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  • Ubuntu 13.10. After login, no desktop displayed. Two Nvidia Graphics Cards, Four Monitors

    - by jmerkow
    I am working on an issue with my Ubuntu 13.10 installation. I am attempting to get 4 monitors up and running but I am having some trouble. So far, I installed and updated to the latest NVIDIA drivers (331.20). Initially X would not start (after installation) so I replaced my xorg.conf with xorg.conf.failsafe. This fixed that problem, but then I tried to enable the other 2 monitors (other video card) and xorg fails to start once again (after I login there is no desktop). I am fairly new to linux but I am not a complete beginner, but I'm not comfortable poking around too much on my own to troubleshoot yet.... lspci -nn | grep VGA: 03:00.0 VGA compatible controller [0300]: NVIDIA Corporation GF110 [GeForce GTX 570 Rev. 2] [10de:1086] (rev a1) 05:00.0 VGA compatible controller [0300]: NVIDIA Corporation GF110 [GeForce GTX 580] [10de:1080] (rev a1) It seems that the nvidia-settings tool does not result in a good xorg.conf file. Here it is: # nvidia-settings: X configuration file generated by nvidia-settings # nvidia-settings: version 331.20 (buildmeister@swio-display-x86-rhel47-05) Wed Oct 30 18:20:32 PDT 2013 Section "ServerLayout" Identifier "Default Layout" Screen 0 "Screen0" 0 0 Screen 1 "Screen1" RightOf "Screen0" InputDevice "Keyboard0" "CoreKeyboard" InputDevice "Mouse0" "CorePointer" Option "Xinerama" "1" EndSection ... Section "Monitor" Identifier "Configured Monitor" EndSection Section "Monitor" Identifier "Monitor0" VendorName "Unknown" ModelName "SHARP HDMI" HorizSync 15.0 - 68.0 VertRefresh 55.0 - 76.0 EndSection Section "Monitor" Identifier "Monitor1" VendorName "Unknown" ModelName "Samsung SyncMaster" HorizSync 0.0 - 0.0 VertRefresh 0.0 EndSection Section "Device" Identifier "Configured Video Device" Driver "vesa" EndSection Section "Device" Identifier "Device0" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GTX 570" BusID "PCI:3:0:0" EndSection Section "Device" Identifier "Device1" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GTX 580" BusID "PCI:5:0:0" EndSection Section "Screen" Identifier "Default Screen" Device "Configured Video Device" Monitor "Configured Monitor" EndSection Section "Screen" Identifier "Screen0" Device "Device0" Monitor "Monitor0" DefaultDepth 24 Option "Stereo" "0" Option "nvidiaXineramaInfoOrder" "DFP-1" Option "metamodes" "HDMI-0: nvidia-auto-select +640+0, DVI-I-3: nvidia-auto-select +0+1080" Option "SLI" "Off" Option "MultiGPU" "Off" Option "BaseMosaic" "off" SubSection "Display" Depth 24 EndSubSection EndSection Section "Screen" Identifier "Screen1" Device "Device1" Monitor "Monitor1" DefaultDepth 24 Option "Stereo" "0" Option "metamodes" "DVI-I-2: nvidia-auto-select +0+0" Option "SLI" "Off" Option "MultiGPU" "Off" Option "BaseMosaic" "off" SubSection "Display" Depth 24 EndSubSection EndSection Section "Extensions" Option "Composite" "Disable" EndSection

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  • Why are my Opteron cores running at only 75% capacity each? (25% CPU idle)

    - by Tim Cooper
    We've just taken delivery of a powerful 32-core AMD Opteron server with 128Gb. We have 2 x 6272 CPU's with 16 cores each. We are running a big long-running java task on 30 threads. We have the NUMA optimisations for Linux and java turned on. Our Java threads are mainly using objects that are private to that thread, sometimes reading memory that other threads will be reading, and very very occasionally writing or locking shared objects. We can't explain why the CPU cores are 25% idle. Below is a dump of "top": top - 23:06:38 up 1 day, 23 min, 3 users, load average: 10.84, 10.27, 9.62 Tasks: 676 total, 1 running, 675 sleeping, 0 stopped, 0 zombie Cpu(s): 64.5%us, 1.3%sy, 0.0%ni, 32.9%id, 1.3%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 132138168k total, 131652664k used, 485504k free, 92340k buffers Swap: 5701624k total, 230252k used, 5471372k free, 13444344k cached ... top - 22:37:39 up 23:54, 3 users, load average: 7.83, 8.70, 9.27 Tasks: 678 total, 1 running, 677 sleeping, 0 stopped, 0 zombie Cpu0 : 75.8%us, 2.0%sy, 0.0%ni, 22.2%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu1 : 77.2%us, 1.3%sy, 0.0%ni, 21.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu2 : 77.3%us, 1.0%sy, 0.0%ni, 21.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu3 : 77.8%us, 1.0%sy, 0.0%ni, 21.2%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu4 : 76.9%us, 2.0%sy, 0.0%ni, 21.1%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu5 : 76.3%us, 2.0%sy, 0.0%ni, 21.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu6 : 12.6%us, 3.0%sy, 0.0%ni, 84.4%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu7 : 8.6%us, 2.0%sy, 0.0%ni, 89.4%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu8 : 77.0%us, 2.0%sy, 0.0%ni, 21.1%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu9 : 77.0%us, 2.0%sy, 0.0%ni, 21.1%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu10 : 77.6%us, 1.7%sy, 0.0%ni, 20.8%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu11 : 75.7%us, 2.0%sy, 0.0%ni, 21.4%id, 1.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu12 : 76.6%us, 2.3%sy, 0.0%ni, 21.1%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu13 : 76.6%us, 2.3%sy, 0.0%ni, 21.1%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu14 : 76.2%us, 2.6%sy, 0.0%ni, 15.9%id, 5.3%wa, 0.0%hi, 0.0%si, 0.0%st Cpu15 : 76.6%us, 2.0%sy, 0.0%ni, 21.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu16 : 73.6%us, 2.6%sy, 0.0%ni, 23.8%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu17 : 74.5%us, 2.3%sy, 0.0%ni, 23.2%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu18 : 73.9%us, 2.3%sy, 0.0%ni, 23.8%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu19 : 72.9%us, 2.6%sy, 0.0%ni, 24.4%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu20 : 72.8%us, 2.6%sy, 0.0%ni, 24.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu21 : 72.7%us, 2.3%sy, 0.0%ni, 25.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu22 : 72.5%us, 2.6%sy, 0.0%ni, 24.8%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu23 : 73.0%us, 2.3%sy, 0.0%ni, 24.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu24 : 74.7%us, 2.7%sy, 0.0%ni, 22.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu25 : 74.5%us, 2.6%sy, 0.0%ni, 22.8%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu26 : 73.7%us, 2.0%sy, 0.0%ni, 24.3%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu27 : 74.1%us, 2.3%sy, 0.0%ni, 23.6%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu28 : 74.1%us, 2.3%sy, 0.0%ni, 23.6%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu29 : 74.0%us, 2.0%sy, 0.0%ni, 24.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu30 : 73.2%us, 2.3%sy, 0.0%ni, 24.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu31 : 73.1%us, 2.0%sy, 0.0%ni, 24.9%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 132138168k total, 131711704k used, 426464k free, 88336k buffers Swap: 5701624k total, 229572k used, 5472052k free, 13745596k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 13865 root 20 0 122g 112g 3.1g S 2334.3 89.6 20726:49 java 27139 jayen 20 0 15428 1728 952 S 2.6 0.0 0:04.21 top 27161 sysadmin 20 0 15428 1712 940 R 1.0 0.0 0:00.28 top 33 root 20 0 0 0 0 S 0.3 0.0 0:06.24 ksoftirqd/7 131 root 20 0 0 0 0 S 0.3 0.0 0:09.52 events/0 1858 root 20 0 0 0 0 S 0.3 0.0 1:35.14 kondemand/0 A dump of the java stack confirms that none of the threads are anywhere near the few places where locks are used, nor are they anywhere near any disk or network i/o. I had trouble finding a clear explanation of what 'top' means by "idle" versus "wait", but I get the impression that "idle" means "no more threads that need to be run" but this doesn't make sense in our case. We're using a "Executors.newFixedThreadPool(30)". There are a large number of tasks pending and each task lasts for 10 seconds or so. I suspect that the explanation requires a good understanding of NUMA. Is the "idle" state what you see when a CPU is waiting for a non-local access? If not, then what is the explanation?

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  • Where to get PNG icons/graphics for game development for kids? [closed]

    - by at.
    Possible Duplicate: Where can I find free sprites and images? I'm teaching kids to program using Ruby and the gaming framework Gosu/Chingu. Kids love it, including the part where they have to look for the icons/graphics for their game objects. I direct them to iconarchive.com, but the selection is sometimes very limited, the graphics aren't always with transparent backgrounds and sometimes the art requires payment. I don't mind paying for an educational license of some sort, but I want the kids to easily select graphics they can use in their games. Is there another resource better suited for this purpose? I don't have a good solution for this, but would also love a site they can get cool background images for their games.

