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  • CentOS 5 : error in installing php-imap

    - by TMMDev
    can someone please help me with this CentOS 5 question? I am trying to install php-imap, i tried yum install php-imap but I am getting the following output: Loaded plugins: fastestmirror, priorities, security Loading mirror speeds from cached hostfile * base: centos.hostingxtreme.com * epel: mirror.steadfast.net * extras: mirror.team-cymru.org * updates: mirror.beyondhosting.net Setting up Install Process Resolving Dependencies --> Running transaction check ---> Package php-imap.x86_64 0:5.1.6-44.el5_10 set to be updated --> Processing Dependency: php-common = 5.1.6-44.el5_10 for package: php-imap --> Finished Dependency Resolution php-imap-5.1.6-44.el5_10.x86_64 from updates has depsolving problems --> Missing Dependency: php-common = 5.1.6-44.el5_10 is needed by package php-imap-5.1.6-44.el5_10.x86_64 (updates) Error: Missing Dependency: php-common = 5.1.6-44.el5_10 is needed by package php-imap-5.1.6-44.el5_10.x86_64 (updates) You could try using --skip-broken to work around the problem You could try running: package-cleanup --problems package-cleanup --dupes rpm -Va --nofiles --nodigest The program package-cleanup is found in the yum-utils package. I already have php-common installed, I ran "yum install php-common" and got the following output Loaded plugins: fastestmirror, priorities, security Loading mirror speeds from cached hostfile * base: centos.hostingxtreme.com * epel: mirror.steadfast.net * extras: mirror.team-cymru.org * updates: mirror.beyondhosting.net Setting up Install Process Package matching php-common-5.1.6-44.el5_10.x86_64 already installed. Checking for update. Nothing to do how can I fix this problem?

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  • Server slowdown

    - by Clinton Bosch
    I have a GWT application running on Tomcat on a cloud linux(Ubuntu) server, recently I released a new version of the application and suddenly my server response times have gone from 500ms average to 15s average. I have run every monitoring tool I know. iostat says my disks are 0.03% utilised mysqltuner.pl says I am OK other see below top says my processor is 99% idle and load average: 0.20, 0.31, 0.33 memory usage is 50% (-/+ buffers/cache: 3997 3974) mysqltuner output [OK] Logged in using credentials from debian maintenance account. -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.63-0ubuntu0.10.04.1-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 370M (Tables: 52) [--] Data in InnoDB tables: 697M (Tables: 1749) [!!] Total fragmented tables: 1754 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 19h 25m 41s (1M q [28.122 qps], 1K conn, TX: 2B, RX: 1B) [--] Reads / Writes: 98% / 2% [--] Total buffers: 1.0G global + 2.7M per thread (500 max threads) [OK] Maximum possible memory usage: 2.4G (30% of installed RAM) [OK] Slow queries: 0% (1/1M) [OK] Highest usage of available connections: 34% (173/500) [OK] Key buffer size / total MyISAM indexes: 16.0M/279.0K [OK] Key buffer hit rate: 99.9% (50K cached / 40 reads) [OK] Query cache efficiency: 61.4% (844K cached / 1M selects) [!!] Query cache prunes per day: 553779 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 34K sorts) [OK] Temporary tables created on disk: 4% (4K on disk / 102K total) [OK] Thread cache hit rate: 84% (185 created / 1K connections) [!!] Table cache hit rate: 0% (256 open / 27K opened) [OK] Open file limit used: 0% (20/2K) [OK] Table locks acquired immediately: 100% (692K immediate / 692K locks) [OK] InnoDB data size / buffer pool: 697.2M/1.0G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries Increase table_cache gradually to avoid file descriptor limits Variables to adjust: query_cache_size (> 16M) table_cache (> 256)

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  • sys.dm_exec_query_stats interaction with recompilation

    - by Sam Saffron
    We use sys.dm_exec_query_stats to track down slow queries and queries that are IO offenders. This works great, we get a lot of very insightful stats. It is clear this is not as accurate as running a profiler trace, as you have no idea when SQL Server will decide to chuck out a an execution plan. We have quite a few queries where the wrong execution plan is cached. For example queries like the following: SELECT TOP 30 a.Id FROM Posts a JOIN Posts q ON q.Id = a.ParentId JOIN PostTags pt ON q.Id = pt.PostId WHERE a.PostTypeId = 2 AND a.DeletionDate IS NULL AND a.CommunityOwnedDate IS NULL AND a.CreationDate @date AND LEN(a.Body) 300 AND pt.Tag = @tag AND a.Score 0 ORDER BY a.Score DESC The problem is that the ideal plan really depends on the date selected (screenshot of ideal plan): However if the wrong plan is cached, it totally chokes when the date range is big: (notice the big fat lines) To overcome this we were recommended to use either OPTION (OPTIMIZE FOR UNKNOWN) or OPTION (RECOMPILE) OPTIMIZE FOR UNKNOWN results in a slightly better plan, which is far from optimal. Executions are tracked in sys.dm_exec_query_stats. RECOMPILE results in the best plan being chosen, however no execution counts and stats are tracked in sys.dm_exec_query_stats. Is there another DMV we could use to track stats on queries with OPTION (RECOMPILE)? Is this behavior by-design? Is there another way we can for recompilation while keeping stats tracked in sys.dm_exec_query_stats? Note: the framework will always execute parameterized queries using sp_executesql

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  • ubuntu's average load never below "0.00 0.01 0.05"

    - by Karma Fusebox
    I have several ubuntu 12.04 VMs running on a ubuntu 12.04 KVM host. Those of the virtual machines that are totally idle with no services (except syslog and the other "small" standard stuff of a fresh installation) show a constant load of "0.00 0.01 0.05" in top/htop as average 1/5/15. When there are "real" applications running, the load averages behave perfectly normal but they never fall below the mentioned values. While this doesn't affect performance at all and could easily be ignored, it screws up the monitoring graphs in a very annoying way: (Notice how load15 behaves nicely if 0.05 for a short time in the right half of the pic) Unfortunately I don't know what diagnostic outputs might be helpful for you, so here's some default stuff: # top top - 16:31:01 up 1:05, 1 user, load average: 0.00, 0.01, 0.05 Tasks: 62 total, 1 running, 61 sleeping, 0 stopped, 0 zombie Cpu(s): 0.2%us, 0.2%sy, 0.0%ni, 99.2%id, 0.5%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 1019464k total, 73452k used, 946012k free, 6140k buffers Swap: 0k total, 0k used, 0k free, 22504k cached . # free -m total used free shared buffers cached Mem: 995 72 923 0 6 21 -/+ buffers/cache: 43 951 Swap: 0 0 0 . # iostat -x /dev/vda Linux 3.2.0-32-virtual (vm3) 11/15/2012 _x86_64_ (2 CPU) avg-cpu: %user %nice %system %iowait %steal %idle 0.25 0.00 0.65 0.20 0.24 98.66 Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await r_await w_await svctm %util vda 0.14 0.12 0.51 0.22 6.74 1.46 22.50 0.02 23.26 20.64 29.30 7.63 0.56 Need something else? Has anyone ever seen this behavior? Might this be a bug in kvm/ubuntu/kernel 3.x in the end? Thanks a lot!

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  • MysqlTunner and query_cache_size dilemma

    - by wbad
    On a busy mysql server MySQLTuner 1.2.0 always recommends to add query_cache_size no matter how I increase the value (I tried up to 512MB). On the other hand it warns that : Increasing the query_cache size over 128M may reduce performance Here are the last results: >> MySQLTuner 1.2.0 - Major Hayden <[email protected]> >> Bug reports, feature requests, and downloads at http://mysqltuner.com/ >> Run with '--help' for additional options and output filtering -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.5.25-1~dotdeb.0-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in InnoDB tables: 6G (Tables: 195) [--] Data in PERFORMANCE_SCHEMA tables: 0B (Tables: 17) [!!] Total fragmented tables: 51 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 1d 19h 17m 8s (254M q [1K qps], 5M conn, TX: 139B, RX: 32B) [--] Reads / Writes: 89% / 11% [--] Total buffers: 24.2G global + 92.2M per thread (1200 max threads) [!!] Maximum possible memory usage: 132.2G (139% of installed RAM) [OK] Slow queries: 0% (2K/254M) [OK] Highest usage of available connections: 32% (391/1200) [OK] Key buffer size / total MyISAM indexes: 128.0M/92.0K [OK] Key buffer hit rate: 100.0% (8B cached / 0 reads) [OK] Query cache efficiency: 79.9% (181M cached / 226M selects) [!!] Query cache prunes per day: 1033203 [OK] Sorts requiring temporary tables: 0% (341 temp sorts / 4M sorts) [OK] Temporary tables created on disk: 14% (760K on disk / 5M total) [OK] Thread cache hit rate: 99% (676 created / 5M connections) [OK] Table cache hit rate: 22% (1K open / 8K opened) [OK] Open file limit used: 0% (49/13K) [OK] Table locks acquired immediately: 99% (64M immediate / 64M locks) [OK] InnoDB data size / buffer pool: 6.1G/19.5G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Reduce your overall MySQL memory footprint for system stability Increasing the query_cache size over 128M may reduce performance Variables to adjust: *** MySQL's maximum memory usage is dangerously high *** *** Add RAM before increasing MySQL buffer variables *** query_cache_size (> 192M) [see warning above] The server has 76GB ram and dual E5-2650. The load is usually below 2. I appreciate your hints to interpret the recommendation and optimize the database configs.

