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  • Optimizing landing pages

    - by Oleg Shaldybin
    In my current project (Rails 2.3) we have a collection of 1.2 million keywords, and each of them is associated with a landing page, which is effectively a search results page for a given keywords. Each of those pages is pretty complicated, so it can take a long time to generate (up to 2 seconds with a moderate load, even longer during traffic spikes, with current hardware). The problem is that 99.9% of visits to those pages are new visits (via search engines), so it doesn't help a lot to cache it on the first visit: it will still be slow for that visit, and the next visit could be in several weeks. I'd really like to make those pages faster, but I don't have too many ideas on how to do it. A couple of things that come to mind: build a cache for all keywords beforehand (with a very long TTL, a month or so). However, building and maintaing this cache can be a real pain, and the search results on the page might be outdated, or even no longer accessible; given the volatile nature of this data, don't try to cache anything at all, and just try to scale out to keep up with traffic. I'd really appreciate any feedback on this problem.

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  • How to optimize this simple function which translates input bits into words?

    - by psihodelia
    I have written a function which reads an input buffer of bytes and produces an output buffer of words where every word can be either 0x0081 for each ON bit of the input buffer or 0x007F for each OFF bit. The length of the input buffer is given. Both arrays have enough physical place. I also have about 2Kbyte free RAM which I can use for lookup tables or so. Now, I found that this function is my bottleneck in a real time application. It will be called very frequently. Can you please suggest a way how to optimize this function? I see one possibility could be to use only one buffer and do in-place substitution. void inline BitsToWords(int8 *pc_BufIn, int16 *pw_BufOut, int32 BufInLen) { int32 i,j,z=0; for(i=0; i<BufInLen; i++) { for(j=0; j<8; j++, z++) { pw_BufOut[z] = ( ((pc_BufIn[i] >> (7-j))&0x01) == 1? 0x0081: 0x007f ); } } } Please do not offer any compiler specific or CPU/Hardware specific optimization, because it is a multi-platform project.

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  • Speed up PostGreSQL createdb?

    - by John
    Is there a way to speed up PostgreSQL's createdb command? Normally I wouldn't care, but doing unit testing in Django creates a database every time, and it takes about 5 seconds. I'm using openSUSE 11.2 64-bit, PostgreSQL 8.4.2

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  • Are conditional subqueries optimized out, if the condition is false?

    - by Tobias Schulte
    I have a table foo and a table bar, where each foo might have a bar (and a bar might belong to multiple foos). Now I need to select all foos with a bar. My sql looks like this SELECT * FROM foo f WHERE [...] AND ($param IS NULL OR (SELECT ((COUNT(*))>0) FROM bar b WHERE f.bar = b.id)) with $param being replaced at runtime. The question is: Will the subquery be executed even if param is null, or will the dbms optimize the subquery out? We are using mysql, mssql and oracle. Is there a difference between these regarding the above?

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  • Strange profiler behavior: same functions, different performances

    - by arthurprs
    I was learning to use gprof and then i got weird results for this code: int one(int a, int b) { return a / (b + 1); } int two(int a, int b) { return a / (b + 1); } int main() { for (int i = 1; i < 30000000; i++) { two(i, i * 2); one(i, i * 2); } return 0; } and this is the profiler output % cumulative self self total time seconds seconds calls ns/call ns/call name 48.39 0.90 0.90 29999999 30.00 30.00 one(int, int) 40.86 1.66 0.76 29999999 25.33 25.33 two(int, int) 10.75 1.86 0.20 main If i call one then two the result is the inverse, two takes more time than one both are the same functions, but the first calls always take less time then the second Why is that? Note: The assembly code is exactly the same and code is being compiled with no optimizations

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  • Best practice for avoiding locks on a heavily read table?

    - by Luiggi
    Hi, I have a big database (~4GB), with 2 large tables (~3M records) having ~180K SELECTs/hour, ~2k UPDATEs/hour and ~1k INSERTs+DELETEs/hour. What would be the best practice to guarantee no locks for the reading tasks while inserting/updating/deleting? I was thinking about using a NOLOCK hint, but there is so much discussed about this (is good, is bad, it depends) that I'm a bit lost. I must say I've tried this in a dev environment and I didn't find any problems, but I don't want to put it on production until I get some feedback... Thank you! Luiggi

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  • Is putting the javascript before the closing body tag okay on an asp.net website?

