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  • MySQL on Linux out of memory

    - by Sunrays
    OS: Redhat Enterprise Linux Server Release 5.3 (Tikanga) Architecture: Intel Xeon 64Bit MySQL Server 5.5.20 Enterprise Server advanced edition. Application: Liferay. My database size is 200MB. RAM is 64GB. The memory consumption increases gradually and we run out of memory. Then only rebooting releases all the memory, but then process of memory consumption starts again and reaches 63-64GB in less than a day. Parameters detail: key_buffer_size=16M innodb_buffer_pool_size=3GB inndb_buffer_pool_instances=3 max_connections=1000 innodb_flush_method=O_DIRECT innodb_change_buffering=inserts read_buffer_size=2M read_rnd_buffer_size=256K It's a serious production server issue that I am facing. What could be the reason behind this and how to resolve. This is the report of 2pm today, after Linux was rebooted yesterday @ around 10pm. Output of free -m total used free shared buffers cached Mem: 64455 22053 42402 0 1544 1164 -/+ buffers/cache: 19343 45112 Swap: 74998 0 74998 Output of vmstat 2 5 procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu------ r b swpd free buff cache si so bi bo in cs us sy id wa st 0 0 0 43423976 1583700 1086616 0 0 1 173 22 27 1 1 98 0 0 2 0 0 43280200 1583712 1228636 0 0 0 146 1265 491 2 2 96 1 0 0 0 0 43421940 1583724 1087160 0 0 0 138 1469 738 2 1 97 0 0 1 0 0 43422604 1583728 1086736 0 0 0 5816 1615 934 1 1 97 0 0 0 0 0 43422372 1583732 1086752 0 0 0 2784 1323 545 2 1 97 0 0 Output of top -n 3 -b top - 14:16:22 up 16:32, 5 users, load average: 0.79, 0.77, 0.93 Tasks: 345 total, 1 running, 344 sleeping, 0 stopped, 0 zombie Cpu(s): 1.0%us, 0.9%sy, 0.0%ni, 98.1%id, 0.1%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 66002772k total, 22656292k used, 43346480k free, 1582152k buffers Swap: 76798724k total, 0k used, 76798724k free, 1163616k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 6434 mysql 15 0 4095m 841m 5500 S 113.5 1.3 426:53.69 mysqld 1 root 15 0 10344 680 572 S 0.0 0.0 0:03.09 init 2 root RT -5 0 0 0 S 0.0 0.0 0:00.01 migration/0 3 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/0 4 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/0 5 root RT -5 0 0 0 S 0.0 0.0 0:00.01 migration/1 6 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/1 7 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/1 8 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/2 9 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/2 10 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/2 11 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/3 12 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/3 13 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/3 14 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/4 15 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/4 16 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/4 17 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/5 18 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/5 19 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/5 20 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/6 21 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/6 22 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/6 23 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/7 24 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/7 25 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/7 26 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/8 27 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/8 28 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/8 29 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/9 30 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/9 31 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/9 32 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/10 33 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/10 34 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/10 35 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/11 36 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/11 37 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/11 38 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/12 39 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/12 40 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/12 41 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/13 42 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/13 43 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/13 44 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/14 45 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/14 46 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/14 47 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/15 48 root 34 19 0 0 0 S 0.0 0.0 0:00.01 ksoftirqd/15 49 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/15 50 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/16 51 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/16 52 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/16 53 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/17 54 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/17 55 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/17 56 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/18 57 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/18 58 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/18 59 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/19 60 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/19 61 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/19 62 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/20 63 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/20 64 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/20 65 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/21 66 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/21 67 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/21 68 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/22 69 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/22 70 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/22 71 root RT -5 0 0 0 S 0.0 0.0 0:00.00 migration/23 72 root 34 19 0 0 0 S 0.0 0.0 0:00.00 ksoftirqd/23 73 root RT -5 0 0 0 S 0.0 0.0 0:00.00 watchdog/23 74 root 10 -5 0 0 0 S 0.0 0.0 0:00.02 events/0 75 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/1 76 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/2 77 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/3 78 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/4 79 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/5 80 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/6 81 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/7 82 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/8 83 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/9 84 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/10 85 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/11 86 root 10 -5 0 0 0 S 0.0 0.0 0:00.01 events/12 87 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/13 88 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/14 89 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/15 90 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/16 91 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/17 92 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/18 93 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/19 94 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/20 95 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/21 96 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/22 97 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 events/23 98 root 10 -5 0 0 0 S 0.0 0.0 0:00.01 khelper 615 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kthread 643 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/0 644 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/1 645 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/2 646 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/3 647 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/4 648 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/5 649 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/6 650 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/7 651 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/8 652 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/9 653 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/10 654 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/11 655 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/12 656 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/13 657 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/14 658 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/15 659 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/16 660 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/17 661 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/18 662 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/19 663 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/20 