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  • How to hide assets from user? ( e.g.: a png file )

    - by burninggramma
    I think the title is quite self-explaining, still this is a big area I think, so let me drop a few words: I've got a simple experiment game project going, and I want to make sure, that the user isn't messing with the game assets like player skin etc. In my opinion the best way would be that on production I would merge all the assets into one file and the application would check the hash of that file, so it could detect the corrupted data. Is this an acceptable practice? There must be sum libraries / applications which are targeting this problem, could you guide me on this? Project details: unix/linux, c++, sdl

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  • Can I embed a .png image into an html page?

    - by Ole Jak
    So I have a .png file. I am using windows OS. How can I embed my png file/image into (blank by default) file.html so that when you open that file in any browser you see that image, but the file is not anyhow linked to it - it is ebbeded into it? Step by step instructions would be nice.

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  • No GLX on Intel card with multiseat with additional nVidia card

    - by MeanEYE
    I have multiseat configured and my Xorg has 2 server layouts. One is for nVidia card and other is for Intel card. They both work, but display server assigned to Intel card doesn't have hardware acceleration since DRI and GLX module being used is from nVidia driver. So my question is, can I configure layouts somehow to use right DRI and GLX with each card? My Xorg.conf: Section "ServerLayout" Identifier "Default" Screen 0 "Screen0" 0 0 Option "Xinerama" "0" EndSection Section "ServerLayout" Identifier "TV" Screen 0 "Screen1" 0 0 Option "Xinerama" "0" EndSection Section "Monitor" # HorizSync source: edid, VertRefresh source: edid Identifier "Monitor0" VendorName "Unknown" ModelName "DELL E198WFP" HorizSync 30.0 - 83.0 VertRefresh 56.0 - 75.0 Option "DPMS" EndSection Section "Monitor" Identifier "Monitor1" VendorName "Unknown" Option "DPMS" EndSection Section "Device" Identifier "Device0" Driver "nvidia" VendorName "NVIDIA Corporation" BoardName "GeForce GT 610" EndSection Section "Device" Identifier "Device1" Driver "intel" BusID "PCI:0:2:0" Option "AccelMethod" "uxa" EndSection Section "Screen" Identifier "Screen0" Device "Device0" Monitor "Monitor0" DefaultDepth 24 Option "Stereo" "0" Option "nvidiaXineramaInfoOrder" "DFP-1" Option "metamodes" "DFP-0: nvidia-auto-select +1440+0, DFP-1: nvidia-auto-select +0+0" SubSection "Display" Depth 24 EndSubSection EndSection Section "Screen" Identifier "Screen1" Device "Device1" Monitor "Monitor1" DefaultDepth 24 SubSection "Display" Depth 24 EndSubSection EndSection Log file for Intel: [ 18.239] X.Org X Server 1.13.0 Release Date: 2012-09-05 [ 18.239] X Protocol Version 11, Revision 0 [ 18.239] Build Operating System: Linux 2.6.24-32-xen x86_64 Ubuntu [ 18.239] Current Operating System: Linux bytewiper 3.5.0-18-generic #29-Ubuntu SMP Fri Oct 19 10:26:51 UTC 2012 x86_64 [ 18.239] Kernel command line: BOOT_IMAGE=/boot/vmlinuz-3.5.0-18-generic root=UUID=fc0616fd-f212-4846-9241-ba4a492f0513 ro quiet splash [ 18.239] Build Date: 20 September 2012 11:55:20AM [ 18.239] xorg-server 2:1.13.0+git20120920.70e57668-0ubuntu0ricotz (For technical support please see http://www.ubuntu.com/support) [ 18.239] Current version of pixman: 0.26.0 [ 18.239] Before reporting problems, check http://wiki.x.org to make sure that you have the latest version. [ 18.239] Markers: (--) probed, (**) from config file, (==) default setting, (++) from command line, (!!) notice, (II) informational, (WW) warning, (EE) error, (NI) not implemented, (??) unknown. [ 18.239] (==) Log file: "/var/log/Xorg.1.log", Time: Wed Nov 21 18:32:14 2012 [ 18.239] (==) Using config file: "/etc/X11/xorg.conf" [ 18.239] (==) Using system config directory "/usr/share/X11/xorg.conf.d" [ 18.239] (++) ServerLayout "TV" [ 18.239] (**) |-->Screen "Screen1" (0) [ 18.239] (**) | |-->Monitor "Monitor1" [ 18.240] (**) | |-->Device "Device1" [ 18.240] (**) Option "Xinerama" "0" [ 18.240] (==) Automatically adding devices [ 18.240] (==) Automatically enabling devices [ 18.240] (==) Automatically adding GPU devices [ 18.240] (WW) The directory "/usr/share/fonts/X11/cyrillic" does not exist. [ 18.240] Entry deleted from font path. [ 18.240] (WW) The directory "/usr/share/fonts/X11/100dpi/" does not exist. [ 18.240] Entry deleted from font path. [ 18.240] (WW) The directory "/usr/share/fonts/X11/75dpi/" does not exist. [ 18.240] Entry deleted from font path. [ 18.240] (WW) The directory "/usr/share/fonts/X11/100dpi" does not exist. [ 18.240] Entry deleted from font path. [ 18.240] (WW) The directory "/usr/share/fonts/X11/75dpi" does not exist. [ 18.240] Entry deleted from font path. [ 18.240] (WW) The directory "/var/lib/defoma/x-ttcidfont-conf.d/dirs/TrueType" does not exist. [ 18.240] Entry deleted from font path. [ 18.240] (==) FontPath set to: /usr/share/fonts/X11/misc, /usr/share/fonts/X11/Type1, built-ins [ 18.240] (==) ModulePath set to "/usr/lib/x86_64-linux-gnu/xorg/extra-modules,/usr/lib/xorg/extra-modules,/usr/lib/xorg/modules" [ 18.240] (II) The server relies on udev to provide the list of input devices. If no devices become available, reconfigure udev or disable AutoAddDevices. [ 18.240] (II) Loader magic: 0x7f6917944c40 [ 18.240] (II) Module ABI versions: [ 18.240] X.Org ANSI C Emulation: 0.4 [ 18.240] X.Org Video Driver: 13.0 [ 18.240] X.Org XInput driver : 18.0 [ 18.240] X.Org Server Extension : 7.0 [ 18.240] (II) config/udev: Adding drm device (/dev/dri/card0) [ 18.241] (--) PCI: (0:0:2:0) 8086:0152:1043:84ca rev 9, Mem @ 0xf7400000/4194304, 0xd0000000/268435456, I/O @ 0x0000f000/64 [ 18.241] (--) PCI:*(0:1:0:0) 10de:104a:1458:3546 rev 161, Mem @ 0xf6000000/16777216, 0xe0000000/134217728, 0xe8000000/33554432, I/O @ 0x0000e000/128, BIOS @ 0x????????