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  • C#. Where struct methods code kept in memory?

    - by maxima120
    It is somewhat known where .NET keeps value types in memory (mostly in stack but could be in heap in certain circumstances etc)... My question is - where is the code of the struct? If I have say 16 byte of data fields in the struct and a massive computation method in it - I am presuming that 16 byte will be copied in stack and the method code is stored somewhere else and is shared for all instances of the struct. Are these presumptions correct?

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  • Do null SQLite Data fields take up extra memory?

    - by CSharperWithJava
    I'm using the built in sqlite library on the Android platform. I'm considering adding several general purpose fields that users will be able to use for their own custom applications, but these fields will be blank most of the time. My question is, how much overhead will these blank fields add to my database? Do null fields even take up per record memory in sqlite? If so, how much? I don't quite understand the inner workings of a sqlite database.

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  • Any way to reserve but not commit memory in linux?

    - by Eloff
    Windows has VirtualAlloc, which allows you to reserve a contiguous region of address space, but not actually use any physical memory. Later when you want to use it (or part of it) you call VirtualAlloc again to commit the region of previously reserved pages. This is actually really useful, but I want to eventually port my application to linux - so I don't want to use it if I can't port it later. Does linux have a way to do this?

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  • Is there an in memory database that supports the DATE function?

    - by Chris J
    Hi, I am doing some unit testing for a DAO that works with postgresql. Some of the SQL queries that my DAO uses involve the DATE function. Is there an in-memory database that supports functions similar to the ones that postgresql does? Currently I am looking for support for the DATE function however, I obviously can see myself using other functions in the future.

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  • NSDecimalNumber leaks memory if not used with AutoRelease pool?

    - by bioffe
    NSString* str = [[NSString alloc] initWithString:@"0.05"]; NSDecimalNumber* num = [[NSDecimalNumber alloc] initWithString:str]; NSLog(@" %@", num); [str release]; [num release]; leaks memory *** __NSAutoreleaseNoPool(): Object 0x707990 of class NSCFString autoreleased with no pool in place - just leaking Can someone suggest a workaround ?

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  • Algorithm to rotate an image 90 degrees in place? (No extra memory)

    - by user9876
    In an embedded C app, I have a large image that I'd like to rotate by 90 degrees. Currently I use the well-known simple algorithm to do this. However, this algorithm requires me to make another copy of the image. I'd like to avoid allocating memory for a copy, I'd rather rotate it in-place. Since the image isn't square, this is tricky. Does anyone know of a suitable algorithm?

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  • Can I upload an object in memory to FTP using Python?

    - by fsckin
    Here's what I'm doing now: mysock = urllib.urlopen('http://localhost/image.jpg') fileToSave = mysock.read() oFile = open(r"C:\image.jpg",'wb') oFile.write(fileToSave) oFile.close f=file('image.jpg','rb') ftp.storbinary('STOR '+os.path.basename('image.jpg'),f) os.remove('image.jpg') Writing files to disk and then imediately deleting them seems like extra work on the system that should be avoided. Can I upload an object in memory to FTP using Python?

