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  • Detecting Duplicates Using Oracle Business Rules

    - by joeywong-Oracle
    Recently I was involved with a Business Process Management Proof of Concept (BPM PoC) where we wanted to show how customers could use Oracle Business Rules (OBR) to easily define some rules to detect certain conditions, such as duplicate account numbers, duplicate names, high transaction amounts, etc, in a set of transactions. Traditionally you would have to loop through the transactions and compare each transaction with each other to find matching conditions. This is not particularly nice as it relies on more traditional approaches (coding) and is not the most efficient way. OBR is a great place to house these types’ of rules as it allows users/developers to externalise the rules, in a simpler manner, externalising the rules from the message flows and allows users to change them when required. So I went ahead looking for some examples. After quite a bit of time spent Googling, I did not find much out in the blogosphere. In fact the best example was actually from...... wait for it...... Oracle Documentation! (http://docs.oracle.com/cd/E28271_01/user.1111/e10228/rules_start.htm#ASRUG228) However, if you followed the link there was not much explanation provided with the example. So the aim of this article is to provide a little more explanation to the example so that it can be better understood. Note: I won’t be covering the BPM parts in great detail. Use case: Payment instruction file is required to be processed. Before instruction file can be processed it needs to be approved by a business user. Before the approval process, it would be useful to run the payment instruction file through OBR to look for transactions of interest. The output of the OBR can then be used to flag the transactions for the approvers to investigate. Example BPM Process So let’s start defining the Business Rules Dictionary. For the input into our rules, we will be passing in an array of payments which contain some basic information for our demo purposes. Input to Business Rules And for our output we want to have an array of rule output messages. Note that the element I am using for the output is only for one rule message element and not an array. We will configure the Business Rules component later to return an array instead. Output from Business Rules Business Rule – Create Dictionary Fill in all the details and click OK. Open the Business Rules component and select Decision Functions from the side. Modify the Decision Function Configuration Select the decision function and click on the edit button (the pencil), don’t worry that JDeveloper indicates that there is an error with the decision function. Then click the Ouputs tab and make sure the checkbox under the List column is checked, this is to tell the Business Rules component that it should return an array of rule message elements. Updating the Decision Service Next we will define the actual rules. Click on Ruleset1 on the side and then the Create Rule in the IF/THEN Rule section. Creating new rule in ruleset Ok, this is where some detailed explanation is required. Remember that the input to this Business Rules dictionary is a list of payments, each of those payments were of the complex type PaymentType. Each of those payments in the Oracle Business Rules engine is treated as a fact in its working memory. Implemented rule So in the IF/THEN rule, the first task is to grab two PaymentType facts from the working memory and assign them to temporary variable names (payment1 and payment2 in our example). Matching facts Once we have them in the temporary variables, we can then start comparing them to each other. For our demonstration we want to find payments where the account numbers were the same but the account name was different. Suspicious payment instruction And to stop the rule from comparing the same facts to each other, over and over again, we have to include the last test. Stop rule from comparing endlessly And that’s it! No for loops, no need to keep track of what you have or have not compared, OBR handles all that for you because everything is done in its working memory. And once all the tests have been satisfied we need to assert a new fact for the output. Assert the output fact Save your Business Rules. Next step is to complete the data association in the BPM process. Pay extra care to use Copy List instead of the default Copy when doing data association at an array level. Input and output data association Deploy and test. Test data Rule matched Parting words: Ideally you would then use the output of the Business Rules component to then display/flag the transactions which triggered the rule so that the approver can investigate. Link: SOA Project Archive [Download]

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  • CD/DVD drive not mounted when inserted with Disc of any kind

    - by Cisco Sán
    I just noticed that if a insert a CD or a DVD of any kind, the Drive will start spinning but it will not show the mounted disc. Before it used to ask me what to do with the media inserted. Now it doesn't even do that. I ran in the terminal this code: eject -n and it displays this: " eject: device is `/dev/sr0'" what can I do to get the functionality back on my drive. also ran this command: sudo mount -o ro,unhide,uid=1000 /dev/cdrom /mnt/cdrom but in return i get this: " mount: mount point /mnt/cdrom does not exist" Running Ubuntu 11.10 HERE IS THE HISTORY UNTIL NOW thanks Waltinator: I ran the 'dmesg' but don't know what I'm looking for. Im a newbie on this. The same thing with the 'ls -rlt /var/log' command. Should I create the directory for the mount? at this point really don't know what to do. – Cisco Sán 7 hours ago Here are 3 lines from my dmesg after I successfully inserted a CD: [ 4804.416018] wlan0: no IPv6 routers present [ 8214.125450] ISdit ISO 9660 Extensions: Microsoft Joliet Level 3 [ 8214.136556] ISO 9660 Extensions: RRIP_1991A The first line is a previous event, my wireless going online. The next 2 lines are a good result. The number in square brackets is "seconds since boot", the rest of the line is usually helpful. And no, you should NOT create the mount point. Let's try to get the automatic mounting to work. – waltinator 7 hours ago ok this are my last 3 lines on the 'dmesg' [ 18.130819] init: plymouth-stop pre-start process (1396) terminated with status 1 [ 28.780011] wlan0: no IPv6 routers present [ 505.632119] CE: hpet increased min_delta_ns to 20113 nsec – Cisco Sán 6 hours ago It looks like your CD/DVD drive is not connected to the data bus, and not causing an interrupt when you insert a platter. – waltinator 6 hours ago Try dmesg | grep -A8 CD-ROM which should show you what the system thought was available when it came up. – waltinator 6 hours ago here is my printout [0.774351] scsi 0:0:0:0: CD-ROM HL-DT-ST DVD+-RW GSA-T40N A100 PQ: 0 ANSI: 5 [0.778117] sr0: scsi3-mmc drive: 24x/24x writer dvd-ram cd/rw xa/form2 cdda tray [0.778122] cdrom: Uniform CD-ROM driver Revision: 3.20 [0.778282] sr 0:0:0:0: Attached scsi CD-ROM sr0 [0.778340] sr 0:0:0:0: Attached scsi generic sg0 type 5 [0.780416] Freeing unused kernel memory: 984k freed [0.780732] Write protecting the kernel read-only data: 10240k [0.780986] Freeing unused kernel memory: 20k freed [0.786331] Freeing unused kernel memory: 1400k freed [0.804912] udevd[90]: starting version 173 [0.874178] r8169 Gigabit Ethernet driver 2.3LK-NAPI loaded [0.874208] r8169 0000:02:00.0: PCI INT A - GSI 16 (level, low) - IRQ 16 OK, your system sees the drive. Can you open and close the tray with eject and eject -t? Run udevadm monitor while you insert a CD (type ^C when done) and see if you get "change" and "add" messages. – waltinator 6 hours ago ok, "eject" works perfectly "eject -t" does nothing. this is the message for "udevadm monitor": KERNEL[13771.009267] change /devices/pci0000:00/0000:00:1f.1/host0/target0:0:0/0:0:0:0/block/sr0 (block) UDEV [13773.878887] change /devices/pci0000:00/0000:00:1f.1/host0/target0:0:0/0:0:0 /block/sr0 (block) – Cisco Sán 6 hours ago sudo hwinfo --cdrom (the hwinfo package is installable through Software Center) describes my CD-ROM, try it. – waltinator 4 hours ago My read out from the "sudo hwinfo --cdrom" are the following: hal.1: read hal dataprocess 2753: arguments to dbus_move_error() were incorrect, assertion "(dest) == NULL || !dbus_error_is_set ((dest))" failed in file ../../dbus/dbus-errors.c line 280. This is normally a bug in some application using the D-Bus library. libhal.c 3483 : Error unsubscribing to signals, error=The name org.freedesktop.Hal was not provided by any .service files 22: SCSI 00.0: 10602 CD-ROM (DVD) [Created at block.247] Unique ID: KD9E.JgkxTS4hgl2 Parent ID: 3p2J.gdUMCD83e+E SysFS ID: /class/block/sr0 SysFS BusID: 0:0:0:0 SysFS Device Link: /devices/pci0000:00/0000:00:1f.1/host0/target0:0:0/0:0:0:0 Hardware Class: cdrom Model: "HL-DT-ST DVD+-RW GSA-T40N" Vendor: "HL-DT-ST" Device: "DVD+-RW GSA-T40N" Revision: "A100" Driver: "ata_piix", "sr" Driver Modules: "ata_piix" Device File: /dev/sr0 (/dev/sg0) Device Files: /dev/sr0, /dev/scd0, /dev/disk/by-id/ata-HL-DT-ST_DVD+_-RW_GSA-T40N_K048BJ74257, /dev/disk/by-path/pci-0000:00:1f.1-scsi-0:0:0:0, /dev/cdrom, /dev/cdrw, /dev/dvd, /dev/dvdrw Device Number: block 11:0 (char 21:0) Features: DVD Config Status: cfg=new, avail=yes, need=no, active=unknown Attached to: #17 (IDE interface) Drive Speed: 31 Volume ID: "Movie" Publisher: "INTERVIDEO" Creation date: "20050424162207000" Thanks for the help. To Castro, hope this is what you meant and sorry for the comments..

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  • Intel Centrino Wireless-N 1000 Again ! Ubuntu 13.04 x64

    - by vafa
    First I have to say that I tried everything written about this concept. The problem is that it stops working randomly in 3 main forms : 1 - sometimes it disconnect from wireless network and reconnect automatically 2 - sometimes it disconnect and wont connect no matter what (needs reboot) 3 - some times it's still connected but cannot ping or surf or whatever. I already tried disabling N mod using these commands : sudo modprobe -r iwlwifi modprobe iwlwifi 11n_disable=1 (or 0, whatever) it didn't help . these are the results of lspci, sudo lshw -C network, ifconfig, iwconfig, rfkill list when it disconnected and didn't connect till reboot : ifconfig : eth0 Link encap:Ethernet HWaddr c8:0a:a9:34:65:77 UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:1563213476557380 errors:9379306629148050 dropped:3126435543049350 overruns:1563217771524675 frame:7816088857623375 TX packets:1563217771524675 errors:6252871086098700 dropped:0 overruns:1563217771524675 carrier:3126435543049350 collisions:7816088857623375 txqueuelen:1000 RX bytes:1563217771524675 (1.5 PB) TX bytes:1563217771524675 (1.5 PB) ham0 Link encap:Ethernet HWaddr 7a:79:19:a5:e4:93 inet addr:25.165.228.147 Bcast:25.255.255.255 Mask:255.0.0.0 inet6 addr: fe80::7879:19ff:fea5:e493/64 Scope:Link inet6 addr: 2620:9b::19a5:e493/96 Scope:Global UP BROADCAST RUNNING MULTICAST MTU:1404 Metric:1 RX packets:7743 errors:0 dropped:0 overruns:0 frame:0 TX packets:1250 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:500 RX bytes:665642 (665.6 KB) TX bytes:204056 (204.0 KB) lo Link encap:Local Loopback inet addr:127.0.0.1 Mask:255.0.0.0 inet6 addr: ::1/128 Scope:Host UP LOOPBACK RUNNING MTU:65536 Metric:1 RX packets:41138 errors:0 dropped:0 overruns:0 frame:0 TX packets:41138 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:6420962 (6.4 MB) TX bytes:6420962 (6.4 MB) wlan0 Link encap:Ethernet HWaddr 00:1e:64:45:fb:70 inet6 addr: fe80::21e:64ff:fe45:fb70/64 Scope:Link UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:286999 errors:0 dropped:0 overruns:0 frame:0 TX packets:226966 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:324386887 (324.3 MB) TX bytes:30674804 (30.6 MB) iwconfig : ham0 no wireless extensions. eth0 no wireless extensions. lo no wireless extensions. wlan0 IEEE 802.11bg ESSID:off/any Mode:Managed Access Point: Not-Associated Tx-Power=14 dBm Retry long limit:7 RTS thr:off Fragment thr:off Power Management:off sudo lshw -C network: *-network description: Wireless interface product: Centrino Wireless-N 1000 [Condor Peak] vendor: Intel Corporation physical id: 0 bus info: pci@0000:07:00.0 logical name: wlan0 version: 00 serial: 00:1e:64:45:fb:70 width: 64 bits clock: 33MHz capabilities: pm msi pciexpress bus_master cap_list ethernet physical wireless configuration: broadcast=yes driver=iwlwifi driverversion=3.8.0-30-generic firmware=39.31.5.1 build 35138 latency=0 link=no multicast=yes wireless=IEEE 802.11bg resources: irq:46 memory:c0400000-c0401fff *-network description: Ethernet interface product: AR8131 Gigabit Ethernet vendor: Qualcomm Atheros physical id: 0 bus info: pci@0000:09:00.0 logical name: eth0 version: c0 serial: c8:0a:a9:34:65:77 capacity: 1Gbit/s width: 64 bits clock: 33MHz capabilities: pm msi pciexpress vpd cap_list ethernet physical tp 10bt 10bt-fd 100bt 100bt-fd 1000bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=atl1c driverversion=1.0.1.1-NAPI latency=0 link=no multicast=yes port=twisted pair resources: irq:47 memory:c0900000-c093ffff ioport:5000(size=128) *-network description: Ethernet interface physical id: 2 logical name: ham0 serial: 7a:79:19:a5:e4:93 size: 10Mbit/s capabilities: ethernet physical configuration: autonegotiation=off broadcast=yes driver=tun driverversion=1.6 duplex=full ip=25.165.228.147 link=yes multicast=yes port=twisted pair speed=10Mbit/s lspci: 00:00.0 Host bridge: Intel Corporation Mobile 4 Series Chipset Memory Controller Hub (rev 07) 00:01.0 PCI bridge: Intel Corporation Mobile 4 Series Chipset PCI Express Graphics Port (rev 07) 00:1a.0 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #4 (rev 03) 00:1a.1 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #5 (rev 03) 00:1a.7 USB controller: Intel Corporation 82801I (ICH9 Family) USB2 EHCI Controller #2 (rev 03) 00:1b.0 Audio device: Intel Corporation 82801I (ICH9 Family) HD Audio Controller (rev 03) 00:1c.0 PCI bridge: Intel Corporation 82801I (ICH9 Family) PCI Express Port 1 (rev 03) 00:1c.3 PCI bridge: Intel Corporation 82801I (ICH9 Family) PCI Express Port 4 (rev 03) 00:1c.5 PCI bridge: Intel Corporation 82801I (ICH9 Family) PCI Express Port 6 (rev 03) 00:1d.0 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #1 (rev 03) 00:1d.1 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #2 (rev 03) 00:1d.2 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #3 (rev 03) 00:1d.3 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #6 (rev 03) 00:1d.7 USB controller: Intel Corporation 82801I (ICH9 Family) USB2 EHCI Controller #1 (rev 03) 00:1e.0 PCI bridge: Intel Corporation 82801 Mobile PCI Bridge (rev 93) 00:1f.0 ISA bridge: Intel Corporation ICH9M LPC Interface Controller (rev 03) 00:1f.2 SATA controller: Intel Corporation 82801IBM/IEM (ICH9M/ICH9M-E) 4 port SATA Controller [AHCI mode] (rev 03) 00:1f.3 SMBus: Intel Corporation 82801I (ICH9 Family) SMBus Controller (rev 03) 01:00.0 VGA compatible controller: NVIDIA Corporation G98M [GeForce G 105M] (rev a1) 07:00.0 Network controller: Intel Corporation Centrino Wireless-N 1000 [Condor Peak] 09:00.0 Ethernet controller: Qualcomm Atheros AR8131 Gigabit Ethernet (rev c0) rfkill list : 1: acer-wireless: Wireless LAN Soft blocked: no Hard blocked: no 2: acer-bluetooth: Bluetooth Soft blocked: yes Hard blocked: no 9: phy0: Wireless LAN Soft blocked: no Hard blocked: no any help will be REALLLYYYY appreciated

