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  • Nginx + uWSGI + Django performance stuck on 100rq/s

    - by dancio
    I have configured Nginx with uWSGI and Django on CentOS 6 x64 (3.06GHz i3 540, 4GB), which should easily handle 2500 rq/s but when I run ab test ( ab -n 1000 -c 100 ) performance stops at 92 - 100 rq/s. Nginx: user nginx; worker_processes 2; events { worker_connections 2048; use epoll; } uWSGI: Emperor /usr/sbin/uwsgi --master --no-orphans --pythonpath /var/python --emperor /var/python/*/uwsgi.ini [uwsgi] socket = 127.0.0.2:3031 master = true processes = 5 env = DJANGO_SETTINGS_MODULE=x.settings env = HTTPS=on module = django.core.handlers.wsgi:WSGIHandler() disable-logging = true catch-exceptions = false post-buffering = 8192 harakiri = 30 harakiri-verbose = true vacuum = true listen = 500 optimize = 2 sysclt changes: # Increase TCP max buffer size setable using setsockopt() net.ipv4.tcp_rmem = 4096 87380 8388608 net.ipv4.tcp_wmem = 4096 87380 8388608 net.core.rmem_max = 8388608 net.core.wmem_max = 8388608 net.core.netdev_max_backlog = 5000 net.ipv4.tcp_max_syn_backlog = 5000 net.ipv4.tcp_window_scaling = 1 net.core.somaxconn = 2048 # Avoid a smurf attack net.ipv4.icmp_echo_ignore_broadcasts = 1 # Optimization for port usefor LBs # Increase system file descriptor limit fs.file-max = 65535 I did sysctl -p to enable changes. Idle server info: top - 13:34:58 up 102 days, 18:35, 1 user, load average: 0.00, 0.00, 0.00 Tasks: 118 total, 1 running, 117 sleeping, 0 stopped, 0 zombie Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 3983068k total, 2125088k used, 1857980k free, 262528k buffers Swap: 2104504k total, 0k used, 2104504k free, 606996k cached free -m total used free shared buffers cached Mem: 3889 2075 1814 0 256 592 -/+ buffers/cache: 1226 2663 Swap: 2055 0 2055 **During the test:** top - 13:45:21 up 102 days, 18:46, 1 user, load average: 3.73, 1.51, 0.58 Tasks: 122 total, 8 running, 114 sleeping, 0 stopped, 0 zombie Cpu(s): 93.5%us, 5.2%sy, 0.0%ni, 0.2%id, 0.0%wa, 0.1%hi, 1.1%si, 0.0%st Mem: 3983068k total, 2127564k used, 1855504k free, 262580k buffers Swap: 2104504k total, 0k used, 2104504k free, 608760k cached free -m total used free shared buffers cached Mem: 3889 2125 1763 0 256 595 -/+ buffers/cache: 1274 2615 Swap: 2055 0 2055 iotop 30141 be/4 nginx 0.00 B/s 7.78 K/s 0.00 % 0.00 % nginx: wo~er process Where is the bottleneck ? Or what am I doing wrong ?

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  • Basic multicast network performance problems

    - by davedavedave
    I've been using mpong from 29west's mtools package to get some basic idea of multicast latency across various Cisco switches: 1Gb 2960G, 10Gb 4900M and 10Gb Nexus N5548P. The 1Gb is just for comparison. I have the following results for ~400 runs of mpong on each switch (sending 65536 "ping"-like messages to a receiver which then sends back -- all over multicast). Numbers are latencies measured in microseconds. Switch Average StdDev Min Max 2960 (1Gb) 109.68463 0.092816 109.4328 109.9464 4900M (10Gb) 705.52359 1.607976 703.7693 722.1514 NX 5548(10Gb) 58.563774 0.328242 57.77603 59.32207 The result for 4900M is very surprising. I've tried unicast ping and I see the 4900 has ~10us higher latency than the N5548P (average 73us vs 64us). Iperf (with no attempt to tune it) shows both 10Gb switches give me 9.4Gbps line speed. The two machines are connected to the same switch and we're not doing any multicast routing. OS is RHEL 6. 10Gb NICs are HP 10GbE PCI-E G2 Dual-port NICs (I believe they are rebranded Mellanox cards). The 4900 switch is used in a project with tight access control so I'm waiting for approval before I can access it and check the config. The other two I have full access to configure. I've looked at the Cisco document[2] detailing differences between NX-OS and IOS w.r.t multicast so I've got some ideas to try out but this isn't an area where I have much expertise. Does anyone have any idea what I should be looking at once I get access to the switch? [1] http://docwiki.cisco.com/wiki/Cisco_NX-OS/IOS_Multicast_Comparison

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  • Different versions of iperf for windows give totally different results

    - by Albert Mata
    Measuring TCP output from a Windows client to Solaris server: WXP SP3 with iperf 1.7.0 -- returns an average around 90Mbit Same client, same server but iperf 2.0.5 for windows -- returns an average of 8.5 Mbit Similar discrepancies have been observed connecting to other servers (W2008, W2003) It's difficult to get to some conclusions when different versions of the same tool provide vastly different results. Example below: C:\tempiperf -v (from iperf.fr) iperf version 2.0.5 (08 Jul 2010) pthreads C:\tempiperf -c solaris10 Client connecting to solaris10, TCP port 5001 TCP window size: 64.0 KByte (default) [ 3] local 10.172.181.159 port 2124 connected with 10.172.180.209 port 5001 [ ID] Interval Transfer Bandwidth [ 3] 0.0-10.2 sec 10.6 MBytes 8.74 Mbits/sec Abysmal perfomance, but now I test from the same host (Windows XP SP3 32bit and 100Mbit) to the same server (Solaris 10/sparc 64bit and 1Gbit running iperf 2.0.5 with default window of 48k) with the old iperf C:\temp1iperf -v iperf version 1.7.0 (13 Mar 2003) win32 threads C:\temp1iperf.exe -c solaris10 -w64k Client connecting to solaris10, TCP port 5001 TCP window size: 64.0 KByte [1208] local 10.172.181.159 port 2128 connected with 10.172.180.209 port 5001 [ ID] Interval Transfer Bandwidth [1208] 0.0-10.0 sec 112 MBytes 94.0 Mbits/sec So one iperf with a 64k window says 8.75Mbit and the old iperf with the same window size says 94.0Mbit. These results are constant through repeated tests. From my testing launching iperf(old) with window size "x" and iperf(new) with window size "x" instead of producing the same or very close results produce totally different results. The only difference I see is the old compiled as win32 threads vs. pthreads but parallelism (-P 10) appears to work in both. Anyone has a clue or can recommend a tool that gives results I can trust?? EDIT: Looking at traces from (old) iperf it sets the TCP Window Scale flag to 3 in the SYN packet, when I run the (new) iperf this is set to 0 in the initial packet. A quick analysis of the window size through the exchange shows the (old) iperf moving back and forth but mostly at 32k while the (new) iperf mostly keeps at 64k. Maybe it will help somebody to connect the dots.

