I get that Postgres scales automatically to multicore with multiple connections, but what about when I'm running a massive query on a SINGLE connection? So frustrating that the CPU usage maxes out at 25% on my 4-core system.
I'm in process of switching from SQL Server and this is the only thing so far that really bugs me. SQL Server will use up to 100% of my CPU for a single connection/query.
I'm running 9.2 on Windows 7 Enterprise 64-bit with Xeon processor if it matters.
If there is not way to get around this, could someone address why this isn't seen as an issue? Is it because Postgres is focused on multi-user scenarios?
PostgreSQL does not currently support executing a single query across multiple CPU cores (minus background things like background writing and wal writing if you're doing a write query, but that doesn't really count). It's work that's in progress, but it's a long-term project, and is not in any current version of PostgreSQL.
This is the same on all platforms and architectures.
It is definitely an issue, but since PostgreSQL is, as you say, focused on multi user scenarios, it's not bubbled to the top of the priority queue until recently. But there are definitely people realizing it's an issue, and working on solving it for future versions, it's just not done yet.
There is a Foreign Data Wrapper that aims to add parallelism via the GPU called pg_strom. I've never used it, and it looks quite specialized, but maybe you (or someone here) has a use-case for it.
Article describing pg_strom
http://gpuscience.com/software/postgresql-gpu-pgstrom/
The code:
https://github.com/kaigai/pg_strom
It's not that it isn't seen as a problem. It's that it requires fundamental architectural changes. The use case for it is pretty specialised. It would only help on data warehouse type environments where you're executing long queries one at a time -- AND the queries are CPU bound, not disk i/o bound as they would usually be.
I recently got a shiny new development workstation. The only disadvantage of this is that the desktop apps I'm developing now run very, very fast, and so I fear that parts of the code that would be annoyingly slow on end users' machines will go unnoticed during my testing.
Is there a good way to slow down an application for testing? I've tried searching around, but all of the results I've been able to find seem pretty fiddly to set up (e.g., manually setting up a high-priority CPU-bound task on the same CPU core as the target app, or running a background process that rapidly interrupts and resumes the target app), and I don't know if the end result is actually a good representation of running on a slower computer (with its slower CPU, slower RAM, slower disk I/O...).
I don't think that this is a job for a profiler; I'm interested in the user's perception of end-to-end performance rather than in where the time goes for particular operations.
setup a virtual machine, give in as little ram as needed and also you can have it use 1,2 or more CPUs. I like VirtualBox myself install your app and test with different RAM configs
Personally, I'd get an old used crappy computer that is typical of what the users have and test on that. It should be cheap and you will see pretty fast how bad things are.
I think the only way to deal with this is through proper end-user testing, i.e. get yourself a "typical" system for testing and use that to identify any perceptible performance bottlenecks.
You can try out either Virtual PC or VMWare Player/Workstation, load an OS onto it, and then throttle back the resources. I know that with any of those tools you can reduce the memory to whatever you'd like. You can also specify the number of cores you want to use. You might even be able to adjust the clock speed in VMWare Workstation... I'm not sure.
I upvoted SQLMenace's answer, but, I also think that profiling needs to be mentioned, no matter how quickly the code is executing - you'll still see what's taking the most time. If you find yourself with some free time, I think profiling and investigating the results is a good way to spend it.
As one who is relatively new to the whole support and bug fixing environment and a young programmer I had never come across a bug that only occurs in the Websphere environment but not on the localhost test enviroment, until today. When I first got this bug report I was confused as to why I couldn't reproduce it on the localhost test environment. I decided to try on the Websphere test environment to see what would happen and I successfully reproduced the bug. The problem is I can't make changes and build to the Websphere test enviroment. I can only make changes to my local environment. Given this handicap what methodologies exist for resolving these kinds of bugs. Or are there even any methodologies at all? Any advice or help on how to approach issues like this?
Campaign for full access to a test environment. Being able to tweak things, redeploy and retry makes a huge difference. It's entirely reasonable to explain how not having access severely restricts your ability to do your job.
Make sure you've got sufficient logging, and make it configurable. Make sure you keep the logs for long enough to track down a problem reported by a customer even if it happened a few days ago.
When you finally diagnose a problem and why it only happens in a particular environment, document it and try to persuade your local system to behave the same way - that should make it easier to diagnose another symptom of the same problem next time.
In short, the methodology is to isolate and understand the differences between environments and which one or ones might be causing the issue.
Check your local build. Make sure it the same version (code and database) as Test and Prod. If it is, what are the environment differences that could effect the issue you are seeing? (Multi-core, load balancing, operating system version, 3rd library version). Don't run locally in the debugger, make sure your running a release build (if that's what is on Test and Prod) and maybe even do a local deployment rather than building from source.
