I'm trying to find some information about the performance of angular.
If I had a list of 10k (or 50k) objects with 20 attributes each, would an average pc be able to filter this array in a reasonable time?
(Assuming a good implementation and this beeing the only operation executed)
Does anybody have any expierience in this direction?
Generally speaking, unless you can find a way to do this asynchronously; it's going to cause blocking UI issues. I've found the average "PC" (and let's not forget browsers are not created equal) is too slow for my use cases and that was with more simple objects (less attributes).
If you had a very limited set of attributes you actually want to filter on, there is a chance you could speed up the work by leveraging IndexedDB.
I recently worked on a project in google sheets. While everything is working, changes in the page take a while to process and load. There are a few parts of the project (described below). Is there a way to find out what is causing the biggest load on the project, so that I can work on that area?
Alternatively, if someone has experience with the following types of functions, what do you think is causing the biggest slowdown:
I have a query to lookup and match values. Would this be faster as a vlookup with sort in an arrayformula?
=IFERROR(QUERY(Record!A:C,"Select A where B = '"&B7&"' order by A desc limit 1 label A ''"),"")
I have random number generation through an arrayformula:
=ARRAYFORMULA(IF(ROW(B6:B)=6,"RANDOM",IF(ISBLANK(B6:B),"",RANDBETWEEN(0+0*ROW(B6:B),COUNTA(B6:B)))))
This fills in a cell with a random number if the one next to it has a value. I use this for random sampling in another query later.
I have some conditional formatting based on whether the cell has something in it.
I have some data validation based on a range of cells.
Note: Since my main question is about performance, I didn't think having an example file would be beneficial. It would take me a little to make one so if Ii should, let me know. Also, since other questions deal with scripting performance (like this one and this one) I feel like my question is different.
I suspect the RANDBETWEEN formula is your biggest culprit - basically every time the spreadsheet changes in any way whatsoever, even if you dont actually edit, the numbers all change, so inside an arrayformula, depending on how many rows you have, its always recalculating the rand for every single row
Is it worth worrying about CSS rendering performance? Or should we just not worry about efficiency at all with CSS and just focus on writing elegant or maintainable CSS instead?
This question is intended to be a useful resource for front-end developers on which parts of CSS can actually have a significant impact on device performance, and which devices / browsers or engines may be affected. This is not a question about how to write elegant or maintainable CSS, it's purely about performance (although hopefully what's written here can inform more general articles on best-practice).
Existing evidence
Google and Mozilla have written guidelines on writing efficient CSS and CSSLint's set of rules includes:
Avoid selectors that look like regular expressions
..
don't use the complex equality operators to avoid performance penalties
but none of them provide any evidence (that I could find) of the impact these have.
A css-tricks.com article on efficient CSS argues (after outlining a load of efficiency best practices) that we should not .. sacrifice semantics or maintainability for efficient CSS these days.
A perfection kills blog post suggested that border-radius and box-shadow rendered orders of magnitude slower than simpler CSS rules. This was hugely significant in Opera's engine, but insignificant in Webkit. Further, a smashing magazine CSS benchmark found that rendering time for CSS3 display rules was insignificant and significantly faster than rendering the equivalent effect using images.
Know your mobile tested various mobile browsers and found that they all rendered CSS3 equally insignificantly fast (in 12ms) but it looks like they did the tests on a PC, so we can't infer anything about how hand-held devices perform with CSS3 in general.
There are many articles on the internet on how to write efficient CSS. However, I have yet to find any comprehensive evidence that badly considered CSS actually has a significant impact on the rendering time or snappiness of a site.
Background
I offered bounty for this question to try to use the community power of SO to create a useful well-researched resource.
The first thing that comes to mind here is: how clever is the rendering engine you're using?
That, generic as it sounds, matters a lot when questioning the efficiency of CSS rendering/selection. For instance, suppose the first rule in your CSS file is:
.class1 {
/*make elements with "class1" look fancy*/
}
So when a very basic engine sees that (and since this is the first rule), it goes and looks at every element in your DOM, and checks for the existence of class1 in each. Better engines probably map classnames to a list of DOM elements, and use something like a hashtable for efficient lookup.
.class1.class2 {
/*make elements with both "class1" and "class2" look extra fancy*/
}
Our example "basic engine" would go and revisit each element in DOM looking for both classes. A cleverer engine will compare n('class1') and n('class2') where n(str) is number of elements in DOM with the class str, and takes whichever is minimum; suppose that's class1, then passes on all elements with class1 looking for elements that have class2 as well.
In any case, modern engines are clever (way more clever than the discussed example above), and shiny new processors can do millions (tens of millions) of operations a second. It's quite unlikely that you have millions of elements in your DOM, so the worst-case performance for any selection (O(n)) won't be too bad anyhow.