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  • Windows 7 machine, can't connect remotely until after ping

    - by rjohnston
    I have a Windows 7 (Home Premium) machine that doubles as a media centre and subversion server. There's a couple of problems with this setup, when connecting to the server from an XP (SP3) machine: Firstly, the machine won't respond to it's machine name until after it's IP address has been pinged. Here's an example: Microsoft Windows XP [Version 5.1.2600] (C) Copyright 1985-2001 Microsoft Corp. C:\Documents and Settings\Rob>ping damascus Ping request could not find host damascus. Please check the name and try again. C:\Documents and Settings\Rob>ping 192.168.1.17 Pinging 192.168.1.17 with 32 bytes of data: Reply from 192.168.1.17: bytes=32 time=2ms TTL=128 ... Ping statistics for 192.168.1.17: Packets: Sent = 4, Received = 4, Lost = 0 (0% loss), Approximate round trip times in milli-seconds: Minimum = 1ms, Maximum = 2ms, Average = 1ms C:\Documents and Settings\Rob>ping damascus Pinging damascus [192.168.1.17] with 32 bytes of data: Reply from 192.168.1.17: bytes=32 time<1ms TTL=128 .... Ping statistics for 192.168.1.17: Packets: Sent = 4, Received = 4, Lost = 0 (0% loss), Approximate round trip times in milli-seconds: Minimum = 0ms, Maximum = 1ms, Average = 0ms C:\Documents and Settings\Rob> Likewise, subversion commands with either the machine name or IP address will fail until the machine's IP address is pinged. Occasionally, the machine won't respond to pings on it's IP address, it'll just come back with "Request timed out". The svn server is VisualSVN, if that helps... Any ideas?

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  • Is basing storage requirements based on IOPS sufficient?

    - by Boden
    The current system in question is running SBS 2003, and is going to be migrated on new hardware to SBS 2008. Currently I'm seeing on average 200-300 disk transfers per second total across all the arrays in the system. The array seeing the bulk of activity is a 6 disk 7200RPM RAID 6 and it struggles to keep up during high traffic times (idle time often only 10-20%; response times peaking 20-50+ ms). Based on some rough calculations this makes sense (avg ~245 IOPS on this array at 70/30 read to write ratio). I'm considering using a much simpler disk configuration using a single RAID 10 array of 10K disks. Using the same parameters for my calculations above, I'm getting 583 average random IOPS / sec. Granted SBS 2008 is not the same beast as 2003, but I'd like to make the assumption that it'll be similar in terms of disk performance, if not better (Exchange 2007 is easier on the disk and there's no ISA server). Am I correct in believing that the proposed system will be sufficient in terms of performance, or am I missing something? I've read so much about recommended disk configurations for various products like Exchange, and they often mention things like dedicating spindles to logs, etc. I understand the reasoning behind this, but if I've got more than enough random I/O overhead, does it really matter? I've always at the very least had separate spindles for the OS, but I could really reduce cost and complexity if I just had a single, good performing array. So as not to make you guys do my job for me, the generic version of this question is: if I have a projected IOPS figure for a new system, is it sufficient to use this value alone to spec the storage, ignoring "best practice" configurations? (given similar technology, not going from DAS to SAN or anything)

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  • Slow performance on VMWare Linux server after Tomcat install

    - by Loftx
    We have a VMWare ESXi 4.1 server hosting a number of Linux and Windows guests. Recently a new Linux guest was added to this server and seemed to be performing well. Tomcat and some other applications on this server were then installed which seem to have caused the server to run really slowly without any obvious resource issues. Slow performance include: The time taken to bring up the password prompt over ssh takes a few seconds when it was previously instantaneous. The time taken to unzip a zip file which was previously a few seconds now takes around 30 seconds The time taken to compile vmware tools has increased by similar factors Both the VMWare console and monitoring commands don't report any issues with high CPU or memory usage but something is obviously slowing the server down somehow. Does anyone have any ideas what may be causing this issue and how it can be resolved? Thanks, Tom Edit As per your questions I’ve looked at some of the performance indicators on both the VM host and VM guest indicated. Firstly I tried reserving the full amount of memory (3gb) for this VM – no other machines on this server have any memory reservation. The swap in rate and swap out rate for the VM host and guest are now both zero. Balloon memory on the guest is zero and on the host is 3.5gb (total memory on the host is 12gb) The swap rate for the guest is also zero. Swap used by the host is 200mb on average. Compression and decompression rates for the host and guest are zero. Command aborts for the host are zero. Read latency is very low – maximum 10ms average 0.8ms. Write latency is higher – a few spikes to 170ms but mostly around 25ms – is this bad? Queue command latency is zero . Physical disk read latency averages 5ms but often 10ms Physical disk write latency averages 15ms but is often 20ms I hope this helps - let me know if you need any more information.

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  • How flexible is the 'indirect' function?

    - by Chuck
    My curiosity pushes me to ask this question. If I were to have a series of functions that referenced a different column in a worksheet but all ended on the same row of data is there a way to point the 'row' part of a cell reference to a blank cell and use it has a variable to show the results of the functions up to a desired row simultaneously? Example: =Average('worksheet 1'.$A$1:'worksheet 1'.$A100) =Max('worksheet 1'.$B$1:'worksheet 1'.$B100) =Min('worksheet 1'.$C$1:'worksheet 1'.$C100) =Sum('worksheet 1'.$D$1:'worksheet 1'.$D100) Pseudo formulas... =Average('worksheet 1'.$A$1:'worksheet 1'.$A*('worksheet 2'.$A$1)*) =Max('worksheet 1'.$B$1:'worksheet 1'.$B*('worksheet 2'.$A$1)*) =Min('worksheet 1'.$C$1:'worksheet 1'.$C*('worksheet 2'.$A$1)*) =Sum('worksheet 1'.$D$1:'worksheet 1'.$D*('worksheet 2'.$A$1)*) Where 'worksheet 2'.$A$1 would only contain a number corresponding to a row in 'worksheet 1'. After stumbling upon and playing with the indirect() function I have only been able to replace the entire cell reference (Column and Row) with any success. The formula so far =SUM('worksheet 1'.C3:INDIRECT(A1)) Where A1 is on 'worksheet 2' and contains a full cell reference pointing to 'worksheet 1'. Any pointers?

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  • Representing server state with a metric

    - by Sal
    I'm using Microsoft's Performance Monitor to dump logs of RAM, CPU, network, and disk usage from multiple servers. I'd like to get a single metric that captures the state of a given variable to a good extent. For instance, disk usage is pretty stable, so if I take a single reading that says I have 50% remaining disk space, that reading will give me an accurate measure for the day. (The servers aren't doing heavy IO writing.) However, the tricky part here is monitoring CPU and network usage. The logs currently dump the % CPU usage every ten seconds. If I take a straight average of the numbers, it may not represent reality, as % CPU will be much lower during the night than day. (We host websites that sell appliance items.) I'd like to get an average over a span during peak hours (about 5 hours in the day) and present a daily peak hour metric. Of course, there are most likely some readings that will come in as overly spiked (if multiple users pinged the server at once) or no use (a momentary idle state). Is there a standard distribution/test industries use in these situation?

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  • SSD causing 100% CPU usage in Apache/PHP

    - by Tim Reynolds
    I wanted to increase the performance on my development laptop so I added an Intel 320 Series SSD as my primary drive. Everything is amazingly fast, as expected, except Apache/PHP. I develop Magento by using an Ubuntu 10.10 virtual machine. Information: Host OS: Win 7 Professional 64bit Guest OS: Ubuntu 10.10 32bit Processor: i7 Chipset QM55 SSD: Intel 320 Series 160gb 30% full HDD: Hitachi 320gb 50% full (in side bay using an adapter) Laptop: Lenovo T510 Using: Shared folders Apache Version: 2.2.16 PHP Version: 5.3.3-1 APC Version: 3.1.3p1 APC Memory: 128M Using tmpfs for cache, log, session directories in Magento In the VM running on the SSD (VM files and source files are on the same drive) loading a product page in the Admin takes on average 26.2 seconds and uses 100% CPU for nearly the entire time. In the VM running on the old HDD loading the same page takes on average 4.4 seconds. It mostly uses around 40-50% of the CPU while rendering the page. I have read this post: Performance issues when using SSD for a developer notebook (WAMP/LAMP stack)? It says to change some settings in the bios. I have turned any and all power management features off in the bios. I can't for the life of me understand why this would be happening.

