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  • Is it possible to perform Google Website Optimization on URL Rewritten pages?

    - by digiguru
    I have a format of pages that I want to perform an A/B comparison on using google website optimizer. the URLs look as follows - the first page I want to compare... <mywebsite.com>/request1/([a-zA-Z0-9\-]*)_([0-9]+).htm vs <mywebsite.com>/request2/([a-zA-Z0-9\-]*)_([0-9]+).htm the goal page is <mywebsite.com>/request-sent.htm How can I set this up in google website optimizer? If it's not possible, are there alternative solutions available for doing such comparison reports online?

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  • How to specify the image scaling algorithm used by a WPF Image?

    - by mackenir
    Is there a way to specify how an image is scaled up in an Image element with LayoutTransform set to a ScaleTransform with integer values for ScaleX and ScaleY? I want to display the scaled image crisply (ie using 'nearest neighbour' scaling), with no blurring. (Imagine how you would want a bitmap editing program to behave when zooming in). I noticed the protected property VisualBitmapScalingMode on Image, so created a subclass of Image that sets this property to BitmapScalingMode.NearestNeighbor. However, this had no effect.

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  • DB Interface Design Optimization: Is it better to optimise for Fewer requests of smaller data size?

    - by Overflow
    The prevailing wisdom in webservices/web requests in general is to design your api such that you use as few requests as possible, and that each request returns therefore as much data as is needed In database design, the accepted wisdom is to design your queries to minimise size over the network, as opposed to minimizing the number of queries. They are both remote calls, so what gives?

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  • What's a good algorithm for searching arrays N and M, in order to find elements in N that also exist

    - by GenTiradentes
    I have two arrays, N and M. they are both arbitrarily sized, though N is usually smaller than M. I want to find out what elements in N also exist in M, in the fastest way possible. To give you an example of one possible instance of the program, N is an array 12 units in size, and M is an array 1,000 units in size. I want to find which elements in N also exist in M. (There may not be any matches.) The more parallel the solution, the better. I used to use a hash map for this, but it's not quite as efficient as I'd like it to be. Typing this out, I just thought of running a binary search of M on sizeof(N) independent threads. (Using CUDA) I'll see how this works, though other suggestions are welcome.

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  • JQuery Optimization: Is there any way to speed up the rendering of the FlexSelect control?

    - by Sephrial
    Greetings, I am new to jQuery, and I have a performance problem with the FlexSelect control where it takes about 5 seconds to render the dropdown control (in the renderDropdown() function). The dropdown list contains about 5000 element. I believe all the runtime is attributed to the following block of code: var list = this.dropdownList.html(""); $.each(this.results, function() { list.append($("<li/>").html(this.name)); }); Question: Are there any alternatives that would build this list of elements in a more inefficient manner?

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  • What is the most efficient algorithm for reversing a String in Java?

    - by Hultner
    I am wondering which way to reverse a string in Java that is most efficient. Should I use some sort of xor method? The easy way would be to put all the chars in a stack and put them back into a string again but I doubt that's a very efficient way to do it. And please do not tell me to use some built in function in Java. I am interested in learning how to do it not to use an efficient function but not knowing why it's efficient or how it's built up.

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  • Problem solving/ Algorithm Skill is a knack or can be developed with practice?

    - by KaluSingh Gabbar
    Every time I start a hard problem and if can not figure out the exact solution or can not get started, I get into this never ending discussion with myself, as below: That problem solving/mathematics/algorithms skills are gifted (not that you can learn by practicing, by practice, you only master the kind of problems that you already have solved before) only those who went to good schools can do it, as they learned it early. What are your thoughts, can one achieve awesomeness in problem solving/algorithms just by hard work or you need to have that extra-gene in you?

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  • What's the fastest lookup algorithm for a pair data structure (i.e, a map)?