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  • Atheros AR2413 wireless not working after shutdown

    - by Chandrasekhar
    I am using a Ubuntu 11.04 on an Acer aspire 3680 laptop and my wifi is not working. I followed the below commands to install the madwifi driver: sudo su apt-get install subversion cd /usr/src svn checkout http://madwifi-project.org/svn/madwifi/trunk madwifi tar cfvz madwifi.tgz cd madwifi make && make install echo "blacklist ath5k" /etc/modprobe.d/blacklist.conf echo "ath_pci" /etc/modules modprobe ath_pci sudo reboot After installation I am facing the same problem. My wifi wont work after I shutdown. Infact it didn't work after suspend but I rectified that problem by the following commands: Command 1: sudo rmmod -f ath_pci sudo rfkill unblock all sudo modprobe ath_pci along with the command SUSPEND_MODULES=ath_pci added to the /etc/pm/config.d/madwifi directory. So if I suspend and then on my laptop the wifi loads well and doesn't create a problem. But if I shutdown my laptop the wifi never loads again and eachtime I have to run a Ubuntu 9.04 live CD to load it. I did try adding the Command 1 to the /etc/rc.local directory but still it doesn't work. So my question is: What should I do in order to make my wireless work without having to run a live CD of ubuntu 9.04 everytime after shutdown? Thanks. Here are the outputs which one might need: Output 1 chandru@chandru-acer:~$ lspci 00:00.0 Host bridge: Intel Corporation Mobile 945GM/PM/GMS, 943/940GML and 945GT Express Memory Controller Hub (rev 03) 00:02.0 VGA compatible controller: Intel Corporation Mobile 945GM/GMS, 943/940GML Express Integrated Graphics Controller (rev 03) 00:02.1 Display controller: Intel Corporation Mobile 945GM/GMS/GME, 943/940GML Express Integrated Graphics Controller (rev 03) 00:1b.0 Audio device: Intel Corporation N10/ICH 7 Family High Definition Audio Controller (rev 02) 00:1c.0 PCI bridge: Intel Corporation N10/ICH 7 Family PCI Express Port 1 (rev 02) 00:1c.1 PCI bridge: Intel Corporation N10/ICH 7 Family PCI Express Port 2 (rev 02) 00:1c.2 PCI bridge: Intel Corporation N10/ICH 7 Family PCI Express Port 3 (rev 02) 00:1d.0 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #1 (rev 02) 00:1d.1 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #2 (rev 02) 00:1d.2 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #3 (rev 02) 00:1d.3 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #4 (rev 02) 00:1d.7 USB Controller: Intel Corporation N10/ICH 7 Family USB2 EHCI Controller (rev 02) 00:1e.0 PCI bridge: Intel Corporation 82801 Mobile PCI Bridge (rev e2) 00:1f.0 ISA bridge: Intel Corporation 82801GBM (ICH7-M) LPC Interface Bridge (rev 02) 00:1f.2 IDE interface: Intel Corporation 82801GBM/GHM (ICH7 Family) SATA IDE Controller (rev 02) 00:1f.3 SMBus: Intel Corporation N10/ICH 7 Family SMBus Controller (rev 02) 02:00.0 Ethernet controller: Marvell Technology Group Ltd. 88E8038 PCI-E Fast Ethernet Controller (rev 14) 0a:03.0 Ethernet controller: Atheros Communications Inc. AR2413 802.11bg NIC (rev 01) 0a:09.0 CardBus bridge: Texas Instruments PCIxx12 Cardbus Controller 0a:09.2 Mass storage controller: Texas Instruments 5-in-1 Multimedia Card Reader (SD/MMC/MS/MS PRO/xD) Output 2: lsmod Module Size Used by wlan_tkip 17074 2 binfmt_misc 13213 1 parport_pc 32111 0 ppdev 12849 0 snd_hda_codec_si3054 12924 1 snd_hda_codec_realtek 255882 1 joydev 17322 0 snd_atiixp_modem 18624 0 snd_via82xx_modem 18305 0 snd_intel8x0m 18493 0 snd_ac97_codec 105614 3 snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m snd_hda_intel 24113 2 ac97_bus 12642 1 snd_ac97_codec snd_hda_codec 90901 3 snd_hda_codec_si3054,snd_hda_codec_realtek,snd_hda_intel i915 451053 3 snd_hwdep 13274 1 snd_hda_codec snd_pcm 80042 7 snd_hda_codec_si3054,snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m,snd_ac97_codec,snd_hda_intel,snd_hda_codec snd_seq_midi 13132 0 snd_rawmidi 25269 1 snd_seq_midi drm_kms_helper 40971 1 i915 snd_seq_midi_event 14475 1 snd_seq_midi snd_seq 51291 2 snd_seq_midi,snd_seq_midi_event pcmcia 39671 0 snd_timer 28659 2 snd_pcm,snd_seq snd_seq_device 14110 3 snd_seq_midi,snd_rawmidi,snd_seq drm 184164 4 i915,drm_kms_helper yenta_socket 27230 0 tifm_7xx1 12898 0 wlan_scan_sta 21945 1 ath_rate_sample 17279 1 pcmcia_rsrc 18292 1 yenta_socket psmouse 73312 0 tifm_core 15040 1 tifm_7xx1 snd 55295 18 snd_hda_codec_si3054,snd_hda_codec_realtek,snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m,snd_ac97_codec,snd_hda_intel,snd_hda_codec,snd_hwdep,snd_pcm,snd_rawmidi,snd_seq,snd_timer,snd_seq_device serio_raw 12990 0 i2c_algo_bit 13184 1 i915 soundcore 12600 1 snd pcmcia_core 21505 3 pcmcia,yenta_socket,pcmcia_rsrc video 19112 1 i915 ath_pci 183044 0 snd_page_alloc 14073 5 snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m,snd_hda_intel,snd_pcm wlan 224640 5 wlan_tkip,wlan_scan_sta,ath_rate_sample,ath_pci ath_hal 398701 3 ath_rate_sample,ath_pci lp 13349 0 parport 36746 3 parport_pc,ppdev,lp usbhid 41704 0 hid 77084 1 usbhid sky2 49172 0 Output 3 root@chandru-acer:~# lshw -C network PCI (sysfs) *-network description: Ethernet interface product: 88E8038 PCI-E Fast Ethernet Controller vendor: Marvell Technology Group Ltd. physical id: 0 bus info: pci@0000:02:00.0 logical name: eth0 version: 14 serial: 00:16:36:fb:aa:64 capacity: 100Mbit/s width: 64 bits clock: 33MHz capabilities: pm vpd msi pciexpress bus_master cap_list ethernet physical tp 10bt 10bt-fd 100bt 100bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=sky2 driverversion=1.28 firmware=N/A latency=0 link=no multicast=yes port=twisted pair resources: irq:43 memory:44000000-44003fff ioport:2000(size=256) *-network description: Wireless interface product: AR2413 802.11bg NIC vendor: Atheros Communications Inc. physical id: 3 bus info: pci@0000:0a:03.0 logical name: wifi0 version: 01 serial: 00:19:7d:d3:0c:fd width: 32 bits clock: 33MHz capabilities: pm bus_master cap_list logical ethernet physical wireless configuration: broadcast=yes driver=ath_pci ip=192.168.1.6 latency=96 maxlatency=28 mingnt=10 multicast=yes wireless=IEEE 802.11g resources: irq:18 memory:d0000000-d000ffff Output 4 root@chandru-acer:~# lsmod | grep ath_pci ath_pci 183044 0 wlan 224640 5 wlan_tkip,wlan_scan_sta,ath_rate_sample,ath_pci ath_hal 398701 3 ath_rate_sample,ath_pci

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  • Oracle NoSQL Database Exceeds 1 Million Mixed YCSB Ops/Sec