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  • On what should i not be pennywise buying a machine for SqlServer 2008?

    - by Michel
    Hi, i'm going to do a project for a client and i'll be hosting the database server myself. Normally it would be on my dev machine, but there will also be data pushed into it during developing and testing, so i would like to setup a dedicated test sql server. But, as you might guess, i can't afford to go to Dell and buy one mega 16 core 16 GIG 10 TB raid 5 machine (wow, that sounds cool) So i have to save the money somewhere... the hardware only has to live for a year (longer is nice of course), and the sql server won't be hit too hard: i guess the average server will only see it as a cough once in a while. But i do want the machine to be a bit performant: if it does get some data, it must be a bit responsive. So my question is were can i leave out the expensive parts: is 2 GB enough, or must i take 4GB, is an average processor enough or should it be a top of the bill? Is Sql server a large resource user or is a simple desktop pc good enough? It wil run on win2008 by the way.

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  • ZFS with L2ARC (SSD) slower for random seeks than without L2ARC

    - by Florian Kruse
    I am currently testing ZFS (Opensolaris 2009.06) in an older fileserver to evaluate its use for our needs. Our current setup is as follows: Dual core (2,4 GHz) with 4 GB RAM 3x SATA controller with 11 HDDs (250 GB) and one SSD (OCZ Vertex 2 100 GB) We want to evaluate the use of a L2ARC, so the current ZPOOL is: $ zpool status pool: tank state: ONLINE scrub: none requested config: NAME STATE READ WRITE CKSUM afstank ONLINE 0 0 0 raidz1 ONLINE 0 0 0 c11t0d0 ONLINE 0 0 0 c11t1d0 ONLINE 0 0 0 c11t2d0 ONLINE 0 0 0 c11t3d0 ONLINE 0 0 0 raidz1 ONLINE 0 0 0 c13t0d0 ONLINE 0 0 0 c13t1d0 ONLINE 0 0 0 c13t2d0 ONLINE 0 0 0 c13t3d0 ONLINE 0 0 0 cache c14t3d0 ONLINE 0 0 0 where c14t3d0 is the SSD (of course). We run IO tests with bonnie++ 1.03d, size is set to 200 GB (-s 200g) so that the test sample will never be completely in ARC/L2ARC. The results without SSD are (average values over several runs which show no differences) write_chr write_blk rewrite read_chr read_blk random seeks 101.998 kB/s 214.258 kB/s 96.673 kB/s 77.702 kB/s 254.695 kB/s 900 /s With SSD it becomes interesting. My assumption was that the results should be in worst case at least the same. While write/read/rewrite rates are not different, the random seek rate differs significantly between individual bonnie++ runs (between 188 /s and 1333 /s so far), average is 548 +- 200 /s, so below the value w/o SSD. So, my questions are mainly: Why do the random seek rates differ so much? If the seeks are really random, they should not differ much (my assumption). So, even if the SSD is impairing the performance it should be the same in each bonnie++ run. Why is the random seek performance worse in most of the bonnie++ runs? I would assume that some part of the bonnie++ data is in the L2ARC and random seeks on this data performs better while random seeks on other data just performs similarly like before.

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  • MySQL query, 2 similar servers, 2 minute difference in execution times

