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  • Problems with Program startup in WIn 7 this week

    - by PyNEwbie
    I have a program (ISYS) that I have been using since 2006. It migrated successfully to Windows 7. Just yesterday it started manifesting this strange behavior. The program has a selector to allow you to select a directory that might have relevant files for the program. As of yesterday the program will only let me select folders on the C drive. For example I have a folder on D that I need to access with this program - from the GUI when I select the D drive the directory list does not load, instead it churns away using 17% of the CPU cycles. I have let it run for an hour several times. I have found that I can get the directory I want by using a batch file to start the program but this limits my ability to do certain things I really need to use the GUI. I did a number of reboots and other tests - I disconnected drives but once I try to select some directory on a drive other than C it churns away. I have experimented quite a bit and am convinced (which means I am wrong) that this has something to do with some setting change on my computer that I can't figure out as I don't see any updates. Since ISYS has not been updated I feel confident it is something internal. Any suggestions would be appreciated.

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  • Apache mod_disk_cache on a seperate drive

    - by pavs
    how can I set Apache mod_disk_cache on a separate drive from where the OS/Apache is installed? I have set up this on my apache2.conf: <IfModule mod_cache_disk.c> # cache cleaning is done by htcacheclean, which can be configured in # /etc/default/apache2 # # For further information, see the comments in that file, # /usr/share/doc/apache2/README.Debian, and the htcacheclean(8) # man page. # This path must be the same as the one in /etc/default/apache2 CacheRoot /media/cacheHD # This will also cache local documents. It usually makes more sense to # put this into the configuration for just one virtual host. CacheEnable disk / # The result of CacheDirLevels * CacheDirLength must not be higher than # 20. Moreover, pay attention on file system limits. Some file systems # do not support more than a certain number of inodes and # subdirectories (e.g. 32000 for ext3) CacheDirLevels 2 CacheDirLength 1 </IfModule> and it doesn't seem to be caching anything at all. The drive itself is a freshly installed ssd drive formatted with ext4.

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  • FreeBSD performance tuning. Sysctls, loader.conf, kernel

