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  • Type of Blobs

    - by kaleidoscope
    With the release of Windows Azure November 2009 CTP, now we have two types of blobs. Block Blob - This blob type is in place since PDC 2008 and is optimized for streaming workloads. [Max Size allowed : 200GB] Page Blob - With November 2009 CTP release, a new blob type is added which is optimized for random read / writes called Page Blob. [Max Size allowed : 1TB] More details can be found at: http://geekswithblogs.net/IUnknown/archive/2009/11/16/azure-november-ctp-announced.aspx Amit, S

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  • O'Reilly deal of the Week on Early Release Books to 19/June/2012 23:39 PT

    - by TATWORTH
    O'Reilly are offering a 50% off deal on early release e-books at http://http://shop.oreilly.com/category/early-release.do?code=WKEARE"With Early Release ebooks, you get entire books in their earliest form — the author's raw and unedited content as he or she writes — so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, as well as the final multiple-format ebook bundle."These are an excellent deal!

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  • When do you call yourself a programmer

    - by benhowdle89
    "A programmer, computer programmer or coder is someone who writes computer software" from Wikipedia If you do frontend development using jQuery/CSS/HTML do you call yourself a programmer? If you develop PHP applications that deal with databases, do you call yourself a programmer? Are you only a programmer if you write applications for desktops and mobiles? Is the web a place where the line between developer and programmer stops?

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  • Attribute Overwriting in MDX

    - by Marco Russo (SQLBI)
    Jeffrey Wang wrote a great blog post about attribute overwriting in MDX that is very clear and full of helpful pictures to show what happens when you write an MDX statement that writes into your multidimensional space. This is very common in an MDX Script and if you tried to customize the DateTool solution you probably experienced how hard this concept can be. The point is not that MDX is hard, is that a model based on multiple hierarchies in a dimension (and each attribute is a hierarchy by default!)...(read more)

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  • links for 2010-05-21

    - by Bob Rhubart
    Stewart Bryson: Rittman Mead America is Recruiting "We don’t employ any junior consultants," writes Bryson, "so you would have to be highly experienced with some or all of the Oracle BI Stack (OBIEE, OWB, ODI, the Oracle Database, Hyperion), preferably have consulting experience, and excellent client-facing skills. Our consultants also provide all of our training services, and most of us write and speak at conferences, so being articulate and passionate about Oracle BI is another requirement. (tags: jobs employment consultants oracle businessintelligence)

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  • SQL Server 2014 – delayed transaction durability

    - by Michael Zilberstein
    As I’m downloading SQL Server 2014 CTP2 at this very moment, I’ve noticed new fascinating feature that hadn’t been announced in CTP1 : delayed transaction durability . It means that if your system is heavy on writes and on another hand you can tolerate data loss on some rare occasions – you can consider declaring transaction as DELAYED_DURABILITY = ON . In this case transaction would be committed when log is written to some buffer in memory – not to disk as usual. This way transactions can become...(read more)

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  • Win7 can't be loaded after installing ubuntu 11.10

    - by Kirill Lykov
    I use MacBookPro8,2. First of all I installed MacOS, then WIn7 on sde4, then Ubuntu on sde5 and swop on sde5. After installing ubuntu win7 isn't loaded when I choose it in grub. Win boot writes the following message: file: \boot\BCD Status: 0xc0000225 An error occurred while attempting to load the boot configuration data What shall I do? Try to repair windows using CD(in this case I think I will damage grub) or I can somehow configure grub to make it work properly?

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  • What's the problem with Scala's XML literals?

    - by Oak
    In this post, Martin (the language's head honcho) writes: [XML literals] Seemed a great idea at the time, now it sticks out like a sore thumb. I believe with the new string interpolation scheme we will be able to put all of XML processing in the libraries, which should be a big win. Being interested in language design myself, I'm wondering: Why does he write that it was a mistake to incorporate XML literals into the language? What is the controversy regarding this feature?