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  • collectd does not work

    - by bery
    I have installed collectd-5.0.0 on Fedora12 server and would like to run its service for receiving data from clients. I have enabled network plugin and rddtool plugin as commented: collectd.conf in server: BaseDir "/opt/collectd/var/lib/collectd" LoadPlugin "logfile" LoadPlugin network LoadPlugin rrdtool <Plugin network> Listen "192.168.8.37" "25826" </Plugin> collectd.conf in client: LoadPlugin logfile LoadPlugin cpu LoadPlugin network LoadPlugin memory <Plugin network> Server"192.168.8.37" "25826" </Plugin> collectd.log in server: [2011-08-03 02:36:04] Exiting normally. [2011-08-03 02:36:04] rrdtool plugin: Shutting down the queue thread. [2011-08-03 02:36:04] network plugin: Stopping receive thread. [2011-08-03 02:36:04] network plugin: Stopping dispatch thread. [2011-08-03 02:37:11] Initialization complete, entering read-loop. collectd.log in client: [2011-08-02 17:31:44] Initialization complete, entering read-loop. results thst execute netstat on server: netstat -ulpn | grep 25826 udp 0 0 192.168.8.37:25826 0.0.0.0:* 4744/collectd problem: but there is noting in "/opt/collectd/var/lib/collectd/" on ser yes,I move the port number of "25826" as your propose(But I think this is the default port for coolectd).there is no rdd files recived on server. collectd.log in client collectd [2011-08-03 10:01:36] plugin_read_thread: Handling memory'. [2011-08-03 10:01:36] plugin_read_thread: Handlingcpu'. [2011-08-03 10:01:36] plugin_dispatch_values: time = 1312380096.431; interval = 10.000; host = uml; plugin = memory; plugin_instance = ; type = memory; type_instance = used; [2011-08-03 10:01:36] plugin_dispatch_values: time = 1312380096.431; interval = 10.000; host = uml; plugin = cpu; plugin_instance = 0; type = cpu; type_instance = user; [2011-08-03 10:01:36] uc_update: uml/memory/memory-used: ds[0] = 280412160.000000 [2011-08-03 10:01:36] plugin: plugin_write: Writing values via network. [2011-08-03 10:01:36] uc_update: uml/cpu-0/cpu-user: ds[0] = 0.100008 [2011-08-03 10:01:36] plugin: plugin_write: Writing values via network. [2011-08-03 10:01:36] plugin_dispatch_values: time = 1312380096.431; interval = 10.000; host = uml; plugin = memory; plugin_instance = ; type = memory; type_instance = buffered; [2011-08-03 10:01:36] plugin_dispatch_values: time = 1312380096.431; interval = 10.000; host = uml; plugin = cpu; plugin_instance = 0; type = cpu; type_instance = nice; [2011-08-03 10:01:36] uc_update: uml/memory/memory-buffered: ds[0] = 344182784.000000 [2011-08-03 10:01:36] plugin: plugin_write: Writing values via network. [2011-08-03 10:01:36] uc_update: uml/cpu-0/cpu-nice: ds[0] = 0.000000 [2011-08-03 10:01:36] plugin: plugin_write: Writing values via network. [2011-08-03 10:01:36] network plugin: flush_buffer: send_buffer_fill = 1340 [2011-08-03 10:01:36] network plugin: network_send_buffer: buffer_len = 1340 ... [2011-08-03 10:01:36] plugin_read_thread: Next read of the cpu plugin at 1312380106.429064774. collectd.log in server collectd: [2011-08-03 20:18:08] type = network [2011-08-03 20:18:08] type = rrdtool [2011-08-03 20:18:08] network plugin: sockent_open: node = 192.168.8.37; service = 25826; [2011-08-03 20:18:08] fd = 3; calling bind' [2011-08-03 20:18:08] Done parsing/opt/collectd//share/collectd/types.db' [2011-08-03 20:18:08] interval_g = 10; [2011-08-03 20:18:08] timeout_g = 2; [2011-08-03 20:18:08] hostname_g = localhost.localdomain; [2011-08-03 20:18:08] Initialization complete, entering read-loop. It looks like, data is sending but doesn't be recived. Where is the mistake?

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  • High Load mysql on Debian server

