nano optimization - Page 59

Does the <script> tag position in HTML affects performance of the webpage?

- by Rahul Joshi

If the script tag is above or below the body in a HTML page, does it matter for the performance of a website? And what if used in between like this: <body> ..blah..blah.. <script language="JavaScript" src="JS_File_100_KiloBytes"> function f1() { .. some logic reqd. for manipulating contents in a webpage } </script> ... some text here too ... </body> Or is this better?: <script language="JavaScript" src="JS_File_100_KiloBytes"> function f1() { .. some logic reqd. for manipulating contents in a webpage } </script> <body> ..blah..blah.. ..call above functions on some events like onclick,onfocus,etc.. </body> Or this one?: <body> ..blah..blah.. ..call above functions on some events like onclick,onfocus,etc.. <script language="JavaScript" src="JS_File_100_KiloBytes"> function f1() { .. some logic reqd. for manipulating contents in a webpage } </script> </body> Need not tell everything is again in the <html> tag!! How does it affect performance of webpage while loading? Does it really? Which one is the best, either out of these 3 or some other which you know? And one more thing, I googled a bit on this, from which I went here: Best Practices for Speeding Up Your Web Site and it suggests put scripts at the bottom, but traditionally many people put it in <head> tag which is above the <body> tag. I know it's NOT a rule but many prefer it that way. If you don't believe it, just view source of this page! And tell me what's the better style for best performance.

Read the article

How to improve performance of map that loads new overlay images

- by anthonysomerset

I have inherited a website to maintain that uses a html map overlaying a real map to link specific countries to specific pages. previously it loaded the default map image, then with some javascript it would change the image src to an image with that particular country in a different colour on mouseover and reset the image source back to the original image on mouse out to make maintenance (adding new countries) easier i made the initial map a background image by utilising some CSS for the div tag, and then created new images for each country which only had that countries hightlight so that the images remain fairly small. this works great but theres one issue which is particularly noticeable on slower internet connections when you hover over a country if you dont have the image file in your browser cache or downloaded it wont load the image unless you hover over another country and then back onto the first country - i guess this is due to the image having to manually be downloaded on first hover. My question: is it possible to force the load of these extra images AFTER the page and all the other assets have finished loading so that this behaviour is all but eliminated? the html code for the MAP is as follows: <div class="gtmap"><img id="Image-Maps_6200909211657061" src="<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png" usemap="#Image-Maps_6200909211657061" alt="We offer Guided Motorcycle Tours all around the world" width="615" height="296" /> <map id="_Image-Maps_6200909211657061" name="Image-Maps_6200909211657061"> <area shape="poly" coords="511,134,532,107,542,113,520,141" href="/guided-motorcycle-tours-japan/" alt="Guided Japan Motorcycle Tours" title="Japan" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-japan.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="252,61,266,58,275,64,262,68" href="/guided-motorcycle-tour.php?iceland-motorcycle-adventure-39" alt="Guided Iceland Motorcycle Tours" title="Iceland" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-iceland.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="587,246,597,256,577,279,568,270" href="/guided-motorcycle-tour.php?new-zealand-south-island-adventure-10" alt="New Zealand Guided Motorcycle Tours" title="New Zealand" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-nz.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="418,133,412,145,412,154,421,178,430,180,430,166,443,154,443,145,438,144,433,142,430,138,431,130,430,129,425,128" href="/guided-motorcycle-tours-india/" alt="India Guided Motorcycle Tours" title="India" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-india.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="460,152,466,149,474,165,470,171,466,161" href="/guided-motorcycle-tours-laos/" alt="Laos Guided Motorcycle Tours" title="Laos" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-laos.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="468,179,475,166,468,152,475,152,482,169" href="/guided-motorcycle-tour.php?indochina-motorcycle-adventure-tour-32" onClick="javascript: pageTracker._trackPageview('/internal-links/guided-tours/map/vietnam');" alt="Vietnam Guided Motorcycle Tours" title="Vietnam" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-viet.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="330,239,337,235,347,226,352,233,351,243,344,250,335,253,327,255,323,249,322,242,323,241" href="/guided-motorcycle-tours-southafrica/" alt="South Africa Guided Motorcycle Tours" title="South Africa" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-sa.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="290,77,293,86,298,96,286,102,285,97,285,89,282,84,282,79" href="/guided-motorcycle-tour.php?great-britain-isle-of-man-scotland-wales-uk-18" alt="United Kingdom" title="United Kingdom Guided Motorcycle Tours" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-uk.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="357,118,368,118,369,126,345,129,338,125,338,117,342,115,348,116" href="/guided-motorcycle-tour.php?explore-turkey-adventure-45" alt="Turkey" title="Turkey Guided Motorcycle Tours" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-turkey.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="206,95,193,101,185,101,178,106,165,111,157,109,147,105,134,103,121,103,107,103,96,103,86,104,81,99,77,91,70,83,62,79,60,72,61,64,59,57,60,51,71,50,83,49,95,50,107,54,117,53,129,47,137,36,148,37,163,38,177,44,187,54,195,60,184,72,191,80,200,87" href="/guided-motorcycle-tours-canada/" alt="Guided Canada Motorcycle Tours" title="Canada" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-canada.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="61,75,60,62,60,55,59,44,51,44,43,43,36,42,28,43,23,48,17,51,15,62,19,74,27,79,19,83,16,93,35,83,43,77,50,75,55,75" href="/guided-motorcycle-tours-alaska/" alt="Guided Alaska Motorcycle Tours" title="Alaska" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-alaska.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="82,101,99,101,133,101,148,105,161,110,172,106,187,100,180,113,171,122,165,131,159,149,147,141,137,140,129,147,120,141,112,138,103,137,93,132,86,122,86,112,86,106" href="/guided-motorcycle-tours-usa/" alt="USA Guided Motorcycle Tours" title="USA" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-usa.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="178,225,180,214,175,208,174,204,178,198,174,193,167,192,157,199,158,204,164,211,167,218" href="/guided-motorcycle-tour.php?peru-machu-picchu-adventure-25" alt="Peru Guided Motorcycle Tours" title="Peru" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-peru.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="172,226,169,239,166,256,166,267,164,279,171,277,174,262,175,250,179,234,180,225,176,224" href="/guided-motorcycle-tours-chile/" alt="Guided Chile Motorcycle Tours" title="Chile" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-chile.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> <area shape="poly" coords="199,260,194,261,187,265,184,276,183,296,170,292,168,282,174,270,174,257,177,245,180,230,190,228,205,237,199,245" href="/guided-motorcycle-tours-argentina/" alt="Guided Argentina Motorcycle Tours" title="Argentina" onmouseover="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-arg.png';" onmouseout="if(document.images) document.getElementById('Image-Maps_6200909211657061').src='<?php echo cdnhttpsCheck(); ?>assets/wmap/a-guided-tours-map-blank.png';" /> </map> </div> The <?php echo cdnhttpsCheck(); ?> is just a site specific function that gets the correct web domain/url from a config file to load resources from CDN where possible (eg all non HTTPS requests) We are loading Jquery at the bottom of the HTML if anybody wonders why it is missing from the code snippet for reference, the page with the map in question is found here: http://www.motoquest.com/guided-motorcycle-tours/