    - by Charles Lamb
    We ran a set of YCSB performance tests on Oracle NoSQL Database using SSD cards and Intel Xeon E5-2690 CPUs with the goal of achieving 1M mixed ops/sec on a 95% read / 5% update workload. We used the standard YCSB parameters: 13 byte keys and 1KB data size (1,102 bytes after serialization). The maximum database size was 2 billion records, or approximately 2 TB of data. We sized the shards to ensure that this was not an "in-memory" test (i.e. the data portion of the B-Trees did not fit into memory). All updates were durable and used the "simple majority" replica ack policy, effectively 'committing to the network'. All read operations used the Consistency.NONE_REQUIRED parameter allowing reads to be performed on any replica. In the past we have achieved 100K ops/sec using SSD cards on a single shard cluster (replication factor 3) so for this test we used 10 shards on 15 Storage Nodes with each SN carrying 2 Rep Nodes and each RN assigned to its own SSD card. After correcting a scaling problem in YCSB, we blew past the 1M ops/sec mark with 8 shards and proceeded to hit 1.2M ops/sec with 10 shards.  Hardware Configuration We used 15 servers, each configured with two 335 GB SSD cards. We did not have homogeneous CPUs across all 15 servers available to us so 12 of the 15 were Xeon E5-2690, 2.9 GHz, 2 sockets, 32 threads, 193 GB RAM, and the other 3 were Xeon E5-2680, 2.7 GHz, 2 sockets, 32 threads, 193 GB RAM.  There might have been some upside in having all 15 machines configured with the faster CPU, but since CPU was not the limiting factor we don't believe the improvement would be significant. The client machines were Xeon X5670, 2.93 GHz, 2 sockets, 24 threads, 96 GB RAM. Although the clients had 96 GB of RAM, neither the NoSQL Database or YCSB clients require anywhere near that amount of memory and the test could have just easily been run with much less. Networking was all 10GigE. YCSB Scaling Problem We made three modifications to the YCSB benchmark. The first was to allow the test to accommodate more than 2 billion records (effectively int's vs long's). To keep the key size constant, we changed the code to use base 32 for the user ids. The second change involved to the way we run the YCSB client in order to make the test itself horizontally scalable.The basic problem has to do with the way the YCSB test creates its Zipfian distribution of keys which is intended to model "real" loads by generating clusters of key collisions. Unfortunately, the percentage of collisions on the most contentious keys remains the same even as the number of keys in the database increases. As we scale up the load, the number of collisions on those keys increases as well, eventually exceeding the capacity of the single server used for a given key.This is not a workload that is realistic or amenable to horizontal scaling. YCSB does provide alternate key distribution algorithms so this is not a shortcoming of YCSB in general. We decided that a better model would be for the key collisions to be limited to a given YCSB client process. That way, as additional YCSB client processes (i.e. additional load) are added, they each maintain the same number of collisions they encounter themselves, but do not increase the number of collisions on a single key in the entire store. We added client processes proportionally to the number of records in the database (and therefore the number of shards). This change to the use of YCSB better models a use case where new groups of users are likely to access either just their own entries, or entries within their own subgroups, rather than all users showing the same interest in a single global collection of keys. If an application finds every user having the same likelihood of wanting to modify a single global key, that application has no real hope of getting horizontal scaling. Finally, we used read/modify/write (also known as "Compare And Set") style updates during the mixed phase. This uses versioned operations to make sure that no updates are lost. This mode of operation provides better application behavior than the way we have typically run YCSB in the past, and is only practical at scale because we eliminated the shared key collision hotspots.It is also a more realistic testing scenario. To reiterate, all updates used a simple majority replica ack policy making them durable. Scalability Results In the table below, the "KVS Size" column is the number of records with the number of shards and the replication factor. Hence, the first row indicates 400m total records in the NoSQL Database (KV Store), 2 shards, and a replication factor of 3. The "Clients" column indicates the number of YCSB client processes. "Threads" is the number of threads per process with the total number of threads. Hence, 90 threads per YCSB process for a total of 360 threads. The client processes were distributed across 10 client machines. Shards KVS Size Clients Mixed (records) Threads OverallThroughput(ops/sec) Read Latencyav/95%/99%(ms) Write Latencyav/95%/99%(ms) 2 400m(2x3) 4 90(360) 302,152 0.76/1/3 3.08/8/35 4 800m(4x3) 8 90(720) 558,569 0.79/1/4 3.82/16/45 8 1600m(8x3) 16 90(1440) 1,028,868 0.85/2/5 4.29/21/51 10 2000m(10x3) 20 90(1800) 1,244,550 0.88/2/6 4.47/23/53

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  • CPU Usage in Very Large Coherence Clusters

    - by jpurdy
    When sizing Coherence installations, one of the complicating factors is that these installations (by their very nature) tend to be application-specific, with some being large, memory-intensive caches, with others acting as I/O-intensive transaction-processing platforms, and still others performing CPU-intensive calculations across the data grid. Regardless of the primary resource requirements, Coherence sizing calculations are inherently empirical, in that there are so many permutations that a simple spreadsheet approach to sizing is rarely optimal (though it can provide a good starting estimate). So we typically recommend measuring actual resource usage (primarily CPU cycles, network bandwidth and memory) at a given load, and then extrapolating from those measurements. Of course there may be multiple types of load, and these may have varying degrees of correlation -- for example, an increased request rate may drive up the number of objects "pinned" in memory at any point, but the increase may be less than linear if those objects are naturally shared by concurrent requests. But for most reasonably-designed applications, a linear resource model will be reasonably accurate for most levels of scale. However, at extreme scale, sizing becomes a bit more complicated as certain cluster management operations -- while very infrequent -- become increasingly critical. This is because certain operations do not naturally tend to scale out. In a small cluster, sizing is primarily driven by the request rate, required cache size, or other application-driven metrics. In larger clusters (e.g. those with hundreds of cluster members), certain infrastructure tasks become intensive, in particular those related to members joining and leaving the cluster, such as introducing new cluster members to the rest of the cluster, or publishing the location of partitions during rebalancing. These tasks have a strong tendency to require all updates to be routed via a single member for the sake of cluster stability and data integrity. Fortunately that member is dynamically assigned in Coherence, so it is not a single point of failure, but it may still become a single point of bottleneck (until the cluster finishes its reconfiguration, at which point this member will have a similar load to the rest of the members). The most common cause of scaling issues in large clusters is disabling multicast (by configuring well-known addresses, aka WKA). This obviously impacts network usage, but it also has a large impact on CPU usage, primarily since the senior member must directly communicate certain messages with every other cluster member, and this communication requires significant CPU time. In particular, the need to notify the rest of the cluster about membership changes and corresponding partition reassignments adds stress to the senior member. Given that portions of the network stack may tend to be single-threaded (both in Coherence and the underlying OS), this may be even more problematic on servers with poor single-threaded performance. As a result of this, some extremely large clusters may be configured with a smaller number of partitions than ideal. This results in the size of each partition being increased. When a cache server fails, the other servers will use their fractional backups to recover the state of that server (and take over responsibility for their backed-up portion of that state). The finest granularity of this recovery is a single partition, and the single service thread can not accept new requests during this recovery. Ordinarily, recovery is practically instantaneous (it is roughly equivalent to the time required to iterate over a set of backup backing map entries and move them to the primary backing map in the same JVM). But certain factors can increase this duration drastically (to several seconds): large partitions, sufficiently slow single-threaded CPU performance, many or expensive indexes to rebuild, etc. The solution of course is to mitigate each of those factors but in many cases this may be challenging. Larger clusters also lead to the temptation to place more load on the available hardware resources, spreading CPU resources thin. As an example, while we've long been aware of how garbage collection can cause significant pauses, it usually isn't viewed as a major consumer of CPU (in terms of overall system throughput). Typically, the use of a concurrent collector allows greater responsiveness by minimizing pause times, at the cost of reducing system throughput. However, at a recent engagement, we were forced to turn off the concurrent collector and use a traditional parallel "stop the world" collector to reduce CPU usage to an acceptable level. In summary, there are some less obvious factors that may result in excessive CPU consumption in a larger cluster, so it is even more critical to test at full scale, even though allocating sufficient hardware may often be much more difficult for these large clusters.

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  • Detect Unicode Usage in SQL Column

    One optimization you can make to a SQL table that is overly large is to change from nvarchar (or nchar) to varchar (or char).  Doing so will cut the size used by the data in half, from 2 bytes per character (+ 2 bytes of overhead for varchar) to only 1 byte per character.  However, you will lose the ability to store Unicode characters, such as those used by many non-English alphabets.  If the tables are storing user-input, and your application is or might one day be used internationally, its likely that using Unicode for your characters is a good thing.  However, if instead the data is being generated by your application itself or your development team (such as lookup data), and you can be certain that Unicode character sets are not required, then switching such columns to varchar/char can be an easy improvement to make. Avoid Premature Optimization If you are working with a lookup table that has a small number of rows, and is only ever referenced in the application by its numeric ID column, then you wont see any benefit to using varchar vs. nvarchar.  More generally, for small tables, you wont see any significant benefit.  Thus, if you have a general policy in place to use nvarchar/nchar because it offers more flexibility, do not take this post as a recommendation to go against this policy anywhere you can.  You really only want to act on measurable evidence that suggests that using Unicode is resulting in a problem, and that you wont lose anything by switching to varchar/char. Obviously the main reason to make this change is to reduce the amount of space required by each row.  This in turn affects how many rows SQL Server can page through at a time, and can also impact index size and how much disk I/O is required to respond to queries, etc.  If for example you have a table with 100 million records in it and this table has a column of type nchar(5), this column will use 5 * 2 = 10 bytes per row, and with 100M rows that works out to 10 bytes * 100 million = 1000 MBytes or 1GB.  If it turns out that this column only ever stores ASCII characters, then changing it to char(5) would reduce this to 5*1 = 5 bytes per row, and only 500MB.  Of course, if it turns out that it only ever stores the values true and false then you could go further and replace it with a bit data type which uses only 1 byte per row (100MB  total). Detecting Whether Unicode Is In Use So by now you think that you have a problem and that it might be alleviated by switching some columns from nvarchar/nchar to varchar/char but youre not sure whether youre currently using Unicode in these columns.  By definition, you should only be thinking about this for a column that has a lot of rows in it, since the benefits just arent there for a small table, so you cant just eyeball it and look for any non-ASCII characters.  Instead, you need a query.  Its actually very simple: SELECT DISTINCT(CategoryName)FROM CategoriesWHERE CategoryName <> CONVERT(varchar, CategoryName) Summary Gregg Stark for the tip. Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Why do I get an exception when playing multiple sound instances?

    - by Boreal
    Right now, I'm adding a rudimentary sound engine to my game. So far, I am able to load in a WAV file and play it once, then free up the memory when I close the game. However, the game crashes with a nice ArgumentOutOfBoundsException when I try to play another sound instance. Specified argument was out of the range of valid values. Parameter name: readLength I'm following this tutorial pretty much exactly, but I still keep getting the aforementioned error. Here's my sound-related code. /// <summary> /// Manages all sound instances. /// </summary> public static class Audio { static XAudio2 device; static MasteringVoice master; static List<SoundInstance> instances; /// <summary> /// The XAudio2 device. /// </summary> internal static XAudio2 Device { get { return device; } } /// <summary> /// Initializes the audio device and master track. /// </summary> internal static void Initialize() { device = new XAudio2(); master = new MasteringVoice(device); instances = new List<SoundInstance>(); } /// <summary> /// Releases all XA2 resources. /// </summary> internal static void Shutdown() { foreach(SoundInstance i in instances) i.Dispose(); master.Dispose(); device.Dispose(); } /// <summary> /// Registers a sound instance with the system. /// </summary> /// <param name="instance">Sound instance</param> internal static void AddInstance(SoundInstance instance) { instances.Add(instance); } /// <summary> /// Disposes any sound instance that has stopped playing. /// </summary> internal static void Update() { List<SoundInstance> temp = new List<SoundInstance>(instances); foreach(SoundInstance i in temp) if(!i.Playing) { i.Dispose(); instances.Remove(i); } } } /// <summary> /// Loads sounds from various files. /// </summary> internal class SoundLoader { /// <summary> /// Loads a .wav sound file. /// </summary> /// <param name="format">The decoded format will be sent here</param> /// <param name="buffer">The data will be sent here</param> /// <param name="soundName">The path to the WAV file</param> internal static void LoadWAV(out WaveFormat format, out AudioBuffer buffer, string soundName) { WaveStream wave = new WaveStream(soundName); format = wave.Format; buffer = new AudioBuffer(); buffer.AudioData = wave; buffer.AudioBytes = (int)wave.Length; buffer.Flags = BufferFlags.EndOfStream; } } /// <summary> /// Manages the data for a single sound. /// </summary> public class Sound : IAsset { WaveFormat format; AudioBuffer buffer; /// <summary> /// Loads a sound from a file. /// </summary> /// <param name="soundName">The path to the sound file</param> /// <returns>Whether the sound loaded successfully</returns> public bool Load(string soundName) { if(soundName.EndsWith(".wav")) SoundLoader.LoadWAV(out format, out buffer, soundName); else return false; return true; } /// <summary> /// Plays the sound. /// </summary> public void Play() { Audio.AddInstance(new SoundInstance(format, buffer)); } /// <summary> /// Unloads the sound from memory. /// </summary> public void Unload() { buffer.Dispose(); } } /// <summary> /// Manages a single sound instance. /// </summary> public class SoundInstance { SourceVoice source; bool playing; /// <summary> /// Whether the sound is currently playing. /// </summary> public bool Playing { get { return playing; } } /// <summary> /// Starts a new instance of a sound. /// </summary> /// <param name="format">Format of the sound</param> /// <param name="buffer">Buffer holding sound data</param> internal SoundInstance(WaveFormat format, AudioBuffer buffer) { source = new SourceVoice(Audio.Device, format); source.BufferEnd += (s, e) => playing = false; source.Start(); source.SubmitSourceBuffer(buffer); // THIS IS WHERE THE EXCEPTION IS THROWN playing = true; } /// <summary> /// Releases memory used by the instance. /// </summary> internal void Dispose() { source.Dispose(); } } The exception occurs on line 156 when I am playing the sound: source.SubmitSourceBuffer(buffer);

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  • Investigating on xVelocity (VertiPaq) column size

    - by Marco Russo (SQLBI)
      In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

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  • Developing Schema Compare for Oracle (Part 6): 9i Query Performance

    - by Simon Cooper
    All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

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  • Investigating on xVelocity (VertiPaq) column size