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  • Apache APC (Windows) Can I optimize these APC settings more?

    - by ar099968
    I would like to optimize APC some more but I am not sure where I could do something. First here is the stats after 1 week of running with the current configuration: General Cache Information APC Version 3.1.9 PHP Version 5.4.4 APC Host XXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Server Software Apache Shared Memory 1 Segment(s) with 128.0 MBytes (IPC shared memory, Windows Slim RWLOCK (native) locking) Start Time 2014/06/08 05:00:00 Uptime 6 days, 11 hours and 55 minutes File Upload Support 1 Host Status Diagrams Memory Usage Free: 99.7 MBytes (77.9%) Used: 28.3 MBytes (22.1%) Hits & Misses Hits: 510818 (99.9%) Misses: 608 (0.1%) Detailed Memory Usage and Fragmentation Fragmentation: 0.60% (609.8 KBytes out of 99.7 MBytes in 83 fragments) File Cache Information Cached Files 693 ( 35.4 MBytes) Hits 5143359 Misses 1087 Request Rate (hits, misses) 13.24 cache requests/second Hit Rate 13.24 cache requests/second Miss Rate 0.00 cache requests/second Insert Rate 0.01 cache requests/second Cache full count 0 User Cache Information Cached Variables 0 ( 0.0 Bytes) Hits 0 Misses 0 Request Rate (hits, misses) 0.00 cache requests/second Hit Rate 0.00 cache requests/second Miss Rate 0.00 cache requests/second Insert Rate 0.00 cache requests/second Cache full count 0 Runtime Settings apc.cache_by_default 1 apc.canonicalize 1 apc.coredump_unmap 0 apc.enable_cli 0 apc.enabled 1 apc.file_md5 0 apc.file_update_protection 2 apc.filters -/apc.php$, -/apc_clean.php$, -.tpl.cache.php$, -.tpl.php$, -.string.cache.php$, -.string.php$ apc.gc_ttl 3600 apc.include_once_override 0 apc.lazy_classes 0 apc.lazy_functions 0 apc.max_file_size 2M apc.num_files_hint 7000 apc.preload_path apc.report_autofilter 0 apc.rfc1867 0 apc.rfc1867_freq 0 apc.rfc1867_name APC_UPLOAD_PROGRESS apc.rfc1867_prefix upload_ apc.rfc1867_ttl 3600 apc.serializer default apc.shm_segments 1 apc.shm_size 128M apc.shm_strings_buffer 4M apc.slam_defense 0 apc.stat 1 apc.stat_ctime 0 apc.ttl 7200 apc.use_request_time 1 apc.user_entries_hint 4096 apc.user_ttl 7200 apc.write_lock 1

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  • Plesk Uninstall Memory issue

    - by user115079
    I am trying to uninstall plesk from my VPS by running following command: yum remove sw-* psa-* plesk-* when i run this command i get following error: Running rpm_check_debug Running Transaction Test memory alloc (4 bytes) returned NULL. First time when i run above command, this mem alloc (4 bytes) was very big number like (67864987). then i googled it, got some clear/ulimit commands. executed them. rebooted my system. stopped all process and executed this command again. but still getting 4 byte issue. dont know how to get rid of it. I also tried ulimit after reboot but no success and Yes. No swap attached. these are stats of my system [root@vps ~]# free -m total used free shared buffers cached Mem: 384 67 316 0 0 0 -/+ buffers/cache: 67 316 Swap: 0 0 0 top - 21:01:07 up 3:12, 1 user, load average: 0.24, 0.08, 0.03 Tasks: 31 total, 2 running, 29 sleeping, 0 stopped, 0 zombie Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 393216k total, 69832k used, 323384k free, 0k buffers Swap: 0k total, 0k used, 0k free, 0k cached is there any other alternative to achieve my goal to uninstall plesk? thanks.

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  • What I should know about memory management?

    - by bua
    first of all: I don't use stackadmin or similar so please don't vote for moving there, I'm reading man top and paper "what every programmer should know about memory ..." I need really simple explanation like for retard ;) Having following top dump: top - 11:21:19 up 37 days, 21:16, 4 users, load average: 0.41, 0.75, 1.09 Tasks: 313 total, 5 running, 308 sleeping, 0 stopped, 0 zombie Cpu(s): 0.4%us, 0.6%sy, 0.9%ni, 96.2%id, 0.1%wa, 0.0%hi, 1.9%si, 0.0%st Mem: 132103848k total, 131916948k used, 186900k free, 54000k buffers Swap: 73400944k total, 73070884k used, 330060k free, 13931192k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 3305 tudb 25 10 144m 52m 940 R 6.0 0.0 1306:09 app 3011 tudb 15 0 71528 19m 604 S 3.3 0.0 171:57.83 app 3373 tudb 25 10 209m 93m 940 S 3.0 0.1 1074:53 app 3338 tudb 25 10 144m 47m 940 R 2.7 0.0 780:48.48 app 4227 tudb 25 10 208m 99m 904 S 1.3 0.1 198:56.01 app 8506 tudb 25 10 80.7g 49g 932 S 2.0 39.6 458:31.22 app I'm wondering what is: RES (my expl. physical memory consumption ? see 49GB) VIRT (memory mapped disk to cache? see 80GB) SHR (shared pages?) Swap: (is this cached label - for memory mapped disk into swap cache?) Should sum of RES give MEM: X used? or maybe sum of VIRT?

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  • Mod_pagespeed, Varnish and Apache cache issues after new code pushes

    - by WerkkreW
    I have a rather strange issue. In my environment we are running a load balanced cluster of 8 apache servers with a master-master MySQL backend. In front of apache we have Varnish in the cache layer. We have been running Apache mod_pagespeed for several weeks now and for the most part it has been working great. The issue arises when we do fresh code updates from Git, and and/all of the JS/CSS assets change. Basically the problem appears to be two fold. One, after the code push we generally take the opportunity to flush varnish, restart apache, and restart varnish. In doing this all of the mod_pagespeed combinied/minified files are cleared out ensuring that all of the new JS/CSS assets are fresh. The problem is, upon doing this the file names that mod_pagespeed creates change, but the old files (appear) to be still cached for many people client side leading to very unexpected results. However, if we do not restart apache, the changes to the files may or may not appear client side due to the cached minified assets. The simple solution is to disable mod_pagespeed, however I would rather not do that as it has made a fairly large impact in performance. I feel as if there must be a better way to deal with the inconsistencies in cache between the client and server to prevent having people to go to great lengths or perform a large number of page refreshes to see a working page. I can provide configuration snippets if anyone needs them. If you would like to inspect the site, source, headers, or anything try the following addresses: http://wellplayed.org http://wellplayed.org/tv Thanks in advance!

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  • CentOS server. What does it mean when the total used RAM does not equal the sum of RES?

    - by Michael Green
    I'm having a problem with a virtual hosted server running CentOS. In the past month a process (java based) that had been running fine started having problems getting memory when the JVM was started. One strange thing I've noticed is that when I start the process, the PID says it is using 470mb of RAM while the 'used' memory immediately drops by over a 1GB. If I run 'top', the total RES used across all processes falls short of the 'used' listed at the top by almost 700mb. The support person says this means I have a memory leak with my process. I don't know what to believe because I would expect a memory leak to simply waste the memory the process is allocated not to consume additional memory that doesn't show up using 'top'. I'm a developer and not a server guy so I'm appealing to the experts. To me, if the total RES memory doesn't add up to the total 'used' it indicates that something is wrong with my virtual server set-up. Would you also suspect a memory leaking java process in this case? If I use free before: total used free shared buffers cached Mem: 2097152 149264 1947888 0 0 0 -/+ buffers/cache: 149264 1947888 Swap: 0 0 0 free after: total used free shared buffers cached Mem: 2097152 1094116 1003036 0 0 0 -/+ buffers/cache: 1094116 1003036 Swap: 0 0 0 So it looks as though the process is using (or causing to be used) nearly 1GB of RAM. Since the process (based on top is only using 452mb, does that mean that the kernal is all of a sudden using an additional 500mb?

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  • How much free memory should I have on my webserver?

    - by neanderslob
    I have a webserver that's currently hosting two Wordpress sites and some java-based collaboration software. The server has 2G of memory and is currently using about 1.8G of the available memory. Right now what's on here is pretty much a pilot project that's getting negligible traffic so I think it's pretty clear that I'll be needing more memory. I was wondering, if I was to release it, how I might anticipate my memory needs based on the traffic it gets. I've poked around on Google and what I've found has been a bit tenuous. Is there a good heuristic that one should use when calculating memory demands as a function of the base (no traffic) load on the server? For reference, the output of free -m can be seen below: total used free shared buffers cached Mem: 2048 1832 215 0 0 0 -/+ buffers/cache: 1832 215 Swap: 0 0 0 To me this looks like actual memory used and isn't an illusion due to caching or anything else. I figure the demands of my collaboration software will have to be experimentally tested so here's free -m without that software running: total used free shared buffers cached Mem: 2048 1109 938 0 0 0 -/+ buffers/cache: 1109 938 Swap: 0 0 0 My plan B to figure this out is to add a bunch of swap space to the server, give it some traffic and adjust according the the amount that swap gets used. I was just wondering if anyone had a good rule of thumb to estimate how much memory I should plan on in advance...or if what I'm thinking is nuts. Many thanks in advance (I'm really quite new to this).

