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  • Postfix spool on ext3 optimiziations in >=linux-2.6.34 days

    - by Luke404
    Given the very specific nature of the subject (we're not talking about mailboxes, just the spool; we're not talking about other filesystems, just ext3; and so on...) and the maturity of the softwares involved (linux kernel, ext3fs, postfix) I'd think there should be a more or less agreed on set of best practices to filesystem related tuning. I'm trying to get a roundup of them: data=journal became the default in recent kernels (somewhere around 2.6.30 IIRC) so we should be ok with that Wietse Venema says atime must be on, but Postfix documentation recommendsnoatime while talking about the Incoming Queue. Does that mean that postfix needs atime on just for some queue directories and will benefit from noatime on the others? can we use noatime if we just don't use ETRN? filesystem can be mounted nodev,noexec,nosuid - no* won't prevent you from setting attributes (postfix uses exec attr) they just won't have any effect (we don't run anything from the spool) the fsync() issue cited by Wietse and/or the chattr -S are probably linked to sync/async options of ext3fs but I do not understand them enough. Mouting the filesystem with async option is equivalent to chattr -R -S the whole fs? Seems like it will increase performance, but will that pose a risk of "loss of mail after a system crash" or is it really "safe on /var/spool/postfix" ? would you tune anything else on postfix-2.6.x to work better on ext3 or do you leave defaults everywhere? is there a "best" linux I/O scheduler for this kind of workload (namely CFQ or deadline?) or that's something that will vary too much based on hardware configuration? would you tune anything else in the filesystem or in the kernel? anything else? References: Postfix Performance here on SF Postfix documentation about the Incoming Queue Wietse Venema in Best file system on [email protected] here Postfix and ext3 on [email protected] here and there

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  • What is the best VM for developing WPF apps from within OS X?

    - by MarqueIV
    All of my machines are Macs (Mac Pro, MacBook Pro, MacBook Air and Mac Mini (and Apple TV 2.0 too! :) ) but for my day-job, I develop .NET/WPF applications. Normally I just boot into Boot Camp and develop that way, which of course works great, but there are times when I need to simultaneously get to things on my Mac-side of the equation, so I've bought both VMware 3.1 and Parallels 6. Both work, however, even on my Mac Pro where I paid to upgrade to the better video cards (the NVidia 8600s I think vs. the stock ATI cards) the WPF performance bites!! Now this confuses me since both boast that they support not only hardware-accelerated OpenGL 2.1, but also hardware-accelerated DirectX 9 (VMware even allegedly supports DirectX 10!) via their respective virtual drivers and both can run 3D games just fine, even in a window. But even the simple act of resizing a WPF window that has a tiled background results in some HIDEOUS repainting and resizing behaviors. It's damn near closer to what you'd expect over RDP let alone a software-only renderer (forget accelerated hardware completely!) So... can anyone please tell me WTF WPF is doing differently? More importantly, how can I speed up the WPF performance? Should I switch to VirtualBox that also has support for DirectX? Or am I just gonna have to 'byte' the bullet (sorry... had to. So I like puns! Thank Jon Stewart!) and continue using Boot Camp?

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  • Real benefits of tcp TIME-WAIT and implications in production environment

    - by user64204
    SOME THEORY I've been doing some reading on tcp TIME-WAIT (here and there) and what I read is that it's a value set to 2 x MSL (maximum segment life) which keeps a connection in the "connection table" for a while to guarantee that, "before your allowed to create a connection with the same tuple, all the packets belonging to previous incarnations of that tuple will be dead". Since segments received (apart from SYN under specific circumstances) while a connection is either in TIME-WAIT or no longer existing would be discarded, why not close the connection right away? Q1: Is it because there is less processing involved in dealing with segments from old connections and less processing to create a new connection on the same tuple when in TIME-WAIT (i.e. are there performance benefits)? If the above explanation doesn't stand, the only reason I see the TIME-WAIT being useful would be if a client sends a SYN for a connection before it sends remaining segments for an old connection on the same tuple in which case the receiver would re-open the connection but then get bad segments and and would have to terminate it. Q2: Is this analysis correct? Q3: Are there other benefits to using TIME-WAIT? SOME PRACTICE I've been looking at the munin graphs on a production server that I administrate. Here is one: As you can see there are more connections in TIME-WAIT than ESTABLISHED, around twice as many most of the time, on some occasions four times as many. Q4: Does this have an impact on performance? Q5: If so, is it wise/recommended to reduce the TIME-WAIT value (and what to)? Q6: Is this ratio of TIME-WAIT / ESTABLISHED connections normal? Could this be related to malicious connection attempts?