    - by Marco Russo (SQLBI)
      In January I published an article about how to optimize high cardinality columns in VertiPaq. In the meantime, VertiPaq has been rebranded to xVelocity: the official name is now “xVelocity in-memory analytics engine (VertiPaq)” but using xVelocity and VertiPaq when we talk about Analysis Services has the same meaning. In this post I’ll show how to investigate on columns size of an existing Tabular database so that you can find the most important columns to be optimized. A first approach can be looking in the DataDir of Analysis Services and look for the folder containing the database. Then, look for the biggest files in all subfolders and you will find the name of a file that contains the name of the most expensive column. However, this heuristic process is not very optimized. A better approach is using a DMV that provides the exact information. For example, by using the following query (open SSMS, open an MDX query on the database you are interested to and execute it) you will see all database objects sorted by used size in a descending way. SELECT * FROM $SYSTEM.DISCOVER_STORAGE_TABLE_COLUMN_SEGMENTS ORDER BY used_size DESC You can look at the first rows in order to understand what are the most expensive columns in your tabular model. The interesting data provided are: TABLE_ID: it is the name of the object – it can be also a dictionary or an index COLUMN_ID: it is the column name the object belongs to – you can also see ID_TO_POS and POS_TO_ID in case they refer to internal indexes RECORDS_COUNT: it is the number of rows in the column USED_SIZE: it is the used memory for the object By looking at the ration between USED_SIZE and RECORDS_COUNT you can understand what you can do in order to optimize your tabular model. Your options are: Remove the column. Yes, if it contains data you will never use in a query, simply remove the column from the tabular model Change granularity. If you are tracking time and you included milliseconds but seconds would be enough, round the data source column to the nearest second. If you have a floating point number but two decimals are good enough (i.e. the temperature), round the number to the nearest decimal is relevant to you. Split the column. Create two or more columns that have to be combined together in order to produce the original value. This technique is described in VertiPaq optimization article. Sort the table by that column. When you read the data source, you might consider sorting data by this column, so that the compression will be more efficient. However, this technique works better on columns that don’t have too many distinct values and you will probably move the problem to another column. Sorting data starting from the lower density columns (those with a few number of distinct values) and going to higher density columns (those with high cardinality) is the technique that provides the best compression ratio. After the optimization you should be able to reduce the used size and improve the count/size ration you measured before. If you are interested in a longer discussion about internal storage in VertiPaq and you want understand why this approach can save you space (and time), you can attend my 24 Hours of PASS session “VertiPaq Under the Hood” on March 21 at 08:00 GMT.

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  • ADO and Two Way Storage Tiering

    - by Andy-Oracle
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 We get asked the following question about Automatic Data Optimization (ADO) storage tiering quite a bit. Can you tier back to the original location if the data gets hot again? The answer is yes but not with standard Automatic Data Optimization policies, at least not reliably. That's not how ADO is meant to operate. ADO is meant to mirror a traditional view of Information Lifecycle Management (ILM) where data will be very volatile when first created, will become less active or cool, and then will eventually cease to be accessed at all (i.e. cold). I think the reason this question gets asked is because customers realize that many of their business processes are cyclical and the thinking goes that those segments that only get used during month end or year-end cycles could sit on lower cost storage when not being used. Unfortunately this doesn't fit very well with the ADO storage tiering model. ADO storage tiering is based on the amount of free and used space in the source tablespace. There are two parameters that control this behavior, TBS_PERCENT_USED and TBS_PERCENT_FREE. When the space in the tablespace exceeds the TBS_PERCENT_USED value then segments specified in storage tiering clause(s) can be moved until the percent of free space reaches the TBS_PERCENT_FREE value. It is worth mentioning that no checks are made for available space in the target tablespace. Now, it is certainly possible to create custom functions to control storage tiering, but this can get complicated. The biggest problem is insuring that there is enough space to move the segment back to tier 1 storage, assuming that that's the goal. This isn't as much of a problem when moving from tier 1 to tier 2 storage because there is typically more tier 2 storage available. At least that's the premise since it is supposed to be less costly, lower performing and higher capacity storage. In either case though, if there isn't enough space then the operation fails. In the case of a customized function, the question becomes do you attempt to free the space so the move can be made or do you just stop and return false so that the move cannot take place? This is really the crux of the issue. Once you cross into this territory you're really going to have to implement two-way hierarchical storage and the whole point of ADO was to provide automatic storage tiering. You're probably better off using heat map and/or business access requirements and building your own hierarchical storage management infrastructure if you really want two way storage tiering. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}

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  • Exiting a reboot loop

    - by user12617035
    If you're in a situation where the system is panic'ing during boot, you can use # boot net -s to regain control of your system. In my case, I'd added some diagnostic code to a (PCI) driver (that is used to boot the root filesystem). There was a bug in the driver, and each time during boot, the bug occurred, and so caused the system to panic: ... 000000000180b950 genunix:vfs_mountroot+60 (800, 200, 0, 185d400, 1883000, 18aec00) %l0-3: 0000000000001770 0000000000000640 0000000001814000 00000000000008fc %l4-7: 0000000001833c00 00000000018b1000 0000000000000600 0000000000000200 000000000180ba10 genunix:main+98 (18141a0, 1013800, 18362c0, 18ab800, 180e000, 1814000) %l0-3: 0000000070002000 0000000000000001 000000000180c000 000000000180e000 %l4-7: 0000000000000001 0000000001074800 0000000000000060 0000000000000000 skipping system dump - no dump device configured rebooting... If you're logged in via the console, you can send a BREAK sequence in order to gain control of the firmware's (OBP's) prompt. Enter Ctrl-Shift-[ in order to get the TELNET prompt. Once telnet has control, enter this: telnet> send brk You'll be presented with OBP's prompt: ok You then enter the following in order to boot into single-user mode via the network: ok boot net -s Note that booting from the network under Solaris will implicitly cause the system to be INSTALLED with whatever software had last been configured to be installed. However, we are using boot net -s as a "handle" with which to get at the Solaris prompt. Once at that prompt, we can perform actions as root that will let us back out our buggy driver (ok... MY buggy driver :-)) ...and replace it with the original, non-buggy driver. Entering the boot command caused the following output, as well as left us at the Solaris prompt (in single-user-mode): Sun Blade 1500, No Keyboard Copyright 1998-2004 Sun Microsystems, Inc. All rights reserved. OpenBoot 4.16.4, 1024 MB memory installed, Serial #53463393. Ethernet address 0:3:ba:2f:c9:61, Host ID: 832fc961. Rebooting with command: boot net -s Boot device: /pci@1f,700000/network@2 File and args: -s 1000 Mbps FDX Link up Timeout waiting for ARP/RARP packet Timeout waiting for ARP/RARP packet 4000 1000 Mbps FDX Link up Requesting Internet address for 0:3:ba:2f:c9:61 SunOS Release 5.10 Version Generic_118833-17 64-bit Copyright 1983-2005 Sun Microsystems, Inc. All rights reserved. Use is subject to license terms. Booting to milestone "milestone/single-user:default". Configuring devices. Using RPC Bootparams for network configuration information. Attempting to configure interface bge0... Configured interface bge0 Requesting System Maintenance Mode SINGLE USER MODE # Our goal is to now move to the directory containing the buggy driver and replace it with the original driver (that we had saved away before ever loading our buggy driver! :-) However, since we booted from the network, the root filesystem ("/") is NOT mounted on one of our local disks. It is mounted on an NFS filesystem exported by our install server. To verify this, enter the following command: # mount | head -1 / on my-server:/export/install/media/s10u2/solarisdvd.s10s_u2dvd/latest/Solaris_10/Tools/Boot remote/read/write/setuid/devices/dev=4ac0001 on Wed Dec 31 16:00:00 1969 As a result, we have to create a temporary mount point and then mount the local disk onto that mount point: # mkdir /tmp/mnt # mount /dev/dsk/c0t0d0s0 /tmp/mnt Note that your system will not necessarily have had its root filesystem on "c0t0d0s0". This is something that you should also have recorded before you ever loaded your.. er... "my" buggy driver! :-) One can find the local disk mounted under the root filesystem by entering: # df -k / Filesystem kbytes used avail capacity Mounted on /dev/dsk/c0t0d0s0 76703839 4035535 71901266 6% / To continue with our example, we can now move to the directory of buggy-driver in order to replace it with the original driver. Note that /tmp/mnt is prefixed to the path of where we'd "normally" find the driver: # cd /tmp/mnt/platform/sun4u/kernel/drv/sparcv9 # ls -l pci\* -rw-r--r-- 1 root root 288504 Dec 6 15:38 pcisch -rw-r--r-- 1 root root 288504 Dec 6 15:38 pcisch.aar -rwxr-xr-x 1 root sys 211616 Jun 8 2006 pcisch.orig # cp -p pcisch.orig pcisch We can now synchronize any in-memory filesystem data structures with those on disk... and then reboot. The system will then boot correctly... as expected: # sync;sync # reboot syncing file systems... done Sun Blade 1500, No Keyboard Copyright 1998-2004 Sun Microsystems, Inc. All rights reserved. OpenBoot 4.16.4, 1024 MB memory installed, Serial #xxxxxxxx. Ethernet address 0:3:ba:2f:c9:61, Host ID: yyyyyyyy. Rebooting with command: boot Boot device: /pci@1e,600000/ide@d/disk@0,0:a File and args: SunOS Release 5.10 Version Generic_118833-17 64-bit Copyright 1983-2005 Sun Microsystems, Inc. All rights reserved. Use is subject to license terms. Hostname: my-host NIS domain name is my-campus.Central.Sun.COM my-host console login: ...so that's how it's done! Of course, the easier way is to never write a buggy-driver... but.. then.. we all "have an eraser on the end of each of our pencils"... don't we ? :-) "...thank you... and good night..."

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  • Rethinking Oracle Optimizer Statistics for P6 Part 2

    - by Brian Diehl
    In the previous post (Part 1), I tried to draw some key insights about the relationship between P6 and Oracle Optimizer Statistics.  The first is that average cardinality has the greatest impact on query optimization and that the particular queries generated by P6 are more likely to use this average during calculations. The second is that these are statistics that are unlikely to change greatly over the life of the application. Ultimately, our goal is to get the best query optimization possible.  Or is it? Stability No application administrator wants to get the call at 9am that their application users cannot get there work done because everything is running slow. This is a possibility with a regularly scheduled nightly collection of statistics. It may not just be slow performance, but a complete loss of service because one or more queries are optimized poorly. Ideally, this should not be the case. The database optimizer should make better decisions with more up-to-date data. Better statistics may give incremental performance benefit. However, this benefit must be balanced against the potential cost of system down time.  It is stability that we ultimately desire and not absolute optimal performance. We do want the benefit from more accurate statistics and better query plans, but not at the risk of an unusable system. As a result, I've developed the following methodology around managing database statistics for the P6 database.  1. No Automatic Re-Gathering - The daily, weekly, or other interval of statistic gathering is unlikely to be beneficial. Quite the opposite. It is more likely to cause problems. 2. Smart Re-Gathering - The time to collect statistics is when things have changed significantly. For a new installation of P6, this is happening more often because the data is growing from a few rows to thousands and more. But for a mature system, the data is not changing significantly from week-to-week. There are times to collect statistics: New releases of the application Changes in the underlying hardware or software versions (ex. new Oracle RDBMS version) When additional user groups are added. The new groups may use the software in significantly different ways. After significant changes in the data. This may be monthly, quarterly or yearly.  3. Always Test - If you take away one thing from this post, it would be to always have a plan to test after changing statistics. In reality, statistics can be collected as often as you desire provided there are tests in place to verify that performance is the same or better. These might be automated tests or simply a manual script of application functions. 4. Have a Way Out - Never change the statistics without a way to return to the previous set. Think of the statistics as one part of the overall application code that also includes the source code--both application and RDBMS. It would be foolish to change to the new code without a way to get back to the previous version. In the final post, I will talk about the actual script I created for P6 PMDB and possible future direction for managing query performance. 