    - by mr12086
    I had a similar question on stack overflow, but it seems to be more server/mysql setup related than coding. The queries below all execute instantly on our development server where as they can take upto 2 minutes 20 seconds. The query execution time seems to be affected by home ambiguous the LIKE string's are. If they closely match a country that has few matches it will take less time, and if you use something like 'ge' for germany - it will take longer to execute. But this doesn't always work out like that, at times its quite erratic. Sending data appears to be the culprit but why and what does that mean. Also memory on production looks to be quite low (free memory)? Production: Intel Quad Xeon E3-1220 3.1GHz 4GB DDR3 2x 1TB SATA in RAID1 Network speed 100Mb Ubuntu Development Intel Core i3-2100, 2C/4T, 3.10GHz 500 GB SATA - No RAID 4GB DDR3 UPDATE 2 : mysqltuner output: [prod] -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.61-0ubuntu0.10.04.1 [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 103M (Tables: 180) [--] Data in InnoDB tables: 491M (Tables: 19) [!!] Total fragmented tables: 38 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 77d 4h 6m 1s (53M q [7.968 qps], 14M conn, TX: 87B, RX: 12B) [--] Reads / Writes: 98% / 2% [--] Total buffers: 58.0M global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 463.8M (11% of installed RAM) [OK] Slow queries: 0% (12K/53M) [OK] Highest usage of available connections: 22% (34/151) [OK] Key buffer size / total MyISAM indexes: 16.0M/10.6M [OK] Key buffer hit rate: 98.7% (162M cached / 2M reads) [OK] Query cache efficiency: 20.7% (7M cached / 36M selects) [!!] Query cache prunes per day: 3934 [OK] Sorts requiring temporary tables: 1% (3K temp sorts / 230K sorts) [!!] Joins performed without indexes: 71068 [OK] Temporary tables created on disk: 24% (3M on disk / 13M total) [OK] Thread cache hit rate: 99% (690 created / 14M connections) [!!] Table cache hit rate: 0% (64 open / 85M opened) [OK] Open file limit used: 12% (128/1K) [OK] Table locks acquired immediately: 99% (16M immediate / 16M locks) [!!] InnoDB data size / buffer pool: 491.9M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Variables to adjust: query_cache_size (> 16M) join_buffer_size (> 128.0K, or always use indexes with joins) table_cache (> 64) innodb_buffer_pool_size (>= 491M) [dev] -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.62-0ubuntu0.11.10.1 [!!] Switch to 64-bit OS - MySQL cannot currently use all of your RAM -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 185M (Tables: 632) [--] Data in InnoDB tables: 967M (Tables: 38) [!!] Total fragmented tables: 73 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 1d 2h 26m 9s (5K q [0.058 qps], 1K conn, TX: 4M, RX: 1M) [--] Reads / Writes: 99% / 1% [--] Total buffers: 58.0M global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 463.8M (11% of installed RAM) [OK] Slow queries: 0% (0/5K) [OK] Highest usage of available connections: 1% (2/151) [OK] Key buffer size / total MyISAM indexes: 16.0M/18.6M [OK] Key buffer hit rate: 99.9% (60K cached / 36 reads) [OK] Query cache efficiency: 44.5% (1K cached / 2K selects) [OK] Query cache prunes per day: 0 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 44 sorts) [OK] Temporary tables created on disk: 24% (162 on disk / 666 total) [OK] Thread cache hit rate: 99% (2 created / 1K connections) [!!] Table cache hit rate: 1% (64 open / 4K opened) [OK] Open file limit used: 8% (88/1K) [OK] Table locks acquired immediately: 100% (1K immediate / 1K locks) [!!] InnoDB data size / buffer pool: 967.7M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Enable the slow query log to troubleshoot bad queries Increase table_cache gradually to avoid file descriptor limits Variables to adjust: table_cache (> 64) innodb_buffer_pool_size (>= 967M) UPDATE 1: When testing the queries listed here there is usually no more than one other query taking place, and usually none. Because production is actually handling apache requests that development gets very few of as it's only myself and 1 other who accesses it - could the 4GB of RAM be getting exhausted by using the single machine for both apache and mysql server? Production: sudo hdparm -tT /dev/sda /dev/sda: Timing cached reads: 24872 MB in 2.00 seconds = 12450.72 MB/sec Timing buffered disk reads: 368 MB in 3.00 seconds = 122.49 MB/sec sudo hdparm -tT /dev/sdb /dev/sdb: Timing cached reads: 24786 MB in 2.00 seconds = 12407.22 MB/sec Timing buffered disk reads: 350 MB in 3.00 seconds = 116.53 MB/sec Server version(mysql + ubuntu versions): 5.1.61-0ubuntu0.10.04.1 Development: sudo hdparm -tT /dev/sda /dev/sda: Timing cached reads: 10632 MB in 2.00 seconds = 5319.40 MB/sec Timing buffered disk reads: 400 MB in 3.01 seconds = 132.85 MB/sec Server version(mysql + ubuntu versions): 5.1.62-0ubuntu0.11.10.1 ORIGINAL DATA : This query is NOT the query in question but is related so ill post it. SELECT f.form_question_has_answer_id FROM form_question_has_answer f INNER JOIN project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id INNER JOIN company c ON p.project_company_has_user_company_id = c.company_id INNER JOIN project p2 ON p.project_company_has_user_project_id = p2.project_id INNER JOIN user u ON p.project_company_has_user_user_id = u.user_id INNER JOIN form f2 ON p.project_company_has_user_project_id = f2.form_project_id WHERE (f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174' And the explain plan for the above query is, run on both dev and production produce the same plan. +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ | 1 | SIMPLE | p2 | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index | | 1 | SIMPLE | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | const | 796 | Using where | | 1 | SIMPLE | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using index | | 1 | SIMPLE | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where | | 1 | SIMPLE | f2 | ref | form_project_id | form_project_id | 4 | const | 15 | Using where | | 1 | SIMPLE | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where | +----+-------------+-------+--------+----------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+-------------+ This query takes 2 minutes ~20 seconds to execute. The query that is ACTUALLY being run on the server is this one: SELECT COUNT(*) AS num_results FROM (SELECT f.form_question_has_answer_id FROM form_question_has_answer f INNER JOIN project_company_has_user p ON f.form_question_has_answer_user_id = p.project_company_has_user_user_id INNER JOIN company c ON p.project_company_has_user_company_id = c.company_id INNER JOIN project p2 ON p.project_company_has_user_project_id = p2.project_id INNER JOIN user u ON p.project_company_has_user_user_id = u.user_id INNER JOIN form f2 ON p.project_company_has_user_project_id = f2.form_project_id WHERE (f2.form_template_name = 'custom' AND p.project_company_has_user_garbage_collection = 0 AND p.project_company_has_user_project_id = '29') AND (LCASE(c.company_country) LIKE '%ge%' OR LCASE(c.company_country) LIKE '%abcde%') AND f.form_question_has_answer_form_id = '174' GROUP BY f.form_question_has_answer_id;) dctrn_count_query; With explain plans (again same on dev and production): +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ | 1 | PRIMARY | NULL | NULL | NULL | NULL | NULL | NULL | NULL | Select tables optimized away | | 2 | DERIVED | p2 | const | PRIMARY | PRIMARY | 4 | | 1 | Using index | | 2 | DERIVED | f | ref | form_question_has_answer_form_id,form_question_has_answer_user_id | form_question_has_answer_form_id | 4 | | 797 | Using where | | 2 | DERIVED | p | ref | project_company_has_user_unique_key,project_company_has_user_user_id,project_company_has_user_company_id,project_company_has_user_project_id,project_company_has_user_garbage_collection | project_company_has_user_user_id | 4 | new_klarents.f.form_question_has_answer_user_id | 1 | Using where | | 2 | DERIVED | f2 | ref | form_project_id | form_project_id | 4 | | 15 | Using where | | 2 | DERIVED | c | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_company_id | 1 | Using where | | 2 | DERIVED | u | eq_ref | PRIMARY | PRIMARY | 4 | new_klarents.p.project_company_has_user_user_id | 1 | Using where; Using index | +----+-------------+-------+--------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+----------------------------------+---------+----------------------------------------------------+------+------------------------------+ On the production server the information I have is as follows. Upon execution: +-------------+ | num_results | +-------------+ | 3 | +-------------+ 1 row in set (2 min 14.28 sec) Show profile: +--------------------------------+------------+ | Status | Duration | +--------------------------------+------------+ | starting | 0.000016 | | checking query cache for query | 0.000057 | | Opening tables | 0.004388 | | System lock | 0.000003 | | Table lock | 0.000036 | | init | 0.000030 | | optimizing | 0.000016 | | statistics | 0.000111 | | preparing | 0.000022 | | executing | 0.000004 | | Sorting result | 0.000002 | | Sending data | 136.213836 | | end | 0.000007 | | query end | 0.000002 | | freeing items | 0.004273 | | storing result in query cache | 0.000010 | | logging slow query | 0.000001 | | logging slow query | 0.000002 | | cleaning up | 0.000002 | +--------------------------------+------------+ On development the results are as follows. +-------------+ | num_results | +-------------+ | 3 | +-------------+ 1 row in set (0.08 sec) Again the profile for this query: +--------------------------------+----------+ | Status | Duration | +--------------------------------+----------+ | starting | 0.000022 | | checking query cache for query | 0.000148 | | Opening tables | 0.000025 | | System lock | 0.000008 | | Table lock | 0.000101 | | optimizing | 0.000035 | | statistics | 0.001019 | | preparing | 0.000047 | | executing | 0.000008 | | Sorting result | 0.000005 | | Sending data | 0.086565 | | init | 0.000015 | | optimizing | 0.000006 | | executing | 0.000020 | | end | 0.000004 | | query end | 0.000004 | | freeing items | 0.000028 | | storing result in query cache | 0.000005 | | removing tmp table | 0.000008 | | closing tables | 0.000008 | | logging slow query | 0.000002 | | cleaning up | 0.000005 | +--------------------------------+----------+ If i remove user and/or project innerjoins the query is reduced to 30s. Last bit of information I have: Mysqlserver and Apache are on the same box, there is only one box for production. Production output from top: before & after. top - 15:43:25 up 78 days, 12:11, 4 users, load average: 1.42, 0.99, 0.78 Tasks: 162 total, 2 running, 160 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 50.4%sy, 0.0%ni, 49.5%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3772580k used, 265288k free, 243704k buffers Swap: 3905528k total, 265384k used, 3640144k free, 1207944k cached top - 15:44:31 up 78 days, 12:13, 4 users, load average: 1.94, 1.23, 0.87 Tasks: 160 total, 2 running, 157 sleeping, 0 stopped, 1 zombie Cpu(s): 0.2%us, 50.6%sy, 0.0%ni, 49.3%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3834300k used, 203568k free, 243736k buffers Swap: 3905528k total, 265384k used, 3640144k free, 1207804k cached But this isn't a good representation of production's normal status so here is a grab of it from today outside of executing the queries. top - 11:04:58 up 79 days, 7:33, 4 users, load average: 0.39, 0.58, 0.76 Tasks: 156 total, 1 running, 155 sleeping, 0 stopped, 0 zombie Cpu(s): 3.3%us, 2.8%sy, 0.0%ni, 93.9%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4037868k total, 3676136k used, 361732k free, 271480k buffers Swap: 3905528k total, 268736k used, 3636792k free, 1063432k cached Development: This one doesn't change during or after. top - 15:47:07 up 110 days, 22:11, 7 users, load average: 0.17, 0.07, 0.06 Tasks: 210 total, 2 running, 208 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 0.2%sy, 0.0%ni, 99.7%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 4111972k total, 1821100k used, 2290872k free, 238860k buffers Swap: 4183036k total, 66472k used, 4116564k free, 921072k cached

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  • How important is dual-gigabit lan for a super user's home NAS?