/524288 [ 18.241] (II) Open ACPI successful (/var/run/acpid.socket) [ 18.241] Initializing built-in extension Generic Event Extension [ 18.241] Initializing built-in extension SHAPE [ 18.241] Initializing built-in extension MIT-SHM [ 18.241] Initializing built-in extension XInputExtension [ 18.241] Initializing built-in extension XTEST [ 18.241] Initializing built-in extension BIG-REQUESTS [ 18.241] Initializing built-in extension SYNC [ 18.241] Initializing built-in extension XKEYBOARD [ 18.241] Initializing built-in extension XC-MISC [ 18.241] Initializing built-in extension SECURITY [ 18.241] Initializing built-in extension XINERAMA [ 18.241] Initializing built-in extension XFIXES [ 18.241] Initializing built-in extension RENDER [ 18.241] Initializing built-in extension RANDR [ 18.241] Initializing built-in extension COMPOSITE [ 18.241] Initializing built-in extension DAMAGE [ 18.241] Initializing built-in extension MIT-SCREEN-SAVER [ 18.241] Initializing built-in extension DOUBLE-BUFFER [ 18.241] Initializing built-in extension RECORD [ 18.241] Initializing built-in extension DPMS [ 18.241] Initializing built-in extension X-Resource [ 18.241] Initializing built-in extension XVideo [ 18.241] Initializing built-in extension XVideo-MotionCompensation [ 18.241] Initializing built-in extension XFree86-VidModeExtension [ 18.241] Initializing built-in extension XFree86-DGA [ 18.241] Initializing built-in extension XFree86-DRI [ 18.241] Initializing built-in extension DRI2 [ 18.241] (II) LoadModule: "glx" [ 18.241] (II) Loading /usr/lib/x86_64-linux-gnu/xorg/extra-modules/libglx.so [ 18.247] (II) Module glx: vendor="NVIDIA Corporation" [ 18.247] compiled for 4.0.2, module version = 1.0.0 [ 18.247] Module class: X.Org Server Extension [ 18.247] (II) NVIDIA GLX Module 310.19 Thu Nov 8 01:12:43 PST 2012 [ 18.247] Loading extension GLX [ 18.247] (II) LoadModule: "intel" [ 18.248] (II) Loading /usr/lib/xorg/modules/drivers/intel_drv.so [ 18.248] (II) Module intel: vendor="X.Org Foundation" [ 18.248] compiled for 1.13.0, module version = 2.20.13 [ 18.248] Module class: X.Org Video Driver [ 18.248] ABI class: X.Org Video Driver, version 13.0 [ 18.248] (II) intel: Driver for Intel Integrated Graphics Chipsets: i810, i810-dc100, i810e, i815, i830M, 845G, 854, 852GM/855GM, 865G, 915G, E7221 (i915), 915GM, 945G, 945GM, 945GME, Pineview GM, Pineview G, 965G, G35, 965Q, 946GZ, 965GM, 965GME/GLE, G33, Q35, Q33, GM45, 4 Series, G45/G43, Q45/Q43, G41, B43, B43, Clarkdale, Arrandale, Sandybridge Desktop (GT1), Sandybridge Desktop (GT2), Sandybridge Desktop (GT2+), Sandybridge Mobile (GT1), Sandybridge Mobile (GT2), Sandybridge Mobile (GT2+), Sandybridge Server, Ivybridge Mobile (GT1), Ivybridge Mobile (GT2), Ivybridge Desktop (GT1), Ivybridge Desktop (GT2), Ivybridge Server, Ivybridge Server (GT2), Haswell Desktop (GT1), Haswell Desktop (GT2), Haswell Desktop (GT2+), Haswell Mobile (GT1), Haswell Mobile (GT2), Haswell Mobile (GT2+), Haswell Server (GT1), Haswell Server (GT2), Haswell Server (GT2+), Haswell SDV Desktop (GT1), Haswell SDV Desktop (GT2), Haswell SDV Desktop (GT2+), Haswell SDV Mobile (GT1), Haswell SDV Mobile (GT2), Haswell SDV Mobile (GT2+), Haswell SDV Server (GT1), Haswell SDV Server (GT2), Haswell SDV Server (GT2+), Haswell ULT Desktop (GT1), Haswell ULT Desktop (GT2), Haswell ULT Desktop (GT2+), Haswell ULT Mobile (GT1), Haswell ULT Mobile (GT2), Haswell ULT Mobile (GT2+), Haswell ULT Server (GT1), Haswell ULT Server (GT2), Haswell ULT Server (GT2+), Haswell CRW Desktop (GT1), Haswell CRW Desktop (GT2), Haswell CRW Desktop (GT2+), Haswell CRW Mobile (GT1), Haswell CRW Mobile (GT2), Haswell CRW Mobile (GT2+), Haswell CRW Server (GT1), Haswell CRW Server (GT2), Haswell CRW Server (GT2+), ValleyView PO board [ 18.248] (++) using VT number 8 [ 18.593] (II) intel(0): using device path '/dev/dri/card0' [ 18.593] (**) intel(0): Depth 24, (--) framebuffer bpp 32 [ 18.593] (==) intel(0): RGB weight 888 [ 18.593] (==) intel(0): Default visual is TrueColor [ 18.593] (**) intel(0): Option "AccelMethod" "uxa" [ 18.593] (--) intel(0): Integrated Graphics Chipset: Intel(R) Ivybridge Desktop (GT1) [ 18.593] (**) intel(0): Relaxed fencing enabled [ 18.593] (**) intel(0): Wait on SwapBuffers? enabled [ 18.593] (**) intel(0): Triple buffering? enabled [ 18.593] (**) intel(0): Framebuffer tiled [ 18.593] (**) intel(0): Pixmaps tiled [ 18.593] (**) intel(0): 3D buffers tiled [ 18.593] (**) intel(0): SwapBuffers wait enabled ... [ 20.312] (II) Module fb: vendor="X.Org Foundation" [ 20.312] compiled for 1.13.0, module version = 1.0.0 [ 20.312] ABI class: X.Org ANSI C Emulation, version 0.4 [ 20.312] (II) Loading sub module "dri2" [ 20.312] (II) LoadModule: "dri2" [ 20.312] (II) Module "dri2" already built-in [ 20.312] (==) Depth 24 pixmap format is 32 bpp [ 20.312] (II) intel(0): [DRI2] Setup complete [ 20.312] (II) intel(0): [DRI2] DRI driver: i965 [ 20.312] (II) intel(0): Allocated new frame buffer 1920x1080 stride 7680, tiled [ 20.312] (II) UXA(0): Driver registered support for the following operations: [ 20.312] (II) solid [ 20.312] (II) copy [ 20.312] (II) composite (RENDER acceleration) [ 20.312] (II) put_image [ 20.312] (II) get_image [ 20.312] (==) intel(0): Backing store disabled [ 20.312] (==) intel(0): Silken mouse enabled [ 20.312] (II) intel(0): Initializing HW Cursor [ 20.312] (II) intel(0): RandR 1.2 enabled, ignore the following RandR disabled message. [ 20.313] (**) intel(0): DPMS enabled [ 20.313] (==) intel(0): Intel XvMC decoder enabled [ 20.313] (II) intel(0): Set up textured video [ 20.313] (II) intel(0): [XvMC] xvmc_vld driver initialized. [ 20.313] (II) intel(0): direct rendering: DRI2 Enabled [ 20.313] (==) intel(0): hotplug detection: "enabled" [ 20.332] (--) RandR disabled [ 20.335] (EE) Failed to initialize GLX extension (Compatible NVIDIA X driver not found) [ 20.335] (II) intel(0): Setting screen physical size to 508 x 285 [ 20.338] (II) XKB: reuse xkmfile /var/lib/xkb/server-B20D7FC79C7F597315E3E501AEF10E0D866E8E92.xkm [ 20.340] (II) config/udev: Adding input device Power Button (/dev/input/event1) [ 20.340] (**) Power Button: Applying InputClass "evdev keyboard catchall" [ 20.340] (II) LoadModule: "evdev" [ 20.340] (II) Loading /usr/lib/xorg/modules/input/evdev_drv.so