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  • Non-volatile cache RAID controllers: what kind of protection is there against NVCACHE failure?

    - by astrostl
    The battery back-up (BBU) model: admin enables write-back cache with BBU writes are cached to the RAID controller's RAM (major performance benefit) the battery saves uncommitted and cached data in the event of a power loss (reliability) If I lose power and come back within a day or so, my data should be both complete and uncorrupted. The downside to this is that, if the battery is dead or low, OR EVEN IF IT IS IN A RELEARN CYCLE (drain/charge loops to ensure the battery's health), the controller reverts to write-through mode and performance will suffer. What's more, the relearn cycles are usually automated on a schedule which may or may not happen in the middle of big traffic. So, that has to be manually disabled and manually scheduled for off-hours if it's a concern. Annoying either way. NV caches have capacitors with a sufficient charge to commit any uncommitted-to-disk data to flash. Not only is that more survivable in longer loss situations, but you don't have to concern yourself with battery death, wear-out, or relearning. All of that sounds great to me. What doesn't sound great to me is the prospect of that flash module having an issue, though. What if it's completely hosed? What if it's only partially hosed? A bit corrupted at the edges? Relearn cycles can tell when something like a simple battery is failing, but is there a similar process to verify that the flash is functional? I'm just far more trusting of a battery, warts and all. I know the card's RAM can fail, the card itself can fail - that's common territory, though. In case you didn't guess, yeah, I've experienced a shocking-to-me amount of flash/SSD/etc. failure :)

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  • Server Memory with Magento

    - by Mohamed Elgharabawy
    I have a cloud server with the following specifications: 2vCPUs 4G RAM 160GB Disk Space Network 400Mb/s System Image: Ubuntu 12.04 LTS I am only running Magento CE 1.7.0.2 on this server. Nothing else. Usually, the server has a loading time of 4-5 seconds. Recently, this has dropped to over 30 seconds and sometimes the server just goes away and I get HTTP error reports to my email stating that HTTP requests took more than 20000ms. Running top command and sorting them returns the following: top - 15:29:07 up 3:40, 1 user, load average: 28.59, 25.95, 22.91 Tasks: 112 total, 30 running, 82 sleeping, 0 stopped, 0 zombie Cpu(s): 90.2%us, 9.3%sy, 0.0%ni, 0.0%id, 0.0%wa, 0.0%hi, 0.3%si, 0.2%st PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 31901 www-data 20 0 360m 71m 5840 R 7 1.8 1:39.51 apache2 32084 www-data 20 0 362m 72m 5548 R 7 1.8 1:31.56 apache2 32089 www-data 20 0 348m 59m 5660 R 7 1.5 1:41.74 apache2 32295 www-data 20 0 343m 54m 5532 R 7 1.4 2:00.78 apache2 32303 www-data 20 0 354m 65m 5260 R 7 1.6 1:38.76 apache2 32304 www-data 20 0 346m 56m 5544 R 7 1.4 1:41.26 apache2 32305 www-data 20 0 348m 59m 5640 R 7 1.5 1:50.11 apache2 32291 www-data 20 0 358m 69m 5256 R 6 1.7 1:44.26 apache2 32517 www-data 20 0 345m 56m 5532 R 6 1.4 1:45.56 apache2 30473 www-data 20 0 355m 66m 5680 R 6 1.7 2:00.05 apache2 32093 www-data 20 0 352m 63m 5848 R 6 1.6 1:53.23 apache2 32302 www-data 20 0 345m 56m 5512 R 6 1.4 1:55.87 apache2 32433 www-data 20 0 346m 57m 5500 S 6 1.4 1:31.58 apache2 32638 www-data 20 0 354m 65m 5508 R 6 1.6 1:36.59 apache2 32230 www-data 20 0 347m 57m 5524 R 6 1.4 1:33.96 apache2 32231 www-data 20 0 355m 66m 5512 R 6 1.7 1:37.47 apache2 32233 www-data 20 0 354m 64m 6032 R 6 1.6 1:59.74 apache2 32300 www-data 20 0 355m 66m 5672 R 6 1.7 1:43.76 apache2 32510 www-data 20 0 347m 58m 5512 R 6 1.5 1:42.54 apache2 32521 www-data 20 0 348m 59m 5508 R 6 1.5 1:47.99 apache2 32639 www-data 20 0 344m 55m 5512 R 6 1.4 1:34.25 apache2 32083 www-data 20 0 345m 56m 5696 R 5 1.4 1:59.42 apache2 32085 www-data 20 0 347m 58m 5692 R 5 1.5 1:42.29 apache2 32293 www-data 20 0 353m 64m 5676 R 5 1.6 1:52.73 apache2 32301 www-data 20 0 348m 59m 5564 R 5 1.5 1:49.63 apache2 32528 www-data 20 0 351m 62m 5520 R 5 1.6 1:36.11 apache2 31523 mysql 20 0 3460m 576m 8288 S 5 14.4 2:06.91 mysqld 32002 www-data 20 0 345m 55m 5512 R 5 1.4 2:01.88 apache2 32080 www-data 20 0 357m 68m 5512 S 5 1.7 1:31.30 apache2 32163 www-data 20 0 347m 58m 5512 S 5 1.5 1:58.68 apache2 32509 www-data 20 0 345m 56m 5504 R 5 1.4 1:49.54 apache2 32306 www-data 20 0 358m 68m 5504 S 4 1.7 1:53.29 apache2 32165 www-data 20 0 344m 55m 5524 S 4 1.4 1:40.71 apache2 32640 www-data 20 0 345m 56m 5528 R 4 1.4 1:36.49 apache2 31888 www-data 20 0 359m 70m 5664 R 4 1.8 1:57.07 apache2 32511 www-data 20 0 357m 67m 5512 S 3 1.7 1:47.00 apache2 32054 www-data 20 0 357m 68m 5660 S 2 1.7 1:53.10 apache2 1 root 20 0 24452 2276 1232 S 0 0.1 0:01.58 init Moreover, running free -m returns the following: total used free shared buffers cached Mem: 4003 3919 83 0 118 901 -/+ buffers/cache: 2899 1103 Swap: 0 0 0 To investigate this further, I have installed apache buddy, it recommeneded that I need to reduce the maxclient connections. Which I did. I also installed MysqlTuner and it suggests that I need to set my innodb_buffer_pool_size to = 3.0G. However, I cannot do that, since the whole memory is 4G. Here is the output from apache buddy: ### GENERAL REPORT ### Settings considered for this report: Your server's physical RAM: 4003MB Apache's MaxClients directive: 40 Apache MPM Model: prefork Largest Apache process (by memory): 73.77MB [ OK ] Your MaxClients setting is within an acceptable range. Max potential memory usage: 2950.8 MB Percentage of RAM allocated to Apache 73.72 % And this is the output of MySQLTuner: -------- Performance Metrics ------------------------------------------------- [--] Up for: 47m 22s (675K q [237.552 qps], 12K conn, TX: 1B, RX: 300M) [--] Reads / Writes: 45% / 55% [--] Total buffers: 2.1G global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 2.5G (64% of installed RAM) [OK] Slow queries: 0% (0/675K) [OK] Highest usage of available connections: 26% (40/151) [OK] Key buffer size / total MyISAM indexes: 36.0M/18.7M [OK] Key buffer hit rate: 100.0% (245K cached / 105 reads) [OK] Query cache efficiency: 92.5% (500K cached / 541K selects) [!!] Query cache prunes per day: 302886 [OK] Sorts requiring temporary tables: 0% (1 temp sorts / 15K sorts) [!!] Joins performed without indexes: 12135 [OK] Temporary tables created on disk: 25% (8K on disk / 32K total) [OK] Thread cache hit rate: 90% (1K created / 12K connections) [!!] Table cache hit rate: 17% (400 open / 2K opened) [OK] Open file limit used: 12% (123/1K) [OK] Table locks acquired immediately: 100% (196K immediate / 196K locks) [!!] InnoDB buffer pool / data size: 2.0G/3.5G [OK] InnoDB log waits: 0 -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Read this before increasing table_cache over 64: http://bit.ly/1mi7c4C Variables to adjust: query_cache_size ( 64M) join_buffer_size ( 128.0K, or always use indexes with joins) table_cache ( 400) innodb_buffer_pool_size (= 3G) Last but not least, the server still has more than 60% of free disk space. Now, based on the above, I have few questions: Are these numbers normal? Do they make sense? Do I need to upgrade the server? If I don't need to upgrade and my configuration is not correct, how do I optimize it?