664 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/21 665 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/22 666 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kblockd/23 667 root 17 -5 0 0 0 S 0.0 0.0 0:00.00 kacpid 840 root 17 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/0 841 root 18 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/1 842 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/2 843 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/3 844 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/4 845 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/5 846 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/6 847 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/7 848 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/8 849 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/9 850 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/10 851 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/11 852 root 15 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/12 853 root 16 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/13 854 root 17 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/14 855 root 18 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/15 856 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/16 857 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/17 858 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/18 859 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/19 860 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/20 861 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/21 862 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/22 863 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 cqueue/23 866 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 khubd 868 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kseriod 1118 root 23 0 0 0 0 S 0.0 0.0 0:00.00 pdflush 1119 root 15 0 0 0 0 S 0.0 0.0 0:00.11 pdflush 1120 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 kswapd0 1121 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 kswapd1 1122 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 aio/0 1123 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 aio/1 1124 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 aio/2 1125 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/3 1126 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/4 1127 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/5 1128 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/6 1129 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/7 1130 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/8 1131 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/9 1132 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/10 1133 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/11 1134 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/12 1135 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/13 1136 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/14 1137 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/15 1138 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/16 1139 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/17 1140 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/18 1141 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/19 1142 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/20 1143 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/21 1144 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/22 1145 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 aio/23 1308 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 kpsmoused 1566 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/0 1567 root 10 -5 0 0 0 S 0.0 0.0 0:00.27 ata/1 1568 root 10 -5 0 0 0 S 0.0 0.0 0:02.39 ata/2 1569 root 10 -5 0 0 0 S 0.0 0.0 0:00.07 ata/3 1570 root 10 -5 0 0 0 S 0.0 0.0 0:00.72 ata/4 1571 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/5 1572 root 10 -5 0 0 0 S 0.0 0.0 0:00.15 ata/6 1573 root 10 -5 0 0 0 S 0.0 0.0 0:00.07 ata/7 1574 root 10 -5 0 0 0 S 0.0 0.0 0:00.06 ata/8 1575 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/9 1576 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/10 1577 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/11 1578 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/12 1579 root 10 -5 0 0 0 S 0.0 0.0 0:00.14 ata/13 1580 root 10 -5 0 0 0 S 0.0 0.0 0:01.56 ata/14 1581 root 10 -5 0 0 0 S 0.0 0.0 0:00.04 ata/15 1582 root 10 -5 0 0 0 S 0.0 0.0 0:00.40 ata/16 1583 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/17 1584 root 10 -5 0 0 0 S 0.0 0.0 0:00.11 ata/18 1585 root 10 -5 0 0 0 S 0.0 0.0 0:00.03 ata/19 1586 root 10 -5 0 0 0 S 0.0 0.0 0:00.02 ata/20 1587 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/21 1588 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/22 1589 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 ata/23 1590 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 ata_aux 1616 root 10 -5 0 0 0 S 0.0 0.0 0:17.20 scsi_eh_0 1617 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 scsi_eh_1 1668 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 scsi_eh_2 1669 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 qla2xxx_2_dpc 1670 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 scsi_wq_2 1671 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 fc_wq_2 1672 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 fc_dl_2 1673 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 scsi_eh_3 1674 root 0 -20 0 0 0 S 0.0 0.0 0:00.00 qla2xxx_3_dpc 1675 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 scsi_wq_3 1676 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 fc_wq_3 1677 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 fc_dl_3 1728 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 kstriped 1829 root 10 -5 0 0 0 S 0.0 0.0 1:09.14 kjournald 1857 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kauditd 1891 root 11 -4 13008 1188 388 S 0.0 0.0 0:00.40 udevd 4555 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/0 4556 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/1 4557 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/2 4558 root 14 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/3 4559 root 15 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/4 4560 root 16 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/5 4561 root 16 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/6 4562 root 17 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/7 4563 root 18 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/8 4564 root 19 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/9 4565 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/10 4566 root 20 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/11 4567 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/12 4568 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/13 4569 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/14 4570 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/15 4571 root 14 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/16 4572 root 14 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/17 4573 root 14 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/18 4574 root 15 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/19 4575 root 16 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/20 4576 root 15 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/21 4577 root 16 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/22 4578 root 16 -5 0 0 0 S 0.0 0.0 0:00.00 kmpathd/23 4579 root 18 -5 0 0 0 S 0.0 0.0 0:00.00 kmpath_handlerd 4734 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kjournald 4736 root 10 -5 0 0 0 S 0.0 0.0 0:04.82 kjournald 4744 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 kjournald 5238 root RT 0 87584 3648 2768 S 0.0 0.0 0:03.60 multipathd 5537 root 11 -4 27328 812 580 S 0.0 0.0 0:00.14 auditd 5539 root 7 -8 81804 768 616 S 0.0 0.0 0:00.04 audispd 5564 root 15 0 5904 632 512 S 0.0 0.0 0:00.10 syslogd 5567 root 15 0 3800 432 344 S 0.0 0.0 0:00.01 klogd 5579 root 18 0 10728 384 244 S 0.0 0.0 0:00.42 irqbalance 5592 rpc 18 0 8048 584 464 S 0.0 0.0 0:00.00 portmap 5625 root 18 0 11032 768 632 S 0.0 0.0 0:00.00 rpc.statd 5681 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/0 5682 root 11 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/1 5683 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/2 5684 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/3 5685 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/4 5686 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/5 5687 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/6 5688 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/7 5689 root 10 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/8 5690 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/9 5691 root 12 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/10 5692 root 13 -5 0 0 0 S 0.0 0.0 0:00.00 rpciod/11