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  • Inventory Management concepts in XNA game

    - by user1332755
    I am trying to code the inventory system in my first real game so I have very little experience in both c# and game engine development. Basically, I need some general guidance and tips with how to structure and organize these sorts of systems. Please tell me if I am on the right track or not before I get too deep into making some badly structured system. It's fine if you don't feel like looking through my code, suggestions about general structure would also be appreciated. What I am aiming to end up with is some sort of system like Minecraft or Terraria. It must include: main inventory GUI (items can be dragged and placed in whatever slot desired Itembar outside of the main inventory which can be assigned to certain items the ability to use items from either location So far, I have 4 main classes: Inventory holds the general info and methods, inventoryslot holds info for individual slots, Itembar holds all info and methods for itself, and finally, ItemManager to manage interactions between the two and hold a master list of items. So far, my itembar works perfectly and interacts well with mousedragging items into and out of it as well as activating the item effect. Here is the code I have so far: (there is a lot but I will try to keep it relevant) This is the code for the itembar on the main screen: class Itembar { public Texture2D itembarfull, iSelected; public static Rectangle itembar = new Rectangle(5, 218, 40, 391); public Rectangle box1 = new Rectangle(itembar.X, 218, 40, 40); //up to 10 Rectangles for each slot public int Selected = 0; private ItemManager manager; public Itembar(Texture2D texture, Texture2D texture3, ItemManager mann) { itembarfull = texture; iSelected = texture3; manager = mann; } public void Update(GameTime gametime) { } public void Draw(SpriteBatch spriteBatch) { spriteBatch.Draw( itembarfull, new Vector2 (itembar.X, itembar.Y), null, Color.White, 0.0f, Vector2.Zero, 1.0f, SpriteEffects.None, 1.0f); if (Selected == 1) spriteBatch.Draw(iSelected, new Rectangle(box1.X-3, box1.Y-3, box1.Width+6, box1.Height+6), Color.White); //goes up to 10 slots } public int Box1Query() { foreach (Item item in manager.items) { if(box1.Contains(item.BoundingBox)) return manager.items.IndexOf(item); } return 999; } //10 different box queries It is working fine right now. I just put an Item in there and the box will query things like the item's effects, stack number, consumable or not etc...This one is basically almost complete. Here is the main inventory class: class Inventory { public bool isActive; public List<Rectangle> mainSlots = new List<Rectangle>(24); public List<InventorySlot> mainSlotscheck = new List<InventorySlot>(24); public static Rectangle inv = new Rectangle(841, 469, 156, 231); public Rectangle invfull = new Rectangle(inv.X, inv.Y, inv.Width, inv.Height); public Rectangle inv1 = new Rectangle(inv.X + 4, inv.Y +3, 32, 32); //goes up to inv24 resulting in a 6x4 grid of Rectangles public Inventory() { mainSlots.Add(inv1); mainSlots.Add(inv2); mainSlots.Add(inv3); mainSlots.Add(inv4); //goes up to 24 foreach (Rectangle slot in mainSlots) mainSlotscheck.Add(new InventorySlot(slot)); } //update and draw methods are empty because im not too sure what to put there public int LookforfreeSlot() { int slotnumber = 999; for (int x = 0; x < mainSlots.Count; x++) { if (mainSlotscheck[x].isFree) { slotnumber = x; break; } } return slotnumber; } } } LookforFreeSlot() method is meant to be called when I do AddtoInventory(). I'm kinda stumped about what other things I need to put in this class. Here is the inventorySlot class: (its main purpose is to check the bool "isFree" to see whether or not something already occupies the slot. But i guess it can also do other stuff like get item info.) class InventorySlot { public int X, Y; public int Width = 32, Height = 32; public Vector2 Position; public int slotnumber; public bool free = true; public int? content = null; public bool isFree { get { return free; } set { free = value; } } public InventorySlot(Rectangle slot) { slot = new Rectangle(X, Y, Width, Height); } } } Finally, here is the ItemManager (I am omitting the master list because it is too long) class ItemManager { public List<Item> items = new List<Item>(20); public List<Item> inventory1 = new List<Item>(24); public List<Item> inventory2 = new List<Item>(24); public List<Item> inventory3 = new List<Item>(24); public List<Item> inventory4 = new List<Item>(24); public Texture2D icon, filta; private Rectangle msRect; MouseState mouseState; public int ISelectedIndex; Inventory inventory; SpriteFont font; public void GenerateItems() { items.Add(new Item(new Rectangle(0, 0, 32, 32), icon, font)); items[0].name = "Grass Chip"; items[0].itemID = 0; items[0].consumable = true; items[0].stackable = true; items[0].maxStack = 99; items.Add(new Item(new Rectangle(32, 0, 32, 32), icon, font)); //master list continues. it will generate all items in the game; } public ItemManager(Inventory inv, Texture2D itemsheet, Rectangle mouseRectt, MouseState ms, Texture2D fil, SpriteFont f) { icon = itemsheet; msRect = mouseRectt; filta = fil; mouseState = ms; inventory = inv; font = f; } //once again, no update or draw public void mousedrag() { items[0].DestinationRect = new Rectangle (msRect.X, msRect.Y, 32, 32); items[0].dragging = true; } public void AddtoInventory(Item item) { int index = inventory.LookforfreeSlot(); if (index == 999) return; item.DestinationRect = inventory.mainSlots[index]; inventory.mainSlotscheck[index].content = item.itemID; inventory.mainSlotscheck[index].isFree = false; item.IsActive = true; } } } The mousedrag works pretty well. AddtoInventory doesn't work because LookforfreeSlot doesn't work. Relevant code from the main program: When I want to add something to the main inventory, I do something like this: foreach (Particle ether in ether1.ethers) { if (ether.isCollected) itemmanager.AddtoInventory(itemmanager.items[14]); } This turned out to be much longer than I had expected :( But I hope someone is interested enough to comment.

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  • ATI propriatery drivers install latest 12.8, broke my kernel. Stuck on kernel 3.2.0-26

    - by user66987
    I messed up a bit. Hoping some here can help me. I tried to install the newest catalyst 12.8. Sadly, this broke my system. I was stuck in low graphics mode. I finally managed to restore the proprietary drivers, and get into ubuntu again. But now I am stuck on kernel 3.2.0.26. I had installed kernel 3.2.0-30, but the system no longer sees it. I have kernel 3.2.0-29 too, but the system cannot see that as well. In the grub menu. When I use sudo update-grub, they are both listed. Here are the output I get: Searching for GRUB installation directory ... found: /boot/grub Cannot determine root device. Assuming /dev/hda1 This error is probably caused by an invalid /etc/fstab Searching for default file ... found: /boot/grub/default Testing for an existing GRUB menu.lst file ... found: /boot/grub/menu.lst Searching for splash image ... none found, skipping ... Found kernel: /boot/vmlinuz-3.2.0-30-generic Found kernel: /boot/vmlinuz-3.2.0-29-generic Found kernel: /boot/vmlinuz-3.2.0-27-generic Found kernel: /boot/vmlinuz-3.2.0-26-generic Found GRUB 2: /boot/grub/core.img Found kernel: /boot/memtest86+.bin Updating /boot/grub/menu.lst ... done I have searched everywhere to find a solution to my problem, but can't find any solutions. If you need any log outputs to figure out the problem, please let me know which ones. Update: here is the output for grub.cfg # # DO NOT EDIT THIS FILE # # It is automatically generated by grub-mkconfig using templates # from /etc/grub.d and settings from /etc/default/grub # ### BEGIN /etc/grub.d/00_header ### if [ -s $prefix/grubenv ]; then set have_grubenv=true load_env fi set default="0" if [ "${prev_saved_entry}" ]; then set saved_entry="${prev_saved_entry}" save_env saved_entry set prev_saved_entry= save_env prev_saved_entry set boot_once=true fi function savedefault { if [ -z "${boot_once}" ]; then saved_entry="${chosen}" save_env saved_entry fi } function recordfail { set recordfail=1 if [ -n "${have_grubenv}" ]; then if [ -z "${boot_once}" ]; then save_env recordfail; fi; fi } function load_video { insmod vbe insmod vga insmod video_bochs insmod video_cirrus } insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b if loadfont /usr/share/grub/unicode.pf2 ; then set gfxmode=auto load_video insmod gfxterm insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b set locale_dir=($root)/boot/grub/locale set lang=nb_NO insmod gettext fi terminal_output gfxterm if [ "${recordfail}" = 1 ]; then set timeout=-1 else set timeout=10 fi ### END /etc/grub.d/00_header ### ### BEGIN /etc/grub.d/05_debian_theme ### set menu_color_normal=white/black set menu_color_highlight=black/light-gray if background_color 44,0,30; then clear fi ### END /etc/grub.d/05_debian_theme ### ### BEGIN /etc/grub.d/10_linux ### function gfxmode { set gfxpayload="${1}" if [ "${1}" = "keep" ]; then set vt_handoff=vt.handoff=7 else set vt_handoff= fi } if [ "${recordfail}" != 1 ]; then if [ -e ${prefix}/gfxblacklist.txt ]; then if hwmatch ${prefix}/gfxblacklist.txt 3; then if [ ${match} = 0 ]; then set linux_gfx_mode=keep else set linux_gfx_mode=text fi else set linux_gfx_mode=text fi else set linux_gfx_mode=keep fi else set linux_gfx_mode=text fi export linux_gfx_mode if [ "${linux_gfx_mode}" != "text" ]; then load_video; fi menuentry 'Ubuntu, med Linux 3.2.0-26-generic' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b linux /boot/vmlinuz-3.2.0-26-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-26-generic } menuentry 'Ubuntu, med Linux 3.2.0-26-generic (gjenopprettelsesmodus)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b echo 'Laster Linux 3.2.0-26-generic ...' linux /boot/vmlinuz-3.2.0-26-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-26-generic } submenu "Previous Linux versions" { menuentry 'Ubuntu, med Linux 3.2.0-25-generic' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b linux /boot/vmlinuz-3.2.0-25-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-25-generic } menuentry 'Ubuntu, med Linux 3.2.0-25-generic (gjenopprettelsesmodus)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b echo 'Laster Linux 3.2.0-25-generic ...' linux /boot/vmlinuz-3.2.0-25-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-25-generic } menuentry 'Ubuntu, med Linux 3.2.0-24-generic' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b linux /boot/vmlinuz-3.2.0-24-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-24-generic } menuentry 'Ubuntu, med Linux 3.2.0-24-generic (gjenopprettelsesmodus)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b echo 'Laster Linux 3.2.0-24-generic ...' linux /boot/vmlinuz-3.2.0-24-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-24-generic } menuentry 'Ubuntu, med Linux 3.2.0-23-generic' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b linux /boot/vmlinuz-3.2.0-23-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-23-generic } menuentry 'Ubuntu, med Linux 3.2.0-23-generic (gjenopprettelsesmodus)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b echo 'Laster Linux 3.2.0-23-generic ...' linux /boot/vmlinuz-3.2.0-23-generic root=UUID=270c7c58-06d8-4e6b-b9bb-8d92f46adc0b ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-23-generic } } ### END /etc/grub.d/10_linux ### ### BEGIN /etc/grub.d/20_linux_xen ### ### END /etc/grub.d/20_linux_xen ### ### BEGIN /etc/grub.d/20_memtest86+ ### menuentry "Memory test (memtest86+)" { insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b linux16 /boot/memtest86+.bin } menuentry "Memory test (memtest86+, serial console 115200)" { insmod part_msdos insmod ext2 set root='(hd2,msdos1)' search --no-floppy --fs-uuid --set=root 270c7c58-06d8-4e6b-b9bb-8d92f46adc0b linux16 /boot/memtest86+.bin console=ttyS0,115200n8 } ### END /etc/grub.d/20_memtest86+ ### ### BEGIN /etc/grub.d/30_os-prober ### menuentry "Windows 7 (loader) (on /dev/sdb1)" --class windows --class os { insmod part_msdos insmod ntfs set root='(hd1,msdos1)' search --no-floppy --fs-uuid --set=root 448AF3CE8AF3BA8E chainloader +1 } ### END /etc/grub.d/30_os-prober ### ### BEGIN /etc/grub.d/40_custom ### # This file provides an easy way to add custom menu entries. Simply type the # menu entries you want to add after this comment. Be careful not to change # the 'exec tail' line above. ### END /etc/grub.d/40_custom ### ### BEGIN /etc/grub.d/41_custom ### if [ -f $prefix/custom.cfg ]; then source $prefix/custom.cfg; fi ### END /etc/grub.d/41_custom ### How can I set kernel 3.2.0.30 as the default kernel? According to this file, kernel 3.2.0-30 does not exist.