    - by Jason Weber
    I pretty much stated what I have to ask. But is taking all of your external .js files and putting them before the closing body tag on your master pages okay on an asp.net website? I'm just going off of what yslow and google speed have been showing. I can't combine these javascripts, so I'm trying to load them "after page load", but doing so makes them useless; some of my jquery things don't work. I moved my .js files above the opening body tag, and they work. What am I doing wrong? And what could I do to load my .js files after page load? Thanks for any advice anybody can offer!

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  • What GC parameters is a JVM running with?

    - by skaffman
    I'm still investigating issues I have with GC tuning (see prior question), which involves lots of reading and experimentation. Sun Java5+ JVMs attempt to automatically select the optimal GC strategy and parameters based on their environment, which is great, but I can't figure out how to query the running JVM to find out what those parameters are. Ideally, I'd like to see what values of the various GC-related -XX options are being used, as selected automatically by the VM. If I had that, I could have a baseline to begin tweaking. Anyone know to recover these values from a running VM?

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  • C#: How to implement a smart cache

    - by Svish
    I have some places where implementing some sort of cache might be useful. For example in cases of doing resource lookups based on custom strings, finding names of properties using reflection, or to have only one PropertyChangedEventArgs per property name. A simple example of the last one: public static class Cache { private static Dictionary<string, PropertyChangedEventArgs> cache; static Cache() { cache = new Dictionary<string, PropertyChangedEventArgs>(); } public static PropertyChangedEventArgs GetPropertyChangedEventArgsa(string propertyName) { if (cache.ContainsKey(propertyName)) return cache[propertyName]; return cache[propertyName] = new PropertyChangedEventArgs(propertyName); } } But, will this work well? For example if we had a whole load of different propertyNames, that would mean we would end up with a huge cache sitting there never being garbage collected or anything. I'm imagining if what is cached are larger values and if the application is a long-running one, this might end up as kind of a problem... or what do you think? How should a good cache be implemented? Is this one good enough for most purposes? Any examples of some nice cache implementations that are not too hard to understand or way too complex to implement?

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  • JAVA bytecode optimization

    - by Idob
    This is a basic question. I have code which shouldn't run on metadata beans. All metadata beans are located under metadata package. Now, I use reflection API to find out whether a class is located in the the metadata package. if (newEntity.getClass().getPackage().getName().contains("metadata")) I use this If in several places within this code. The question is: Should I do this once with: boolean isMetadata = false if (newEntity.getClass().getPackage().getName().contains("metadata")) { isMetadata = true; } C++ makes optimizations and knows that this code was already called and it won't call it again. Does JAVA makes optimization? I know reflection API is a beat heavy and I prefer not to lose expensive runtime.

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  • Python : How do you find the CPU consumption for a piece of code?

    - by Yugal Jindle
    Background: I have a django application, it works and responds pretty well on low load, but on high load like 100 users/sec, it consumes 100% CPU and then due to lack of CPU slows down. Problem : Profiling the application gives me time taken by functions. This time increases on high load. Time consumed may be due to complex calculation or for waiting for CPU. so, how to find the CPU cycles consumed by a piece of code ? Since, reducing the CPU consumption will increase the response time. I might have written extremely efficient code and need to add more CPU power OR I might have some stupid code taking the CPU and causing the slow down ? Any help is appreciated ! Update: I am using Jmeter to profile my webapp, it gives me a throughput of 2 requests/sec. [ 100 users] I get a average time of 36 seconds on 100 request vs 1.25 sec time on 1 request. More Info Configuration Nginx + Uwsgi with 4 workers No database used, using a responses from a REST API On 1st hit the response of REST API gets cached, therefore doesn't makes a difference. Using ujson for json parsing. Curious to Know: Python-Django is used by so many orgs for so many big sites, then there must be some high end Debug / Memory-CPU analysis tools. All those I found were casual snippets of code that perform profiling.

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  • Will an IO blocked process show 100% CPU utilization in 'top' output?

    - by Alex Stoddard
    I have an analysis that can be parallelized over a different number of processes. It is expected that things will be both IO and CPU intensive (very high throughput short-read DNA alignment if anyone is curious.) The system running this is a 48 core linux server. The question is how to determine the optimum number of processes such that total throughput is maximized. At some point the processes will presumably become IO bound such that adding more processes will be of no benefit and possibly detrimental. Can I tell from standard system monitoring tools when that point has been reached? Would the output of top (or maybe a different tool) enable me to distinguish between a IO bound and CPU bound process? I am suspicious that a process blocked on IO might still show 100% CPU utilization.

