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  • How to read oom-killer syslog messages?

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

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  • Pimp my Silverlight Firestarter

    - by mbcrump
    So Silverlight Firestarter is over and your sitting on your couch thinking… what now? Well its time to So how exactly can you pimp the Silverlight Firestarter? Well read below and you will find out: 1) Pimp the videos: First we are going to use a program named Juice to download all of the Silverlight Firestarter videos. Go ahead and point your browser to http://juicereceiver.sourceforge.net/ and download the application. It works on Mac, Linux and PC. After it is downloaded you are going to want to add an RSS feed by clicking the button highlighted below. At this point you are going to want to add the following URL inside the textbox and hit Save: http://channel9.msdn.com/Series/Silverlight-Firestarter/RSS This RSS feed includes all the Silverlight Firestarter Labs and Presentations located below. The Future of Silverlight Data Binding Strategies with Silverlight and WP7 Building Compelling Apps with WCF using REST and LINQ Building Feature Rich Business Apps Today with RIA Services MVVM: Why and How? Tips and Patterns using MVVM and Service Patterns with Silverlight and WP7 Tips and Tricks for a Great Installation Experience Tune Your Application: Profiling and Performance Tips Performance Tips for Silverlight Windows Phone 7 Select all the videos and click the Download button located below (has blue arrow): Once all the videos are downloaded you will have about 4.64GB of Silverlight fun. You can now move these videos to your MediaServer and watch them with whatever device you want. Put it on an iPad, iPhone.. emm wait I mean WP7 or WMC7.  2) Pimp the Training Material – Download the offline installer for the labs here. This will give you almost a gig of free training materials. Here is the topics covered: Level 100: Getting Started Lab 01 - WinForms and Silverlight Lab 02 - ASP.NET and Silverlight Lab 03 - XAML and Controls Lab 04 - Data Binding Level 200: Ready for More Lab 05 - Migrating Apps to Out-of-Browser Lab 06 - Great UX with Blend Lab 07 - Web Services and Silverlight Lab 08 - Using WCF RIA Services Level 300: Take me Further Lab 09 - Deep Dive into Out-of-Browser Lab 10 - Silverlight Patterns: Using MVVM Lab 11 - Silverlight and Windows Phone 7 You will notice that it install Firestarter to the default of C:\Firestarter. So you will have to navigate to that folder and double click on Default.htm to get started. Now if you followed part one of the pimping guide then you will already have all the videos on your pc. You will notice that once you go into the lab you will get a Lab Document and Source at the bottom of the article. Now instead of opening the Source Folder in a web browser you can just copy the folder C:\Firestarter\Labs into your Visual Studio 2010 Project Folder. This will save a lot of time later.   3) Pimp my Silverlight 5 Knowledge – Always keep reading as much as possible and remember that the Silverlight 5 Beta should come Q1 of 2011 and the final release at the end of 2011. Here are 5 great blog post on Silverlight 5. Scott Gu’s Blog Mary Jo’s Article on Silverlight 5 The Future of Silverlight (Official) Kunal Chowdhury Blog Tim Heuer’s Blog Thats all that I got for now. Have fun with all the new Silverlight content.  Subscribe to my feed

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  • Free RAM disappears - Memory leak?