Read the article

Is SQL DATEDIFF(year, ..., ...) an Expensive Computation?

- by rlb.usa

I'm trying to optimize up some horrendously complicated SQL queries because it takes too long to finish. In my queries, I have dynamically created SQL statements with lots of the same functions, so I created a temporary table where each function is only called once instead of many, many times - this cut my execution time by 3/4. So my question is, can I expect to see much of a difference if say, 1,000 datediff computations are narrowed to 100?

Read the article

Difference between Logarithmic and Uniform cost criteria

- by Marthin

I'v got some problem to understand the difference between Logarithmic(Lcc) and Uniform(Ucc) cost criteria and also how to use it in calculations. Could someone please explain the difference between the two and perhaps show how to calculate the complexity for a problem like A+B*C (Yes this is part of an assignment =) ) Thx for any help! /Marthin

Read the article

Postgre database ignoring created index ?!

- by drasto

I have an Postgre database and a table called my_table. There are 4 columns in that table (id, column1, column2, column3). The id column is primary key, there are no other constrains or indexes on columns. The table has about 200000 rows. I want to print out all rows which has value of column column2 equal(case insensitive) to 'value12'. I use this: SELECT * FROM my_table WHERE column2 = lower('value12') here is the execution plan for this statement(result of set enable_seqscan=on; EXPLAIN SELECT * FROM my_table WHERE column2 = lower('value12')): Seq Scan on my_table (cost=0.00..4676.00 rows=10000 width=55) Filter: ((column2)::text = 'value12'::text) I consider this to be to slow so I create an index on column column2 for better prerformance of searches: CREATE INDEX my_index ON my_table (lower(column2)) Now I ran the same select: SELECT * FROM my_table WHERE column2 = lower('value12') and I expect it to be much faster because it can use index. However it is not faster, it is as slow as before. So I check the execution plan and it is the same as before(see above). So it still uses sequential scen and it ignores the index! Where is the problem ?