    - by SaveTheRbtz
    I wanted to share knowledge of tuning FreeBSD via sysctl.conf/loader.conf/KENCONF. It was initially based on Igor Sysoev's (author of nginx) presentation about FreeBSD tuning up to 100,000-200,000 active connections. Tunings are for FreeBSD-CURRENT. Since 7.2 amd64 some of them are tuned well by default. Prior 7.0 some of them are boot only (set via /boot/loader.conf) or does not exist at all. sysctl.conf: # No zero mapping feature # May break wine # (There are also reports about broken samba3) #security.bsd.map_at_zero=0 # If you have really busy webserver with apache13 you may run out of processes #kern.maxproc=10000 # Same for servers with apache2 / Pound #kern.threads.max_threads_per_proc=4096 # Max. backlog size kern.ipc.somaxconn=4096 # Shared memory // 7.2+ can use shared memory > 2Gb kern.ipc.shmmax=2147483648 # Sockets kern.ipc.maxsockets=204800 # Can cause this on older kernels: # http://old.nabble.com/Significant-performance-regression-for-increased-maxsockbuf-on-8.0-RELEASE-tt26745981.html#a26745981 ) kern.ipc.maxsockbuf=10485760 # Mbuf 2k clusters (on amd64 7.2+ 25600 is default) # For such high value vm.kmem_size must be increased to 3G kern.ipc.nmbclusters=262144 # Jumbo pagesize(_SC_PAGESIZE) clusters # Used as general packet storage for jumbo frames # can be monitored via `netstat -m` #kern.ipc.nmbjumbop=262144 # Jumbo 9k/16k clusters # If you are using them #kern.ipc.nmbjumbo9=65536 #kern.ipc.nmbjumbo16=32768 # For lower latency you can decrease scheduler's maximum time slice # default: stathz/10 (~ 13) #kern.sched.slice=1 # Increase max command-line length showed in `ps` (e.g for Tomcat/Java) # Default is PAGE_SIZE / 16 or 256 on x86 # This avoids commands to be presented as [executable] in `ps` # For more info see: http://www.freebsd.org/cgi/query-pr.cgi?pr=120749 kern.ps_arg_cache_limit=4096 # Every socket is a file, so increase them kern.maxfiles=204800 kern.maxfilesperproc=200000 kern.maxvnodes=200000 # On some systems HPET is almost 2 times faster than default ACPI-fast # Useful on systems with lots of clock_gettime / gettimeofday calls # See http://old.nabble.com/ACPI-fast-default-timecounter,-but-HPET-83--faster-td23248172.html # After revision 222222 HPET became default: http://svnweb.freebsd.org/base?view=revision&revision=222222 kern.timecounter.hardware=HPET # Small receive space, only usable on http-server, on file server this # should be increased to 65535 or even more #net.inet.tcp.recvspace=8192 # This is useful on Fat-Long-Pipes #net.inet.tcp.recvbuf_max=10485760 #net.inet.tcp.recvbuf_inc=65535 # Small send space is useful for http servers that serve small files # Autotuned since 7.x net.inet.tcp.sendspace=16384 # This is useful on Fat-Long-Pipes #net.inet.tcp.sendbuf_max=10485760 #net.inet.tcp.sendbuf_inc=65535 # Turn off receive autotuning # You can play with it. #net.inet.tcp.recvbuf_auto=0 #net.inet.tcp.sendbuf_auto=0 # This should be enabled if you going to use big spaces (>64k) # Also timestamp field is useful when using syncookies net.inet.tcp.rfc1323=1 # Turn this off on high-speed, lossless connections (LAN 1Gbit+) # If you set it there is no need in TCP_NODELAY sockopt (see man tcp) net.inet.tcp.delayed_ack=0 # This feature is useful if you are serving data over modems, Gigabit Ethernet, # or even high speed WAN links (or any other link with a high bandwidth delay product), # especially if you are also using window scaling or have configured a large send window. # Automatically disables on small RTT ( http://www.freebsd.org/cgi/cvsweb.cgi/src/sys/netinet/tcp_subr.c?#rev1.237 ) # This sysctl was removed in 10-CURRENT: # See: http://www.mail-archive.com/[email protected]/msg06178.html #net.inet.tcp.inflight.enable=0 # TCP slowstart algorithm tunings # We assuming we have very fast clients #net.inet.tcp.slowstart_flightsize=100 #net.inet.tcp.local_slowstart_flightsize=100 # Disable randomizing of ports to avoid false RST # Before usage check SA here www.bsdcan.org/2006/papers/ImprovingTCPIP.pdf # (it's also says that port randomization auto-disables at some conn.rates, but I didn't checked it thou) #net.inet.ip.portrange.randomized=0 # Increase portrange # For outgoing connections only. Good for seed-boxes and ftp servers. net.inet.ip.portrange.first=1024 net.inet.ip.portrange.last=65535 # # stops route cache degregation during a high-bandwidth flood # http://www.freebsd.org/doc/en/books/handbook/securing-freebsd.html #net.inet.ip.rtexpire=2 net.inet.ip.rtminexpire=2 net.inet.ip.rtmaxcache=1024 # Security net.inet.ip.redirect=0 net.inet.ip.sourceroute=0 net.inet.ip.accept_sourceroute=0 net.inet.icmp.maskrepl=0 net.inet.icmp.log_redirect=0 net.inet.icmp.drop_redirect=1 net.inet.tcp.drop_synfin=1 # # There is also good example of sysctl.conf with comments: # http://www.thern.org/projects/sysctl.conf # # icmp may NOT rst, helpful for those pesky spoofed # icmp/udp floods that end up taking up your outgoing # bandwidth/ifqueue due to all that outgoing RST traffic. # #net.inet.tcp.icmp_may_rst=0 # Security net.inet.udp.blackhole=1 net.inet.tcp.blackhole=2 # IPv6 Security # For more info see http://www.fosslc.org/drupal/content/security-implications-ipv6 # Disable Node info replies # To see this vulnerability in action run `ping6 -a sglAac ::1` or `ping6 -w ::1` on unprotected node net.inet6.icmp6.nodeinfo=0 # Turn on IPv6 privacy extensions # For more info see proposal http://unix.derkeiler.com/Mailing-Lists/FreeBSD/net/2008-06/msg00103.html net.inet6.ip6.use_tempaddr=1 net.inet6.ip6.prefer_tempaddr=1 # Disable ICMP redirect net.inet6.icmp6.rediraccept=0 # Disable acceptation of RA and auto linklocal generation if you don't use them #net.inet6.ip6.accept_rtadv=0 #net.inet6.ip6.auto_linklocal=0 # Increases default TTL, sometimes useful # Default is 64 net.inet.ip.ttl=128 # Lessen max segment life to conserve resources # ACK waiting time in miliseconds # (default: 30000. RFC from 1979 recommends 120000) net.inet.tcp.msl=5000 # Max bumber of timewait sockets net.inet.tcp.maxtcptw=200000 # Don't use tw on local connections # As of 15 Apr 2009. Igor Sysoev says that nolocaltimewait has some buggy realization. # So disable it or now till get fixed #net.inet.tcp.nolocaltimewait=1 # FIN_WAIT_2 state fast recycle net.inet.tcp.fast_finwait2_recycle=1 # Time before tcp keepalive probe is sent # default is 2 hours (7200000) #net.inet.tcp.keepidle=60000 # Should be increased until net.inet.ip.intr_queue_drops is zero net.inet.ip.intr_queue_maxlen=4096 # Interrupt handling via multiple CPU, but with context switch. # You can play with it. Default is 1; #net.isr.direct=0 # This is for routers only #net.inet.ip.forwarding=1 #net.inet.ip.fastforwarding=1 # This speed ups dummynet when channel isn't saturated net.inet.ip.dummynet.io_fast=1 # Increase dummynet(4) hash #net.inet.ip.dummynet.hash_size=2048 #net.inet.ip.dummynet.max_chain_len # Should be increased when you have A LOT of files on server # (Increase until vfs.ufs.dirhash_mem becomes lower) vfs.ufs.dirhash_maxmem=67108864 # Note from commit http://svn.freebsd.org/base/head@211031 : # For systems with RAID volumes and/or virtualization envirnments, where # read performance is very important, increasing this sysctl tunable to 32 # or even more will demonstratively yield additional performance benefits. vfs.read_max=32 # Explicit Congestion Notification (see http://en.wikipedia.org/wiki/Explicit_Congestion_Notification) net.inet.tcp.ecn.enable=1 # Flowtable - flow caching mechanism # Useful for routers #net.inet.flowtable.enable=1 #net.inet.flowtable.nmbflows=65535 # Extreme polling tuning #kern.polling.burst_max=1000 #kern.polling.each_burst=1000 #kern.polling.reg_frac=100 #kern.polling.user_frac=1 #kern.polling.idle_poll=0 # IPFW dynamic rules and timeouts tuning # Increase dyn_buckets till net.inet.ip.fw.curr_dyn_buckets is lower net.inet.ip.fw.dyn_buckets=65536 net.inet.ip.fw.dyn_max=65536 net.inet.ip.fw.dyn_ack_lifetime=120 net.inet.ip.fw.dyn_syn_lifetime=10 net.inet.ip.fw.dyn_fin_lifetime=2 net.inet.ip.fw.dyn_short_lifetime=10 # Make packets pass firewall only once when using dummynet # i.e. packets going thru pipe are passing out from firewall with accept #net.inet.ip.fw.one_pass=1 # shm_use_phys Wires all shared pages, making them unswappable # Use this to lessen Virtual Memory Manager's work when using Shared Mem. # Useful for databases #kern.ipc.shm_use_phys=1 # ZFS # Enable prefetch. Useful for sequential load type i.e fileserver. # FreeBSD sets vfs.zfs.prefetch_disable to 1 on any i386 systems and # on any amd64 systems with less than 4GB of avaiable memory # For additional info check this nabble thread http://old.nabble.com/Samba-read-speed-performance-tuning-td27964534.html #vfs.zfs.prefetch_disable=0 # On highload servers you may notice following message in dmesg: # "Approaching the limit on PV entries, consider increasing either the # vm.pmap.shpgperproc or the vm.pmap.pv_entry_max tunable" vm.pmap.shpgperproc=2048 loader.conf: # Accept filters for data, http and DNS requests # Useful when your software uses select() instead of kevent/kqueue or when you under DDoS # DNS accf available on 8.0+ accf_data_load="YES" accf_http_load="YES" accf_dns_load="YES" # Async IO system calls aio_load="YES" # Linux specific devices in /dev # As for 8.1 it only /dev/full #lindev_load="YES" # Adds NCQ support in FreeBSD # WARNING! all ad[0-9]+ devices will be renamed to ada[0-9]+ # 8.0+ only #ahci_load="YES" #siis_load="YES" # FreeBSD 8.2+ # New Congestion Control for FreeBSD # http://caia.swin.edu.au/urp/newtcp/tools/cc_chd-readme-0.1.txt # http://www.ietf.org/proceedings/78/slides/iccrg-5.pdf # Initial merge commit message http://www.mail-archive.com/[email protected]/msg31410.html #cc_chd_load="YES" # Increase kernel memory size to 3G. # # Use ONLY if you have KVA_PAGES in kernel configuration, and you have more than 3G RAM # Otherwise panic will happen on next reboot! # # It's required for high buffer sizes: kern.ipc.nmbjumbop, kern.ipc.nmbclusters, etc # Useful on highload stateful firewalls, proxies or ZFS fileservers # (FreeBSD 7.2+ amd64 users: Check that current value is lower!) #vm.kmem_size="3G" # If your server has lots of swap (>4Gb) you should increase following value # according to http://lists.freebsd.org/pipermail/freebsd-hackers/2009-October/029616.html # Otherwise you'll be getting errors # "kernel: swap zone exhausted, increase kern.maxswzone" # kern.maxswzone="256M" # Older versions of FreeBSD can't tune maxfiles on the fly #kern.maxfiles="200000" # Useful for databases # Sets maximum data size to 1G # (FreeBSD 7.2+ amd64 users: Check that current value is lower!) #kern.maxdsiz="1G" # Maximum buffer size(vfs.maxbufspace) # You can check current one via vfs.bufspace # Should be lowered/upped depending on server's load-type # Usually decreased to preserve kmem # (default is 10% of mem) #kern.maxbcache="512M" # Sendfile buffers # For i386 only #kern.ipc.nsfbufs=10240 # FreeBSD 9+ # HPET "legacy route" support. It should allow HPET to work per-CPU # See http://www.mail-archive.com/[email protected]/msg03603.html #hint.atrtc.0.clock=0 #hint.attimer.0.clock=0 #hint.hpet.0.legacy_route=1 # syncache Hash table tuning net.inet.tcp.syncache.hashsize=1024 net.inet.tcp.syncache.bucketlimit=512 net.inet.tcp.syncache.cachelimit=65536 # Increased hostcache # Later host cache can be viewed via net.inet.tcp.hostcache.list hidden sysctl # Very useful for it's RTT RTTVAR # Must be power of two net.inet.tcp.hostcache.hashsize=65536 # hashsize * bucketlimit (which is 30 by default) # It allocates 255Mb (1966080*136) of RAM net.inet.tcp.hostcache.cachelimit=1966080 # TCP control-block Hash table tuning net.inet.tcp.tcbhashsize=4096 # Disable ipfw deny all # Should be uncommented when there is a chance that # kernel and ipfw binary may be out-of sync on next reboot #net.inet.ip.fw.default_to_accept=1 # # SIFTR (Statistical Information For TCP Research) is a kernel module that # logs a range of statistics on active TCP connections to a log file. # See prerelease notes http://groups.google.com/group/mailing.freebsd.current/browse_thread/thread/b4c18be6cdce76e4 # and man 4 sitfr #siftr_load="YES" # Enable superpages, for 7.2+ only # Also read http://lists.freebsd.org/pipermail/freebsd-hackers/2009-November/030094.html vm.pmap.pg_ps_enabled=1 # Usefull if you are using Intel-Gigabit NIC #hw.em.rxd=4096 #hw.em.txd=4096 #hw.em.rx_process_limit="-1" # Also if you have ALOT interrupts on NIC - play with following parameters # NOTE: You should set them for every NIC #dev.em.0.rx_int_delay: 250 #dev.em.0.tx_int_delay: 250 #dev.em.0.rx_abs_int_delay: 250 #dev.em.0.tx_abs_int_delay: 250 # There is also multithreaded version of em/igb drivers can be found here: # http://people.yandex-team.ru/~wawa/ # # for additional em monitoring and statistics use # sysctl dev.em.0.stats=1 ; dmesg # sysctl dev.em.0.debug=1 ; dmesg # Also after r209242 (-CURRENT) there is a separate sysctl for each stat variable; # Same tunings for igb #hw.igb.rxd=4096 #hw.igb.txd=4096 #hw.igb.rx_process_limit=100 # Some useful netisr tunables. See sysctl net.isr #net.isr.maxthreads=4 #net.isr.defaultqlimit=4096 #net.isr.maxqlimit: 10240 # Bind netisr threads to CPUs #net.isr.bindthreads=1 # # FreeBSD 9.x+ # Increase interface send queue length # See commit message http://svn.freebsd.org/viewvc/base?view=revision&revision=207554 #net.link.ifqmaxlen=1024 # Nicer boot logo =) loader_logo="beastie" And finally here is KERNCONF: # Just some of them, see also # cat /sys/{i386,amd64,}/conf/NOTES # This one useful only on i386 #options KVA_PAGES=512 # You can play with HZ in environments with high interrupt rate (default is 1000) # 100 is for my notebook to prolong it's battery life #options HZ=100 # Polling is goot on network loads with high packet rates and low-end NICs # NB! Do not enable it if you want more than one netisr thread #options DEVICE_POLLING # Eliminate datacopy on socket read-write # To take advantage with zero copy sockets you should have an MTU >= 4k # This req. is only for receiving data. # Read more in man zero_copy_sockets # Also this epic thread on kernel trap: # http://kerneltrap.org/node/6506 # Here Linus says that "anybody that does it that way (FreeBSD) is totally incompetent" #options ZERO_COPY_SOCKETS # Support TCP sign. Used for IPSec options TCP_SIGNATURE # There was stackoverflow found in KAME IPSec stack: # See http://secunia.com/advisories/43995/ # For quick workaround you can use `ipfw add deny proto ipcomp` options IPSEC # This ones can be loaded as modules. They described in loader.conf section #options ACCEPT_FILTER_DATA #options ACCEPT_FILTER_HTTP # Adding ipfw, also can be loaded as modules options IPFIREWALL # On 8.1+ you can disable verbose to see blocked packets on ipfw0 interface. # Also there is no point in compiling verbose into the kernel, because # now there is net.inet.ip.fw.verbose tunable. #options IPFIREWALL_VERBOSE #options IPFIREWALL_VERBOSE_LIMIT=10 options IPFIREWALL_FORWARD # Adding kernel NAT options IPFIREWALL_NAT options LIBALIAS # Traffic shaping options DUMMYNET # Divert, i.e. for userspace NAT options IPDIVERT # This is for OpenBSD's pf firewall device pf device pflog # pf's QoS - ALTQ options ALTQ options ALTQ_CBQ # Class Bases Queuing (CBQ) options ALTQ_RED # Random Early Detection (RED) options ALTQ_RIO # RED In/Out options ALTQ_HFSC # Hierarchical Packet Scheduler (HFSC) options ALTQ_PRIQ # Priority Queuing (PRIQ) options ALTQ_NOPCC # Required for SMP build # Pretty console # Manual can be found here http://forums.freebsd.org/showthread.php?t=6134 #options VESA #options SC_PIXEL_MODE # Disable reboot on Ctrl Alt Del #options SC_DISABLE_REBOOT # Change normal|kernel messages color options SC_NORM_ATTR=(FG_GREEN|BG_BLACK) options SC_KERNEL_CONS_ATTR=(FG_YELLOW|BG_BLACK) # More scroll space options SC_HISTORY_SIZE=8192 # Adding hardware crypto device device crypto device cryptodev # Useful network interfaces device vlan device tap #Virtual Ethernet driver device gre #IP over IP tunneling device if_bridge #Bridge interface device pfsync #synchronization interface for PF device carp #Common Address Redundancy Protocol device enc #IPsec interface device lagg #Link aggregation interface device stf #IPv4-IPv6 port # Also for my notebook, but may be used with Opteron device amdtemp # Same for Intel processors device coretemp # man 4 cpuctl device cpuctl # CPU control pseudo-device # Support for ECMP. More than one route for destination # Works even with default route so one can use it as LB for two ISP # For now code is unstable and panics (panic: rtfree 2) on route deletions. #options RADIX_MPATH # Multicast routing #options MROUTING #options PIM # Debug & DTrace options KDB # Kernel debugger related code options KDB_TRACE # Print a stack trace for a panic options KDTRACE_FRAME # amd64-only(?) options KDTRACE_HOOKS # all architectures - enable general DTrace hooks #options DDB #options DDB_CTF # all architectures - kernel ELF linker loads CTF data # Adaptive spining in lockmgr (8.x+) # See http://www.mail-archive.com/[email protected]/msg10782.html options ADAPTIVE_LOCKMGRS # UTF-8 in console (8.x+) #options TEKEN_UTF8 # FreeBSD 8.1+ # Deadlock resolver thread # For additional information see http://www.mail-archive.com/[email protected]/msg18124.html # (FYI: "resolution" is panic so use with caution) #options DEADLKRES # Increase maximum size of Raw I/O and sendfile(2) readahead #options MAXPHYS=(1024*1024) #options MAXBSIZE=(1024*1024) # For scheduler debug enable following option. # Debug will be available via `kern.sched.stats` sysctl # For more information see http://svnweb.freebsd.org/base/head/sys/conf/NOTES?view=markup #options SCHED_STATS If you are tuning network for maximum performance you may wish to play with ifconfig options like: # You can list all capabilities via `ifconfig -m` ifconfig [-]rxcsum [-]txcsum [-]tso [-]lro mtu In case you've enabled DDB in kernel config, you should edit your /etc/ddb.conf and add something like this to enable automatic reboot (and textdump as bonus): script kdb.enter.panic=textdump set; capture on; show pcpu; bt; ps; alltrace; capture off; call doadump; reset script kdb.enter.default=textdump set; capture on; bt; ps; capture off; call doadump; reset And do not forget to add ddb_enable="YES" to /etc/rc.conf Since FreeBSD 9 you can select to enable/disable flowcontrol on your NIC: # See http://en.wikipedia.org/wiki/Ethernet_flow_control and # http://www.mail-archive.com/[email protected]/msg07927.html for additional info ifconfig bge0 media auto mediaopt flowcontrol PS. Also most of FreeBSD's limits can be monitored by # vmstat -z and # limits PPS. variety of network counters can be monitored via # netstat -s In FreeBSD-9 netstat's -Q option appeared, try following command to display netisr stats # netstat -Q PPPS. also see # man 7 tuning PPPPS. I wanted to thank FreeBSD community, especially author of nginx - Igor Sysoev, nginx-ru@ and FreeBSD-performance@ mailing lists for providing useful information about FreeBSD tuning. FreeBSD WIP * Whats cooking for FreeBSD 7? * Whats cooking for FreeBSD 8? * Whats cooking for FreeBSD 9? So here is the question: What tunings are you using on yours FreeBSD servers? You can also post your /etc/sysctl.conf, /boot/loader.conf, kernel options, etc with description of its' meaning (do not copy-paste from sysctl -d). Don't forget to specify server type (web, smb, gateway, etc) Let's share experience!