    - by truncheon
    In the following example a std::map structure is filled with 26 values from A - Z (for key) and 0 – 26 for value. The time taken (on my system) to lookup the last entry (10000000 times) is roughly 250 ms for the vector, and 125 ms for the map. (I compiled using release mode, with O3 option turned on for g++ 4.4) But if for some odd reason I wanted better performance than the std::map, what data structures and functions would I need to consider using? I apologize if the answer seems obvious to you, but I haven't had much experience in the performance critical aspects of C++ programming. UPDATE: This example is rather trivial and hides the true complexity of what I'm trying to achieve. My real world project is a simple scripting language that uses a parser, data tree, and interpreter (instead of a VM stack system). I need to use some kind of data structure (perhaps map) to store the variables names created by script programmers. These are likely to be pretty randomly named, so I need a lookup method that can quickly find a particular key within a (probably) fairly large list of names. #include <ctime> #include <map> #include <vector> #include <iostream> struct mystruct { char key; int value; mystruct(char k = 0, int v = 0) : key(k), value(v) { } }; int find(const std::vector<mystruct>& ref, char key) { for (std::vector<mystruct>::const_iterator i = ref.begin(); i != ref.end(); ++i) if (i->key == key) return i->value; return -1; } int main() { std::map<char, int> mymap; std::vector<mystruct> myvec; for (int i = 'a'; i < 'a' + 26; ++i) { mymap[i] = i - 'a'; myvec.push_back(mystruct(i, i - 'a')); } int pre = clock(); for (int i = 0; i < 10000000; ++i) { find(myvec, 'z'); } std::cout << "linear scan: milli " << clock() - pre << "\n"; pre = clock(); for (int i = 0; i < 10000000; ++i) { mymap['z']; } std::cout << "map scan: milli " << clock() - pre << "\n"; return 0; }

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  • What algorithm would you use to code a parrot?

    - by Phil H
    A parrot learns the most commonly uttered words and phrases in its vicinity so it can repeat them at inappropriate moments. So how would you create a software version? Assuming it has access to a microphone and can record sound at will, how would you code it without requiring infinite resources? The best I can imagine is to divide the stream using silences in the sound, and then use some pattern recognition to encode each one as a list of tokens, storing new ones as you meet them. Hashing the token sequences and counting occurrences in a database, you could build up a picture of the most frequently uttered phrases. But given the huge variety in phrases, how do you prevent this just becoming a huge list? And the sheer number of pairs to match would surely generate lot of false positives from the combinatorial nature of matching. Would you use a neural net, since that's how a real parrot manages it? Or is there another, cleverer way of matching large-scale patterns in analogue data?

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  • What are all the concurrent things [data structure, algorithm, locking mechanism] missing in .Net 3.

    - by user49767
    First time I am bit disappointed in StackOverflow cause my http://stackoverflow.com/questions/2571727/c-concurrency-vs-java-concurrency-which-is-neatly-designed-which-is-better question was closed. My intension was just trying to gather knowledge from programming guru's who worked in both the programming technologies. Rather closing this question, please help me by discussing what is good, bad, and ugly in multi-threading part in both the platforms. It is also welcome, if someone would like to compare with .Net 4.0 with JDK 6 (or JDK 7)

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  • A very interesting MYSQL problem (related to indexing, million records, algorithm.)

    - by terence410
    This problem is pretty hard to describe and therefore difficult to search the answer. I hope some expert could share you opinions on that. I have a table with around 1 million of records. The table structure is similar to something like this: items{ uid (primary key, bigint, 15) updated (indexed, int, 11) enabled (indexed, tinyint, 1) } The scenario is like this. I have to select all of the records everyday and do some processing. It takes around 3 second to handle each item. I have written a PHP script to fetch 200 items each time using the following. select * from items where updated unix_timestamp(now()) - 86400 and enabled = 1 limit 200; I will then update the "updated" field of the selected items to make sure that it wont' be selected again within one day. The selected query is something like that. update items set updated = unix_timestamp(now()) where uid in (1,2,3,4,...); Then, the PHP will continue to run and process the data which doesn't require any MYSQL connection anymore. Since I have million records and each record take 3 seconds to process, it's definitely impossible to do it sequentially. Therefore, I will execute the PHP in every 10 seconds. However, as time goes by and the table growth, the select getting much slower. Sometimes, it take more than 100 seconds to run! Do you guys have any suggestion how may I solve this problem?