    - by Izzy
    On a fresh started system, free reports about 1.5G used RAM (8G RAM alltogether, Ubuntu 12.04 with lightdm and plasma desktop, one konsole window started). Having the apps running I use, it still consumes not more than 2G. However, having the system running for a couple of days, more and more of my free RAM disappears -- without showing up in the list of used apps: while smem --pie=name reports less than 20% used (and 80% being available), everything else says differently. free -m for example reports on about day 7: total used free shared buffers cached Mem: 7459 7013 446 0 178 997 -/+ buffers/cache: 5836 1623 Swap: 9536 296 9240 (so you can see, it's not the buffers or the cache). Today this finally ended with the system crashing completely: the windows manager being gone, apps "hanging in the air" (frameless) -- and a popup notifying me about "too many open files". Syslog reports: kernel: [856738.020829] VFS: file-max limit 752838 reached So I closed those applications I was able to close, and killed X using Ctrl-Alt-backspace. X tried to come up again after that with failsafeX, but was unable to do so as it could no longer detect its configuration. So I switched to a console using Ctrl-Alt-F2, captured all information I could think of (vmstat, free, smem, proc/meminfo, lsof, ps aux), and finally rebooted. X again came up with failsafeX; this time I told it to "recover from my backed-up configuration", then switched to a console and successfully used startx to bring up the graphical environment. I have no real clue to what is causing this issue -- though it must have to do either with X itself, or with some user processes running on X -- as after killing X, free -m output looked like this: total used free shared buffers cached Mem: 7459 2677 4781 0 62 419 -/+ buffers/cache: 2195 5263 Swap: 9536 59 9477 (~3.5GB being freed) -- to compare with the output after a fresh start: total used free shared buffers cached Mem: 7459 1483 5975 0 63 730 -/+ buffers/cache: 689 6769 Swap: 9536 0 9536 Two more helpful outputs are provided by memstat -u. Shortly before the crash: User Count Swap USS PSS RSS mail 1 0 200 207 616 whoopsie 1 764 740 817 2300 colord 1 3200 836 894 2156 root 62 70404 352996 382260 569920 izzy 80 177508 1465416 1519266 1851840 After having X killed: User Count Swap USS PSS RSS mail 1 0 184 188 356 izzy 1 1400 708 739 1080 whoopsie 1 848 668 826 1772 colord 1 3204 804 888 1728 root 62 54876 131708 149950 267860 And after a restart, back in X: User Count Swap USS PSS RSS mail 1 0 212 217 628 whoopsie 1 0 1536 1880 5096 colord 1 0 3740 4217 7936 root 54 0 148668 180911 345132 izzy 47 0 370928 437562 915056 Edit: Just added two graphs from my monitoring system. Interesting to see: everytime when there's a "jump" in memory consumption, CPU peaks as well. Just found this right now -- and it reminds me of another indicator pointing to X itself: Often when returning to my machine and unlocking the screen, I found something doing heavvy work on my CPU. Checking with top, it always turned out to be /usr/bin/X :0 -auth /var/run/lightdm/root/:0 -nolisten tcp vt7 -novtswitch -background none. So after this long explanation, finally my questions: What could be the possible causes? How can I better identify involved processes/applications? What steps could be taken to avoid this behaviour -- short from rebooting the machine all X days? I was running 8.04 (Hardy) for about 5 years on my old machine, never having experienced the like (always more than 100 days uptime, before rebooting for e.g. kernel updates). This now is a complete new machine with a fresh install of 8.04. In case it matters, some specs: AMD A4-3400 APU with Radeon(tm) HD Graphics, using the open-source ati/radeon driver (so no fglrx installed), 8GB RAM, WDC WD1002FAEX-0 hdd (1TB), Asus F1A75-V Evo mainboard. Ubuntu 12.04 64-bit with KDE4/Plasma. Apps usually open more or less permanently include Evolution, Firefox, konsole (with Midnight Commander running inside, about 4 tabs), and LibreOffice -- plus occasionally Calibre, Gimp and Moneyplex (banking software I'm already using for almost 20 years now, in a version which did fine on Hardy).

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  • Apache2 config problem

    - by Hellnar
    For using my Debian VPS for multiple domains , I did such actions: removed the default one from sites-enabled/ and sites-available/ (config and the symbolic link) and I added this under sites-available/www.mysite.com : <VirtualHost MYIP:80> ServerName mysite.com ServerAlias www.mysite.com Alias /media/ /home/myuser/mysite/media/ Alias /admin_media/ /home/myuser/django/Django-1.2/django/contrib/admin/media/ WSGIScriptAlias / /home/myuser/mysite/wsgi.py ErrorLog /home/myuser/mysite/logs/error.log CustomLog /home/myuser/mysite/logs/access.log combined </VirtualHost> And I have changed my ports.conf to: NameVirtualHost MYIP:80 Listen 80 <IfModule mod_ssl.c> # SSL name based virtual hosts are not yet supported, therefore no # NameVirtualHost statement here Listen 443 </IfModule> Lastly I enabled the new domain via the command: a2ensite www.mysite.com After restart I get this error: myuser:~# /etc/init.d/apache2 restart Restarting web server: apache2apache2: Syntax error on line 281 of /etc/apache2/apache2.conf: Syntax error on line 1 of /etc/apache2/sites-enabled/www.birertek.com: /etc/apache2/sites-enabled/www.birertek.com:1: <VirtualHost> was not closed. failed! Please help this poor soul.