Check to see if it is particular data that might be causing the problem. If you can, pull a copy of the database back from Test onto Local and see if that enables you to repro the problem.
Check with other developers. See if they can repro. the issue in their environment. Check with your QA guys, get their thoughts on what might be causing such an issue (often times they will have seen "similar" issues and might give you a clue).
At that point, if nothing helps, I generally go into a deep state of zen to try and understand what I am missing. But, there must be a difference, you just have to find it.
The Scientific Method always applies-- check your assumptions first. If the systems are different, the problem might reside in some sort of implicit default being different, or a different implementation of some function.
In all debugging processes, localization is the key. You gotta isolate the area of the problem first. If your OS, patches, libraries, and the main software itself are all identical, then it's probably the system settings (limits for sockets, file descriptors, etc). If you know you have enough inodes, space and memory left, then it's not a resource issue. If the computer is barely responsive to your interactive prodding, your load is too high, or you have some runaway processes. Remember what every process needs to run, and make sure they got what they need.
It can be also code just can't deal with the load of the production system. Locking mechanisms are a very popular cause of problem in production vs dev/test systems, simply because you can't generate enough of test cases that you get for free in production.
Logging can be easily overlooked, but I also like to add a lot of debug values into the code, to make debugging easier. I cannot even count how many times some environment variable, path, or broken symlink have ruined my day, just to realize that it would be a trivial fix if I looked at the values of variables while running, not just looking at the static code.
If all else fails, ltrace and strace are the best way to really look at what's going on under the hood. They're not easy to read, but once you get used to how spot and interpret return values of some syscalls, you gain a very powerful debugging tool.
The question says it all. If you have a bug that multiple users report, but there is no record of the bug occurring in the log, nor can the bug be repeated, no matter how hard you try, how do you fix it? Or even can you?
I am sure this has happened to many of you out there. What did you do in this situation, and what was the final outcome?
Edit:
I am more interested in what was done about an unfindable bug, not an unresolvable bug. Unresolvable bugs are such that you at least know that there is a problem and have a starting point, in most cases, for searching for it. In the case of an unfindable one, what do you do? Can you even do anything at all?
Language
Different programming languages will have their own flavour of bugs.
C
Adding debug statements can make the problem impossible to duplicate because the debug statement itself shifts pointers far enough to avoid a SEGFAULT---also known as Heisenbugs. Pointer issues are arduous to track and replicate, but debuggers can help (such as GDB and DDD).
Java
An application that has multiple threads might only show its bugs with a very specific timing or sequence of events. Improper concurrency implementations can cause deadlocks in situations that are difficult to replicate.
JavaScript
Some web browsers are notorious for memory leaks. JavaScript code that runs fine in one browser might cause incorrect behaviour in another browser. Using third-party libraries that have been rigorously tested by thousands of users can be advantageous to avoid certain obscure bugs.
Environment
Depending on the complexity of the environment in which the application (that has the bug) is running, the only recourse might be to simplify the environment. Does the application run:
on a server?
on a desktop?
in a web browser?
In what environment does the application produce the problem?
development?
test?
production?
Exit extraneous applications, kill background tasks, stop all scheduled events (cron jobs), eliminate plug-ins, and uninstall browser add-ons.
Networking
As networking is essential to so many applications:
Ensure stable network connections, including wireless signals.
Does the software reconnect after network failures robustly?
Do all connections get closed properly so as to release file descriptors?
Are people using the machine who shouldn't be?
Are rogue devices interacting with the machine's network?
Are there factories or radio towers nearby that can cause interference?
Do packet sizes and frequency fall within nominal ranges?
Are packets being monitored for loss?
Are all network devices adequate for heavy bandwidth usage?
Consistency
Eliminate as many unknowns as possible:
Isolate architectural components.
Remove non-essential, or possibly problematic (conflicting), elements.
Deactivate different application modules.
Remove all differences between production, test, and development. Use the same hardware. Follow the exact same steps, perfectly, to setup the computers. Consistency is key.
Logging
Use liberal amounts of logging to correlate the time events happened. Examine logs for any obvious errors, timing issues, etc.
Hardware
If the software seems okay, consider hardware faults:
Are the physical network connections solid?
Are there any loose cables?
Are chips seated properly?
Do all cables have clean connections?
Is the working environment clean and free of dust?
Have any hidden devices or cables been damaged by rodents or insects?
Are there bad blocks on drives?
Are the CPU fans working?
Can the motherboard power all components? (CPU, network card, video card, drives, etc.)
Could electromagnetic interference be the culprit?