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  • Bahnbrechend und einsatzbereit: Oracle 12c In-Memory-Option Launch in Frankfurt

    - by Anne Manke
    Seit der Ankündigung der Oracle 12c In-Memory-Databankoption in San Francisco auf der Openworld im letzten Jahr, ist die DB Community gespannt, was diese bahnbrechende Technologie für Ad-hoc-Echtzeitanalysen von Live-Transaktionen, Data Warehousing, Reporting und Online Transaction Processing (OLTP) bringen wird. Die Messlatte liegt hoch, denn Larry Ellison verspricht mit der neuen 12c In-Memory-Option eine 100-fach schnellerer Verarbeitung von Abfragen bei Echtzeitanalysen für OLTP Prozesse oder Datawarehouses eine Verdoppelung der Transaktionsverarbeitung eine 100%ige Kompatibilität zu bestehenden Anwendungen Daten werden im Zeilenformat und Spaltenformat (In-Memory) abgelegt, und sind dabei aktiv und konsitstent Cloud-ready ohne Datamigration eine Ausweitung der In-Memory-basierten Abfrageprozesse auf mehrere Server    Um nur einige Features zu nennen >> mehr Infos finden Sie hier! Abfragen werden mit der neuen 12c In-Memory-Datenbankoption schneller bearbeitet, als die Anfrage gestellt werden kann, so Larry Ellison. Am 17. Juni 2014 wird die 12c In-Memory auf einer exklusiven Launch-Veranstaltung in Frankfurt am Main vorgestellt. Auf der Agenda stehen Vorträge, Diskussionen und eine LiveDemo der In-Memory-Datenbankoption.  Melden Sie sich jetzt an! Ort & Zeit: 17. Juni 2014, 9:30 - 15:15 Uhr in Radisson Blu Hotel (Franklinstrasse 65, 60486 Frankfurt am Main) Agenda 9:30 Registrierung 10:00 Begrüßung Guenther Stuerner, Vice President Sales Consulting, Oracle Deutschland (in deutscher Sprache) 10:15 Analystenvortrag Carl W. Olofson, Research Vice President, IDC (in englischer Sprache) 10:35 Keynote Andy Mendelsohn, Head of Database Development, Oracle (in englischer Sprache) 11:35 Podiumsdiskussion (in englischer Sprache): · Jens-Christian Pokolm, Postbank Systems AG · Andy Mendelsohn, Head of Database Development, Oracle · Carl W. Olofson, Research Vice President, IDC · Dr. Dietmar Neugebauer, Vorstandsvorsitzender, DOAG 12:30 Mittagessen 13:45 Oracle Database In Memory Option    Perform – Manage – Live Demo Ralf Durben, Senior Leitender Systemberater, Oracle Deutschland (in deutscher Sprache) 14:30 In Memory – Revolution for your DWH – Real Time Datawarehouse – Mixed Workloads – Live Demo – Live Data Query Alfred Schlaucher, Senior Leitender Systemberater, Oracle Deutschland (in deutscher Sprache) 15:15 Schlusswort & Networking

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  • Memory Bandwidth Performance for Modern Machines