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  • Upload File to Windows Azure Blob in Chunks through ASP.NET MVC, JavaScript and HTML5

    - by Shaun
    Originally posted on: http://geekswithblogs.net/shaunxu/archive/2013/07/01/upload-file-to-windows-azure-blob-in-chunks-through-asp.net.aspxMany people are using Windows Azure Blob Storage to store their data in the cloud. Blob storage provides 99.9% availability with easy-to-use API through .NET SDK and HTTP REST. For example, we can store JavaScript files, images, documents in blob storage when we are building an ASP.NET web application on a Web Role in Windows Azure. Or we can store our VHD files in blob and mount it as a hard drive in our cloud service. If you are familiar with Windows Azure, you should know that there are two kinds of blob: page blob and block blob. The page blob is optimized for random read and write, which is very useful when you need to store VHD files. The block blob is optimized for sequential/chunk read and write, which has more common usage. Since we can upload block blob in blocks through BlockBlob.PutBlock, and them commit them as a whole blob with invoking the BlockBlob.PutBlockList, it is very powerful to upload large files, as we can upload blocks in parallel, and provide pause-resume feature. There are many documents, articles and blog posts described on how to upload a block blob. Most of them are focus on the server side, which means when you had received a big file, stream or binaries, how to upload them into blob storage in blocks through .NET SDK.  But the problem is, how can we upload these large files from client side, for example, a browser. This questioned to me when I was working with a Chinese customer to help them build a network disk production on top of azure. The end users upload their files from the web portal, and then the files will be stored in blob storage from the Web Role. My goal is to find the best way to transform the file from client (end user’s machine) to the server (Web Role) through browser. In this post I will demonstrate and describe what I had done, to upload large file in chunks with high speed, and save them as blocks into Windows Azure Blob Storage.   Traditional Upload, Works with Limitation The simplest way to implement this requirement is to create a web page with a form that contains a file input element and a submit button. 1: @using (Html.BeginForm("About", "Index", FormMethod.Post, new { enctype = "multipart/form-data" })) 2: { 3: <input type="file" name="file" /> 4: <input type="submit" value="upload" /> 5: } And then in the backend controller, we retrieve the whole content of this file and upload it in to the blob storage through .NET SDK. We can split the file in blocks and upload them in parallel and commit. The code had been well blogged in the community. 1: [HttpPost] 2: public ActionResult About(HttpPostedFileBase file) 3: { 4: var container = _client.GetContainerReference("test"); 5: container.CreateIfNotExists(); 6: var blob = container.GetBlockBlobReference(file.FileName); 7: var blockDataList = new Dictionary<string, byte[]>(); 8: using (var stream = file.InputStream) 9: { 10: var blockSizeInKB = 1024; 11: var offset = 0; 12: var index = 0; 13: while (offset < stream.Length) 14: { 15: var readLength = Math.Min(1024 * blockSizeInKB, (int)stream.Length - offset); 16: var blockData = new byte[readLength]; 17: offset += stream.Read(blockData, 0, readLength); 18: blockDataList.Add(Convert.ToBase64String(BitConverter.GetBytes(index)), blockData); 19:  20: index++; 21: } 22: } 23:  24: Parallel.ForEach(blockDataList, (bi) => 25: { 26: blob.PutBlock(bi.Key, new MemoryStream(bi.Value), null); 27: }); 28: blob.PutBlockList(blockDataList.Select(b => b.Key).ToArray()); 29:  30: return RedirectToAction("About"); 31: } This works perfect if we selected an image, a music or a small video to upload. But if I selected a large file, let’s say a 6GB HD-movie, after upload for about few minutes the page will be shown as below and the upload will be terminated. In ASP.NET there is a limitation of request length and the maximized request length is defined in the web.config file. It’s a number which less than about 4GB. So if we want to upload a really big file, we cannot simply implement in this way. Also, in Windows Azure, a cloud service network load balancer will terminate the connection if exceed the timeout period. From my test the timeout looks like 2 - 3 minutes. Hence, when we need to upload a large file we cannot just use the basic HTML elements. Besides the limitation mentioned above, the simple HTML file upload cannot provide rich upload experience such as chunk upload, pause and pause-resume. So we need to find a better way to upload large file from the client to the server.   Upload in Chunks through HTML5 and JavaScript In order to break those limitation mentioned above we will try to upload the large file in chunks. This takes some benefit to us such as - No request size limitation: Since we upload in chunks, we can define the request size for each chunks regardless how big the entire file is. - No timeout problem: The size of chunks are controlled by us, which means we should be able to make sure request for each chunk upload will not exceed the timeout period of both ASP.NET and Windows Azure load balancer. It was a big challenge to upload big file in chunks until we have HTML5. There are some new features and improvements introduced in HTML5 and we will use them to implement our solution.   In HTML5, the File interface had been improved with a new method called “slice”. It can be used to read part of the file by specifying the start byte index and the end byte index. For example if the entire file was 1024 bytes, file.slice(512, 768) will read the part of this file from the 512nd byte to 768th byte, and return a new object of interface called "Blob”, which you can treat as an array of bytes. In fact,  a Blob object represents a file-like object of immutable, raw data. The File interface is based on Blob, inheriting blob functionality and expanding it to support files on the user's system. For more information about the Blob please refer here. File and Blob is very useful to implement the chunk upload. We will use File interface to represent the file the user selected from the browser and then use File.slice to read the file in chunks in the size we wanted. For example, if we wanted to upload a 10MB file with 512KB chunks, then we can read it in 512KB blobs by using File.slice in a loop.   Assuming we have a web page as below. User can select a file, an input box to specify the block size in KB and a button to start upload. 1: <div> 2: <input type="file" id="upload_files" name="files[]" /><br /> 3: Block Size: <input type="number" id="block_size" value="512" name="block_size" />KB<br /> 4: <input type="button" id="upload_button_blob" name="upload" value="upload (blob)" /> 5: </div> Then we can have the JavaScript function to upload the file in chunks when user clicked the button. 1: <script type="text/javascript"> 1: 2: $(function () { 3: $("#upload_button_blob").click(function () { 4: }); 5: });</script> Firstly we need to ensure the client browser supports the interfaces we are going to use. Just try to invoke the File, Blob and FormData from the “window” object. If any of them is “undefined” the condition result will be “false” which means your browser doesn’t support these premium feature and it’s time for you to get your browser updated. FormData is another new feature we are going to use in the future. It could generate a temporary form for us. We will use this interface to create a form with chunk and associated metadata when invoked the service through ajax. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: if (window.File && window.Blob && window.FormData) { 4: alert("Your brwoser is awesome, let's rock!"); 5: } 6: else { 7: alert("Oh man plz update to a modern browser before try is cool stuff out."); 8: return; 9: } 10: }); Each browser supports these interfaces by their own implementation and currently the Blob, File and File.slice are supported by Chrome 21, FireFox 13, IE 10, Opera 12 and Safari 5.1 or higher. After that we worked on the files the user selected one by one since in HTML5, user can select multiple files in one file input box. 1: var files = $("#upload_files")[0].files; 2: for (var i = 0; i < files.length; i++) { 3: var file = files[i]; 4: var fileSize = file.size; 5: var fileName = file.name; 6: } Next, we calculated the start index and end index for each chunks based on the size the user specified from the browser. We put them into an array with the file name and the index, which will be used when we upload chunks into Windows Azure Blob Storage as blocks since we need to specify the target blob name and the block index. At the same time we will store the list of all indexes into another variant which will be used to commit blocks into blob in Azure Storage once all chunks had been uploaded successfully. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10:  11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: var blockSizeInKB = $("#block_size").val(); 14: var blockSize = blockSizeInKB * 1024; 15: var blocks = []; 16: var offset = 0; 17: var index = 0; 18: var list = ""; 19: while (offset < fileSize) { 20: var start = offset; 21: var end = Math.min(offset + blockSize, fileSize); 22:  23: blocks.push({ 24: name: fileName, 25: index: index, 26: start: start, 27: end: end 28: }); 29: list += index + ","; 30:  31: offset = end; 32: index++; 33: } 34: } 35: }); Now we have all chunks’ information ready. The next step should be upload them one by one to the server side, and at the server side when received a chunk it will upload as a block into Blob Storage, and finally commit them with the index list through BlockBlobClient.PutBlockList. But since all these invokes are ajax calling, which means not synchronized call. So we need to introduce a new JavaScript library to help us coordinate the asynchronize operation, which named “async.js”. You can download this JavaScript library here, and you can find the document here. I will not explain this library too much in this post. We will put all procedures we want to execute as a function array, and pass into the proper function defined in async.js to let it help us to control the execution sequence, in series or in parallel. Hence we will define an array and put the function for chunk upload into this array. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4:  5: // start to upload each files in chunks 6: var files = $("#upload_files")[0].files; 7: for (var i = 0; i < files.length; i++) { 8: var file = files[i]; 9: var fileSize = file.size; 10: var fileName = file.name; 11: // calculate the start and end byte index for each blocks(chunks) 12: // with the index, file name and index list for future using 13: ... ... 14:  15: // define the function array and push all chunk upload operation into this array 16: blocks.forEach(function (block) { 17: putBlocks.push(function (callback) { 18: }); 19: }); 20: } 21: }); 22: }); As you can see, I used File.slice method to read each chunks based on the start and end byte index we calculated previously, and constructed a temporary HTML form with the file name, chunk index and chunk data through another new feature in HTML5 named FormData. Then post this form to the backend server through jQuery.ajax. This is the key part of our solution. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: blocks.forEach(function (block) { 15: putBlocks.push(function (callback) { 16: // load blob based on the start and end index for each chunks 17: var blob = file.slice(block.start, block.end); 18: // put the file name, index and blob into a temporary from 19: var fd = new FormData(); 20: fd.append("name", block.name); 21: fd.append("index", block.index); 22: fd.append("file", blob); 23: // post the form to backend service (asp.net mvc controller action) 24: $.ajax({ 25: url: "/Home/UploadInFormData", 26: data: fd, 27: processData: false, 28: contentType: "multipart/form-data", 29: type: "POST", 30: success: function (result) { 31: if (!result.success) { 32: alert(result.error); 33: } 34: callback(null, block.index); 35: } 36: }); 37: }); 38: }); 39: } 40: }); Then we will invoke these functions one by one by using the async.js. And once all functions had been executed successfully I invoked another ajax call to the backend service to commit all these chunks (blocks) as the blob in Windows Azure Storage. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.series(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); That’s all in the client side. The outline of our logic would be - Calculate the start and end byte index for each chunks based on the block size. - Defined the functions of reading the chunk form file and upload the content to the backend service through ajax. - Execute the functions defined in previous step with “async.js”. - Commit the chunks by invoking the backend service in Windows Azure Storage finally.   