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  • An efficient way to store view counts for objects?

    - by Nick Brooks
    I maintain an application where users are able to store images, and then share them. The system is powered by MongoDB at the back end. Most of the image depiction pages are cached as flat HTML files, but I can run some code just before loading the file. I've decided to implement a view count for the system. I am wondering what is the best storage place for that. It should be like Memcached but it should save the viewcounts every hour or so, so even if our server has to be restarted we won't lose the view counts. What is the best solution for that (preferably with a PHP extension as a client)?

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  • SQL JOIN with two or more tables as output - most efficient way?

    - by littlegreen
    I have an SQL query that executes a LEFT JOIN on another table, then outputs all results that could be coupled into a designated table. I then have a second SQL query that executes the LEFT JOIN again, then outputs the results that could not be coupled to a designated table. In code, this is something like: INSERT INTO coupledrecords SELECT b.col1, b.col2... s.col1, s.col2... FROM bigtable AS b LEFT JOIN smallertable AS s ON criterium WHERE s.col1 IS NOT NULL INSERT INTO notcoupledrecords SELECT b.col1, b.col2... bigtable AS b LEFT JOIN smallertable AS s ON criterium WHERE s.col1 IS NULL My question: I now have to execute the JOIN two times, in order to achieve what I want. I have a feeling that this is twice as slow as it could be. Is this true, and if yes, is there a way to do it more efficiently?

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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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  • What is most efficient way of setting row to zeros for a sparce scipy matrix?

    - by Alex Reinking
    I'm trying to convert the following MATLAB code to Python and am having trouble finding a solution that works in any reasonable amount of time. M = diag(sum(a)) - a; where = vertcat(in, out); M(where,:) = 0; M(where,where) = 1; Here, a is a sparse matrix and where is a vector (as are in/out). The solution I have using Python is: M = scipy.sparse.diags([degs], [0]) - A where = numpy.hstack((inVs, outVs)).astype(int) M = scipy.sparse.lil_matrix(M) M[where, :] = 0 # This is the slowest line M[where, where] = 1 M = scipy.sparse.csc_matrix(M) But since A is 334863x334863, this takes like three minutes. If anyone has any suggestions on how to make this faster, please contribute them! For comparison, MATLAB does this same step imperceptibly fast. Thanks!

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  • Quickest and most efficient method to search top 3 numbers?

    - by Donal Rafferty
    I currently have an array of around 8 - 10 numbers that changes on a periodic basis. So around every 5 - 10 seconds the numbers get updated. I need to get the top 3 numbers in the array every 10 seconds. This is all done on a mobile device. At the minute I iterate through the array 3 times and each time I take out the three highest numbers and place them in three previously declared variables. My question is what should I look to do to increase speed and efficiency in this instance?

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  • C# Simpler / more efficient method of if ... else flow?

    - by Scott
    I'm currently working on an emulation server for a flash-client based game, which has a "pets system", and I was wondering if there was a simpler way of going about checking the level of specified pets. Current code: public int Level { get { if (Expirience 100) // Level 2 { if (Expirience 200) // Level 3 { if (Expirience 400) // Level 4 - Unsure of Goal { if (Expirience 600) // Level 5 - Unsure of Goal { if (Expirience 1000) // Level 6 { if (Expirience 1300) // Level 7 { if (Expirience 1800) // Level 8 { if (Expirience 2400) // Level 9 { if (Expirience 3200) // Level 10 { if (Expirience 4300) // Level 11 { if (Expirience 7200) // Level 12 - Unsure of Goal { if (Expirience 8500) // Level 13 - Unsure of Goal { if (Expirience 10100) // Level 14 { if (Expirience 13300) // Level 15 { if (Expirience 17500) // Level 16 { if (Expirience 23000) // Level 17 { return 17; // Bored } return 16; } return 15; } return 14; } return 13; } return 12; } return 11; } return 10; } return 9; } return 8; } return 7; } return 6; } return 5; } return 4; } return 3; } return 2; } return 1; } } Yes, I'm aware I've misspelt Experience, I had made the mistake in a previous function and hadn't gotten around to updating everything... :P

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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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  • 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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  • What would be the most efficient way to do this search (mysql or text)?

    - by alex
    Suppose I have 500 rows of data, each with a paragraph of text (like this paragraph). That's it.I want to do a search that is not only based on words. (%LIKE%, not FULL_TEXT) What would be faster? SELECT * FROM ...WHERE LIKE "%query%"; This would put load on the database server. Select all. Then, go through each one and do .find = 0 This would put load on the web server. This is a website, and people will be searching frequently.

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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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  • Low-overhead way to access the memory space of a traced process?

    - by vovick
    Hello all. I'm looking for an efficient way to access(for both read and write operations) the memory space of my ptraced child process. The size of blocks being accessed may vary from several bytes up to several megabytes in size, so using the ptrace call with PTRACE_PEEKDATA and PTRACE_POKEDATA which read only one word at a time and switch context every time they're called seems like a pointless waste of resources. The only one alternative solution I could find, though, was the /proc/<pid>/mem file, but it has long since been made read only. Is there any other (relatively simple) way to do that job? The ideal solution would be to somehow share the address space of my child process with its parent and then use the simple memcpy call to copy data I need in both directions, but I have no clues how to do it and where to begin. Any ideas?

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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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