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  • Framework 4 Features: Support for Timed Jobs

    - by Anthony Shorten
    One of the new features of the Oracle Utilities Application Framework V4 is the ability for the batch framework to support Timed Batch. Traditionally batch is associated with set processing in the background in a fixed time frame. For example, billing customers. Over the last few versions their has been functionality required by the products required a more monitoring style batch process. The monitor is a batch process that looks for specific business events based upon record status or other pieces of data. For example, the framework contains a fact monitor (F1-FCTRN) that can be configured to look for specific status's or other conditions. The batch process then uses the instructions on the object to determine what to do. To support monitor style processing, you need to run the process regularly a number of times a day (for example, every ten minutes). Traditional batch could support this but it was not as optimal as expected (if you are a site using the old Workflow subsystem, you understand what I mean). The Batch framework was extended to add additional facilities to support times (and continuous batch which is another new feature for another blog entry). The new facilities include: The batch control now defines the job as Timed or Not Timed. Non-Timed batch are traditional batch jobs. The timer interval (the interval between executions) can be specified The timer can be made active or inactive. Only active timers are executed. Setting the Timer Active to inactive will stop the job at the next time interval. Setting the Timer Active to Active will start the execution of the timed job. You can specify the credentials, language to view the messages and an email address to send the a summary of the execution to. The email address is optional and requires an email server to be specified in the relevant feature configuration. You can specify the thread limits and commit intervals to be sued for the multiple executions. Once a timer job is defined it will be executed automatically by the Business Application Server process if the DEFAULT threadpool is active. This threadpool can be started using the online batch daemon (for non-production) or externally using the threadpoolworker utility. At that time any batch process with the Timer Active set to Active and Batch Control Type of Timed will begin executing. As Timed jobs are executed automatically then they do not appear in any external schedule or are managed by an external scheduler (except via the DEFAULT threadpool itself of course). Now, if the job has no work to do as the timer interval is being reached then that instance of the job is stopped and the next instance started at the timer interval. If there is still work to complete when the interval interval is reached, the instance will continue processing till the work is complete, then the instance will be stopped and the next instance scheduled for the next timer interval. One of the key ways of optimizing this processing is to set the timer interval correctly for the expected workload. This is an interesting new feature of the batch framework and we anticipate it will come in handy for specific business situations with the monitor processes.

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  • How to Sync Any Browser’s Bookmarks With Your iPad or iPhone

    - by Chris Hoffman
    Apple makes it easy to synchronize bookmarks between the Safari browser on a Mac and the Safari browser on iOS, but you don’t have to use Safari — or a Mac — to sync your bookmarks back and forth. You can do this with any browser. Whether you’re using Chrome, Firefox, or even Internet Explorer, there’s a way to sync your browser bookmarks so you can access your same bookmarks on your iPad. Safari on a Mac Apple’s iCloud service is the officially supported way to sync data with your iPad or iPhone. It’s included on Macs, but Apple also offers similar iCloud bookmark syncing features for Windows. On a Mac, this should be enabled by default. To check whether it’s enabled, you can launch the System Preferences panel on your Mac, open the iCloud preferences panel, and ensure the Safari option is checked. If you’re using Safari on Windows — well, you shouldn’t be. Apple is no longer updating Safari for Windows. iCloud allows you to synchronize bookmarks between other browsers on your Windows system and Safari on your iOS device, so Safari isn’t necessary. Internet Explorer, Firefox, or Chrome via iCloud To get started, download Apple’s iCloud Control Panel application for Windows and install it. Launch the iCloud Control Panel and log in with the same iCloud account (Apple ID) you use on your iPad or iPhone. You’ll be able to enable Bookmark syncing with Internet Explorer, Firefox, or Chrome. Click the Options button to select the browser you want to synchronize bookmarks with. (Note that bookmarks are called “favorites” in Internet Explorer.) You’ll be able to access your synced bookmarks in the Safari browser on your iPad or iPhone, and they’ll sync back and forth automatically over the Internet. Google Chrome Sync Google Chrome also has its own built-in sync feature and Google provides an official Chrome app for iPad and iPhone. If you’re a Chrome user, you can set up Chrome Sync on your desktop version of Chrome — you should already have this enabled if you have logged into your Chrome browser. You can check if this Chrome Sync is enabled by opening Chrome’s settings screen and seeing whether you’re signed in. Click the Advanced sync settings button and ensure bookmark syncing is enabled. Once you have Chrome Sync set up, you can install the Chrome app from the App Store and sign in with the same Google account. Your bookmarks, as well as other data like your open browser tabs, will automatically sync. This can be a better solution because the Chrome browser is available for so many platforms and you gain the ability to synchronize other browser data, such as your open browser tabs, between your devices. Unfortunately, the Chrome browser is slower than Apple’s own Safari browser on iPad and iPhone because of the way Apple limits third-party browsers, so using it involves a trade-off. Manual Bookmark Sync in iTunes iTunes also allows you to sync bookmarks between your computer and your iPad or iPhone. It does this the old-fashioned way, by initiating a manual sync when your device is plugged in via USB. To access this option, connect your device to your computer, select the device in iTunes, and click the Info tab. This is the more outdated way of synchronizing your bookmarks. This feature may be useful if you want to create a one-time copy of your bookmarks from your PC, but it’s nowhere near ideal for regular syncing. You don’t have to use this feature, just as you really don’t have to use iTunes anymore. In fact, this option is unavailable if you’ve set up iCloud syncing in iTunes. After you set up bookmark syncing via iCloud or Chrome Sync, bookmarks will sync immediately after you save, remove, or edit them.     

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  • A temporary disagreement

    - by Tony Davis
    Last month, Phil Factor caused a furore amongst some MVPs with an article that attempted to offer simple advice to developers regarding the use of table variables, versus local and global temporary tables, in their code. Phil makes clear that the table variables do come with some fairly major limitations.no distribution statistics, no parallel query plans for queries that modify table variables.but goes on to suggest that for reasonably small-scale strategic uses, and with a bit of due care and testing, table variables are a "good thing". Not everyone shares his opinion; in fact, I imagine he was rather aghast to learn that there were those felt his article was akin to pulling the pin out of a grenade and tossing it into the database; table variables should be avoided in almost all cases, according to their advice, in favour of temp tables. In other words, a fairly major feature of SQL Server should be more-or-less 'off limits' to developers. The problem with temp tables is that, because they are scoped either in the procedure or the connection, it is easy to allow them to hang around for too long, eating up precious memory and bulking up the shared tempdb database. Unless they are explicitly dropped, global temporary tables, and local temporary tables created within a connection rather than within a stored procedure, will persist until the connection is closed or, with connection pooling, until the connection is reused. It's also quite common with ASP.NET applications to have connection leaks, as Bill Vaughn explains in his chapter in the "SQL Server Deep Dives" book, meaning that the web page exits without closing the connection object, maybe due to an error condition. This will then hang around in the heap for what might be hours before picked up by the garbage collector. Table variables are much safer in this regard, since they are batch-scoped and so are cleaned up automatically once the batch is complete, which also means that they are intuitive to use for the developer because they conform to scoping rules that are closer to those in procedural code. On the surface then, an ideal way to deal with issues related to tempdb memory hogging. So why did Phil qualify his recommendation to use Table Variables? This is another of those cases where, like scalar UDFs and table-valued multi-statement UDFs, developers can sometimes get into trouble with a relatively benign-looking feature, due to way it's been implemented in SQL Server. Once again the biggest problem is how they are handled internally, by the SQL Server query optimizer, which can make very poor choices for JOIN orders and so on, in the absence of statistics, especially when joining to tables with highly-skewed data. The resulting execution plans can be horrible, as will be the resulting performance. If the JOIN is to a large table, that will hurt. Ideally, Microsoft would simply fix this issue so that developers can't get burned in this way; they've been around since SQL Server 2000, so Microsoft has had a bit of time to get it right. As I commented in regard to UDFs, when developers discover issues like with such standard features, the database becomes an alien planet to them, where death lurks around each corner, and they continue to avoid these "killer" features years after the problems have been eventually resolved. In the meantime, what is the right approach? Is it to say "hammers can kill, don't ever use hammers", or is it to try to explain, as Phil's article and follow-up blog post have tried to do, what the feature was intended for, why care must be applied in its use, and so enable developers to make properly-informed decisions, without requiring them to delve deep into the inner workings of SQL Server? Cheers, Tony.