    - by Oleg Abrazhaev
    I have Debian server with 32 gb memory. And there is apache2, memcached and nginx on this server. Memory load always on maximum. Only 500m free. Most memory leak do MySql. Apache only 70 clients configured, other services small memory usage. When mysql use all memory it stops. And nothing works, need mysql reboot. Mysql configured use maximum 24 gb memory. I have hight weight InnoDB bases. (400000 rows, 30 gb). And on server multithread daemon, that makes many inserts in this tables, thats why InnoDB. There is my mysql config. [mysqld] # # * Basic Settings # default-time-zone = "+04:00" user = mysql pid-file = /var/run/mysqld/mysqld.pid socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp language = /usr/share/mysql/english skip-external-locking default-time-zone='Europe/Moscow' # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. # # * Fine Tuning # #low_priority_updates = 1 concurrent_insert = ALWAYS wait_timeout = 600 interactive_timeout = 600 #normal key_buffer_size = 2024M #key_buffer_size = 1512M #70% hot cache key_cache_division_limit= 70 #16-32 max_allowed_packet = 32M #1-16M thread_stack = 8M #40-50 thread_cache_size = 50 #orderby groupby sort sort_buffer_size = 64M #same myisam_sort_buffer_size = 400M #temp table creates when group_by tmp_table_size = 3000M #tables in memory max_heap_table_size = 3000M #on disk open_files_limit = 10000 table_cache = 10000 join_buffer_size = 5M # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #myisam_use_mmap = 1 max_connections = 200 thread_concurrency = 8 # # * Query Cache Configuration # #more ignored query_cache_limit = 50M query_cache_size = 210M #on query cache query_cache_type = 1 # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. #log = /var/log/mysql/mysql.log # # Error logging goes to syslog. This is a Debian improvement :) # # Here you can see queries with especially long duration log_slow_queries = /var/log/mysql/mysql-slow.log long_query_time = 1 log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log server-id = 1 log-bin = /var/lib/mysql/mysql-bin #replicate-do-db = gate log-bin-index = /var/lib/mysql/mysql-bin.index log-error = /var/lib/mysql/mysql-bin.err relay-log = /var/lib/mysql/relay-bin relay-log-info-file = /var/lib/mysql/relay-bin.info relay-log-index = /var/lib/mysql/relay-bin.index binlog_do_db = 24avia expire_logs_days = 10 max_binlog_size = 100M read_buffer_size = 4024288 innodb_buffer_pool_size = 5000M innodb_flush_log_at_trx_commit = 2 innodb_thread_concurrency = 8 table_definition_cache = 2000 group_concat_max_len = 16M #binlog_do_db = gate #binlog_ignore_db = include_database_name # # * BerkeleyDB # # Using BerkeleyDB is now discouraged as its support will cease in 5.1.12. #skip-bdb # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # You might want to disable InnoDB to shrink the mysqld process by circa 100MB. #skip-innodb # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 500M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 32M key_buffer_size = 512M # # * NDB Cluster # # See /usr/share/doc/mysql-server-*/README.Debian for more information. # # The following configuration is read by the NDB Data Nodes (ndbd processes) # not from the NDB Management Nodes (ndb_mgmd processes). # # [MYSQL_CLUSTER] # ndb-connectstring=127.0.0.1 # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ Please, help me make it stable. Memory used /etc/mysql # free total used free shared buffers cached Mem: 32930800 32766424 164376 0 139208 23829196 -/+ buffers/cache: 8798020 24132780 Swap: 33553328 44660 33508668 Maybe my problem not in memory, but MySQL stops every day. As you can see, cache memory free 24 gb. Thank to Michael Hampton? for correction. Load overage on server 3.5. Maybe hdd or another problem? Maybe my config not optimal for 30gb InnoDB ?

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  • Boost Netbook Speed with an SD Card & ReadyBoost

    - by Matthew Guay
    Looking for a way to increase the performance of your netbook?  Here’s how you can use a standard SD memory card or a USB flash drive to boost performance with ReadyBoost. Most netbooks ship with 1Gb of Ram, and many older netbooks shipped with even less.  Even if you want to add more ram, often they can only be upgraded to a max of 2GB.  With ReadyBoost in Windows 7, it’s easy to boost your system’s performance with flash memory.  If your netbook has an SD card slot, you can insert a memory card into it and just leave it there to always boost your netbook’s memory; otherwise, you can use a standard USB flash drive the same way. Also, you can use ReadyBoost on any desktop or laptop; ones with limited memory will see the most performance increase from using it. Please Note:  ReadyBoost requires at least 256Mb of free space on your flash drive, and also requires minimum read/write speeds.  Most modern memory cards or flash drives meet these requirements, but be aware that an old card may not work with it. Using ReadyBoost Insert an SD card into your card reader, or connect a USB flash drive to a USB port on your computer.  Windows will automatically see if your flash memory is ReadyBoost capable, and if so, you can directly choose to speed up your computer with ReadyBoost. The ReadyBoost settings dialog will open when you select this.  Choose “Use this device” and choose how much space you want ReadyBoost to use. Click Ok, and Windows will setup ReadyBoost and start using it to speed up your computer.  It will automatically use ReadyBoost whenever the card is connected to the computer. When you view your SD card or flash drive in Explorer, you will notice a ReadyBoost file the size you chose before.  This will be deleted when you eject your card or flash drive. If you need to remove your drive to use elsewhere, simply eject as normal. Windows will inform you that the drive is currently being used.  Make sure you have closed any programs or files you had open from the drive, and then press Continue to stop ReadyBoost and eject your drive. If you remove the drive without ejecting it, the ReadyBoost file may still remain on the drive.  You can delete this to save space on the drive, and the cache will be recreated when you use ReadyBoost next time. Conclusion Although ReadyBoost may not make your netbook feel like a Core i7 laptop with 6GB of RAM, it will still help performance and make multitasking even easier.  Also, if you have, say, a memory stick and a flash drive, you can use both of them with ReadyBoost for the maximum benefit.  We have even noticed better battery life when multitasking with ReadyBoost, as it lets you use your hard drive less.  SD cards and thumb drives are relatively cheap today, and many of us have several already, so this is a great way to improve netbook performance cheaply. Similar Articles Productive Geek Tips Speed up Your Windows Vista Computer with ReadyBoostSet the Speed Dial as the Opera Startup PageAsk the Readers: What are Your Computer’s Hardware Specs?Understanding Windows Vista Aero Glass RequirementsReplace Google Chrome’s New Tab Page with Speed Dial TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Recycle ! Find That Elusive Icon with FindIcons Looking for Good Windows Media Player 12 Plug-ins? Find Out the Celebrity You Resemble With FaceDouble Whoa ! Use Printflush to Solve Printing Problems