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  • What are good design practices when working with Entity Framework

    - by AD
    This will apply mostly for an asp.net application where the data is not accessed via soa. Meaning that you get access to the objects loaded from the framework, not Transfer Objects, although some recommendation still apply. This is a community post, so please add to it as you see fit. Applies to: Entity Framework 1.0 shipped with Visual Studio 2008 sp1. Why pick EF in the first place? Considering it is a young technology with plenty of problems (see below), it may be a hard sell to get on the EF bandwagon for your project. However, it is the technology Microsoft is pushing (at the expense of Linq2Sql, which is a subset of EF). In addition, you may not be satisfied with NHibernate or other solutions out there. Whatever the reasons, there are people out there (including me) working with EF and life is not bad.make you think. EF and inheritance The first big subject is inheritance. EF does support mapping for inherited classes that are persisted in 2 ways: table per class and table the hierarchy. The modeling is easy and there are no programming issues with that part. (The following applies to table per class model as I don't have experience with table per hierarchy, which is, anyway, limited.) The real problem comes when you are trying to run queries that include one or many objects that are part of an inheritance tree: the generated sql is incredibly awful, takes a long time to get parsed by the EF and takes a long time to execute as well. This is a real show stopper. Enough that EF should probably not be used with inheritance or as little as possible. Here is an example of how bad it was. My EF model had ~30 classes, ~10 of which were part of an inheritance tree. On running a query to get one item from the Base class, something as simple as Base.Get(id), the generated SQL was over 50,000 characters. Then when you are trying to return some Associations, it degenerates even more, going as far as throwing SQL exceptions about not being able to query more than 256 tables at once. Ok, this is bad, EF concept is to allow you to create your object structure without (or with as little as possible) consideration on the actual database implementation of your table. It completely fails at this. So, recommendations? Avoid inheritance if you can, the performance will be so much better. Use it sparingly where you have to. In my opinion, this makes EF a glorified sql-generation tool for querying, but there are still advantages to using it. And ways to implement mechanism that are similar to inheritance. Bypassing inheritance with Interfaces First thing to know with trying to get some kind of inheritance going with EF is that you cannot assign a non-EF-modeled class a base class. Don't even try it, it will get overwritten by the modeler. So what to do? You can use interfaces to enforce that classes implement some functionality. For example here is a IEntity interface that allow you to define Associations between EF entities where you don't know at design time what the type of the entity would be. public enum EntityTypes{ Unknown = -1, Dog = 0, Cat } public interface IEntity { int EntityID { get; } string Name { get; } Type EntityType { get; } } public partial class Dog : IEntity { // implement EntityID and Name which could actually be fields // from your EF model Type EntityType{ get{ return EntityTypes.Dog; } } } Using this IEntity, you can then work with undefined associations in other classes // lets take a class that you defined in your model. // that class has a mapping to the columns: PetID, PetType public partial class Person { public IEntity GetPet() { return IEntityController.Get(PetID,PetType); } } which makes use of some extension functions: public class IEntityController { static public IEntity Get(int id, EntityTypes type) { switch (type) { case EntityTypes.Dog: return Dog.Get(id); case EntityTypes.Cat: return Cat.Get(id); default: throw new Exception("Invalid EntityType"); } } } Not as neat as having plain inheritance, particularly considering you have to store the PetType in an extra database field, but considering the performance gains, I would not look back. It also cannot model one-to-many, many-to-many relationship, but with creative uses of 'Union' it could be made to work. Finally, it creates the side effet of loading data in a property/function of the object, which you need to be careful about. Using a clear naming convention like GetXYZ() helps in that regards. Compiled Queries Entity Framework performance is not as good as direct database access with ADO (obviously) or Linq2SQL. There are ways to improve it however, one of which is compiling your queries. The performance of a compiled query is similar to Linq2Sql. What is a compiled query? It is simply a query for which you tell the framework to keep the parsed tree in memory so it doesn't need to be regenerated the next time you run it. So the next run, you will save the time it takes to parse the tree. Do not discount that as it is a very costly operation that gets even worse with more complex queries. There are 2 ways to compile a query: creating an ObjectQuery with EntitySQL and using CompiledQuery.Compile() function. (Note that by using an EntityDataSource in your page, you will in fact be using ObjectQuery with EntitySQL, so that gets compiled and cached). An aside here in case you don't know what EntitySQL is. It is a string-based way of writing queries against the EF. Here is an example: "select value dog from Entities.DogSet as dog where dog.ID = @ID". The syntax is pretty similar to SQL syntax. You can also do pretty complex object manipulation, which is well explained [here][1]. Ok, so here is how to do it using ObjectQuery< string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); The first time you run this query, the framework will generate the expression tree and keep it in memory. So the next time it gets executed, you will save on that costly step. In that example EnablePlanCaching = true, which is unnecessary since that is the default option. The other way to compile a query for later use is the CompiledQuery.Compile method. This uses a delegate: static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => ctx.DogSet.FirstOrDefault(it => it.ID == id)); or using linq static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => (from dog in ctx.DogSet where dog.ID == id select dog).FirstOrDefault()); to call the query: query_GetDog.Invoke( YourContext, id ); The advantage of CompiledQuery is that the syntax of your query is checked at compile time, where as EntitySQL is not. However, there are other consideration... Includes Lets say you want to have the data for the dog owner to be returned by the query to avoid making 2 calls to the database. Easy to do, right? EntitySQL string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)).Include("Owner"); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); CompiledQuery static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => (from dog in ctx.DogSet.Include("Owner") where dog.ID == id select dog).FirstOrDefault()); Now, what if you want to have the Include parametrized? What I mean is that you want to have a single Get() function that is called from different pages that care about different relationships for the dog. One cares about the Owner, another about his FavoriteFood, another about his FavotireToy and so on. Basicly, you want to tell the query which associations to load. It is easy to do with EntitySQL public Dog Get(int id, string include) { string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)) .IncludeMany(include); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); } The include simply uses the passed string. Easy enough. Note that it is possible to improve on the Include(string) function (that accepts only a single path) with an IncludeMany(string) that will let you pass a string of comma-separated associations to load. Look further in the extension section for this function. If we try to do it with CompiledQuery however, we run into numerous problems: The obvious static readonly Func<Entities, int, string, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, string, Dog>((ctx, id, include) => (from dog in ctx.DogSet.Include(include) where dog.ID == id select dog).FirstOrDefault()); will choke when called with: query_GetDog.Invoke( YourContext, id, "Owner,FavoriteFood" ); Because, as mentionned above, Include() only wants to see a single path in the string and here we are giving it 2: "Owner" and "FavoriteFood" (which is not to be confused with "Owner.FavoriteFood"!). Then, let's use IncludeMany(), which is an extension function static readonly Func<Entities, int, string, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, string, Dog>((ctx, id, include) => (from dog in ctx.DogSet.IncludeMany(include) where dog.ID == id select dog).FirstOrDefault()); Wrong again, this time it is because the EF cannot parse IncludeMany because it is not part of the functions that is recognizes: it is an extension. Ok, so you want to pass an arbitrary number of paths to your function and Includes() only takes a single one. What to do? You could decide that you will never ever need more than, say 20 Includes, and pass each separated strings in a struct to CompiledQuery. But now the query looks like this: from dog in ctx.DogSet.Include(include1).Include(include2).Include(include3) .Include(include4).Include(include5).Include(include6) .[...].Include(include19).Include(include20) where dog.ID == id select dog which is awful as well. Ok, then, but wait a minute. Can't we return an ObjectQuery< with CompiledQuery? Then set the includes on that? Well, that what I would have thought so as well: static readonly Func<Entities, int, ObjectQuery<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, ObjectQuery<Dog>>((ctx, id) => (ObjectQuery<Dog>)(from dog in ctx.DogSet where dog.ID == id select dog)); public Dog GetDog( int id, string include ) { ObjectQuery<Dog> oQuery = query_GetDog(id); oQuery = oQuery.IncludeMany(include); return oQuery.FirstOrDefault; } That should have worked, except that when you call IncludeMany (or Include, Where, OrderBy...) you invalidate the cached compiled query because it is an entirely new one now! So, the expression tree needs to be reparsed and you get that performance hit again. So what is the solution? You simply cannot use CompiledQueries with parametrized Includes. Use EntitySQL instead. This doesn't mean that there aren't uses for CompiledQueries. It is great for localized queries that will always be called in the same context. Ideally CompiledQuery should always be used because the syntax is checked at compile time, but due to limitation, that's not possible. An example of use would be: you may want to have a page that queries which two dogs have the same favorite food, which is a bit narrow for a BusinessLayer function, so you put it in your page and know exactly what type of includes are required. Passing more than 3 parameters to a CompiledQuery Func is limited to 5 parameters, of which the last one is the return type and the first one is your Entities object from the model. So that leaves you with 3 parameters. A pitance, but it can be improved on very easily. public struct MyParams { public string param1; public int param2; public DateTime param3; } static readonly Func<Entities, MyParams, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, MyParams, IEnumerable<Dog>>((ctx, myParams) => from dog in ctx.DogSet where dog.Age == myParams.param2 && dog.Name == myParams.param1 and dog.BirthDate > myParams.param3 select dog); public List<Dog> GetSomeDogs( int age, string Name, DateTime birthDate ) { MyParams myParams = new MyParams(); myParams.param1 = name; myParams.param2 = age; myParams.param3 = birthDate; return query_GetDog(YourContext,myParams).ToList(); } Return Types (this does not apply to EntitySQL queries as they aren't compiled at the same time during execution as the CompiledQuery method) Working with Linq, you usually don't force the execution of the query until the very last moment, in case some other functions downstream wants to change the query in some way: static readonly Func<Entities, int, string, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, IEnumerable<Dog>>((ctx, age, name) => from dog in ctx.DogSet where dog.Age == age && dog.Name == name select dog); public IEnumerable<Dog> GetSomeDogs( int age, string name ) { return query_GetDog(YourContext,age,name); } public void DataBindStuff() { IEnumerable<Dog> dogs = GetSomeDogs(4,"Bud"); // but I want the dogs ordered by BirthDate gridView.DataSource = dogs.OrderBy( it => it.BirthDate ); } What is going to happen here? By still playing with the original ObjectQuery (that is the actual return type of the Linq statement, which implements IEnumerable), it will invalidate the compiled query and be force to re-parse. So, the rule of thumb is to return a List< of objects instead. static readonly Func<Entities, int, string, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, IEnumerable<Dog>>((ctx, age, name) => from dog in ctx.DogSet where dog.Age == age && dog.Name == name select dog); public List<Dog> GetSomeDogs( int age, string name ) { return query_GetDog(YourContext,age,name).ToList(); //<== change here } public void DataBindStuff() { List<Dog> dogs = GetSomeDogs(4,"Bud"); // but I want the dogs ordered by BirthDate gridView.DataSource = dogs.OrderBy( it => it.BirthDate ); } When you call ToList(), the query gets executed as per the compiled query and then, later, the OrderBy is executed against the objects in memory. It may be a little bit slower, but I'm not even sure. One sure thing is that you have no worries about mis-handling the ObjectQuery and invalidating the compiled query plan. Once again, that is not a blanket statement. ToList() is a defensive programming trick, but if you have a valid reason not to use ToList(), go ahead. There are many cases in which you would want to refine the query before executing it. Performance What is the performance impact of compiling a query? It can actually be fairly large. A rule of thumb is that compiling and caching the query for reuse takes at least double the time of simply executing it without caching. For complex queries (read inherirante), I have seen upwards to 10 seconds. So, the first time a pre-compiled query gets called, you get a performance hit. After that first hit, performance is noticeably better than the same non-pre-compiled query. Practically the same as Linq2Sql When you load a page with pre-compiled queries the first time you will get a hit. It will load in maybe 5-15 seconds (obviously more than one pre-compiled queries will end up being called), while subsequent loads will take less than 300ms. Dramatic difference, and it is up to you to decide if it is ok for your first user to take a hit or you want a script to call your pages to force a compilation of the queries. Can this query be cached? { Dog dog = from dog in YourContext.DogSet where dog.ID == id select dog; } No, ad-hoc Linq queries are not cached and you will incur the cost of generating the tree every single time you call it. Parametrized Queries Most search capabilities involve heavily parametrized queries. There are even libraries available that will let you build a parametrized query out of lamba expressions. The problem is that you cannot use pre-compiled queries with those. One way around that is to map out all the possible criteria in the query and flag which one you want to use: public struct MyParams { public string name; public bool checkName; public int age; public bool checkAge; } static readonly Func<Entities, MyParams, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, MyParams, IEnumerable<Dog>>((ctx, myParams) => from dog in ctx.DogSet where (myParams.checkAge == true && dog.Age == myParams.age) && (myParams.checkName == true && dog.Name == myParams.name ) select dog); protected List<Dog> GetSomeDogs() { MyParams myParams = new MyParams(); myParams.name = "Bud"; myParams.checkName = true; myParams.age = 0; myParams.checkAge = false; return query_GetDog(YourContext,myParams).ToList(); } The advantage here is that you get all the benifits of a pre-compiled quert. The disadvantages are that you most likely will end up with a where clause that is pretty difficult to maintain, that you will incur a bigger penalty for pre-compiling the query and that each query you run is not as efficient as it could be (particularly with joins thrown in). Another way is to build an EntitySQL query piece by piece, like we all did with SQL. protected List<Dod> GetSomeDogs( string name, int age) { string query = "select value dog from Entities.DogSet where 1 = 1 "; if( !String.IsNullOrEmpty(name) ) query = query + " and dog.Name == @Name "; if( age > 0 ) query = query + " and dog.Age == @Age "; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>( query, YourContext ); if( !String.IsNullOrEmpty(name) ) oQuery.Parameters.Add( new ObjectParameter( "Name", name ) ); if( age > 0 ) oQuery.Parameters.Add( new ObjectParameter( "Age", age ) ); return oQuery.ToList(); } Here the problems are: - there is no syntax checking during compilation - each different combination of parameters generate a different query which will need to be pre-compiled when it is first run. In this case, there are only 4 different possible queries (no params, age-only, name-only and both params), but you can see that there can be way more with a normal world search. - Noone likes to concatenate strings! Another option is to query a large subset of the data and then narrow it down in memory. This is particularly useful if you are working with a definite subset of the data, like all the dogs in a city. You know there are a lot but you also know there aren't that many... so your CityDog search page can load all the dogs for the city in memory, which is a single pre-compiled query and then refine the results protected List<Dod> GetSomeDogs( string name, int age, string city) { string query = "select value dog from Entities.DogSet where dog.Owner.Address.City == @City "; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>( query, YourContext ); oQuery.Parameters.Add( new ObjectParameter( "City", city ) ); List<Dog> dogs = oQuery.ToList(); if( !String.IsNullOrEmpty(name) ) dogs = dogs.Where( it => it.Name == name ); if( age > 0 ) dogs = dogs.Where( it => it.Age == age ); return dogs; } It is particularly useful when you start displaying all the data then allow for filtering. Problems: - Could lead to serious data transfer if you are not careful about your subset. - You can only filter on the data that you returned. It means that if you don't return the Dog.Owner association, you will not be able to filter on the Dog.Owner.Name So what is the best solution? There isn't any. You need to pick the solution that works best for you and your problem: - Use lambda-based query building when you don't care about pre-compiling your queries. - Use fully-defined pre-compiled Linq query when your object structure is not too complex. - Use EntitySQL/string concatenation when the structure could be complex and when the possible number of different resulting queries are small (which means fewer pre-compilation hits). - Use in-memory filtering when you are working with a smallish subset of the data or when you had to fetch all of the data on the data at first anyway (if the performance is fine with all the data, then filtering in memory will not cause any time to be spent in the db). Singleton access The best way to deal with your context and entities accross all your pages is to use the singleton pattern: public sealed class YourContext { private const string instanceKey = "On3GoModelKey"; YourContext(){} public static YourEntities Instance { get { HttpContext context = HttpContext.Current; if( context == null ) return Nested.instance; if (context.Items[instanceKey] == null) { On3GoEntities entity = new On3GoEntities(); context.Items[instanceKey] = entity; } return (YourEntities)context.Items[instanceKey]; } } class Nested { // Explicit static constructor to tell C# compiler // not to mark type as beforefieldinit static Nested() { } internal static readonly YourEntities instance = new YourEntities(); } } NoTracking, is it worth it? When executing a query, you can tell the framework to track the objects it will return or not. What does it mean? With tracking enabled (the default option), the framework will track what is going on with the object (has it been modified? Created? Deleted?) and will also link objects together, when further queries are made from the database, which is what is of interest here. For example, lets assume that Dog with ID == 2 has an owner which ID == 10. Dog dog = (from dog in YourContext.DogSet where dog.ID == 2 select dog).FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; Person owner = (from o in YourContext.PersonSet where o.ID == 10 select dog).FirstOrDefault(); //dog.OwnerReference.IsLoaded == true; If we were to do the same with no tracking, the result would be different. ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>) (from dog in YourContext.DogSet where dog.ID == 2 select dog); oDogQuery.MergeOption = MergeOption.NoTracking; Dog dog = oDogQuery.FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; ObjectQuery<Person> oPersonQuery = (ObjectQuery<Person>) (from o in YourContext.PersonSet where o.ID == 10 select o); oPersonQuery.MergeOption = MergeOption.NoTracking; Owner owner = oPersonQuery.FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; Tracking is very useful and in a perfect world without performance issue, it would always be on. But in this world, there is a price for it, in terms of performance. So, should you use NoTracking to speed things up? It depends on what you are planning to use the data for. Is there any chance that the data your query with NoTracking can be used to make update/insert/delete in the database? If so, don't use NoTracking because associations are not tracked and will causes exceptions to be thrown. In a page where there are absolutly no updates to the database, you can use NoTracking. Mixing tracking and NoTracking is possible, but it requires you to be extra careful with updates/inserts/deletes. The problem is that if you mix then you risk having the framework trying to Attach() a NoTracking object to the context where another copy of the same object exist with tracking on. Basicly, what I am saying is that Dog dog1 = (from dog in YourContext.DogSet where dog.ID == 2).FirstOrDefault(); ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>) (from dog in YourContext.DogSet where dog.ID == 2 select dog); oDogQuery.MergeOption = MergeOption.NoTracking; Dog dog2 = oDogQuery.FirstOrDefault(); dog1 and dog2 are 2 different objects, one tracked and one not. Using the detached object in an update/insert will force an Attach() that will say "Wait a minute, I do already have an object here with the same database key. Fail". And when you Attach() one object, all of its hierarchy gets attached as well, causing problems everywhere. Be extra careful. How much faster is it with NoTracking It depends on the queries. Some are much more succeptible to tracking than other. I don't have a fast an easy rule for it, but it helps. So I should use NoTracking everywhere then? Not exactly. There are some advantages to tracking object. The first one is that the object is cached, so subsequent call for that object will not hit the database. That cache is only valid for the lifetime of the YourEntities object, which, if you use the singleton code above, is the same as the page lifetime. One page request == one YourEntity object. So for multiple calls for the same object, it will load only once per page request. (Other caching mechanism could extend that). What happens when you are using NoTracking and try to load the same object multiple times? The database will be queried each time, so there is an impact there. How often do/should you call for the same object during a single page request? As little as possible of course, but it does happens. Also remember the piece above about having the associations connected automatically for your? You don't have that with NoTracking, so if you load your data in multiple batches, you will not have a link to between them: ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>)(from dog in YourContext.DogSet select dog); oDogQuery.MergeOption = MergeOption.NoTracking; List<Dog> dogs = oDogQuery.ToList(); ObjectQuery<Person> oPersonQuery = (ObjectQuery<Person>)(from o in YourContext.PersonSet select o); oPersonQuery.MergeOption = MergeOption.NoTracking; List<Person> owners = oPersonQuery.ToList(); In this case, no dog will have its .Owner property set. Some things to keep in mind when you are trying to optimize the performance. No lazy loading, what am I to do? This can be seen as a blessing in disguise. Of course it is annoying to load everything manually. However, it decreases the number of calls to the db and forces you to think about when you should load data. The more you can load in one database call the better. That was always true, but it is enforced now with this 'feature' of EF. Of course, you can call if( !ObjectReference.IsLoaded ) ObjectReference.Load(); if you want to, but a better practice is to force the framework to load the objects you know you will need in one shot. This is where the discussion about parametrized Includes begins to make sense. Lets say you have you Dog object public class Dog { public Dog Get(int id) { return YourContext.DogSet.FirstOrDefault(it => it.ID == id ); } } This is the type of function you work with all the time. It gets called from all over the place and once you have that Dog object, you will do very different things to it in different functions. First, it should be pre-compiled, because you will call that very often. Second, each different pages will want to have access to a different subset of the Dog data. Some will want the Owner, some the FavoriteToy, etc. Of course, you could call Load() for each reference you need anytime you need one. But that will generate a call to the database each time. Bad idea. So instead, each page will ask for the data it wants to see when it first request for the Dog object: static public Dog Get(int id) { return GetDog(entity,"");} static public Dog Get(int id, string includePath) { string query = "select value o " + " from YourEntities.DogSet as o " +

