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• Another "Windows 7 entry missing from Grub2" Question

  - by 4x10

  Like many before me had the following problem that after installing Ubuntu (with windows 7 already installed), the grub boot loader wouldnt show windows 7 as a boot option, though i can boot fine if I use the "Choose Boot Device" options on the x220. The difference is that I try using UEFI only so many answers didn't really fit my problem, though i tried several stuffs: after running boot repair it destroyed the ubuntu boot loader custom entry in /etc/grub.d/40_custom for windows which doesnt show up many update-grub and reboots trying windows repair recovery thing while being there i also did bootrec.exe /FixBoot and update-grub and reboot again and finaly because it was so much fun, i installed linux all over again, while formatting and deleting everything linux related before that. Now that i think of it, Ubuntu also didn't notice Windows being there during the Setup and it still doesnt according to the Boot Info from Boot Repair. Boot Info Script 0.61-git-patched [23 April 2012] ============================= Boot Info Summary: =============================== => No boot loader is installed in the MBR of /dev/sda. sda1: __________________________________________________________________________ File system: vfat Boot sector type: Windows 7: FAT32 Boot sector info: No errors found in the Boot Parameter Block. Operating System: Boot files: /efi/Boot/bootx64.efi /efi/ubuntu/grubx64.efi sda2: __________________________________________________________________________ File system: Boot sector type: - Boot sector info: Mounting failed: mount: unknown filesystem type '' sda3: __________________________________________________________________________ File system: ntfs Boot sector type: Windows Vista/7: NTFS Boot sector info: No errors found in the Boot Parameter Block. Operating System: Windows 7 Boot files: /Windows/System32/winload.exe sda4: __________________________________________________________________________ File system: ext4 Boot sector type: - Boot sector info: Operating System: Ubuntu precise (development branch) Boot files: /boot/grub/grub.cfg /etc/fstab sda5: __________________________________________________________________________ File system: ext4 Boot sector type: - Boot sector info: Operating System: Boot files: sda6: __________________________________________________________________________ File system: swap Boot sector type: - Boot sector info: ============================ Drive/Partition Info: ============================= Drive: sda _____________________________________________________________________ Disk /dev/sda: 320.1 GB, 320072933376 bytes 255 heads, 63 sectors/track, 38913 cylinders, total 625142448 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes Partition Boot Start Sector End Sector # of Sectors Id System /dev/sda1 1 625,142,447 625,142,447 ee GPT GUID Partition Table detected. Partition Start Sector End Sector # of Sectors System /dev/sda1 2,048 206,847 204,800 EFI System partition /dev/sda2 206,848 468,991 262,144 Microsoft Reserved Partition (Windows) /dev/sda3 468,992 170,338,303 169,869,312 Data partition (Windows/Linux) /dev/sda4 170,338,304 330,338,304 160,000,001 Data partition (Windows/Linux) /dev/sda5 330,338,305 617,141,039 286,802,735 Data partition (Windows/Linux) /dev/sda6 617,141,040 625,141,040 8,000,001 Swap partition (Linux) "blkid" output: ________________________________________________________________ Device UUID TYPE LABEL /dev/sda1 885C-ED1B vfat /dev/sda3 EE06CC0506CBCCB1 ntfs /dev/sda4 604dd3b2-64ca-4200-b8fb-820e8d0ca899 ext4 /dev/sda5 d62515fd-8120-4a74-b17b-0bdf244124a3 ext4 /dev/sda6 7078b649-fb2a-4c59-bd03-fd31ef440d37 swap ================================ Mount points: ================================= Device Mount_Point Type Options /dev/sda1 /boot/efi vfat (rw) /dev/sda4 / ext4 (rw,errors=remount-ro) /dev/sda5 /home ext4 (rw) =========================== sda4/boot/grub/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 "${boot_once}" ]; then save_env recordfail; fi; fi } function load_video { insmod efi_gop insmod efi_uga insmod video_bochs insmod video_cirrus } insmod part_gpt insmod ext2 set root='(hd0,gpt4)' search --no-floppy --fs-uuid --set=root 604dd3b2-64ca-4200-b8fb-820e8d0ca899 if loadfont /usr/share/grub/unicode.pf2 ; then set gfxmode=auto load_video insmod gfxterm insmod part_gpt insmod ext2 set root='(hd0,gpt4)' search --no-floppy --fs-uuid --set=root 604dd3b2-64ca-4200-b8fb-820e8d0ca899 set locale_dir=($root)/boot/grub/locale set lang=en_US 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, with Linux 3.2.0-20-generic' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_gpt insmod ext2 set root='(hd0,gpt4)' search --no-floppy --fs-uuid --set=root 604dd3b2-64ca-4200-b8fb-820e8d0ca899 linux /boot/vmlinuz-3.2.0-20-generic root=UUID=604dd3b2-64ca-4200-b8fb-820e8d0ca899 ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-20-generic } menuentry 'Ubuntu, with Linux 3.2.0-20-generic (recovery mode)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_gpt insmod ext2 set root='(hd0,gpt4)' search --no-floppy --fs-uuid --set=root 604dd3b2-64ca-4200-b8fb-820e8d0ca899 echo 'Loading Linux 3.2.0-20-generic ...' linux /boot/vmlinuz-3.2.0-20-generic root=UUID=604dd3b2-64ca-4200-b8fb-820e8d0ca899 ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-20-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_gpt insmod ext2 set root='(hd0,gpt4)' search --no-floppy --fs-uuid --set=root 604dd3b2-64ca-4200-b8fb-820e8d0ca899 linux16 /boot/memtest86+.bin } menuentry "Memory test (memtest86+, serial console 115200)" { insmod part_gpt insmod ext2 set root='(hd0,gpt4)' search --no-floppy --fs-uuid --set=root 604dd3b2-64ca-4200-b8fb-820e8d0ca899 linux16 /boot/memtest86+.bin console=ttyS0,115200n8 } ### END /etc/grub.d/20_memtest86+ ### ### BEGIN /etc/grub.d/30_os-prober ### ### 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 ### -------------------------------------------------------------------------------- =============================== sda4/etc/fstab: ================================ -------------------------------------------------------------------------------- # /etc/fstab: static file system information. # # Use 'blkid' to print the universally unique identifier for a # device; this may be used with UUID= as a more robust way to name devices # that works even if disks are added and removed. See fstab(5). # # <file system> <mount point> <type> <options> <dump> <pass> proc /proc proc nodev,noexec,nosuid 0 0 # / was on /dev/sda4 during installation UUID=604dd3b2-64ca-4200-b8fb-820e8d0ca899 / ext4 errors=remount-ro 0 1 # /boot/efi was on /dev/sda1 during installation UUID=885C-ED1B /boot/efi vfat defaults 0 1 # /home was on /dev/sda5 during installation UUID=d62515fd-8120-4a74-b17b-0bdf244124a3 /home ext4 defaults 0 2 # swap was on /dev/sda6 during installation UUID=7078b649-fb2a-4c59-bd03-fd31ef440d37 none swap sw 0 0 -------------------------------------------------------------------------------- =================== sda4: Location of files loaded by Grub: ==================== GiB - GB File Fragment(s) 129.422874451 = 138.966753280 boot/grub/grub.cfg 1 83.059570312 = 89.184534528 boot/initrd.img-3.2.0-20-generic 2 101.393131256 = 108.870045696 boot/vmlinuz-3.2.0-20-generic 1 83.059570312 = 89.184534528 initrd.img 2 101.393131256 = 108.870045696 vmlinuz 1 ADDITIONAL INFORMATION : =================== log of boot-repair 2012-04-25__23h40 =================== boot-repair version : 3.18-0ppa3~precise boot-sav version : 3.18-0ppa4~precise glade2script version : 0.3.2.1-0ppa7~precise internet: connected python-software-properties version : 0.82.7 0 upgraded, 0 newly installed, 1 reinstalled, 0 to remove and 591 not upgraded. dpkg-preconfigure: unable to re-open stdin: No such file or directory boot-repair is executed in installed-session (Ubuntu precise (development branch) , precise , Ubuntu , x86_64) WARNING: GPT (GUID Partition Table) detected on '/dev/sda'! The util fdisk doesn't support GPT. Use GNU Parted. =================== OSPROBER: /dev/sda4:The OS now in use - Ubuntu precise (development branch) CurrentSession:linux =================== BLKID: /dev/sda3: UUID="EE06CC0506CBCCB1" TYPE="ntfs" /dev/sda1: UUID="885C-ED1B" TYPE="vfat" /dev/sda4: UUID="604dd3b2-64ca-4200-b8fb-820e8d0ca899" TYPE="ext4" /dev/sda5: UUID="d62515fd-8120-4a74-b17b-0bdf244124a3" TYPE="ext4" /dev/sda6: UUID="7078b649-fb2a-4c59-bd03-fd31ef440d37" TYPE="swap" 1 disks with OS, 1 OS : 1 Linux, 0 MacOS, 0 Windows, 0 unknown type OS. WARNING: GPT (GUID Partition Table) detected on '/dev/sda'! The util sfdisk doesn't support GPT. Use GNU Parted. =================== /etc/default/grub : # If you change this file, run 'update-grub' afterwards to update # /boot/grub/grub.cfg. # For full documentation of the options in this file, see: # info -f grub -n 'Simple configuration' GRUB_DEFAULT=0 #GRUB_HIDDEN_TIMEOUT=0 #GRUB_HIDDEN_TIMEOUT_QUIET=true GRUB_TIMEOUT=10 GRUB_DISTRIBUTOR=`lsb_release -i -s 2> /dev/null || echo Debian` GRUB_CMDLINE_LINUX_DEFAULT="quiet splash" GRUB_CMDLINE_LINUX="" # Uncomment to enable BadRAM filtering, modify to suit your needs # This works with Linux (no patch required) and with any kernel that obtains # the memory map information from GRUB (GNU Mach, kernel of FreeBSD ...) #GRUB_BADRAM="0x01234567,0xfefefefe,0x89abcdef,0xefefefef" # Uncomment to disable graphical terminal (grub-pc only) #GRUB_TERMINAL=console # The resolution used on graphical terminal # note that you can use only modes which your graphic card supports via VBE # you can see them in real GRUB with the command `vbeinfo' #GRUB_GFXMODE=640x480 # Uncomment if you don't want GRUB to pass "root=UUID=xxx" parameter to Linux #GRUB_DISABLE_LINUX_UUID=true # Uncomment to disable generation of recovery mode menu entries #GRUB_DISABLE_RECOVERY="true" # Uncomment to get a beep at grub start #GRUB_INIT_TUNE="480 440 1" EFI_OF_PART[1] (, ) =================== dmesg | grep EFI : [ 0.000000] EFI v2.00 by Lenovo [ 0.000000] Kernel-defined memdesc doesn't match the one from EFI! [ 0.000000] EFI: mem00: type=3, attr=0xf, range=[0x0000000000000000-0x0000000000001000) (0MB) [ 0.000000] EFI: mem01: type=7, attr=0xf, range=[0x0000000000001000-0x000000000004e000) (0MB) [ 0.000000] EFI: mem02: type=3, attr=0xf, range=[0x000000000004e000-0x0000000000058000) (0MB) [ 0.000000] EFI: mem03: type=10, attr=0xf, range=[0x0000000000058000-0x0000000000059000) (0MB) [ 0.000000] EFI: mem04: type=7, attr=0xf, range=[0x0000000000059000-0x000000000005e000) (0MB) [ 0.000000] EFI: mem05: type=4, attr=0xf, range=[0x000000000005e000-0x000000000005f000) (0MB) [ 0.000000] EFI: mem06: type=3, attr=0xf, range=[0x000000000005f000-0x00000000000a0000) (0MB) [ 0.000000] EFI: mem07: type=2, attr=0xf, range=[0x0000000000100000-0x00000000005b9000) (4MB) [ 0.000000] EFI: mem08: type=7, attr=0xf, range=[0x00000000005b9000-0x0000000020000000) (506MB) [ 0.000000] EFI: mem09: type=0, attr=0xf, range=[0x0000000020000000-0x0000000020200000) (2MB) [ 0.000000] EFI: mem10: type=7, attr=0xf, range=[0x0000000020200000-0x00000000364e4000) (354MB) [ 0.000000] EFI: mem11: type=2, attr=0xf, range=[0x00000000364e4000-0x000000003726a000) (13MB) [ 0.000000] EFI: mem12: type=7, attr=0xf, range=[0x000000003726a000-0x0000000040000000) (141MB) [ 0.000000] EFI: mem13: type=0, attr=0xf, range=[0x0000000040000000-0x0000000040200000) (2MB) [ 0.000000] EFI: mem14: type=7, attr=0xf, range=[0x0000000040200000-0x000000009df35000) (1501MB) [ 0.000000] EFI: mem15: type=2, attr=0xf, range=[0x000000009df35000-0x00000000d39a0000) (858MB) [ 0.000000] EFI: mem16: type=4, attr=0xf, range=[0x00000000d39a0000-0x00000000d39c0000) (0MB) [ 0.000000] EFI: mem17: type=7, attr=0xf, range=[0x00000000d39c0000-0x00000000d5df5000) (36MB) [ 0.000000] EFI: mem18: type=4, attr=0xf, range=[0x00000000d5df5000-0x00000000d6990000) (11MB) [ 0.000000] EFI: mem19: type=7, attr=0xf, range=[0x00000000d6990000-0x00000000d6b82000) (1MB) [ 0.000000] EFI: mem20: type=1, attr=0xf, range=[0x00000000d6b82000-0x00000000d6b9f000) (0MB) [ 0.000000] EFI: mem21: type=7, attr=0xf, range=[0x00000000d6b9f000-0x00000000d77b0000) (12MB) [ 0.000000] EFI: mem22: type=4, attr=0xf, range=[0x00000000d77b0000-0x00000000d780a000) (0MB) [ 0.000000] EFI: mem23: type=7, attr=0xf, range=[0x00000000d780a000-0x00000000d7826000) (0MB) [ 0.000000] EFI: mem24: type=4, attr=0xf, range=[0x00000000d7826000-0x00000000d7868000) (0MB) [ 0.000000] EFI: mem25: type=7, attr=0xf, range=[0x00000000d7868000-0x00000000d7869000) (0MB) [ 0.000000] EFI: mem26: type=4, attr=0xf, range=[0x00000000d7869000-0x00000000d786a000) (0MB) [ 0.000000] EFI: mem27: type=7, attr=0xf, range=[0x00000000d786a000-0x00000000d786b000) (0MB) [ 0.000000] EFI: mem28: type=4, attr=0xf, range=[0x00000000d786b000-0x00000000d786c000) (0MB) [ 0.000000] EFI: mem29: type=7, attr=0xf, range=[0x00000000d786c000-0x00000000d786d000) (0MB) [ 0.000000] EFI: mem30: type=4, attr=0xf, range=[0x00000000d786d000-0x00000000d825f000) (9MB) [ 0.000000] EFI: mem31: type=7, attr=0xf, range=[0x00000000d825f000-0x00000000d8261000) (0MB) [ 0.000000] EFI: mem32: type=4, attr=0xf, range=[0x00000000d8261000-0x00000000d82f7000) (0MB) [ 0.000000] EFI: mem33: type=7, attr=0xf, range=[0x00000000d82f7000-0x00000000d82f8000) (0MB) [ 0.000000] EFI: mem34: type=4, attr=0xf, range=[0x00000000d82f8000-0x00000000d8705000) (4MB) [ 0.000000] EFI: mem35: type=7, attr=0xf, range=[0x00000000d8705000-0x00000000d8706000) (0MB) [ 0.000000] EFI: mem36: type=4, attr=0xf, range=[0x00000000d8706000-0x00000000d8761000) (0MB) [ 0.000000] EFI: mem37: type=7, attr=0xf, range=[0x00000000d8761000-0x00000000d8768000) (0MB) [ 0.000000] EFI: mem38: type=4, attr=0xf, range=[0x00000000d8768000-0x00000000d9b9f000) (20MB) [ 0.000000] EFI: mem39: type=7, attr=0xf, range=[0x00000000d9b9f000-0x00000000d9e4c000) (2MB) [ 0.000000] EFI: mem40: type=2, attr=0xf, range=[0x00000000d9e4c000-0x00000000d9e52000) (0MB) [ 0.000000] EFI: mem41: type=3, attr=0xf, range=[0x00000000d9e52000-0x00000000da59f000) (7MB) [ 0.000000] EFI: mem42: type=5, attr=0x800000000000000f, range=[0x00000000da59f000-0x00000000da6c3000) (1MB) [ 0.000000] EFI: mem43: type=5, attr=0x800000000000000f, range=[0x00000000da6c3000-0x00000000da79f000) (0MB) [ 0.000000] EFI: mem44: type=6, attr=0x800000000000000f, range=[0x00000000da79f000-0x00000000da8b1000) (1MB) [ 0.000000] EFI: mem45: type=6, attr=0x800000000000000f, range=[0x00000000da8b1000-0x00000000da99f000) (0MB) [ 0.000000] EFI: mem46: type=0, attr=0xf, range=[0x00000000da99f000-0x00000000daa22000) (0MB) [ 0.000000] EFI: mem47: type=0, attr=0xf, range=[0x00000000daa22000-0x00000000daa9b000) (0MB) [ 0.000000] EFI: mem48: type=0, attr=0xf, range=[0x00000000daa9b000-0x00000000daa9c000) (0MB) [ 0.000000] EFI: mem49: type=0, attr=0xf, range=[0x00000000daa9c000-0x00000000daa9f000) (0MB) [ 0.000000] EFI: mem50: type=10, attr=0xf, range=[0x00000000daa9f000-0x00000000daadd000) (0MB) [ 0.000000] EFI: mem51: type=10, attr=0xf, range=[0x00000000daadd000-0x00000000dab9f000) (0MB) [ 0.000000] EFI: mem52: type=9, attr=0xf, range=[0x00000000dab9f000-0x00000000dabdc000) (0MB) [ 0.000000] EFI: mem53: type=9, attr=0xf, range=[0x00000000dabdc000-0x00000000dabff000) (0MB) [ 0.000000] EFI: mem54: type=4, attr=0xf, range=[0x00000000dabff000-0x00000000dac00000) (0MB) [ 0.000000] EFI: mem55: type=7, attr=0xf, range=[0x0000000100000000-0x000000021e600000) (4582MB) [ 0.000000] EFI: mem56: type=11, attr=0x8000000000000001, range=[0x00000000f80f8000-0x00000000f80f9000) (0MB) [ 0.000000] EFI: mem57: type=11, attr=0x8000000000000001, range=[0x00000000fed1c000-0x00000000fed20000) (0MB) [ 0.000000] ACPI: UEFI 00000000dabde000 0003E (v01 LENOVO TP-8D 00001280 PTL 00000002) [ 0.000000] ACPI: UEFI 00000000dabdd000 00042 (v01 PTL COMBUF 00000001 PTL 00000001) [ 0.000000] ACPI: UEFI 00000000dabdc000 00292 (v01 LENOVO TP-8D 00001280 PTL 00000002) [ 0.795807] fb0: EFI VGA frame buffer device [ 1.057243] EFI Variables Facility v0.08 2004-May-17 [ 9.122104] fb: conflicting fb hw usage inteldrmfb vs EFI VGA - removing generic driver ReadEFI: /dev/sda , N 128 , 0 , , PRStart 1024 , PRSize 128 WARNING: GPT (GUID Partition Table) detected on '/dev/sda'! The util fdisk doesn't support GPT. Use GNU Parted. =================== PARTITIONS & DISKS: sda4 : sda, not-sepboot, grubenv-ok grub2, grub-efi, update-grub, 64, with-boot, is-os, gpt-but-not-EFI, fstab-has-bad-efi, no-nt, no-winload, no-recov-nor-hid, no-bmgr, no-grldr, no-b-bcd, apt-get, grub-install, . sda3 : sda, maybesepboot, no-grubenv nogrub, no-docgrub, no-update-grub, 32, no-boot, no-os, gpt-but-not-EFI, part-has-no-fstab, no-nt, haswinload, no-recov-nor-hid, no-bmgr, no-grldr, no-b-bcd, nopakmgr, nogrubinstall, /mnt/boot-sav/sda3. sda1 : sda, maybesepboot, no-grubenv