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  • BizTalk 2009 - Architecture Decisions

    - by StuartBrierley
    In the first step towards implementing a BizTalk 2009 environment, from development through to live, I put forward a proposal that detailed the options available, as well as the costs and benefits associated with these options, to allow an informed discusion to take place with the business drivers and budget holders of the project.  This ultimately lead to a decision being made to implement an initial BizTalk Server 2009 environment using the Standard Edition of the product. It is my hope that in the long term, as projects require it and allow, we will be looking to implement my ideal recommendation of a multi-server enterprise level environment, but given the differences in cost and the likely initial work load for the environment this was not something that I could fully recommend at this time.  However, it must be noted that this decision was made in full awareness of the limits of the standard edition, and the business drivers of this project were made fully aware of the risks associated with running without the failover capabilities of the enterprise edition. When considering the creation of this new BizTalk Server 2009 environment, I have also recommended the creation of the following pre-production environments:   Usage Environment Development Development of solutions; Unit testing against technical specifications; Initial load testing; Testing of deployment packages;  Visual Studio; BizTalk; SQL; Client PCs/Laptops; Server environment similar to Live implementation; Test Testing of Solutions against business and technical requirements;  BizTalk; SQL; Server environment similar to Live implementation; Pseudo-Live As Live environment to allow testing against Live implementation; Acts as back-up hardware in case of failure of Live environment; BizTalk; SQL; Server environment identical to Live implementation; The creation of these differing environments allows for the separation of the various stages of the development cycle.  The development environment is for use when actively developing a solution, it is a potentially volatile environment whose state at any given time can not be guaranteed.  It allows developers to carry out initial tests in an environment that is similar to the live environment and also provides an area for the testing of deployment packages prior to any release to the test environment. The test environment is intended to be a semi-volatile environment that is similar to the live environment.  It will change periodically through the development of a solution (or solutions) but should be otherwise stable.  It allows for the continued testing of a solution against requirements without the worry that the environment is being actively changed by any ongoing development.  This separation of development and test is crucial in ensuring the quality and control of the tested solution. The pseudo-live environment should be considered to be an almost static environment.  It should mimic the live environment and can act as back up hardware in the case of live failure.  This environment acts as an area to allow for “as live” testing, where the performance and behaviour of the live solutions can be replicated.  There should be relatively few changes to this environment, with software releases limited to “release candidate” level releases prior to going live. Whereas the pseudo-live environment should always mimic the live environment, to save on costs the development and test servers could be implemented on lower specification hardware.  Consideration can also be given to the use of a virtual server environment to further reduce hardware costs in the development and test environments, indeed this virtual approach can also be extended to pseudo-live and live assuming the underlying technology is in place. Although there is no requirement for the development and test server environments to be identical to live, the overriding architecture implemented should be the same as in live and an understanding must be gained of the performance differences to be expected across the different environments.

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  • SQL SERVER – Why Do We Need Data Quality Services – Importance and Significance of Data Quality Services (DQS)

    - by pinaldave
    Databases are awesome.  I’m sure my readers know my opinion about this – I have made SQL Server my life’s work after all!  I love technology and all things computer-related.  Of course, even with my love for technology, I have to admit that it has its limits.  For example, it takes a human brain to notice that data has been input incorrectly.  Computer “brains” might be faster than humans, but human brains are still better at pattern recognition.  For example, a human brain will notice that “300” is a ridiculous age for a human to be, but to a computer it is just a number.  A human will also notice similarities between “P. Dave” and “Pinal Dave,” but this would stump most computers. In a database, these sorts of anomalies are incredibly important.  Databases are often used by multiple people who rely on this data to be true and accurate, so data quality is key.  That is why the improved SQL Server features Master Data Management talks about Data Quality Services.  This service has the ability to recognize and flag anomalies like out of range numbers and similarities between data.  This allows a human brain with its pattern recognition abilities to double-check and ensure that P. Dave is the same as Pinal Dave. A nice feature of Data Quality Services is that once you set the rules for the program to follow, it will not only keep your data organized in the future, but go to the past and “fix up” any data that has already been entered.  It also allows you do combine data from multiple places and it will apply these rules across the board, so that you don’t have any weird issues that crop up when trying to fit a round peg into a square hole. There are two parts of Data Quality Services that help you accomplish all these neat things.  The first part is DQL Server, which you can think of as the hardware component of the system.  It is installed on the side of (it needs to install separately after SQL Server is installed) SQL Server and runs quietly in the background, performing all its cleanup services. DQS Client is the user interface that you can interact with to set the rules and check over your data.  There are three main aspects of Client: knowledge base management, data quality projects and administration.  Knowledge base management is the part of the system that allows you to set the rules, or program the “knowledge base,” so that your database is clean and consistent. Data Quality projects are what run in the background and clean up the data that is already present.  The administration allows you to check out what DQS Client is doing, change rules, and generally oversee the entire process.  The whole process is user-friendly and a pleasure to use.  I highly recommend implementing Data Quality Services in your database. Here are few of my blog posts which are related to Data Quality Services and I encourage you to try this out. SQL SERVER – Installing Data Quality Services (DQS) on SQL Server 2012 SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS SQL SERVER – DQS Error – Cannot connect to server – A .NET Framework error occurred during execution of user-defined routine or aggregate “SetDataQualitySessions” – SetDataQualitySessionPhaseTwo SQL SERVER – Configuring Interactive Cleansing Suggestion Min Score for Suggestions in Data Quality Services (DQS) – Sensitivity of Suggestion SQL SERVER – Unable to DELETE Project in Data Quality Projects (DQS) Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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  • Three Key Tenets of Optimal Social Collaboration

    - by kellsey.ruppel
    Today's blog post comes to us from John Bruswick! This post is an abridged version of John’s white paper in which he discusses three principals to optimize social collaboration within an enterprise.   By [email protected], Oracle Principal Sales Consultant Effective social collaboration is actionable, deeply contextual and inherently derives its value from business entities outside of itself. How does an organization begin the journey from traditional, siloed collaboration to natural, business entity based social collaboration? Successful enablement of enterprise social collaboration requires that organizations embrace the following tenets and understand that traditional collaborative functionality has inherent limits - it is innovation and integration in accordance with the following tenets that will provide net-new efficiency benefits. Key Tenets of Optimal Social Collaboration Leverage a Ubiquitous Social Fabric - Collaborative activities should be supported through a ubiquitous social fabric, providing a personalized experience, broadcasting key business events and connecting people and business processes.  This supports education of participants working in and around a specific business entity that will benefit from an implicit capture of tacit knowledge and provide continuity between participants.  In the absence of this ubiquitous platform activities can still occur but are essentially siloed causing frequent duplication of effort across similar tasks, with critical tacit knowledge eluding capture. Supply Continuous Context to Support Decision Making and Problem Solving - People generally engage in collaborative behavior to obtain a decision or the resolution for a specific issue.  The time to achieve resolution is referred to as "Solve Time".  Users have traditionally been forced to switch or "alt-tab" between business systems and synthesize their own context across disparate systems and processes.  The constant loss of context forces end users to exert a large amount of effort that could be spent on higher value problem solving. Extend the Collaborative Lifecycle into Back Office - Beyond the solve time from decision making efforts, additional time is expended formalizing the resolution that was generated from collaboration in a system of record.  Extending collaboration to result in the capture of an explicit decision maximizes efficiencies, creating a closed circuit for a particular thread.  This type of structured action may exist today within your organization's customer support system around opening, solving and closing support issues, but generally does not extend to Sales focused collaborative activities. Excelling in the Unstructured Future We will always have to deal with unstructured collaborative processes within our organizations.  Regardless of the participants and nature of the collaborate process, two things are certain – the origination and end points are generally known and relate to a business entity, perhaps a customer, opportunity, order, shipping location, product or otherwise. Imagine the benefits if an organization's key business systems supported a social fabric, provided continuous context and extended the lifecycle around the collaborative decision making to include output into back office systems of record.   The technical hurdle to embracing optimal social collaboration would fall away, leaving the company with an opportunity to focus on and refine how processes were approached.  Time and resources previously required could then be reallocated to focusing on innovation to support competitive differentiation unique to your business. How can you achieve optimal social collaboration? Oracle Social Network enables business users to collaborate with each other using a broad range of collaboration styles and integrates data from a variety of sources and business applications -- allowing you to achieve optimal social collaboration. Looking to learn more? Read John's white paper, where he discusses in further detail the three principals to optimize social collaboration within an enterprise. 