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  • C++ Function pointers vs Switch

    - by Perfix
    What is faster: Function pointers or switch? The switch statement would have around 30 cases, consisting of enumarated unsigned ints from 0 to 30. I could do the following: class myType { FunctionEnum func; string argv[123]; int someOtherValue; }; // In another file: myType current; // Iterate through a vector containing lots of myTypes // ... for ( i=0; i < myVecSize; i ++ ) switch ( current.func ) { case 1: //... break; // ........ case 30: // blah break; } And go trough the switch with func every time. The good thing about switch would also be that my code is more organized than with 30 functions. Or I could do that (not so sure with that): class myType { myReturnType (*func); string argv[123]; int someOtherValue; }; I'd have 30 different functions then, at the beginning a pointer to one of them is assigned to myType. What is probably faster: Switch statement or function pointer? Calls per second: Around 10 million. I can't just test it out - that would require me to rewrite the whole thing. Currently using switch. I'm building an interpreter which I want to be faster than Python & Ruby - every clock cycle matters!

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  • Create a PHP cache system in MySQL database?

    - by Zach Smith
    I'm creating a web service that often scrapes data from remote web pages. After scraping this data, I have a simple multidimensional array of information to use. The scraping process is fairly taxing on my server, and the page load takes a while. I was considering adding a simple cache system using a MySQL database, where I create one row per remote web page with a the array of information pulled from it stored as a JSON encoded string. Is this a good enough system? Or would something like a text file per web page be a better idea?

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  • Intersection() and Except() is too slow with large collections of custom objects

    - by Theo
    I am importing data from another database. My process is importing data from a remote DB into a List<DataModel> named remoteData and also importing data from the local DB into a List<DataModel> named localData. I am then using LINQ to create a list of records that are different so that I can update the local DB to match the data pulled from remote DB. Like this: var outdatedData = this.localData.Intersect(this.remoteData, new OutdatedDataComparer()).ToList(); I am then using LINQ to create a list of records that no longer exist in remoteData, but do exist in localData, so that I delete them from local database. Like this: var oldData = this.localData.Except(this.remoteData, new MatchingDataComparer()).ToList(); I am then using LINQ to do the opposite of the above to add the new data to the local database. Like this: var newData = this.remoteData.Except(this.localData, new MatchingDataComparer()).ToList(); Each collection imports about 70k records, and each of the 3 LINQ operation take between 5 - 10 minutes to complete. How can I make this faster? Here is the object the collections are using: internal class DataModel { public string Key1{ get; set; } public string Key2{ get; set; } public string Value1{ get; set; } public string Value2{ get; set; } public byte? Value3{ get; set; } } The comparer used to check for outdated records: class OutdatedDataComparer : IEqualityComparer<DataModel> { public bool Equals(DataModel x, DataModel y) { var e = string.Equals(x.Key1, y.Key1) && string.Equals(x.Key2, y.Key2) && ( !string.Equals(x.Value1, y.Value1) || !string.Equals(x.Value2, y.Value2) || x.Value3 != y.Value3 ); return e; } public int GetHashCode(DataModel obj) { return 0; } } The comparer used to find old and new records: internal class MatchingDataComparer : IEqualityComparer<DataModel> { public bool Equals(DataModel x, DataModel y) { return string.Equals(x.Key1, y.Key1) && string.Equals(x.Key2, y.Key2); } public int GetHashCode(DataModel obj) { return 0; } }

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  • In sync query calls, one query causing other query to run slower. Why?

    - by Irchi
    Sorry for the long question, but I think this is an interesting situation and I couldn't find any explanations for it: I was involved in optimization of an application that performed a large number of sequential SELECT and INSERT statements on a single dedicated SQL Server database. The process needs to INSERT a large number of records into a table, but for each of them there should be some value mappings, which performed using SELECT statements on another table in the same database. For a specific execution, it took 90 minutes to run. I used a profiler (JProfiler - the application is Java-based) to determine how much time does each part of the application take. It yields that 60% of the time was spent on INSERT method calls, and almost 20% on SELECT calls (the rest distributed in other parts). After some trials, I came to this situation: I commented out the INSERT query that took 60% of the time. I was expecting for the total run time to be around 35 minutes, as I have removed 60% of the 90 minutes. But the whole process took the same 90 minutes (doing only SELECTs and nothing else), but each SELECT took longer this time! Everything was running sync, there were no async calls. And there was only one single thread of execution. SELECT and INSERT queries are very simple, and don't have anything special, and they are on different tables, but on the same DB. I tested with both the DB on the application machine, and on a remote network machine. I can't think of any explanation for this, as the Profiler (Application profiler, not SQL Profiler) reported the changes in the method call times, and by removing INSERT statements SELECT statements took longer to run. Can anyone give me some kind of explanation of what could have happened? (there can't be cache / query optimization stuff, because the queries were run in sync, and in a single thread, and it was far from affecting the cache this much) I should note that the bottleneck of the speed was in SQL server, using most of the CPU time.