nogrub, no-docgrub, no-update-grub, 32, no-boot, no-os, is-correct-EFI, part-has-no-fstab, no-nt, no-winload, no-recov-nor-hid, no-bmgr, no-grldr, no-b-bcd, nopakmgr, nogrubinstall, /boot/efi. sda5 : sda, maybesepboot, no-grubenv nogrub, no-docgrub, no-update-grub, 32, no-boot, no-os, gpt-but-not-EFI, part-has-no-fstab, no-nt, no-winload, no-recov-nor-hid, no-bmgr, no-grldr, no-b-bcd, nopakmgr, nogrubinstall, /home. sda : GPT-BIS, GPT, no-BIOS_boot, has-correctEFI, 2048 sectors * 512 bytes =================== PARTED: Model: ATA HITACHI HTS72323 (scsi) Disk /dev/sda: 320GB Sector size (logical/physical): 512B/512B Partition Table: gpt Number Start End Size File system Name Flags 1 1049kB 106MB 105MB fat32 EFI system partition boot 2 106MB 240MB 134MB Microsoft reserved partition msftres 3 240MB 87.2GB 87.0GB ntfs Basic data partition 4 87.2GB 169GB 81.9GB ext4 5 169GB 316GB 147GB ext4 6 316GB 320GB 4096MB linux-swap(v1) =================== MOUNT: /dev/sda4 on / type ext4 (rw,errors=remount-ro) proc on /proc type proc (rw,noexec,nosuid,nodev) sysfs on /sys type sysfs (rw,noexec,nosuid,nodev) none on /sys/fs/fuse/connections type fusectl (rw) none on /sys/kernel/debug type debugfs (rw) none on /sys/kernel/security type securityfs (rw) udev on /dev type devtmpfs (rw,mode=0755) devpts on /dev/pts type devpts (rw,noexec,nosuid,gid=5,mode=0620) tmpfs on /run type tmpfs (rw,noexec,nosuid,size=10%,mode=0755) none on /run/lock type tmpfs (rw,noexec,nosuid,nodev,size=5242880) none on /run/shm type tmpfs (rw,nosuid,nodev) /dev/sda1 on /boot/efi type vfat (rw) /dev/sda5 on /home type ext4 (rw) gvfs-fuse-daemon on /home/vierlex/.gvfs type fuse.gvfs-fuse-daemon (rw,nosuid,nodev,user=vierlex) /dev/sda3 on /mnt/boot-sav/sda3 type fuseblk (rw,nosuid,nodev,allow_other,blksize=4096) /sys/block/sda: alignment_offset bdi capability dev device discard_alignment events events_async events_poll_msecs ext_range holders inflight power queue range removable ro sda1 sda2 sda3 sda4 sda5 sda6 size slaves stat subsystem trace uevent /dev: agpgart autofs block bsg btrfs-control bus char console core cpu cpu_dma_latency disk dri ecryptfs fb0 fd full fuse hpet input kmsg log mapper mcelog mei mem net network_latency network_throughput null oldmem port ppp psaux ptmx pts random rfkill rtc rtc0 sda sda1 sda2 sda3 sda4 sda5 sda6 sg0 shm snapshot snd stderr stdin stdout tpm0 uinput urandom usbmon0 usbmon1 usbmon2 v4l vga_arbiter video0 watchdog zero /dev/mapper: control /boot/efi: EFI /boot/efi/EFI: Boot Microsoft ubuntu /boot/efi/efi: Boot Microsoft ubuntu /boot/efi/efi/Boot: bootx64.efi /boot/efi/efi/ubuntu: grubx64.efi WARNING: GPT (GUID Partition Table) detected on '/dev/sda'! The util fdisk doesn't support GPT. Use GNU Parted. =================== DF: Filesystem Type Size Used Avail Use% Mounted on /dev/sda4 ext4 77G 4.1G 69G 6% / udev devtmpfs 3.9G 12K 3.9G 1% /dev tmpfs tmpfs 1.6G 864K 1.6G 1% /run none tmpfs 5.0M 0 5.0M 0% /run/lock none tmpfs 3.9G 152K 3.9G 1% /run/shm /dev/sda1 vfat 96M 18M 79M 19% /boot/efi /dev/sda5 ext4 137G 2.2G 128G 2% /home /dev/sda3 fuseblk 81G 30G 52G 37% /mnt/boot-sav/sda3 =================== FDISK: Disk /dev/sda: 320.1 GB, 320072933376 bytes 255 heads, 63 sectors/track, 38913 cylinders, total 625142448 sectors Units = sectors of 1 * 512 = 512 bytes Sector size (logical/physical): 512 bytes / 512 bytes I/O size (minimum/optimal): 512 bytes / 512 bytes Disk identifier: 0xf34fe538 Device Boot Start End Blocks Id System /dev/sda1 1 625142447 312571223+ ee GPT =================== Before mainwindow FSCK no PASTEBIN yes WUBI no WINBOOT yes recommendedrepair, purge, QTY_OF_PART_FOR_REINSTAL 1 no-kernel-purge UNHIDEBOOT_ACTION yes (10s), noflag () PART_TO_REINSTALL_GRUB sda4, FORCE_GRUB no (sda) REMOVABLEDISK no USE_SEPARATEBOOTPART no (sda3) grub2 () UNCOMMENT_GFXMODE no ATA ADD_KERNEL_OPTION no (acpi=off) MBR_TO_RESTORE ( ) EFI detected. Please check the options. =================== Actions FSCK no PASTEBIN yes WUBI no WINBOOT no bootinfo, nombraction, QTY_OF_PART_FOR_REINSTAL 1 no-kernel-purge UNHIDEBOOT_ACTION no (10s), noflag () PART_TO_REINSTALL_GRUB sda4, FORCE_GRUB no (sda) REMOVABLEDISK no USE_SEPARATEBOOTPART no (sda3) grub2 () UNCOMMENT_GFXMODE no ATA ADD_KERNEL_OPTION no (acpi=off) MBR_TO_RESTORE ( ) No change has been performed on your computer. See you soon! internet: connected Thanks for your time and attention. EDIT: additional Info Request =No boot loader is installed in the MBR of /dev/sda. But maybe this is how it is supposed to work? yea this is ok. boot stuff seems to be on a seperate partition, in my case sda1. I'm very new to this UEFI thing too. missing files like bootmgr i don't really have a clue :D but yea, maybe thats how it suppose to be? Instead and whats not shown in the log for some reason: There is additional microsoft bootfiles on sda1 under /efi/microsoft/ [much stuff] I remember also doing some kind of hack to make a UEFI windows 7 usb stick. http://jake.io/b/2011/installing-windows-7-with-uefi-boot-on-an-x220-from-usb/ In short: creating and placing bootx64.efi on the stick so it can be booted in UEFI mode. boot order i decide that in my BIOS. i read somwhere that the thinkpad x220 (essential part of the serial number: 4921 http://www.lenovo.com/shop/americas/content/user_guides/x220_x220i_x220tablet_x220itablet_ug_en.pdf) doesnt really have UEFI interface or something, still, these 2 options are listed with all the other usual devices you can give a boot priority to. Right now it looks like this: Boot Priority Order 1. ubuntu 2. Windows Boot Manager 3. USB FDD 4. USB HDD 5. ATA HDD0 HITACHI [random string]