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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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  • HP Proliant DL380 G4 - Can this server still perform in 2011?

    - by BSchriver
    Can the HP Proliant DL380 G4 series server still perform at high a quality in the 2011 IT world? This may sound like a weird question but we are a very small company whose primary business is NOT IT related. So my IT dollars have to stretch a long way. I am in need of a good web and database server. The load and demand for a while will be fairly low so I am not looking nor do I have the money to buy a brand new HP Dl380 G7 series box for $6K. While searching around today I found a company in ATL that buys servers off business leases and then stripes them down to parts. They clean, check and test each part and then custom "rebuild" the server based on whatever specs you request. The interesting thing is they also provide a 3-year warranty on all their servers they sell. I am contemplating buying two of the following: HP Proliant DL380 G4 Dual (2) Intel Xeon 3.6 GHz 800Mhz 1MB Cache processors 8GB PC3200R ECC Memory 6 x 73GB U320 15K rpm SCSI drives Smart Array 6i Card Dual Power Supplies Plus the usual cdrom, dual nic, etc... All this for $750 each or $1500 for two pretty nicely equipped servers. The price then jumps up on the next model up which is the G5 series. It goes from $750 to like $2000 for a comparable server. I just do not have $4000 to buy two servers right now. So back to my original question, if I load Windows 2008 R2 Server and IIS 7 on one of the machines and Windows 2008 R2 server and MS SQL 2008 R2 Server on another machine, what kind of performance might I expect to see from these machines? The facts is this series is now 3 versions behind the G7's and this series of server was built when Windows 200 Server was the dominant OS and Windows 2003 Server was just coming out. If you are running Windows 2008 R2 Server on a G4 with similar or less specs I would love to hear what your performance is like.

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  • Caching all files in varnish

    - by csgwro
    I want my varnish servers to cache all files. At backend there is lighttpd hosting only static files, and there is an md5 in the url in case of file change, ex. /gfx/Bird.b6e0bc2d6cbb7dfe1a52bc45dd2b05c4.swf). However my hit ratio is very poorly (about 0.18) My config: sub vcl_recv { set req.backend=default; ### passing health to backend if (req.url ~ "^/health.html$") { return (pass); } remove req.http.If-None-Match; remove req.http.cookie; remove req.http.authenticate; if (req.request == "GET") { return (lookup); } } sub vcl_fetch { ### do not cache wrong codes if (beresp.status == 404 || beresp.status >= 500) { set beresp.ttl = 0s; } remove beresp.http.Etag; remove beresp.http.Last-Modified; } sub vcl_deliver { set resp.http.expires = "Thu, 31 Dec 2037 23:55:55 GMT"; } I have made an performance tuning: DAEMON_OPTS="${DAEMON_OPTS} -p thread_pool_min=200 -p thread_pool_max=4000 -p thread_pool_add_delay=2 -p session_linger=100" The main url which is missed is... /health.html. Is that forward to backend correctly configured? Disabling health checking hit ratio increases to 0.45. Now mostly "/crossdomain.xml" is missed (from many domains, as it is wildcard). How can I avoid that? Should I carry on other headers like User-Agent or Accept-Encoding? I thing that default hashing mechanism is using url + host/IP. Compression is used at the backend. What else can improve performance?