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  • ASP.NET GZip Encoding Caveats

    - by Rick Strahl
    GZip encoding in ASP.NET is pretty easy to accomplish using the built-in GZipStream and DeflateStream classes and applying them to the Response.Filter property.  While applying GZip and Deflate behavior is pretty easy there are a few caveats that you have watch out for as I found out today for myself with an application that was throwing up some garbage data. But before looking at caveats let’s review GZip implementation for ASP.NET. ASP.NET GZip/Deflate Basics Response filters basically are applied to the Response.OutputStream and transform it as data is written to it through the ASP.NET Response object. So a Response.Write eventually gets written into the output stream which if a filter is also written through the filter stream’s interface. To perform the actual GZip (and Deflate) encoding typically used by Web pages .NET includes the GZipStream and DeflateStream stream classes which can be readily assigned to the Repsonse.OutputStream. With these two stream classes in place it’s almost trivially easy to create a couple of reusable methods that allow you to compress your HTTP output. In my standard WebUtils utility class (from the West Wind West Wind Web Toolkit) created two static utility methods – IsGZipSupported and GZipEncodePage – that check whether the client supports GZip encoding and then actually encodes the current output (note that although the method includes ‘Page’ in its name this code will work with any ASP.NET output). /// <summary> /// Determines if GZip is supported /// </summary> /// <returns></returns> public static bool IsGZipSupported() { string AcceptEncoding = HttpContext.Current.Request.Headers["Accept-Encoding"]; if (!string.IsNullOrEmpty(AcceptEncoding) && (AcceptEncoding.Contains("gzip") || AcceptEncoding.Contains("deflate"))) return true; return false; } /// <summary> /// Sets up the current page or handler to use GZip through a Response.Filter /// IMPORTANT: /// You have to call this method before any output is generated! /// </summary> public static void GZipEncodePage() { HttpResponse Response = HttpContext.Current.Response; if (IsGZipSupported()) { string AcceptEncoding = HttpContext.Current.Request.Headers["Accept-Encoding"]; if (AcceptEncoding.Contains("deflate")) { Response.Filter = new System.IO.Compression.DeflateStream(Response.Filter, System.IO.Compression.CompressionMode.Compress); Response.Headers.Remove("Content-Encoding"); Response.AppendHeader("Content-Encoding", "deflate"); } else { Response.Filter = new System.IO.Compression.GZipStream(Response.Filter, System.IO.Compression.CompressionMode.Compress); Response.Headers.Remove("Content-Encoding"); Response.AppendHeader("Content-Encoding", "gzip"); } } } As you can see the actual assignment of the Filter is as simple as: Response.Filter = new DeflateStream(Response.Filter, System.IO.Compression.CompressionMode.Compress); which applies the filter to the OutputStream. You also need to ensure that your response reflects the new GZip or Deflate encoding and ensure that any pages that are cached in Proxy servers can differentiate between pages that were encoded with the various different encodings (or no encoding). To use this utility function now is trivially easy: In any ASP.NET code that wants to compress its Response output you simply use: protected void Page_Load(object sender, EventArgs e) { WebUtils.GZipEncodePage(); Entry = WebLogFactory.GetEntry(); var entries = Entry.GetLastEntries(App.Configuration.ShowEntryCount, "pk,Title,SafeTitle,Body,Entered,Feedback,Location,ShowTopAd", "TEntries"); if (entries == null) throw new ApplicationException("Couldn't load WebLog Entries: " + Entry.ErrorMessage); this.repEntries.DataSource = entries; this.repEntries.DataBind(); } Here I use an ASP.NET page, but the above WebUtils.GZipEncode() method call will work in any ASP.NET application type including HTTP Handlers. The only requirement is that the filter needs to be applied before any other output is sent to the OutputStream. For example, in my CallbackHandler service implementation by default output over a certain size is GZip encoded. The output that is generated is JSON or XML and if the output is over 5k in size I apply WebUtils.GZipEncode(): if (sbOutput.Length > GZIP_ENCODE_TRESHOLD) WebUtils.GZipEncodePage(); Response.ContentType = ControlResources.STR_JsonContentType; HttpContext.Current.Response.Write(sbOutput.ToString()); Ok, so you probably get the idea: Encoding GZip/Deflate content is pretty easy. Hold on there Hoss –Watch your Caching Or is it? There are a few caveats that you need to watch out for when dealing with GZip content. The fist issue is that you need to deal with the fact that some clients don’t support GZip or Deflate content. Most modern browsers support it, but if you have a programmatic Http client accessing your content GZip/Deflate support is by no means guaranteed. For example, WinInet Http clients don’t support GZip out of the box – it has to be explicitly implemented. Other low level HTTP clients on other platforms too don’t support GZip out of the box. The problem is that your application, your Web Server and Proxy Servers on the Internet might be caching your generated content. If you return content with GZip once and then again without, either caching is not applied or worse the wrong type of content is returned back to the client from a cache or proxy. The result is an unreadable response for *some clients* which is also very hard to debug and fix once in production. You already saw the issue of Proxy servers addressed in the GZipEncodePage() function: // Allow proxy servers to cache encoded and unencoded versions separately Response.AppendHeader("Vary", "Content-Encoding"); This ensures that any Proxy servers also check for the Content-Encoding HTTP Header to cache their content – not just the URL. The same thing applies if you do OutputCaching in your own ASP.NET code. If you generate output for GZip on an OutputCached page the GZipped content will be cached (either by ASP.NET’s cache or in some cases by the IIS Kernel Cache). But what if the next client doesn’t support GZip? She’ll get served a cached GZip page that won’t decode and she’ll get a page full of garbage. Wholly undesirable. To fix this you need to add some custom OutputCache rules by way of the GetVaryByCustom() HttpApplication method in your global_ASAX file: public override string GetVaryByCustomString(HttpContext context, string custom) { // Override Caching for compression if (custom == "GZIP") { string acceptEncoding = HttpContext.Current.Response.Headers["Content-Encoding"]; if (string.IsNullOrEmpty(acceptEncoding)) return ""; else if (acceptEncoding.Contains("gzip")) return "GZIP"; else if (acceptEncoding.Contains("deflate")) return "DEFLATE"; return ""; } return base.GetVaryByCustomString(context, custom); } In a page that use Output caching you then specify: <%@ OutputCache Duration="180" VaryByParam="none" VaryByCustom="GZIP" %> To use that custom rule. It’s all Fun and Games until ASP.NET throws an Error Ok, so you’re up and running with GZip, you have your caching squared away and your pages that you are applying it to are jamming along. Then BOOM, something strange happens and you get a lovely garbled page that look like this: Lovely isn’t it? What’s happened here is that I have WebUtils.GZipEncode() applied to my page, but there’s an error in the page. The error falls back to the ASP.NET error handler and the error handler removes all existing output (good) and removes all the custom HTTP headers I’ve set manually (usually good, but very bad here). Since I applied the Response.Filter (via GZipEncode) the output is now GZip encoded, but ASP.NET has removed my Content-Encoding header, so the browser receives the GZip encoded content without a notification that it is encoded as GZip. The result is binary output. Here’s what Fiddler says about the raw HTTP header output when an error occurs when GZip encoding was applied: HTTP/1.1 500 Internal Server Error Cache-Control: private Content-Type: text/html; charset=utf-8 Date: Sat, 30 Apr 2011 22:21:08 GMT Content-Length: 2138 Connection: close ?`I?%&/m?{J?J??t??` … binary output striped here Notice: no Content-Encoding header and that’s why we’re seeing this garbage. ASP.NET has stripped the Content-Encoding header but left our filter intact. So how do we fix this? In my applications I typically have a global Application_Error handler set up and in this case I’ve been using that. One thing that you can do in the Application_Error handler is explicitly clear out the Response.Filter and set it to null at the top: protected void Application_Error(object sender, EventArgs e) { // Remove any special filtering especially GZip filtering Response.Filter = null; … } And voila I get my Yellow Screen of Death or my custom generated error output back via uncompressed content. BTW, the same is true for Page level errors handled in Page_Error or ASP.NET MVC Error handling methods in a controller. Another and possibly even better solution is to check whether a filter is attached just before the headers are sent to the client as pointed out by Adam Schroeder in the comments: protected void Application_PreSendRequestHeaders() { // ensure that if GZip/Deflate Encoding is applied that headers are set // also works when error occurs if filters are still active HttpResponse response = HttpContext.Current.Response; if (response.Filter is GZipStream && response.Headers["Content-encoding"] != "gzip") response.AppendHeader("Content-encoding", "gzip"); else if (response.Filter is DeflateStream && response.Headers["Content-encoding"] != "deflate") response.AppendHeader("Content-encoding", "deflate"); } This uses the Application_PreSendRequestHeaders() pipeline event to check for compression encoding in a filter and adjusts the content accordingly. This is actually a better solution since this is generic – it’ll work regardless of how the content is cleaned up. For example, an error Response.Redirect() or short error display might get changed and the filter not cleared and this code actually handles that. Sweet, thanks Adam. It’s unfortunate that ASP.NET doesn’t natively clear out Response.Filters when an error occurs just as it clears the Response and Headers. I can’t see where leaving a Filter in place in an error situation would make any sense, but hey - this is what it is and it’s easy enough to fix as long as you know where to look. Riiiight! IIS and GZip I should also mention that IIS 7 includes good support for compression natively. If you can defer encoding to let IIS perform it for you rather than doing it in your code by all means you should do it! Especially any static or semi-dynamic content that can be made static should be using IIS built-in compression. Dynamic caching is also supported but is a bit more tricky to judge in terms of performance and footprint. John Forsyth has a great article on the benefits and drawbacks of IIS 7 compression which gives some detailed performance comparisons and impact reviews. I’ll post another entry next with some more info on IIS compression since information on it seems to be a bit hard to come by. Related Content Built-in GZip/Deflate Compression in IIS 7.x HttpWebRequest and GZip Responses © Rick Strahl, West Wind Technologies, 2005-2011Posted in ASP.NET   IIS7  