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  • Can you use gzip over SSL? And Connection: Keep-Alive headers

    - by magenta
    I'm evaluating the front end performance of a secure (SSL) web app here at work and I'm wondering if it's possible to compress text files (html/css/javascript) over SSL. I've done some googling around but haven't found anything specifically related to SSL. If it's possible, is it even worth the extra CPU cycles since responses are also being encrypted? Would compressing responses hurt performance? Also, I'm wanting to make sure we're keeping the SSL connection alive so we're not making SSL handshakes over and over. I'm not seeing Connection: Keep-Alive in the response headers. I do see Keep-Alive: 115 in the request headers but that's only keeping the connection alive for 115 milliseconds (seems like the app server is closing the connection after a single request is processed?) Wouldn't you want the server to be setting that response header for as long as the session inactivity timeout is? I understand browsers don't cache SSL content to disk so we're serving the same files over and over and over on subsequent visits even though nothing has changed. The main optimization recommendations are reducing the number of http requests, minification, moving scripts to bottom, image optimization, possible domain sharding (though need to weigh the cost of another SSL handshake), things of that nature.

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  • Using Traveling Salesman Solver to Decide Hamiltonian Path

    - by Firas Assaad
    This is for a project where I'm asked to implement a heuristic for the traveling salesman optimization problem and also the Hamiltonian path or cycle decision problem. I don't need help with the implementation itself, but have a question on the direction I'm going in. I already have a TSP heuristic based on a genetic algorithm: it assumes a complete graph, starts with a set of random solutions as a population, and works to improve the population for a number of generations. Can I also use it to solve the Hamiltonian path or cycle problems? Instead of optimizing to get the shortest path, I just want to check if there is a path. Now any complete graph will have a Hamiltonian path in it, so the TSP heuristic would have to be extended to any graph. This could be done by setting the edges to some infinity value if there is no path between two cities, and returning the first path that is a valid Hamiltonian path. Is that the right way to approach it? Or should I use a different heuristic for Hamiltonian path? My main concern is whether it's a viable approach since I can be somewhat sure that TSP optimization works (because you start with solutions and improve them) but not if a Hamiltonian path decider would find any path in a fixed number of generations. I assume the best approach would be to test it myself, but I'm constrained by time and thought I'd ask before going down this route... (I could find a different heuristic for Hamiltonian path instead)

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  • Iterating through String word at a time in Python

    - by AlgoMan
    I have a string buffer of a huge text file. I have to search a given words/phrases in the string buffer. Whats the efficient way to do it ? I tried using re module matches. But As i have a huge text corpus that i have to search through. This is taking large amount of time. Given a Dictionary of words and Phrases. I iterate through the each file, read that into string , search all the words and phrases in the dictionary and increment the count in the dictionary if the keys are found. One small optimization that we thought was to sort the dictionary of phrases/words with the max number of words to lowest. And then compare each word start position from the string buffer and compare the list of words. If one phrase is found, we don search for the other phrases (as it matched the longest phrase ,which is what we want) Can some one suggest how to go about word by word in the string buffer. (Iterate string buffer word by word) ? Also, Is there any other optimization that can be done on this ?

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  • efficiently determining if a polynomial has a root in the interval [0,T]

    - by user168715
    I have polynomials of nontrivial degree (4+) and need to robustly and efficiently determine whether or not they have a root in the interval [0,T]. The precise location or number of roots don't concern me, I just need to know if there is at least one. Right now I'm using interval arithmetic as a quick check to see if I can prove that no roots can exist. If I can't, I'm using Jenkins-Traub to solve for all of the polynomial roots. This is obviously inefficient since it's checking for all real roots and finding their exact positions, information I don't end up needing. Is there a standard algorithm I should be using? If not, are there any other efficient checks I could do before doing a full Jenkins-Traub solve for all roots? For example, one optimization I could do is to check if my polynomial f(t) has the same sign at 0 and T. If not, there is obviously a root in the interval. If so, I can solve for the roots of f'(t) and evaluate f at all roots of f' in the interval [0,T]. f(t) has no root in that interval if and only if all of these evaluations have the same sign as f(0) and f(T). This reduces the degree of the polynomial I have to root-find by one. Not a huge optimization, but perhaps better than nothing.

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  • Moving inserted container element if possible

    - by doublep
    I'm trying to achieve the following optimization in my container library: when inserting an lvalue-referenced element, copy it to internal storage; but when inserting rvalue-referenced element, move it if supported. The optimization is supposed to be useful e.g. if contained element type is something like std::vector, where moving if possible would give substantial speedup. However, so far I was unable to devise any working scheme for this. My container is quite complicated, so I can't just duplicate insert() code several times: it is large. I want to keep all "real" code in some inner helper, say do_insert() (may be templated) and various insert()-like functions would just call that with different arguments. My best bet code for this (a prototype, of course, without doing anything real): #include <iostream> #include <utility> struct element { element () { }; element (element&&) { std::cerr << "moving\n"; } }; struct container { void insert (const element& value) { do_insert (value); } void insert (element&& value) { do_insert (std::move (value)); } private: template <typename Arg> void do_insert (Arg arg) { element x (arg); } }; int main () { { // Shouldn't move. container c; element x; c.insert (x); } { // Should move. container c; c.insert (element ()); } } However, this doesn't work at least with GCC 4.4 and 4.5: it never prints "moving" on stderr. Or is what I want impossible to achieve and that's why emplace()-like functions exist in the first place?