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• New Feature in ODI 11.1.1.6: ODI for Big Data

  - by Julien Testut

  Normal 0 false false false EN-US X-NONE X-NONE /* 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:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} By Ananth Tirupattur Starting with Oracle Data Integrator 11.1.1.6.0, ODI is offering a solution to process Big Data. This post provides an overview of this feature. With all the buzz around Big Data and before getting into the details of ODI for Big Data, I will provide a brief introduction to Big Data and Oracle Solution for Big Data. So, what is Big Data? Big data includes: structured data (this includes data from relation data stores, xml data stores), semi-structured data (this includes data from weblogs) unstructured data (this includes data from text blob, images) Traditionally, business decisions are based on the information gathered from transactional data. For example, transactional Data from CRM applications is fed to a decision system for analysis and decision making. Products such as ODI play a key role in enabling decision systems. However, with the emergence of massive amounts of semi-structured and unstructured data it is important for decision system to include them in the analysis to achieve better decision making capability. While there is an abundance of opportunities for business for gaining competitive advantages, process of Big Data has challenges. The challenges of processing Big Data include: Volume of data Velocity of data - The high Rate at which data is generated Variety of data In order to address these challenges and convert them into opportunities, we would need an appropriate framework, platform and the right set of tools. Hadoop is an open source framework which is highly scalable, fault tolerant system, for storage and processing large amounts of data. Hadoop provides 2 key services, distributed and reliable storage called Hadoop Distributed File System or HDFS and a framework for parallel data processing called Map-Reduce. Innovations in Hadoop and its related technology continue to rapidly evolve, hence therefore, it is highly recommended to follow information on the web to keep up with latest information. Oracle's vision is to provide a comprehensive solution to address the challenges faced by Big Data. Oracle is providing the necessary Hardware, software and tools for processing Big Data Oracle solution includes: Big Data Appliance Oracle NoSQL Database Cloudera distribution for Hadoop Oracle R Enterprise- R is a statistical package which is very popular among data scientists. ODI solution for Big Data Oracle Loader for Hadoop for loading data from Hadoop to Oracle. Further details can be found here: http://www.oracle.com/us/products/database/big-data-appliance/overview/index.html ODI Solution for Big Data: ODI’s goal is to minimize the need to understand the complexity of Hadoop framework and simplify the adoption of processing Big Data seamlessly in an enterprise. ODI is providing the capabilities for an integrated architecture for processing Big Data. This includes capability to load data in to Hadoop, process data in Hadoop and load data from Hadoop into Oracle. ODI is expanding its support for Big Data by providing the following out of the box Knowledge Modules (KMs). IKM File to Hive (LOAD DATA).Load unstructured data from File (Local file system or HDFS ) into Hive IKM Hive Control AppendTransform and validate structured data on Hive IKM Hive TransformTransform unstructured data on Hive IKM File/Hive to Oracle (OLH)Load processed data in Hive to Oracle RKM HiveReverse engineer Hive tables to generate models Using the Loading KM you can map files (local and HDFS files) to the corresponding Hive tables. For example, you can map weblog files categorized by date into a corresponding partitioned Hive table schema. Normal 0 false false false EN-US X-NONE X-NONE /* 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:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Hive control Append KM you can validate and transform data in Hive. In the below example, two source Hive tables are joined and mapped to a target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* 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:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} The Hive Transform KM facilitates processing of semi-structured data in Hive. In the below example, the data from weblog is processed using a Perl script and mapped to target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* 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:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Oracle Loader for Hadoop (OLH) KM you can load data from Hive table or HDFS to a corresponding table in Oracle. OLH is available as a standalone product. ODI greatly enhances OLH capability by generating the configuration and mapping files for OLH based on the configuration provided in the interface and KM options. ODI seamlessly invokes OLH when executing the scenario. In the below example, a HDFS file is mapped to a table in Oracle. Development and Deployment:The following diagram illustrates the development and deployment of ODI solution for Big Data. Using the ODI Studio on your development machine create and develop ODI solution for processing Big Data by connecting to a MySQL DB or Oracle database on a BDA machine or Hadoop cluster. Schedule the ODI scenarios to be executed on the ODI agent deployed on the BDA machine or Hadoop cluster. ODI Solution for Big Data provides several exciting new capabilities to facilitate the adoption of Big Data in an enterprise. You can find more information about the Oracle Big Data connectors on OTN. You can find an overview of all the new features introduced in ODI 11.1.1.6 in the following document: ODI 11.1.1.6 New Features Overview

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• Scala: Correcting type inference of representation type over if statement

  - by drhagen

  This is a follow-up to two questions on representation types, which are type parameters of a trait designed to represent the type underlying a bounded type member (or something like that). I've had success creating instances of classes, e.g ConcreteGarage, that have instances cars of bounded type members CarType. trait Garage { type CarType <: Car[CarType] def cars: Seq[CarType] def copy(cars: Seq[CarType]): Garage def refuel(car: CarType, fuel: CarType#FuelType): Garage = copy( cars.map { case `car` => car.refuel(fuel) case other => other }) } class ConcreteGarage[C <: Car[C]](val cars: Seq[C]) extends Garage { type CarType = C def copy(cars: Seq[C]) = new ConcreteGarage(cars) } trait Car[C <: Car[C]] { type FuelType <: Fuel def fuel: FuelType def copy(fuel: C#FuelType): C def refuel(fuel: C#FuelType): C = copy(fuel) } class Ferrari(val fuel: Benzin) extends Car[Ferrari] { type FuelType = Benzin def copy(fuel: Benzin) = new Ferrari(fuel) } class Mustang(val fuel: Benzin) extends Car[Mustang] { type FuelType = Benzin def copy(fuel: Benzin) = new Mustang(fuel) } trait Fuel case class Benzin() extends Fuel I can easily create instances of Cars like Ferraris and Mustangs and put them into a ConcreteGarage, as long as it's simple: val newFerrari = new Ferrari(Benzin()) val newMustang = new Mustang(Benzin()) val ferrariGarage = new ConcreteGarage(Seq(newFerrari)) val mustangGarage = new ConcreteGarage(Seq(newMustang)) However, if I merely return one or the other, based on a flag, and try to put the result into a garage, it fails: val likesFord = true val new_car = if (likesFord) newFerrari else newMustang val switchedGarage = new ConcreteGarage(Seq(new_car)) // Fails here The switch alone works fine, it is the call to ConcreteGarage constructor that fails with the rather mystical error: error: inferred type arguments [this.Car[_ >: this.Ferrari with this.Mustang <: this.Car[_ >: this.Ferrari with this.Mustang <: ScalaObject]{def fuel: this.Benzin; type FuelType<: this.Benzin}]{def fuel: this.Benzin; type FuelType<: this.Benzin}] do not conform to class ConcreteGarage's type parameter bounds [C <: this.Car[C]] val switchedGarage = new ConcreteGarage(Seq(new_car)) // Fails here ^ I have tried putting those magic [C <: Car[C]] representation type parameters everywhere, but without success in finding the magic spot.