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  • Caching NHibernate Named Queries

    - by TStewartDev
    I recently started a new job and one of my first tasks was to implement a "popular products" design. The parameters were that it be done with NHibernate and be cached for 24 hours at a time because the query will be pretty taxing and the results do not need to be constantly up to date. This ended up being tougher than it sounds. The database schema meant a minimum of four joins with filtering and ordering criteria. I decided to use a stored procedure rather than letting NHibernate create the SQL for me. Here is a summary of what I learned (even if I didn't ultimately use all of it): You can't, at the time of this writing, use Fluent NHibernate to configure SQL named queries or imports You can return persistent entities from a stored procedure and there are a couple ways to do that You can populate POCOs using the results of a stored procedure, but it isn't quite as obvious You can reuse your named query result mapping other places (avoid duplication) Caching your query results is not at all obvious Testing to see if your cache is working is a pain NHibernate does a lot of things right. Having unified, up-to-date, comprehensive, and easy-to-find documentation is not one of them. By the way, if you're new to this, I'll use the terms "named query" and "stored procedure" (from NHibernate's perspective) fairly interchangeably. Technically, a named query can execute any SQL, not just a stored procedure, and a stored procedure doesn't have to be executed from a named query, but for reusability, it seems to me like the best practice. If you're here, chances are good you're looking for answers to a similar problem. You don't want to read about the path, you just want the result. So, here's how to get this thing going. The Stored Procedure NHibernate has some guidelines when using stored procedures. For Microsoft SQL Server, you have to return a result set. The scalar value that the stored procedure returns is ignored as are any result sets after the first. Other than that, it's nothing special. CREATE PROCEDURE GetPopularProducts @StartDate DATETIME, @MaxResults INT AS BEGIN SELECT [ProductId], [ProductName], [ImageUrl] FROM SomeTableWithJoinsEtc END The Result Class - PopularProduct You have two options to transport your query results to your view (or wherever is the final destination): you can populate an existing mapped entity class in your model, or you can create a new entity class. If you go with the existing model, the advantage is that the query will act as a loader and you'll get full proxied access to the domain model. However, this can be a disadvantage if you require access to the related entities that aren't loaded by your results. For example, my PopularProduct has image references. Unless I tie them into the query (thus making it even more complicated and expensive to run), they'll have to be loaded on access, requiring more trips to the database. Since we're trying to avoid trips to the database by using a second-level cache, we should use the second option, which is to create a separate entity for results. This approach is (I believe) in the spirit of the Command-Query Separation principle, and it allows us to flatten our data and optimize our report-generation process from data source to view. public class PopularProduct { public virtual int ProductId { get; set; } public virtual string ProductName { get; set; } public virtual string ImageUrl { get; set; } } The NHibernate Mappings (hbm) Next up, we need to let NHibernate know about the query and where the results will go. Below is the markup for the PopularProduct class. Notice that I'm using the <resultset> element and that it has a name attribute. The name allows us to drop this into our query map and any others, giving us reusability. Also notice the <import> element which lets NHibernate know about our entity class. <?xml version="1.0" encoding="utf-8" ?> <hibernate-mapping xmlns="urn:nhibernate-mapping-2.2"> <import class="PopularProduct, Infrastructure.NHibernate, Version=1.0.0.0"/> <resultset name="PopularProductResultSet"> <return-scalar column="ProductId" type="System.Int32"/> <return-scalar column="ProductName" type="System.String"/> <return-scalar column="ImageUrl" type="System.String"/> </resultset> </hibernate-mapping>  And now the PopularProductsMap: <?xml version="1.0" encoding="utf-8" ?> <hibernate-mapping xmlns="urn:nhibernate-mapping-2.2"> <sql-query name="GetPopularProducts" resultset-ref="PopularProductResultSet" cacheable="true" cache-mode="normal"> <query-param name="StartDate" type="System.DateTime" /> <query-param name="MaxResults" type="System.Int32" /> exec GetPopularProducts @StartDate = :StartDate, @MaxResults = :MaxResults </sql-query> </hibernate-mapping>  The two most important things to notice here are the resultset-ref attribute, which links in our resultset mapping, and the cacheable attribute. The Query Class – PopularProductsQuery So far, this has been fairly obvious if you're familiar with NHibernate. This next part, maybe not so much. You can implement your query however you want to; for me, I wanted a self-encapsulated Query class, so here's what it looks like: public class PopularProductsQuery : IPopularProductsQuery { private static readonly IResultTransformer ResultTransformer; private readonly ISessionBuilder _sessionBuilder;   static PopularProductsQuery() { ResultTransformer = Transformers.AliasToBean<PopularProduct>(); }   public PopularProductsQuery(ISessionBuilder sessionBuilder) { _sessionBuilder = sessionBuilder; }   public IList<PopularProduct> GetPopularProducts(DateTime startDate, int maxResults) { var session = _sessionBuilder.GetSession(); var popularProducts = session .GetNamedQuery("GetPopularProducts") .SetCacheable(true) .SetCacheRegion("PopularProductsCacheRegion") .SetCacheMode(CacheMode.Normal) .SetReadOnly(true) .SetResultTransformer(ResultTransformer) .SetParameter("StartDate", startDate.Date) .SetParameter("MaxResults", maxResults) .List<PopularProduct>();   return popularProducts; } }  Okay, so let's look at each line of the query execution. The first, GetNamedQuery, matches up with our NHibernate mapping for the sql-query. Next, we set it as cacheable (this is probably redundant since our mapping also specified it, but it can't hurt, right?). Then we set the cache region which we'll get to in the next section. Set the cache mode (optional, I believe), and my cache is read-only, so I set that as well. The result transformer is very important. This tells NHibernate how to transform your query results into a non-persistent entity. You can see I've defined ResultTransformer in the static constructor using the AliasToBean transformer. The name is obviously leftover from Java/Hibernate. Finally, set your parameters and then call a result method which will execute the query. Because this is set to cached, you execute this statement every time you run the query and NHibernate will know based on your parameters whether to use its cached version or a fresh version. The Configuration – hibernate.cfg.xml and Web.config You need to explicitly enable second-level caching in your hibernate configuration: <hibernate-configuration xmlns="urn:nhibernate-configuration-2.2"> <session-factory> [...] <property name="dialect">NHibernate.Dialect.MsSql2005Dialect</property> <property name="cache.provider_class">NHibernate.Caches.SysCache.SysCacheProvider,NHibernate.Caches.SysCache</property> <property name="cache.use_query_cache">true</property> <property name="cache.use_second_level_cache">true</property> [...] </session-factory> </hibernate-configuration> Both properties "use_query_cache" and "use_second_level_cache" are necessary. As this is for a web deployement, we're using SysCache which relies on ASP.NET's caching. Be aware of this if you're not deploying to the web! You'll have to use a different cache provider. We also need to tell our cache provider (in this cache, SysCache) about our caching region: <syscache> <cache region="PopularProductsCacheRegion" expiration="86400" priority="5" /> </syscache> Here I've set the cache to be valid for 24 hours. This XML snippet goes in your Web.config (or in a separate file referenced by Web.config, which helps keep things tidy). The Payoff That should be it! At this point, your queries should run once against the database for a given set of parameters and then use the cache thereafter until it expires. You can, of course, adjust settings to work in your particular environment. Testing Testing your application to ensure it is using the cache is a pain, but if you're like me, you want to know that it's actually working. It's a bit involved, though, so I'll create a separate post for it if comments indicate there is interest.

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  • My PNG has transparency, but after saving with PHP GD, transparency is lost [closed]

    - by Harry Stroker
    I found the solution to my problem. See below the original post and completely at the bottom my solution. I made a stupid mistake :) First I crop an image and then save it to a png file. Right after this, I also show the image. However, the saved png does not have transparency and the shown one has. What is going on? $this->resource = imagecreatefrompng($this->url); imagealphablending($this->resource, false); imagesavealpha($this->resource, true); $newResource = imagecreatetruecolor($destWidth, $destHeight); imagealphablending($newResource, false); imagesavealpha($newResource, true); $resample = imagecopyresampled($newResource,$this->resource,0,0,$srcX1,$srcY1,$destWidth,$destHeight,$srcX2-$srcX1, $srcY2-$srcY1); imagedestroy($this->resource); $this->resource = $newResource; // SAVING imagepng($this->resource, $destination, 100); // SHOWING header('Content-type: image/png'); imagepng($this->resource); The reason I also save the image is for caching. If the script is executed on a png, it saves a cached png. Next time the image is requested, the png file will be shown, but it has lost its transparency. Even stranger: When I save that cached png image as (within Firefox), it saves it suddenly as a jpg, even though the extension was png. Downloading the cached png using chrome and opening it in Photoshop gives the error: "file-format module cannot parse the file". I will show you the shown PNG and the generated PNG: http://www.foodmuseum.nl/SaveProblemTransparency.png Once I try to show that saved PNG with the GD library, it gives me an error. EDIT NO NO NO NO THIS IS NOT A DUPLICATE!!!... I ALREADY USED THEIR SOLUTION. The solution in the supposedly duplicate works for showing my image. But I also try to save it with the exact same resource, but then it has no transparency. EDIT 2 - SOLUTION I found out what the problem was. It was a stupid mistake. The script I provided above were cut out of a class and placed as sequential code, while in real this is not what exactly happened. The save image function: function saveImage($destination,$quality = 90) { $this->loadResource(); switch($extension){ default: case 'JPG': case 'jpg': imagejpeg($this->resource, $destination, $quality); break; case 'gif': imagegif($this->resource, $destination); break; case 'png': imagepng($this->resource, $destination); break; case 'gd2': imagegd2($this->resource, $destination); break; } } However... $extension does not exist. I fixed it by adding: $extension = $this->getExtension($destination);