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  • Automatically Kill/Restart Process(es) When Memory is Critically Low

    - by nemesisfixx
    I have a Debian Wheezy VPS box where am running a couple of Django apps in production. Ideally, would have tried addressed my current memory footprint issues by optimizing the apps, adding more RAM or augmenting with Swap. But the problem is that I doubt there's much memory optimization I'd milk from optimizing the Django apps (the stack being open-source and robust), and adding RAM is a cost constraint for me (this is a remote VPS), also, the host doesn't offer options to use Swap! So, in the meantime (as I wait to secure more resources to afford more RAM), I wish to mitigate the scenarios where the server runs out memory so that I just have to request a VPS restart (as in, at that point, I can't even SSH into the box!). So, what I would love in a solution is the ability to detect when a process (or generally, total system memory usage) exceeds a certain critical amount (for now, example the FREE RAM falls to say 10%) - which I've noticed occurs after the VPS's been up for long, and when also traffic is suddenly much to some of the heavy apps (most are just staging apps anyway). So, I wish to be able to kill/restart the offending process(es) - most likely Apache. Which solution when done manually in these situations has restored sane memory usage levels - a hint that possibly one or more of the Django apps has a memory leak? In brief: Monitor overall system RAM usage When FREE RAM falls below a given critical threshold (say below 10%), kill/restart the offending process(es) - or simpler, if we assume from my current log analysis (using linux-dash) that Apache is often the offender, then kill/restart it. Rinse and repeat...

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  • 404 not found error for virtual host

    - by qubit
    Hello, In my /etc/apache2/sites-enabled, i have a file site2.com.conf, which defines a virtual host as follows : <VirtualHost *:80> ServerAdmin hostmaster@wharfage ServerName site2.com ServerAlias www.site2.com site2.com DirectoryIndex index.html index.htm index.php DocumentRoot /var/www LogLevel debug ErrorLog /var/log/apache2/site2_error.log CustomLog /var/log/apache2/site2_access.log combined ServerSignature Off <Location /> Options -Indexes </Location> Alias /favicon.ico /srv/site2/static/favicon.ico Alias /static /srv/site2/static # Alias /media /usr/local/lib/python2.5/site-packages/django/contrib/admin/media Alias /admin/media /var/lib/python-support/python2.5/django/contrib/admin/media WSGIScriptAlias / /srv/site2/wsgi/django.wsgi WSGIDaemonProcess site2 user=samj group=samj processes=1 threads=10 WSGIProcessGroup site2 </VirtualHost> I do the following to enable the site : 1) In /etc/apache2/sites-enabled, i run the command a2ensite site2.com.conf 2) I then get a message site successfully enabled, and then i run the command /etc/init.d/apache2 reload. But, if i navigate to www.site2.com, i get 404 not found. I do have an index.html in /var/www (permissions:777 and ownership www-data:www-data), and i have also verified that a symlink was created for site2.com.conf in /etc/apache2/sites-enabled. Any way to fix this ? Thank you.

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  • T4MVC and duplicate controller names in different areas

    - by artvolk
    In my application I have controller named Snippets both in default area (in application root) and in my area called Manage. I use T4MVC and custom routes, like this: routes.MapRoute( "Feed", "feed/", MVC.Snippets.Rss() ); And I get this error: Multiple types were found that match the controller named 'snippets'. This can happen if the route that services this request ('{controller}/{action}/{id}/') does not specify namespaces to search for a controller that matches the request. If this is the case, register this route by calling an overload of the 'MapRoute' method that takes a 'namespaces' parameter. The request for 'snippets' has found the following matching controllers: Snippets.Controllers.SnippetsController Snippets.Areas.Manage.Controllers.SnippetsController I know that there are overloads for MapRoute that take namespaces argument, but there are no such overloads with T4MVC support. May be I'm missing something? The possible syntax can be: routes.MapRoute( "Feed", "feed/", MVC.Snippets.Rss(), new string[] {"Snippets.Controllers"} ); or, it seems quite good to me to have namespace as T4MVC property: routes.MapRoute( "Feed", "feed/", MVC.Snippets.Rss(), new string[] {MVC.Snippets.Namespace} ); Thanks in advance!