Save Chunks as Blocks into Blob Storage In above we finished the client size JavaScript code. It uploaded the file in chunks to the backend service which we are going to implement in this step. We will use ASP.NET MVC as our backend service, and it will receive the chunks, upload into Windows Azure Bob Storage in blocks, then finally commit as one blob. As in the client side we uploaded chunks by invoking the ajax call to the URL "/Home/UploadInFormData", I created a new action under the Index controller and it only accepts HTTP POST request. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: } 8: catch (Exception e) 9: { 10: error = e.ToString(); 11: } 12:  13: return new JsonResult() 14: { 15: Data = new 16: { 17: success = string.IsNullOrWhiteSpace(error), 18: error = error 19: } 20: }; 21: } Then I retrieved the file name, index and the chunk content from the Request.Form object, which was passed from our client side. And then, used the Windows Azure SDK to create a blob container (in this case we will use the container named “test”.) and create a blob reference with the blob name (same as the file name). Then uploaded the chunk as a block of this blob with the index, since in Blob Storage each block must have an index (ID) associated with so that finally we can put all blocks as one blob by specifying their block ID list. 1: [HttpPost] 2: public JsonResult UploadInFormData() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var index = int.Parse(Request.Form["index"]); 9: var file = Request.Files[0]; 10: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 11:  12: var container = _client.GetContainerReference("test"); 13: container.CreateIfNotExists(); 14: var blob = container.GetBlockBlobReference(name); 15: blob.PutBlock(id, file.InputStream, null); 16: } 17: catch (Exception e) 18: { 19: error = e.ToString(); 20: } 21:  22: return new JsonResult() 23: { 24: Data = new 25: { 26: success = string.IsNullOrWhiteSpace(error), 27: error = error 28: } 29: }; 30: } Next, I created another action to commit the blocks into blob once all chunks had been uploaded. Similarly, I retrieved the blob name from the Request.Form. I also retrieved the chunks ID list, which is the block ID list from the Request.Form in a string format, split them as a list, then invoked the BlockBlob.PutBlockList method. After that our blob will be shown in the container and ready to be download. 1: [HttpPost] 2: public JsonResult Commit() 3: { 4: var error = string.Empty; 5: try 6: { 7: var name = Request.Form["name"]; 8: var list = Request.Form["list"]; 9: var ids = list 10: .Split(',') 11: .Where(id => !string.IsNullOrWhiteSpace(id)) 12: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 13: .ToArray(); 14:  15: var container = _client.GetContainerReference("test"); 16: container.CreateIfNotExists(); 17: var blob = container.GetBlockBlobReference(name); 18: blob.PutBlockList(ids); 19: } 20: catch (Exception e) 21: { 22: error = e.ToString(); 23: } 24:  25: return new JsonResult() 26: { 27: Data = new 28: { 29: success = string.IsNullOrWhiteSpace(error), 30: error = error 31: } 32: }; 33: } Now we finished all code we need. The whole process of uploading would be like this below. Below is the full client side JavaScript code. 1: <script type="text/javascript" src="~/Scripts/async.js"></script> 2: <script type="text/javascript"> 3: $(function () { 4: $("#upload_button_blob").click(function () { 5: // assert the browser support html5 6: if (window.File && window.Blob && window.FormData) { 7: alert("Your brwoser is awesome, let's rock!"); 8: } 9: else { 10: alert("Oh man plz update to a modern browser before try is cool stuff out."); 11: return; 12: } 13:  14: // start to upload each files in chunks 15: var files = $("#upload_files")[0].files; 16: for (var i = 0; i < files.length; i++) { 17: var file = files[i]; 18: var fileSize = file.size; 19: var fileName = file.name; 20:  21: // calculate the start and end byte index for each blocks(chunks) 22: // with the index, file name and index list for future using 23: var blockSizeInKB = $("#block_size").val(); 24: var blockSize = blockSizeInKB * 1024; 25: var blocks = []; 26: var offset = 0; 27: var index = 0; 28: var list = ""; 29: while (offset < fileSize) { 30: var start = offset; 31: var end = Math.min(offset + blockSize, fileSize); 32:  33: blocks.push({ 34: name: fileName, 35: index: index, 36: start: start, 37: end: end 38: }); 39: list += index + ","; 40:  41: offset = end; 42: index++; 43: } 44:  45: // define the function array and push all chunk upload operation into this array 46: var putBlocks = []; 47: blocks.forEach(function (block) { 48: putBlocks.push(function (callback) { 49: // load blob based on the start and end index for each chunks 50: var blob = file.slice(block.start, block.end); 51: // put the file name, index and blob into a temporary from 52: var fd = new FormData(); 53: fd.append("name", block.name); 54: fd.append("index", block.index); 55: fd.append("file", blob); 56: // post the form to backend service (asp.net mvc controller action) 57: $.ajax({ 58: url: "/Home/UploadInFormData", 59: data: fd, 60: processData: false, 61: contentType: "multipart/form-data", 62: type: "POST", 63: success: function (result) { 64: if (!result.success) { 65: alert(result.error); 66: } 67: callback(null, block.index); 68: } 69: }); 70: }); 71: }); 72:  73: // invoke the functions one by one 74: // then invoke the commit ajax call to put blocks into blob in azure storage 75: async.series(putBlocks, function (error, result) { 76: var data = { 77: name: fileName, 78: list: list 79: }; 80: $.post("/Home/Commit", data, function (result) { 81: if (!result.success) { 82: alert(result.error); 83: } 84: else { 85: alert("done!"); 86: } 87: }); 88: }); 89: } 90: }); 91: }); 92: </script> And below is the full ASP.NET MVC controller code. 1: public class HomeController : Controller 2: { 3: private CloudStorageAccount _account; 4: private CloudBlobClient _client; 5:  6: public HomeController() 7: : base() 8: { 9: _account = CloudStorageAccount.Parse(CloudConfigurationManager.GetSetting("DataConnectionString")); 10: _client = _account.CreateCloudBlobClient(); 11: } 12:  13: public ActionResult Index() 14: { 15: ViewBag.Message = "Modify this template to jump-start your ASP.NET MVC application."; 16:  17: return View(); 18: } 19:  20: [HttpPost] 21: public JsonResult UploadInFormData() 22: { 23: var error = string.Empty; 24: try 25: { 26: var name = Request.Form["name"]; 27: var index = int.Parse(Request.Form["index"]); 28: var file = Request.Files[0]; 29: var id = Convert.ToBase64String(BitConverter.GetBytes(index)); 30:  31: var container = _client.GetContainerReference("test"); 32: container.CreateIfNotExists(); 33: var blob = container.GetBlockBlobReference(name); 34: blob.PutBlock(id, file.InputStream, null); 35: } 36: catch (Exception e) 37: { 38: error = e.ToString(); 39: } 40:  41: return new JsonResult() 42: { 43: Data = new 44: { 45: success = string.IsNullOrWhiteSpace(error), 46: error = error 47: } 48: }; 49: } 50:  51: [HttpPost] 52: public JsonResult Commit() 53: { 54: var error = string.Empty; 55: try 56: { 57: var name = Request.Form["name"]; 58: var list = Request.Form["list"]; 59: var ids = list 60: .Split(',') 61: .Where(id => !string.IsNullOrWhiteSpace(id)) 62: .Select(id => Convert.ToBase64String(BitConverter.GetBytes(int.Parse(id)))) 63: .ToArray(); 64:  65: var container = _client.GetContainerReference("test"); 66: container.CreateIfNotExists(); 67: var blob = container.GetBlockBlobReference(name); 68: blob.PutBlockList(ids); 69: } 70: catch (Exception e) 71: { 72: error = e.ToString(); 73: } 74:  75: return new JsonResult() 76: { 77: Data = new 78: { 79: success = string.IsNullOrWhiteSpace(error), 80: error = error 81: } 82: }; 83: } 84: } And if we selected a file from the browser we will see our application will upload chunks in the size we specified to the server through ajax call in background, and then commit all chunks in one blob. Then we can find the blob in our Windows Azure Blob Storage.   Optimized by Parallel Upload In previous example we just uploaded our file in chunks. This solved the problem that ASP.NET MVC request content size limitation as well as the Windows Azure load balancer timeout. But it might introduce the performance problem since we uploaded chunks in sequence. In order to improve the upload performance we could modify our client side code a bit to make the upload operation invoked in parallel. The good news is that, “async.js” library provides the parallel execution function. If you remembered the code we invoke the service to upload chunks, it utilized “async.series” which means all functions will be executed in sequence. Now we will change this code to “async.parallel”. This will invoke all functions in parallel. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallel(putBlocks, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: }); In this way all chunks will be uploaded to the server side at the same time to maximize the bandwidth usage. This should work if the file was not very large and the chunk size was not very small. But for large file this might introduce another problem that too many ajax calls are sent to the server at the same time. So the best solution should be, upload the chunks in parallel with maximum concurrency limitation. The code below specified the concurrency limitation to 4, which means at the most only 4 ajax calls could be invoked at the same time. 1: $("#upload_button_blob").click(function () { 2: // assert the browser support html5 3: ... ... 4: // start to upload each files in chunks 5: var files = $("#upload_files")[0].files; 6: for (var i = 0; i < files.length; i++) { 7: var file = files[i]; 8: var fileSize = file.size; 9: var fileName = file.name; 10: // calculate the start and end byte index for each blocks(chunks) 11: // with the index, file name and index list for future using 12: ... ... 13: // define the function array and push all chunk upload operation into this array 14: ... ... 15: // invoke the functions one by one 16: // then invoke the commit ajax call to put blocks into blob in azure storage 17: async.parallelLimit(putBlocks, 4, function (error, result) { 18: var data = { 19: name: fileName, 20: list: list 21: }; 22: $.post("/Home/Commit", data, function (result) { 23: if (!result.success) { 24: alert(result.error); 25: } 26: else { 27: alert("done!"); 28: } 29: }); 30: }); 31: } 32: });   Summary In this post we discussed how to upload files in chunks to the backend service and then upload them into Windows Azure Blob Storage in blocks. We focused on the frontend side and leverage three new feature introduced in HTML 5 which are - File.slice: Read part of the file by specifying the start and end byte index. - Blob: File-like interface which contains the part of the file content. - FormData: Temporary form element that we can pass the chunk alone with some metadata to the backend service. Then we discussed the performance consideration of chunk uploading. Sequence upload cannot provide maximized upload speed, but the unlimited parallel upload might crash the browser and server if too many chunks. So we finally came up with the solution to upload chunks in parallel with the concurrency limitation. We also demonstrated how to utilize “async.js” JavaScript library to help us control the asynchronize call and the parallel limitation.   Regarding the chunk size and the parallel limitation value there is no “best” value. You need to test vary composition and find out the best one for your particular scenario. It depends on the local bandwidth, client machine cores and the server side (Windows Azure Cloud Service Virtual Machine) cores, memory and bandwidth. Below is one of my performance test result. The client machine was Windows 8 IE 10 with 4 cores. I was using Microsoft Cooperation Network. The web site was hosted on Windows Azure China North data center (in Beijing) with one small web role (1.7GB 1 core CPU, 1.75GB memory with 100Mbps bandwidth). The test cases were - Chunk size: 512KB, 1MB, 2MB, 4MB. - Upload Mode: Sequence, parallel (unlimited), parallel with limit (4 threads, 8 threads). - Chunk Format: base64 string, binaries. - Target file: 100MB. - Each case was tested 3 times. Below is the test result chart. Some thoughts, but not guidance or best practice: - Parallel gets better performance than series. - No significant performance improvement between parallel 4 threads and 8 threads. - Transform with binaries provides better performance than base64. - In all cases, chunk size in 1MB - 2MB gets better performance.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Convert .png images into a .ppt presentation on Linux?