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  • Server slowdown

    - by Clinton Bosch
    I have a GWT application running on Tomcat on a cloud linux(Ubuntu) server, recently I released a new version of the application and suddenly my server response times have gone from 500ms average to 15s average. I have run every monitoring tool I know. iostat says my disks are 0.03% utilised mysqltuner.pl says I am OK other see below top says my processor is 99% idle and load average: 0.20, 0.31, 0.33 memory usage is 50% (-/+ buffers/cache: 3997 3974) mysqltuner output [OK] Logged in using credentials from debian maintenance account. -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.63-0ubuntu0.10.04.1-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: +Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 370M (Tables: 52) [--] Data in InnoDB tables: 697M (Tables: 1749) [!!] Total fragmented tables: 1754 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 19h 25m 41s (1M q [28.122 qps], 1K conn, TX: 2B, RX: 1B) [--] Reads / Writes: 98% / 2% [--] Total buffers: 1.0G global + 2.7M per thread (500 max threads) [OK] Maximum possible memory usage: 2.4G (30% of installed RAM) [OK] Slow queries: 0% (1/1M) [OK] Highest usage of available connections: 34% (173/500) [OK] Key buffer size / total MyISAM indexes: 16.0M/279.0K [OK] Key buffer hit rate: 99.9% (50K cached / 40 reads) [OK] Query cache efficiency: 61.4% (844K cached / 1M selects) [!!] Query cache prunes per day: 553779 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 34K sorts) [OK] Temporary tables created on disk: 4% (4K on disk / 102K total) [OK] Thread cache hit rate: 84% (185 created / 1K connections) [!!] Table cache hit rate: 0% (256 open / 27K opened) [OK] Open file limit used: 0% (20/2K) [OK] Table locks acquired immediately: 100% (692K immediate / 692K locks) [OK] InnoDB data size / buffer pool: 697.2M/1.0G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries Increase table_cache gradually to avoid file descriptor limits Variables to adjust: query_cache_size (> 16M) table_cache (> 256)

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  • Why database partitioning didn't work? Extract from thedailywtf.com

    - by questzen
    Original link. http://thedailywtf.com/Articles/The-Certified-DBA.aspx. Article summary: The DBA suggests an approach involving rigorous partitioning, 10 partitions per disk (3 actual disks and 3 raid). The stats show that the performance is non-optimal. Then the DBA suggests an alternative of 1 partition per disk (with more added disks). This also fails. The sys-admin then sets up a single disk, single partition and saves the day. The size of disks was not mentioned but given today,s typical disk sizes (of the order of 100 GB), the partitions ; would be huge, it surprises me that a single disk with all partitions outperformed. Initially I suspect that the data was segregated and hence faster reads. But how come the performance didn't degrade as time went by with all the inserts and updates happening? Saw this on reddit, but the explanation was by far spindle/platter centered. There was no mention in the article about this. Is there any other reason? I can only guess that the tables were using a incorrect hash distribution causing non-uniform allocation across disks (wrong partitioning); this would increase fetch times. Any thoughts?

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  • Is there an objective way to measure slowness of PC/WINDOWS?

    - by ekms
    We've a lot of users that usually complain about that his PC is "slow". (we use win XP). We usually check startup programs, virus, fragmentation, disk health and common problems that causes slowness (Symantec AV drops disk to 1mb/s , or a seagate HD firmware error in certain models), but in those cases the slowness is pretty evident. In other hand, the most common is the user complaining about his pc but for us looks OK, even in 6 years old desktops. People sometimes even complains about his new quad core desktops speed!!! So, we are asking if there's a way to OBJECTIVELY check that a computer didn't dropped its performance, compared with similar ones o previous measures, specially for work use (I don't think that 3dmark benchmark o similar may help). The only thing that I found that was useful is HDTune, but it only check hard disk performance. Basically, what we want is something that enable us to say to our users "see? your PC is as slow as was three years ago! stop complaining! Is all in your head!"

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  • Disk fragmentation when dealing with many small files

    - by Zorlack
    On a daily basis we generate about 3.4 Million small jpeg files. We also delete about 3.4 Million 90 day old images. To date, we've dealt with this content by storing the images in a hierarchical manner. The heriarchy is something like this: /Year/Month/Day/Source/ This heirarchy allows us to effectively delete days worth of content across all sources. The files are stored on a Windows 2003 server connected to a 14 disk SATA RAID6. We've started having significant performance issues when writing-to and reading-from the disks. This may be due to the performance of the hardware, but I suspect that disk fragmentation may be a culprit at well. Some people have recommended storing the data in a database, but I've been hesitant to do this. An other thought was to use some sort of container file, like a VHD or something. Does anyone have any advice for mitigating this kind of fragmentation? Additional Info: The average file size is 8-14KB Format information from fsutil: NTFS Volume Serial Number : 0x2ae2ea00e2e9d05d Version : 3.1 Number Sectors : 0x00000001e847ffff Total Clusters : 0x000000003d08ffff Free Clusters : 0x000000001c1a4df0 Total Reserved : 0x0000000000000000 Bytes Per Sector : 512 Bytes Per Cluster : 4096 Bytes Per FileRecord Segment : 1024 Clusters Per FileRecord Segment : 0 Mft Valid Data Length : 0x000000208f020000 Mft Start Lcn : 0x00000000000c0000 Mft2 Start Lcn : 0x000000001e847fff Mft Zone Start : 0x0000000002163b20 Mft Zone End : 0x0000000007ad2000

