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  • Multiple copies of JBoss acting as one? [migrated]

    - by scphantm
    I have a few ideas how to solve the problem, but one question about jboss clustering. Please, keep in mind these applications were written very poorly, that is why they require so much memory and there is nothing i can do about that right now. So, I have clustered applications on Jboss where the application was small enough to run on one box. Meaning that one machine could handle the load. But, the current problem is that i have been asked to run several systems on the same environment. Our machines are virtuals and due to limited hardware, are restricted to 8 GB RAM, which gives jboss about 7GB to itself. Unfortunately, that isn't enough to run the group of applications. Im constantly getting heap errors and crashes. If i cluster 2 or 3 jboss instances together, can i run applications that consume more resources than a single box can handle?

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  • DBCC CHECKDB on VVLDB and latches (Or: My Pain is Your Gain)

    - by Argenis
      Does your CHECKDB hurt, Argenis? There is a classic blog series by Paul Randal [blog|twitter] called “CHECKDB From Every Angle” which is pretty much mandatory reading for anybody who’s even remotely considering going for the MCM certification, or its replacement (the Microsoft Certified Solutions Master: Data Platform – makes my fingers hurt just from typing it). Of particular interest is the post “Consistency Options for a VLDB” – on it, Paul provides solid, timeless advice (I use the word “timeless” because it was written in 2007, and it all applies today!) on how to perform checks on very large databases. Well, here I was trying to figure out how to make CHECKDB run faster on a restored copy of one of our databases, which happens to exceed 7TB in size. The whole thing was taking several days on multiple systems, regardless of the storage used – SAS, SATA or even SSD…and I actually didn’t pay much attention to how long it was taking, or even bothered to look at the reasons why - as long as it was finishing okay and found no consistency errors. Yes – I know. That was a huge mistake, as corruption found in a database several days after taking place could only allow for further spread of the corruption – and potentially large data loss. In the last two weeks I increased my attention towards this problem, as we noticed that CHECKDB was taking EVEN LONGER on brand new all-flash storage in the SAN! I couldn’t really explain it, and were almost ready to blame the storage vendor. The vendor told us that they could initially see the server driving decent I/O – around 450Mb/sec, and then it would settle at a very slow rate of 10Mb/sec or so. “Hum”, I thought – “CHECKDB is just not pushing the I/O subsystem hard enough”. Perfmon confirmed the vendor’s observations. Dreaded @BlobEater What was CHECKDB doing all the time while doing so little I/O? Eating Blobs. It turns out that CHECKDB was taking an extremely long time on one of our frankentables, which happens to be have 35 billion rows (yup, with a b) and sucks up several terabytes of space in the database. We do have a project ongoing to purge/split/partition this table, so it’s just a matter of time before we deal with it. But the reality today is that CHECKDB is coming to a screeching halt in performance when dealing with this particular table. Checking sys.dm_os_waiting_tasks and sys.dm_os_latch_stats showed that LATCH_EX (DBCC_OBJECT_METADATA) was by far the top wait type. I remembered hearing recently about that wait from another post that Paul Randal made, but that was related to computed-column indexes, and in fact, Paul himself reminded me of his article via twitter. But alas, our pathologic table had no non-clustered indexes on computed columns. I knew that latches are used by the database engine to do internal synchronization – but how could I help speed this up? After all, this is stuff that doesn’t have a lot of knobs to tweak. (There’s a fantastic level 500 talk by Bob Ward from Microsoft CSS [blog|twitter] called “Inside SQL Server Latches” given at PASS 2010 – and you can check it out here. DISCLAIMER: I