I currently have a GUI single-threaded application in C++ and Qt. It takes a good 1 minute to load (read from disk) and ~5 seconds to close (saving settings, finalize connections, ...).
What can I do to make my application appear to be faster?
My first thought was to have a server component of the app that does all the works while the GUI component is only for displaying. The communication is done via socket, pipe or memory map. That seems like an overkill (in term of development effort) since my application is only used by a handful of people.
The first step is to start profiling. Use an actual, low-overhead profiling tool (eg, on Linux, you could use oprofile), not guesswork. What is your app doing in that one minute it takes to start up? Can any of that work be deferred until later, or perhaps skipped entirely?
For example, if you're loading, say, a list of document templates, you could defer that until the user tells you to create a new document. If you're scanning the system for a list of fonts, load a cached list from last startup and use that until you finish updating the font list in a separate thread. These are just examples - use a profiler to figure out where the time's actually going, and then attack the code starting with the largest time figures.
In any case, some of the more effective approaches to keep in mind:
Skip work until needed. If you're doing initialization for some feature that's used infrequently, skip it until that feature is actually used.
Defer work until after startup. You can take care of a lot of things on a separate thread while the UI is responsive. If you are collecting information that changes infrequently but is needed immediately, consider caching the value from a previous run, then updating it in the background.
For your shutdown time, hide your GUI instantly, and then spend those five seconds shutting down in the background. As long as the user doesn't notice the work, it might as well be instantaneous.
You could employ the standard trick of showing something interesting while you load.
Like many games nowadays show a tip or two while they are loading
It looks to me like you're only guessing at where all this time is being burned. "Read from disk" would not be high on my list of candidates. Learn more about what's really going on.
Use a decent profiler.
Profiling is a given, of course.
Most likely, you may find I/O is substantial - reading in your startup files. As bdonlan notes, deferring work is a standard technique. Google 'lazy evaluation'.
You can also consider caching data that does not change. Save a cache in a faster format, such as binary. This is most useful if you happen to have a large static data set read into something like an array.
Related
I'm building in C++ what can be easily described as an app that graphically shows the evolution in time of a system of partial differential equation (PDE from now on).
A list of important constraints:
The user provides the PDE system by writing them using a simplified programming code in a txt.
The user then launches the app. As interpreting is not viable (see below), the PDE txt must be read here, but there are not heavy time limits - the user can well tolerate anything from ten seconds up to a minute of loading.
When the app is ready, the user can and will ask it to update the system potentially hundreds of times per second, which is by far the biggest performance bottleneck in the app - imagine 10-100 intertwined PDE, with 1k - 10k spatial locations interacting with each other.
No third-party software must be installed on the user machine. I can't ask the user to compile code or anything like that; anything more complex than editing that txt and launching the app is off chart.
(Lesser constraint, which can be dropped) It would be cool to be able to edit the txt and reload it while the app is running through a proper UI.
As you can see, I need to parse this txt (easily done) and use its contents in the tightest (performance-wise) cycle of the app. So I can't interpret it on the fly as it would have nightmarish performance. Even if I store a parsed tree of the txt, running through the tree every iteration would still have a lot of overhead.
I know, as I saw it working, that something like this can be done with good enough performance. So how is it done? Can you dinamically create something that has similar execution time to a statically compiled function?
Any link to materials would be appreciated.
There are C++ desktop application, and i need to measure UI lags because users say that it sometimes lags. How can i implement this ? Tried to use pywinauto with timer start-stop after actions, but it clicks the elements very slowly. On the other side, tried to use SikuliX, it works faster, but very flaky. And another tried solution is uberAgent but it detects all performance subsidence performance, even what is not needed.
To speed up the elements search I'd recommend using .child_window(title="...", control_type="...") specifications instead of best_match names like app.Dialog.OKButton which is usually slow. Preliminary filtering by control_type is extremely fast because it even doesn't need cross-process interaction while getting title/text requires at least 2 cross-process operations: get length and get text then. So pre-filtered list of elements can dramatically reduce number of text retrievals.
Also pywinauto has little pause after some actions like 0.001 sec. inside .click_input(). These pauses can be zeroed in pywinauto.timings module but it can make the automation flaky in some cases. So try it at your own risk.
This question is a refinement of my question Different ways of observing data changes.
I still have a lot of classes in my C++ application, which are updated (or could be updated) frequently in complex mathematical routines and in complex pieces of business logic.
If I go for the 'observer' approach, and send out notifications every time a value of an instance is changed, I have 2 big risks:
sending out the notifications itself may slow down the applications seriously
if user interface elements need to be updated by the change, they are updated with every change, resulting in e.g. screens being updated thousends of times while some piece of business logic is executing
Some problems may be solved by adding buffering-mechanisms (where you send out notifications when you are going to start with an algorith, and when the algorithm is finished), but since the business logic may be executed on many places in the software, we end up adding buffering almost everywhere, after every possible action chosen in the menu.
Instead of the 'observer' aproach, I could also use the 'mark-dirty' approach, only marking the instances that have been altered, and at the end of the action telling the user interface that it should update itself.
Again, business logic may be executed from everywhere within the application, so in practice we may have to add an extra call (telling all windows they should update themselves) after almost every action executed by the user.
Both approaches seem to have similar, but opposite disadvantages:
With the 'observer' approach we have the risk of updating the user-interface too many times
With the 'mark-dirty' approach we have the risk of not updating the user-interface at all
Both disadvantages could be solved by embedding every application action within additional logic (for observers: sending out start-end notifications, for mark-dirty: sending out update-yourself notifications).
Notice that in non-windowing applications this is probably not a problem. You could e.g. use the mark-dirty approach and only if some calculation needs the data, it may need to do some extra processing in case the data is dirty (this is a kind of caching approach).