    - by darenw
    I've created a presentation as a series of .png images, one per slide. What is a good way to convert these into a .ppt (PowerPoint) that I can give to some audio-visual person? I'm entirely on Linux, with no Windows or Mac software available. (Or maybe PowerPoint isn't the only game in town for presentation file formats?)

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  • Why do I get completely different results when saving a BitmapSource to bmp, jpeg, and png in WPF

    - by DanM
    I wrote a little utility class that saves BitmapSource objects to image files. The image files can be either bmp, jpeg, or png. Here is the code: public class BitmapProcessor { public void SaveAsBmp(BitmapSource bitmapSource, string path) { Save(bitmapSource, path, new BmpBitmapEncoder()); } public void SaveAsJpg(BitmapSource bitmapSource, string path) { Save(bitmapSource, path, new JpegBitmapEncoder()); } public void SaveAsPng(BitmapSource bitmapSource, string path) { Save(bitmapSource, path, new PngBitmapEncoder()); } private void Save(BitmapSource bitmapSource, string path, BitmapEncoder encoder) { using (var stream = new FileStream(path, FileMode.Create)) { encoder.Frames.Add(BitmapFrame.Create(bitmapSource)); encoder.Save(stream); } } } Each of the three Save methods work, but I get unexpected results with bmp and jpeg. Png is the only format that produces an exact reproduction of what I see if I show the BitmapSource on screen using a WPF Image control. Here are the results: BMP - too dark JPEG - too saturated PNG - correct Why am I getting completely different results for different file types? I should note that the BitmapSource in my example uses an alpha value of 0.1 (which is why it appears very desaturated), but it should be possible to show the resulting colors in any image format. I know if I take a screen capture using something like HyperSnap, it will look correct regardless of what file type I save to. Here's a HyperSnap screen capture saved as a bmp: As you can see, this isn't a problem, so there's definitely something strange about WPF's image encoders. Do I have a setting wrong? Am I missing something?

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  • Masking FLV video in AS3 with PNG alpha channel.

    - by James Roberts
    Hey there, I'm trying to mask an FLV with a PNG alpha channel. I'm using BitmapData (from a PNG) but it's not working. Is there anything I'm missing? Cut up code below: var musclesLoader:Loader = new Loader(); var musclesContainer:Sprite = new Sprite(); var musclesImage:Bitmap = new Bitmap(); var musclesBitmapData:BitmapData; var musclesVideo:Video = new Video(752, 451.2); var connection:NetConnection = new NetConnection(); var stream:NetStream; function loadMuscles():void { musclesLoader.load(new URLRequest('img/muscles.png')); musclesLoader.contentLoaderInfo.addEventListener(Event.COMPLETE, musclesComplete); } function musclesComplete():void { musclesBitmapData = new BitmapData(musclesLoader.content.width, musclesLoader.content.height, true, 0x000000); musclesImage.bitmapData = musclesBitmapData; musclesImage.smoothing = true; musclesContainer.addChild(musclesImage); contentContainer.addChild(musclesContainer); } function loadMusclesVideo():void { connection.connect(null); stream = new NetStream(connection); stream.client = this; musclesVideo.mask = musclesBitmapData; stage.addChild(musclesVideo); musclesVideo.attachNetStream(stream); stream.bufferTime = 1; stream.receiveAudio(true); stream.receiveVideo(true); stream.play("vid/muscles.flv"); } Outside this code I have a function that adds the containers to the stage, etc and places the objects in the appropriate spots. It sort of works - the mask applies, but in a square (the size of the boundaries of musclesBitmapData) rather than with the shape of the alpha channel. Is this the right way to go about this?

