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  • Fastest algorithm to check if a number is pandigital?

    - by medopal
    Pandigital number is a number that contains the digits 1..number length. For example 123, 4312 and 967412385. I have solved many Project Euler problems, but the Pandigital problems always exceed the one minute rule. This is my pandigital function: private boolean isPandigital(int n){ Set<Character> set= new TreeSet<Character>(); String string = n+""; for (char c:string.toCharArray()){ if (c=='0') return false; set.add(c); } return set.size()==string.length(); } Create your own function and test it with this method int pans=0; for (int i=123456789;i<=123987654;i++){ if (isPandigital(i)){ pans++; } } Using this loop, you should get 720 pandigital numbers. My average time was 500 millisecond. I'm using Java, but the question is open to any language.

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  • how to get started with TopCoder to update/develop algorithm skills ?

    - by KaluSingh Gabbar
    at workplace, the work I do is hardly near to challenging and doing that I think I might be loosing the skills to look at a completely new problem and think about different ideas to solve it. A friend suggested TopCoder.com to me, but looking at the overwhelming number of problems I can not decide how to get started? what I want is to sharpen my techniques ( not particular language or framework ).

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  • How do I implement an higher lower game algorithm?

    - by lazorde
    The computer will guess a player’s number between 1 and 100. After each guess the human player should respond “higher”, “lower” or “correct”. Your program should be able to guess the player’s number in no more than 7 tries. Begin by explaining the game to the player, telling him/her to think of a number between 1 and 100. Make the computer do what you would normally do to guess a number in a certain range. Allow the user to respond with “higher”, “lower”, or “correct” after each computer guess. Output the number of tries it took the computer to guess the number. Make the game as user friendly as you can.

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  • SQL SERVER – What is Spatial Database? – Developing with SQL Server Spatial and Deep Dive into Spati

    - by pinaldave
    What is Spatial Database? A spatial database is a database that is optimized to store and query data related to objects in space, including points, lines and polygons. While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases to process spatial data types. (Source: Wikipedia) Today I will be talking about the same subject at Microsoft TechEd India. If you want to learn about how to spatial aspect of data and how to integrate them with SQL Server this is the perfect session for you. Spatial is very special concept of SQL Server and I really like how it is implemented in SQL Server. In general Performance Tuning and Query Optimization is something I always have enjoyed in my professional life. Index are my best friends and many time, by implementing and many time by removing I have improved the performance of the system. In this session, I will be talking about Index along with Spatial Data. As Spatial Database is very interesting concept, I will cover super short but very interesting 10 quick slides about this subject. I will make sure in very first 20 mins, you will understand following topics Introduction to Spatial Database One line definition Understanding Spatial Indexing Index Internals Query/Performance Tuning Query Hinting/Cost Analysis Spatial Index Catalog Views Performance Troubleshooting Finding Optimal Index using Spatial Index SP Common Errors Index Maintenance This slides decks will be followed by around 30 mins demo which will have story of geometry, geography, index internals and performance tuning. If you are interested in learning how GIS works and how SQL Server out of the box supports this wonderful tools, you will really like how the story is told. I am sure all people who attend the event will know how the Bangalore is positioned on the map of India. I will take example of Bangalore and Hyderabad and demonstrate how index can improve the performance. Well there are lots of story to tell in the session, and I will be opening this session with the beautiful script of Botticelli’s Birth of Venus created by Michael J. Swart. I will also demonstrate few real life scenario where I will be talking about Spatial Database and its usage. Do not miss this session. At the end of session there will be book awarded to best participant. My session details: Session 3: Developing with SQL Server Spatial and Deep Dive into Spatial Indexing Date: April 14, 2010 Time: 5:00pm-6:00pm Microsoft SQL Server 2008 delivers new spatial data types that enable you to consume, use, and extend location-based data through spatial-enabled applications. Attend this session to learn how to use spatial functionality in next version of SQL Server to build and optimize spatial queries. This session outlines the new geography data type to store geodetic spatial data and perform operations on it, use the new geometry data type to store planar spatial data and perform operations on it, take advantage of new spatial indexes for high performance queries, use the new spatial results tab to quickly and easily view spatial query results directly from within Management Studio, extend spatial data capabilities by building or integrating location-enabled applications through support for spatial standards and specifications and much more. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL, Technology Tagged: Spatial Database