assume no responsibility for any brain melting that might ensue from watching Bob’s talk!) Failed Hypotheses Earlier on this week I flew down to Palo Alto, CA, to visit our Headquarters – and after having a great time with my Monkey peers, I was relaxing on the plane back to Seattle watching a great talk by SQL Server MVP and fellow MCM Maciej Pilecki [twitter] called “Masterclass: A Day in the Life of a Database Transaction” where he discusses many different topics related to transaction management inside SQL Server. Very good stuff, and when I got home it was a little late – that slow DBCC CHECKDB that I had been dealing with was way in the back of my head. As I was looking at the problem at hand earlier on this week, I thought “How about I set the database to read-only?” I remembered one of the things Maciej had (jokingly) said in his talk: “if you don’t want locking and blocking, set the database to read-only” (or something to that effect, pardon my loose memory). I immediately killed the CHECKDB which had been running painfully for days, and set the database to read-only mode. Then I ran DBCC CHECKDB against it. It started going really fast (even a bit faster than before), and then throttled down again to around 10Mb/sec. All sorts of expletives went through my head at the time. Sure enough, the same latching scenario was present. Oh well. I even spent some time trying to figure out if NUMA was hurting performance. Folks on Twitter made suggestions in this regard (thanks, Lonny! [twitter]) …Eureka? This past Friday I was still scratching my head about the whole thing; I was ready to start profiling with XPERF to see if I could figure out which part of the engine was to blame and then get Microsoft to look at the evidence. After getting a bunch of good news I’ll blog about separately, I sat down for a figurative smack down with CHECKDB before the weekend. And then the light bulb went on. A sparse column. I thought that I couldn’t possibly be experiencing the same scenario that Paul blogged about back in March showing extreme latching with non-clustered indexes on computed columns. Did I even have a non-clustered index on my sparse column? As it turns out, I did. I had one filtered non-clustered index – with the sparse column as the index key (and only column). To prove that this was the problem, I went and setup a test. Yup, that'll do it The repro is very simple for this issue: I tested it on the latest public builds of SQL Server 2008 R2 SP2 (CU6) and SQL Server 2012 SP1 (CU4). First, create a test database and a test table, which only needs to contain a sparse column: CREATE DATABASE SparseColTest; GO USE SparseColTest; GO CREATE TABLE testTable (testCol smalldatetime SPARSE NULL); GO INSERT INTO testTable (testCol) VALUES (NULL); GO 1000000 That’s 1 million rows, and even though you’re inserting NULLs, that’s going to take a while. In my laptop, it took 3 minutes and 31 seconds. Next, we run DBCC CHECKDB against the database: DBCC CHECKDB('SparseColTest') WITH NO_INFOMSGS, ALL_ERRORMSGS; This runs extremely fast, as least on my test rig – 198 milliseconds. Now let’s create a filtered non-clustered index on the sparse column: CREATE NONCLUSTERED INDEX [badBadIndex] ON testTable (testCol) WHERE testCol IS NOT NULL; With the index in place now, let’s run DBCC CHECKDB one more time: DBCC CHECKDB('SparseColTest') WITH NO_INFOMSGS, ALL_ERRORMSGS; In my test system this statement completed in 11433 milliseconds. 11.43 full seconds. Quite the jump from 198 milliseconds. I went ahead and dropped the filtered non-clustered indexes on the restored copy of our production database, and ran CHECKDB against that. We went down from 7+ days to 19 hours and 20 minutes. Cue the “Argenis is not impressed” meme, please, Mr. LaRock. My pain is your gain, folks. Go check to see if you have any of such indexes – they’re likely causing your consistency checks to run very, very slow. Happy CHECKDBing, -Argenis ps: I plan to file a Connect item for this issue – I consider it a pretty serious bug in the engine. After all, filtered indexes were invented BECAUSE of the sparse column feature – and it makes a lot of sense to use them together. Watch this space and my twitter timeline for a link.