Update: To get some actual practical illustrative proof, I've decided to do some tests. First of all, to get an idea about how many DOM elements on average we can see in real-world applications, let's take a look at how many elements some popular sites' webpages have:
Facebook: ~1900 elements (tested on my personal main page).
Google: ~340 elements (tested on the main page, no search results).
Google: ~950 elements (tested on a search result page).
Yahoo!: ~1400 elements (tested on the main page).
Stackoverflow: ~680 elements (tested on a question page).
AOL: ~1060 elements (tested on the main page).
Wikipedia: ~6000 elements, 2420 of which aren't spans or anchors (Tested on the Wikipedia article about Glee).
Twitter: ~270 elements (tested on the main page).
Summing those up, we get an average of ~1500 elements. Now it's time to do some testing. For each test, I generated 1500 divs (nested within some other divs for some tests), each with appropriate attributes depending on the test.
The tests
The styles and elements are all generated using PHP. I've uploaded the PHPs I used, and created an index, so that others can test locally: little link.
Results:
Each test is performed 5 times on three browsers (the average time is reported): Firefox 15.0 (A), Chrome 19.0.1084.1 (B), Internet Explorer 8 (C):
A B C
1500 class selectors (.classname) 35ms 100ms 35ms
1500 class selectors, more specific (div.classname) 36ms 110ms 37ms
1500 class selectors, even more specific (div div.classname) 40ms 115ms 40ms
1500 id selectors (#id) 35ms 99ms 35ms
1500 id selectors, more specific (div#id) 35ms 105ms 38ms
1500 id selectors, even more specific (div div#id) 40ms 110ms 39ms
1500 class selectors, with attribute (.class[title="ttl"]) 45ms 400ms 2000ms
1500 class selectors, more complex attribute (.class[title~="ttl"]) 45ms 1050ms 2200ms
Similar experiments:
Apparently other people have carried out similar experiments; this one has some useful statistics as well: little link.
The bottom line: Unless you care about saving a few milliseconds when rendering (1ms = 0.001s), don't bother give this too much thought. On the other hand, it's good practice to avoid using complex selectors to select large subsets of elements, as that can make some noticeable difference (as we can see from the test results above). All common CSS selectors are reasonably fast in modern browsers.
Suppose you're building a chat page, and you want to style all the messages. You know that each message is in a div which has a title and is nested within a div with a class .chatpage. It is correct to use .chatpage div[title] to select the messages, but it's also bad practice efficiency-wise. It's simpler, more maintainable, and more efficient to give all the messages a class and select them using that class.
The fancy one-liner conclusion:
Anything within the limits of "yeah, this CSS makes sense" is okay.
Most answers here focus on selector performance as if it were the only thing that matters. I'll try to cover some spriting trivia (spoiler alert: they're not always a good idea), css used value performance and rendering of certain properties.
Before I get to the answer, let me get an IMO out of the way: personally, I strongly disagree with the stated need for "evidence-based data". It simply makes a performance claim appear credible, while in reality the field of rendering engines is heterogenous enough to make any such statistical conclusion inaccurate to measure and impractical to adopt or monitor.
As original findings quickly become outdated, I'd rather see front-end devs have an understanding of foundation principles and their relative value against maintainability/readability brownie points - after all, premature optimization is the root of all evil ;)
Let's start with selector performance:
Shallow, preferably one-level, specific selectors are processed faster. Explicit performance metrics are missing from the original answer but the key point remains: at runtime an HTML document is parsed into a DOM tree containing N elements with an average depth D and than has a total of S CSS rules applied. To lower computational complexity O(N*D*S), you should
Have the right-most keys match as few elements as possible - selectors are matched right-to-left^ for individual rule eligibility so if the right-most key does not match a particular element, there is no need to further process the selector and it is discarded.
It is commonly accepted that * selector should be avoided, but this point should be taken further. A "normal" CSS reset does, in fact, match most elements - when this SO page is profiled, the reset is responsible for about 1/3 of all selector matching time so you may prefer normalize.css (still, that only adds up to 3.5ms - the point against premature optimisation stands strong)
Avoid descendant selectors as they require up to ~D elements to be iterated over. This mainly impacts mismatch confirmations - for instance a positive .container .content match may only require one step for elements in a parent-child relationship, but the DOM tree will need to be traversed all the way up to html before a negative match can be confirmed.
Minimize the number of DOM elements as their styles are applied individually (worth noting, this gets offset by browser logic such as reference caching and recycling styles from identical elements - for instance, when styling identical siblings)
Remove unused rules since the browser ends up having to evaluate their applicability for every element rendered. Enough said - the fastest rule is the one that isn't there :)
These will result in quantifiable (but, depending on the page, not necessarily perceivable) improvements from a rendering engine performance standpoint, however there are always additional factors such as traffic overhead and DOM parsing etc.