And mostly for embedded:
Insufficient supply bypassing?
Board contamination?
Bad solder joints / bad reflow?
CPU not reset when supply voltages are out of tolerance?
Bad resets because supply rails are back-powered from I/O ports and don't fully discharge?
Latch-up?
Floating input pins?
Insufficient (sometimes negative) noise margins on logic levels?
Insufficient (sometimes negative) timing margins?
Tin whiskers?
ESD damage?
ESD upsets?
Chip errata?
Interface misuse (e.g. I2C off-board or in the presence of high-power signals)?
Race conditions?
Counterfeit components?
Network vs. Local
What happens when you run the application locally (i.e., not across the network)? Are other servers experiencing the same issues? Is the database remote? Can you use a local database?
Firmware
In between hardware and software is firmware.
Is the computer BIOS up-to-date?
Is the BIOS battery working?
Are the BIOS clock and system clock synchronized?
Time and Statistics
Timing issues are difficult to track:
When does the problem happen?
How frequently?
What other systems are running at that time?
Is the application time-sensitive (e.g., will leap days or leap seconds cause issues)?
Gather hard numerical data on the problem. A problem that might, at first, appear random, might actually have a pattern.
Change Management
Sometimes problems appear after a system upgrade.
When did the problem first start?
What changed in the environment (hardware and software)?
What happens after rolling back to a previous version?
What differences exist between the problematic version and good version?
Library Management
Different operating systems have different ways of distributing conflicting libraries:
Windows has DLL Hell.
Unix can have numerous broken symbolic links.
Java library files can be equally nightmarish to resolve.
Perform a fresh install of the operating system, and include only the supporting software required for your application.
Java
Make sure every library is used only once. Sometimes application containers have a different version of a library than the application itself. This might not be possible to replicate in the development environment.
Use a library management tool such as Maven or Ivy.
Debugging
Code a detection method that triggers a notification (e.g., log, e-mail, pop-up, pager beep) when the bug happens. Use automated testing to submit data into the application. Use random data. Use data that covers known and possible edge cases. Eventually the bug should reappear.
Sleep
It is worth reiterating what others have mentioned: sleep on it. Spend time away from the problem, finish other tasks (like documentation). Be physically distant from computers and get some exercise.
Code Review
Walk through the code, line-by-line, and describe what every line does to yourself, a co-worker, or a rubber duck. This may lead to insights on how to reproduce the bug.
Cosmic Radiation
Cosmic Rays can flip bits. This is not as big as a problem in the past due to modern error checking of memory. Software for hardware that leaves Earth's protection is subject to issues that simply cannot be replicated due to the randomness of cosmic radiation.
Tools
Sometimes, albeit infrequently, the compiler will introduce a bug, especially for niche tools (e.g. a C micro-controller compiler suffering from a symbol table overflow). Is it possible to use a different compiler? Could any other tool in the tool-chain be introducing issues?
If it's a GUI app, it's invaluable to watch the customer generate the error (or try to). They'll no doubt being doing something you'd never have guessed they were doing (not wrongly, just differently).
Otherwise, concentrate your logging in that area. Log most everything (you can pull it out later) and get your app to dump its environment as well. e.g. machine type, VM type, encoding used.
Does your app report a version number, a build number, etc.? You need this to determine precisely which version you're debugging (or not!).
If you can instrument your app (e.g. by using JMX if you're in the Java world) then instrument the area in question. Store stats e.g. requests+parameters, time made, etc. Make use of buffers to store the last 'n' requests/responses/object versions/whatever, and dump them out when the user reports an issue.
If you can't replicate it, you may fix it, but can't know that you've fixed it.
I've made my best explanation about how the bug was triggered (even if I didn't know how that situation could come about), fixed that, and made sure that if the bug surfaced again, our notification mechanisms would let a future developer know the things that I wish I had known. In practice, this meant adding log events when the paths which could trigger the bug were crossed, and metrics for related resources were recorded. And, of course, making sure that the tests exercised the code well in general.
Deciding what notifications to add is a feasability and triage question. So is deciding on how much developer time to spend on the bug in the first place. It can't be answered without knowing how important the bug is.
I've had good outcomes (didn't show up again, and the code was better for it), and bad (spent too much time not fixing the problem, whether the bug ended up fixed or not). That's what estimates and issue priorities are for.
Sometimes I just have to sit and study the code until I find the bug. Try to prove that the bug is impossible, and in the process you may figure out where you might be mistaken. If you actually succeed in convincing yourself it's impossible, assume you messed up somewhere.
It may help to add a bunch of error checking and assertions to confirm or deny your beliefs/assumptions. Something may fail that you'd never expect to.