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  • Improved Genetic algorithm for multiknapsack problem

    - by user347918
    Hello guys, Recently i've been improving traditional genetic algorithm for multiknapsack problem. So My Improved Genetic Algorithm is working better then Traditional Genetic Algorithm. I tested. (i used publically available from OR-Library (http://people.brunel.ac.uk/~mastjjb/jeb/orlib/mknapinfo.html) were used to test the GAs.) Does anybody know other improved GA. I wanted to compare with other improved genetic algorithm. Actually i searched in internet. But couldn't find good algorithm to compare.

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  • CSS optimization - extra classes in dom or preprocessor-repetitive styling in css file?

    - by anna.mi
    I'm starting on a fairly large project and I'm considering the option of using LESS for pre-processing my css. the useful thing about LESS is that you can define a mixin that contains for example: .border-radius(@radius) { -webkit-border-radius: @radius; -moz-border-radius: @radius; -o-border-radius: @radius; -ms-border-radius: @radius; border-radius: @radius; } and then use it in a class declaration as .rounded-div { .border-radius(10px); } to get the outputted css as: .rounded-div { -webkit-border-radius: 10px; -moz-border-radius: 10px; -o-border-radius: 10px; -ms-border-radius: 10px; border-radius: 10px; } this is extremely useful in the case of browser prefixes. However this same concept could be used to encapsulate commonly-used css, for example: .column-container { overflow: hidden; display: block; width: 100%; } .column(@width) { float: left; width: @width; } and then use this mixin whenever i need columns in my design: .my-column-outer { .column-container(); background: red; } .my-column-inner { .column(50%); font-color: yellow; } (of course, using the preprocessor we could easily expand this to be much more useful, eg. pass the number of columns and the container width as variables and have LESS determine the width of each column depending on the number of columns and container width!) the problem with this is that when compliled, my final css file would have 100 such declarations, copy&pasted, making the file huge and bloated and repetitive. The alternative to this would be to use a grid system which has predefined classes for each column-layout option, eg .c-50 ( with a "float: left; width:50%;" definition ), .c-33, .c-25 to accomodate for a 2-column, 3-column and 4-column layout and then use these classes to my dom. i really mislike the idea of the extra classes, from experience it results to bloated dom (creating extra divs just to attach the grid classes to). Also the most basic tutorial for html/css would tell you that the dom should be separated from the styling - grid classes are styling related! to me, its the same as attaching a "border-radius-10" class to the .rounded-div example above! on the other hand, the large css file that would result from the repetitive code is also a disadvantage so i guess my question is, which one would you recommend? and which do you use? and, which solution is best for optimization? apart from the larger file size, has there even been any research on whether browser renders multiple classes faster than a large css file, or the other way round? tnx! i'd love to hear your opinion!

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  • SQL SERVER – Quick Look at SQL Server Configuration for Performance Indications

    - by pinaldave
    Earlier I wrote SQL SERVER – Beginning SQL Server: One Step at a Time – SQL Server Magazine. That was the first article on the series of my real world experience of Performance Tuning experience. I have written second part the same series over here. Read second part over here: Quick Look at SQL Server Configuration for Performance Indications. In this second part I talk about two types of my clients. 1) Those who want instant results 2) Those who want the right results It is really fun to work with both the clients. I talk about various configuration options which I look at when I try to give very early opinion about SQL Server Performance. There are various eight configurations, I give quick look and start talking about performance. Head over to original article over here: Quick Look at SQL Server Configuration for Performance Indications. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Wait Stats – Wait Types – Wait Queues – Day 0 of 28