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  • What influences running time of reading a bunch of images?

    - by remi
    I have a program where I read a handful of tiny images (50000 images of size 32x32). I read them using OpenCV imread function, in a program like this: std::vector<std::string> imageList; // is initialized with full path to the 50K images for(string s : imageList) { cv::Mat m = cv::imread(s); } Sometimes, it will read the images in a few seconds. Sometimes, it takes a few minutes to do so. I run this program in GDB, with a breakpoint further away than the loop for reading images so it's not because I'm stuck in a breakpoint. The same "erratic" behaviour happens when I run the program out of GDB. The same "erratic" behaviour happens with program compiled with/without optimisation The same "erratic" behaviour happens while I have or not other programs running in background The images are always at the same place in the hard drive of my machine. I run the program on a Linux Suse distrib, compiled with gcc. So I am wondering what could affect the time of reading the images that much?

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  • Wpf. Chart optimization. More than million points

    - by Evgeny
    I have custom control - chart with size, for example, 300x300 pixels and more than one million points (maybe less) in it. And its clear that now he works very slowly. I am searching for algoritm which will show only few points with minimal visual difference. I have link to component which have functionallity exactly what i need (2 million points demo): http://www.mindscape.co.nz/demo/SilverlightElements/demopage.html#/ChartOverviewPage I will be grateful for any matherials, links or thoughts how to realize such functionallity.

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  • Slowing process creation under Java?

    - by oconnor0
    I have a single, large heap (up to 240GB, though in the 20-40GB range for most of this phase of execution) JVM [1] running under Linux [2] on a server with 24 cores. We have tens of thousands of objects that have to be processed by an external executable & then load the data created by those executables back into the JVM. Each executable produces about half a megabyte of data (on disk) that when read right in, after the process finishes, is, of course, larger. Our first implementation was to have each executable handle only a single object. This involved the spawning of twice as many executables as we had objects (since we called a shell script that called the executable). Our CPU utilization would start off high, but not necessarily 100%, and slowly worsen. As we began measuring to see what was happening we noticed that the process creation time [3] continually slows. While starting at sub-second times it would eventually grow to take a minute or more. The actual processing done by the executable usually takes less than 10 seconds. Next we changed the executable to take a list of objects to process in an attempt to reduce the number of processes created. With batch sizes of a few hundred (~1% of our current sample size), the process creation times start out around 2 seconds & grow to around 5-6 seconds. Basically, why is it taking so long to create these processes as execution continues? [1] Oracle JDK 1.6.0_22 [2] Red Hat Enterprise Linux Advanced Platform 5.3, Linux kernel 2.6.18-194.26.1.el5 #1 SMP [3] Creation of the ProcessBuilder object, redirecting the error stream, and starting it.

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  • What is microbenchmarking?

    - by polygenelubricants
    I've heard this term used, but I'm not entirely sure what it means, so: What DOES it mean and what DOESN'T it mean? What are some examples of what IS and ISN'T microbenchmarking? What are the dangers of microbenchmarking and how do you avoid it? (or is it a good thing?)

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  • Sql Server 2000 Stored Procedure Prevents Parallelism or something?

    - by user187305
    I have a huge disgusting stored procedure that wasn't slow a couple months ago, but now is. I barely know what this thing does and I am in no way interested in rewriting it. I do know that if I take the body of the stored procedure and then declare/set the values of the parameters and run it in query analyzer that it runs more than 20x faster. From the internet, I've read that this is probably due to a bad cached query plan. So, I've tried running the sp with "WITH RECOMPILE" after the EXEC and I've also tried putting the "WITH RECOMPLE" inside the sp, but neither of those helped even a little bit. When I look at the execution plan of the sp vs the query, the biggest difference is that the sp has "Parallelism" operations all over the place and the query doesn't have any. Can this be the cause of the difference in speeds? Thank you, any ideas would be great... I'm stuck.

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