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  • C#/.NET Little Wonders: Interlocked Read() and Exchange()

    - by James Michael Hare
    Once again, in this series of posts I look at the parts of the .NET Framework that may seem trivial, but can help improve your code by making it easier to write and maintain. The index of all my past little wonders posts can be found here. Last time we discussed the Interlocked class and its Add(), Increment(), and Decrement() methods which are all useful for updating a value atomically by adding (or subtracting).  However, this begs the question of how do we set and read those values atomically as well? Read() – Read a value atomically Let’s begin by examining the following code: 1: public class Incrementor 2: { 3: private long _value = 0; 4:  5: public long Value { get { return _value; } } 6:  7: public void Increment() 8: { 9: Interlocked.Increment(ref _value); 10: } 11: } 12:  It uses an interlocked increment, as we discuss in my previous post (here), so we know that the increment will be thread-safe.  But, to realize what’s potentially wrong we have to know a bit about how atomic reads are in 32 bit and 64 bit .NET environments. When you are dealing with an item smaller or equal to the system word size (such as an int on a 32 bit system or a long on a 64 bit system) then the read is generally atomic, because it can grab all of the bits needed at once.  However, when dealing with something larger than the system word size (reading a long on a 32 bit system for example), it cannot grab the whole value at once, which can lead to some problems since this read isn’t atomic. For example, this means that on a 32 bit system we may read one half of the long before another thread increments the value, and the other half of it after the increment.  To protect us from reading an invalid value in this manner, we can do an Interlocked.Read() to force the read to be atomic (of course, you’d want to make sure any writes or increments are atomic also): 1: public class Incrementor 2: { 3: private long _value = 0; 4:  5: public long Value 6: { 7: get { return Interlocked.Read(ref _value); } 8: } 9:  10: public void Increment() 11: { 12: Interlocked.Increment(ref _value); 13: } 14: } Now we are guaranteed that we will read the 64 bit value atomically on a 32 bit system, thus ensuring our thread safety (assuming all other reads, writes, increments, etc. are likewise protected).  Note that as stated before, and according to the MSDN (here), it isn’t strictly necessary to use Interlocked.Read() for reading 64 bit values on 64 bit systems, but for those still working in 32 bit environments, it comes in handy when dealing with long atomically. Exchange() – Exchanges two values atomically Exchange() lets us store a new value in the given location (the ref parameter) and return the old value as a result. So just as Read() allows us to read atomically, one use of Exchange() is to write values atomically.  For example, if we wanted to add a Reset() method to our Incrementor, we could do something like this: 1: public void Reset() 2: { 3: _value = 0; 4: } But the assignment wouldn’t be atomic on 32 bit systems, since the word size is 32 bits and the variable is a long (64 bits).  Thus our assignment could have only set half the value when a threaded read or increment happens, which would put us in a bad state. So instead, we could write Reset() like this: 1: public void Reset() 2: { 3: Interlocked.Exchange(ref _value, 0); 4: } And we’d be safe again on a 32 bit system. But this isn’t the only reason Exchange() is valuable.  The key comes in realizing that Exchange() doesn’t just set a new value, it returns the old as well in an atomic step.  Hence the name “exchange”: you are swapping the value to set with the stored value. So why would we want to do this?  Well, anytime you want to set a value and take action based on the previous value.  An example of this might be a scheme where you have several tasks, and during every so often, each of the tasks may nominate themselves to do some administrative chore.  Perhaps you don’t want to make this thread dedicated for whatever reason, but want to be robust enough to let any of the threads that isn’t currently occupied nominate itself for the job.  An easy and lightweight way to do this would be to have a long representing whether someone has acquired the “election” or not.  So a 0 would indicate no one has been elected and 1 would indicate someone has been elected. We could then base our nomination strategy as follows: every so often, a thread will attempt an Interlocked.Exchange() on the long and with a value of 1.  The first thread to do so will set it to a 1 and return back the old value of 0.  We can use this to show that they were the first to nominate and be chosen are thus “in charge”.  Anyone who nominates after that will attempt the same Exchange() but will get back a value of 1, which indicates that someone already had set it to a 1 before them, thus they are not elected. Then, the only other step we need take is to remember to release the election flag once the elected thread accomplishes its task, which we’d do by setting the value back to 0.  In this way, the next thread to nominate with Exchange() will get back the 0 letting them know they are the new elected nominee. Such code might look like this: 1: public class Nominator 2: { 3: private long _nomination = 0; 4: public bool Elect() 5: { 6: return Interlocked.Exchange(ref _nomination, 1) == 0; 7: } 8: public bool Release() 9: { 10: return Interlocked.Exchange(ref _nomination, 0) == 1; 11: } 12: } There’s many ways to do this, of course, but you get the idea.  Running 5 threads doing some “sleep” work might look like this: 1: var nominator = new Nominator(); 2: var random = new Random(); 3: Parallel.For(0, 5, i => 4: { 5:  6: for (int j = 0; j < _iterations; ++j) 7: { 8: if (nominator.Elect()) 9: { 10: // elected 11: Console.WriteLine("Elected nominee " + i); 12: Thread.Sleep(random.Next(100, 5000)); 13: nominator.Release(); 14: } 15: else 16: { 17: // not elected 18: Console.WriteLine("Did not elect nominee " + i); 19: } 20: // sleep before check again 21: Thread.Sleep(1000); 22: } 23: }); And would spit out results like: 1: Elected nominee 0 2: Did not elect nominee 2 3: Did not elect nominee 1 4: Did not elect nominee 4 5: Did not elect nominee 3 6: Did not elect nominee 3 7: Did not elect nominee 1 8: Did not elect nominee 2 9: Did not elect nominee 4 10: Elected nominee 3 11: Did not elect nominee 2 12: Did not elect nominee 1 13: Did not elect nominee 4 14: Elected nominee 0 15: Did not elect nominee 2 16: Did not elect nominee 4 17: ... Another nice thing about the Interlocked.Exchange() is it can be used to thread-safely set pretty much anything 64 bits or less in size including references, pointers (in unsafe mode), floats, doubles, etc.  Summary So, now we’ve seen two more things we can do with Interlocked: reading and exchanging a value atomically.  Read() and Exchange() are especially valuable for reading/writing 64 bit values atomically in a 32 bit system.  Exchange() has value even beyond simply atomic writes by using the Exchange() to your advantage, since it reads and set the value atomically, which allows you to do lightweight nomination systems. There’s still a few more goodies in the Interlocked class which we’ll explore next time! Technorati Tags: C#,CSharp,.NET,Little Wonders,Interlocked