Read the article

Coalesce function for PHP?

- by mikl

Many programming languages has a coalesce function (example). PHP, sadly, does not. What would be the most efficient way to implement one in PHP?

Read the article

How can I optimize this subqueried and Joined MySQL Query?

- by kevzettler

Read the article

Meassure website

- by s0mmer

Hi, I was wondering if it is possible to install or use any online service to measure your website's performance? I've seen many just checking the download speed of images, external files etc. But is it possible to meassure how long asp/php code takes to execute? I have a site running a bit slowly, and it would be very nice with some app/service guiding where to optimize.

Read the article

Most Efficient Alternative Method of Storing Settings for iPhone Apps

- by JPK

I am not using the Settings bundle to store the settings for my app, as I prefer to allow the user to access the settings within the app (they may be changed fairly often). I do realize that there is the option to do both, but for now, I am trying to find the most optimal place to store the settings within the app. I have a good number of settings (from what I have read, probably too many for NSUserDefaults), and the two main options I am considering are: 1) storing the settings in a dictionary in the plist, loading the settings into a NSDictionary property in the app delegate and accessing them via the sharedDelegate 2) storing the settings in a Core Data entity (1 row on Settings entity), loading the settings into a Settings object in the app delegate and accessing them via the sharedDelegate Of these two, which would be the optimal method, performance wise?

Read the article

SQL Server indexed view matching of views with joins not working

- by usr

Does anyone have experience of when SQL Servr 2008 R2 is able to automatically match indexed view (also known as materialized views) that contain joins to a query? for example the view select dbo.Orders.Date, dbo.OrderDetails.ProductID from dbo.OrderDetails join dbo.Orders on dbo.OrderDetails.OrderID = dbo.Orders.ID cannot be automatically matched to the same exact query. When I select directly from this view ith (noexpand) I actually get a much faster query plan that does a scan on the clustered index of the indexed view. Can I get SQL Server to do this matching automatically? I have quite a few queries and views... I am on enterprise edition of SQL Server 2008 R2.

Read the article

How can I optimize retrieving lowest edit distance from a large table in SQL?

- by Matt

Hey, I'm having troubles optimizing this Levenshtein Distance calculation I'm doing. I need to do the following: Get the record with the minimum distance for the source string as well as a trimmed version of the source string Pick the record with the minimum distance If the min distances are equal (original vs trimmed), choose the trimmed one with the lowest distance If there are still multiple records that fall under the above two categories, pick the one with the highest frequency Here's my working version: DECLARE @Results TABLE ( ID int, [Name] nvarchar(200), Distance int, Frequency int, Trimmed bit ) INSERT INTO @Results SELECT ID, [Name], (dbo.Levenshtein(@Source, [Name])) As Distance, Frequency, 'False' As Trimmed FROM MyTable INSERT INTO @Results SELECT ID, [Name], (dbo.Levenshtein(@SourceTrimmed, [Name])) As Distance, Frequency, 'True' As Trimmed FROM MyTable SET @ResultID = (SELECT TOP 1 ID FROM @Results ORDER BY Distance, Trimmed, Frequency) SET @Result = (SELECT TOP 1 [Name] FROM @Results ORDER BY Distance, Trimmed, Frequency) SET @ResultDist = (SELECT TOP 1 Distance FROM @Results ORDER BY Distance, Trimmed, Frequency) SET @ResultTrimmed = (SELECT TOP 1 Trimmed FROM @Results ORDER BY Distance, Trimmed, Frequency) I believe what I need to do here is to.. Not dumb the results to a temporary table Do only 1 select from `MyTable` Setting the results right in the select from the initial select statement. (Since select will set variables and you can set multiple variables in one select statement) I know there has to be a good implementation to this but I can't figure it out... this is as far as I got: SELECT top 1 @ResultID = ID, @Result = [Name], (dbo.Levenshtein(@Source, [Name])) As distOrig, (dbo.Levenshtein(@SourceTrimmed, [Name])) As distTrimmed, Frequency FROM MyTable WHERE /* ... yeah I'm lost */ ORDER BY distOrig, distTrimmed, Frequency Any ideas?