    - by Andrew
    Long story short: I'm building my own home server based on Ubuntu with 4 drives in RAID 10. Its primary purpose will be NAS and backup. Would I be making a terrible mistake by building a NAS Server with a single Gigabit NIC? Long story long: I know the absolute max I can get out of a single Gigabit port is 125MB/s, and I want this NAS to be able to handle up to 6 computers accessing files simultaneously, with up to two of them streaming video. With Ubuntu NIC-bonding and the performance of RAID 10, I can theoretically double my throughput and achieve 250MB/s (ok, not really, but it would be faster). The drives have an average read throughput of 83.87MB/s according to Tom's Hardware. The unit itself will be based on the Chenbro ES34069-BK-180 case. With my current hardware choices, it'll have this motherboard with a Core i3 CPU and 8GB of RAM. Overkill, I know, but this server will be doing other things as well (like transcoding video). Unfortunately, the only Mini-ITX boards I can find with dual-gigabit and 6 SATA ports are Intel Atom-based, and I need more processing power than an Atom has to offer. I would love to find a board with 6 SATA ports and two Gigabit LAN ports that supports a Core i3 CPU. So far, my search has come up empty. Thus, my dilemma. Should I hold out for such a board, go with an Atom-based solution, or stick with my current single-gigabit configuration? I know there are consumer NAS units with just one gigabit interface (probably most of them), but I think I will demand a lot more from my server than the average home user. Any advice is appreciated. Thanks.

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  • Top cpu% analyis

    - by user111196
    I would like the know in what cpus % can be considered in save range and also load average? Which indication will give signal something is wrong with the server? top - 22:55:51 up 3 days, 6:39, 1 user, load average: 0.53, 0.43, 0.37 Tasks: 229 total, 2 running, 227 sleeping, 0 stopped, 0 zombie Cpu0 : 16.2%us, 0.7%sy, 0.0%ni, 82.8%id, 0.0%wa, 0.0%hi, 0.3%si, 0.0%st Cpu1 : 10.5%us, 0.7%sy, 0.0%ni, 88.5%id, 0.0%wa, 0.0%hi, 0.3%si, 0.0%st Cpu2 : 9.0%us, 0.0%sy, 0.0%ni, 91.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu3 : 0.3%us, 0.3%sy, 0.0%ni, 99.4%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu4 : 1.0%us, 0.0%sy, 0.0%ni, 99.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Cpu5 : 44.8%us, 2.6%sy, 0.0%ni, 37.0%id, 0.0%wa, 9.4%hi, 6.2%si, 0.0%st Cpu6 : 3.0%us, 0.0%sy, 0.0%ni, 96.7%id, 0.0%wa, 0.0%hi, 0.4%si, 0.0%st Cpu7 : 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 16468596k total, 2423908k used, 14044688k free, 200172k buffers

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  • 100% CPU load on Ubuntu 10.04.3 LTS 64bit

    - by deadtired
    I have 2 days since I am trying to fix this issue, with no success. The server is a mysql database server. Hardware: DELL Poweredge 1950, 2x Intel Xeon Quad Core E5345 @ 2.33GHz, 16 Gb mem, 2x 146Gb SAS (software RAID1) Software: Ubuntu 10.04.3 LTS, MySQL 5.1.41 Issue: while mysql is not used and runs with no database, everything seems alright. As soon as I install a database, it has the reason to bring all 8 cores in 100% with low memory consumption. So, you can imagine the load average goes high (I saw 212 load average for the first time). The server doesn't become unresponsive, but you can see it's slow while browsing the project installed. Additional info: the database used is not more than 24MB and it was moved from a server with less resources and a lot more larger databases. So it's not the database/project. my.cnf is not a reason also, as I used both default one and the one I use on the same distribution on another server.What is interesting is that mysql doesn't close any process and runs to the limit of the max_connections. Logs are quiet. Nothing there. I switched to this Ubuntu version after I suspected some problems in the newly Ubuntu 11.10 server. This one worked alright for an hour after I made a kernel upgrade to 3.0.1 (it was using the memory also) I tested disk speed and seems alright. Some more output on the running server: dstat -cndymlp -N total -D total 3: htop command: Idea? Did anyone meet the same problem? Any fix you can think of?

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  • Spreadsheet application that can handle big data OS X

    - by Peter
    I've been working with Excel for quite a while for some statistical analysis that I do regularly. The size of the data that I'm working with has gotten much larger as of late, however. The layout of the databases in question is quite simple, usually just three rows which includes a UNIX timestamp, and EST value, a proprietary numeric value and finally an average of the rows that have a timestamp +/- 1000 that row's timestamp (little AVERAGEIFS() formula). That formula and the EST conversion are the only formulas in the sheet. I'm beginning to work with files with 500,000+ rows. Running the average formula down the entire row takes forever. The end result is the production of print-worthy graphs. I'm looking for either a UNIX CL utility or separate spreadsheet/database application that can handle this amount of data without melting my CPU or making me wait an hour. Is there anything out there? TL;DR: Simple excel sheet with over half a million rows is getting too slow to work with. OS X alternatives?

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  • Microsoft Excel not graphing

    - by SmartLemon
    Im not sure if this is a math question or a su question. The experiment was relating the period of one "bounce" when you hang a weight on a spring and let it bounce. I have this data here, one being mass and one being time. The time is an average of 5 trials, each one being and average of 20 bounces, to minimize human error. t 0.3049s 0.3982s 0.4838s 0.5572s 0.6219s 0.6804s 0.7362s 0.7811s 0.8328s 0.869s The mass is the mass that was used in each trial (they aren't going up in exact differences because each weight has a slight difference, nothing is perfect in the real world) m 50.59g 100.43g 150.25g 200.19g 250.89g 301.16g 351.28g 400.79g 450.43g 499.71g My problem is that I need to find the relationship between them, I know m = (k/4PI^2)*T^2 so I can work out k like that but we need to graph it. I can assume that the relationship is a sqrt relation, not sure on that one. But it appears to be the reverse of a square. Should it be 1/x^2 then? Either way my problem is still present, I have tried 1/x, 1/x^2, sqrt, x^2, none of them produce a straight line. The problem for SU is that when I go to graph the data on Excel I set the y axis data (which is the weights) and then when I go to set the x axis (which is the time) it just replaces the y axis with what I want to be the x axis, this is only happening when I have the sqrt of "m" as the y axis and I try to set the x axis as the time. The problem of math is that, am I even using the right thing? To get a straight line it would need to be x = y^1/2 right? I thought I was doing the right thing, it is what we were told to do. I'm just not getting anything that looks right.

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  • Anyone have real world experience with Rackspace Cloud Sites at high scale?

    - by Allara
    I have a pure web service application layer using .NET. I was originally planning to use Amazon EC2, but rolling my own autoscaling procedures is a bit intimidating, and the scaling isn't very granular from a cost perspective. If the app is successful, we could be looking at relatively high scale (millions of requests per month). The app uses Amazon SimpleDB as the database layer. As a test, I have the app running successfully in Rackspace Cloud Sites. Performance seems to be equal to (if not better than) a standard EC2 instance, even with the added latency of the SimpleDB requests travelling to the Rackspace network. However, testing at this stage is at a very low scale. My question is this: has anyone had real-world experience running a high scale application on Rackspace Cloud Sites? Moreover, once you pass the "included" 10,000 compute cycles per month, does the overall cost seem to be lower than rolling lots of EC2 instances? My assumption would be that with completely smooth scaling (i.e. only adding compute resources as needed), the cost could be lower on average. However, their stated goal of calibrating 10,000 CCs as a single 1.2 Ghz CPU seems on average to be much more expensive than EC2. I like the idea of no-touch scaling, but is it too good to be true?