    - by porgarmingduod
    I'm designing a real-time system that occasionally has to duplicate a large amount of memory. The memory consists of non-tiny regions, so I expect the copying performance will be fairly close to the maximum bandwidth the relevant components (CPU, RAM, MB) can do. This led me to wonder what kind of raw memory bandwidth modern commodity machine can muster? My aging Core2Duo gives me 1.5 GB/s if I use 1 thread to memcpy() (and understandably less if I memcpy() with both cores simultaneously.) While 1.5 GB is a fair amount of data, the real-time application I'm working on will have have something like 1/50th of a second, which means 30 MB. Basically, almost nothing. And perhaps worst of all, as I add multiple cores, I can process a lot more data without any increased performance for the needed duplication step. But a low-end Core2Due isn't exactly hot stuff these days. Are there any sites with information, such as actual benchmarks, on raw memory bandwidth on current and near-future hardware? Furthermore, for duplicating large amounts of data in memory, are there any shortcuts, or is memcpy() as good as it will get? Given a bunch of cores with nothing to do but duplicate as much memory as possible in a short amount of time, what's the best I can do?

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  • .NET out of memory troubleshooting

    - by bushman
    After reading a few enlightening articles about memory in the .NET technology, Out of Memory does not refer to physical memory, 597499. I thought I understood why a C# app would throw an out of memory exception -- until I started experimenting with two servers-- both are having 2.5 gigs of ram, windows server 2003 and identical programs running. The only significant difference between the two being one has 7% hard drive storage left and the other more than 50%. The server with 7% storage space left is consistently throwing an out of memory while the other is performing consistently well. My app is a C# web application that process' hundreds of MBs of String object. Why would this difference happen seeing that the most likely reason for the out of memory issue is out of contiguous virtual address space -- What solutions do you guys propose -- and what do you say about the following 1. turn on the 3gb switch to increase the virtual address space -- 2. instead of using one giant string object, break it up into smaller pieces and collect it in a jagged array (here I have to find a way to return to the caller in some other way as right now, the return type is a string) thanks SO

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  • Memory Leak Looping cfmodule inside cffunction

    - by orangepips
    Hoping someone else can confirm or tell me what I'm doing wrong. I am able to consistently reproduce an OOM running by calling the file oom.cfm (shown below). Using jconsole I am able to see the request consumes memory and never releases it until complete. The issue appears to be calling <cfmodule> inside of <cffunction>, where if I comment out the <cfmodule> call things are garbage collected while the request is running. ColdFusion version: 9,0,1,274733 JVM Arguments java.home=C:/Program Files/Java/jdk1.6.0_18 java.args=-server -Xms768m -Xmx768m -Dsun.io.useCanonCaches=false -XX:MaxPermSize=512m -XX:+UseParallelGC -Xbatch -Dcoldfusion.rootDir={application.home}/ -Djava.security.policy={application.home}/servers/41ep8/cfusion.ear/cfusion.war/WEB-INF/cfusion/lib/coldfusion.policy -Djava.security.auth.policy={application.home}/servers/41ep8/cfusion.ear/cfusion.war/WEB-INF/cfusion/lib/neo_jaas.policy -Xdebug -Xrunjdwp:transport=dt_socket,server=y,suspend=n,address=56033 Test Case oom.cfm (this calls template.cfm below) <cffunction name="fun" output="false" access="public" returntype="any" hint=""> <cfset var local = structNew()/> <!--- comment out cfmodule and no OOM ---> <cfmodule template="template.cfm"> </cffunction> <cfset size = 1000 * 200> <cfloop from="1" to="#size#" index="idx"> <cfset fun()> <cfif NOT idx mod 1000> <cflog file="se-err" text="#idx# of #size#"> </cfif> </cfloop> template.cfm <!--- I am empty! --->

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  • Cryptography: best practices for keys in memory?

    - by Johan
    Background: I got some data encrypted with AES (ie symmetric crypto) in a database. A server side application, running on a (assumed) secure and isolated Linux box, uses this data. It reads the encrypted data from the DB, and writes back encrypted data, only dealing with the unencrypted data in memory. So, in order to do this, the app is required to have the key stored in memory. The question is, is there any good best practices for this? Securing the key in memory. A few ideas: Keeping it in unswappable memory (for linux: setting SHM_LOCK with shmctl(2)?) Splitting the key over multiple memory locations. Encrypting the key. With what, and how to keep the...key key.. secure? Loading the key from file each time its required (slow and if the evildoer can read our memory, he can probably read our files too) Some scenarios on why the key might leak: evildoer getting hold of mem dump/core dump; bad bounds checking in code leading to information leakage; The first one seems like a good and pretty simple thing to do, but how about the rest? Other ideas? Any standard specifications/best practices? Thanks for any input!