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  • boost::serialization with mutable members

    - by redmoskito
    Using boost::serialization, what's the "best" way to serialize an object that contains cached, derived values in mutable members, such that cached members aren't serialized, but on deserialization, they are initialized the their appropriate default. A definition of "best" follows later, but first an example: class Example { public: Example(float n) : num(n), sqrt_num(-1.0) {} float get_num() const { return num; } // compute and cache sqrt on first read float get_sqrt() const { if(sqrt_num < 0) sqrt_num = sqrt(num); return sqrt_num; } template <class Archive> void serialize(Archive& ar, unsigned int version) { ... } private: float num; mutable float sqrt_num; }; On serialization, only the "num" member should be saved. On deserialization, the sqrt_num member must be initialized to its sentinel value indicating it needs to be computed. What is the most elegant way to implement this? In my mind, an elegant solution would avoid splitting serialize() into separate save() and load() methods (which introduces maintenance problems). One possible implementation of serialize: template <class Archive> void serialize(Archive& ar, unsigned int version) { ar & num; sqrt_num = -1.0; } This handles the deserialization case, but in the serialization case, the cached value is killed and must be recomputed. Also, I've never seen an example of boost::serialize that explicitly sets members inside of serialize(), so I wonder if this is generally not recommended. Some might suggest that the default constructor handles this, for example: int main() { Example e; { std::ifstream ifs("filename"); boost::archive::text_iarchive ia(ifs); ia >> e; } cout << e.get_sqrt() << endl; return 0; } which works in this case, but I think fails if the object receiving the deserialized data has already been initialized, as in the example below: int main() { Example ex1(4); Example ex2(9); cout << ex1.get_sqrt() << endl; // outputs 2; cout << ex2.get_sqrt() << endl; // outputs 3; // the following two blocks should implement ex2 = ex1; // save ex1 to archive { std::ofstream ofs("filename"); boost::archive::text_oarchive oa(ofs); oa << ex1; } // read it back into ex2 { std::ifstream ifs("filename"); boost::archive::text_iarchive ia(ifs); ia >> ex2; } // these should be equal now, but aren't, // since Example::serialize() doesn't modify num_sqrt cout << ex1.get_sqrt() << endl; // outputs 2; cout << ex2.get_sqrt() << endl; // outputs 3; return 0; } I'm sure this issue has come up with others, but I have struggled to find any documentation on this particular scenario. Thanks!

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  • Neo4j increasing latency as SKIP increases on Cypher query + REST API

    - by voldomazta
    My setup: Java(TM) SE Runtime Environment (build 1.7.0_45-b18) Java HotSpot(TM) 64-Bit Server VM (build 24.45-b08, mixed mode) Neo4j 2.0.0-M06 Enterprise First I made sure I warmed up the cache by executing the following: START n=node(*) RETURN COUNT(n); START r=relationship(*) RETURN count(r); The size of the table is 63,677 nodes and 7,169,995 relationships Now I have the following query: START u1=node:node_auto_index('uid:39') MATCH (u1:user)-[w:WANTS]->(c:card)<-[h:HAS]-(u2:user) WHERE u2.uid <> 39 WITH u2.uid AS uid, (CASE WHEN w.qty < h.qty THEN w.qty ELSE h.qty END) AS have RETURN uid, SUM(have) AS total ORDER BY total DESC SKIP 0 LIMIT 25 This UID has about 40k+ results that I want to be able to put a pagination to. The initial skip was around 773ms. I tried page 2 (skip 25) and the latency was around the same even up to page 500 it only rose up to 900ms so I didn't really bother. Now I tried some fast forward paging and jumped by thousands so I did 1000, then 2000, then 3000. I was hoping the ORDER BY arrangement will already have been cached by Neo4j and using SKIP will just move to that index in the result and wont have to iterate through each one again. But for each thousand skip I made the latency increased by alot. It's not just cache warming because for one I already warmed up the cache and two, I tried the same skip a couple of times for each skip and it yielded the same results: SKIP 0: 773ms SKIP 1000: 1369ms SKIP 2000: 2491ms SKIP 3000: 3899ms SKIP 4000: 5686ms SKIP 5000: 7424ms Now who the hell would want to view 5000 pages of results? 40k even?! :) Good point! I will probably put a cap on the maximum results a user can view but I was just curious about this phenomenon. Will somebody please explain why Neo4j seems to be re-iterating through stuff which appears to be already known to it? Here is my profiling for the 0 skip: ==> ColumnFilter(symKeys=["uid", " INTERNAL_AGGREGATE65c4d6a2-1930-4f32-8fd9-5e4399ce6f14"], returnItemNames=["uid", "total"], _rows=25, _db_hits=0) ==> Slice(skip="Literal(0)", _rows=25, _db_hits=0) ==> Top(orderBy=["SortItem(Cached( INTERNAL_AGGREGATE65c4d6a2-1930-4f32-8fd9-5e4399ce6f14 of type Any),false)"], limit="Add(Literal(0),Literal(25))", _rows=25, _db_hits=0) ==> EagerAggregation(keys=["uid"], aggregates=["( INTERNAL_AGGREGATE65c4d6a2-1930-4f32-8fd9-5e4399ce6f14,Sum(have))"], _rows=41659, _db_hits=0) ==> ColumnFilter(symKeys=["have", "u1", "uid", "c", "h", "w", "u2"], returnItemNames=["uid", "have"], _rows=146826, _db_hits=0) ==> Extract(symKeys=["u1", "c", "h", "w", "u2"], exprKeys=["uid", "have"], _rows=146826, _db_hits=587304) ==> Filter(pred="((NOT(Product(u2,uid(0),true) == Literal(39)) AND hasLabel(u1:user(0))) AND hasLabel(u2:user(0)))", _rows=146826, _db_hits=146826) ==> TraversalMatcher(trail="(u1)-[w:WANTS WHERE (hasLabel(NodeIdentifier():card(1)) AND hasLabel(NodeIdentifier():card(1))) AND true]->(c)<-[h:HAS WHERE (NOT(Product(NodeIdentifier(),uid(0),true) == Literal(39)) AND hasLabel(NodeIdentifier():user(0))) AND true]-(u2)", _rows=146826, _db_hits=293696) And for the 5000 skip: ==> ColumnFilter(symKeys=["uid", " INTERNAL_AGGREGATE99329ea5-03cd-4d53-a6bc-3ad554b47872"], returnItemNames=["uid", "total"], _rows=25, _db_hits=0) ==> Slice(skip="Literal(5000)", _rows=25, _db_hits=0) ==> Top(orderBy=["SortItem(Cached( INTERNAL_AGGREGATE99329ea5-03cd-4d53-a6bc-3ad554b47872 of type Any),false)"], limit="Add(Literal(5000),Literal(25))", _rows=5025, _db_hits=0) ==> EagerAggregation(keys=["uid"], aggregates=["( INTERNAL_AGGREGATE99329ea5-03cd-4d53-a6bc-3ad554b47872,Sum(have))"], _rows=41659, _db_hits=0) ==> ColumnFilter(symKeys=["have", "u1", "uid", "c", "h", "w", "u2"], returnItemNames=["uid", "have"], _rows=146826, _db_hits=0) ==> Extract(symKeys=["u1", "c", "h", "w", "u2"], exprKeys=["uid", "have"], _rows=146826, _db_hits=587304) ==> Filter(pred="((NOT(Product(u2,uid(0),true) == Literal(39)) AND hasLabel(u1:user(0))) AND hasLabel(u2:user(0)))", _rows=146826, _db_hits=146826) ==> TraversalMatcher(trail="(u1)-[w:WANTS WHERE (hasLabel(NodeIdentifier():card(1)) AND hasLabel(NodeIdentifier():card(1))) AND true]->(c)<-[h:HAS WHERE (NOT(Product(NodeIdentifier(),uid(0),true) == Literal(39)) AND hasLabel(NodeIdentifier():user(0))) AND true]-(u2)", _rows=146826, _db_hits=293696) The only difference is the LIMIT clause on the Top function. I hope we can make this work as intended, I really don't want to delve into doing an embedded Neo4j + my own Jetty REST API for the web app.