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  • VS 2008 C++ build output?

    - by STingRaySC
    Why when I watch the build output from a VC++ project in VS do I see: 1Compiling... 1a.cpp 1b.cpp 1c.cpp 1d.cpp 1e.cpp [etc...] 1Generating code... 1x.cpp 1y.cpp [etc...] The output looks as though several compilation units are being handled before any code is generated. Is this really going on? I'm trying to improve build times, and by using pre-compiled headers, I've gotten great speedups for each ".cpp" file, but there is a relatively long pause during the "Generating Code..." message. I do not have "Whole Program Optimization" nor "Link Time Code Generation" turned on. If this is the case, then why? Why doesn't VC++ compile each ".cpp" individually (which would include the code generation phase)? If this isn't just an illusion of the output, is there cross-compilation-unit optimization potentially going on here? There don't appear to be any compiler options to control that behavior (I know about WPO and LTCG, as mentioned above). EDIT: The build log just shows the ".obj" files in the output directory, one per line. There is no indication of "Compiling..." vs. "Generating code..." steps. EDIT: I have confirmed that this behavior has nothing to do with the "maximum number of parallel project builds" setting in Tools - Options - Projects and Solutions - Build and Run. Nor is it related to the MSBuild project build output verbosity setting. Indeed if I cancel the build before the "Generating code..." step, the ".obj" files will not exist for the most recent set of "compiled" files. E.g., if I cancel the build during "c.cpp" above, I will see only "a.obj" and "b.obj".

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  • Thread management advice - Is TPL a good idea?

    - by Ian
    I'm hoping to get some advice on the use of thread managment and hopefully the task parallel library, because I'm not sure I've been going down the correct route. Probably best is that I give an outline of what I'm trying to do. Given a Problem I need to generate a Solution using a heuristic based algorithm. I start of by calculating a base solution, this operation I don't think can be parallelised so we don't need to worry about. Once the inital solution has been generated, I want to trigger n threads, which attempt to find a better solution. These threads need to do a couple of things: They need to be initalized with a different 'optimization metric'. In other words they are attempting to optimize different things, with a precedence level set within code. This means they all run slightly different calculation engines. I'm not sure if I can do this with the TPL.. If one of the threads finds a better solution that the currently best known solution (which needs to be shared across all threads) then it needs to update the best solution, and force a number of other threads to restart (again this depends on precedence levels of the optimization metrics). I may also wish to combine certain calculations across threads (e.g. keep a union of probabilities for a certain approach to the problem). This is probably more optional though. The whole system needs to be thread safe obviously and I want it to be running as fast as possible. I tried quite an implementation that involved managing my own threads and shutting them down etc, but it started getting quite complicated, and I'm now wondering if the TPL might be better. I'm wondering if anyone can offer any general guidance? Thanks...

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  • In sync query calls, one query causing other query to run slower. Why?

    - by Irchi
    Sorry for the long question, but I think this is an interesting situation and I couldn't find any explanations for it: I was involved in optimization of an application that performed a large number of sequential SELECT and INSERT statements on a single dedicated SQL Server database. The process needs to INSERT a large number of records into a table, but for each of them there should be some value mappings, which performed using SELECT statements on another table in the same database. For a specific execution, it took 90 minutes to run. I used a profiler (JProfiler - the application is Java-based) to determine how much time does each part of the application take. It yields that 60% of the time was spent on INSERT method calls, and almost 20% on SELECT calls (the rest distributed in other parts). After some trials, I came to this situation: I commented out the INSERT query that took 60% of the time. I was expecting for the total run time to be around 35 minutes, as I have removed 60% of the 90 minutes. But the whole process took the same 90 minutes (doing only SELECTs and nothing else), but each SELECT took longer this time! Everything was running sync, there were no async calls. And there was only one single thread of execution. SELECT and INSERT queries are very simple, and don't have anything special, and they are on different tables, but on the same DB. I tested with both the DB on the application machine, and on a remote network machine. I can't think of any explanation for this, as the Profiler (Application profiler, not SQL Profiler) reported the changes in the method call times, and by removing INSERT statements SELECT statements took longer to run. Can anyone give me some kind of explanation of what could have happened? (there can't be cache / query optimization stuff, because the queries were run in sync, and in a single thread, and it was far from affecting the cache this much) I should note that the bottleneck of the speed was in SQL server, using most of the CPU time.

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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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  • How to read oom-killer syslog messages?