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  • Windows XP to remote server 2008 R2 shares - awful response times

    - by nick3216
    I have a network infrastructure of Windows XP clients (a mix of XP and 64-bit XP), that are accessing a network share on a Windows 2008 R2 server. Whenever users type the address of a folder into the address bar of Windows Explorer it's as snappy at determining the contents of the current folder and presenting them to you in the address bar as if you're working on a local drive. But if you open one of the subfolders users get the animated red torch and 'Searching for items...' dialog, typically for 45 seconds. Similarly when using the open folder dialog to try and select a subfolder on this share it takes, on average, 45 seconds for the dialog to expand each node and show the subfolders of each node. Also, while the Explorer instance accsesing the network share is running slowly users notice that the performance of all other Explorer windows suffers. So while Explorer is searching for files on the network share they can't switch to another task and navigate around their local drive using Explorer because it's now as slow as a dead dog at accessing anything. Are there any settings we can change which will improve the performance accessing network shares?

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  • How to force two process to run on the same CPU?

    - by kovan
    Context: I'm programming a software system that consists of multiple processes. It is programmed in C++ under Linux. and they communicate among them using Linux shared memory. Usually, in software development, is in the final stage when the performance optimization is made. Here I came to a big problem. The software has high performance requirements, but in machines with 4 or 8 CPU cores (usually with more than one CPU), it was only able to use 3 cores, thus wasting 25% of the CPU power in the first ones, and more than 60% in the second ones. After many research, and having discarded mutex and lock contention, I found out that the time was being wasted on shmdt/shmat calls (detach and attach to shared memory segments). After some more research, I found out that these CPUs, which usually are AMD Opteron and Intel Xeon, use a memory system called NUMA, which basically means that each processor has its fast, "local memory", and accessing memory from other CPUs is expensive. After doing some tests, the problem seems to be that the software is designed so that, basically, any process can pass shared memory segments to any other process, and to any thread in them. This seems to kill performance, as process are constantly accessing memory from other processes. Question: Now, the question is, is there any way to force pairs of processes to execute in the same CPU?. I don't mean to force them to execute always in the same processor, as I don't care in which one they are executed, altough that would do the job. Ideally, there would be a way to tell the kernel: If you schedule this process in one processor, you must also schedule this "brother" process (which is the process with which it communicates through shared memory) in that same processor, so that performance is not penalized.

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  • List of rich web application technologies

    - by Michal Czardybon
    I am trying to get myself acquainted with the world of rich web application. There are some comparison tables of available technologies on the Wikipedia, but I still find it unclear what are the options for rich application development. Could you please verify and complete the information I gathered below? What are the key pros and cons of each option? Which is the best choice for big and very rich web application? Option 1: ASP.NET/ASP.NET MVC Vendor: Microsoft Environment: Visual Studio Language: C# Output: HTML+JavaScript+AJAX Example: www.stackoverflow.com Option 2: Silverlight Vendor: Microsoft Environment: Visual Studio Language: C# Output: .NET executable? Example: ? Option 3: Google Web Toolkit Vendor: Google Environment: Eclipse Language: Java Output: HTML+JavaScript+AJAX Example: http://www.projectkaiser.com:8080/pk/ Option 4: Flex Vendor: Adobe Environment: ? Language: ? Output: Flash (.swf file) Example: http://listen.grooveshark.com/ Option 5: Adobe AIR Vendor: Adobe Environment: ? Language: ? Output: AIR Example: http://www.colabolo.com/en/download.html Option 5: Ruby on Rails Vendor: Rails Core Team Envirnoment: ? Language: Ruby Output: HTML+JavaScript+AJAX? Example: ? Option 6: Java Applets Vendor: Sun Environment: Eclipse Language: Java Output: Java Applet Option 7: OpenLeszlo Vendor: ? Environment: ? Language: ? Output: ? Example: ? Option 8: Python? ??? Option 9: XUL ???