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  • How to Identify Which Hardware Component is Failing in Your Computer

    - by Chris Hoffman
    Concluding that your computer has a hardware problem is just the first step. If you’re dealing with a hardware issue and not a software issue, the next step is determining what hardware problem you’re actually dealing with. If you purchased a laptop or pre-built desktop PC and it’s still under warranty, you don’t need to care about this. Have the manufacturer fix the PC for you — figuring it out is their problem. If you’ve built your own PC or you want to fix a computer that’s out of warranty, this is something you’ll need to do on your own. Blue Screen 101: Search for the Error Message This may seem like obvious advice, but searching for information about a blue screen’s error message can help immensely. Most blue screens of death you’ll encounter on modern versions of Windows will likely be caused by hardware failures. The blue screen of death often displays information about the driver that crashed or the type of error it encountered. For example, let’s say you encounter a blue screen that identified “NV4_disp.dll” as the driver that caused the blue screen. A quick Google search will reveal that this is the driver for NVIDIA graphics cards, so you now have somewhere to start. It’s possible that your graphics card is failing if you encounter such an error message. Check Hard Drive SMART Status Hard drives have a built in S.M.A.R.T. (Self-Monitoring, Analysis, and Reporting Technology) feature. The idea is that the hard drive monitors itself and will notice if it starts to fail, providing you with some advance notice before the drive fails completely. This isn’t perfect, so your hard drive may fail even if SMART says everything is okay. If you see any sort of “SMART error” message, your hard drive is failing. You can use SMART analysis tools to view the SMART health status information your hard drives are reporting. Test Your RAM RAM failure can result in a variety of problems. If the computer writes data to RAM and the RAM returns different data because it’s malfunctioning, you may see application crashes, blue screens, and file system corruption. To test your memory and see if it’s working properly, use Windows’ built-in Memory Diagnostic tool. The Memory Diagnostic tool will write data to every sector of your RAM and read it back afterwards, ensuring that all your RAM is working properly. Check Heat Levels How hot is is inside your computer? Overheating can rsult in blue screens, crashes, and abrupt shut downs. Your computer may be overheating because you’re in a very hot location, it’s ventilated poorly, a fan has stopped inside your computer, or it’s full of dust. Your computer monitors its own internal temperatures and you can access this information. It’s generally available in your computer’s BIOS, but you can also view it with system information utilities such as SpeedFan or Speccy. Check your computer’s recommended temperature level and ensure it’s within the appropriate range. If your computer is overheating, you may see problems only when you’re doing something demanding, such as playing a game that stresses your CPU and graphics card. Be sure to keep an eye on how hot your computer gets when it performs these demanding tasks, not only when it’s idle. Stress Test Your CPU You can use a utility like Prime95 to stress test your CPU. Such a utility will fore your computer’s CPU to perform calculations without allowing it to rest, working it hard and generating heat. If your CPU is becoming too hot, you’ll start to see errors or system crashes. Overclockers use Prime95 to stress test their overclock settings — if Prime95 experiences errors, they throttle back on their overclocks to ensure the CPU runs cooler and more stable. It’s a good way to check if your CPU is stable under load. Stress Test Your Graphics Card Your graphics card can also be stress tested. For example, if your graphics driver crashes while playing games, the games themselves crash, or you see odd graphical corruption, you can run a graphics benchmark utility like 3DMark. The benchmark will stress your graphics card and, if it’s overheating or failing under load, you’ll see graphical problems, crashes, or blue screens while running the benchmark. If the benchmark seems to work fine but you have issues playing a certain game, it may just be a problem with that game. Swap it Out Not every hardware problem is easy to diagnose. If you have a bad motherboard or power supply, their problems may only manifest through occasional odd issues with other components. It’s hard to tell if these components are causing problems unless you replace them completely. Ultimately, the best way to determine whether a component is faulty is to swap it out. For example, if you think your graphics card may be causing your computer to blue screen, pull the graphics card out of your computer and swap in a new graphics card. If everything is working well, it’s likely that your previous graphics card was bad. This isn’t easy for people who don’t have boxes of components sitting around, but it’s the ideal way to troubleshoot. Troubleshooting is all about trial and error, and swapping components out allows you to pin down which component is actually causing the problem through a process of elimination. This isn’t a complete guide to everything that could likely go wrong and how to identify it — someone could write a full textbook on identifying failing components and still not cover everything. But the tips above should give you some places to start dealing with the more common problems. Image Credit: Justin Marty on Flickr     

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  • DBA Best Practices - A Blog Series: Episode 1 - Backups