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  • db optimization - have a total field or query table?

    - by Dorian Fife
    I have an app where users get points for actions they perform - either 1 point for an easy action or 2 for a difficult one. I wish to display to the user the total number of points he got in my app and the points obtained this week (since Monday at midnight). I have a table that records all actions, along with their time and number of points. I have two alternatives and I'm not sure which is better: Every time the user sees the report perform a query and sum the points the user got Add two fields to each user that records the number of points obtained so far (total and weekly). The weekly points value will be set to 0 every Monday at midnight. The first option is easier, but I'm afraid that as I'll get many users and actions queries will take a long time. The second option bares the risk of inconsistency between the table of actions and the summary values. I'm very interested in what you think is the best alternative here. Thanks, Dorian

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  • What's the fastest lookup algorithm for a key, pair data structure (i.e, a map)?

    - by truncheon
    In the following example a std::map structure is filled with 26 values from A - Z (for key) and 0 – 26 for value. The time taken (on my system) to lookup the last entry (10000000 times) is roughly 250 ms for the vector, and 125 ms for the map. (I compiled using release mode, with O3 option turned on for g++ 4.4) But if for some odd reason I wanted better performance than the std::map, what data structures and functions would I need to consider using? I apologize if the answer seems obvious to you, but I haven't had much experience in the performance critical aspects of C++ programming. #include <ctime> #include <map> #include <vector> #include <iostream> struct mystruct { char key; int value; mystruct(char k = 0, int v = 0) : key(k), value(v) { } }; int find(const std::vector<mystruct>& ref, char key) { for (std::vector<mystruct>::const_iterator i = ref.begin(); i != ref.end(); ++i) if (i->key == key) return i->value; return -1; } int main() { std::map<char, int> mymap; std::vector<mystruct> myvec; for (int i = 'a'; i < 'a' + 26; ++i) { mymap[i] = i - 'a'; myvec.push_back(mystruct(i, i - 'a')); } int pre = clock(); for (int i = 0; i < 10000000; ++i) { find(myvec, 'z'); } std::cout << "linear scan: milli " << clock() - pre << "\n"; pre = clock(); for (int i = 0; i < 10000000; ++i) { mymap['z']; } std::cout << "map scan: milli " << clock() - pre << "\n"; return 0; }

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  • Oracle Query Optimization: Why is My Second Query Faster?

    - by Patrick Cuff
    I was having some performance issues with an Oracle query, so I downloaded a trial of the Quest SQL Optimizer for Oracle, which made some changes that dramatically improved the query's performance. I'm not exactly sure why the recommended query had such an improvement; can anyone provide an explanation? Before: SELECT t1.version_id, t1.id, t2.field1, t3.person_id, t2.id FROM table1 t1, table2 t2, table3 t3 WHERE t1.id = t2.id AND t1.version_id = t2.version_id AND t2.id = 123 AND t1.version_id = t3.version_id AND t1.VERSION_NAME <> 'AA' order by t1.id Plan Cost: 831 Elapsed Time: 00:00:21.40 Number of Records: 40,717 After: SELECT /*+ USE_NL_WITH_INDEX(t1) */ t1.version_id, t1.id, t2.field1, t3.person_id, t2.id FROM table2 t2, table3 t3, table1 t1 WHERE t1.id = t2.id + 0 AND t1.version_id = t2.version_id + 0 AND t2.id = 123 AND t1.version_id = t3.version_id + 0 AND t1.VERSION_NAME || '' <> 'AA' AND t3.version_id = t2.version_id + 0 order by t1.id Plan Cost: 686 Elapsed Time: 00:00:00.95 Number of Records: 40,717 Questions: Why does re-arranging the order of the tables in the FROM clause help? Why does adding + 0 to the WHERE clause comparisons help? Why does || '' <> 'AA' in the WHERE clause VERSION_NAME comparison help? Is this a more efficient way of handling possible nulls on this column?

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