Read the article

Single Large v/s Multiple Small MySQL tables for storing Options

- by Prasad

Hi there, I'm aware of several question on this forum relating to this. But I'm not talking about splitting tables for the same entity (like user for example) Suppose I have a huge options table that stores list options like Gender, Marital Status, and many more domain specific groups with same structure. I plan to capture in a OPTIONS table. Another simple option is to have the field set as ENUM, but there are disadvantages of that as well. http://www.brandonsavage.net/why-you-should-replace-enum-with-something-else/ OPTIONS Table: option_id <will be referred instead of the name> name value group Query: select .. from options where group = '15' - Since this table is expected to be multi-tenant, the no of rows could grow drastically. - I believe splitting the tables instead of finding by the group would be easier to write & faster to execute. - or perhaps partitioning by the group or tenant? Pl suggest. Thanks

Read the article

Trying to reduce the speed overhead of an almost-but-not-quite-int number class

- by Fumiyo Eda

I have implemented a C++ class which behaves very similarly to the standard int type. The difference is that it has an additional concept of "epsilon" which represents some tiny value that is much less than 1, but greater than 0. One way to think of it is as a very wide fixed point number with 32 MSBs (the integer parts), 32 LSBs (the epsilon parts) and a huge sea of zeros in between. The following class works, but introduces a ~2x speed penalty in the overall program. (The program includes code that has nothing to do with this class, so the actual speed penalty of this class is probably much greater than 2x.) I can't paste the code that is using this class, but I can say the following: +, -, +=, <, > and >= are the only heavily used operators. Use of setEpsilon() and getInt() is extremely rare. * is also rare, and does not even need to consider the epsilon values at all. Here is the class: #include <limits> struct int32Uepsilon { typedef int32Uepsilon Self; int32Uepsilon () { _value = 0; _eps = 0; } int32Uepsilon (const int &i) { _value = i; _eps = 0; } void setEpsilon() { _eps = 1; } Self operator+(const Self &rhs) const { Self result = *this; result._value += rhs._value; result._eps += rhs._eps; return result; } Self operator-(const Self &rhs) const { Self result = *this; result._value -= rhs._value; result._eps -= rhs._eps; return result; } Self operator-( ) const { Self result = *this; result._value = -result._value; result._eps = -result._eps; return result; } Self operator*(const Self &rhs) const { return this->getInt() * rhs.getInt(); } // XXX: discards epsilon bool operator<(const Self &rhs) const { return (_value < rhs._value) || (_value == rhs._value && _eps < rhs._eps); } bool operator>(const Self &rhs) const { return (_value > rhs._value) || (_value == rhs._value && _eps > rhs._eps); } bool operator>=(const Self &rhs) const { return (_value >= rhs._value) || (_value == rhs._value && _eps >= rhs._eps); } Self &operator+=(const Self &rhs) { this->_value += rhs._value; this->_eps += rhs._eps; return *this; } Self &operator-=(const Self &rhs) { this->_value -= rhs._value; this->_eps -= rhs._eps; return *this; } int getInt() const { return(_value); } private: int _value; int _eps; }; namespace std { template<> struct numeric_limits<int32Uepsilon> { static const bool is_signed = true; static int max() { return 2147483647; } } }; The code above works, but it is quite slow. Does anyone have any ideas on how to improve performance? There are a few hints/details I can give that might be helpful: 32 bits are definitely insufficient to hold both _value and _eps. In practice, up to 24 ~ 28 bits of _value are used and up to 20 bits of _eps are used. I could not measure a significant performance difference between using int32_t and int64_t, so memory overhead itself is probably not the problem here. Saturating addition/subtraction on _eps would be cool, but isn't really necessary. Note that the signs of _value and _eps are not necessarily the same! This broke my first attempt at speeding this class up. Inline assembly is no problem, so long as it works with GCC on a Core i7 system running Linux!

Read the article

An image from byte to optimized web page presentation

- by blgnklc

I get the data of the stored image on database as byte[] array; then I convert it to System.Drawing.Image like the code shown below; public System.Drawing.Image CreateImage(byte[] bytes) { System.IO.MemoryStream memoryStream = new System.IO.MemoryStream(bytes); System.Drawing.Image image = System.Drawing.Image.FromStream(memoryStream); return image; } (*) On the other hand I am planning to show a list of images on asp.net pages as the client scrolls downs the page. The more user gets down and down on the page he/she does see the more photos. So it means fast page loads and rich user experience. (you may see what I mean on www.mashable.com, just take care the new loads of the photos as you scroll down.) Moreover, the returned imgae object from the method above, how can i show it in a loop dynamically using the (*) conditions above. Regards bk

Read the article

"Anagram solver" based on statistics rather than a dictionary/table?