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  • Why one loop is performing better than other memory wise as well as performance wise?

    - by Mohit
    I have following two loops in C#, and I am running these loops for a collection with 10,000 records being downloaded with paging using "yield return" First foreach(var k in collection) { repo.Save(k); } Second var collectionEnum = collection.GetEnumerator(); while (collectionEnum.MoveNext()) { var k = collectionEnum.Current; repo.Save(k); k = null; } Seems like that the second loop consumes less memory and it faster than the first loop. Memory I understand may be because of k being set to null(Even though I am not sure). But how come it is faster than for each. Following is the actual code [Test] public void BechmarkForEach_Test() { bool isFirstTimeSync = true; Func<Contact, bool> afterProcessing = contactItem => { return true; }; var contactService = CreateSerivce("/administrator/components/com_civicrm"); var contactRepo = new ContactRepository(new Mock<ILogger>().Object); contactRepo.Drop(); contactRepo = new ContactRepository(new Mock<ILogger>().Object); Profile("For Each Profiling",1,()=>{ var localenumertaor=contactService.Download(); foreach (var item in localenumertaor) { if (isFirstTimeSync) item.StateFlag = 1; item.ClientTimeStamp = DateTime.UtcNow; if (item.StateFlag == 1) contactRepo.Insert(item); else contactRepo.Update(item); afterProcessing(item); } contactRepo.DeleteAll(); }); } [Test] public void BechmarkWhile_Test() { bool isFirstTimeSync = true; Func<Contact, bool> afterProcessing = contactItem => { return true; }; var contactService = CreateSerivce("/administrator/components/com_civicrm"); var contactRepo = new ContactRepository(new Mock<ILogger>().Object); contactRepo.Drop(); contactRepo = new ContactRepository(new Mock<ILogger>().Object); var itemsCollection = contactService.Download().GetEnumerator(); Profile("While Profiling", 1, () => { while (itemsCollection.MoveNext()) { var item = itemsCollection.Current; //if First time sync then ignore and overwrite the stateflag if (isFirstTimeSync) item.StateFlag = 1; item.ClientTimeStamp = DateTime.UtcNow; if (item.StateFlag == 1) contactRepo.Insert(item); else contactRepo.Update(item); afterProcessing(item); item = null; } contactRepo.DeleteAll(); }); } static void Profile(string description, int iterations, Action func) { // clean up GC.Collect(); GC.WaitForPendingFinalizers(); GC.Collect(); // warm up func(); var watch = Stopwatch.StartNew(); for (int i = 0; i < iterations; i++) { func(); } watch.Stop(); Console.Write(description); Console.WriteLine(" Time Elapsed {0} ms", watch.ElapsedMilliseconds); } I m using the micro bench marking, from a stackoverflow question itself benchmarking-small-code The time taken is For Each Profiling Time Elapsed 5249 ms While Profiling Time Elapsed 116 ms

