = counter; setTimeout(leakTest,100); } else document.getElementById('counter').innerHTML = 'finished.' } </script> </head> <body> <div>Memory usage is stable, right?</div> <div id="counter"></div> </body> </html>

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  • Is special memory required for a MacBook Pro ?

    - by user38900
    I have a MacBook Pro (MacBookPro5,2 / 2.8 GHz) with 4 GB of ram (2x2GB). I'm looking to upgrade to 8GB. The memory in it now is DDR3 PC3-8500 1067. Checking out prices for 4 GB sticks of PC3-8500 there is about $100 difference for "apple certified" ram. Will any DDR3 PC3-8500 module work or is there really a difference?

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  • How memory hungry is Jetty?

    - by Sanoj
    I am planning to use Jetty + MySQL on a small VPS with just 256 or 512MB memory, for serving a few websites. I haven't used Jetty before, only PHP on shared hosting. Is 256 or 512MB too limited for a Jetty server? or should I go with nginx + php + php-fpm setup instead? The websites will not have much traffic, they are just small sites.

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  • MySQL: Load database to memory

    - by Adam Matan
    Hi, Is there a way to load an entire MySQL database to the RAM, especially on en EC2 server? The database is quite small (~500 MegaBytes) I have enough memory Speed issues are crucial - the resulted queries are used to serve a dynamic webpage. Thanks, Adam

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  • Increase process memory cap.

    - by Janis Veinbergs
    Doing copy/paste in Visual Studio 2010 RTM on Windows 7, 3GB ram machine, I was unable to copy text because of an error: Task Manager shows that devenv.exe is using a little more than 500MB. However I still have almost 1GB of free RAM available. Is that somekind of memory cap? If so, is there a way to increase it? It may be a bug, but maybe there is a workaround?

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  • check history of cpu/memory usage in ubuntu?

    - by johnlai2004
    Is there a way for me to review cpu or memory usage on my ubuntu linux server? I've noticed my server (lamp set up) being slow at times, but by the time I log in as root and run a PS command, everything may have returned to normal. It would be great to review a log of what resources different parts of the server consumed.

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  • Free memory on linux [closed]

    - by Julia Roberts
    Possible Duplicate: Meaning of the buffers/cache line in the output of free What would be a good setting to free memory on linux? I have 8GB but gets used up so fast. current settings: kernel.sched_min_granularity_ns = 10000000 kernel.sched_wakeup_granularity_ns = 15000000 vm.dirty_ratio = 40 kernel.pid_max = 4096 vm.bdflush = 100 1200 128 512 15 5000 500 1884 2 What settings would I need so linux frees old ram faster?

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  • Celery - minimize memory consuption

    - by Andrew
    We have ~300 celeryd processes running under Ubuntu 10.4 64-bit , in idle every process takes ~19mb RES, ~174mb VIRT, thus - it's around 6GB of RAM in idle for all processes. In active state - process takes up to 100mb of RES and ~300mb VIRT Every process uses minidom(xml files are < 500kb, simple structure) and urllib. Quetions is - how can we decrease RAM consuption - at least for idle workers, probably some celery or python options may help? How to determine which part takes most of memory?

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