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 4

    - by MarkPearl
    Learning Outcomes Explain the characteristics of memory systems Describe the memory hierarchy Discuss cache memory principles Discuss issues relevant to cache design Describe the cache organization of the Pentium Computer Memory Systems There are key characteristics of memory… Location – internal or external Capacity – expressed in terms of bytes Unit of Transfer – the number of bits read out of or written into memory at a time Access Method – sequential, direct, random or associative From a users perspective the two most important characteristics of memory are… Capacity Performance – access time, memory cycle time, transfer rate The trade off for memory happens along three axis… Faster access time, greater cost per bit Greater capacity, smaller cost per bit Greater capacity, slower access time This leads to people using a tiered approach in their use of memory   As one goes down the hierarchy, the following occurs… Decreasing cost per bit Increasing capacity Increasing access time Decreasing frequency of access of the memory by the processor The use of two levels of memory to reduce average access time works in principle, but only if conditions 1 to 4 apply. A variety of technologies exist that allow us to accomplish this. Thus it is possible to organize data across the hierarchy such that the percentage of accesses to each successively lower level is substantially less than that of the level above. A portion of main memory can be used as a buffer to hold data temporarily that is to be read out to disk. This is sometimes referred to as a disk cache and improves performance in two ways… Disk writes are clustered. Instead of many small transfers of data, we have a few large transfers of data. This improves disk performance and minimizes processor involvement. Some data designed for write-out may be referenced by a program before the next dump to disk. In that case the data is retrieved rapidly from the software cache rather than slowly from disk. Cache Memory Principles Cache memory is substantially faster than main memory. A caching system works as follows.. When a processor attempts to read a word of memory, a check is made to see if this in in cache memory… If it is, the data is supplied, If it is not in the cache, a block of main memory, consisting of a fixed number of words is loaded to the cache. Because of the phenomenon of locality of references, when a block of data is fetched into the cache, it is likely that there will be future references to that same memory location or to other words in the block. Elements of Cache Design While there are a large number of cache implementations, there are a few basic design elements that serve to classify and differentiate cache architectures… Cache Addresses Cache Size Mapping Function Replacement Algorithm Write Policy Line Size Number of Caches Cache Addresses Almost all non-embedded processors support virtual memory. Virtual memory in essence allows a program to address memory from a logical point of view without needing to worry about the amount of physical memory available. When virtual addresses are used the designer may choose to place the cache between the MMU (memory management unit) and the processor or between the MMU and main memory. The disadvantage of virtual memory is that most virtual memory systems supply each application with the same virtual memory address space (each application sees virtual memory starting at memory address 0), which means the cache memory must be completely flushed with each application context switch or extra bits must be added to each line of the cache to identify which virtual address space the address refers to. Cache Size We would like the size of the cache to be small enough so that the overall average cost per bit is close to that of main memory alone and large enough so that the overall average access time is close to that of the cache alone. Also, larger caches are slightly slower than smaller ones. Mapping Function Because there are fewer cache lines than main memory blocks, an algorithm is needed for mapping main memory blocks into cache lines. The choice of mapping function dictates how the cache is organized. Three techniques can be used… Direct – simplest technique, maps each block of main memory into only one possible cache line Associative – Each main memory block to be loaded into any line of the cache Set Associative – exhibits the strengths of both the direct and associative approaches while reducing their disadvantages For detailed explanations of each approach – read the text book (page 148 – 154) Replacement Algorithm For associative and set associating mapping a replacement algorithm is needed to determine which of the existing blocks in the cache must be replaced by a new block. There are four common approaches… LRU (Least recently used) FIFO (First in first out) LFU (Least frequently used) Random selection Write Policy When a block resident in the cache is to be replaced, there are two cases to consider If no writes to that block have happened in the cache – discard it If a write has occurred, a process needs to be initiated where the changes in the cache are propagated back to the main memory. There are several approaches to achieve this including… Write Through – all writes to the cache are done to the main memory as well at the point of the change Write Back – when a block is replaced, all dirty bits are written back to main memory The problem is complicated when we have multiple caches, there are techniques to accommodate for this but I have not summarized them. Line Size When a block of data is retrieved and placed in the cache, not only the desired word but also some number of adjacent words are retrieved. As the block size increases from very small to larger sizes, the hit ratio will at first increase because of the principle of locality, which states that the data in the vicinity of a referenced word are likely to be referenced in the near future. As the block size increases, more useful data are brought into cache. The hit ratio will begin to decrease as the block becomes even bigger and the probability of using the newly fetched information becomes less than the probability of using the newly fetched information that has to be replaced. Two specific effects come into play… Larger blocks reduce the number of blocks that fit into a cache. Because each block fetch overwrites older cache contents, a small number of blocks results in data being overwritten shortly after they are fetched. As a block becomes larger, each additional word is farther from the requested word and therefore less likely to be needed in the near future. The relationship between block size and hit ratio is complex, and no set approach is judged to be the best in all circumstances.   Pentium 4 and ARM cache organizations The processor core consists of four major components: Fetch/decode unit – fetches program instruction in order from the L2 cache, decodes these into a series of micro-operations, and stores the results in the L2 instruction cache Out-of-order execution logic – Schedules execution of the micro-operations subject to data dependencies and resource availability – thus micro-operations may be scheduled for execution in a different order than they were fetched from the instruction stream. As time permits, this unit schedules speculative execution of micro-operations that may be required in the future Execution units – These units execute micro-operations, fetching the required data from the L1 data cache and temporarily storing results in registers Memory subsystem – This unit includes the L2 and L3 caches and the system bus, which is used to access main memory when the L1 and L2 caches have a cache miss and to access the system I/O resources

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  • Oracle SRM increases enterprise footprint with Eloqua integration: an Ovum report