Next, CSS3 properties performance:
CSS3 brought us (among other things) rounded corners, background gradients and drop-shadow variations - and with them, a truckload of issues. Think about it, by definition a pre-rendered image performs better than a set of CSS3 rules that has to be rendered first. From webkit wiki:
Gradients, shadows, and other decorations in CSS should be used only
when necessary (e.g. when the shape is dynamic based on the content) -
otherwise, static images are always faster.
If that's not bad enough, gradients etc. may have to be recalculated on every repaint/reflow event (more details below). Keep this in mind until the majority of users user can browse a css3-heavy page like this without noticeable lag.
Next, spriting performance:
Avoid tall and wide sprites, even if their traffic footprint is relatively small. It is commonly forgotten that a rendering engine cannot work with gif/jpg/png and at runtime all graphical assets are operated with as uncompressed bitmaps. At least it's easy to calculate: this sprite's width times height times four bytes per pixel (RGBA) is 238*1073*4≅1MB. Use it on a few elements across different simultaneously open tabs, and it quickly adds up to a significant value.
A rather extreme case of it has been picked up on mozilla webdev, but this is not at all unexpected when questionable practices like diagonal sprites are used.
An alternative to consider is individual base64-encoded images embedded directly into CSS.
Next, reflows and repaints:
It is a misconception that a reflow can only be triggered with JS DOM manipulation - in fact, any application of layout-affecting style would trigger it affecting the target element, its children and elements following it etc. The only way to prevent unnecessary iterations of it is to try and avoid rendering dependencies. A straightforward example of this would be rendering tables:
Tables often require multiple passes before the layout is completely established because they are one of the rare cases where elements can
affect the display of other elements that came before them on the DOM.
Imagine a cell at the end of the table with very wide content that
causes the column to be completely resized. This is why tables are not
rendered progressively in all browsers.
I'll make edits if I recall something important that has been missed. Some links to finish with:
http://perfectionkills.com/profiling-css-for-fun-and-profit-optimization-notes/
http://jacwright.com/476/runtime-performance-with-css3-vs-images/
https://developers.google.com/speed/docs/best-practices/payload
https://trac.webkit.org/wiki/QtWebKitGraphics
https://blog.mozilla.org/webdev/2009/06/22/use-sprites-wisely/
http://dev.opera.com/articles/view/efficient-javascript/
While it's true that
computers were way slower 10 years ago.
You also have a much wider variety of device that are capable of accessing your website these days. And while desktops/laptops have come on in leaps and bounds, the devices in the mid and low end smartphone market, in many cases aren't much more powerful than what we had in desktops ten years ago.
But having said that CSS Selection speed is probably near the bottom of the list of things you need to worry about in terms of providing a good experience to as broad a device range as possible.
Expanding upon this I was unable to find specific information relating to more modern browsers or mobile devices struggling with inefficient CSS selectors but I was able to find the following:
http://www.stevesouders.com/blog/2009/03/10/performance-impact-of-css-selectors/
Quite dated (IE8, Chrome 2) now but has a decent attempt of establishing efficiency of various selectors in some browsers and also tries to quantify how the # of CSS rules impacts page rendering time.
http://www.thebrightlines.com/2010/07/28/css-performance-who-cares/
Again quite dated (IE8, Chrome 6) but goes to extremes in inefficient CSS selectors * * * * * * * * * { background: #ff1; } to establish performance degradation.
For such a large bounty I am willing to risk the Null answer: there are no official CSS selectors that cause any appreciable slow-downs in the rendering, and (in this day of fast computers and rapid browser iteration) any that are found are quickly solved by browser makers. Even in mobile browsers there is no problem, unless the unwary developer is willing to use non-standard jQuery selectors. These are marked as risky by the jQuery developers, and can indeed be problematic.
In this case the lack of evidence is evidence of the lack of problems. So, use semantic markup (especially OOCSS), and report any slow-downs that you find when using standard CSS selectors in obscure browsers.
People from the future: CSS performance problems in 2012 were already a thing of the past.
isn't css a irrelevant way to make it faster, it must be the last thing you look at when you look at performance. Make your css in what ever way that suites you, compile it. and then put it in the head. This might be rough but their are loads of other things to look for when your looking in to browser performance. If you work at a digital bureau you wont get paid to do that extra 1ms in load time.
As i commented use pagespeed for chrome its a google tool that analyze the website in 27 parameters css is 1 of them.
My post just concern exactly, wouldn't rather have around 99% of web users be able to open the website and see it right, even the people with IE7 and such. Than closing out around 10% by using css3, (If it turns out that you can get an extra 1-10ms on performance).
Most people have atleast 1mbit/512kbit or higher, and if you load a heavy site it takes around 3 secounds to load, but you can save 10ms maybe on css??