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  • Speed up SQL Server queries with PREFETCH

    - by Akshay Deep Lamba
    Problem The SAN data volume has a throughput capacity of 400MB/sec; however my query is still running slow and it is waiting on I/O (PAGEIOLATCH_SH). Windows Performance Monitor shows data volume speed of 4MB/sec. Where is the problem and how can I find the problem? Solution This is another summary of a great article published by R. Meyyappan at www.sqlworkshops.com.  In my opinion, this is the first article that highlights and explains with working examples how PREFETCH determines the performance of a Nested Loop join.  First of all, I just want to recall that Prefetch is a mechanism with which SQL Server can fire up many I/O requests in parallel for a Nested Loop join. When SQL Server executes a Nested Loop join, it may or may not enable Prefetch accordingly to the number of rows in the outer table. If the number of rows in the outer table is greater than 25 then SQL will enable and use Prefetch to speed up query performance, but it will not if it is less than 25 rows. In this section we are going to see different scenarios where prefetch is automatically enabled or disabled. These examples only use two tables RegionalOrder and Orders.  If you want to create the sample tables and sample data, please visit this site www.sqlworkshops.com. The breakdown of the data in the RegionalOrders table is shown below and the Orders table contains about 6 million rows. In this first example, I am creating a stored procedure against two tables and then execute the stored procedure.  Before running the stored proceudre, I am going to include the actual execution plan. --Example provided by www.sqlworkshops.com --Create procedure that pulls orders based on City --Do not forget to include the actual execution plan CREATE PROC RegionalOrdersProc @City CHAR(20) AS BEGIN DECLARE @OrderID INT, @OrderDetails CHAR(200) SELECT @OrderID = o.OrderID, @OrderDetails = o.OrderDetails       FROM RegionalOrders ao INNER JOIN Orders o ON (o.OrderID = ao.OrderID)       WHERE City = @City END GO SET STATISTICS time ON GO --Example provided by www.sqlworkshops.com --Execute the procedure with parameter SmallCity1 EXEC RegionalOrdersProc 'SmallCity1' GO After running the stored procedure, if we right click on the Clustered Index Scan and click Properties we can see the Estimated Numbers of Rows is 24.    If we right click on Nested Loops and click Properties we do not see Prefetch, because it is disabled. This behavior was expected, because the number of rows containing the value ‘SmallCity1’ in the outer table is less than 25.   Now, if I run the same procedure with parameter ‘BigCity’ will Prefetch be enabled? --Example provided by www.sqlworkshops.com --Execute the procedure with parameter BigCity --We are using cached plan EXEC RegionalOrdersProc 'BigCity' GO As we can see from the below screenshot, prefetch is not enabled and the query takes around 7 seconds to execute. This is because the query used the cached plan from ‘SmallCity1’ that had prefetch disabled. Please note that even if we have 999 rows for ‘BigCity’ the Estimated Numbers of Rows is still 24.   Finally, let’s clear the procedure cache to trigger a new optimization and execute the procedure again. DBCC freeproccache GO EXEC RegionalOrdersProc 'BigCity' GO This time, our procedure runs under a second, Prefetch is enabled and the Estimated Number of Rows is 999.   The RegionalOrdersProc can be optimized by using the below example where we are using an optimizer hint. I have also shown some other hints that could be used as well. --Example provided by www.sqlworkshops.com --You can fix the issue by using any of the following --hints --Create procedure that pulls orders based on City DROP PROC RegionalOrdersProc GO CREATE PROC RegionalOrdersProc @City CHAR(20) AS BEGIN DECLARE @OrderID INT, @OrderDetails CHAR(200) SELECT @OrderID = o.OrderID, @OrderDetails = o.OrderDetails       FROM RegionalOrders ao INNER JOIN Orders o ON (o.OrderID = ao.OrderID)       WHERE City = @City       --Hinting optimizer to use SmallCity2 for estimation       OPTION (optimize FOR (@City = 'SmallCity2'))       --Hinting optimizer to estimate for the currnet parameters       --option (recompile)       --Hinting optimize not to use histogram rather       --density for estimation (average of all 3 cities)       --option (optimize for (@City UNKNOWN))       --option (optimize for UNKNOWN) END GO Conclusion, this tip was mainly aimed at illustrating how Prefetch can speed up query execution and how the different number of rows can trigger this.

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  • July, the 31 Days of SQL Server DMO’s – Day 19 (sys.dm_exec_query_stats)

    - by Tamarick Hill
    The sys.dm_exec_query_stats DMV is one of the most useful DMV’s out there when it comes to performance tuning. If you have been keeping up with this blog series this month, you know that I started out on Day 1 reviewing many of the DMV’s within the ‘exec’ namespace. I’m not sure how I missed this one considering how valuable it is, but hey, they say it’s better late than never right?? On Day 7 and Day 8 we reviewed the sys.dm_exec_procedure_stats and sys.dm_exec_trigger_stats respectively. This sys.dm_exec_query_stats DMV is very similar to these two. As a matter of fact, this DMV will return all of the information you saw in the other two DMV’s, but in addition to that, you can see stats for all queries that have cached execution plans on your server. You can even see stats for statements that are ran Ad-Hoc as long as they are still cached in the buffer pool. To better illustrate this DMV, let have a quick look at it: SELECT * FROM sys.dm_exec_query_stats As you can see, there is a lot of information returned from this DMV. I wont go into detail about each and every one of these columns, but I will touch on a few of them briefly. The first column is the ‘sql_handle’, which if you remember from Day 4 of our blog series, I explained how you can use this column to extract the actual SQL text that was executed. The next columns statement_start_offset and statement_end_offset provide you a way of extracting the exact SQL statement that was executed as part of a batch. The plan_handle column is used to extract the Execution plan that was used, which we talked about during Day 5 of this blog series. Later in the result set, you have columns to identify how many times a particular statement was executed, how much CPU time it used, how many reads/writes it performed, the duration, how many rows were returned, etc. These columns provide you with a solid avenue to begin your performance optimization. The last column I will touch on is the query_plan_hash column. A lot of times when you have Dynamic SQL running on your server, you have similar statements with different parameter values being passed in. Many times these types of statements will get similar execution plans and then a Binary hash value can be generated based on these similar plans. This query plan hash can be used to find the cost of all queries that have similar execution plans and then you can tune based on that plan to improve the performance of all of the individual queries. This is a very powerful way of identifying and tuning Ad-hoc statements that run on your server. As I stated earlier, this sys.dm_exec_query_stats DMV is a very powerful and recommended DMV for performance tuning. You are able to quickly identify statements that are running on your server and analyze their impact on system resources. Using this DMV to track down the biggest performance killers on your server will allow you to make the biggest gains once you focus your tuning efforts on those top offenders. For more information about this DMV, please see the below Books Online link: http://msdn.microsoft.com/en-us/library/ms189741.aspx Follow me on Twitter @PrimeTimeDBA

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  • A quick look at: sys.dm_os_buffer_descriptors

    - by Jonathan Allen
    SQL Server places data into cache as it reads it from disk so as to speed up future queries. This dmv lets you see how much data is cached at any given time and knowing how this changes over time can help you ensure your servers run smoothly and are adequately resourced to run your systems. This dmv gives the number of cached pages in the buffer pool along with the database id that they relate to: USE [tempdb] GO SELECT COUNT(*) AS cached_pages_count , CASE database_id WHEN 32767 THEN 'ResourceDb' ELSE DB_NAME(database_id) END AS Database_name FROM sys.dm_os_buffer_descriptors GROUP BY DB_NAME(database_id) , database_id ORDER BY cached_pages_count DESC; This gives you results which are quite useful, but if you add a new column with the code: …to convert the pages value to show a MB value then they become more relevant and meaningful. To see how your server reacts to queries, start up SSMS and connect to a test server and database – mine is called AdventureWorks2008. Make sure you start from a know position by running: -- Only run this on a test server otherwise your production server's-- performance may drop off a cliff and your phone will start ringing. DBCC DROPCLEANBUFFERS GO Now we can run a query that would normally turn a DBA’s hair white: USE [AdventureWorks2008] go SELECT * FROM [Sales].[SalesOrderDetail] AS sod INNER JOIN [Sales].[SalesOrderHeader] AS soh ON [sod].[SalesOrderID] = [soh].[SalesOrderID] …and then check our cache situation: A nice low figure – not! Almost 2000 pages of data in cache equating to approximately 15MB. Luckily these tables are quite narrow; if this had been on a table with more columns then this could be even more dramatic. So, let’s make our query more efficient. After resetting the cache with the DROPCLEANBUFFERS and FREEPROCCACHE code above, we’ll only select the columns we want and implement a WHERE predicate to limit the rows to a specific customer. SELECT [sod].[OrderQty] , [sod].[ProductID] , [soh].[OrderDate] , [soh].[CustomerID] FROM [Sales].[SalesOrderDetail] AS sod INNER JOIN [Sales].[SalesOrderHeader] AS soh ON [sod].[SalesOrderID] = [soh].[SalesOrderID] WHERE [soh].[CustomerID] = 29722 …and check our effect cache: Now that is more sympathetic to our server and the other systems sharing its resources. I can hear you asking: “What has this got to do with logging, Jonathan?” Well, a smart DBA will keep an eye on this metric on their servers so they know how their hardware is coping and be ready to investigate anomalies so that no ‘disruptive’ code starts to unsettle things. Capturing this information over a period of time can lead you to build a picture of how a database relies on the cache and how it interacts with other databases. This might allow you to decide on appropriate schedules for over night jobs or otherwise balance the work of your server. You could schedule this job to run with a SQL Agent job and store the data in your DBA’s database by creating a table with: IF OBJECT_ID('CachedPages') IS NOT NULL DROP TABLE CachedPages CREATE TABLE CachedPages ( cached_pages_count INT , MB INT , Database_Name VARCHAR(256) , CollectedOn DATETIME DEFAULT GETDATE() ) …and then filling it with: INSERT INTO [dbo].[CachedPages] ( [cached_pages_count] , [MB] , [Database_Name] ) SELECT COUNT(*) AS cached_pages_count , ( COUNT(*) * 8.0 ) / 1024 AS MB , CASE database_id WHEN 32767 THEN 'ResourceDb' ELSE DB_NAME(database_id) END AS Database_name FROM sys.dm_os_buffer_descriptors GROUP BY database_id After this has been left logging your system metrics for a while you can easily see how your databases use the cache over time and may see some spikes that warrant your attention. This sort of logging can be applied to all sorts of server statistics so that you can gather information that will give you baseline data on how your servers are performing. This means that when you get a problem you can see what statistics are out of their normal range and target you efforts to resolve the issue more rapidly.