    - by Argenis
      This blog post is part of the DBA Best Practices series, on which various topics of concern for daily database operations are discussed. Your feedback and comments are very much welcome, so please drop by the comments section and be sure to leave your thoughts on the subject. Morning Coffee When I was a DBA, the first thing I did when I sat down at my desk at work was checking that all backups had completed successfully. It really was more of a ritual, since I had a dual system in place to check for backup completion: 1) the scheduled agent jobs to back up the databases were set to alert the NOC in failure, and 2) I had a script run from a central server every so often to check for any backup failures. Why the redundancy, you might ask. Well, for one I was once bitten by the fact that database mail doesn't work 100% of the time. Potential causes for failure include issues on the SMTP box that relays your server email, firewall problems, DNS issues, etc. And so to be sure that my backups completed fine, I needed to rely on a mechanism other than having the servers do the taking - I needed to interrogate the servers and ask each one if an issue had occurred. This is why I had a script run every so often. Some of you might have monitoring tools in place like Microsoft System Center Operations Manager (SCOM) or similar 3rd party products that would track all these things for you. But at that moment, we had no resort but to write our own Powershell scripts to do it. Now it goes without saying that if you don't have backups in place, you might as well find another career. Your most sacred job as a DBA is to protect the data from a disaster, and only properly safeguarded backups can offer you peace of mind here. "But, we have a cluster...we don't need backups" Sadly I've heard this line more than I would have liked to. You need to understand that a cluster is comprised of shared storage, and that is precisely your single point of failure. A cluster will protect you from an issue at the Operating System level, and also under an outage of any SQL-related service or dependent devices. But it will most definitely NOT protect you against corruption, nor will it protect you against somebody deleting data from a table - accidentally or otherwise. Backup, fine. How often do I take a backup? The answer to this is something you will hear frequently when working with databases: it depends. What does it depend on? For one, you need to understand how much data your business is willing to lose. This is what's called Recovery Point Objective, or RPO. If you don't know how much data your business is willing to lose, you need to have an honest and realistic conversation about data loss expectations with your customers, internal or external. From my experience, their first answer to the question "how much data loss can you withstand?" will be "zero". In that case, you will need to explain how zero data loss is very difficult and very costly to achieve, even in today's computing environments. Do you want to go ahead and take full backups of all your databases every hour, or even every day? Probably not, because of the impact that taking a full backup can have on a system. That's what differential and transaction log backups are for. Have I answered the question of how often to take a backup? No, and I did that on purpose. You need to think about how much time you have to recover from any event that requires you to restore your databases. This is what's called Recovery Time Objective. Again, if you go ask your customer how long of an outage they can withstand, at first you will get a completely unrealistic number - and that will be your starting point for discussing a solution that is cost effective. The point that I'm trying to get across is that you need to have a plan. This plan needs to be practiced, and tested. Like a football playbook, you need to rehearse the moves you'll perform when the time comes. How often is up to you, and the objective is that you feel better about yourself and the steps you need to follow when emergency strikes. A backup is nothing more than an untested restore Backups are files. Files are prone to corruption. Put those two together and realize how you feel about those backups sitting on that network drive. When was the last time you restored any of those? Restoring your backups on another box - that, by the way, doesn't have to match the specs of your production server - will give you two things: 1) peace of mind, because now you know that your backups are good and 2) a place to offload your consistency checks with DBCC CHECKDB or any of the other DBCC commands like CHECKTABLE or CHECKCATALOG. This is a great strategy for VLDBs that cannot withstand the additional load created by the consistency checks. If you choose to offload your consistency checks to another server though, be sure to run DBCC CHECKDB WITH PHYSICALONLY on the production server, and if you're using SQL Server 2008 R2 SP1 CU4 and above, be sure to enable traceflags 2562 and/or 2549, which will speed up the PHYSICALONLY checks further - you can read more about this enhancement here. Back to the "How Often" question for a second. If you have the disk, and the network latency, and the system resources to do so, why not backup the transaction log often? As in, every 5 minutes, or even less than that? There's not much downside to doing it, as you will have to clear the log with a backup sooner than later, lest you risk running out space on your tlog, or even your drive. The one drawback to this approach is that you will have more files to deal with at restore time, and processing each file will add a bit of extra time to the entire process. But it might be worth that time knowing that you minimized the amount of data lost. Again, test your plan to make sure that it matches your particular needs. Where to back up to? Network share? Locally? SAN volume? This is another topic where everybody has a favorite choice. So, I'll stick to mentioning what I like to do and what I consider to be the best practice in this regard. I like to backup to a SAN volume, i.e., a drive that actually lives in the SAN, and can be easily attached to another server in a pinch, saving you valuable time - you wouldn't need to restore files on the network (slow) or pull out drives out a dead server (been there, done that, it’s also slow!). The key is to have a copy of those backup files made quickly, and, if at all possible, to a remote target on a different datacenter - or even the cloud. There are plenty of solutions out there that can help you put such a solution together. That right there is the first step towards a practical Disaster Recovery plan. But there's much more to DR, and that's material for a different blog post in this series.