    - by Grant
    I have a Ubuntu 12.04 server which sometimes dies completely - no SSH, no ping, nothing until it is physically rebooted. After the reboot, I see in syslog that the oom-killer killed, well, pretty much everything. There's a lot of detailed memory usage information in them. How do I read these logs to see what caused the OOM issue? The server has far more memory than it needs, so it shouldn't be running out of memory. Oct 25 07:28:04 nldedip4k031 kernel: [87946.529511] oom_kill_process: 9 callbacks suppressed Oct 25 07:28:04 nldedip4k031 kernel: [87946.529514] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529516] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529518] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:04 nldedip4k031 kernel: [87946.529519] Call Trace: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529525] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529528] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529530] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529532] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529535] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529537] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529541] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529543] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529546] [] vfs_read+0x8c/0x160 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529548] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529550] [] sys_read+0x3d/0x70 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529554] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529555] Mem-Info: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529556] DMA per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529557] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529558] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529560] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529561] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529562] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529563] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529564] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529565] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529566] Normal per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529567] CPU 0: hi: 186, btch: 31 usd: 179 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529568] CPU 1: hi: 186, btch: 31 usd: 182 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529569] CPU 2: hi: 186, btch: 31 usd: 132 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529570] CPU 3: hi: 186, btch: 31 usd: 175 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529571] CPU 4: hi: 186, btch: 31 usd: 91 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529572] CPU 5: hi: 186, btch: 31 usd: 173 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529573] CPU 6: hi: 186, btch: 31 usd: 159 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529574] CPU 7: hi: 186, btch: 31 usd: 164 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529575] HighMem per-cpu: Oct 25 07:28:04 nldedip4k031 kernel: [87946.529576] CPU 0: hi: 186, btch: 31 usd: 165 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529577] CPU 1: hi: 186, btch: 31 usd: 183 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529578] CPU 2: hi: 186, btch: 31 usd: 185 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529579] CPU 3: hi: 186, btch: 31 usd: 138 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529580] CPU 4: hi: 186, btch: 31 usd: 155 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529581] CPU 5: hi: 186, btch: 31 usd: 104 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529582] CPU 6: hi: 186, btch: 31 usd: 133 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529583] CPU 7: hi: 186, btch: 31 usd: 170 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529586] active_anon:5523 inactive_anon:354 isolated_anon:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529586] active_file:2815 inactive_file:6849119 isolated_file:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529587] unevictable:0 dirty:449 writeback:10 unstable:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529587] free:1304125 slab_reclaimable:104672 slab_unreclaimable:3419 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529588] mapped:2661 shmem:138 pagetables:313 bounce:0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529591] DMA free:4252kB min:780kB low:972kB high:1168kB active_anon:0kB inactive_anon:0kB active_file:4kB inactive_file:0kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15756kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:11564kB slab_unreclaimable:4kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:1 all_unreclaimable? yes Oct 25 07:28:04 nldedip4k031 kernel: [87946.529594] lowmem_reserve[]: 0 869 32460 32460 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529599] Normal free:44052kB min:44216kB low:55268kB high:66324kB active_anon:0kB inactive_anon:0kB active_file:616kB inactive_file:568kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:890008kB mlocked:0kB dirty:0kB writeback:0kB mapped:4kB shmem:0kB slab_reclaimable:407124kB slab_unreclaimable:13672kB kernel_stack:992kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:2083 all_unreclaimable? yes Oct 25 07:28:04 nldedip4k031 kernel: [87946.529602] lowmem_reserve[]: 0 0 252733 252733 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529606] HighMem free:5168196kB min:512kB low:402312kB high:804112kB active_anon:22092kB inactive_anon:1416kB active_file:10640kB inactive_file:27395920kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:32349872kB mlocked:0kB dirty:1796kB writeback:40kB mapped:10640kB shmem:552kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:1252kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Oct 25 07:28:04 nldedip4k031 kernel: [87946.529609] lowmem_reserve[]: 0 0 0 0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529611] DMA: 6*4kB 6*8kB 6*16kB 5*32kB 5*64kB 4*128kB 2*256kB 1*512kB 0*1024kB 1*2048kB 0*4096kB = 4232kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529616] Normal: 297*4kB 180*8kB 119*16kB 73*32kB 67*64kB 47*128kB 35*256kB 13*512kB 5*1024kB 1*2048kB 1*4096kB = 44052kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529622] HighMem: 1*4kB 6*8kB 27*16kB 11*32kB 2*64kB 1*128kB 0*256kB 0*512kB 4*1024kB 1*2048kB 1260*4096kB = 5168196kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529627] 6852076 total pagecache pages Oct 25 07:28:04 nldedip4k031 kernel: [87946.529628] 0 pages in swap cache Oct 25 07:28:04 nldedip4k031 kernel: [87946.529629] Swap cache stats: add 0, delete 0, find 0/0 Oct 25 07:28:04 nldedip4k031 kernel: [87946.529630] Free swap = 3998716kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.529631] Total swap = 3998716kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.571914] 8437743 pages RAM Oct 25 07:28:04 nldedip4k031 kernel: [87946.571916] 8209409 pages HighMem Oct 25 07:28:04 nldedip4k031 kernel: [87946.571917] 159556 pages reserved Oct 25 07:28:04 nldedip4k031 kernel: [87946.571917] 6862034 pages shared Oct 25 07:28:04 nldedip4k031 kernel: [87946.571918] 123540 pages non-shared Oct 25 07:28:04 nldedip4k031 kernel: [87946.571919] [ pid ] uid tgid total_vm rss cpu oom_adj oom_score_adj name Oct 25 07:28:04 nldedip4k031 kernel: [87946.571927] [ 421] 0 421 709 152 3 0 0 upstart-udev-br Oct 25 07:28:04 nldedip4k031 kernel: [87946.571929] [ 429] 0 429 773 326 5 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571931] [ 567] 0 567 772 224 4 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571932] [ 568] 0 568 772 231 7 -17 -1000 udevd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571934] [ 764] 0 764 712 103 1 0 0 upstart-socket- Oct 25 07:28:04 nldedip4k031 kernel: [87946.571936] [ 772] 103 772 815 164 5 0 0 dbus-daemon Oct 25 07:28:04 nldedip4k031 kernel: [87946.571938] [ 785] 0 785 1671 600 1 -17 -1000 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571940] [ 809] 101 809 7766 380 1 0 0 rsyslogd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571942] [ 869] 0 869 1158 213 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571943] [ 873] 0 873 1158 214 6 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571945] [ 911] 0 911 1158 215 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571947] [ 912] 0 912 1158 214 2 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571949] [ 914] 0 914 1158 213 1 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571950] [ 916] 0 916 618 86 1 0 0 atd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571952] [ 917] 0 917 655 226 3 0 0 cron Oct 25 07:28:04 nldedip4k031 kernel: [87946.571954] [ 948] 0 948 902 159 3 0 0 irqbalance Oct 25 07:28:04 nldedip4k031 kernel: [87946.571956] [ 993] 0 993 1145 363 3 0 0 master Oct 25 07:28:04 nldedip4k031 kernel: [87946.571957] [ 1002] 104 1002 1162 333 1 0 0 qmgr Oct 25 07:28:04 nldedip4k031 kernel: [87946.571959] [ 1016] 0 1016 730 149 2 0 0 mdadm Oct 25 07:28:04 nldedip4k031 kernel: [87946.571961] [ 1057] 0 1057 6066 2160 3 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571963] [ 1086] 0 1086 1158 213 3 0 0 getty Oct 25 07:28:04 nldedip4k031 kernel: [87946.571965] [ 1088] 33 1088 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571967] [ 1089] 33 1089 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571969] [ 1090] 33 1090 6175 1451 3 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571971] [ 1091] 33 1091 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571972] [ 1092] 33 1092 6191 1451 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571974] [ 1109] 33 1109 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571976] [ 1151] 33 1151 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:04 nldedip4k031 kernel: [87946.571978] [ 1201] 104 1201 1803 652 1 0 0 tlsmgr Oct 25 07:28:04 nldedip4k031 kernel: [87946.571980] [ 2475] 0 2475 2435 812 0 0 0 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571982] [ 2494] 0 2494 1745 839 1 0 0 bash Oct 25 07:28:04 nldedip4k031 kernel: [87946.571984] [ 2573] 0 2573 3394 1689 0 0 0 sshd Oct 25 07:28:04 nldedip4k031 kernel: [87946.571986] [ 2589] 0 2589 5014 457 3 0 0 rsync Oct 25 07:28:04 nldedip4k031 kernel: [87946.571988] [ 2590] 0 2590 7970 522 1 0 0 rsync Oct 25 07:28:04 nldedip4k031 kernel: [87946.571990] [ 2652] 104 2652 1150 326 5 0 0 pickup Oct 25 07:28:04 nldedip4k031 kernel: [87946.571992] Out of memory: Kill process 421 (upstart-udev-br) score 1 or sacrifice child Oct 25 07:28:04 nldedip4k031 kernel: [87946.572407] Killed process 421 (upstart-udev-br) total-vm:2836kB, anon-rss:156kB, file-rss:452kB Oct 25 07:28:04 nldedip4k031 kernel: [87946.573107] init: upstart-udev-bridge main process (421) killed by KILL signal Oct 25 07:28:04 nldedip4k031 kernel: [87946.573126] init: upstart-udev-bridge main process ended, respawning Oct 25 07:28:34 nldedip4k031 kernel: [87976.461570] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461573] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461576] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:34 nldedip4k031 kernel: [87976.461578] Call Trace: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461585] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461588] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461591] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461595] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461599] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461602] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461606] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461609] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461613] [] vfs_read+0x8c/0x160 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461616] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461619] [] sys_read+0x3d/0x70 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461624] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461626] Mem-Info: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461628] DMA per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461629] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461631] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461633] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461634] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461636] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461638] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461639] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461641] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461642] Normal per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461644] CPU 0: hi: 186, btch: 31 usd: 61 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461646] CPU 1: hi: 186, btch: 31 usd: 49 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461647] CPU 2: hi: 186, btch: 31 usd: 8 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461649] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461651] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461652] CPU 5: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461654] CPU 6: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461656] CPU 7: hi: 186, btch: 31 usd: 30 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461657] HighMem per-cpu: Oct 25 07:28:34 nldedip4k031 kernel: [87976.461658] CPU 0: hi: 186, btch: 31 usd: 4 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461660] CPU 1: hi: 186, btch: 31 usd: 204 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461662] CPU 2: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461663] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461665] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461667] CPU 5: hi: 186, btch: 31 usd: 31 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461668] CPU 6: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461670] CPU 7: hi: 186, btch: 31 usd: 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461674] active_anon:5441 inactive_anon:412 isolated_anon:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461674] active_file:2668 inactive_file:6922842 isolated_file:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461675] unevictable:0 dirty:836 writeback:0 unstable:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461676] free:1231664 slab_reclaimable:105781 slab_unreclaimable:3399 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461677] mapped:2649 shmem:138 pagetables:313 bounce:0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461682] DMA free:4248kB min:780kB low:972kB high:1168kB active_anon:0kB inactive_anon:0kB active_file:0kB inactive_file:4kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:15756kB mlocked:0kB dirty:0kB writeback:0kB mapped:0kB shmem:0kB slab_reclaimable:11560kB slab_unreclaimable:4kB kernel_stack:0kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:5687 all_unreclaimable? yes Oct 25 07:28:34 nldedip4k031 kernel: [87976.461686] lowmem_reserve[]: 0 869 32460 32460 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461693] Normal free:44184kB min:44216kB low:55268kB high:66324kB active_anon:0kB inactive_anon:0kB active_file:20kB inactive_file:1096kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:890008kB mlocked:0kB dirty:4kB writeback:0kB mapped:4kB shmem:0kB slab_reclaimable:411564kB slab_unreclaimable:13592kB kernel_stack:992kB pagetables:0kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:1816 all_unreclaimable? yes Oct 25 07:28:34 nldedip4k031 kernel: [87976.461697] lowmem_reserve[]: 0 0 252733 252733 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461703] HighMem free:4878224kB min:512kB low:402312kB high:804112kB active_anon:21764kB inactive_anon:1648kB active_file:10652kB inactive_file:27690268kB unevictable:0kB isolated(anon):0kB isolated(file):0kB present:32349872kB mlocked:0kB dirty:3340kB writeback:0kB mapped:10592kB shmem:552kB slab_reclaimable:0kB slab_unreclaimable:0kB kernel_stack:0kB pagetables:1252kB unstable:0kB bounce:0kB writeback_tmp:0kB pages_scanned:0 all_unreclaimable? no Oct 25 07:28:34 nldedip4k031 kernel: [87976.461708] lowmem_reserve[]: 0 0 0 0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461711] DMA: 8*4kB 7*8kB 6*16kB 5*32kB 5*64kB 4*128kB 2*256kB 1*512kB 0*1024kB 1*2048kB 0*4096kB = 4248kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461719] Normal: 272*4kB 178*8kB 76*16kB 52*32kB 42*64kB 36*128kB 23*256kB 20*512kB 7*1024kB 2*2048kB 1*4096kB = 44176kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461727] HighMem: 1*4kB 45*8kB 31*16kB 24*32kB 5*64kB 3*128kB 1*256kB 2*512kB 4*1024kB 2*2048kB 1188*4096kB = 4877852kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461736] 6925679 total pagecache pages Oct 25 07:28:34 nldedip4k031 kernel: [87976.461737] 0 pages in swap cache Oct 25 07:28:34 nldedip4k031 kernel: [87976.461739] Swap cache stats: add 0, delete 0, find 0/0 Oct 25 07:28:34 nldedip4k031 kernel: [87976.461740] Free swap = 3998716kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.461741] Total swap = 3998716kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.524951] 8437743 pages RAM Oct 25 07:28:34 nldedip4k031 kernel: [87976.524953] 8209409 pages HighMem Oct 25 07:28:34 nldedip4k031 kernel: [87976.524954] 159556 pages reserved Oct 25 07:28:34 nldedip4k031 kernel: [87976.524955] 6936141 pages shared Oct 25 07:28:34 nldedip4k031 kernel: [87976.524956] 124602 pages non-shared Oct 25 07:28:34 nldedip4k031 kernel: [87976.524957] [ pid ] uid tgid total_vm rss cpu oom_adj oom_score_adj name Oct 25 07:28:34 nldedip4k031 kernel: [87976.524966] [ 429] 0 429 773 326 5 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524968] [ 567] 0 567 772 224 4 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524971] [ 568] 0 568 772 231 7 -17 -1000 udevd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524973] [ 764] 0 764 712 103 3 0 0 upstart-socket- Oct 25 07:28:34 nldedip4k031 kernel: [87976.524976] [ 772] 103 772 815 164 2 0 0 dbus-daemon Oct 25 07:28:34 nldedip4k031 kernel: [87976.524979] [ 785] 0 785 1671 600 1 -17 -1000 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524981] [ 809] 101 809 7766 380 1 0 0 rsyslogd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524983] [ 869] 0 869 1158 213 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524986] [ 873] 0 873 1158 214 6 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524988] [ 911] 0 911 1158 215 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524990] [ 912] 0 912 1158 214 2 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524992] [ 914] 0 914 1158 213 1 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.524995] [ 916] 0 916 618 86 1 0 0 atd Oct 25 07:28:34 nldedip4k031 kernel: [87976.524997] [ 917] 0 917 655 226 3 0 0 cron Oct 25 07:28:34 nldedip4k031 kernel: [87976.524999] [ 948] 0 948 902 159 5 0 0 irqbalance Oct 25 07:28:34 nldedip4k031 kernel: [87976.525002] [ 993] 0 993 1145 363 3 0 0 master Oct 25 07:28:34 nldedip4k031 kernel: [87976.525004] [ 1002] 104 1002 1162 333 1 0 0 qmgr Oct 25 07:28:34 nldedip4k031 kernel: [87976.525007] [ 1016] 0 1016 730 149 2 0 0 mdadm Oct 25 07:28:34 nldedip4k031 kernel: [87976.525009] [ 1057] 0 1057 6066 2160 3 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525012] [ 1086] 0 1086 1158 213 3 0 0 getty Oct 25 07:28:34 nldedip4k031 kernel: [87976.525014] [ 1088] 33 1088 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525017] [ 1089] 33 1089 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525019] [ 1090] 33 1090 6175 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525021] [ 1091] 33 1091 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525024] [ 1092] 33 1092 6191 1451 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525026] [ 1109] 33 1109 6191 1517 0 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525029] [ 1151] 33 1151 6191 1451 1 0 0 /usr/sbin/apach Oct 25 07:28:34 nldedip4k031 kernel: [87976.525031] [ 1201] 104 1201 1803 652 1 0 0 tlsmgr Oct 25 07:28:34 nldedip4k031 kernel: [87976.525033] [ 2475] 0 2475 2435 812 0 0 0 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.525036] [ 2494] 0 2494 1745 839 1 0 0 bash Oct 25 07:28:34 nldedip4k031 kernel: [87976.525038] [ 2573] 0 2573 3394 1689 3 0 0 sshd Oct 25 07:28:34 nldedip4k031 kernel: [87976.525040] [ 2589] 0 2589 5014 457 3 0 0 rsync Oct 25 07:28:34 nldedip4k031 kernel: [87976.525043] [ 2590] 0 2590 7970 522 1 0 0 rsync Oct 25 07:28:34 nldedip4k031 kernel: [87976.525045] [ 2652] 104 2652 1150 326 5 0 0 pickup Oct 25 07:28:34 nldedip4k031 kernel: [87976.525048] [ 2847] 0 2847 709 89 0 0 0 upstart-udev-br Oct 25 07:28:34 nldedip4k031 kernel: [87976.525050] Out of memory: Kill process 764 (upstart-socket-) score 1 or sacrifice child Oct 25 07:28:34 nldedip4k031 kernel: [87976.525484] Killed process 764 (upstart-socket-) total-vm:2848kB, anon-rss:204kB, file-rss:208kB Oct 25 07:28:34 nldedip4k031 kernel: [87976.526161] init: upstart-socket-bridge main process (764) killed by KILL signal Oct 25 07:28:34 nldedip4k031 kernel: [87976.526180] init: upstart-socket-bridge main process ended, respawning Oct 25 07:28:44 nldedip4k031 kernel: [87986.439671] irqbalance invoked oom-killer: gfp_mask=0x80d0, order=0, oom_adj=0, oom_score_adj=0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439674] irqbalance cpuset=/ mems_allowed=0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439676] Pid: 948, comm: irqbalance Not tainted 3.2.0-55-generic-pae #85-Ubuntu Oct 25 07:28:44 nldedip4k031 kernel: [87986.439678] Call Trace: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439684] [] dump_header.isra.6+0x85/0xc0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439686] [] oom_kill_process+0x5c/0x80 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439688] [] out_of_memory+0xc5/0x1c0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439691] [] __alloc_pages_nodemask+0x72c/0x740 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439694] [] __get_free_pages+0x1c/0x30 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439696] [] get_zeroed_page+0x12/0x20 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439699] [] fill_read_buffer.isra.8+0xaa/0xd0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439702] [] sysfs_read_file+0x7d/0x90 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439704] [] vfs_read+0x8c/0x160 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439707] [] ? fill_read_buffer.isra.8+0xd0/0xd0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439709] [] sys_read+0x3d/0x70 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439712] [] sysenter_do_call+0x12/0x28 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439714] Mem-Info: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439714] DMA per-cpu: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439716] CPU 0: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439717] CPU 1: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439718] CPU 2: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439719] CPU 3: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439720] CPU 4: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439721] CPU 5: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439722] CPU 6: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439723] CPU 7: hi: 0, btch: 1 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439724] Normal per-cpu: Oct 25 07:28:44 nldedip4k031 kernel: [87986.439725] CPU 0: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439726] CPU 1: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439727] CPU 2: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439728] CPU 3: hi: 186, btch: 31 usd: 0 Oct 25 07:28:44 nldedip4k031 kernel: [87986.439729] CPU 4: hi: 186, btch: 31 usd: 0 Oct 25 07:33:48 nldedip4k031 kernel: imklog 5.8.6, log source = /proc/kmsg started. Oct 25 07:33:48 nldedip4k031 rsyslogd: [origin software="rsyslogd" swVersion="5.8.6" x-pid="2880" x-info="http://www.rsyslog.com"] start Oct 25 07:33:48 nldedip4k031 rsyslogd: rsyslogd's groupid changed to 103 Oct 25 07:33:48 nldedip4k031 rsyslogd: rsyslogd's userid changed to 101 Oct 25 07:33:48 nldedip4k031 rsyslogd-2039: Could not open output pipe '/dev/xconsole' [try http://www.rsyslog.com/e/2039 ]

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