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  • MSSQL in ASP.NET application getting unstable after a certain period

    - by Barslett
    Hello, I have an ASP.NET 2.0 application that I made to keep track of disruption reports about our public transport system. The architecture is pretty straight-forward; an MSSQL Express 2008 database, ADO.NET and a DataSet/DAL with a few methods to access the database. There is a set of .aspx pages for the UI in use by our dispatchers and on our public website, as well as a set of SOAP and REST webservices and an RSS feed. Everything worked just fine for more than a year, until two weeks ago. Now and then, it seems as the database enters an unstable mode, and the application starts responding something right, something wrong. The typical error is that apparently, an empty DataTable is returned to the public disruption overview or to the RSS generator. Thus, the user gets e.g. an empty GridView, but no exception is thrown AFAIK, and nothing is written to the Windows Application log. After a restart of the MSSQL Express service, the situation is back to normal. It has to be said that the situation first time appeared a few days after I made a new minor upgrade of the application. The RSS generator was slightly rewritten, and I added a WCF REST service. But the DAL and the database schema were untouched... Any hints of how we could keep the database stable? It is a bit annoying not to have a clue ;-)

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  • Display all feeds using simplexml_load() using PHP

    - by Jean
    Hello, I want to loop to get all feeds, but displaying only one $url = "http://localhost/feeds/feeds.rss"; $xml = simplexml_load_file($url); foreach($xml->item as $result){ echo $result->description."<br>"; } RSS Feed is - <channel> <title>/</title> <link>/</link> <atom:link type="application/rss+xml" href="/" rel="self"/> <description>/</description> <language>/</language> <ttl>/</ttl> <item> <title>/</title> <description>/</description> <pubDate>/</pubDate> <guid>/</guid> <link>/</link> </item> <item> <title>/</title> <description>/</description> <pubDate>/</pubDate> <guid>/</guid> <link>/</link> </item> </channel> Thanks Jean

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  • Using TPL and PLINQ to raise performance of feed aggregator