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  • VBA compare and sort strings with quirky characters

    - by Smandoli
    I am comparing text values from two DAO recordsets in MS Access. I sort on the text field, then go through both recordsets comparing the values from each. The sets are substantially different and while they're mostly alpha-numeric, spaces and symbols like hyphens and periods are very common. My program depends on predictable sorting and fool-proof comparing. But unfortunately, the sort will rank two values differently than the comparison function. StrComp is the obvious first choice: varResult = StrComp(Val_1, Val_2) RFA-300 14.9044 RFA300 14-2044 But for the two pairs above, StrComp returns a different value than one would expect based on the sort. Including vbTextCompare or vbBinaryCompare affects StrComp's result, but not so as to solve the problem. Note the values must always be compared as strings. Of course I make sure that "14-2044" and "14.9044" aren't evaluated as -2030 and ~15. That's not the cause of my problem. I learned API-based functions are more reliable for quirky texts, so I tried these: varResult = CompareString(LOCALE_SYSTEM_DEFAULT, _ SORT_STRINGSORT, strVal_2, -1, strVal_1, -1) varResult = CompareString(LOCALE_SYSTEM_DEFAULT, _ NORM_IGNOREWIDTH, strVal_2, -1, strVal_1, -1) The first one returns the opposite of StrComp. The second one returns the same as StrComp. But neither yields a result that is consistent with the sort order. (NORM_IGNOREWIDTH is probably not relevant, but I needed a place-holder substitute and it looked as good as any.) UPDATE: This is a complete rewrite of the original post, deleting all the info about why I really need this -- just take my word for it and enjoy the brevity.

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  • Alternative or succesor to GDBM

    - by Anon Guy
    We a have a GDBM key-value database as the backend to a load-balanced web-facing application that is in implemented in C++. The data served by the application has grown very large, so our admins have moved the GDBM files from "local" storage (on the webservers, or very close by) to a large, shared, remote, NFS-mounted filesystem. This has affected performance. Our performance tests (in a test environment) show page load times jumping from hundreds of milliseconds (for local disk) to several seconds (over NFS, local network), and sometimes getting as high as 30 seconds. I believe a large part of the problem is that the application makes lots of random reads from the GDBM files, and that these are slow over NFS, and this will be even worse in production (where the front-end and back-end have even more network hardware between them) and as our database gets even bigger. While this is not a critical application, I would like to improve performance, and have some resources available, including the application developer time and Unix admins. My main constraint is time only have the resources for a few weeks. As I see it, my options are: Improve NFS performance by tuning parameters. My instinct is we wont get much out of this, but I have been wrong before, and I don't really know very much about NFS tuning. Move to a different key-value database, such as memcachedb or Tokyo Cabinet. Replace NFS with some other protocol (iSCSI has been mentioned, but i am not familiar with it). How should I approach this problem?

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  • Designing small comparable objects

    - by Thomas Ahle
    Intro Consider you have a list of key/value pairs: (0,a) (1,b) (2,c) You have a function, that inserts a new value between two current pairs, and you need to give it a key that keeps the order: (0,a) (0.5,z) (1,b) (2,c) Here the new key was chosen as the average between the average of keys of the bounding pairs. The problem is, that you list may have milions of inserts. If these inserts are all put close to each other, you may end up with keys such to 2^(-1000000), which are not easily storagable in any standard nor special number class. The problem How can you design a system for generating keys that: Gives the correct result (larger/smaller than) when compared to all the rest of the keys. Takes up only O(logn) memory (where n is the number of items in the list). My tries First I tried different number classes. Like fractions and even polynomium, but I could always find examples where the key size would grow linear with the number of inserts. Then I thought about saving pointers to a number of other keys, and saving the lower/greater than relationship, but that would always require at least O(sqrt) memory and time for comparison. Extra info: Ideally the algorithm shouldn't break when pairs are deleted from the list.

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  • Refactoring or Rewriting Monolithic PHP Spaghetti Codebase

    - by nategood
    I've inherited a really poorly designed PHP spaghetti code project. It's been gaining a good bit of traffic recently and is starting to have performance issues on top of the poor monolithic code base. Its maxing out performance on a chunky 16GB dedicated machine when it really shouldn't be. I'm planning on doing some performance tweaks right off the bat to help the performance issue, but this still won't really help the horrible code base. The team is small but expecting to grow very soon. I've read Joel's article on the troubles of doing a complete rewrite and see the concerns. But how bad does the code base have to be before you consider a rewrite? There is PHP handling logic interjected into what one would usually consider a "view". Even worse, in some places SQL statements are in these same files! The only real separation of presentation and logic are a few PHP scripts that serve as function libraries. These scripts do most of the ORM stuff... if you can even call it that. Trying to slowly refractor this seems like a nightmare. Open to your thoughts and opinions... however not interested in hearing, "Run away, Run away!".