- by James M.

My problem is conceptually similar to solving anagrams, except I can't just use a dictionary lookup. I am trying to find plausible words rather than real words. I have created an N-gram model (for now, N=2) based on the letters in a bunch of text. Now, given a random sequence of letters, I would like to permute them into the most likely sequence according to the transition probabilities. I thought I would need the Viterbi algorithm when I started this, but as I look deeper, the Viterbi algorithm optimizes a sequence of hidden random variables based on the observed output. I am trying to optimize the output sequence. Is there a well-known algorithm for this that I can read about? Or am I on the right track with Viterbi and I'm just not seeing how to apply it?

Read the article

Can I use Duff's Device on an array in C?

- by Ben Fossen

I have a loop here and I want to make it run faster. I am passing in a large array. I recently heard of Duff's Device can it be applied to this for loop? any ideas? for (i = 0; i < dim; i++) { for (j = 0; j < dim; j++) { dst[RIDX(dim-1-j, i, dim)] = src[RIDX(i, j, dim)]; } }

Read the article

Can anyone recommend a decent tool for optimising images other than photoshop

- by toomanyairmiles

Can anyone recommend a decent tool for optimising images other than adobe photoshop, the gimp etc? I'm looking to optimise images for the web preferably online and free. Basically I have a client who can't install additional software on their work PC but needs to optimise photographs and other images for their website and is presently uploading 1 or 2 Mb files. On a personal level I'm interested to see what other people are using...

Read the article

Any difference between lazy loading Javascript files vs. placing just before </body>

- by mhr

Looked around, couldn't find this specific question discussed. Pretty sure the difference is negligible, just curious as to your thoughts. Scenario: All Javascript that doesn't need to be loaded before page render has been placed just before the closing </body> tag. Are there any benefits or detriments to lazy loading these instead through some Javascript code in the head that executes when the DOM load/ready event is fired? Let's say that this only concerns downloading one entire .js file full of functions and not lazy loading several individual files as needed upon usage. Hope that's clear, thanks.

Read the article

Speeding up inner joins between a large table and a small table

- by Zaid

This may be a silly question, but it may shed some light on how joins work internally. Let's say I have a large table L and a small table S (100K rows vs. 100 rows). Would there be any difference in terms of speed between the following two options?: OPTION 1: OPTION 2: --------- --------- SELECT * SELECT * FROM L INNER JOIN S FROM S INNER JOIN L ON L.id = S.id; ON L.id = S.id; Notice that the only difference is the order in which the tables are joined. I realize performance may vary between different SQL languages. If so, how would MySQL compare to Access?

Read the article

Find point which sum of distances to set of other points is minimal

- by Pawel Markowski

I have one set (X) of points (not very big let's say 1-20 points) and the second (Y), much larger set of points. I need to choose some point from Y which sum of distances to all points from X is minimal. I came up with an idea that I would treat X as a vertices of a polygon and find centroid of this polygon, and then I will choose a point from Y nearest to the centroid. But I'm not sure whether centroid minimizes sum of its distances to the vertices of polygon, so I'm not sure whether this is a good way? Is there any algorithm for solving this problem? Points are defined by geographical coordinates.