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  • The All New Hotmail Looks Very Impressive [Video Tour]

    - by Gopinath
    With loads of new new features being introduced into GMail every now and then, Microsoft can’t sit and relax any more. Microsoft realized this and worked hard to introduce really impressive features in upcoming version of Windows Live Hotmail that was previewed couple of days ago. Most of the new features announced in the upcoming version are focusing on the important need of email users – de-clutter the mail box and effectively manage email over load easily. Here is the list highlight of new features New Features Sweep away clutter – This is the most impressive in the set of new features. It allows you to manage email overload. If you’ve subscribed to a newsletter but decided to not to allow it into your inbox, you can activate the sweep feature to move all the messages of the newsletter in to a folder other than your inbox. This may sound similar to filters option in GMail but the workflow is very easy in Hotmail. Quickly find message – Easy to use options are provided to see mails in separate views likes mails from contacts, social networking mail, mails from e-mail subscription services, etc. Now it’s easy to prioritize email checking like how you wish to. I prefer to check mails from my contacts first, then social networking messages and then the newsletter subscriptions. Improved spam detection – The span detection rules are tightened for better spam protection and also hotmail learns from user actions to effectively catch spam No more mail box storage restrictions – With a smart decision of Microsoft, users  no longer need to worry about the storage restrictions of their mail box – large attachments of hotmail can be stored in Windows Live SkyDrive. With Hotmail, we’ve combined the simplicity of sending photos through email with the power of Windows Live SkyDrive so that you can send up to 200 photos, each up to 50 MB in size, all in a single email. You can send all your vacation photos at once without worrying about attachment limits, Excellent Integration With Office Web Apps -  View and editing of office documents attached to the emails are made very easy by integrating Office Web Apps with Hotmail. When you receive a document/presentation/spreadsheet in hotmail, you can view it, edit it, save it or even you can send the modified document to original sender – all these without leaving hotmail. Inline viewing options for Photos, Videos, Social Network Messages – You can view photos embedded in the mail as slideshows(with the help of SilverLight), YouTube  & Hulu videos can be played inline  and track shipping notifications. Threaded conversations – emails in Hotmail are grouped just like it happens in GMail Others - enhanced account protection, full-session SSL, multiple email accounts, subfolders, contact management Video Tour Of New Features Here is an impressive video tour of new Hotmail features. When are these new features coming to Hotmail? Majority of the new features announced today are rolled out in coming weeks gradually to all the users. But advanced features like Office Integration with Hotmail is expected to take couple of months for general availability. Will You Switch back to Hotmail? Will these features lure GMail/Yahoo users to switch back to Hotmail? May be not immediately but these features may hold the existing users from leaving Hotmail. I used Hotmail, in the pre GMail era and now I use  Hotmail id only to sign-in to Microsoft websites that requites Hotmail authentication. It’s been years since I composed a new email in Hotmail. Even though the new features announced by Hotmail are very impressive, I like the way how GMail rapidly brings new features at regular intervals. If Hotmail also keeps innovating with new features at regular intervals, then there are good chances for it’s old users to return home. Join us on Facebook to read all our stories right inside your Facebook news feed.

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  • DAC pack up all your troubles

    - by Tony Davis
    Visual Studio 2010, or perhaps its apparently-forthcoming sister, "SQL Studio", is being geared up to become the natural way for developers to create databases. Central to this drive is the introduction of 'data-tier application components', or DACs. Applications are developed as normal but when it comes to deployment, instead of supplying the DBA with a bunch of scripts to create the required database objects, the developer creates a single DAC Package ("DAC Pack"); a zipped XML file containing all the database objects needed by the application, along with versioning information, policies for deployment, and so on. It's an intriguing prospect. Developers can work on their development database using their existing tools and source control, and then package up the changes into a single DACPAC for deployment and management. DBAs get an "application level view" of how their instances are being used and the ability to collectively, rather than individually, manage the objects. The DBA needing to manage a large number of relatively small databases can use "DAC snapshots" to get a quick overview of what has changed across all the databases they manage. The reason that DAC packs haven't caused more excitement is that they can only be pushed to SQL Server 2008 R2, and they must be developed or inspected using Visual Studio 2010. Furthermore, what we see right now in VS2010 is more of a 'work-in-progress' or 'vision of the future', with serious shortcomings and restrictions that render it unsuitable for anything but small 'non-critical' departmental databases. The first problem is that DAC packs support a limited set of schema objects (corresponding closely to the features available on 'Azure'). This means that Service Broker queues, CLR Objects, and perhaps most critically security (permissions, certificates etc.), are off-limits. Applications that require these objects will need to add them via a post-deployment TSQL script, rather defeating the whole idea. More worrying still is the process for altering a database with a DAC pack. The grand 'collective' philosophy, whereby a single XML file can be used for deploying and managing builds and changes, extends, unfortunately, to database upgrades. Any change to a database object will result in the creation of a new database, copying the data from the old version, nuking the previous one, and then renaming the new one. Simple eh? The problem is that even something as trivial as adding a comment to a stored procedure in a 5GB database will require the server to find at least twice as much space, as well sufficient elbow-room in the transaction log for copying the largest table. Of course, you'll need to take the database offline for the full course of the deployment, which is likely to take a long time if there is a lot of data. This upgrade/rename process breaks the log chain, makes any subsequent full restore operation highly complicated, and will also break log shipping. As with any grand vision, the devil is always in the detail. It's hard to fathom why Microsoft hasn't used a SQL Compare-style approach to the upgrade process, altering a database with a change script, and this will surely be adopted in the near future. Something had to be in place for VS2010, but right now DAC packs only make sense for Azure. For this, they're cute, but hardly compelling. Nevertheless, DBAs would do well to get familiar with VS 2010 and DAC packs. Like it or not, they're both coming. Cheers, Tony.

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  • AppKata - Enter the next level of programming exercises

    - by Ralf Westphal
    Doing CodeKatas is all the rage lately. That´s great since widely accepted exercises are important to further the art. They provide a means of communication across platforms and allow to compare results which is part of any deliberate practice. But CodeKatas suffer from their size. They are intentionally small, so they can be done again and again. Repetition helps to build habit and to dig deeper. Over time ever new nuances of the problem or one´s approach become visible. On the other hand, though, their small size limits the methods, techniques, technologies that can be applied. To improve your TDD skills doing CodeKatas might be enough. But what about other skills? Developing on a software in a team, designing larger pieces of software, iteratively releasing software… all this and more is kinda hard to train using the tiny CodeKata problems. That´s why I´d like to present here another kind of kata I call Application Kata (or just AppKata). AppKatas are larger programming problems. They require the development of “whole” applications, i.e. not just one class or method, but bunches of classes accessible through a user interface. Also AppKata problems always are split into iterations. To get the most out of them, just look at the requirements of one iteration at a time. This way you´re closer to reality where requirements evolve in unexpected ways. So if you´re looking for more of a challenge for your software development skills, check out these AppKatas – or invent your own. AppKatas are platform independent like CodeKatas. Use whatever programming language and IDE you like. Also use whatever approach to software development you like. Just be sensitive to how easy it is to evolve your code across iterations. Reflect on what went well and what not. Compare your solutions with others. Or – for even more challenge – go for the “Coding Carousel” (see below). CSV Viewer An application to view CSV files. Sounds easy, but watch out! Requirements sometimes drastically change if the customer is happy with what you delivered. Iteration 1 Iteration 2 Iteration 3 Iteration 4 Iteration 5 (to come) Questionnaire If you like GUI programming, this AppKata might be for you. It´s about an app to let people fill out questionnaires. Also this problem might be interestin for you, if you´re into DDD. Iteration 1 Iteration 2 (to come) Iteration 3 (to come) Iteration 4 (to come) Tic Tac Toe For developers who like game programming. Although Tic Tac Toe is a trivial game, this AppKata poses some interesting infrastructure challenges. The GUI, however, stays simple; leave any 3D ambitions at home ;-) Iteration 1 Iteration 2 (to come) Iteration 3 (to come) Iteration 4 (to come) Iteration 5 (to come) Coding Carousel There are many ways you can do AppKatas. Work on them alone or in a team, pitch several devs against each other in an AppKata contest – or go around in a Coding Carousel. For the Coding Carousel you need at least 3 dev teams (regardless of size). All teams work on the same iteration at the same time. But here´s the trick: After each iteration the teams swap their code. Whatever they did for iteration n will be the basis for changes another team has to apply in iteration n+1. The code is going around the teams like in a carousel. I promise you, that´s gonna be fun! :-)

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  • Threading Overview

    - by ACShorten
    One of the major features of the batch framework is the ability to support multi-threading. The multi-threading support allows a site to increase throughput on an individual batch job by splitting the total workload across multiple individual threads. This means each thread has fine level control over a segment of the total data volume at any time. The idea behind the threading is based upon the notion that "many hands make light work". Each thread takes a segment of data in parallel and operates on that smaller set. The object identifier allocation algorithm built into the product randomly assigns keys to help ensure an even distribution of the numbers of records across the threads and to minimize resource and lock contention. The best way to visualize the concept of threading is to use a "pie" analogy. Imagine the total workset for a batch job is a "pie". If you split that pie into equal sized segments, each segment would represent an individual thread. The concept of threading has advantages and disadvantages: Smaller elapsed runtimes - Jobs that are multi-threaded finish earlier than jobs that are single threaded. With smaller amounts of work to do, jobs with threading will finish earlier. Note: The elapsed runtime of the threads is rarely proportional to the number of threads executed. Even though contention is minimized, some contention does exist for resources which can adversely affect runtime. Threads can be managed individually – Each thread can be started individually and can also be restarted individually in case of failure. If you need to rerun thread X then that is the only thread that needs to be resubmitted. Threading can be somewhat dynamic – The number of threads that are run on any instance can be varied as the thread number and thread limit are parameters passed to the job at runtime. They can also be configured using the configuration files outlined in this document and the relevant manuals.Note: Threading is not dynamic after the job has been submitted Failure risk due to data issues with threading is reduced – As mentioned earlier individual threads can be restarted in case of failure. This limits the risk to the total job if there is a data issue with a particular thread or a group of threads. Number of threads is not infinite – As with any resource there is a theoretical limit. While the thread limit can be up to 1000 threads, the number of threads you can physically execute will be limited by the CPU and IO resources available to the job at execution time. Theoretically with the objects identifiers evenly spread across the threads the elapsed runtime for the threads should all be the same. In other words, when executing in multiple threads theoretically all the threads should finish at the same time. Whilst this is possible, it is also possible that individual threads may take longer than other threads for the following reasons: Workloads within the threads are not always the same - Whilst each thread is operating on the roughly the same amounts of objects, the amount of processing for each object is not always the same. For example, an account may have a more complex rate which requires more processing or a meter has a complex amount of configuration to process. If a thread has a higher proportion of objects with complex processing it will take longer than a thread with simple processing. The amount of processing is dependent on the configuration of the individual data for the job. Data may be skewed – Even though the object identifier generation algorithm attempts to spread the object identifiers across threads there are some jobs that use additional factors to select records for processing. If any of those factors exhibit any data skew then certain threads may finish later. For example, if more accounts are allocated to a particular part of a schedule then threads in that schedule may finish later than other threads executed. Threading is important to the success of individual jobs. For more guidelines and techniques for optimizing threading refer to Multi-Threading Guidelines in the Batch Best Practices for Oracle Utilities Application Framework based products (Doc Id: 836362.1) whitepaper available from My Oracle Support