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• Data recovery on a data HDD (no OS)

  - by aCuria

  I am helping a family member with a dead hard disk. It is a seagate 200Gb 3.5" HDD in one of those old-school external enclosures. The problem was that windows failed to detect the hard disk when plugged in through USB. I removed the hard disk from its enclosure, and plugged it into my desktop PC. The BIOS does detect it upon POST, but unfortunately windows 7 would refuse to boot. It will get stuck on the loading screen with the glowing windows logo. Safe mode doesn't help either. What options do I have before going for some professional data recovery? edit: Someone modified the Title to something completely different from what I was asking, i just changed it back. 1) 2 HDD drives, DiskA(Dead), DiskB(my OS disk) 2) when B is connected to my system, everything works fine 3) when A AND B is connected, failure to boot. POSTs fine, but windows wont load 4) A has NO OS, its PURE data. It came from an EXTERNAL HDD enclosure which doesnt belong to me, and im trying to do data recovery.

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• Where is the Java Language Conversion Assistant (JLCA) 3.0?

  - by David Pfeffer

  Microsoft supposedly offer(ed?) something called the JLCA, which converts Java into C#. I can't find any download or anything for it. Does anyone have any information about this tool and how to use it in VS2008/2010? I can find version 2.0 but not 3.0... supposedly it came built into VS2005?

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• Data Governance 2010 Conference in San Diego

  - by Tony Ouk

  The Data Governance Annual Conference is one of the world's most authoritative and vendor neutral event on Data Governance and Data Quality.  The conference will focus on the "how-tos" from starting a data governance and stewardship program to attaining data governance maturity with specific topics on MDM.  This year's event will be hosted June 7 through June 10 in San Diego, California. For more information, including registration details, visit the Data Governance 2010 Conference website.

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• How to search for newline or linebreak characters in Excel?

  - by Highly Irregular

  I've imported some data into Excel (from a text file) and it contains some sort of newline characters. It looks like this initially: If I hit F2 (to edit) then Enter (to save changes) on each of the cells with a newline (without actually editing anything), Excel automatically changes the layout to look like this: I don't want these newlines characters here, as it messes up data processing further down the track. How can I do a search for these to detect more of them? The usual search function doesn't accept an enter character as a search character.

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• Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

  - by Thanos Terentes Printzios

  In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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• Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

  - by Compudicted

  Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Weindows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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• Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

  - by Compudicted

  Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review-again.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Windows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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• Internal Mutation of Persistent Data Structures

  - by Greg Ros

  To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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• Sabre Manages Fast Data Growth with Oracle Data Integration Products

  - by Irem Radzik

  Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* 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-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; 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-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Last year at OpenWorld we announced Sabre Holding as a winner of the Fusion Middleware Innovation Awards. The Sabre team did an excellent job at leveraging cutting edge technologies for managing rapid data growth and exponential scalability demands they have experienced in the travel industry. Today we announced the details and specific benefits of Sabre’s new real-time data integration solution in a press release. Please take a look if you haven’t seen it yet. Sabre Holdings Deploys Oracle Data Integrator and Oracle GoldenGate to Support Rapid Customer Growth There are 3 different areas of benefits Sabre achieved by using Oracle Data Integration products: Manages 7X increase in data sources for the enterprise data warehouse Reduced infrastructure complexity Decreased time to market for new products and services by 30 percent. This simply shows that using latest technologies helps the companies to innovate robust solutions against today’s key data management challenges. And the benefit of using a next generation data integration technology is not only seen in the IT operations, but also in the business side. A better data integration solution for the enterprise data warehouse delivered the platform they need to accelerate how they service their customers, improving their competitive advantage. Tomorrow I will give another great example of innovation with next generation data integration from Oracle. We will be discussing the Fusion Middleware Innovation Awards 2012 winners and their results with using Oracle’s data integration products.

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• Type Conversion in JPA 2.1

  - by delabassee

  The Java Persistence 2.1 specification (JSR 338) adds support for various new features such as schema generation, stored procedure invocation, use of entity graphs in queries and find operations, unsynchronized persistence contexts, injection into entity listener classes, etc. JPA 2.1 also add support for Type Conversion methods, sometime called Type Converter. This new facility let developers specify methods to convert between the entity attribute representation and the database representation for attributes of basic types. For additional details on Type Conversion, you can check the JSR 338 Specification and its corresponding JPA 2.1 Javadocs. In addition, you can also check those 2 articles. The first article ('How to implement a Type Converter') gives a short overview on Type Conversion while the second article ('How to use a JPA Type Converter to encrypt your data') implements a simple use-case (encrypting data) to illustrate Type Conversion. Mission critical applications would probably rely on transparent database encryption facilities provided by the database but that's not the point here, this use-case is easy enough to illustrate JPA 2.1 Type Conversion.

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• implementing dynamic query handler on historical data

  - by user2390183

  EDIT : Refined question to focus on the core issue Context: I have historical data about property (house) sales collected from various sources in a centralized/cloud data source (assume info collection is handled by a third party) Planning to develop an application to query and retrieve data from this centralized data source Example Queries: Simple : for given XYZ post code, what is average house price for 3 bed room house? Complex: What is estimated price for an house at "DD,Some Street,XYZ Post Code" (worked out from average values of historic data filtered by various characteristics of the house: house post code, no of bed rooms, total area, and other deeper insights like house building type, year of built, features)? In addition to average price, the application should support other property info ** maximum, or minimum price..etc and trend (graph) on a selected property attribute over a period of time**. Hence, the queries should not enforce the search based on a primary key or few fixed fields In other words, queries can be What is the change in 3 Bed Room house price (irrespective of location) over last 30 days? What kind of properties we can get for X price (irrespective of location or house type) The challenge I have is identifying the domain (BI/ Data Analytical or DB Design or DB Query Interface or DW related or something else) this problem (dynamic query on historic data) belong to, so that I can do further exploration My findings so far I could be wrong on the following, so please correct me if you think so I briefly read about BI/Data Analytics - I think it is heavy weight solution for my problem and has scalability issues. DB Design - As I understand RDBMS works well if you know Data model at design time. I am expecting attributes about property or other entity (user) that am going to bring in, would evolve quickly. hence maintenance would be an issue. As I am going to have multiple users executing query at same time, performance would be a bottleneck Other options like Graph DB (http://www.tinkerpop.com/) seems to be bit complex (they are good. but using those tools meant for generic purpose, make me think like assembly programming to solve my problem ) BigData related solution are to analyse data from multiple unrelated domains So, Any suggestion on the space this problem fit in ? (Especially if you have design/implementation experience of back-end for property listing or similar portals)

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• Am I sending large amounts of data sensibly?