    - by Richard Lefebvre
    At Oracle OpenWorld in September, Oracle announced that Social Relationship Management (SRM) suite is further integrated with Oracle Eloqua, its newly acquired marketing automation platform. "Oracle is the only leading vendor to date to have fully integrated social with a sales lead management platform within the context of marketing automation" writes Gerry Brown in this Ovum report, in which you can read and understand all the benefits of this integration,

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  • Using Ops Center to Provision Solaris using a Card-Based NIC

    - by Larry Wake
    Scott Dickson writes:  "Here's what I want to do:  I have a Sun Fire T2000 server with a Quad-GbE nxge card installed.  The only network is connected to port 2 on that card rather than the built-in network interfaces.  I want to install Solaris on it across the network, either Solaris 10 or Solaris 11." See what he did, using Oracle Enterprise Manager Ops Center 12c. [Read More]

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  • Great Solaris 10 features paving the way to Solaris 11

    - by Larry Wake
    Karoly Vegh writes on the Oracle Systems Blog Austria about what you can do with Solaris 10 today that will get you ready for Solaris 11. Even today, many people still use Solaris 10 as if it were a patch update to Solaris 8 or 9, missing out on the power behind Live Upgrade, Zones, resource management, and ZFS. Learning more about these will help set your feet on the road to the even more sophisticated capabilities of Oracle Solaris 11. [Read More]

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  • System requirement specification vs functional one - separate docs?

    - by user970696
    A lot of sources (e.g. Wikipedia) mentiones System requirement specification and Functional specification as two separate entities. However, Wiegers in his book writes: The software requirements specification is sometimes called a functional specification, a product specification... This is very confusing for me as I thought FS describes just functions while SRS whole system. From this point of view, FS would contain both non functional and functional requirements and everything else.

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  • Watch syntax help

    - by Jason
    In my Systems Programming class, there are weekly programming experiments, and I'm having trouble with the current one. The objective is to write a C program that slowly writes a string of text to a file, metered by usleep() in a 100 count for loop. The goal of the experiment is to observe the file size buffer in action via the watch command. However, I can't get it to work using watch -d ./output What syntax do I need for the watch command to see the changes made to the file size?

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  • Geek City: What gets logged for index rebuild operations?

    - by Kalen Delaney
    This blog post was inspired by a question from a future student. Someone who was already booked for my SQL Server Internals class in June asked for some information on a current problem he was having with transaction log writes causing excessive wait times during index rebuild operations when run in ONLINE mode. He wanted to know if switching to BULK_LOGGED recovery could help. I knew the difference between ALTER INDEX in FULL vs BULK_LOGGED recovery when doing normal OFFLINE rebuilds, but I wasn't...(read more)

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  • Page views in Google Analytics are off compared to a similar metric

    - by tiki16
    We have a page where a user can sign a pledge to recycle by clicking a pledge button. A script writes it to a text file which updates the number on the page. In the past 2 days there have been 185 pledges signed but only 63 page views in GA. I trust that they are unique pledges and not just people adding multiple fake names and entering it. Is there anyway to get a better report from Google Analytics?

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  • Keyboard problem with ubuntu 13.10 when holding key down

    - by Lachezar Raychev
    I have the fallowing problem after isntalling the new Ubuntu OS. When i press and hold a key, for example "p" it writes one time "p", and while i am holding it the other "pppp" that are written come with a huge delay between each other - like 1 second or more. If i want to hold down backspace to delete a string of 5 letters it takes me like 10 seconds to do it. Is this a reported problem or does anybody has a solution to this problem?