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  • Why Ultra-Low Power Computing Will Change Everything

    - by Tori Wieldt
    The ARM TechCon keynote "Why Ultra-Low Power Computing Will Change Everything" was anything but low-powered. The speaker, Dr. Johnathan Koomey, knows his subject: he is a Consulting Professor at Stanford University, worked for more than two decades at Lawrence Berkeley National Laboratory, and has been a visiting professor at Stanford University, Yale University, and UC Berkeley's Energy and Resources Group. His current focus is creating a standard (computations per kilowatt hour) and measuring computer energy consumption over time. The trends are impressive: energy consumption has halved every 1.5 years for the last 60 years. Battery life has made roughly a 10x improvement each decade since 1960. It's these improvements that have made laptops and cell phones possible. What does the future hold? Dr. Koomey said that in the past, the race by chip manufacturers was to create the fastest computer, but the priorities have now changed. New computers are tiny, smart, connected and cheap. "You can't underestimate the importance of a shift in industry focus from raw performance to power efficiency for mobile devices," he said. There is also a confluence of trends in computing, communications, sensors, and controls. The challenge is how to reduce the power requirements for these tiny devices. Alternate sources of power that are being explored are light, heat, motion, and even blood sugar. The University of Michigan has produced a miniature sensor that harnesses solar energy and could last for years without needing to be replaced. Also, the University of Washington has created a sensor that scavenges power from existing radio and TV signals.Specific devices designed for a purpose are much more efficient than general purpose computers. With all these sensors, instead of big data, developers should focus on nano-data, personalized information that will adjust the lights in a room, a machine, a variable sign, etc.Dr. Koomey showed some examples:The Proteus Digital Health Feedback System, an ingestible sensor that transmits when a patient has taken their medicine and is powered by their stomach juices. (Gives "powered by you" a whole new meaning!) Streetline Parking Systems, that provide real-time data about available parking spaces. The information can be sent to your phone or update parking signs around the city to point to areas with available spaces. Less driving around looking for parking spaces!The BigBelly trash system that uses solar power, compacts trash, and sends a text message when it is full. This dramatically reduces the number of times a truck has to come to pick up trash, freeing up resources and slashing fuel costs. This is a classic example of the efficiency of moving "bits not atoms." But researchers are approaching the physical limits of sensors, Dr. Kommey explained. With the current rate of technology improvement, they'll reach the three-atom transistor by 2041. Once they hit that wall, it will force a revolution they way we do computing. But wait, researchers at Purdue University and the University of New South Wales are both working on a reliable one-atom transistors! Other researchers are working on "approximate computing" that will reduce computing requirements drastically. So it's unclear where the wall actually is. In the meantime, as Dr. Koomey promised, ultra-low power computing will change everything.

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  • Functional/nonfunctional requirements VS design ideas

    - by Nicholas Chow
    Problem domain Functional requirements defines what a system does. Non-Functional requirements defines quality attributes of what the system does as a whole.(performance, security, reliability, volume, useability, etc.) Constraints limits the design space, they restrict designers to certain types of solutions. Solution domain Design ideas , defines how the system does it. For example a stakeholder need might be we want to increase our sales, therefore we must improve the usability of our webshop so more customers will purchase, a requirement can be written for this. (problem domain) Design takes this further into the solution domain by saying "therefore we want to offer credit card payments in addition to the current prepayment option". My problem is that the transition phase from requirement to design seems really vague, therefore when writing requirements I am often confused whether or not I incorporated design ideas in my requirements, that would make my requirement wrong. Another problem is that I often write functional requirements as what a system does, and then I also specify in what timeframe it must be done. But is this correct? Is it then a still a functional requirement or a non functional one? Is it better to seperate it into two distinct requirements? Here are a few requirements I wrote: FR1 Registration of Organizer FR1 describes the registration of an Organizer on CrowdFundum FR1.1 The system shall display a registration form on the website. FR1.2 The system shall require a Name, Username, Document number passport/ID card, Address, Zip code, City, Email address, Telephone number, Bank account, Captcha code on the registration form when a user registers. FR1.4 The system shall display an error message containing: “Registration could not be completed” to the subscriber within 1 seconds after the system check of the registration form was unsuccessful. FR1.5 The system shall send a verification email containing a verification link to the subscriber within 30 seconds after the system check of the registration form was successful. FR1.6 The system shall add the newly registered Organizer to the user base within 5 seconds after the verification link was accessed. FR2 Organizer submits a Project FR2 describes the submission of a Project by an Organizer on CrowdFundum - FR2 The system shall display a submit Project form to the Organizer accounts on the website.< - FR2.3 The system shall check for completeness the Name of the Project, 1-3 Photo’s, Keywords of the Project, Punch line, Minimum and maximum amount of people, Funding threshold, One or more reward tiers, Schedule of when what will be organized, Budget plan, 300-800 Words of additional information about the Project, Contact details within 1 secondin after an Organizer submits the submit Project form. - FR2.8 The system shall add to the homepage in the new Projects category the Project link within 30 seconds after the system made a Project webpage - FR2.9 The system shall include in the Project link for the homepage : Name of the Project, 1 Photo, Punch line within 30 seconds after the system made a Project webpage. Questions: FR 1.1 : Have I incorporated a design idea here, would " the system shall have a registration form" be a better functional requirement? F1.2 ,2.3 : Is this not singular? Would the conditions be better written for each its own separate requirement FR 1.4: Is this a design idea? Is this a correct functional requirement or have I incorporated non functional(performance) in it? Would it be better if I written it like this: FR1 The system shall display an error message when check is unsuccessful. NFR: The system will respond to unsuccesful registration form checks within 1 seconds. Same question with FR 2.8 and 2.9. FR2.3: The system shall check for "completeness", is completeness here used ambigiously? Should I rephrase it? FR1.2: I added that the system shall require a "Captcha code" is this a functional requirement or does it belong to the "security aspect" of a non functional requirement. I am eagerly waiting for your response. Thanks!

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  • Tyrus 1.8

    - by Pavel Bucek
    Another version of Tyrus, the reference implementation of JSR 356 – Java API for WebSocket is out! Complete list of fixes and features is below, but let me describe some of the new features in more detail. All information presented here is also available in Tyrusdocumentation. What’s new? First to mention is that JSR 356 Maintenance review Ballot is over and the change proposed for 1.1 release was accepted. More details about changes in the API can be found in this article. Important part is that Tyrus 1.8 implements this API, meaning you can use Lambda expressions and some features of Nashorn without the need for any workarounds. Almost all other features are related to client side support, which was significantly improved in this release. Firstly – I have to admit, that Tyrus client contained security issue – SSL Hostname verification was not performed when connecting to “wss” endpoints. This was fixed as part of TYRUS-339 and resulted in some changes in the client configuration API. Now you can control whether HostnameVerification should be performed (SslEngineConfigurator#setHostnameVerificationEnabled(boolean)) or even set your own HostnameVerifier (please use carefully): #setHostnameVerifier(…). Detailed description can be found in Host verification chapter. Another related enhancement is support for Http Basic and Digest authentication schemes. Tyrus client now enables users to provide credentials and underlying implementation will take care of everything else. Our implementation is strictly non pre-emptive, so the login information is sent always as a response to 401 Http Status Code. If the Basic and Digest are not good enough and there is a need to use some custom scheme or something which is not yet supported in Tyrus, custom Authenticator can be registered and the authentication part of the handshake process will be handled by it. Please seeClient HTTP Authentication chapter in the user guide for more details. There are other features, like fine-grain threadpool configuration for JDK client container, build-in Http redirect support and some reshuffling related to unifying the location of client configuration classes and properties definition – every property should be now part of ClientProperties class. All new features are described in the user guide – in chapterTyrus proprietary configuration. Update – Tyrus 1.8.1 There was another slightly late reported issue related to running in environments with SecurityManager enabled, so this version fixes that. Another noteworthy fixes are TYRUS-355 and TYRUS-361; the first one is about incorrect thread factory used for shared container timeout, which resulted in JVM waiting for that thread and not exiting as it should. The other issue enables relative URIs in Location header when using redirect feature. Links Tyrus homepage mailing list JIRA Complete list of changes: Bug [TYRUS-333] – Multiple endpoints on one client [TYRUS-334] – When connection is closed by a peer, periodic heartbeat pong is not stopped [TYRUS-336] – ReaderBuffer.getNextChars() keeps blocking a server thread after client has closed the session [TYRUS-338] – JDK client SSL filter needs better synchronization during handshake phase [TYRUS-339] – SSL hostname verification is missing [TYRUS-340] – Test PathParamTest are not stable with JDK client [TYRUS-341] – A control frame inside a stream of continuation frames is treated as the part of the stream [TYRUS-343] – ControlFrameInDataStreamTest does not pass on GF [TYRUS-345] – NPE is thrown, when shared container timeout property in JDK client is not set [TYRUS-346] – IllegalStateException is thrown, when using proxy in JDK client [TYRUS-347] – Introduce better synchronization in JDK client thread pool [TYRUS-348] – When a client and server close connection simultaneously, JDK client throws NPE [TYRUS-356] – Tyrus cannot determine the connection port for a wss URL [TYRUS-357] – Exception thrown in MessageHandler#OnMessage is not caught in @OnError method [TYRUS-359] – Client based on Java 7 Asynchronous IO makes application unexitable Improvement [TYRUS-328] – JDK 1.7 AIO Client container – threads – (setting threadpool, limits, …) [TYRUS-332] – Consolidate shared client properties into one file. [TYRUS-337] – Create an SSL version of Basic Servlet test New Feature [TYRUS-228] – Add client support for HTTP Basic/Digest Task [TYRUS-330] – create/run tests/servlet/basic via wss [TYRUS-335] – [clustering] – introduce RemoteSession and expose them via separate method (not include remote sessions in the getOpenSessions()) [TYRUS-344] – Introduce Client support for HTTP Redirect

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  • Tuning Default WorkManager - Advantages and Disadvantages