  - by Sofus Albertsen

  I am about to design a video conversion service, that is scalable on the conversion side. The architecture is as follows: Webpage for video upload When done, a message gets sent out to one of several resizing servers The server locates the video, saves it on disk, and converts it to several formats and resolutions The resizing server uploads the output to a content server, and messages back that the conversion is done. Messaging is something I have covered, but right now I am transferring via FTP, and wonder if there is a better way? is there something faster, or more reliable? All the servers will be sitting in the same gigabit switch or neighboring switch, so fast transfer is expected.

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• AngularJS dealing with large data sets (Strategy)

  - by Brian

  I am working on developing a personal temperature logging viewer based on my rasppi curl'ing data into my web server's api. Temperatures are taken every 2 seconds and I can have several temperature sensors posting data. Needless to say I will have a lot of data to handle even within the scope of an hour. I have implemented a very simple paging api from the server so the server doesn't timeout and is currently only returning data in 1000 units per call, then paging through the data. I had the idea to intially show say the last 20 minutes of data from a sensor (or all sensors depending on user choices), then allowing the user to select other timeframes from which to show data. The issue comes in when you want to view all sensors or an extended time period (say 24 hours). Is there a best practice of handling this large amount of data? Would it be useful to load those first 20 minutes into the live view and then cache into local storage something like the last 24 hours? I haven't been able to find a decent idea of this in use yet even though there are a lot of ways to take this problem. I am just looking for some suggestions as to what might provide a good balance between good performance and not caching the entire data set on the client side (as beyond a week of data this might not be feasible).

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• I need some help creating a non-binary tree (or some other data structure that will better solve my problem)

  - by EDO

  I have about ten lists of numbers and some strings. Each list has about <= 30K lines. Each line on a list has a distinct number. I need to build an efficient way of finding all the lines in each list that has the same 'control' number (or key for dB guys) and comparing what is in their string parts. I am writing this in Java. I have thought about using trees but my brain cells are about burnt now. I need some help.

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• replacing data.frame element-wise operations with data.table (that used rowname)

  - by Harold

  So lets say I have the following data.frames: df1 <- data.frame(y = 1:10, z = rnorm(10), row.names = letters[1:10]) df2 <- data.frame(y = c(rep(2, 5), rep(5, 5)), z = rnorm(10), row.names = letters[1:10]) And perhaps the "equivalent" data.tables: dt1 <- data.table(x = rownames(df1), df1, key = 'x') dt2 <- data.table(x = rownames(df2), df2, key = 'x') If I want to do element-wise operations between df1 and df2, they look something like dfRes <- df1 / df2 And rownames() is preserved: R> head(dfRes) y z a 0.5 3.1405463 b 1.0 1.2925200 c 1.5 1.4137930 d 2.0 -0.5532855 e 2.5 -0.0998303 f 1.2 -1.6236294 My poor understanding of data.table says the same operation should look like this: dtRes <- dt1[, !'x', with = F] / dt2[, !'x', with = F] dtRes[, x := dt1[,x,]] setkey(dtRes, x) (setkey optional) Is there a more data.table-esque way of doing this? As a slightly related aside, more generally, I would have other columns such as factors in each data.table and I would like to omit those columns while doing the element-wise operations, but still have them in the result. Does this make sense? Thanks!

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• PHP - post data ends when '&' is in data.

  - by Phil Jackson

  Hi all, im posting data using jquery/ajax and PHP at the backend. Problem being, when I input something like 'Jack & Jill went up the hill' im only recieving 'Jack' when it gets to the backend. I have thrown an error at the frontend before that data is sent which alerts 'Jack & Jill went up the hill'. When I put die(print_r($_POST)); at the very top of my index page im only getting [key] => Jack how can I be loosing the data? I thought It may have been my filter; <?php function filter( $data ) { $data = trim( htmlentities( strip_tags( mb_convert_encoding( $data, 'HTML-ENTITIES', "UTF-8") ) ) ); if ( get_magic_quotes_gpc() ) { $data = stripslashes( $data ); } //$data = mysql_real_escape_string( $data ); return $data; } echo "<xmp>" . filter("you & me") . "</xmp>"; ?> but that returns fine in the test above you &amp; me which is in place after I added die(print_r($_POST));. Can anyone think of how and why this is happening? Any help much appreciated. Regards, Phil.

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• General type conversion without risking Exceptions

  - by Mongus Pong

  I am working on a control that can take a number of different datatypes (anything that implements IComparable). I need to be able to compare these with another variable passed in. If the main datatype is a DateTime, and I am passed a String, I need to attempt to convert the String to a DateTime to perform a Date comparison. if the String cannot be converted to a DateTime then do a String comparison. So I need a general way to attempt to convert from any type to any type. Easy enough, .Net provides us with the TypeConverter class. Now, the best I can work out to do to determine if the String can be converted to a DateTime is to use exceptions. If the ConvertFrom raises an exception, I know I cant do the conversion and have to do the string comparison. The following is the best I got : string theString = "99/12/2009"; DateTime theDate = new DateTime ( 2009, 11, 1 ); IComparable obj1 = theString as IComparable; IComparable obj2 = theDate as IComparable; try { TypeConverter converter = TypeDescriptor.GetConverter ( obj2.GetType () ); if ( converter.CanConvertFrom ( obj1.GetType () ) ) { Console.WriteLine ( obj2.CompareTo ( converter.ConvertFrom ( obj1 ) ) ); Console.WriteLine ( "Date comparison" ); } } catch ( FormatException ) { Console.WriteLine ( obj1.ToString ().CompareTo ( obj2.ToString () ) ); Console.WriteLine ( "String comparison" ); } Part of our standards at work state that : Exceptions should only be raised when an Exception situation - ie. an error is encountered. But this is not an exceptional situation. I need another way around it. Most variable types have a TryParse method which returns a boolean to allow you to determine if the conversion has succeeded or not. But there is no TryConvert method available to TypeConverter. CanConvertFrom only dermines if it is possible to convert between these types and doesnt consider the actual data to be converted. The IsValid method is also useless. Any ideas? EDIT I cannot use AS and IS. I do not know either data types at compile time. So I dont know what to As and Is to!!! EDIT Ok nailed the bastard. Its not as tidy as Marc Gravells, but it works (I hope). Thanks for the inpiration Marc. Will work on tidying it up when I get the time, but I've got a bit stack of bugfixes that I have to get on with. public static class CleanConverter { /// <summary> /// Stores the cache of all types that can be converted to all types. /// </summary> private static Dictionary<Type, Dictionary<Type, ConversionCache>> _Types = new Dictionary<Type, Dictionary<Type, ConversionCache>> (); /// <summary> /// Try parsing. /// </summary> /// <param name="s"></param> /// <param name="value"></param> /// <returns></returns> public static bool TryParse ( IComparable s, ref IComparable value ) { // First get the cached conversion method. Dictionary<Type, ConversionCache> type1Cache = null; ConversionCache type2Cache = null; if ( !_Types.ContainsKey ( s.GetType () ) ) { type1Cache = new Dictionary<Type, ConversionCache> (); _Types.Add ( s.GetType (), type1Cache ); } else { type1Cache = _Types[s.GetType ()]; } if ( !type1Cache.ContainsKey ( value.GetType () ) ) { // We havent converted this type before, so create a new conversion type2Cache = new ConversionCache ( s.GetType (), value.GetType () ); // Add to the cache type1Cache.Add ( value.GetType (), type2Cache ); } else { type2Cache = type1Cache[value.GetType ()]; } // Attempt the parse return type2Cache.TryParse ( s, ref value ); } /// <summary> /// Stores the method to convert from Type1 to Type2 /// </summary> internal class ConversionCache { internal bool TryParse ( IComparable s, ref IComparable value ) { if ( this._Method != null ) { // Invoke the cached TryParse method. object[] parameters = new object[] { s, value }; bool result = (bool)this._Method.Invoke ( null, parameters); if ( result ) value = parameters[1] as IComparable; return result; } else return false; } private MethodInfo _Method; internal ConversionCache ( Type type1, Type type2 ) { // Use reflection to get the TryParse method from it. this._Method = type2.GetMethod ( "TryParse", new Type[] { type1, type2.MakeByRefType () } ); } } }