    - by DigiMortal
    In this posting I will show you how to use Task Parallel Library (TPL) and PLINQ features to boost performance of simple RSS-feed aggregator. I will use here only very basic .NET classes that almost every developer starts from when learning parallel programming. Of course, we will also measure how every optimization affects performance of feed aggregator. Feed aggregator Our feed aggregator works as follows: Load list of blogs Download RSS-feed Parse feed XML Add new posts to database Our feed aggregator is run by task scheduler after every 15 minutes by example. We will start our journey with serial implementation of feed aggregator. Second step is to use task parallelism and parallelize feeds downloading and parsing. And our last step is to use data parallelism to parallelize database operations. We will use Stopwatch class to measure how much time it takes for aggregator to download and insert all posts from all registered blogs. After every run we empty posts table in database. Serial aggregation Before doing parallel stuff let’s take a look at serial implementation of feed aggregator. All tasks happen one after other. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();           for (var index = 0; index <blogs.Count; index++)         {              ImportFeed(blogs[index]);         }     }       private void ImportFeed(BlogDto blog)     {         if(blog == null)             return;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                 }       private void ImportRssFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = RssFeed.Create(uri);           foreach (var item in feed.Channel.Items)         {             SaveRssFeedItem(item, blog.Id, blog.CreatedById);         }     }       private void ImportAtomFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           foreach (var item in feed.Entries)         {             SaveAtomFeedEntry(item, blog.Id, blog.CreatedById);         }     } } Serial implementation of feed aggregator downloads and inserts all posts with 25.46 seconds. Task parallelism Task parallelism means that separate tasks are run in parallel. You can find out more about task parallelism from MSDN page Task Parallelism (Task Parallel Library) and Wikipedia page Task parallelism. Although finding parts of code that can run safely in parallel without synchronization issues is not easy task we are lucky this time. Feeds import and parsing is perfect candidate for parallel tasks. We can safely parallelize feeds import because importing tasks doesn’t share any resources and therefore they don’t also need any synchronization. After getting the list of blogs we iterate through the collection and start new TPL task for each blog feed aggregation. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();                var tasks = new Task[blogs.Count];           for (var index = 0; index <blogs.Count; index++)         {             tasks[index] = new Task(ImportFeed, blogs[index]);             tasks[index].Start();         }           Task.WaitAll(tasks);     }       private void ImportFeed(object blogObject)     {         if(blogObject == null)             return;         var blog = (BlogDto)blogObject;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                }       private void ImportRssFeed(BlogDto blog)     {          var uri = new Uri(blog.RssUrl);          var feed = RssFeed.Create(uri);           foreach (var item in feed.Channel.Items)          {              SaveRssFeedItem(item, blog.Id, blog.CreatedById);          }     }     private void ImportAtomFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           foreach (var item in feed.Entries)         {             SaveAtomFeedEntry(item, blog.Id, blog.CreatedById);         }     } } You should notice first signs of the power of TPL. We made only minor changes to our code to parallelize blog feeds aggregating. On my machine this modification gives some performance boost – time is now 17.57 seconds. Data parallelism There is one more way how to parallelize activities. Previous section introduced task or operation based parallelism, this section introduces data based parallelism. By MSDN page Data Parallelism (Task Parallel Library) data parallelism refers to scenario in which the same operation is performed concurrently on elements in a source collection or array. In our code we have independent collections we can process in parallel – imported feed entries. As checking for feed entry existence and inserting it if it is missing from database doesn’t affect other entries the imported feed entries collection is ideal candidate for parallelization. internal class FeedClient {     private readonly INewsService _newsService;     private const int FeedItemContentMaxLength = 255;       public FeedClient()     {          ObjectFactory.Initialize(container =>          {              container.PullConfigurationFromAppConfig = true;          });           _newsService = ObjectFactory.GetInstance<INewsService>();     }       public void Execute()     {         var blogs = _newsService.ListPublishedBlogs();                var tasks = new Task[blogs.Count];           for (var index = 0; index <blogs.Count; index++)         {             tasks[index] = new Task(ImportFeed, blogs[index]);             tasks[index].Start();         }           Task.WaitAll(tasks);     }       private void ImportFeed(object blogObject)     {         if(blogObject == null)             return;         var blog = (BlogDto)blogObject;         if (string.IsNullOrEmpty(blog.RssUrl))             return;           var uri = new Uri(blog.RssUrl);         SyndicationContentFormat feedFormat;           feedFormat = SyndicationDiscoveryUtility.SyndicationContentFormatGet(uri);           if (feedFormat == SyndicationContentFormat.Rss)             ImportRssFeed(blog);         if (feedFormat == SyndicationContentFormat.Atom)             ImportAtomFeed(blog);                }       private void ImportRssFeed(BlogDto blog)     {         var uri = new Uri(blog.RssUrl);         var feed = RssFeed.Create(uri);           feed.Channel.Items.AsParallel().ForAll(a =>         {             SaveRssFeedItem(a, blog.Id, blog.CreatedById);         });      }        private void ImportAtomFeed(BlogDto blog)      {         var uri = new Uri(blog.RssUrl);         var feed = AtomFeed.Create(uri);           feed.Entries.AsParallel().ForAll(a =>         {              SaveAtomFeedEntry(a, blog.Id, blog.CreatedById);         });      } } We did small change again and as the result we parallelized checking and saving of feed items. This change was data centric as we applied same operation to all elements in collection. On my machine I got better performance again. Time is now 11.22 seconds. Results Let’s visualize our measurement results (numbers are given in seconds). As we can see then with task parallelism feed aggregation takes about 25% less time than in original case. When adding data parallelism to task parallelism our aggregation takes about 2.3 times less time than in original case. More about TPL and PLINQ Adding parallelism to your application can be very challenging task. You have to carefully find out parts of your code where you can safely go to parallel processing and even then you have to measure the effects of parallel processing to find out if parallel code performs better. If you are not careful then troubles you will face later are worse than ones you have seen before (imagine error that occurs by average only once per 10000 code runs). Parallel programming is something that is hard to ignore. Effective programs are able to use multiple cores of processors. Using TPL you can also set degree of parallelism so your application doesn’t use all computing cores and leaves one or more of them free for host system and other processes. And there are many more things in TPL that make it easier for you to start and go on with parallel programming. In next major version all .NET languages will have built-in support for parallel programming. There will be also new language constructs that support parallel programming. Currently you can download Visual Studio Async to get some idea about what is coming. Conclusion Parallel programming is very challenging but good tools offered by Visual Studio and .NET Framework make it way easier for us. In this posting we started with feed aggregator that imports feed items on serial mode. With two steps we parallelized feed importing and entries inserting gaining 2.3 times raise in performance. Although this number is specific to my test environment it shows clearly that parallel programming may raise the performance of your application significantly.