    - by pinaldave
    This blog post will have running account of the all the blog post I will be doing in this month related to SQL Server Wait Types and Wait Queues. SQL SERVER – Introduction to Wait Stats and Wait Types – Wait Type – Day 1 of 28 SQL SERVER – Signal Wait Time Introduction with Simple Example – Wait Type – Day 2 of 28 SQL SERVER – DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28 SQL SERVER – DMV – sys.dm_os_waiting_tasks and sys.dm_exec_requests – Wait Type – Day 4 of 28 SQL SERVER – Capturing Wait Types and Wait Stats Information at Interval – Wait Type – Day 5 of 28 SQL SERVER – CXPACKET – Parallelism – Usual Solution – Wait Type – Day 6 of 28 SQL SERVER – CXPACKET – Parallelism – Advanced Solution – Wait Type – Day 7 of 28 SQL SERVER – SOS_SCHEDULER_YIELD – Wait Type – Day 8 of 28 SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28 SQL SERVER – IO_COMPLETION – Wait Type – Day 10 of 28 SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28 SQL SERVER – PAGELATCH_DT, PAGELATCH_EX, PAGELATCH_KP, PAGELATCH_SH, PAGELATCH_UP – Wait Type – Day 12 of 28 SQL SERVER – FT_IFTS_SCHEDULER_IDLE_WAIT – Full Text – Wait Type – Day 13 of 28 SQL SERVER – BACKUPIO, BACKUPBUFFER – Wait Type – Day 14 of 28 SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28 Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Convert IN to EXISTS – Performance Talk

    - by pinaldave
    In recent training one of the attendee asked if I can show simple method to convert IN clause to EXISTS clause. Here is the simple example. USE AdventureWorks GO -- use of = SELECT * FROM HumanResources.Employee E WHERE E.EmployeeID = ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO -- use of exists SELECT * FROM HumanResources.Employee E WHERE EXISTS ( SELECT EA.EmployeeID FROM HumanResources.EmployeeAddress EA WHERE EA.EmployeeID = E.EmployeeID) GO It is NOT necessary that every time when IN is replaced by EXISTS it gives better performance. However, in our case listed above it does for sure give better performance. Click on below image to see the execution plan. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Fast Fashion Freshness

    - by David Dorf
    Fashion retailers such as H&M, Zara, and Wet Seal have perfected the fast fashion retailing model. The concept requires no replenishment in order to maintain assortment freshness and to create a sense of urgency for the consumer to purchase now. However, maintaining assortment freshness results in high product turnover, making markdown optimization a necessity. Wet Seal, for instance, needed to move from ad-hoc markdowns and dealing with surplus inventory to handling markdowns methodically across 8,000 SKUs with only 12-15 week lifecycle (from DC receipt to exit). By optimizing and automating markdowns, Wet Seal is reaching their goal of assortment freshness, which in turn increases sales. If you're interested in learning more, register for a free webinar occurring on May 13th featuring Join Daniel Ryu, Vice President of Planning and Allocation at Wet Seal. He'll be discussing how the fast fashion retailer maintains their goal of assortment freshness.

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  • JIT compiler for C, C++, and the likes

    - by Ebrahim
    Is there any just-in-time compiler out there for compiled languages, such as C and C++? (The first names that come to mind are Clang and LLVM! But I don't think they currently support it.) Explanation: I think the software could benefit from runtime profiling feedback and aggressively optimized recompilation of hotspots at runtime, even for compiled-to-machine languages like C and C++. Profile-guided optimization does a similar job, but with the difference a JIT would be more flexible in different environments. In PGO you run your binary prior to releasing it. After you released it, it would use no environment/input feedbacks collected at runtime. So if the input pattern is changed, it is probe to performance penalty. But JIT works well even in that conditions. However I think it is controversial wether the JIT compiling performance benefit outweights its own overhead. Edit: Grammar

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  • Single click handler for all buttons in Javascript? Is it a pattern? Whats the benefit?

    - by Hasan Khan
    I have been told that when there are multiple buttons on the page for same purpose but targeting different item e.g. delete item on a grid of items, they say it is recommended to just register for click handler only on the top most element like 'body' and check what was clicked instead of hooking up click with every delete button. Whats the benefit of this? Creating more handlers causes problems? Is it an optimization of some sort? Is it a pattern? Does it have anything to do with performance? Where can I read more about it?

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  • Best practices when loading images for improving page loading speed

    - by Naoise Golden
    I am working on optimizing a page's loading speed. Here are some analytics: Notice how the images, although only accounting for 65% of the total size (1.1MB), are by far the slowest loading assets: 96% of time. I'd like to know which are the recommended practices on optimizing loading speed, only taking images into account. Some of the techniques we are already applying: image compression images hosted on cookieless domain and CDN spriting everything that can be sprited http headers: keep alive and Expires to one year. Disclaimer: I have gone through the available documentation, I think by focusing on image loading optimization I am not creating a duplicate or a subjective question.