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  • DBA Best Practices - A Blog Series: Episode 1 - Backups

    - by Argenis
      This blog post is part of the DBA Best Practices series, on which various topics of concern for daily database operations are discussed. Your feedback and comments are very much welcome, so please drop by the comments section and be sure to leave your thoughts on the subject. Morning Coffee When I was a DBA, the first thing I did when I sat down at my desk at work was checking that all backups have completed successfully. It really was more of a ritual, since I had a dual system in place to check for backup completion: 1) the scheduled agent jobs to back up the databases were set to alert the NOC in failure, and 2) I had a script run from a central server every so often to check for any backup failures. Why the redundancy, you might ask. Well, for one I was once bitten by the fact that database mail doesn't work 100% of the time. Potential causes for failure include issues on the SMTP box that relays your server email, firewall problems, DNS issues, etc. And so to be sure that my backups completed fine, I needed to rely on a mechanism other than having the servers do the taking - I needed to interrogate the servers and ask each one if an issue had occurred. This is why I had a script run every so often. Some of you might have monitoring tools in place like Microsoft System Center Operations Manager (SCOM) or similar 3rd party products that would track all these things for you. But at that moment, we had no resort but to write our own Powershell scripts to do it. Now it goes without saying that if you don't have backups in place, you might as well find another career. Your most sacred job as a DBA is to protect the data from a disaster, and only properly safeguarded backups can offer you peace of mind here. "But, we have a cluster...we don't need backups" Sadly I've heard this line more than I would have liked to. You need to understand that a cluster is comprised of shared storage, and that is precisely your single point of failure. A cluster will protect you from an issue at the Operating System level, and also under an outage of any SQL-related service or dependent devices. But it will most definitely NOT protect you against corruption, nor will it protect you against somebody deleting data from a table - accidentally or otherwise. Backup, fine. How often do I take a backup? The answer to this is something you will hear frequently when working with databases: it depends. What does it depend on? For one, you need to understand how much data your business is willing to lose. This is what's called Recovery Point Objective, or RPO. If you don't know how much data your business is willing to lose, you need to have an honest and realistic conversation about data loss expectations with your customers, internal or external. From my experience, their first answer to the question "how much data loss can you withstand?" will be "zero". In that case, you will need to explain how zero data loss is very difficult and very costly to achieve, even in today's computing environments. Do you want to go ahead and take full backups of all your databases every hour, or even every day? Probably not, because of the impact that taking a full backup can have on a system. That's what differential and transaction log backups are for. Have I answered the question of how often to take a backup? No, and I did that on purpose. You need to think about how much time you have to recover from any event that requires you to restore your databases. This is what's called Recovery Time Objective. Again, if you go ask your customer how long of an outage they can withstand, at first you will get a completely unrealistic number - and that will be your starting point for discussing a solution that is cost effective. The point that I'm trying to get across is that you need to have a plan. This plan needs to be practiced, and tested. Like a football playbook, you need to rehearse the moves you'll perform when the time comes. How often is up to you, and the objective is that you feel better about yourself and the steps you need to follow when emergency strikes. A backup is nothing more than an untested restore Backups are files. Files are prone to corruption. Put those two together and realize how you feel about those backups sitting on that network drive. When was the last time you restored any of those? Restoring your backups on another box - that, by the way, doesn't have to match the specs of your production server - will give you two things: 1) peace of mind, because now you know that your backups are good and 2) a place to offload your consistency checks with DBCC CHECKDB or any of the other DBCC commands like CHECKTABLE or CHECKCATALOG. This is a great strategy for VLDBs that cannot withstand the additional load created by the consistency checks. If you choose to offload your consistency checks to another server though, be sure to run DBCC CHECKDB WITH PHYSICALONLY on the production server, and if you're using SQL Server 2008 R2 SP1 CU4 and above, be sure to enable traceflags 2562 and/or 2549, which will speed up the PHYSICALONLY checks further - you can read more about this enhancement here. Back to the "How Often" question for a second. If you have the disk, and the network latency, and the system resources to do so, why not backup the transaction log often? As in, every 5 minutes, or even less than that? There's not much downside to doing it, as you will have to clear the log with a backup sooner than later, lest you risk running out space on your tlog, or even your drive. The one drawback to this approach is that you will have more files to deal with at restore time, and processing each file will add a bit of extra time to the entire process. But it might be worth that time knowing that you minimized the amount of data lost. Again, test your plan to make sure that it matches your particular needs. Where to back up to? Network share? Locally? SAN volume? This is another topic where everybody has a favorite choice. So, I'll stick to mentioning what I like to do and what I consider to be the best practice in this regard. I like to backup to a SAN volume, i.e., a drive that actually lives in the SAN, and can be easily attached to another server in a pinch, saving you valuable time - you wouldn't need to restore files on the network (slow) or pull out drives out a dead server (been there, done that, it’s also slow!). The key is to have a copy of those backup files made quickly, and, if at all possible, to a remote target on a different datacenter - or even the cloud. There are plenty of solutions out there that can help you put such a solution together. That right there is the first step towards a practical Disaster Recovery plan. But there's much more to DR, and that's material for a different blog post in this series.