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  • Retrieve Performance Data from SOA Infrastructure Database

    - by fip
    My earlier blog posting shows how to enable, retrieve and interpret BPEL engine performance statistics to aid performance troubleshooting. The strength of BPEL engine statistics at EM is its break down per request. But there are some limitations with the BPEL performance statistics mentioned in that blog posting: The statistics were stored in memory instead of being persisted. To avoid memory overflow, the data are stored to a buffer with limited size. When the statistic entries exceed the limitation, old data will be flushed out to give ways to new statistics. Therefore it can only keep the last X number of entries of data. The statistics 5 hour ago may not be there anymore. The BPEL engine performance statistics only includes latencies. It does not provide throughputs. Fortunately, Oracle SOA Suite runs with the SOA Infrastructure database and a lot of performance data are naturally persisted there. It is at a more coarse grain than the in-memory BPEL Statistics, but it does have its own strengths as it is persisted. Here I would like offer examples of some basic SQL queries you can run against the infrastructure database of Oracle SOA Suite 11G to acquire the performance statistics for a given period of time. You can run it immediately after you modify the date range to match your actual system. 1. Asynchronous/one-way messages incoming rates The following query will show number of messages sent to one-way/async BPEL processes during a given time period, organized by process names and states select composite_name composite, state, count(*) Count from dlv_message where receive_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and receive_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, state order by Count; 2. Throughput of BPEL process instances The following query shows the number of synchronous and asynchronous process instances created during a given time period. It list instances of all states, including the unfinished and faulted ones. The results will include all composites cross all SOA partitions select state, count(*) Count, composite_name composite, component_name,componenttype from cube_instance where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype order by count(*) desc; 3. Throughput and latencies of BPEL process instances This query is augmented on the previous one, providing more comprehensive information. It gives not only throughput but also the maximum, minimum and average elapse time BPEL process instances. select composite_name Composite, component_name Process, componenttype, state, count(*) Count, trunc(Max(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MaxTime, trunc(Min(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MinTime, trunc(AVG(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) AvgTime from cube_instance where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype, state order by count(*) desc;   4. Combine all together Now let's combine all of these 3 queries together, and parameterize the start and end time stamps to make the script a bit more robust. The following script will prompt for the start and end time before querying against the database: accept startTime prompt 'Enter start time (YYYY-MM-DD HH24:MI:SS)' accept endTime prompt 'Enter end time (YYYY-MM-DD HH24:MI:SS)' Prompt "==== Rejected Messages ===="; REM 2012-10-24 21:00:00 REM 2012-10-24 21:59:59 select count(*), composite_dn from rejected_message where created_time >= to_timestamp('&&StartTime','YYYY-MM-DD HH24:MI:SS') and created_time <= to_timestamp('&&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_dn; Prompt " "; Prompt "==== Throughput of one-way/asynchronous messages ===="; select state, count(*) Count, composite_name composite from dlv_message where receive_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS') and receive_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_name, state order by Count; Prompt " "; Prompt "==== Throughput and latency of BPEL process instances ====" select state, count(*) Count, trunc(Max(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MaxTime, trunc(Min(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MinTime, trunc(AVG(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) AvgTime, composite_name Composite, component_name Process, componenttype from cube_instance where creation_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype, state order by count(*) desc;  

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  • What is the significance of '*' (star, asterisk) in the file listing results?

    - by vfclists
    I have noticed that some of my files have an asterisk at end. Does the asterisk at the end have any particular significance? I think they are mostly executable and displayed in green by the ls command. You will see that ./bkmp* and ./bkmp0* have an asterisk at the end. They are executable bash scripts. Here's my output: drwxr-xr-x 7 username username 4096 Oct 2 18:28 ./ drwxr-xr-x 8 root root 4096 Oct 2 09:25 ../ -rw-r--r-- 1 username username 3724 Sep 22 03:06 .bashrc -rwxr--r-- 1 username username 319 Sep 22 03:42 .bkmp* -rwxr--r-- 1 username username 324 Sep 29 23:30 .bkmp0* drwx------ 2 username username 4096 Sep 17 13:52 .cache/ -rw-r--r-- 1 username username 675 Sep 17 13:37 .profile drwx------ 2 username username 4096 Sep 22 10:10 .ssh/ drwx------ 2 username username 4096 Sep 24 19:49 .ssh.local/ drwxr-xr-x 2 username username 4096 Sep 22 04:10 archives/ drwxr-xr-x 3 username username 4096 Sep 24 19:51 home/ -rw-r--r-- 1 username username 27511 Sep 24 19:51 username_backup.20120924_1908.tar.gz

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  • Ubuntu btrfs: how to remove rootflags=subvol=@ from grub.cfg

    - by mnpria
    When i mount "btrfs" as a root filesytem, the mount info is as below: root@ubuntu1304Btrfs:~# mount /dev/mapper/ubuntu1304Btrfs--vg-root on / type btrfs (rw,subvol=@) Is there a way to have a mount info without the "subvol" information ? I have tried executing what was mentioned here. I also updated the grub.cfg. Still rootflags=subvol=@ is not removed. Is there a way to remove this subvol information ? root@ubuntu1304Btrfs:/home# mount /dev/mapper/ubuntu1304Btrfs--vg-root on / type btrfs (rw,subvol=@) /dev/mapper/ubuntu1304Btrfs--vg-root on /home type btrfs (rw,subvol=@home) root@ubuntu1304Btrfs:/# stat / File: ‘/’ Size: 262 Blocks: 0 IO Block: 4096 directory Device: 12h/18d Inode: 256 Links: 1 Access: (0755/drwxr-xr-x) Uid: ( 0/ root) Gid: ( 0/ root) Access: 2013-11-11 19:56:04.548121873 +0530 Modify: 2013-11-11 19:55:18.008120103 +0530 Change: 2013-11-11 19:55:18.008120103 +0530 Birth: - root@ubuntu1304Btrfs:/# stat /home/ File: ‘/home/’ Size: 230 Blocks: 0 IO Block: 4096 directory Device: 19h/25d Inode: 256 Links: 1 Access: (0755/drwxr-xr-x) Uid: ( 0/ root) Gid: ( 0/ root) Access: 2013-11-12 12:24:52.346377976 +0530 Modify: 2013-11-12 12:24:50.338377900 +0530 Change: 2013-11-12 12:24:50.338377900 +0530 Birth: -

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  • can not install gimp

    - by user71700
    I tried to install Gimp but I get an error that there are unmet dependencies. How can I handle that. I am running UBUNTU 12.04 in 64 bit. This is the message I get: The following packages have unmet dependencies: gimp: Depends: python-gtk2 (= 2.8.0) but 2.24.0-3 is to be installed Depends: libc6 (= 2.15) but 2.15-0ubuntu10 is to be installed Depends: libfontconfig1 (= 2.8.0) but 2.8.0-3ubuntu9 is to be installed Depends: libgdk-pixbuf2.0-0 (= 2.22.0) but 2.26.1-1 is to be installed Depends: libglib2.0-0 (= 2.31.2) but 2.32.3-0ubuntu1 is to be installed Depends: libgtk2.0-0 (= 2.24.0) but 2.24.10-0ubuntu6 is to be installed Depends: libjpeg8 (= 8c) but 8c-2ubuntu7 is to be installed Depends: librsvg2-2 (= 2.14.4) but 2.36.1-0ubuntu1 is to be installed Depends: zlib1g (= 1:1.1.4) but 1:1.2.3.4.dfsg-3ubuntu4 is to be installed Depends: python (= 2.7.1-0ubuntu2) but 2.7.3-0ubuntu2 is to be installed

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  • Why are the colors worse on Ubuntu 12.04 than on Windows 7 on my Sony Vaio E-Series?

    - by Simon Hoare
    The colours look "lacking" and ever slightly blueish and rather washed-out and lacking in dimension. Graphics are ok - this page for example looks fine - but if I view something like a news site with high quality photos, the experience is not optimal and is noticeably inferior to Windows 7. Oddly, when I install Ubuntu as a VM on VirtualBox in Windows, the colours look as I expect them to. It's only on my dual-boot version of Ubuntu that they look wrong (not Wubi, although a previous Wubi-based installation had the same problem). Now, I have the proprietary ATI driver and I can use amdcccle to get the colours closer to what they should be, but I can't seem to do anything about colour depth. The depth settings in Xorg are all 24. I tried changing all three mentions of 24 to 32 but was forced into safety mode. Fortunately, I remembered where I'd been tinkering and got the file set back to 24.

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