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  • Joomla performance problems on AWS

    - by Bobby Jack
    I'm running a site on AWS with the following setup: Single m1.small instance (web server) Single RDS m1.small db Joomla 1.5 Generally, the site is performant, but is fairly low-traffic - say around 50-100 visits / hour. However, at peak time, we see about double that traffic. During peak time, pretty much every day: CPU usage on the web server slowly climbs to 100% CPU usage on the RDS server climbs quite quickly to about 30%, from an average of about 15 Database connections shoot up to about 140, from a normal average of about 2 or 3 The site is then occasionally unreachable, certainly according to pingdom monitoring. Does anyone recognise this behaviour? Can you point me in the right direction to begin investigating? Of course, RDS makes it difficult to do things like slow query logging, so I've started by regularly dumping the mysql process list into a file to see if there's anything I can spot there, but it would be good to have something more concrete to investigate. UPDATE At least, can someone confirm that I'm definitely right in saying that the level of traffic implies the problem must be a specific type of query taking way longer than it should to execute? This would happen if a table gets locked, and many queries need to write to it, right? For this very reason, I've already changed the __session table type to InnoDB.

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  • Strange File-Server I/O Spikes - What Is Causing This?

    - by CruftRemover
    I am currently having a problem with a small Linux server that is providing file-sharing services to four Windows 7 32-bit clients. The server is an AMD PhenomX3 with two Western Digital 10EADS (1TB) drives, attached to a Gigabyte GA-MA770T-UD3 mainboard and running Ubuntu Server 10.04.1 LTS. The client machines are taking an extremely long time to access/transfer data on the file server. Applications often become non-responsive while trying to open files located remotely, or one program attempting to open a file but having to wait will prevent other software from accessing network resources at all. Other examples include one image taking 20 seconds or more to open, and in one instance a user waited 110 seconds for Microsoft Word 2007 to save a document. I had initially thought the problem was network-related, but this appears not to be the case. All cables and switches have been tested (one cable was replaced) for verification. This was additionally confirmed when closing down all client machines and rebooting the server resulted in the hard-drive light staying on solid during the startup process. For the first 15 minutes during boot, logon and after logging on (with no client machines attached), the system displayed a load average of 4 or higher. Symptoms included waiting several minutes for the logon prompt to appear, and then several minutes for the password prompt to appear after typing in a user name. After logon, it also took upwards of 45 seconds for the 'smartctl' man page to appear after the command 'man smartctl' was issued. After 15 minutes of this behaviour, the load average dropped to around 0.02 and the machine behaved normally. I have also considered that the problem is hard-drive-related, however diagnostic programs reveal no drive problems. Western Digital DLG, Spinrite and SMARTUDM show no abnormal characteristics - the drives are in perfect health as far as the hardware is concerned. I have thus far been completely unable to track down the cause of this problem, so any help is greatly appreciated. Requested Information: Output of 'free' hxxp://pastebin.com/mfsJS8HS (stupid spam filter) The command 'hdparm -d /dev/sda1' reports: HDIO_GET_DMA failed: Inappropriate ioctl for device (the BIOS is set to AHCI - I probably should have mentioned that).

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  • How Should I Generate Trade Statistics For CouchDB/Rails3 Application?

    - by James
    My Problem: I am trying to developing a web application for currency traders. The application allows traders to enter or upload information about their trades and I want to calculate a wide variety of statistics based on what the user entered. Now, normally I would use a relational database for this, but I have two requirements that don't fit well with a relational database so I am attempting to use couchdb. Those two problems are: 1) Primarily, I have a companion desktop application that users will be able to work with and replicate to the site using couchdb's awesome replication feature and 2) I would like to allow users to be able to define their own custom things to track about trades and generate results based off of what they enter. The schema less nature of couch seems perfect here, but it may end up being harder than it sounds. (I already know couch requires you to define views in advance and such so I was just planning on sticking all the custom attributes in an array and then emitting the array in the view and further processing from there.) What I Am Doing: Right now I am just emitting each trade in couch keyed by each user's system and querying with the key of the system to get an array of trades per system. Simple. I am not using a reduce function currently to calculate any stats because I couldn't figure out how to get everything I need without getting a reduce overflow error. Here is an example of rows that are getting emitted from couch: {"total_rows":134,"offset":0,"rows":[ {"id":"5b1dcd47221e160d8721feee4ccc64be", "key":["80e40ba2fa43589d57ec3f1d19db41e6","2010/05/14 04:32:37 +0000"], null, "doc":{ "_id":"5b1dcd47221e160d8721feee4ccc64be", "_rev":"1-bc9fe763e2637694df47d6f5efb58e5b", "couchrest-type":"Trade", "system":"80e40ba2fa43589d57ec3f1d19db41e6", "pair":"EUR/USD", "direction":"Buy", "entry":12600, "exit":12700, "stop_loss":12500, "profit_target":12700, "status":"Closed", "slug":"101332132375", "custom_tracking": [{"name":"signal", "value":"Pin Bar"}] "updated_at":"2010/05/14 04:32:37 +0000", "created_at":"2010/05/14 04:32:37 +0000", "result":100}} ]} In my rails 3 controller I am basically just populating an array of trades such as the one above and then extracting out the relevant data into smaller arrays that I can compute my statistics on. Here is my show action for the page that I want to display the stats and all the trades: def show @trades = Trade.by_system(:startkey => [@system.id], :endkey => [@system.id, Time.now ]) @trades.each do |trade| if trade.result > 0 @winning_trades << trade.result elsif trade.result < 0 @losing_trades << trade.result else @breakeven_trades << trade.result end if trade.direction == "Buy" @long_trades << trade.result else @short_trades << trade.result end if trade["custom_tracking"] != nil @custom_tracking << {"result" => trade.result, "variables" => trade["custom_tracking"]} end end end I am omitting some other stuff that is going on, but that is the gist of what I am doing. Then I am calculating stuff in the view layer to produce some results: <% winning_long_trades = @long_trades.reject {|trade| trade <= 0 } %> <% winning_short_trades = @short_trades.reject {|trade| trade <= 0 } %> <ul> <li>Total Trades: <%= @trades.count %></li> <li>Winners: <%= @winning_trades.size %></li> <li>Biggest Winner (Pips): <%= @winning_trades.max %></li> <li>Average Win(Pips): <%= @winning_trades.sum/@winning_trades.size %></li> <li>Losers: <%= @losing_trades.size %></li> <li>Biggest Loser (Pips): <%= @losing_trades.min %></li> <li>Average Loss(Pips): <%= @losing_trades.sum/@losing_trades.size %></li> <li>Breakeven Trades: <%= @breakeven_trades.size %></li> <li>Long Trades: <%= @long_trades.size %></li> <li>Winning Long Trades: <%= winning_long_trades.size %></li> <li>Short Trades: <%= @short_trades.size %></li> <li>Winning Short Trades: <%= winning_short_trades.size %></li> <li>Total Pips: <%= @winning_trades.sum + @losing_trades.sum %></li> <li>Win Rate (%): <%= @winning_trades.size/@trades.count.to_f * 100 %></li> </ul> This produces the following results, which aside from a few things is exactly what I want: Total Trades: 134 Winners: 70 Biggest Winner (Pips): 1488 Average Win(Pips): 440 Losers: 58 Biggest Loser (Pips): -516 Average Loss(Pips): -225 Breakeven Trades: 6 Long Trades: 125 Winning Long Trades: 67 Short Trades: 9 Winning Short Trades: 3 Total Pips: 17819 Win Rate (%): 52.23880597014925 What I Am Wondering- Finally The Actual Questions: I am starting to get really skeptical of how well this method will work when a user has 5,000 trades instead of just 134 like in this example. I anticipate most users will only have somewhere under 200 per year, but some users may have a couple thousand trades per year. Probably no more than 5,000 per year. It seems to work ok now, but the page load times are already getting a tad high for my tastes. (About 800ms to generate the page according to rails logs with about a 250ms of that spent in the view layer.) I will end up caching this page I am sure, but I still need the regenerate the page each time a trade is updated and I can't afford to have this be too slow. Sooo..... Is doing something similar here possible with a straight couchdb reduce function? I am assuming handing this off to couch would possibly help with larger data sets. I couldn't figure out how, but I suppose that doesn't mean it isn't possible. If possible, any hints will be helpful. Could I use a list function if a reduce was not available due to reduce constraints? Are couchdb list functions suitable for this type of calculations? Anyone have any idea of whether or not list functions perform well? Any hints what one would look like for the type of calculations I am trying to achieve? I thought about other options such as running the calculations at the time each trade was saved or nightly if I had to and saving the results to a statistics doc that I could then query so that all the processing was done ahead of time. I would like this to be the last resort because then I can't really filter out trades by time periods dynamically like I would really like to. (I want to have a slider that a user can slide to only show trades from that time period using the startkey and endkey in couchdb if I can.) If I should continue running the calculations inside the rails app at the time of the page view, what can I do to improve my current implementation. I am new to rails, couch and programming in general. I am sure that I could be doing something better here. Do I need to create an array for each stat or is there a better way to do that. I guess I just would really like some advice on how to tackle this problem. I want to keep the page generation time minimal since I anticipate these being some of the highest trafficked pages. My gut is that I will need to offload the statistics calculation to either couch or run the stats in advance of when they are called, but I am not sure. Lastly: Like I mentioned above, one of the primary reasons for using couch is to allow users to define their own things to track per trade. Getting the data into couch is no problem, but how would I be able to take the custom_tracking array and find how many winning trades for each named tracking attribute. If anyone can give me any hints to the possibility of doing this that would be great. Thanks a bunch. Would really appreciate any help. Willing to fork out some $$$ if someone wants to take on the problem for me. (Don't know if that is allowed on stack overflow or not.)