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  • display MultiPolygonField data on Geodjango/OpenLayers

    - by Markos Gogoulos
    Hi all, I'm a Geodjango novice and would like to get some help on the following: I have a MultiPolygonField field, for a GeoDjango application, and would like to display it on my view as cool as it gets displayed on django admin Say for example I have def index(request): "Index,main view" border = WorldBorders.objects.get(name='Italy') return render_to_response('world/index.html', {'user': request.user, 'border': border}, context_instance=RequestContext(request)) then on world/index.html, what is the way to display the border, as it would be on django admin? Thanks in advance for all replies!

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  • Java web frameworks

    - by mnml
    I was looking around to see if there is an equivalent to django/RoR in java. I found: Play Framework Grails Does anyone have ever tried those frameworks, or do you know any other? Are they faster than django/RoR?

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  • Database migrations for SQL Server

    - by Art
    I need a database migration framework for SQL Server, capable of managing both schema changes and data migrations. I guess I am looking for something similar to django's South framework here. Given the fact that South is tightly coupled with django's ORM, and the fact that there's so many ORMs for SQL Server I guess having just a generic migration framework, enabling you to write and execute in controlled and sequential manner SQL data/schema change scripts should be sufficient.

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  • Database migrations for MS SQL Server

    - by Art
    I need a database migration framework for MS SQL Server, capable of managing both schema changes and data migrations. I guess I am looking for something similar to django's South framework here. given the fact that South is tightly coupled with django's ORM, and the fact that there's so many ORMs for MS SQL I guess having just a generic migration framework, enabling you to write and execute in controlled and sequential manner SQL data/schema change scripts should be sufficient. Thanks!

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  • Komodo Double Indentation with Tab

    - by T. Stone
    In Komodo Edit, if I name the file *.django.html it gives me django syntax highlighting BUT it also indents with a tab character (8 spaces) instead of giving me the usual 4 space indent. How can I fix this? I've tried changing the value in Edit Preferences Editor Indentation Language Settings, but that seems to have no effect on it. The indentation works as normal (4 spaces) if I'm using any other extension (.py, .html, etc.). Ideas?

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  • Regex for Matching First Alphanumeric Character skipping (The |An? )

    - by TheLizardKing
    I have a list of artists, albums and tracks that I want to sort using the first letter of their respective name. The issue arrives when I want to ignore "The ", "A ", "An " and other various non-alphanumeric characters (Talking to you "Weird Al" Yankovic and [dialog]). Django has a nice start '^(An?|The) +' but I want to ignore those and a few others of my choice. I am doing this in Django, using a MySQL db with utf8_bin collation.

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  • GUI editor for DOT language (Mac OS)

    - by Saff
    Hi, i have a problem. I need to create pure diagram for my project (Django). I use django-extensions to generate DOT diagram. Diagram is very pure, but now i want to add for example comments on this diagram. It is possible to do this? Maybe anyone can advise me some software for this?

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  • jQuery - How can I temporarily disable the onclick event listener after the event has been fired?