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  • What is the fastest way to check if files are identical?

    - by ojblass
    If you have 1,000,0000 source files, you suspect they are all the same, and you want to compare them what is the current fasted method to compare those files? Assume they are Java files and platform where the comparison is done is not important. cksum is making me cry. When I mean identical I mean ALL identical. Update: I know about generating checksums. diff is laughable ... I want speed. Update: Don't get stuck on the fact they are source files. Pretend for example you took a million runs of a program with very regulated output. You want to prove all 1,000,000 versions of the output are the same. Update: read the number of blocks rather than bytes? Immediatly throw out those? Is that faster than finding the number of bytes? Update: Is this ANY different than the fastest way to compare two files?

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  • What are the quality metrics for RAM?

    - by Hi-Tech KitKat Android
    I have searched RAM and i found there are given some specification for the same capacity RAM, What are the difference and performance comparison between these? Like RAM1 General Brand Transcend Memory Type 2 GB (8 x 128 MB) DDR2 DIMM Memory Standard DDR2-800/PC-6400 Compatible Device PC Pins 240-pin Burst Length 4, 8 Buffered/Unbuffered Unbuffered Memory Memory Clock 400 MHz Technology DDR2 SDRAM Memory CAS Latency 4, 5, 6 RAM 2 General Brand Transcend Memory Type 2 GB (8 x 128 MB) DDR2 DIMM Memory Standard DDR2-667/PC2-5300 Compatible Device PC Pins 240-pin Burst Length 4, 8 Buffered/Unbuffered Unbuffered Memory Memory Clock 333 MHz Technology DDR2 SDRAM Memory CAS Latency 3, 4, 5 RAM3 General Brand Kingston Memory Type 2 GB (64 x 256 MB) 800 MHz DDR2 DIMM Compatible Device PC Pins 240-pin Error Check Non-ECC Buffered/Unbuffered Unbuffered Memory Memory Clock 200 MHz Technology DDR2 SDRAM Memory CAS Latency 6 What are the affect of the following Memory Type(given as 8 x 128 MB) Memory Clock (given in MHz) CAS Latency (given as 4,5,6) my Requirement is 2 GB DDR2 Type Desktop Please help

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  • How can a single disk in a hardware SATA RAID-10 array bring the entire array to a screeching halt?

    - by Stu Thompson
    Prelude: I'm a code-monkey that's increasingly taken on SysAdmin duties for my small company. My code is our product, and increasingly we provide the same app as SaaS. About 18 months ago I moved our servers from a premium hosting centric vendor to a barebones rack pusher in a tier IV data center. (Literally across the street.) This ment doing much more ourselves--things like networking, storage and monitoring. As part the big move, to replace our leased direct attached storage from the hosting company, I built a 9TB two-node NAS based on SuperMicro chassises, 3ware RAID cards, Ubuntu 10.04, two dozen SATA disks, DRBD and . It's all lovingly documented in three blog posts: Building up & testing a new 9TB SATA RAID10 NFSv4 NAS: Part I, Part II and Part III. We also setup a Cacit monitoring system. Recently we've been adding more and more data points, like SMART values. I could not have done all this without the awesome boffins at ServerFault. It's been a fun and educational experience. My boss is happy (we saved bucket loads of $$$), our customers are happy (storage costs are down), I'm happy (fun, fun, fun). Until yesterday. Outage & Recovery: Some time after lunch we started getting reports of sluggish performance from our application, an on-demand streaming media CMS. About the same time our Cacti monitoring system sent a blizzard of emails. One of the more telling alerts was a graph of iostat await. Performance became so degraded that Pingdom began sending "server down" notifications. The overall load was moderate, there was not traffic spike. After logging onto the application servers, NFS clients of the NAS, I confirmed that just about everything was experiencing highly intermittent and insanely long IO wait times. And once I hopped onto the primary NAS node itself, the same delays were evident when trying to navigate the problem array's file system. Time to fail over, that went well. Within 20 minuts everything was confirmed to be back up and running perfectly. Post-Mortem: After any and all system failures I perform a post-mortem to determine the cause of the failure. First thing I did was ssh back into the box and start reviewing logs. It was offline, completely. Time for a trip to the data center. Hardware reset, backup an and running. In /var/syslog I found this scary looking entry: Nov 15 06:49:44 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_00], 6 Currently unreadable (pending) sectors Nov 15 06:49:44 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_07], SMART Prefailure Attribute: 1 Raw_Read_Error_Rate changed from 171 to 170 Nov 15 06:49:45 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_10], 16 Currently unreadable (pending) sectors Nov 15 06:49:45 umbilo smartd[2827]: Device: /dev/twa0 [3ware_disk_10], 4 Offline uncorrectable sectors Nov 15 06:49:45 umbilo smartd[2827]: Num Test_Description Status Remaining LifeTime(hours) LBA_of_first_error Nov 15 06:49:45 umbilo smartd[2827]: # 1 Short offline Completed: read failure 90% 6576 3421766910 Nov 15 06:49:45 umbilo smartd[2827]: # 2 Short offline Completed: read failure 90% 6087 3421766910 Nov 15 06:49:45 umbilo smartd[2827]: # 3 Short offline Completed: read failure 10% 5901 656821791 Nov 15 06:49:45 umbilo smartd[2827]: # 4 Short offline Completed: read failure 90% 5818 651637856 Nov 15 06:49:45 umbilo smartd[2827]: So I went to check the Cacti graphs for the disks in the array. Here we see that, yes, disk 7 is slipping away just like syslog says it is. But we also see that disk 8's SMART Read Erros are fluctuating. There are no messages about disk 8 in syslog. More interesting is that the fluctuating values for disk 8 directly correlate to the high IO wait times! My interpretation is that: Disk 8 is experiencing an odd hardware fault that results in intermittent long operation times. Somehow this fault condition on the disk is locking up the entire array Maybe there is a more accurate or correct description, but the net result has been that the one disk is impacting the performance of the whole array. The Question(s) How can a single disk in a hardware SATA RAID-10 array bring the entire array to a screeching halt? Am I being naïve to think that the RAID card should have dealt with this? How can I prevent a single misbehaving disk from impacting the entire array? Am I missing something?