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  • IPC in C under linux

    - by poly
    I'm building a messaging solution with the followingsetup: all the messages are saved on a DB, two or more reader processes will read from this DB and send data to other process(es) which will send it over the network. My approach is depicted below, The following have 4 sender process with 4 fifos, and 2 readers with 2 fifos reader0 ? read data from DB reader1 ? read data from DB sending part network_handler0 ? network_handler_fifo0 ? reader0 network_handler1 ? network_handler_fifo1 ? reader1 network_handler2 ? network_handler_fifo2 ? reader0 network_handler3 ? network_handler_fifo3 ? reader1 receiving part network_handler0 ? reader_fifo0 ? reader0 ? write to DB network_handler1 ? reader_fifo1 ? reader1 ? write to DB network_handler2 ? reader_fifo0 ? reader0 ? write to DB network_handler3 ? reader_fifo1 ? reader1 ? write to DB I have few problem with this setup, and please note that the number of processes could be more than that based on the environment, so I could make it 20 readers and 10 network_handlers or it it could as shown above. The size of the buffer is 64K and the message size is 200k, is this small enough to make the write/read to/from fifo atomic? How can make the processes aware of each other, so for example, reader 0 writes to network_handler_fifo0 and network_handler_fifo2, how can I make it start writing on other fifo if the current ones are full or their network_handlers are dea d I thought about making the reader process writing more general in writing, so for example it writes to all network fifos using lock mechanism and stop writing on the one that its process dead, I didn't use it as lock mechanism could slow thing down. BTW, each network_handler is an SCTP association, so network_handler0 is association 0, network_handler1 is association 1 and so on. Any idea is appreciated. I mean even if I have to change the setup above.

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  • Page views in Google Analitics are off compared to a similar metric

    - by tiki16
    We have a page where a user can sign a pledge to recycle by clicking a pledge button. A script writes it to a text file which updates the number on the page. In the past 2 days there have been 185 pledges signed but only 63 page views in GA. I trust that they are unique pledges and not just people adding multiple fake names and entering it. Is there anyway to get a better report from Google Analytics?

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  • Concept: Interpretive Spells [closed]

    - by Deathly
    The goal is to be able to create complex spells, that can manipulate the game's environment in non-preprogrammed ways, and to make the program understand spells. For example: $@ $=Big @=Fire You can probably understand what this one means. The player types, writes, or selects symbols. Of course, a spell can be only a few characters, or more sophisticated spells could potentially be hundreds or thousands of symbols long. How could something like this be accomplished?

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  • How to actually defragment a JFFS2 filesystem

    - by Julie in Austin
    I have searched all over the Internet, including on a number of StackExchange forums, for a workable method for defragmenting a JFFS2 filesystem and cannot find an answer. The system in question has a 256MB NAND flash part. It is being accessed as a MTD device which is divided into three partitions. The third partition is where the root file system is being stored as a JFFS2 file system. The issue is that writes to the root file system have non-deterministic performance due to the usual issues of the JFFS2 garbage collector deciding to run at the worst possible times. When that happens, the product is hung for some unknown length of time while the garbage collector (and pdflush) run. Changing the file system isn't an option. The solution needs to be something that can run during off-hours that after having been run results in more predictable write performance. Right now I am working on a program that will attempt to force the garbage collector to run, then delete the file with the hope that all of the freed nodes are suddenly more readily available and make writes perform better. Thoughts?

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  • Error when reloading supervisord: unix:///tmp/supervisor.sock no such file