Read the article

Optimize a MySQL count each duplicate Query

- by Onema

I have the following query That gets the city name, city id, the region name, and a count of duplicate names for that record: SELECT Country_CA.City AS currentCity, Country_CA.CityID, globe_region.region_name, ( SELECT count(Country_CA.City) FROM Country_CA WHERE City LIKE currentCity ) as counter FROM Country_CA LEFT JOIN globe_region ON globe_region.region_id = Country_CA.RegionID AND globe_region.country_code = Country_CA.CountryCode ORDER BY City This example is for Canada, and the cities will be displayed on a dropdown list. There are a few towns in Canada, and in other countries, that have the same names. Therefore I want to know if there is more than one town with the same name region name will be appended to the town name. Region names are found in the globe_region table. Country_CA and globe_region look similar to this (I have changed a few things for visualization purposes) CREATE TABLE IF NOT EXISTS `Country_CA` ( `City` varchar(75) NOT NULL DEFAULT '', `RegionID` varchar(10) NOT NULL DEFAULT '', `CountryCode` varchar(10) NOT NULL DEFAULT '', `CityID` int(11) NOT NULL DEFAULT '0', PRIMARY KEY (`City`,`RegionID`), KEY `CityID` (`CityID`) ) ENGINE=MyISAM DEFAULT CHARSET=utf8; AND CREATE TABLE IF NOT EXISTS `globe_region` ( `country_code` char(2) COLLATE utf8_unicode_ci NOT NULL, `region_code` char(2) COLLATE utf8_unicode_ci NOT NULL, `region_name` varchar(50) COLLATE utf8_unicode_ci NOT NULL, PRIMARY KEY (`country_code`,`region_code`) ) ENGINE=MyISAM DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci; The query on the top does exactly what I want it to do, but It takes way too long to generate a list for 5000 records. I would like to know if there is a way to optimize the sub-query in order to obtain the same results faster. the results should look like this City CityID region_name counter sheraton 2349269 British Columbia 1 sherbrooke 2349270 Quebec 2 sherbrooke 2349271 Nova Scotia 2 shere 2349273 British Columbia 1 sherridon 2349274 Manitoba 1

Read the article

Rewriting a for loop in pure NumPy to decrease execution time

- by Statto

I recently asked about trying to optimise a Python loop for a scientific application, and received an excellent, smart way of recoding it within NumPy which reduced execution time by a factor of around 100 for me! However, calculation of the B value is actually nested within a few other loops, because it is evaluated at a regular grid of positions. Is there a similarly smart NumPy rewrite to shave time off this procedure? I suspect the performance gain for this part would be less marked, and the disadvantages would presumably be that it would not be possible to report back to the user on the progress of the calculation, that the results could not be written to the output file until the end of the calculation, and possibly that doing this in one enormous step would have memory implications? Is it possible to circumvent any of these? import numpy as np import time def reshape_vector(v): b = np.empty((3,1)) for i in range(3): b[i][0] = v[i] return b def unit_vectors(r): return r / np.sqrt((r*r).sum(0)) def calculate_dipole(mu, r_i, mom_i): relative = mu - r_i r_unit = unit_vectors(relative) A = 1e-7 num = A*(3*np.sum(mom_i*r_unit, 0)*r_unit - mom_i) den = np.sqrt(np.sum(relative*relative, 0))**3 B = np.sum(num/den, 1) return B N = 20000 # number of dipoles r_i = np.random.random((3,N)) # positions of dipoles mom_i = np.random.random((3,N)) # moments of dipoles a = np.random.random((3,3)) # three basis vectors for this crystal n = [10,10,10] # points at which to evaluate sum gamma_mu = 135.5 # a constant t_start = time.clock() for i in range(n[0]): r_frac_x = np.float(i)/np.float(n[0]) r_test_x = r_frac_x * a[0] for j in range(n[1]): r_frac_y = np.float(j)/np.float(n[1]) r_test_y = r_frac_y * a[1] for k in range(n[2]): r_frac_z = np.float(k)/np.float(n[2]) r_test = r_test_x +r_test_y + r_frac_z * a[2] r_test_fast = reshape_vector(r_test) B = calculate_dipole(r_test_fast, r_i, mom_i) omega = gamma_mu*np.sqrt(np.dot(B,B)) # write r_test, B and omega to a file frac_done = np.float(i+1)/(n[0]+1) t_elapsed = (time.clock()-t_start) t_remain = (1-frac_done)*t_elapsed/frac_done print frac_done*100,'% done in',t_elapsed/60.,'minutes...approximately',t_remain/60.,'minutes remaining'