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  • How does Google manage to serve results so fast?

    - by Quintin Par
    I am building an autocomplete functionality for my site and the Google instant results are my benchmark. When I look at Google, the 50-60 ms response time baffle me. They look insane. In comparison here’s how mine looks like. To give you an idea my results are cached on the load balancer and served from a machine that has httpd slowstart and initcwnd fixed. My site is also behind cloudflare From a server side perspective I don’t think I can do anything more. Can someone help me take this 500 ms response time to 60ms? What more should I be doing to achieve Google level performance?

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  • SAN with iSCSI-Target Performance Horrendous

    - by Justin
    We have a poor man's SAN setup in a 1U Ubuntu server running iSCSI-Target with two 300GB drives in RAID-0. We then are using it for block level storage for virtual machines. The hypervisor is connected to the SAN via gigabit on a dedicated VLAN and interfaces. We only have a single virtual machine setup and doing some benchmarks. If we run hdparm -t /dev/sda1 from the virtual machine, we get 'ok' performance of 75MB/s from the virtual machine to the SAN. Then we basically compile a package with ./configure and make. Things start ok, but then all the sudden the load average on the SAN grows to 7+ and things slow down to a crawl. When we SSH into the SAN and run top, sure the load is 7+, but the CPU usage is basically nothing, also the server has 1.5GB of memory available. When we kill the compile on the virtual machine, slowly the LOAD on the SAN goes back to sub 1 figures. What in the world is causing this? How can we diagnosis this further? Here are two screenshot from the SAN during high load. 1> Output of iotop on the SAN: 2> Output of top on the SAN:

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  • X11 performance problem after upgrading from Centos3 to Centos5 with an ATI Rage XL