However, for windowing applications, there is no signal that the user is 'looking at your screen' and that the windows should be updated. So there is no real good moment where you have to look at the dirty-data (although you could do some tricks with focus-events).
What is a good solution to solve this problem? And how have you solved problems like this in your application?
Notice that I don't want to introduce windowing techniques in the calculation/datamodel part of my application. If windowing techniques are needed to solve this problem, it must only be used in the user-interface part of my application.
Any idea?
An approach I used was with a large windows app a few years back was to use WM_KICKIDLE. All things that are update-able utilise a abstract base class called IdleTarget. An IdleTargetManager then intercepts the KICKIDLE messages and calls the update on a list of registered clients. In your instance you could create a list of specific targets to update but I found the list of registered clients enough.
The only gotcha I hit was with a realtime graph. Using just the kick idle message it would spike the CPU to 100% due to constant updating of the graph. Use a timer to sleep until the next refresh solved that problem.
If you need more assistance - I am available at reasonable rates...:-)
Another point I was thinking about.
If you are overwhelmed by the number of events generated, and possibly the extra-work it is causing, you may have a two phases approach:
Do the work
Commit
where notifications are only sent on commit.
It does have the disadvantage of forcing to rewrite some code...
You could use the observer pattern with coalescing. It might be a little ugly to implement in C++, though. It would look something like this:
m_observerList.beginCoalescing();
m_observerList.notify();
m_observerList.notify();
m_observerList.notify();
m_observerList.endCoalescing(); //observers are notified here, only once
So even though you call notify three times, the observers aren't actually notified until endCoalescing when the observers are only notified once.
I currently have a django site, and it's kind of slow, so I want to understand what's going on. How can I profile it so to differentiate between:
effect of the network
effect of the hosting I'm using
effect of the javascript
effect of the server side execution (python code) and sql access.
any other effect I am not considering due to the massive headache I happen to have tonight.
Of course, for some of them I can use firebug, but some effects are correlated (e.g. javascript could appear slow because it's doing slow network access)
Thanks
client side:
check with firebug if/which page components take long to load, and how long the browser needs to render the page after loading is completed. If everything is fast but rendering takes its time, then probably your html/css/js is the problem, otherwise it's server side.
server side (i assume you sit on some unix-alike server):
check the web server with a small static content (a small gif or a little html page), using apache bench (ab, part of the apache webserver package) or httperf, the server should be able to answerat least 100 requests per second (of course this depends heavily on the size of your test content, webserver type, hardware and other stuff, so dont take that 100 to seriously). if that looks good,
test django with ab or httperf on a "static view" (one that doesnt use a database object), if thats slow it's a hint that you need more cpu power. check cpu utilization on the server with top. if thats ok, the problem might be in the way the web server executes the python code
if serving semi-static content is ok, your problem might be the database or IO-bound. Database problems are a wide field, here is some general advice:
check i/o throughput with iostat. if you see lot's of writes then you have get a better disc subsystem, faster raid, SSD hard drives .. or optimize your application to write less.
if its lots of reads, the host might not have enough ram dedicated as file system buffer, or your database queries might not be optimized
if i/o looks ok, then the database might be not be suited for your workload or not correctly configured. logging slow queries and monitoring database activity, locks etc might give you some idea
if you let us know what hardware/software you use i might be able to give more detailed advice
edit/PS: forgot one thing: of course your app might have a bad design and does lots of unnecessary/inefficient things ...
Take a look at the Django debug toolbar - that'll help you with the server side code (e.g. what database queries ran and how long they took); and is generally a great resource for Django development.
The other non-Django specific bits you could profile with yslow.
There are various tools, but problems like this are not hard to find because they are big.
You have a problem, and when you remove it, you will experience a speedup. Suppose that speedup is some factor, like 2x. That means the program is spending 50% of its time waiting for the slow part. What I do is just stop it a few times and see what it's waiting for. In this case, I would see the problem 50% of the times I stop it.
First I would do this on the client side. If I see that the 50% is spent waiting for the server, then I would try stopping it on the server side. Then if I see it is waiting for SQL queries, I could look at those.
What I'm almost certain to find out is that more work is being requested than is actually needed. It is not usually something esoteric like a "hotspot" or an "algorithm". It is usually something dumb, like doing multiple queries when one would have been sufficient, so as to avoid having to write the code to save the result from the first query.
Here's an example.
First things first; make sure you know which pages are slow. You might be surprised. I recommend django_dumpslow.
SQLite is a great little database, but I am having an issue with it on Windows. It can take up to 50 seconds to perform a query on a 100MB database the first time the application is launched. Subsequent loads take 10% of that time.
After some discussions on the SQLite mailing list, I am told
"The bug is in Windows. It aggressively pre-caches big database files
-- reads in big chunks of the files -- to make it look as if programs
like Outlook are better than they really are. Unfortunately although
this speeds up some programs it makes others act jerky because they
have no control over how much is read when they ask for just a few
bytes of file."
This problem is compounded because there is no way to get progress information while all this is happening from SQLite, so my users think something is broken. (I could display a dummy progress report, but that is really cheesy for a sharp tool.)
I believe there is a way to turn the pre-caching off globally, but is there some way around this programmatically?
I don't know how to fix the caching problem, but 50 seconds sounds extreme. If the query itself takes 10% of that, that means 45 seconds to load a 100mb file. Even if Windows does read in the entire file in one go, that shouldn't take more than a couple of seconds given normal harddrive speeds.
Is the file very fragmented or something?
It sounds to me like there's more than just precaching at play here.
I'm too having the same problem with my first query. The problem returns after not querying the database for a long time. It seems to be a memory caching problem. My software runs 24/7 and every once in a while the user performs the SELECT query. I am also performing the query on a database of the same size.