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  • WebLogic Server Performance and Tuning: Part I - Tuning JVM

    - by Gokhan Gungor
    Each WebLogic Server instance runs in its own dedicated Java Virtual Machine (JVM) which is their runtime environment. Every Admin Server in any domain executes within a JVM. The same also applies for Managed Servers. WebLogic Server can be used for a wide variety of applications and services which uses the same runtime environment and resources. Oracle WebLogic ships with 2 different JVM, HotSpot and JRocket but you can choose which JVM you want to use. JVM is designed to optimize itself however it also provides some startup options to make small changes. There are default values for its memory and garbage collection. In real world, you will not want to stick with the default values provided by the JVM rather want to customize these values based on your applications which can produce large gains in performance by making small changes with the JVM parameters. We can tell the garbage collector how to delete garbage and we can also tell JVM how much space to allocate for each generation (of java Objects) or for heap. Remember during the garbage collection no other process is executed within the JVM or runtime, which is called STOP THE WORLD which can affect the overall throughput. Each JVM has its own memory segment called Heap Memory which is the storage for java Objects. These objects can be grouped based on their age like young generation (recently created objects) or old generation (surviving objects that have lived to some extent), etc. A java object is considered garbage when it can no longer be reached from anywhere in the running program. Each generation has its own memory segment within the heap. When this segment gets full, garbage collector deletes all the objects that are marked as garbage to create space. When the old generation space gets full, the JVM performs a major collection to remove the unused objects and reclaim their space. A major garbage collect takes a significant amount of time and can affect system performance. When we create a managed server either on the same machine or on remote machine it gets its initial startup parameters from $DOMAIN_HOME/bin/setDomainEnv.sh/cmd file. By default two parameters are set:     Xms: The initial heapsize     Xmx: The max heapsize Try to set equal initial and max heapsize. The startup time can be a little longer but for long running applications it will provide a better performance. When we set -Xms512m -Xmx1024m, the physical heap size will be 512m. This means that there are pages of memory (in the state of the 512m) that the JVM does not explicitly control. It will be controlled by OS which could be reserve for the other tasks. In this case, it is an advantage if the JVM claims the entire memory at once and try not to spend time to extend when more memory is needed. Also you can use -XX:MaxPermSize (Maximum size of the permanent generation) option for Sun JVM. You should adjust the size accordingly if your application dynamically load and unload a lot of classes in order to optimize the performance. You can set the JVM options/heap size from the following places:     Through the Admin console, in the Server start tab     In the startManagedWeblogic script for the managed servers     $DOMAIN_HOME/bin/startManagedWebLogic.sh/cmd     JAVA_OPTIONS="-Xms1024m -Xmx1024m" ${JAVA_OPTIONS}     In the setDomainEnv script for the managed servers and admin server (domain wide)     USER_MEM_ARGS="-Xms1024m -Xmx1024m" When there is free memory available in the heap but it is too fragmented and not contiguously located to store the object or when there is actually insufficient memory we can get java.lang.OutOfMemoryError. We should create Thread Dump and analyze if that is possible in case of such error. The second option we can use to produce higher throughput is to garbage collection. We can roughly divide GC algorithms into 2 categories: parallel and concurrent. Parallel GC stops the execution of all the application and performs the full GC, this generally provides better throughput but also high latency using all the CPU resources during GC. Concurrent GC on the other hand, produces low latency but also low throughput since it performs GC while application executes. The JRockit JVM provides some useful command-line parameters that to control of its GC scheme like -XgcPrio command-line parameter which takes the following options; XgcPrio:pausetime (To minimize latency, parallel GC) XgcPrio:throughput (To minimize throughput, concurrent GC ) XgcPrio:deterministic (To guarantee maximum pause time, for real time systems) Sun JVM has similar parameters (like  -XX:UseParallelGC or -XX:+UseConcMarkSweepGC) to control its GC scheme. We can add -verbosegc -XX:+PrintGCDetails to monitor indications of a problem with garbage collection. Try configuring JVM’s of all managed servers to execute in -server mode to ensure that it is optimized for a server-side production environment.