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  • LVS TCP connection timeouts - lingering connections

    - by Jon Topper
    I'm using keepalived to load-balance connections between a number of TCP servers. I don't expect it matters, but the service in this case is rabbitmq. I'm using NAT type balancing with weighted round-robin. A client connects to the server thus: [client]-----------[lvs]------------[real server] a b If a client connects to the LVS and remains idle, sending nothing on the socket, this eventually times out, according to timeouts set using ipvsadm --set. At this point, the connection marked 'a' above correctly disappears from the output of netstat -anp on the client, and from the output of ipvsadm -L -n -c on the lvs box. Connection 'b', however, remains ESTABLISHED according to netstat -anp on the real server box. Why is this? Can I force lvs to properly reset the connection to the real server?

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  • LVS TCP connection timeouts - lingering connections

    - by Jon Topper
    I'm using keepalived to load-balance connections between a number of TCP servers. I don't expect it matters, but the service in this case is rabbitmq. I'm using NAT type balancing with weighted round-robin. A client connects to the server thus: [client]-----------[lvs]------------[real server] a b If a client connects to the LVS and remains idle, sending nothing on the socket, this eventually times out, according to timeouts set using ipvsadm --set. At this point, the connection marked 'a' above correctly disappears from the output of netstat -anp on the client, and from the output of ipvsadm -L -n -c on the lvs box. Connection 'b', however, remains ESTABLISHED according to netstat -anp on the real server box. Why is this? Can I force lvs to properly reset the connection to the real server?

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  • nginx+php-fpm help optimize configs

    - by Dmitro
    I have 3 servers. First server (CPU - model name: 06/17, 2.66GHz, 4 cores, 8GB RAM) have nginx as load balancer with next config upstream lb_mydomain { server mydomain.ru:81 weight=2; server 66.0.0.18 weight=6; } server { listen 80; server_name ~(?!mydomain.ru)(.*); client_max_body_size 20m; location / { proxy_pass http://lb_mydomain; proxy_redirect off; proxy_set_header Connection close; proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_pass_header Set-Cookie; proxy_pass_header P3P; proxy_pass_header Content-Type; proxy_pass_header Content-Disposition; proxy_pass_header Content-Length; } } And configs from nginx.conf: user www-data; worker_processes 5; # worker_priority -1; error_log /var/log/nginx/error.log; pid /var/run/nginx.pid; events { worker_connections 5024; # multi_accept on; } http { include /etc/nginx/mime.types; access_log /var/log/nginx/access.log; sendfile on; default_type application/octet-stream; #tcp_nopush on; keepalive_timeout 65; tcp_nodelay on; gzip on; gzip_disable "MSIE [1-6]\.(?!.*SV1)"; # PHP-FPM (backend) upstream php-fpm { server 127.0.0.1:9000; } include /etc/nginx/conf.d/*.conf; include /etc/nginx/sites-enabled/*; } And config php-fpm: listen = 127.0.0.1:9000 ;listen.backlog = -1 ;listen.allowed_clients = 127.0.0.1 ;listen.owner = www-data ;listen.group = www-data ;listen.mode = 0666 user = www-data group = www-data pm = dynamic pm.max_children = 80 ;pm.start_servers = 20 pm.min_spare_servers = 5 pm.max_spare_servers = 35 ;pm.max_requests = 500 pm.status_path = /status ping.path = /ping ;ping.response = pong request_terminate_timeout = 30s request_slowlog_timeout = 10s slowlog = /var/log/php-fpm.log.slow ;rlimit_files = 1024 ;rlimit_core = 0 ;chroot = chdir = /var/www ;catch_workers_output = yes ;env[HOSTNAME] = $HOSTNAME ;env[PATH] = /usr/local/bin:/usr/bin:/bin ;env[TMP] = /tmp ;env[TMPDIR] = /tmp ;env[TEMP] = /tmp ;php_admin_value[sendmail_path] = /usr/sbin/sendmail -t -i -f [email protected] ;php_flag[display_errors] = off ;php_admin_value[error_log] = /var/log/fpm-php.www.log ;php_admin_flag[log_errors] = on ;php_admin_value[memory_limit] = 32M In top I see 20 php-fpm processes which use from 1% - 15% CPU. So it's have high load averadge: top - 15:36:22 up 34 days, 20:54, 1 user, load average: 5.98, 7.75, 8.78 Tasks: 218 total, 1 running, 217 sleeping, 0 stopped, 0 zombie Cpu(s): 34.1%us, 3.2%sy, 0.0%ni, 37.0%id, 24.8%wa, 0.0%hi, 0.9%si, 0.0%st Mem: 8183228k total, 7538584k used, 644644k free, 351136k buffers Swap: 9936892k total, 14636k used, 9922256k free, 990540k cached Second server(CPU - model name: Intel(R) Xeon(R) CPU E5504 @ 2.00GHz, 8 cores, 8GB RAM). Nginx configs from nginx.conf: user www-data; worker_processes 5; # worker_priority -1; error_log /var/log/nginx/error.log; pid /var/run/nginx.pid; events { worker_connections 5024; # multi_accept on; } http { include /etc/nginx/mime.types; access_log /var/log/nginx/access.log; sendfile on; default_type application/octet-stream; #tcp_nopush on; keepalive_timeout 65; tcp_nodelay on; gzip on; gzip_disable "MSIE [1-6]\.(?!.*SV1)"; # PHP-FPM (backend) upstream php-fpm { server 127.0.0.1:9000; } include /etc/nginx/conf.d/*.conf; include /etc/nginx/sites-enabled/*; } And config of php-fpm: listen = 127.0.0.1:9000 ;listen.backlog = -1 ;listen.allowed_clients = 127.0.0.1 ;listen.owner = www-data ;listen.group = www-data ;listen.mode = 0666 user = www-data group = www-data pm = dynamic pm.max_children = 50 ;pm.start_servers = 20 pm.min_spare_servers = 5 pm.max_spare_servers = 35 ;pm.max_requests = 500 ;pm.status_path = /status ;ping.path = /ping ;ping.response = pong ;request_terminate_timeout = 0 ;request_slowlog_timeout = 0 ;slowlog = /var/log/php-fpm.log.slow ;rlimit_files = 1024 ;rlimit_core = 0 ;chroot = chdir = /var/www ;catch_workers_output = yes ;env[HOSTNAME] = $HOSTNAME ;env[PATH] = /usr/local/bin:/usr/bin:/bin ;env[TMP] = /tmp ;env[TMPDIR] = /tmp ;env[TEMP] = /tmp ;php_admin_value[sendmail_path] = /usr/sbin/sendmail -t -i -f [email protected] ;php_flag[display_errors] = off ;php_admin_value[error_log] = /var/log/fpm-php.www.log ;php_admin_flag[log_errors] = on ;php_admin_value[memory_limit] = 32M In top I see 50 php-fpm processes which use from 10% - 25% CPU. So it's have high load averadge: top - 15:53:05 up 33 days, 1:15, 1 user, load average: 41.35, 40.28, 39.61 Tasks: 239 total, 40 running, 199 sleeping, 0 stopped, 0 zombie Cpu(s): 96.5%us, 3.1%sy, 0.0%ni, 0.0%id, 0.0%wa, 0.0%hi, 0.4%si, 0.0%st Mem: 8185560k total, 7804224k used, 381336k free, 161648k buffers Swap: 19802108k total, 16k used, 19802092k free, 5068112k cached Third server is server with database postgresql. Also i try ab -n 50 -c 5 http://www.mydomain.ru/ And I get next info: Complete requests: 50 Failed requests: 48 (Connect: 0, Receive: 0, Length: 48, Exceptions: 0) Write errors: 0 Total transferred: 9271367 bytes HTML transferred: 9247767 bytes Requests per second: 1.02 [#/sec] (mean) Time per request: 4882.427 [ms] (mean) Time per request: 976.486 [ms] (mean, across all concurrent requests) Transfer rate: 185.44 [Kbytes/sec] received Please advise how can I make lower level of load average?