    - by Murali Veligeti
    Before discussing on Tuning Default WorkManager, lets have a brief introduction on What is Default WorkManger Before Weblogic Server 9.0 release, we had the concept of Execute Queues. WebLogic Server (before WLS 9.0), processing was performed in multiple execute queues. Different classes of work were executed in different queues, based on priority and ordering requirements, and to avoid deadlocks. In addition to the default execute queue, weblogic.kernel.default, there were pre-configured queues dedicated to internal administrative traffic, such as weblogic.admin.HTTP and weblogic.admin.RMI.Users could control thread usage by altering the number of threads in the default queue, or configure custom execute queues to ensure that particular applications had access to a fixed number of execute threads, regardless of overall system load. From WLS 9.0 release onwards WebLogic Server uses is a single thread pool (single thread pool which is called Default WorkManager), in which all types of work are executed. WebLogic Server prioritizes work based on rules you define, and run-time metrics, including the actual time it takes to execute a request and the rate at which requests are entering and leaving the pool.The common thread pool changes its size automatically to maximize throughput. The queue monitors throughput over time and based on history, determines whether to adjust the thread count. For example, if historical throughput statistics indicate that a higher thread count increased throughput, WebLogic increases the thread count. Similarly, if statistics indicate that fewer threads did not reduce throughput, WebLogic decreases the thread count. This new strategy makes it easier for administrators to allocate processing resources and manage performance, avoiding the effort and complexity involved in configuring, monitoring, and tuning custom executes queues. The Default WorkManager is used to handle thread management and perform self-tuning.This Work Manager is used by an application when no other Work Managers are specified in the application’s deployment descriptors. In many situations, the default Work Manager may be sufficient for most application requirements. WebLogic Server’s thread-handling algorithms assign each application its own fair share by default. Applications are given equal priority for threads and are prevented from monopolizing them. The default work-manager, as its name tells, is the work-manager defined by default.Thus, all applications deployed on WLS will use it. But sometimes, when your application is already in production, it's obvious you can't take your EAR / WAR, update the deployment descriptor(s) and redeploy it.The default work-manager belongs to a thread-pool, as initial thread-pool comes with only five threads, that's not much. If your application has to face a large number of hits, you may want to start with more than that.Well, that's quite easy. You have  two option to do so.1) Modify the config.xmlJust add the following line(s) in your server definition : <server> <name>AdminServer</name> <self-tuning-thread-pool-size-min>100</self-tuning-thread-pool-size-min> <self-tuning-thread-pool-size-max>200</self-tuning-thread-pool-size-max> [...] </server> 2) Adding some JVM parameters Add the following system property in setDomainEnv.sh/setDomainEnv.cmd or startWebLogic.sh/startWebLogic.cmd : -Dweblogic.threadpool.MinPoolSize=100 -Dweblogic.threadpool.MaxPoolSize=100 Reboot WLS and see the option has been taken into account . Disadvantage: So far its fine. But here there is an disadvantage in tuning Default WorkManager. Internally Weblogic Server has many work managers configured for different types of work.  if we run out of threads in the self-tuning pool(because of system property -Dweblogic.threadpool.MaxPoolSize) due to being undersized, then important work that WLS might need to do could be starved.  So, while limiting the self-tuning would limit the default WorkManager and internally it also limits all other internal WorkManagers which WLS uses.So the best alternative is to override the default WorkManager that means creating a WorkManager for the Application and assign the WorkManager for the application instead of tuning the Default WorkManager.

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  • Exploring TCP throughput with DTrace

    - by user12820842
    One key measure to use when assessing TCP throughput is assessing the amount of unacknowledged data in the pipe. This is sometimes termed the Bandwidth Delay Product (BDP) (note that BDP is often used more generally as the product of the link capacity and the end-to-end delay). In DTrace terms, the amount of unacknowledged data in bytes for the connection is the different between the next sequence number to send and the lowest unacknoweldged sequence number (tcps_snxt - tcps_suna). According to the theory, when the number of unacknowledged bytes for the connection is less than the receive window of the peer, the path bandwidth is the limiting factor for throughput. In other words, if we can fill the pipe without the peer TCP complaining (by virtue of its window size reaching 0), we are purely bandwidth-limited. If the peer's receive window is too small however, the sending TCP has to wait for acknowledgements before it can send more data. In this case the round-trip time (RTT) limits throughput. In such cases the effective throughput limit is the window size divided by the RTT, e.g. if the window size is 64K and the RTT is 0.5sec, the throughput is 128K/s. So a neat way to visually determine if the receive window of clients may be too small should be to compare the distribution of BDP values for the server versus the client's advertised receive window. If the BDP distribution overlaps the send window distribution such that it is to the right (or lower down in DTrace since quantizations are displayed vertically), it indicates that the amount of unacknowledged data regularly exceeds the client's receive window, so that it is possible that the sender may have more data to send but is blocked by a zero-window on the client side. In the following example, we compare the distribution of BDP values to the receive window advertised by the receiver (10.175.96.92) for a large file download via http. # dtrace -s tcp_tput.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 6 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 9 4096 | 14 8192 | 27 16384 | 67 32768 |@@ 1464 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 32396 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 16384 | 0 32768 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 17067 65536 | 0 Here we have a puzzle. We can see that the receiver's advertised window is in the 32768-65535 range, while the amount of unacknowledged data in the pipe is largely in the 65536-131071 range. What's going on here? Surely in a case like this we should see zero-window events, since the amount of data in the pipe regularly exceeds the window size of the receiver. We can see that we don't see any zero-window events since the SWND distribution displays no 0 values - it stays within the 32768-65535 range. The explanation is straightforward enough. TCP Window scaling is in operation for this connection - the Window Scale TCP option is used on connection setup to allow a connection to advertise (and have advertised to it) a window greater than 65536 bytes. In this case the scaling shift is 1, so this explains why the SWND values are clustered in the 32768-65535 range rather than the 65536-131071 range - the SWND value needs to be multiplied by two since the reciever is also scaling its window by a shift factor of 1. Here's the simple script that compares BDP and SWND distributions, fixed to take account of window scaling. #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::send / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @bdp["BDP(bytes)", args[2]-ip_daddr, args[4]-tcp_sport] = quantize(args[3]-tcps_snxt - args[3]-tcps_suna); } tcp:::receive / (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { @swnd["SWND(bytes)", args[2]-ip_saddr, args[4]-tcp_dport] = quantize((args[4]-tcp_window)*(1 tcps_snd_ws)); } And here's the fixed output. # dtrace -s tcp_tput_scaled.d ^C BDP(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count -1 | 0 0 | 39 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 3 512 | 0 1024 | 0 2048 | 4 4096 | 9 8192 | 22 16384 | 37 32768 |@ 99 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 3858 131072 | 0 SWND(bytes) 10.175.96.92 80 value ------------- Distribution ------------- count 512 | 0 1024 | 1 2048 | 0 4096 | 2 8192 | 4 16384 | 7 32768 | 14 65536 |@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ 1956 131072 | 0

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  • How Do You Actually Model Data?

    Since the 1970’s Developers, Analysts and DBAs have been able to represent concepts and relations in the form of data through the use of generic symbols.  But what is data modeling?  The first time I actually heard this term I could not understand why anyone would want to display a computer on a fashion show runway. Hey, what do you expect? At that time I was a freshman in community college, and obviously this was a long time ago.  I have since had the chance to learn what data modeling truly is through using it. Data modeling is a process of breaking down information and/or requirements in to common categories called objects. Once objects start being defined then relationships start to form based on dependencies found amongst other existing objects.  Currently, there are several tools on the market that help data designer actually map out objects and their relationships through the use of symbols and lines.  These diagrams allow for designs to be review from several perspectives so that designers can ensure that they have the optimal data design for their project and that the design is flexible enough to allow for potential changes and/or extension in the future. Additionally these basic models can always be further refined to show different levels of details depending on the target audience through the use of three different types of models. Conceptual Data Model(CDM)Conceptual Data Models include all key entities and relationships giving a viewer a high level understanding of attributes. Conceptual data model are created by gathering and analyzing information from various sources pertaining to a project during the typical planning phase of a project. Logical Data Model (LDM)Logical Data Models are conceptual data models that have been expanded to include implementation details pertaining to the data that it will store. Additionally, this model typically represents an origination’s business requirements and business rules by defining various attribute data types and relationships regarding each entity. This additional information can be directly translated to the Physical Data Model which reduces the actual time need to implement it. Physical Data Model(PDMs)Physical Data Model are transformed Logical Data Models that include the necessary tables, columns, relationships, database properties for the creation of a database. This model also allows for considerations regarding performance, indexing and denormalization that are applied through database rules, data integrity. Further expanding on why we actually use models in modern application/database development can be seen in the benefits that data modeling provides for data modelers and projects themselves, Benefits of Data Modeling according to Applied Information Science Abstraction that allows data designers remove concepts and ideas form hard facts in the form of data. This gives the data designers the ability to express general concepts and/or ideas in a generic form through the use of symbols to represent data items and the relationships between the items. Transparency through the use of data models allows complex ideas to be translated in to simple symbols so that the concept can be understood by all viewpoints and limits the amount of confusion and misunderstanding. Effectiveness in regards to tuning a model for acceptable performance while maintaining affordable operational costs. In addition it allows systems to be built on a solid foundation in terms of data. I shudder at the thought of a world without data modeling, think about it? Data is everywhere in our lives. Data modeling allows for optimizing a design for performance and the reduction of duplication. If one was to design a database without data modeling then I would think that the first things to get impacted would be database performance due to poorly designed database and there would be greater chances of unnecessary data duplication that would also play in to the excessive query times because unneeded records would need to be processed. You could say that a data designer designing a database is like a box of chocolates. You will never know what kind of database you will get until after it is built.