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  • SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28

    - by pinaldave
    Locking is a mechanism used by the SQL Server Database Engine to synchronize access by multiple users to the same piece of data, at the same time. In simpler words, it maintains the integrity of data by protecting (or preventing) access to the database object. From Book On-Line: LCK_M_BU Occurs when a task is waiting to acquire a Bulk Update (BU) lock. LCK_M_IS Occurs when a task is waiting to acquire an Intent Shared (IS) lock. LCK_M_IU Occurs when a task is waiting to acquire an Intent Update (IU) lock. LCK_M_IX Occurs when a task is waiting to acquire an Intent Exclusive (IX) lock. LCK_M_S Occurs when a task is waiting to acquire a Shared lock. LCK_M_SCH_M Occurs when a task is waiting to acquire a Schema Modify lock. LCK_M_SCH_S Occurs when a task is waiting to acquire a Schema Share lock. LCK_M_SIU Occurs when a task is waiting to acquire a Shared With Intent Update lock. LCK_M_SIX Occurs when a task is waiting to acquire a Shared With Intent Exclusive lock. LCK_M_U Occurs when a task is waiting to acquire an Update lock. LCK_M_UIX Occurs when a task is waiting to acquire an Update With Intent Exclusive lock. LCK_M_X Occurs when a task is waiting to acquire an Exclusive lock. LCK_M_XXX Explanation: I think the explanation of this wait type is the simplest. When any task is waiting to acquire lock on any resource, this particular wait type occurs. The common reason for the task to be waiting to put lock on the resource is that the resource is already locked and some other operations may be going on within it. This wait also indicates that resources are not available or are occupied at the moment due to some reasons. There is a good chance that the waiting queries start to time out if this wait type is very high. Client application may degrade the performance as well. You can use various methods to find blocking queries: EXEC sp_who2 SQL SERVER – Quickest Way to Identify Blocking Query and Resolution – Dirty Solution DMV – sys.dm_tran_locks DMV – sys.dm_os_waiting_tasks Reducing LCK_M_XXX wait: Check the Explicit Transactions. If transactions are very long, this wait type can start building up because of other waiting transactions. Keep the transactions small. Serialization Isolation can build up this wait type. If that is an acceptable isolation for your business, this wait type may be natural. The default isolation of SQL Server is ‘Read Committed’. One of my clients has changed their isolation to “Read Uncommitted”. I strongly discourage the use of this because this will probably lead to having lots of dirty data in the database. Identify blocking queries mentioned using various methods described above, and then optimize them. Partition can be one of the options to consider because this will allow transactions to execute concurrently on different partitions. If there are runaway queries, use timeout. (Please discuss this solution with your database architect first as timeout can work against you). Check if there is no memory and IO-related issue using the following counters: Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Flaws in my PHP development setup - sharing sources causing lags

    - by Wiktor
    I have following development setup for my PHP projects: Working station running on Windows 7 with PhpStorm IDE. GIT for version controlling. CentOS on virtual machine (VirtualBox) with Apache and MySQL (copy of production server). So far, I've been sharing project's source folders between host and guest systems and it was working quite well only really slow. The reason behind this is that Apache was reading files from remote folder (mounted locally). After doing some research, I found out that this set up can be improved by using disk mapping (Samba) instead of folder sharing. So I did that change. I configured my PhpStorm to automatically deploy files to mapped drive. Everything works like a charm now, except for one problem - when I change branches I need to synchronize project's local folder with the one on mapped drive and that takes time, a lot of time (like branching in SVN). Is there another way to handle this than just working on files directly on mapped drive?