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  • my webserver with 16GB ram shows all RAM as used, but is it really, see the 'top'

    - by Alex
    I have some questions about my web server. Its a LAMP web server running centos 5.5 and php5, mysql5. The server gets hundreds (maybe thousand) of concurrent users during peak hours. I'm trying to optimize a little and understand "top". From what I can see: all 16GB of my ram have been used up? does that mean that my server needs more memory? My swap is only 2GB, should it be increased? usually during peak hours my server load average first number is about 2.5-3. What could I do to optimize the server so that the load average even during peak doesn't go above 1? In the past I was told a good working server should stay under 1 load, is this still true? Although even during load of 2.5-3, server pages and applications seem to load with pretty good speed. what should the memory size in php.ini be set to? top - 14:30:18 up 2 days, 12:41, 5 users, load average: 1.25, 1.74, 2.92 Tasks: 305 total, 2 running, 302 sleeping, 0 stopped, 1 zombie Cpu(s): 6.3%us, 0.9%sy, 0.0%ni, 92.5%id, 0.2%wa, 0.0%hi, 0.1%si, 0.0%st Mem: 16427200k total, 16111472k used, 315728k free, 3120316k buffers Swap: 2104496k total, 268k used, 2104228k free, 6216756k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 29080 apache 15 0 358m 36m 5192 S 20.2 0.2 2:08.40 httpd 29093 apache 18 0 357m 36m 5192 S 18.2 0.2 2:02.52 httpd 29079 apache 15 0 370m 49m 5832 S 10.0 0.3 2:32.14 httpd 1812 apache 15 0 370m 49m 5196 S 7.3 0.3 2:25.30 httpd 5204 apache 15 0 358m 36m 5168 S 5.3 0.2 0:59.28 httpd 29075 apache 15 0 370m 48m 5184 S 3.3 0.3 2:15.93 httpd 9712 apache 15 0 360m 38m 5180 S 3.0 0.2 0:54.81 httpd 29072 apache 16 0 358m 36m 5192 S 2.7 0.2 2:24.43 httpd 6310 apache 17 0 388m 67m 5180 S 2.3 0.4 0:58.85 httpd 8674 apache 15 0 343m 21m 4980 S 2.0 0.1 0:07.91 httpd 29085 apache 15 0 371m 49m 5224 S 2.0 0.3 2:16.86 httpd 29083 apache 15 0 370m 48m 5196 S 1.7 0.3 2:10.64 httpd 5575 apache 15 0 357m 36m 5228 S 1.3 0.2 0:53.78 httpd 29066 apache 15 0 379m 59m 5860 R 1.3 0.4 2:11.93 httpd 29078 apache 15 0 370m 48m 5188 S 1.3 0.3 2:14.52 httpd 29084 apache 15 0 370m 48m 5208 S 1.0 0.3 2:02.49 httpd 29089 apache 15 0 370m 48m 5188 S 1.0 0.3 2:27.61 httpd 29082 apache 15 0 390m 68m 5188 S 0.7 0.4 2:32.48 httpd 29984 apache 15 0 358m 36m 5228 S 0.7 0.2 2:08.32 httpd 3571 root 16 0 13400 1792 848 S 0.3 0.0 2:37.89 top 4419 mysql 15 0 668m 175m 7204 S 0.3 1.1 3:32.25 mysqld 28181 root 15 0 90460 3624 2680 S 0.3 0.0 0:17.60 sshd 29091 apache 15 0 390m 69m 5196 S 0.3 0.4 2:29.99 httpd 32476 root 15 0 12900 1320 848 R 0.3 0.0 0:06.46 top 1 root 15 0 10372 680 572 S 0.0 0.0 0:02.01 init 2 root RT -5 0 0 0 S 0.0 0.0 0:00.51 migration/0 3 root 34 19 0 0 0 S 0.0 0.0 0:00.07 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 0:00.12 migration/1 6 root 34 19 0 0 0 S 0.0 0.0 0:00.03 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 0:00.06 migration/2 9 root 34 19 0 0 0 S 0.0 0.0 0:00.03 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 0:00.06 migration/3 12 root 34 19 0 0 0 S 0.0 0.0 0:00.04 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 0:01.45 migration/4 15 root 34 19 0 0 0 S 0.0 0.0 0:00.01 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 0:00.22 migration/5 18 root 34 19 0 0 0 S 0.0 0.0 0:00.01 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 0:00.15 migration/6 21 root 34 19 0 0 0 S 0.0 0.0 0:00.02 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 0:00.15 migration/7 24 root 34 19 0 0 0 S 0.0 0.0 0:00.01 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 0:00.19 migration/8 27 root 34 19 0 0 0 S 0.0 0.0 0:00.04 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 0:00.34 migration/9 30 root 34 19 0 0 0 S 0.0 0.0 0:00.03 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 0:00.16 migration/10 33 root 34 19 0 0 0 S 0.0 0.0 0:00.04 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 0:00.12 migration/11 36 root 34 19 0 0 0 S 0.0 0.0 0:00.05 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 0:00.35 migration/12

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