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  • SQL Server IO handling mechanism can be severely affected by high CPU usage

    - by sqlworkshops
    Are you using SSD or SAN / NAS based storage solution and sporadically observe SQL Server experiencing high IO wait times or from time to time your DAS / HDD becomes very slow according to SQL Server statistics? Read on… I need your help to up vote my connect item – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage. Instead of taking few seconds, queries could take minutes/hours to complete when CPU is busy.In SQL Server when a query / request needs to read data that is not in data cache or when the request has to write to disk, like transaction log records, the request / task will queue up the IO operation and wait for it to complete (task in suspended state, this wait time is the resource wait time). When the IO operation is complete, the task will be queued to run on the CPU. If the CPU is busy executing other tasks, this task will wait (task in runnable state) until other tasks in the queue either complete or get suspended due to waits or exhaust their quantum of 4ms (this is the signal wait time, which along with resource wait time will increase the overall wait time). When the CPU becomes free, the task will finally be run on the CPU (task in running state).The signal wait time can be up to 4ms per runnable task, this is by design. So if a CPU has 5 runnable tasks in the queue, then this query after the resource becomes available might wait up to a maximum of 5 X 4ms = 20ms in the runnable state (normally less as other tasks might not use the full quantum).In case the CPU usage is high, let’s say many CPU intensive queries are running on the instance, there is a possibility that the IO operations that are completed at the Hardware and Operating System level are not yet processed by SQL Server, keeping the task in the resource wait state for longer than necessary. In case of an SSD, the IO operation might even complete in less than a millisecond, but it might take SQL Server 100s of milliseconds, for instance, to process the completed IO operation. For example, let’s say you have a user inserting 500 rows in individual transactions. When the transaction log is on an SSD or battery backed up controller that has write cache enabled, all of these inserts will complete in 100 to 200ms. With a CPU intensive parallel query executing across all CPU cores, the same inserts might take minutes to complete. WRITELOG wait time will be very high in this case (both under sys.dm_io_virtual_file_stats and sys.dm_os_wait_stats). In addition you will notice a large number of WAITELOG waits since log records are written by LOG WRITER and hence very high signal_wait_time_ms leading to more query delays. However, Performance Monitor Counter, PhysicalDisk, Avg. Disk sec/Write will report very low latency times.Such delayed IO handling also occurs to read operations with artificially very high PAGEIOLATCH_SH wait time (with number of PAGEIOLATCH_SH waits remaining the same). This problem will manifest more and more as customers start using SSD based storage for SQL Server, since they drive the CPU usage to the limits with faster IOs. We have a few workarounds for specific scenarios, but we think Microsoft should resolve this issue at the product level. We have a connect item open – https://connect.microsoft.com/SQLServer/feedback/details/744650/sql-server-io-handling-mechanism-can-be-severely-affected-by-high-cpu-usage - (with example scripts) to reproduce this behavior, please up vote the item so the issue will be addressed by the SQL Server product team soon.Thanks for your help and best regards,Ramesh MeyyappanHome: www.sqlworkshops.comLinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • WebLogic Server Performance and Tuning: Part II - Thread Management

    - by Gokhan Gungor
    WebLogic Server, like any other java application server, provides resources so that your applications use them to provide services. Unfortunately none of these resources are unlimited and they must be managed carefully. One of these resources is threads which are pooled to provide better throughput and performance along with the fast response time and to avoid deadlocks. Threads are execution points that WebLogic Server delivers its power and execute work. Managing threads is very important because it may affect the overall performance of the entire system. In previous releases of WebLogic Server 9.0 we had multiple execute queues and user defined thread pools. There were different queues for different type of work which had fixed number of execute threads.  Tuning of this thread pools and finding the proper number of threads was time consuming which required many trials. WebLogic Server 9.0 and the following releases use a single thread pool and a single priority-based execute queue. All type of work is executed in this single thread pool. Its size (thread count) is automatically decreased or increased (self-tuned). The new “self-tuning” system simplifies getting the proper number of threads and utilizing them.Work manager allows your applications to run concurrently in multiple threads. Work manager is a mechanism that allows you to manage and utilize threads and create rules/guidelines to follow when assigning requests to threads. We can set a scheduling guideline or priority a request with a work manager and then associate this work manager with one or more applications. At run-time, WebLogic Server uses these guidelines to assign pending work/requests to execution threads. The position of a request in the execute queue is determined by its priority. There is a default work manager that is provided. The default work manager should be sufficient for most applications. However there can be cases you want to change this default configuration. Your application(s) may be providing services that need mixture of fast response time and long running processes like batch updates. However wrong configuration of work managers can lead a performance penalty while expecting improvement.We can define/configure work managers at;•    Domain Level: config.xml•    Application Level: weblogic-application.xml •    Component Level: weblogic-ejb-jar.xml or weblogic.xml(For a specific web application use weblogic.xml)We can use the following predefined rules/constraints to manage the work;•    Fair Share Request Class: Specifies the average thread-use time required to process requests. The default is 50.•    Response Time Request Class: Specifies a response time goal in milliseconds.•    Context Request Class: Assigns request classes to requests based on context information.•    Min Threads Constraint: Limits the number of concurrent threads executing requests.•    Max Threads Constraint: Guarantees the number of threads the server will allocate to requests.•    Capacity Constraint: Causes the server to reject requests only when it has reached its capacity. Let’s create a work manager for our application for a long running work.Go to WebLogic console and select Environment | Work Managers from the domain structure tree. Click New button and select Work manager and click next. Enter the name for the work manager and click next. Then select the managed server instances(s) or clusters from available targets (the one that your long running application is deployed) and finish. Click on MyWorkManager, and open the Configuration tab and check Ignore Stuck Threads and save. This will prevent WebLogic to tread long running processes (that is taking more than a specified time) as stuck and enable to finish the process.

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  • When things go awry

    - by Phil Factor
    The moment the Entrepreneur opened his mouth on prime-time national TV, spelled out the URL and waxed big on how exciting ‘his’ new website was, I knew I was in for a busy night. I’d designed and built it. All at once, half a million people tried to log into the website. Although all my stress-testing paid off, I have to admit that the network locked up tight long before there was any danger of a database or website problem. Soon afterwards, the Entrepreneur and the Big Boss were there in the autopsy meeting. We picked through all our systems in detail to see how they’d borne the unexpected strain. Mercifully, in view of the sour mood of the Big Boss, it turned out that the only thing we could have done better was buy a bigger pipe to and from the internet. We’d specified that ‘big pipe’ when designing the system. The Big Boss had then railed at the cost and so we’d subsequently compromised. I felt that my design decisions were vindicated. The Big Boss brooded for a while. Then he made the significant comment: “What really ****** me off is the fact that, for ten minutes, we couldn’t take people’s money.” At that point I stopped feeling smug. Had the internet connection been better, the system would have reached its limit and failed rather precipitously, and that wasn’t what he wanted. Then it occurred to me that what had gummed up the connection was all those images on the site, that had made it so impressive for the visitors. If there had been a way to automatically pare down the site to the bare essentials under stress… Hmm. I began to consider disaster-recovery in the broadest sense – maintaining a service in spite of unusual or unexpected events. What he said makes a lot of sense: sacrifice whatever isn’t essential to keep the core service running when we approach the capacity limits. Maybe in IT we should borrow (or revive) the business concept of the ‘Skeleton service’, maintaining only the priority parts under stress, using a process that is well-prepared and carefully rehearsed. How might this work? Whatever the event we have to prepare for, it is all about understanding the priorities; knowing what one can dispense with when the going gets tough. In the event of database disaster, it’s much faster to deploy a skeletal system with only the essential data than to restore the entire system, though there would have to be a reconciliation process to update the revived database retrospectively, once the emergency was over. It isn’t just the database that could be designed for resilience. One could prepare for unusually high traffic in a website by designing a system that degraded gradually to a ‘skeletal’ site, one that maintained the commercial essentials without fat images, JavaScript libraries and razzmatazz. This is all what the Big Boss scathingly called ‘a mere technicality’. It seems to me that what is needed first is a culture of application and database design which acknowledges that we live in a very imperfect world, and react accordingly when things go awry.

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  • System.Runtime.InteropServices.COMException (0x80070008): Not enough storage is available to process

    - by Darryl Braaten
    I am trying to diagnose this exception. "System.Runtime.InteropServices.COMException (0x80070008): Not enough storage is available to process this command. (Exception from HRESULT: 0x80070008) at System.Runtime.Remoting.RemotingServices.AllocateUninitializedObject(RuntimeType objectType) at System.Runtime.Remoting.RemotingServices.AllocateUninitializedObject(Type objectType) at System.Runtime.Remoting.Activation.ActivationServices.CreateInstance(Type serverType) at System.Runtime.Remoting.Activation.ActivationServices.IsCurrentContextOK(Type serverType, Object[] props, Boolean bNewObj) at Oracle.DataAccess.Client.CThreadPool..ctor() at Oracle.DataAccess.Client.OracleCommand.set_CommandTimeout(Int32 value) ... It does not look like any of the normal types of "storage" have hit any limits. The application is using about 400MB of memory, 70 threads, 2000 handles and the hard drive has many GB free. The machine is running Windows 2003 Enterprise server with 16GB of RAM so memory shouldn't be an issue. The application is running as a windows service so there are no GDI objects being used. Running out of GDI handles is a common cause of this exception. Database connections, commands & readers are all all wrapped with using blocks so they should be getting cleaned up correctly.

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  • Notification Email Best Practices--From Server Setup to Programming

    - by Andrew Wagner
    All, I'm in the process now of building a SaaS tool that allows network admins to generate notification emails to the members of the end-users of our platform (among many many other things). I'm running into a bit of an "out of my expertise" wall, as I know there are a lot of variables involved with configuring an application that can: Run in a distributed way via load balancing and still-- Leverage a single mail server for sending notification emails Process unsubscribe requests Avoid any ISP blacklisting in the process. If anyone has the time and has done this before, I'd love if you could walk me through the A-Z of best practices both from a configuration perspective and an execution perspective for generating these emails (anything from necessary DNS settings to ideal SMTP setup and configuration) Currently, our application generates email via Google Apps using the PHPMailer class. While this works well, it doesn't queue messages (potential for timeout problems if any of our clients amass a very large list of end-users), and Google limits the amount of allowed generated email messages to 500/day. I know this is a lofty question, but any guidance you could provide would be smashing and a big help as we work through this hurtle in our beta development stage. Thanks!

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  • Any task-control algorithms programming practices?

    - by NumberFour
    Hi, I was just wondering if there's any field which concerns the task-control programming (or at least that's the way I call it). For a better explanation of task-control consider the following scenario: An application (master-thread) waits for a command - which might be a particular action or a set of actions the application should perform. When a command is received the master-thread creates a task (= spawns an independent thread which actually does the action) and adds a record in it's task-list - thus keeping track of the time of execution, thread handle, task priority...etc. The master-thread awaits for any other incoming commands while taking care of all the tasks - e.g: kills tasks running too long, prioritizes tasks with higher priorities, kills a task on a request of another task, limits the number of currently running tasks, allows task scheduling, cleans finished tasks (threads) and so on. The model is pretty similar to what we can see in OS dealing with running processes. Are there any good practices programming such task-models or is there some theoretical work done in this field? Maybe my question is too generalized, but at least I wanted to know whether there are any experiences working on such models or if there's a better approach. Thanks for any answers.

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