    - by Yarin
    I'm running supervisord on my CentOS 6 box like so, /usr/bin/supervisord -c /etc/supervisord.conf and when I launch supervisorctl all process status are fine, but if I try to reload using supervisorctl I get unix:///tmp/supervisor.sock no such file I'm using the same config file I've used successfully on other boxes, and im running everything as root. I can't undesrtand what the problem is... Config file: ; Sample supervisor config file. [unix_http_server] file=/tmp/supervisor.sock ; (the path to the socket file) ;chmod=0700 ; socket file mode (default 0700) ;chown=nobody:nogroup ; socket file uid:gid owner ;username=user ; (default is no username (open server)) ;password=123 ; (default is no password (open server)) ;[inet_http_server] ; inet (TCP) server disabled by default ;port=127.0.0.1:9001 ; (ip_address:port specifier, *:port for all iface) ;username=user ; (default is no username (open server)) ;password=123 ; (default is no password (open server)) [supervisord] logfile=/tmp/supervisord.log ; (main log file;default $CWD/supervisord.log) logfile_maxbytes=50MB ; (max main logfile bytes b4 rotation;default 50MB) logfile_backups=10 ; (num of main logfile rotation backups;default 10) loglevel=info ; (log level;default info; others: debug,warn,trace) pidfile=/tmp/supervisord.pid ; (supervisord pidfile;default supervisord.pid) nodaemon=false ; (start in foreground if true;default false) minfds=1024 ; (min. avail startup file descriptors;default 1024) minprocs=200 ; (min. avail process descriptors;default 200) ;umask=022 ; (process file creation umask;default 022) ;user=chrism ; (default is current user, required if root) ;identifier=supervisor ; (supervisord identifier, default is 'supervisor') ;directory=/tmp ; (default is not to cd during start) ;nocleanup=true ; (don't clean up tempfiles at start;default false) ;childlogdir=/tmp ; ('AUTO' child log dir, default $TEMP) ;environment=KEY=value ; (key value pairs to add to environment) ;strip_ansi=false ; (strip ansi escape codes in logs; def. false) ; the below section must remain in the config file for RPC ; (supervisorctl/web interface) to work, additional interfaces may be ; added by defining them in separate rpcinterface: sections [rpcinterface:supervisor] supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface [supervisorctl] serverurl=unix:///tmp/supervisor.sock ; use a unix:// URL for a unix socket ;serverurl=http://127.0.0.1:9001 ; use an http:// url to specify an inet socket ;username=chris ; should be same as http_username if set ;password=123 ; should be same as http_password if set ;prompt=mysupervisor ; cmd line prompt (default "supervisor") ;history_file=~/.sc_history ; use readline history if available ; The below sample program section shows all possible program subsection values, ; create one or more 'real' program: sections to be able to control them under ; supervisor. ;[program:foo] ;command=/bin/cat [program:embed_scheduler] command=/opt/web-apps/mywebsite/custom_process.py process_name=%(program_name)s_%(process_num)d numprocs=3 ;[program:theprogramname] ;command=/bin/cat ; the program (relative uses PATH, can take args) ;process_name=%(program_name)s ; process_name expr (default %(program_name)s) ;numprocs=1 ; number of processes copies to start (def 1) ;directory=/tmp ; directory to cwd to before exec (def no cwd) ;umask=022 ; umask for process (default None) ;priority=999 ; the relative start priority (default 999) ;autostart=true ; start at supervisord start (default: true) ;autorestart=unexpected ; whether/when to restart (default: unexpected) ;startsecs=1 ; number of secs prog must stay running (def. 1) ;startretries=3 ; max # of serial start failures (default 3) ;exitcodes=0,2 ; 'expected' exit codes for process (default 0,2) ;stopsignal=QUIT ; signal used to kill process (default