    Read the article

  • Declaring variables with New DataSet vs DataSet

    - by eych
    What is the impact of creating variables using: Dim ds as New DataSet ds = GetActualData() where GetActualData() also creates a New DataSet and returns it? Does the original empty DataSet that was 'New'ed just get left in the Heap? What if this kind of code was in many places? Would that affect the ASP.NET process and cause it to recycle sooner?

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  • My block is not retaining some of its objects

    - by Drew Crawford
    From the Blocks documentation: In a reference-counted environment, by default when you reference an Objective-C object within a block, it is retained. This is true even if you simply reference an instance variable of the object. I am trying to implement a completion handler pattern, where a block is given to an object before the work is performed and the block is executed by the receiver after the work is performed. Since I am being a good memory citizen, the block should own the objects it references in the completion handler and then they will be released when the block goes out of scope. I know enough to know that I must copy the block to move it to the heap since the block will survive the stack scope in which it was declared. However, one of my objects is getting deallocated unexpectedly. After some playing around, it appears that certain objects are not retained when the block is copied to the heap, while other objects are. I am not sure what I am doing wrong. Here's the smallest test case I can produce: typedef void (^ActionBlock)(UIView*); In the scope of some method: NSObject *o = [[[NSObject alloc] init] autorelease]; mailViewController = [[[MFMailComposeViewController alloc] init] autorelease]; NSLog(@"o's retain count is %d",[o retainCount]); NSLog(@"mailViewController's retain count is %d",[mailViewController retainCount]); ActionBlock myBlock = ^(UIView *view) { [mailViewController setCcRecipients:[NSArray arrayWithObjects:@"[email protected]",nil]]; [o class]; }; NSLog(@"mailViewController's retain count after the block is %d",[mailViewController retainCount]); NSLog(@"o's retain count after the block is %d",[o retainCount]); Block_copy(myBlock); NSLog(@"o's retain count after the copy is %d",[o retainCount]); NSLog(@"mailViewController's retain count after the copy is %d",[mailViewController retainCount]); I expect both objects to be retained by the block at some point, and I certainly expect their retain counts to be identical. Instead, I get this output: o's retain count is 1 mailViewController's retain count is 1 mailViewController's retain count after the block is 1 o's retain count after the block is 1 o's retain count after the copy is 2 mailViewController's retain count after the copy is 1 o (subclass of NSObject) is getting retained properly and will not go out of scope. However mailViewController is not retained and will be deallocated before the block is run, causing a crash.

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  • Sun permgen & JRockit garbage collection

    - by Striker
    In the Sun JVM, classes that are loaded by the class loader are put in permgen space and never gc'd. (Unless the class loader goes out of scope) It's my understanding that JRockit puts that same data on the heap instead. Is that data then subject to garbage collection? Thanks.

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  • How to implement continuations?

    - by Kyle Cronin
    I'm working on a Scheme interpreter written in C. Currently it uses the C runtime stack as its own stack, which is presenting a minor problem with implementing continuations. My current solution is manual copying of the C stack to the heap then copying it back when needed. Aside from not being standard C, this solution is hardly ideal. What is the simplest way to implement continuations for Scheme in C?

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  • what is the reason of Invalid Address specified to RtlFreeHeap

    - by carl
    the develop environment is vs2008, the language is c++, when I release the problem,at beginning it run with out problem but after several minutes it stop and show error like that : HEAP[guessModel.exe]: Invalid Address specified to RtlFreeHeap( 003E0000, 7D7C737B ). who can tell me the reason of the error. thank you very much.