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  • Hibernate: Walk millions of rows and don't leak memory

    - by Autocracy
    The below code functions, but Hibernate never lets go of its grip of any object. Calling session.clear() causes exceptions regarding fetching a joined class, and calling session.evict(currentObject) before retrieving the next object also fails to free the memory. Eventually I exhaust my heap space. Checking my heap dumps, StatefulPersistenceContext is the garbage collector's root for all references pointing to my objects. public class CriteriaReportSource implements JRDataSource { private ScrollableResults sr; private Object currentObject; private Criteria c; private static final int scrollSize = 10; private int offset = 1; public CriteriaReportSource(Criteria c) { this.c = c; advanceScroll(); } private void advanceScroll() { // ((Session) Main.em.getDelegate()).clear(); this.sr = c.setFirstResult(offset) .setMaxResults(scrollSize) .scroll(ScrollMode.FORWARD_ONLY); offset += scrollSize; } public boolean next() { if (sr.next()) { currentObject = sr.get(0); if (sr.isLast()) { advanceScroll(); } return true; } return false; } public Object getFieldValue(JRField jrf) throws JRException { Object retVal = null; if(currentObject == null) { return null; } try { retVal = PropertyUtils.getProperty(currentObject, jrf.getName()); } catch (Exception ex) { Logger.getLogger(CriteriaReportSource.class.getName()).log(Level.SEVERE, null, ex); } return retVal; } }

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  • How is external memory, internal memory, and cache organized?

    - by goldenmean
    Consider a system as follows:= A hardware board having say ARM Cortex-A8 and Neon Vector coprocessor, and Embedded Linux OS running on Cortex-A8. On this environment, if there is some application - say, a video decoder is executing - then: How is it decided that which buffers would be in external memory, which ones would be allocated in internal SRAM, etc. When one says calloc/malloc on such system/code, the pointer returned is from which memory: internal or external? Can a user make buffers to be allocated to the memories of his choice (internal/external)? In ARM architectures, there is another memory called as Tightly coupled memory (TCM). What is that and how can user enable and use it? Can I declare buffers in this memory? Do I need to see the memory map (if any) of the hardware board to understand about all these different physical memories present in a typical hardware board? How much of a role does the OS play in distinguishing these different memories? Sorry for multiple questions, but i think they all are interlinked.

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  • Memory Leak in returning NSMutableArray from class

    - by Structurer
    Hi I am quite new to Objective C for the iPhone, so I hope you wont kill me for asking a simple question. I have made an App that works fine, except that Instruments reports memory leaks from the class below. I use it to store settings from one class and then retrieve them from another class. These settings are stored on a file so they can be retrieved every time the App is ran. What can I do do release the "setting" and is there anything that can be done to call (use) the class in a smarter way? Thanks ----- Below is Settings.m ----- import "Settings.h" @implementation Settings @synthesize settings; -(NSString *)dataFilePath // Return path for settingfile, including filename { NSArray *paths = NSSearchPathForDirectoriesInDomains(NSDocumentDirectory, NSUserDomainMask, YES); NSString *documentsDirectory = [paths objectAtIndex:0]; return [documentsDirectory stringByAppendingPathComponent:kUserSettingsFileName]; } -(NSMutableArray *)getParameters // Return settings from disk after checking if file exist (if not create with default values) { NSString *filePath = [self dataFilePath]; if ([[NSFileManager defaultManager] fileExistsAtPath:filePath]) // Getting data from file { settings = [[NSMutableArray alloc] initWithContentsOfFile:filePath]; } else // Creating default settings { settings = [[NSMutableArray alloc] initWithObjects: [NSNumber numberWithInteger:50], [NSNumber numberWithInteger:50], nil]; [settings writeToFile:[self dataFilePath] atomically:YES]; } return settings; } ----- Below is my other class from where I call my Settings class ----- // Get settings from file Settings *aSetting = [[Settings alloc] init]; mySettings = [aSetting getParameters]; [aSetting release];

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  • How to use most of memory available on MySQL

    - by Zilvinas
    I've got a MySQL server which has both InnoDB and MyISAM tables. InnoDB tablespace is quite small under 4 GB. MyISAM is big ~250 GB in total of which 50 GB is for indexes. Our server has 32 GB of RAM but it usually uses only ~8GB. Our key_buffer_size is only 2GB. But our key cache hit ratio is ~95%. I find it hard to believe.. Here's our key statistics: | Key_blocks_not_flushed | 1868 | | Key_blocks_unused | 109806 | | Key_blocks_used | 1714736 | | Key_read_requests | 19224818713 | | Key_reads | 60742294 | | Key_write_requests | 1607946768 | | Key_writes | 64788819 | key_cache_block_size is default at 1024. We have 52 GB's of index data and 2GB key cache is enough to get a 95% hit ratio. Is that possible? On the other side data set is 200GB and since MyISAM uses OS (Centos) caching I would expect it to use a lot more memory to cache accessed myisam data. But at this stage I see that key_buffer is completely used, our buffer pool size for innodb is 4gb and is also completely used that adds up to 6GB. Which means data is cached using just 1 GB? My question is how could I check where all the free memory could be used? How could I check if MyISAM hits OS cache for data reads instead of disk?