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  • Adding Output Caching and Expire Header in IIS7 to improve performance

    - by Renso
    The problem: Images and other static files will not be cached unless you tell it to. In IIS7 it is remarkably easy to do this. Web pages are becoming increasingly complex with more scripts, style sheets, images, and Flash on them. A first-time visit to a page may require several HTTP requests to load all the components. By using Expires headers these components become cacheable, which avoids unnecessary HTTP requests on subsequent page views. Expires headers are most often associated with images, but they can and should be used on all page components including scripts, style sheets, and Flash. Every time a page is loaded, every image and other static content like JavaScript files and CSS files will be reloaded on every page request. If the content does not change frequently why not cache it and avoid the network traffic?! The solution: In IIS7 there are two ways to cache content, using the web.config file to set caching for all static content, and in IIS7 itself setting aching by file extension that gives you that extra level of granularity. Web.config: In IIS7, Expires Headers can be enabled in the system.webServer section of the web.config file:   <staticContent>     <clientCache cacheControlMode="UseMaxAge" cacheControlMaxAge="1.00:00:00" />   </staticContent> In the above example a cache expiration of 1 day was added. It will be a full day before the content is downloaded from the web server again. To expire the content on a specific date:   <staticContent>     <clientCache cacheControlMode="UseExpires" httpExpires="Sun, 31 Dec 2011 23:59:59 UTC" />   </staticContent> This will expire the content on December 31st 2011 one second before midnight. Issues/Challenges: Once the file has been set to be cached it wont be updated on the user's browser for the set cache expiration. So be careful here with content that may change frequently, like during development. Typically in development you don't want to cache at all for testing purposes. You could also suffix files with timestamp or versions to force a reload into the user's browser cache. IIS7 Expire Web Content Open up your web app in IIS. Open up the sub-folders until you find the folder or file you want to ad an expiration date to. In IIS6 you used to right-click and select properties, no such luck in IIS7, double click HTTP Response. Once the window loads for the HTTP Response Headers, look to the Actions navigation bar to the right, all the way at the top select SET COMMON HEADERS. The Enable HTTP keep-alive will already be pre-selected. Go ahead and add the appropriate expiration header to the file or folder. Note that if you selected a folder, it will apply that setting to all images inside that folder and all nested content, even subfolders. So, two approaches, depending on what level or granularity you need.

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  • NHibernate Pitfalls: Custom Types and Detecting Changes

    - by Ricardo Peres
    This is part of a series of posts about NHibernate Pitfalls. See the entire collection here. NHibernate supports the declaration of properties of user-defined types, that is, not entities, collections or primitive types. These are used for mapping a database columns, of any type, into a different type, which may not even be an entity; think, for example, of a custom user type that converts a BLOB column into an Image. User types must implement interface NHibernate.UserTypes.IUserType. This interface specifies an Equals method that is used for comparing two instances of the user type. If this method returns false, the entity is marked as dirty, and, when the session is flushed, will trigger an UPDATE. So, in your custom user type, you must implement this carefully so that it is not mistakenly considered changed. For example, you can cache the original column value inside of it, and compare it with the one in the other instance. Let’s see an example implementation of a custom user type that converts a Byte[] from a BLOB column into an Image: 1: [Serializable] 2: public sealed class ImageUserType : IUserType 3: { 4: private Byte[] data = null; 5: 6: public ImageUserType() 7: { 8: this.ImageFormat = ImageFormat.Png; 9: } 10: 11: public ImageFormat ImageFormat 12: { 13: get; 14: set; 15: } 16: 17: public Boolean IsMutable 18: { 19: get 20: { 21: return (true); 22: } 23: } 24: 25: public Object Assemble(Object cached, Object owner) 26: { 27: return (cached); 28: } 29: 30: public Object DeepCopy(Object value) 31: { 32: return (value); 33: } 34: 35: public Object Disassemble(Object value) 36: { 37: return (value); 38: } 39: 40: public new Boolean Equals(Object x, Object y) 41: { 42: return (Object.Equals(x, y)); 43: } 44: 45: public Int32 GetHashCode(Object x) 46: { 47: return ((x != null) ? x.GetHashCode() : 0); 48: } 49: 50: public override Int32 GetHashCode() 51: { 52: return ((this.data != null) ? this.data.GetHashCode() : 0); 53: } 54: 55: public override Boolean Equals(Object obj) 56: { 57: ImageUserType other = obj as ImageUserType; 58: 59: if (other == null) 60: { 61: return (false); 62: } 63: 64: if (Object.ReferenceEquals(this, other) == true) 65: { 66: return (true); 67: } 68: 69: return (this.data.SequenceEqual(other.data)); 70: } 71: 72: public Object NullSafeGet(IDataReader rs, String[] names, Object owner) 73: { 74: Int32 index = rs.GetOrdinal(names[0]); 75: Byte[] data = rs.GetValue(index) as Byte[]; 76: 77: this.data = data as Byte[]; 78: 79: if (data == null) 80: { 81: return (null); 82: } 83: 84: using (MemoryStream stream = new MemoryStream(this.data ?? new Byte[0])) 85: { 86: return (Image.FromStream(stream)); 87: } 88: } 89: 90: public void NullSafeSet(IDbCommand cmd, Object value, Int32 index) 91: { 92: if (value != null) 93: { 94: Image data = value as Image; 95: 96: using (MemoryStream stream = new MemoryStream()) 97: { 98: data.Save(stream, this.ImageFormat); 99: value = stream.ToArray(); 100: } 101: } 102: 103: (cmd.Parameters[index] as DbParameter).Value = value ?? DBNull.Value; 104: } 105: 106: public Object Replace(Object original, Object target, Object owner) 107: { 108: return (original); 109: } 110: 111: public Type ReturnedType 112: { 113: get 114: { 115: return (typeof(Image)); 116: } 117: } 118: 119: public SqlType[] SqlTypes 120: { 121: get 122: { 123: return (new SqlType[] { new SqlType(DbType.Binary) }); 124: } 125: } 126: } In this case, we need to cache the original Byte[] data because it’s not easy to compare two Image instances, unless, of course, they are the same.

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  • WCF ChannelFactory caching

    - by Myles J
    I've just read this great article on WCF ChannelFactory caching by Wenlong Dong. My question is simply how can you actually prove that the ChannelFactory is in fact being cached between calls? I've followed the rules regarding the ClientBase’s constructors. We are using the following overloaded constructor on our object that inherits from ClientBase: ClientBase(string endpointConfigurationName, EndpointAddress remoteAddress); In the article mentioned above it is stated that: For these constructors, all arguments (including default ones) are in the following list: · InstanceContext callbackInstance · string endpointConfigurationName · EndpointAddress remoteAddress As long as these three arguments are the same when ClientBase is constructed, we can safely assume that the same ChannelFactory can be used. Fortunately, String and EndpointAddress types are immutable, i.e., we can make simple comparison to determine whether two arguments are the same. For InstanceContext, we can use Object reference comparison. The type EndpointTrait is thus used as the key of the MRU cache. To test the ChannelFactory cache theory we are checking the Hashcode in the ClientBase constructor e.g. var testHash = RuntimeHelpers.GetHashCode(base.ChannelFactory); The hash value is different between calls which makes us think that the ChannelFactory isn't actually cached. Any thoughts? Regards Myles

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  • solution for RPC_E_ATTEMPTED_MULTITHREAD error caused by SPRequestContext caching SPSites?

    - by kerray
    Hi, I'm developing a solution for SharePoint 2007, and I'm using SPSecurity.RunWithElevatedPrivileges a lot, passing in UserToken of the SystemAccount. After reading http://hristopavlov.wordpress.com/2009/01/19/understanding-sharepoint-sprequest/ I finally began to understand why I get these System.Runtime.InteropServices.COMException (0x80010102): Attempted to make calls on more than one thread in single threaded mode. (Exception from HRESULT: 0x80010102 (RPC_E_ATTEMPTED_MULTITHREAD)) errors, but there seems to be no solution - "known issue in the product" The article is more then a year old. I wasn't able to find anything more recent and helpful, but I was hoping maybe someone else has? My code goes like this SPSecurity.RunWithElevatedPrivileges(delegate() { using (SPSite elevatedSite = new SPSite(web.Site.ID, web.Site.SystemAccount.UserToken)) { using (SPWeb elevatedWeb = elevatedSite.OpenWeb(web.ID)) { // some operations on lists and items obtained through elevatedWeb } } } The errors come up wherever such an elevated code is used, and more often when there are more users who use these functionalities, so I guess perhaps the elevated SPSite is getting cached and reused. Is there any way to solve this? If my understanding is correct, how to make Sharepoint forget about the cached SPSites, and use a fresh one instead? Thanks

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