    - by Marcelo Santos
    After upgrading a computer from Centos3 to Centos5 an application that does a lot of scrolling took a very high performance hit. top tells me that X is using a lot of CPU and that was not happening before. The machine has an ATI Rage XL with 8MB and X is using the ati driver as there is no proprietary ATI driver for this board on linux. The xorg.conf: Section "Device" Identifier "Videocard0" Driver "ati" EndSection Section "Screen" Identifier "Screen0" Device "Videocard0" DefaultDepth 24 SubSection "Display" Viewport 0 0 Depth 24 Modes "1024x768" "800x600" "640x480" EndSubSection EndSection Section "DRI" Group 0 Mode 0666 EndSection A similar machine that still has Centos3 installed is able to start DRI on the X server while this one is not, this is the Xorg.0.log for the Centos5 machine: drmOpenDevice: node name is /dev/dri/card0 drmOpenDevice: open result is -1, (No such device or address) drmOpenDevice: open result is -1, (No such device or address) drmOpenDevice: Open failed drmOpenDevice: node name is /dev/dri/card0 drmOpenDevice: open result is -1, (No such device or address) drmOpenDevice: open result is -1, (No such device or address) drmOpenDevice: Open failed [drm] failed to load kernel module "mach64" (II) ATI(0): [drm] drmOpen failed (EE) ATI(0): [dri] DRIScreenInit Failed (II) ATI(0): Largest offscreen areas (with overlaps): (II) ATI(0): 1024 x 1279 rectangle at 0,768 (II) ATI(0): 768 x 1280 rectangle at 0,768 (II) ATI(0): Using XFree86 Acceleration Architecture (XAA) Screen to screen bit blits Solid filled rectangles 8x8 mono pattern filled rectangles Indirect CPU to Screen color expansion Solid Lines Offscreen Pixmaps Setting up tile and stipple cache: 32 128x128 slots 10 256x256 slots (==) ATI(0): Backing store disabled (==) ATI(0): Silken mouse enabled (II) ATI(0): Direct rendering disabled (==) RandR enabled I also tried using EXA instead of XAA and setting: Option "AccelMethod" "XAA" Option "XAANoOffscreenPixmaps" "true" uname -a Linux sir5.erg.inpe.br 2.6.18-128.7.1.el5 #1 SMP Mon Aug 24 08:20:55 EDT 2009 i686 i686 i386 GNU/Linux rpm -qa | grep xorg-x11-server xorg-x11-server-utils-7.1-4.fc6 xorg-x11-server-sdk-1.1.1-48.52.el5 xorg-x11-server-Xvfb-1.1.1-48.52.el5 xorg-x11-server-Xnest-1.1.1-48.52.el5 xorg-x11-server-Xorg-1.1.1-48.52.el5 The drmOpenDevice error continues when using the suggested Option "AIGLX" "true".

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  • Bad Performance when SQL Server hits 99% Memory Usage

    - by user15863
    I've got a server that reports 8 GB of ram used up at 99%. When restart Sql Server, it drops down to about 5% usage, but gradually builds back up to 99% over about 2 hours. When I look at the sqlserver process, its reported as only using 100k ram, and generally never goes up or below that number by very much. In fact, if I add up all the processes in my TaskManager, it's barely scratching the surface of my total available (yet TaskManager still shows 99% memory usage with "All processes shown"). It appears that Sql Server has a huge memory leak going on but it's not reporting it. The server has ran fine for nearly two years, with this only starting to manifest itself in the last 3-4 weeks. Anyone seen this or have any insight into the problem? EDIT When the server hits 99%, performance goes down hill. All queries to the server, apps, etc. come to a crawl. Restarting the service makes things zippy again, until 2 hours has passed and the server hits 99% once again.

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  • Performance of Virtual machines on very low end machines

    - by TheLQ
    I am managing a few cheap servers as my user base isn't large enough to get much more powerful servers. I also don't have the money lying around to invest in a server to prepare for the larger user base. So I'm stuck with the old hardware I have. I am toying with the idea of virtualizing all the current OS's with most likely VMware vSphere Hypervisor (AKA ESXi) Xen (ESXi has too strict of an HCL, and my hardware is too old). Big reasons for doing so: Ability to upgrade and scale hardware rapidly - This is most likely what I'll be doing as I distribute services, get a bigger server, centralize (electricity bills are horrible), distribute, get a bigger server, etc... Manually doing this by reinstalling the entire OS would be a big pain Safety from me - I've made many rookie mistakes, like doing lots of risky work on a vital production server. With a VM I can just backup the state, work on my machine, test, and revert if necessary. No worries, and no OS reinstallation Safety from other factors - As I scale servers might go down, and a backup VM can instantly be started. Various other reasons. However the limiting factor here is hardware. And I mean very depressing hardware. The current server's run off of a Pentium 3 and 4, and have 512 MB and 768 MB RAM respectively (RAM can be upgraded soon however). Is the Virtualization layer small enough to run itself and a Linux OS effectively? Will performance be acceptable (50% CPU overhead for every operation isn't acceptable)? Does it leave enough RAM for the Linux OS? Is this even feasible?

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