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  • When to start thinking about scalability?

    - by Rits
    I'm having a funny but also terrible problem. I'm about to launch a new (iPhone) app. It's a turn-based multiplayer game running on my own custom backend. But I'm afraid to launch. For some reason, I think it might become something big and that its popularity will kill my poor lonely single server + MySQL database. On one hand I'm thinking that if it's growing, I'd better be prepared and have a scalable infrastructure already in place. On the other hand I just feel like getting it out into the world and see what happens. I often read stuff like "premature optimization is the root of all evil" or people saying that you should just build your killer game now, with the tools at hand, and worry about other stuff like scalability later. I'd love to hear some opinions on this from experts or people with experience with this. Thanks!

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  • Worse is better. Is there an example?

    - by J.F. Sebastian
    Is there a widely-used algorithm that has time complexity worse than that of another known algorithm but it is a better choice in all practical situations (worse complexity but better otherwise)? An acceptable answer might be in a form: There are algorithms A and B that have O(N**2) and O(N) time complexity correspondingly, but B has such a big constant that it has no advantages over A for inputs less then a number of atoms in the Universe. Examples highlights from the answers: Simplex algorithm -- worst-case is exponential time -- vs. known polynomial-time algorithms for convex optimization problems. A naive median of medians algorithm -- worst-case O(N**2) vs. known O(N) algorithm. Backtracking regex engines -- worst-case exponential vs. O(N) Thompson NFA -based engines. All these examples exploit worst-case vs. average scenarios. Are there examples that do not rely on the difference between the worst case vs. average case scenario? Related: The Rise of ``Worse is Better''. (For the purpose of this question the "Worse is Better" phrase is used in a narrower (namely -- algorithmic time-complexity) sense than in the article) Python's Design Philosophy: The ABC group strived for perfection. For example, they used tree-based data structure algorithms that were proven to be optimal for asymptotically large collections (but were not so great for small collections). This example would be the answer if there were no computers capable of storing these large collections (in other words large is not large enough in this case). Coppersmith–Winograd algorithm for square matrix multiplication is a good example (it is the fastest (2008) but it is inferior to worse algorithms). Any others? From the wikipedia article: "It is not used in practice because it only provides an advantage for matrices so large that they cannot be processed by modern hardware (Robinson 2005)."

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  • How does lucene index documents?

    - by Mehdi Amrollahi
    Hello, I read some document about Lucene; also I read the document in this link (http://lucene.sourceforge.net/talks/pisa). I don't really understand how Lucene indexes documents and don't understand which algorithms Lucene uses for indexing? On the above link, it says Lucene uses this algorithm for indexing: incremental algorithm: maintain a stack of segment indices create index for each incoming document push new indexes onto the stack let b=10 be the merge factor; M=8 for (size = 1; size < M; size *= b) { if (there are b indexes with size docs on top of the stack) { pop them off the stack; merge them into a single index; push the merged index onto the stack; } else { break; } } How does this algorithm provide optimized indexing? Does Lucene use B-tree algorithm or any other algorithm like that for indexing - or does it have a particular algorithm? Thank you for reading my post.

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  • Applying iterative algorithm to a set of rows from database

    - by Corvin
    Hello, this question may seem too basic to some, but please bear with be, it's been a while since I dealt with decent database programming. I have an algorithm that I need to program in PHP/MySQL to work on a website. It performs some computations iteratively on an array of objects (it ranks the objects based on their properties). In each iteration the algorithm runs through all collection a couple of times, accessing various data from different places of the whole collection. The algorithm needs several hundred iterations to complete. The array comes from a database. The straightforward solution that I see is to take the results of a database query and create an object for each row of the query, put the objects to an array and pass the array to my algorithm. However, I'm concerned with efficacy of such solution when I have to work with an array of several thousand of items because what I do is essentially mirror the results of a query to memory. On the other hand, making database query a couple of times on each iteration of the algorithm also seems wrong. So, my question is - what is the correct architectural solution for a problem like this? Is it OK to mirror the query results to memory? If not, which is the best way to work with query results in such an algorithm? Thanks!

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