Read the article

Long-running Database Query

- by JamesMLV

I have a long-running SQL Server 2005 query that I have been hoping to optimize. When I look at the actual execution plan, it says a Clustered Index Seek has 66% of the cost. Execuation Plan Snippit: <RelOp AvgRowSize="31" EstimateCPU="0.0113754" EstimateIO="0.0609028" EstimateRebinds="0" EstimateRewinds="0" EstimateRows="10198.5" LogicalOp="Clustered Index Seek" NodeId="16" Parallel="false" PhysicalOp="Clustered Index Seek" EstimatedTotalSubtreeCost="0.0722782"> <OutputList> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="quoteDate" /> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="price" /> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </OutputList> <RunTimeInformation> <RunTimeCountersPerThread Thread="0" ActualRows="1067" ActualEndOfScans="1" ActualExecutions="1" /> </RunTimeInformation> <IndexScan Ordered="true" ScanDirection="FORWARD" ForcedIndex="false" NoExpandHint="false"> <DefinedValues> <DefinedValue> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="quoteDate" /> </DefinedValue> <DefinedValue> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="price" /> </DefinedValue> <DefinedValue> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </DefinedValue> </DefinedValues> <Object Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Index="[_dta_index_Indices_14_320720195__K5_K2_K1_3]" Alias="[I]" /> <SeekPredicates> <SeekPredicate> <Prefix ScanType="EQ"> <RangeColumns> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="HedgeProduct" ComputedColumn="true" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="(1)"> <Const ConstValue="(1)" /> </ScalarOperator> </RangeExpressions> </Prefix> <StartRange ScanType="GE"> <RangeColumns> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="[@StartMonth]"> <Identifier> <ColumnReference Column="@StartMonth" /> </Identifier> </ScalarOperator> </RangeExpressions> </StartRange> <EndRange ScanType="LE"> <RangeColumns> <ColumnReference Database="[wf_1]" Schema="[dbo]" Table="[Indices]" Alias="[I]" Column="tenure" /> </RangeColumns> <RangeExpressions> <ScalarOperator ScalarString="[@EndMonth]"> <Identifier> <ColumnReference Column="@EndMonth" /> </Identifier> </ScalarOperator> </RangeExpressions> </EndRange> </SeekPredicate> </SeekPredicates> </IndexScan> </RelOp> From this, does anyone see an obvious problem that would be causing this to take so long? Here is the query: (SELECT quotedate, tenure, price, ActualVolume, HedgePortfolioValue, Price AS UnhedgedPrice, ((ActualVolume*Price - HedgePortfolioValue)/ActualVolume) AS HedgedPrice FROM ( SELECT [quoteDate] ,[price] , tenure ,isnull(wf_1.[Risks].[HedgePortValueAsOfDate2](1,tenureMonth,quotedate,price),0) as HedgePortfolioValue ,[TotalOperatingGasVolume] as ActualVolume FROM [wf_1].[dbo].[Indices] I inner join ( SELECT DISTINCT tenureMonth FROM [wf_1].[Risks].[KnowRiskTrades] WHERE HedgeProduct = 1 AND portfolio <> 'Natural Gas Hedge Transactions' ) B ON I.tenure=B.tenureMonth inner join ( SELECT [Month],[TotalOperatingGasVolume] FROM [wf_1].[Risks].[ActualGasVolumes] ) C ON C.[Month]=B.tenureMonth WHERE HedgeProduct = 1 AND quoteDate>=dateadd(day, -3*365, tenureMonth) AND quoteDate<=dateadd(day,-3,tenureMonth) )A )

Read the article

Will the compiler optimize escaping an inner loop?

- by BCS

The code I have looks like this (all uses of done shown): bool done = false; for(int i = 0; i < big; i++) { ... for(int j = 0; j < wow; j++) { ... if(foo(i,j)) { done = true; break; } ... } if(done) break; ... } will any compilers convert it to this: for(int i = 0; i < big; i++) { ... for(int j = 0; j < wow; j++) { ... if(foo(i,j)) goto __done; // same as a labeled break if we had it ... } ... } __done:;

Read the article

Mysql - help me optimize this query (improved question)