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  • where is memory gone (no, not buffers or cache)

    - by Marki
    can anyone tell me where the memory is gone: (no, this time neither buffers nor cache) # free total used free shared buffers cached Mem: 3928200 3868560 59640 0 2888 92924 -/+ buffers/cache: 3772748 155452 Swap: 4192956 226352 3966604 top, sorted by memory, descending: top - 13:42:06 up 1 day, 3:47, 2 users, load average: 0.08, 0.12, 0.36 Tasks: 228 total, 1 running, 227 sleeping, 0 stopped, 0 zombie Cpu0 : 2.0%us, 4.0%sy, 0.0%ni, 90.1%id, 0.0%wa, 0.0%hi, 4.0%si, 0.0%st Cpu1 : 0.0%us, 0.0%sy, 0.0%ni, 0.0%id,100.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 3928200k total, 3868020k used, 60180k free, 2896k buffers Swap: 4192956k total, 226048k used, 3966908k free, 82068k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 3863 root 20 0 902m 199m 3296 S 7 5.2 99:08.77 ndsd 21906 root 20 0 138m 9076 2988 S 0 0.2 0:00.02 sfcbd 2332 root 20 0 126m 4660 1332 S 0 0.1 0:17.72 mono 4243 wwwrun 20 0 683m 4468 668 S 0 0.1 0:07.38 java 2994 root 20 0 202m 2288 1660 S 0 0.1 6:10.02 httpstkd 4338 root 20 0 184m 2240 1112 S 0 0.1 0:00.52 namcd 21898 root 20 0 32368 1832 1256 R 1 0.0 0:00.08 top In fact, some time ago oom kicked in and crashed the system (kernel panic), and I'm afraid we're again not far from that point.... UPDATE # cat /proc/meminfo MemTotal: 3928200 kB MemFree: 51336 kB Buffers: 2964 kB Cached: 72876 kB SwapCached: 29128 kB Active: 233440 kB Inactive: 88040 kB Active(anon): 188920 kB Inactive(anon): 56752 kB Active(file): 44520 kB Inactive(file): 31288 kB Unevictable: 0 kB Mlocked: 0 kB SwapTotal: 4192956 kB SwapFree: 3966824 kB Dirty: 32 kB Writeback: 0 kB AnonPages: 225112 kB Mapped: 11356 kB Shmem: 32 kB Slab: 1624080 kB SReclaimable: 13740 kB SUnreclaim: 1610340 kB KernelStack: 4176 kB PageTables: 10500 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 6157056 kB Committed_AS: 2397684 kB VmallocTotal: 34359738367 kB VmallocUsed: 441372 kB VmallocChunk: 34359246755 kB HardwareCorrupted: 0 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 10240 kB DirectMap2M: 4184064 kB slabtop Active / Total Objects (% used) : 9041019 / 9207548 (98.2%) Active / Total Slabs (% used) : 401132 / 401156 (100.0%) Active / Total Caches (% used) : 91 / 159 (57.2%) Active / Total Size (% used) : 1491537.88K / 1519791.56K (98.1%) Minimum / Average / Maximum Object : 0.02K / 0.17K / 4096.00K OBJS ACTIVE USE OBJ SIZE SLABS OBJ/SLAB CACHE SIZE NAME 4240470 4240319 99% 0.12K 141349 30 565396K pid 2245140 2219675 98% 0.25K 149676 15 598704K size-256 2238090 2210087 98% 0.12K 74603 30 298412K size-128 ...