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• SQL Developer Debugging, Watches, Smart Data, & Data

  - by thatjeffsmith

  After presenting the SQL Developer PL/SQL debugger for about an hour yesterday at KScope12 in San Antonio, my boss came up and asked, “Now, would you really want to know what the Smart Data panel does?” Apparently I had ‘made up’ my own story about what that panel’s intent is based on my experience with it. Not good Jeff, not good. It was a very small point of my presentation, but I probably should have read the docs. The Smart Data tab displays information about variables, using your Debugger: Smart Data preferences. You can also specify these preferences by right-clicking in the Smart Data window and selecting Preferences. Debugger Smart Data Preferences, control number of variables to display The Smart Data panel auto-inspects the last X accessed variables. So if you have a program with 26 variables, instead of showing you all 26, it will just show you the last two variables that were referenced in your program. If you were to click on the ‘Data’ debug panel, you’ll see EVERYTHING. And if you only want to see a very specific set of values, then you should use Watches. The Smart Data Panel As I step through the code, the variables being tracked change as they are referenced. Only the most recent ones display. This is controlled by the ‘Maximum Locations to Remember’ preference. Step through the code, see the latest variables accessed The Data Panel All variables are displayed. Might be information overload on large PL/SQL programs where you have many dozens or even hundreds of variables to track. Shows everything all the time Watches Watches are added manually and only show what you ask for. Data on Demand – add a watch to track a specific variable Remember, you can interact with your data If you want to do more than just watch, you can mouse-right on a data element, and change the value of the variable as the program is running. This is one of the primary benefits to debugging over using DBMS_OUTPUT to track what’s happening in your program. Change the values while the program is running to test your ‘What if?’ scenarios

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• SQL – Biggest Concerns in a Data-Driven World

  - by Pinal Dave

  The ongoing chaos over Government Agency’s snooping has ignited a heated debate on privacy of personal data and its use by government and/or other institutions. It has created a feeling of disapproval and distrust among users. This incident proves to be a lesson for companies that are looking to leverage their business using a data driven approach. According to analysts, the goal of gathering personal information should be to deliver benefits to both the parties – the user as well as the data collector(government or business). Using data the right way is crucial, and companies need to deploy the right software applications and systems to ensure that their efforts are well-directed. However, there are various issues plaguing analysts regarding available software, which are highlighted below. According to a InformationWeek 2013 Survey of Analytics, Business Intelligence and Information Management where 541 business technology professionals contributed as respondents, it was discovered that the biggest concern was deemed to be the scarcity of expertise and high costs associated with the same. This concern was voiced by as many as 38% of the participants. A close second came out to be the issue of data warehouse appliance platforms being expensive, with 33% of those present believing it to be a huge roadblock. Another revelation made in this respect was that 31% professionals weren’t even sure how Data Analytics can create business opportunities for them. Another 17% shared that they found data platform technologies such as Hadoop and NoSQL technologies hard to learn. These results clearly pointed out that there are awareness and expertise issues that also need much attention. Unless the demand-supply gap of Business Intelligence professionals well versed in data analysis technologies is met, this divide is going to affect how companies make the most of their BI campaigns. One of the key action points that can be taken to salvage the situation, is to provide training on Data Analytics concepts. Koenig Solutions offer courses on many such technologies including a course on MCSE SQL Server 2012: BI Platform. So it’s time to brush up your skills and get down to work in a data driven world that awaits you ahead. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Conversion of bytes into a type without changing the application (ie storing the conversion method i

  - by geoaxis

  Is there a way to store a conversion strategy (for converting some bytes) into a database and then execute it on the run time. If one were to store a complete java file, you would need to compile it, store the class and some how inject into the already running system. I am not sure how this would be possible. But using some kind of dynamic language on JVM would be nice. I see an example of execution of groovy from within spring context here http://www.devx.com/tips/Tip/42789 but this is still static in nature as application context contains the reference to the implementation and cannot be changed by database. Perhaps with JavaConfig of context it is possible. I am exploring options now, specifically with Spring 3.0. Your suggestions in any direction would be welcome.

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• Store XML data in Core Data

  - by ct2k7

  Hi, is there any easy way of store XML data into core data? Currently, my app just pulls the values from the XML file directly, however, this isn't efficient for XML files which holds over 100 entries, thus storing the data in Core Data would be the best option. XML file is called/downloaded/parsed ever time the app opens. With the Core Data, the XML data would be downloaded ever 3600 seconds or so, and refresh the current data in the core data, to reduce the loading time when opening the app. Any ideas on how I can do this? Having reviewed the developer documentation, it doesn't look very tasty.

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• How to check if a generic type definition inherits from another generic type definition

  - by Anne

  I'm trying to check whether an open generic type definition implements some open generic interface. Look at the sample below: public interface IService<T> { } public class ServiceImpl<T> : IService<T> { } private static bool OpenGenericTypeImplementsOpenGenericInterface( Type derivedType, Type interfaceType) { return derivedType.GetInterfaces().Contains(interfaceType); } [TestMethod] public void Verify() { Type openGenericImplementation = typeof(ServiceImpl<>); Type expectedInterfaceType = typeof(IService<>); bool implDoesImplementInterface = OpenGenericTypeImplementsOpenGenericInterface( openGenericImplementation, expectedInterfaceType); // This assert fails. Why? Assert.IsTrue(implDoesImplementInterface); } I found out that the returned type from the Type.GetInterfaces() method does not match the type returned from typeof(IService<>). I can't figure out why that is and how to correctly validate whether some generic type definition inherits or implements some other generic type definition. What's going on here and how do I solve fix this problem?

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