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  • 3GB RAM Installed and Detected by BIOS, Windows Vista 32bit Only Sees 2GB

    - by Nathan Taylor
    I am attempting to install more RAM on a Windows Vista 32bit machine which is using a X6DAL-XG motherboard and the RAM amount reported in the BIOS is 3GB+, but Windows is only reporting 2GB installed. The motherboard has 6 RAM bays which I have populated with various combinations of 4 1GB sticks, and 2 512mb sticks, but no matter how I configure them Windows doesn't see more than 2GB. I realize of course 32-bit Windows has a 3gb cap on memory, but that doesn't explain why it will only report 2GB when there are in fact (currently) 5GB installed. I should think I would be able to see at least 3GB. According to the spec list for the motherboard the minimum RAM requirements are DDR333/266mhz installed in pairs. I have done this exactly, and the BIOS isn't reporting any problems at POST. RAM Configuration (according to CPU-Z): Slot #1: Kingston 128mx72D266C25 - 1024mb PC2100 (133mhz) Slot #2: Kingston KVR266X72RC25/1024 - 1024mb PC2100 (133mhz) Slot #3: PQI - 512mb PC2700 (166mhz) Slot #4: Kingston 128mx72D266C25 - 1024mb PC2100 (133mhz) Slot #5: Kingston KVR266X72RC25/1024 - 1024mb PC2100 (133mhz) Slot #6: PQI - 512mb PC2700 (166mhz) I'm not sure if memory specs above conflict with this statement in the motherboard manual or not: Memory Support The X6DAL-XG supports up to 12GB/24GB of registered ECC DDR333/266 (PC2700/PC2100) memory. The motherboard was designed to support 4GB (PC2100) modules in each slot, but only the 2GB modules have been tested. When using registered ECC DDR333 (PC2700) memory, installing four pieces of double-banked memory or six pieces of single-banked memory is supported. So, am I doing something wrong with the RAM I have now, or is there some sort of compatibility problem which I am missing? Thanks!

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  • How to force two process to run on the same CPU?

    - by kovan
    Context: I'm programming a software system that consists of multiple processes. It is programmed in C++ under Linux. and they communicate among them using Linux shared memory. Usually, in software development, is in the final stage when the performance optimization is made. Here I came to a big problem. The software has high performance requirements, but in machines with 4 or 8 CPU cores (usually with more than one CPU), it was only able to use 3 cores, thus wasting 25% of the CPU power in the first ones, and more than 60% in the second ones. After many research, and having discarded mutex and lock contention, I found out that the time was being wasted on shmdt/shmat calls (detach and attach to shared memory segments). After some more research, I found out that these CPUs, which usually are AMD Opteron and Intel Xeon, use a memory system called NUMA, which basically means that each processor has its fast, "local memory", and accessing memory from other CPUs is expensive. After doing some tests, the problem seems to be that the software is designed so that, basically, any process can pass shared memory segments to any other process, and to any thread in them. This seems to kill performance, as process are constantly accessing memory from other processes. Question: Now, the question is, is there any way to force pairs of processes to execute in the same CPU?. I don't mean to force them to execute always in the same processor, as I don't care in which one they are executed, altough that would do the job. Ideally, there would be a way to tell the kernel: If you schedule this process in one processor, you must also schedule this "brother" process (which is the process with which it communicates through shared memory) in that same processor, so that performance is not penalized.

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  • Best practice PHP Form Action

    - by Rob
    Hi there i've built a new script (from scratch not a CMS) and i've done alot of work on reducing memory usage and the time it takes for the page to be displayed (caching HTML etc) There's one thing that i'm not sure about though. Take a simple example of an article with a comments section. If the comment form posts to another page that then redirects back to the article page I won't have the problem of people clicking refresh and resending the information. However if I do it that way, I have to load up my script twice use twice as much memory and it takes twice as long whilst i'm still only displaying the page once. Here's an example from my load log. The first load of the article is from the cache, the second rebuilds the page after the comment is posted. Example 1 0 queries using 650856 bytes of memory in 0.018667 - domain.com/article/1/my_article.html 9 queries using 1325723 bytes of memory in 0.075825 - domain.com/article/1/my_article/newcomment.html 0 queries using 650856 bytes of memory in 0.029449 - domain.com/article/1/my_article.html Example 2 0 queries using 650856 bytes of memory in 0.023526 - domain.com/article/1/my_article.html 9 queries using 1659096 bytes of memory in 0.060032 - domain.com/article/1/my_article.html Obviously the time fluctuates so you can't really compare that. But as you can see with the first method I use more memory and it takes longer to load. BUT the first method avoides the refresh problem. Does anyone have any suggestions for the best approach or for alternative ways to avoid the extra load (admittadely minimal but i'd still like to avoid it) whilst also avoiding the refresh problem?

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