And when it comes to mobile devices you should make sites just for mobiles so when you have a device with screen size less than "Width"px, you have a separate site
Please comment below this is my perspective and my personal experience with web development
While not directly code-related, using <link> over #import to include your stylesheets provides much faster performance.
'Don’t use #import' via stevesouders.com
The article contains numerous speed test examples between each type as well as including one type with another (ex: A CSS file called via <link> also contains #import to another css file).
What do you think the performance difference would be?
20,000 nodes
Each node has a Link field. The number of values range from 50 to 200. The Links will have no title.
OR
20,000 nodes
Each node will have the links in the body field as straight text with filtered html. As so:
http://link1.com
http://link2.com
http://link3.com
http://link4.com
http://link5.com
http://link6.com
http://link7.com
http://link8.com
http://link9.com
http://link10.com
It really depends how/what you are going to use them. I doubt you are going to display 20.000 nodes at once. It's really hard to say much about performance, without a specific use case, and even then, you have to take caching and what not into consideration as well.
In any regard, CCK will probably always be a tiny bit slower, because you are extracting multiple values instead of a single value, which makes the query a tiny bit more complex. I doubt that you will be able to measure that on your drupal site though.
Another thing to keep in mind, is that using CCK fields will give you added flexibility, is it integrates well with views. So you can easily pull out the links and format them in different ways.
All web developers run into this problem when the amount of data in their project grows, and I have yet to see a definitive, intuitive best practice for solving it. When you start a project, you often create forms with tags to help pick related objects for one-to-many relationships.
For instance, I might have a system with Neighbors and each Neighbor belongs to a Neighborhood. In version 1 of the application I create an edit user form that has a drop down for selecting users, that simply lists the 5 possible neighborhoods in my geographically limited application.
In the beginning, this works great. So long as I have maybe 100 records or less, my select box will load quickly, and be fairly easy to use. However, lets say my application takes off and goes national. Instead of 5 neighborhoods I have 10,000. Suddenly my little drop-down takes forever to load, and once it loads, its hard to find your neighborhood in the massive alphabetically sorted list.
Now, in this particular situation, having hierarchical data, and letting users drill down using several dynamically generated drop downs would probably work okay. However, what is the best solution when the objects/records being selected are not hierarchical in nature? In the past, of done this with a popup with a search box, and a list, but this seems clunky and dated. In today's web 2.0 world, what is a good way to find one object amongst many for ones forms?
I've considered using an Ajaxifed search box, but this seems to work best for free text, and falls apart a little when the data to be saved is just a reference to another object or record.
Feel free to cite specific libraries with generic solutions to this problem, or simply share what you have done in your projects in a more general way
I think an auto-completing text box is a good approach in this case. Here on SO, they also use an auto-completing box for tags where the entry already needs to exist, i.e. not free-text but a selection. (remember that creating new tags requires reputation!)
I personally prefer this anyways, because I can type faster than select something with the mouse, but that is programmer's disease I guess :)
Auto-complete is usually the best solution in my experience for searches, but only where the user is able to provide text tokens easily, either as part of the object name or taxonomy that contains the object (such as a product category, or postcode).
However this doesn't always work, particularly where 'browse' behavior would be more suitable - to give a real example, I once wrote a page for a community site that allowed a user to send a message to their friends. We used auto-complete there, allowing multiple entries separated by commas.
It works great when you know the names of the people you want to send the message to, but we found during user acceptance that most people didn't really know who was on their friend list and couldn't use the page very well - so we added a list popup with friend icons, and that was more successful.
(this was quite some time ago - everyone just copies Facebook now...)
Different methods of organizing large amounts of data:
Hierarchies
Spatial (geography/geometry)
Tags or facets
Different methods of searching large amounts of data:
Filtering (including autocomplete)
Sorting/paging (alphabetically-sorted data can also be paged by first letter)
Drill-down (assuming the data is organized as above)
Free-text search
Hierarchies are easy to understand and (usually) easy to implement. However, they can be difficult to navigate and lead to ambiguities. Spatial visualization is by far the best option if your data is actually spatial or can be represented that way; unfortunately this applies to less than 1% of the data we normally deal with day-to-day. Tags are great, but - as we see here on SO - can often be misused, misunderstood, or otherwise rendered less effective than expected.
If it's possible for you to reorganize your data in some relatively natural way, then that should always be the first step. Whatever best communicates the natural ordering is usually the best answer.
No matter how you organize the data, you'll eventually need to start providing search capabilities, and unlike organization of data, search methods tend to be orthogonal - you can implement more than one. Filtering and sorting/paging are the easiest, and if an autocomplete textbox or paged list (grid) can achieve the desired result, go for that. If you need to provide the ability to search truly massive amounts of data with no coherent organization, then you'll need to provide a full textual search.
If I could point you to some list of "best practices", I would, but HID is rarely so clear-cut. Use the aforementioned options as a starting point and see where that takes you.