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  • Experience of moving to 64 bit JVM

    - by Fazal
    Our company is planning to move to 64 bit JVM in order to get away from 2 GB maximum heap size limit. Google gave me very mixed results about 64 bit JVM performance. Has anyone tried moving to 64 bit java and share your experience

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  • Javascript running in facebox window

    - by Rudiger
    I'm modifying a website to have a pop up box appear when a user rates something prompting the user to login. Unfortunately the login process is something that I don't control and it uses a whole heap of javascript and redirects to do it and it seems that the javascript is failing. Can javascript run in the modal box or is there a way around this?

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  • Memory layout of executable

    - by Ross
    Hi all, When loading an executable then segments like the code, data, bss and so on need to be placed in memory. I am just wondering, if someone could tell me where on a standard x86 for example the libc library is placed. Is that at the top or bottom of memory. My guess is at the bottom, close to the application code, ie., that would look something like this here: --------- 0x1000 Stack | V ^ | Heap ---------- Data + BSS ---------- App Code ---------- libc ---------- 0x0000 Thanks a lot, Ross

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  • Some questions about Vector in STL

    - by skydoor
    I have some questions about vector in STL to clarify..... Where are the objects in vector allocated? heap? does vector have boundary check? If the index out of the boundary, what error will happen? Why array is faster than vector? Is there any case in which vector is not applicable but array is a must?

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  • Strip OLE header information (MS Access / SQL Server)

    - by crimson13
    I have a C++ application that needs to support binary database content (images, etc). When using MS Access or MS SQL Server this data is wrapped inside an OLE object. How do I strip this OLE header information? Note that I can't just look for the beginning of a specific tag as the content can be png, jpg and a whole heap of other formats. Should I use something like COleDataObject?

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  • Good Postgres graphical client for Windows

    - by alex
    The name pretty much says it all. Right now I'm using Squirrel - it crashes frequently and suffers from memory problems (I've tried increasing the heap size). I don't need anything particularly fancy or full-featured - just something that won't take up 2.4 GB of RAM to store a 1.5 million line, 8 column result set.

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  • Memory efficient int-int dict in Python

    - by Bolo
    Hi, I need a memory efficient int-int dict in Python that would support the following operations in O(log n) time: d[k] = v # replace if present v = d[k] # None or a negative number if not present I need to hold ~250M pairs, so it really has to be tight. Do you happen to know a suitable implementation (Python 2.7)? EDIT Removed impossible requirement and other nonsense. Thanks, Craig and Kylotan! To rephrase. Here's a trivial int-int dictionary with 1M pairs: >>> import random, sys >>> from guppy import hpy >>> h = hpy() >>> h.setrelheap() >>> d = {} >>> for _ in xrange(1000000): ... d[random.randint(0, sys.maxint)] = random.randint(0, sys.maxint) ... >>> h.heap() Partition of a set of 1999530 objects. Total size = 49161112 bytes. Index Count % Size % Cumulative % Kind (class / dict of class) 0 1 0 25165960 51 25165960 51 dict (no owner) 1 1999521 100 23994252 49 49160212 100 int On average, a pair of integers uses 49 bytes. Here's an array of 2M integers: >>> import array, random, sys >>> from guppy import hpy >>> h = hpy() >>> h.setrelheap() >>> a = array.array('i') >>> for _ in xrange(2000000): ... a.append(random.randint(0, sys.maxint)) ... >>> h.heap() Partition of a set of 14 objects. Total size = 8001108 bytes. Index Count % Size % Cumulative % Kind (class / dict of class) 0 1 7 8000028 100 8000028 100 array.array On average, a pair of integers uses 8 bytes. I accept that 8 bytes/pair in a dictionary is rather hard to achieve in general. Rephrased question: is there a memory-efficient implementation of int-int dictionary that uses considerably less than 49 bytes/pair?

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  • java dynamic memory allocation?

    - by JavaUser
    Hi, Why an object initialization using " new " keyword is called as dynamic memory allocation since compile time itself we know the memory needed for that object . Also please explain what happen when u do ClassA object = new ClassA(); in heap and stack . Thx

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