TERM) ;stopwaitsecs=10 ; max num secs to wait b4 SIGKILL (default 10) ;killasgroup=false ; SIGKILL the UNIX process group (def false) ;user=chrism ; setuid to this UNIX account to run the program ;redirect_stderr=true ; redirect proc stderr to stdout (default false) ;stdout_logfile=/a/path ; stdout log path, NONE for none; default AUTO ;stdout_logfile_maxbytes=1MB ; max # logfile bytes b4 rotation (default 50MB) ;stdout_logfile_backups=10 ; # of stdout logfile backups (default 10) ;stdout_capture_maxbytes=1MB ; number of bytes in 'capturemode' (default 0) ;stdout_events_enabled=false ; emit events on stdout writes (default false) ;stderr_logfile=/a/path ; stderr log path, NONE for none; default AUTO ;stderr_logfile_maxbytes=1MB ; max # logfile bytes b4 rotation (default 50MB) ;stderr_logfile_backups=10 ; # of stderr logfile backups (default 10) ;stderr_capture_maxbytes=1MB ; number of bytes in 'capturemode' (default 0) ;stderr_events_enabled=false ; emit events on stderr writes (default false) ;environment=A=1,B=2 ; process environment additions (def no adds) ;serverurl=AUTO ; override serverurl computation (childutils) ; The below sample eventlistener section shows all possible ; eventlistener subsection values, create one or more 'real' ; eventlistener: sections to be able to handle event notifications ; sent by supervisor. ;[eventlistener:theeventlistenername] ;command=/bin/eventlistener ; the program (relative uses PATH, can take args) ;process_name=%(program_name)s ; process_name expr (default %(program_name)s) ;numprocs=1 ; number of processes copies to start (def 1) ;events=EVENT ; event notif. types to subscribe to (req'd) ;buffer_size=10 ; event buffer queue size (default 10) ;directory=/tmp ; directory to cwd to before exec (def no cwd) ;umask=022 ; umask for process (default None) ;priority=-1 ; the relative start priority (default -1) ;autostart=true ; start at supervisord start (default: true) ;autorestart=unexpected ; whether/when to restart (default: unexpected) ;startsecs=1 ; number of secs prog must stay running (def. 1) ;startretries=3 ; max # of serial start failures (default 3) ;exitcodes=0,2 ; 'expected' exit codes for process (default 0,2) ;stopsignal=QUIT ; signal used to kill process (default TERM) ;stopwaitsecs=10 ; max num secs to wait b4 SIGKILL (default 10) ;killasgroup=false ; SIGKILL the UNIX process group (def false) ;user=chrism ; setuid to this UNIX account to run the program ;redirect_stderr=true ; redirect proc stderr to stdout (default false) ;stdout_logfile=/a/path ; stdout log path, NONE for none; default AUTO ;stdout_logfile_maxbytes=1MB ; max # logfile bytes b4 rotation (default 50MB) ;stdout_logfile_backups=10 ; # of stdout logfile backups (default 10) ;stdout_events_enabled=false ; emit events on stdout writes (default false) ;stderr_logfile=/a/path ; stderr log path, NONE for none; default AUTO ;stderr_logfile_maxbytes=1MB ; max # logfile bytes b4 rotation (default 50MB) ;stderr_logfile_backups ; # of stderr logfile backups (default 10) ;stderr_events_enabled=false ; emit events on stderr writes (default false) ;environment=A=1,B=2 ; process environment additions ;serverurl=AUTO ; override serverurl computation (childutils) ; The below sample group section shows all possible group values, ; create one or more 'real' group: sections to create "heterogeneous" ; process groups. ;[group:thegroupname] ;programs=progname1,progname2 ; each refers to 'x' in [program:x] definitions ;priority=999 ; the relative start priority (default 999) ; The [include] section can just contain the "files" setting. This ; setting can list multiple files (separated by whitespace or ; newlines). It can also contain wildcards. The filenames are ; interpreted as relative to this file. Included files *cannot* ; include files themselves. ;[include] ;files = relative/directory/*.ini