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  • Apache httpd processes and PHP out of memory

    - by Ofri
    I have a VPS running apache-php-mysql on centos and a single drupal website installed. The VPS has 256MB of RAM (could be the root cause of all my problems... maybe I just need more). Whenever I try to open my website from multiple browser tabs (about 8... not 800) all at once, apache crashes! I have this on the log: [Wed Oct 24 11:26:31 2012] [error] [client xxx] PHP Fatal error: Out of memory (allocated 28049408) (tried to allocate 201335 bytes) in xxx on line 2139, referer: xxx I have read many many posts here, but I think there is something fundamental that I'm missing - If I understand correctly some php script tried to allocate 200K after allocating 28MB, and fails to do so. First question is: should this cause the apache to crash??? Next, I tried to look at 'top' command while I do my little test. Indeed I see 7 httpd processes, each reserving about 30MB - which explains why my RAM runs out. How do I prevent apache from creating new processes until it's out of memory? I tried configuring /etc/httpd/conf/httpd.conf like this: <IfModule prefork.c> StartServers 1 MinSpareServers 1 MaxSpareServers 1 ServerLimit 1 MaxClients 1 MaxRequestsPerChild 100 </IfModule> But got the same exact result! What am I missing? Thanks a lot!

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  • Updated my WAMP Server and MySQL is eating up 580mB of memory

    - by Jon
    I updated my dev-box's WAMPSERVER, and along with updating PHP and Apache, MySQL updated to '5.6.12'. After doing that, I copied the data folder from my old (5.1.36) install to the new one and now MySQL takes up 580mB which is way too much, since I'm the only person using it (Locally) and there are only 20 or so databases on it, none of which have 'memory' tables. How can I get this down to a decent amount? My my.ini: # For advice on how to change settings please see # http://dev.mysql.com/doc/refman/5.6/en/server-configuration-defaults.html # *** DO NOT EDIT THIS FILE. It's a template which will be copied to the # *** default location during install, and will be replaced if you # *** upgrade to a newer version of MySQL. [mysqld] # Remove leading # and set to the amount of RAM for the most important data # cache in MySQL. Start at 70% of total RAM for dedicated server, else 10%. # innodb_buffer_pool_size = 128M # Remove leading # to turn on a very important data integrity option: logging # changes to the binary log between backups. # log_bin # These are commonly set, remove the # and set as required. # basedir = ..... # datadir = ..... # port = ..... # server_id = ..... # Remove leading # to set options mainly useful for reporting servers. # The server defaults are faster for transactions and fast SELECTs. # Adjust sizes as needed, experiment to find the optimal values. # join_buffer_size = 128M # sort_buffer_size = 2M # read_rnd_buffer_size = 2M sql_mode=NO_ENGINE_SUBSTITUTION,STRICT_TRANS_TABLES Database info: Storage Engine Data Size Index Size Total Size InnoDB 48.00 KB 0.00 B 48.00 KB MEMORY 0.00 B 0.00 B 0.00 B MyISAM 163.64 MB 122.49 MB 286.13 MB Total 163.69 MB 122.49 MB 286.18 MB

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  • Memory overcommitment on VmWare ESXi 5.0

    - by Tibor
    I would like to understand better the possibilities of VmWare ESXi memory overcommitment. I've read this paper from VmWare, so I am familiar with general concepts, such as hypervisor swapping, memory balooning and page sharing. It seems that a combination of these techniques allows for quite a large degree of overcommitment. However, I am not sure. I am deploying a virtual test lab comprising of 4 identical sets of virtual servers and workstations and a couple of virtual router instances. Overall, I expect to be running around 20 virtual machines with Windows XP, Windows 7 and Ubuntu for workstation hosts as well as CentOS and Windows 2008 Server instances for servers. The problem is, however, that the host machine only has 12GB of RAM and I don't have an option to stuff in some more. I would like to know what is the best option to configure hosts in order to achieve reasonable performance within the constrains. I have these two options: Allocate as little as possible of RAM to each virtual machine. Allocate an extraordinary amount (such as 4 GB per instance) and let the baloon driver do the rest. Something else? Which would work better? Machines will mostly be idle, so I don't have any major performance expectations, but they should run reasonably smoothly nevertheless.

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  • windows 2008 r2 iis worker proccess memory usage increase

    - by nLL
    I have this web site written in c#. around 400-500 users online at any time. it was on windows 2008 32 bit machine before and never ever locked/slowed down due to increased memory consumption up until i upgraded it's server to win 2008 r2 64 bit. Old server had only 4 gig ram and quad core cpu at 2ghz. site was working just fine. since i've upgraded the server i noticed (2 times with in 10 days) it started to eat ram. last night it went up to 4 gb ram. with ram increase response slows down quite a lot. recycling app pool doesn't help. I have to restart it's worker process to recover. i've noticed this usually happens if there are continuous errors. as i didn't change anything in the code am i safe to assume it is not related to memory leak in the code? did anyone came across something like that? same thing happens if i create continuous errors with classic asp. thanks

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  • 4GB Memory Upgrade for Acer Aspire 5102WLMi