It can be difficult, and sometimes near impossible. But my experience is, that you will sooner or later be able to reproduce and fix the bug, if you spend enough time on it (if that spent time is worth it, is another matter).
General suggestions that might help in this situation.
Add more logging, if possible, so that you have more data the next time the bug appears.
Ask the users, if they can replicate the bug. If yes, you can have them replicate it while watching over their shoulder, and hopefully find out, what triggers the bug.
Make random changes until something works :-)
Assuming you have already added all the logging that you think would help and it didn't... two things spring to mind:
Work backwards from the reported symptom. Think to yourself.. "it I wanted to produce the symptom that was reported, what bit of code would I need to be executing, and how would I get to it, and how would I get to that?" D leads to C leads to B leads to A. Accept that if a bug is not reproducible, then normal methods won't help. I've had to stare at code for many hours with these kind of thought processes going on to find some bugs. Usually it turns out to be something really stupid.
Remember Bob's first law of debugging: if you can't find something, it's because you're looking in the wrong place :-)
Think. Hard. Lock yourself away, admit no interuptions.
I once had a bug where the evidence was a hex dump of a corrupt database. The chains of pointers were systematically screwed up. All the user's programs, and our database software, worked faultlessly in testing. I stared at it for a week (it was an important customer), and after eliminating dozens of possible ideas, I realised that the data was spread across two physical files and the corruption occurred where the chains crossed file boundaries. I realized that if a backup/restore operation failed at a critical point, the two files could end up "out of sync", restored to different time points. If you then ran one of the customer's programs on the already-corrupt data, it would produce exactly the knotted chains of pointers I was seeing. I then demonstrated a sequence of events that reproduced the corruption exactly.
modify the code where you think the problem is happening, so extra debug info is recorded somewhere. when it happens next time, you will have what your need to solve the problem.
There are two types of bugs you can't replicate. The kind you discovered, and the kind someone else discovered.
If you discovered the bug, you should be able to replicate it. If you can't replicate it, then you simply haven't considered all of the contributing factors leading towards the bug. This is why whenever you have a bug, you should document it. Save the log, get a screenshot, etc. If you don't, then how can you even prove the bug really exists? Maybe it's just a false memory?
If someone else discovered a bug, and you can't replicate it, obviously ask them to replicate it. If they can't replicate it, then you try to replicate it. If you can't replicate it quickly, ignore it.
I know that sounds bad, but I think it is justified. The amount of time it will take you to replicate a bug that someone else discovered is very large. If the bug is real, it will happen again naturally. Someone, maybe even you, will stumble across it again. If it is difficult to replicate, then it is also rare, and probably won't cause too much damage if it happens a few more times.
You can be a lot more productive if you spend your time actually working, fixing other bugs and writing new code, than you will be trying to replicate a mystery bug that you can't even guarantee actually exists. Just wait for it to appear again naturally, then you will be able to spend all your time fixing it, rather than wasting your time trying to reveal it.
Discuss the problem, read code, often quite a lot of it. Often we do it in pairs, because you can usually eliminate the possibilities analytically quite quickly.
Start by looking at what tools you have available to you. For example crashes on a Windows platform go to WinQual, so if this is your case you now have crash dump information. Do you can static analysis tools that spot potential bugs, runtime analysis tools, profiling tools?
Then look at the input and output. Anything similar about the inputs in situations when users report the error, or anything out of place in the output? Compile a list of reports and look for patterns.
Finally, as David stated, stare at the code.
Ask user to give you a remote access for his computer and see everything yourself. Ask user to make a small video of how he reproduces this bug and send it to you.
Sure both are not always possible but if they are it may clarify some things. The common way of finding bugs are still the same: separating parts that may cause bug, trying to understand what`s happening, narrowing codespace that could cause the bug.
There are tools like gotomeeting.com, which you can use to share screen with your user and observe the behaviour. There could be many potential problems like number of softwares installed on their machines, some tools utility conflicting with your program. I believe gotomeeting, is not the only solution, but there could be timeout issues, slow internet issue.
Most of times I would say softwares do not report you correct error messages, for example, in case of java and c# track every exceptions.. dont catch all but keep a point where you can catch and log. UI Bugs are difficult to solve unless you use remote desktop tools. And most of time it could be bug in even third party software.
If you work on a real significant sized application, you probably have a queue of 1,000 bugs, most of which are definitely reproducible.
Therefore, I'm afraid I'd probably close the bug as WORKSFORME (Bugzilla) and then get on fixing some more tangible bugs. Or doing whatever the project manager decides to do.
Certainly making random changes is a bad idea, even if they're localised, because you risk introducing new bugs.