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  • Can compressing Program Files save space *and* give a significant boost to SSD performance?

    - by Christopher Galpin
    Considering solid-state disk space is still an expensive resource, compressing large folders has appeal. Thanks to VirtualStore, could Program Files be a case where it might even improve performance? Discovery In particular I have been reading: SSD and NTFS Compression Speed Increase? Does NTFS compression slow SSD/flash performance? Will somebody benchmark whole disk compression (HD,SSD) please? (may have to scroll up) The first link is particularly dreamy, but maybe head a little too far in the clouds. The third link has this sexy semi-log graph (logarithmic scale!). Quote (with notes): Using highly compressable data (IOmeter), you get at most a 30x performance increase [for reads], and at least a 49x performance DECREASE [for writes]. Assuming I interpreted and clarified that sentence correctly, this single user's benchmark has me incredibly interested. Although write performance tanks wretchedly, read performance still soars. It gave me an idea. Idea: VirtualStore It so happens that thanks to sanity saving security features introduced in Windows Vista, write access to certain folders such as Program Files is virtualized for non-administrator processes. Which means, in normal (non-elevated) usage, a program or game's attempt to write data to its install location in Program Files (which is perhaps a poor location) is redirected to %UserProfile%\AppData\Local\VirtualStore, somewhere entirely different. Thus, to my understanding, writes to Program Files should primarily only occur when installing an application. This makes compressing it not only a huge source of space gain, but also a potential candidate for performance gain. Testing The beginning of this post has me a bit timid, it suggests benchmarking NTFS compression on a whole drive is difficult because turning it off "doesn't decompress the objects". However it seems to me the compact command is perfectly capable of doing so for both drives and individual folders. Could it be only marking them for decompression the next time the OS reads from them? I need to find the answer before I begin my own testing.

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