    - by Richard Slater
    I have bought a 4GB memory upgrade (2x 2GB PC2-5300 SODIMM) for my Acer Aspire 5102WLMi (Aspire 5100 Series) laptop, I installed the two memory modules correctly however with 4GB installed the laptop refuses to POST. I have tried the following: Tried both 2GB SODIMMs without the other (Worked Fine) Tried the original 512MB SODIMMs (Worked Fine) Tried with original 512MB SODIMM and new 2GB SODIMM (Worked Fine) Tried swapping over the 2GB SODIMs (Didn't Boot) Left the computer for 10 minutes with both 2GB SODIMMs installed (Didn't Boot) Checked latest BIOS installed (No Change) The Crucial website said that the laptop supported 4GB of RAM as do several other sites through found through Google, up until now I was fairly confident this would work. Couple of questions that would be good to have answered: Question: Has anyone got an Acer Aspire 5100 Series running with 4GB RAM? Answer: Yes, I have now got one working with 3.75GB Usable, the rest is occupied utilized by the Graphics Card. Question: Any tips on getting this to work; is there a CMOS reset switch? Answer: Yes there is, if both SODIMMs are removed two very small interlocking PCB tracks are revealed. If these are shorted together with a screwdriver the BIOS will be reset. Thanks.

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  • Allocating More Than 4 GB Of Memory

    - by TPatti
    I am facing an issue with memory allocation. I have: Host OS: Microsoft Windows XP - Professional x64 Edition - Version 2003 - Service Pack 2. Host Physical Memory: 8 GB Guest OS: Red Hat Enterprise Linux WS release 4 (Nahant Update 5). I am not sure if it is 32 or 64 bits. The lsb_release -a command says that argument LSB Version: core-3.0-ia32, so I guess that would be 32 bits... VMware Player Version: 2.5.2 build-156735 I would like that VMware Player could allocate more that 4 GB, but when I go to the setting, it only lists 4 GB. If I choose the "About" option, it actually says that I have 8 GB installed in the host machine. This VMware image created by someone else and provided to me, apparently done with VMware Workstation 5. Why can't I allocate 8 GB? Where is the problem? In the WMware Player Version, Guest OS or Host OS? How can I solve this? I understand that for this version of player there isn't one version for 32 and another for 64 bits.

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  • iPhone: Leak with UIWebView loading Office documents. Any ideas how to avoid it?

    - by Thomas Tempelmann
    While there are already quite a few posts about leaks around UIWebView, mine is a bit more special, I believe, and thus deserves its own post here. I see a reproducible large leak every time I load a Office document such as a Word or Excel file. For instance, every time I display a 180KB .doc file, I get a 100KB leak. And that happens with both the simulator and an actual device, running OS 3.1.3. The leak is not visible with the Leaks instrument but only by looking at the malloc instances via the ObjectAlloc instrument. Here's a picture from the instruments trace: I've also made a demo project, UIWebView-Leak.zip, so you can verify this yourself. To see the leak, use the ObjectAlloc instrument, switch to the view where you see individual allocation objects, and sort by size so that you see the large ones in a group, just like in my picture above. Then view a Office document a few times and find the Malloc objects that keep staying "Live" even after the actual UIWebView has been freed. Is this a known bug? Or is there any way I can avoid these leaks? I.e, have you successfully shown Office documents on an iPhone withing getting such leaks? Note: I've reported this as a bug to Apple now, too (ID 7950594) I am still waiting for someone (including Apple) to confirm this as a true leak or show why it isn't (i.e. that I do something wrong or make wrong assumptions)

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  • Does a CPU assigns a value atomically to memory?

    - by Poni
    Hi! A quick question I've been wondering about for some time; Does the CPU assign values atomically, or, is it bit by bit (say for example a 32bit integer). If it's bit by bit, could another thread accessing this exact location get a "part" of the to-be-assigned value? Think of this: I have two threads and one shared "unsigned int" variable (call it "g_uiVal"). Both threads loop. On is printing "g_uiVal" with printf("%u\n", g_uiVal). The second just increase this number. Will the printing thread ever print something that is totally not or part of "g_uiVal"'s value? In code: unsigned int g_uiVal; void thread_writer() { g_uiVal++; } void thread_reader() { while(1) printf("%u\n", g_uiVal); }

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  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Is special memory required for a MacBook Pro ?

    - by user38900
    I have a MacBook Pro (MacBookPro5,2 / 2.8 GHz) with 4 GB of ram (2x2GB). I'm looking to upgrade to 8GB. The memory in it now is DDR3 PC3-8500 1067. Checking out prices for 4 GB sticks of PC3-8500 there is about $100 difference for "apple certified" ram. Will any DDR3 PC3-8500 module work or is there really a difference?

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