    - by aldux
    How can I temporarily disable the onclick event listener, (jQuery preferred), after the event has been fired? Example: After the user clicks on the button and fires this function below, I want to disabled the onclick listener, therefore not firing the same command to my django view. $(".btnRemove").click(function(){ $(this).attr("src", "/url/to/ajax-loader.gif"); $.ajax({ type: "GET", url: "/url/to/django/view/to/remove/item/" + this.id, dataType: "json", success: function(returned_data){ $.each(returned_data, function(i, item){ // do stuff }); } }); Thanks a lot, Aldo

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  • Getting the URL of a model in Lift

    - by scompt.com
    I'm coming at Lift from a Django point of view, so in Django parlence, I'm trying to find the Lift equivalent of reverse. In generic terms, I have an instance of a model and I would like to get the URL that that model can be accessed at according to the SiteMap. I've tried extending Loc, but that doesn't seem to have brought me further towards my goal. I'm using the most recent 1.1 milestone (M8?).

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  • What should I learn & use to become a pro in PHP & Python Web development?

    - by pecker
    Hello, I'll just show some code to show how I do web development in PHP. <html> <head> <title>Example #3 TDavid's Very First PHP Script ever!</title> </head> <? print(Date("m/j/y")); require_once("somefile.php"); $mysql_db = "DATABASE NAME"; $mysql_user = "YOUR MYSQL USERNAME"; $mysql_pass = "YOUR MYSQL PASSWORD"; $mysql_link = mysql_connect("localhost", $mysql_user, $mysql_pass); mysql_select_db($mysql_db, $mysql_link); $result = mysql_query("SELECT impressions from tds_counter where COUNT_ID='$cid'", $mysql_link); if(mysql_num_rows($result)) { mysql_query("UPDATE tds_counter set impressions=impressions+1 where COUNT_ID='$cid'", $mysql_link); $row = mysql_fetch_row($result); if(!$inv) { print("$row[0]"); } } ?> <body> </body> </html> Thats it. I write every file like this. Recently, I learnt OOP and started using classes & objects in PHP. I hear that there are many frameworks there for PHP. They say that one must use these libraries. But I feel they are just making things complicated. Anyway, this is how I've been doing my web development. Now, I want to improve this. and make it professional. Also I want to move to Python. I searched SO archives and found everyone suggesting Django. But, can any one give me some idea about how web development in Python works? user (client) request for page --- webserver(-embedded PHP interpreter) ---- Server side(PHP) Script --- MySQL Server. Now, is it that instead of PHP interpreter there is python interpreter & instead of php script there is python script, which contains both HTML & python (embedded in some kind of python tags). Python script connects to database server and fetches some data which will be printed as HTML. or is it different in python world? Is this Django thing like frameworks for PHP? Can't one code in python without using Django. Because, I never encountered any post without django Please give me some kick start.

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  • iPhone: "there was a problem downloading this podcast"

    - by brianegge
    I have several podcasts which work perfectly fine in iTunes, but when I attempt to download additional episodes on the iPhone I get the message "there was a problem downloading this podcast" once the download completes. All I can find points to my iPhone not having enough disk space. The settings tells me I have 1GB available. I've also tried deleting some content and receive the same message. Originally, I thought this might be due to the RSS feed indicating a different file size than the media file, but I manually verified its correct. A podcast which I can always reproduce this problem has the following feed: http://www.podquiz.com/rss.php I can reproduce the problem on both WiFi and 3G.

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  • Re-downloading accidentally deleted podcasts in iTunes

    - by Matt
    I deleted some previously deleted podcast episodes in iTunes 9 and I'd like to re-download them. (I don't want to manually re-download them because then they won't show up in the podcast's list in the iTunes Podcast section.) I've read http://blog.krisgielen.be/archives/54 as well as Way to get old podcasts in iTunes where the suggestion is to delete the iTunes entries for the podcasts I'd like to recover, then hold shift while re-opening that podcast's little triangle icon. Here's the problem though: holding shift and re-opening the triangle tells iTunes to refresh the RSS feed, and it's possible that the RSS feed no longer contains the item you want. What I'm really looking for is a means of getting the "Get" button (that normally appears on un-downloaded podcasts) to reappear on the episodes I've previously downloaded but deleted.

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