- by sandeepan-nath

About the system: - There are tutors who create classes and packs - A tags based search approach is being followed.Tag relations are created when new tutors register and when tutors create packs (this makes tutors and packs searcheable). For details please check the section How tags work in this system? below. Following is the concerned query SELECT SUM(DISTINCT( t.tag LIKE "%Dictatorship%" )) AS key_1_total_matches, SUM(DISTINCT( t.tag LIKE "%democracy%" )) AS key_2_total_matches, COUNT(DISTINCT( od.id_od )) AS tutor_popularity, CASE WHEN ( IF(( wc.id_wc > 0 ), ( wc.wc_api_status = 1 AND wc.wc_type = 0 AND wc.class_date > '2010-06-01 22:00:56' AND wccp.status = 1 AND ( wccp.country_code = 'IE' OR wccp.country_code IN ( 'INT' ) ) ), 0) ) THEN 1 ELSE 0 END AS 'classes_published', CASE WHEN ( IF(( lp.id_lp > 0 ), ( lp.id_status = 1 AND lp.published = 1 AND lpcp.status = 1 AND ( lpcp.country_code = 'IE' OR lpcp.country_code IN ( 'INT' ) ) ), 0) ) THEN 1 ELSE 0 END AS 'packs_published', td . *, u . * FROM tutor_details AS td JOIN users AS u ON u.id_user = td.id_user LEFT JOIN learning_packs_tag_relations AS lptagrels ON td.id_tutor = lptagrels.id_tutor LEFT JOIN learning_packs AS lp ON lptagrels.id_lp = lp.id_lp LEFT JOIN learning_packs_categories AS lpc ON lpc.id_lp_cat = lp.id_lp_cat LEFT JOIN learning_packs_categories AS lpcp ON lpcp.id_lp_cat = lpc.id_parent LEFT JOIN learning_pack_content AS lpct ON ( lp.id_lp = lpct.id_lp ) LEFT JOIN webclasses_tag_relations AS wtagrels ON td.id_tutor = wtagrels.id_tutor LEFT JOIN webclasses AS wc ON wtagrels.id_wc = wc.id_wc LEFT JOIN learning_packs_categories AS wcc ON wcc.id_lp_cat = wc.id_wp_cat LEFT JOIN learning_packs_categories AS wccp ON wccp.id_lp_cat = wcc.id_parent LEFT JOIN order_details AS od ON td.id_tutor = od.id_author LEFT JOIN orders AS o ON od.id_order = o.id_order LEFT JOIN tutors_tag_relations AS ttagrels ON td.id_tutor = ttagrels.id_tutor JOIN tags AS t ON ( t.id_tag = ttagrels.id_tag ) OR ( t.id_tag = lptagrels.id_tag ) OR ( t.id_tag = wtagrels.id_tag ) WHERE ( u.country = 'IE' OR u.country IN ( 'INT' ) ) AND CASE WHEN ( ( t.id_tag = lptagrels.id_tag ) AND ( lp.id_lp 0 ) ) THEN lp.id_status = 1 AND lp.published = 1 AND lpcp.status = 1 AND ( lpcp.country_code = 'IE' OR lpcp.country_code IN ( 'INT' ) ) ELSE 1 END AND CASE WHEN ( ( t.id_tag = wtagrels.id_tag ) AND ( wc.id_wc 0 ) ) THEN wc.wc_api_status = 1 AND wc.wc_type = 0 AND wc.class_date '2010-06-01 22:00:56' AND wccp.status = 1 AND ( wccp.country_code = 'IE' OR wccp.country_code IN ( 'INT' ) ) ELSE 1 END AND CASE WHEN ( od.id_od 0 ) THEN od.id_author = td.id_tutor AND o.order_status = 'paid' AND CASE WHEN ( od.id_wc 0 ) THEN od.can_attend_class = 1 ELSE 1 END ELSE 1 END GROUP BY td.id_tutor HAVING key_1_total_matches = 1 AND key_2_total_matches = 1 ORDER BY tutor_popularity DESC, u.surname ASC, u.name ASC LIMIT 0, 20 The problem The results returned by the above query are correct (AND logic working as per expectation), but the time taken by the query rises alarmingly for heavier data and for the current data I have it is like 25 seconds as against normal query timings of the order of 0.005 - 0.0002 seconds, which makes it totally unusable. It is possible that some of the delay is being caused because all the possible fields have not yet been indexed. The tag field of tags table is indexed. Is there something faulty with the query? What can be the reason behind 20+ seconds of execution time? How tags work in this system? When a tutor registers, tags are entered and tag relations are created with respect to tutor's details like name, surname etc. When a Tutors create packs, again tags are entered and tag relations are created with respect to pack's details like pack name, description etc. tag relations for tutors stored in tutors_tag_relations and those for packs stored in learning_packs_tag_relations. All individual tags are stored in tags table. The explain query output:- Please see this screenshot - http://www.test.examvillage.com/Explain_query.jpg

Search Results

Search found 3706 results on 149 pages for 'nano optimization'.

Page 59/149 | < Previous Page | 55 56 57 58 59 60 61 62 63 64 65 66 | Next Page >

- by Rahul Joshi

- by anthonysomerset

- by rlb.usa

- by Marthin

- by drasto

- by mikl

- by kevzettler

- by s0mmer

- by JPK

- by usr

- by Matt

- by Prasad

- by Fumiyo Eda

- by blgnklc

- by James M.

- by Ben Fossen

- by toomanyairmiles

- by mhr

- by Zaid

- by Pawel Markowski

- by Onema

- by Statto

- by JamesMLV

- by BCS

- by sandeepan-nath

< Previous Page | 55 56 57 58 59 60 61 62 63 64 65 66 | Next Page >