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  • Large ListView containing images in Android

    - by Marco W.
    For various Android applications, I need large ListViews, i.e. such views with 100-300 entries. All entries must be loaded in bulk when the application is started, as some sorting and processing is necessary and the application cannot know which items to display first, otherwise. So far, I've been loading the images for all items in bulk as well, which are then saved in an ArrayList<CustomType> together with the rest of the data for each entry. But of course, this is not a good practice, as you're very likely to have an OutOfMemoryException then: The references to all images in the ArrayList prevent the garbage collector from working. So the best solution is, obviously, to load only the text data in bulk whereas the images are then loaded as needed, right? The Google Play application does this, for example: You can see that images are loaded as you scroll to them, i.e. they are probably loaded in the adapter's getView() method. But with Google Play, this is a different problem, anyway, as the images must be loaded from the Internet, which is not the case for me. My problem is not that loading the images takes too long, but storing them requires too much memory. So what should I do with the images? Load in getView(), when they are really needed? Would make scrolling sluggish. So calling an AsyncTask then? Or just a normal Thread? Parametrize it? I could save the images that are already loaded into a HashMap<String,Bitmap>, so that they don't need to be loaded again in getView(). But if this is done, you have the memory problem again: The HashMap stores references to all images, so in the end, you could have the OutOfMemoryException again. I know that there are already lots of questions here that discuss "Lazy loading" of images. But they mainly cover the problem of slow loading, not too much memory consumption.

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  • Fastest way to perform subset test operation on a large collection of sets with same domain

    - by niktech
    Assume we have trillions of sets stored somewhere. The domain for each of these sets is the same. It is also finite and discrete. So each set may be stored as a bit field (eg: 0000100111...) of a relatively short length (eg: 1024). That is, bit X in the bitfield indicates whether item X (of 1024 possible items) is included in the given set or not. Now, I want to devise a storage structure and an algorithm to efficiently answer the query: what sets in the data store have set Y as a subset. Set Y itself is not present in the data store and is specified at run time. Now the simplest way to solve this would be to AND the bitfield for set Y with bit fields of every set in the data store one by one, picking the ones whose AND result matches Y's bitfield. How can I speed this up? Is there a tree structure (index) or some smart algorithm that would allow me to perform this query without having to AND every stored set's bitfield? Are there databases that already support such operations on large collections of sets?

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  • Statistical analysis on large data set to be published on the web

    - by dassouki
    I have a non-computer related data logger, that collects data from the field. This data is stored as text files, and I manually lump the files together and organize them. The current format is through a csv file per year per logger. Each file is around 4,000,000 lines x 7 loggers x 5 years = a lot of data. some of the data is organized as bins item_type, item_class, item_dimension_class, and other data is more unique, such as item_weight, item_color, date_collected, and so on ... Currently, I do statistical analysis on the data using a python/numpy/matplotlib program I wrote. It works fine, but the problem is, I'm the only one who can use it, since it and the data live on my computer. I'd like to publish the data on the web using a postgres db; however, I need to find or implement a statistical tool that'll take a large postgres table, and return statistical results within an adequate time frame. I'm not familiar with python for the web; however, I'm proficient with PHP on the web side, and python on the offline side. users should be allowed to create their own histograms, data analysis. For example, a user can search for all items that are blue shipped between week x and week y, while another user can search for sort the weight distribution of all items by hour for all year long. I was thinking of creating and indexing my own statistical tools, or automate the process somehow to emulate most queries. This seemed inefficient. I'm looking forward to hearing your ideas Thanks

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  • Python Speeding Up Retrieving data from extremely large string

    - by Burninghelix123
    I have a list I converted to a very very long string as I am trying to edit it, as you can gather it's called tempString. It works as of now it just takes way to long to operate, probably because it is several different regex subs. They are as follow: tempString = ','.join(str(n) for n in coords) tempString = re.sub(',{2,6}', '_', tempString) tempString = re.sub("[^0-9\-\.\_]", ",", tempString) tempString = re.sub(',+', ',', tempString) clean1 = re.findall(('[-+]?[0-9]*\.?[0-9]+,[-+]?[0-9]*\.?[0-9]+,' '[-+]?[0-9]*\.?[0-9]+'), tempString) tempString = '_'.join(str(n) for n in clean1) tempString = re.sub(',', ' ', tempString) Basically it's a long string containing commas and about 1-5 million sets of 4 floats/ints (mixture of both possible),: -5.65500020981,6.88999986649,-0.454999923706,1,,,-5.65500020981,6.95499992371,-0.454999923706,1,,, The 4th number in each set I don't need/want, i'm essentially just trying to split the string into a list with 3 floats in each separated by a space. The above code works flawlessly but as you can imagine is quite time consuming on large strings. I have done a lot of research on here for a solution but they all seem geared towards words, i.e. swapping out one word for another. EDIT: Ok so this is the solution i'm currently using: def getValues(s): output = [] while s: # get the three values you want, discard the 3 commas, and the # remainder of the string v1, v2, v3, _, _, _, s = s.split(',', 6) output.append("%s %s %s" % (v1.strip(), v2.strip(), v3.strip())) return output coords = getValues(tempString) Anyone have any advice to speed this up even farther? After running some tests It still takes much longer than i'm hoping for. I've been glancing at numPy, but I honestly have absolutely no idea how to the above with it, I understand that after the above has been done and the values are cleaned up i could use them more efficiently with numPy, but not sure how NumPy could apply to the above. The above to clean through 50k sets takes around 20 minutes, I cant imagine how long it would be on my full string of 1 million sets. I'ts just surprising that the program that originally exported the data took only around 30 secs for the 1 million sets

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  • Out-of-memory algorithms for addressing large arrays

    - by reve_etrange
    I am trying to deal with a very large dataset. I have k = ~4200 matrices (varying sizes) which must be compared combinatorially, skipping non-unique and self comparisons. Each of k(k-1)/2 comparisons produces a matrix, which must be indexed against its parents (i.e. can find out where it came from). The convenient way to do this is to (triangularly) fill a k-by-k cell array with the result of each comparison. These are ~100 X ~100 matrices, on average. Using single precision floats, it works out to 400 GB overall. I need to 1) generate the cell array or pieces of it without trying to place the whole thing in memory and 2) access its elements (and their elements) in like fashion. My attempts have been inefficient due to reliance on MATLAB's eval() as well as save and clear occurring in loops. for i=1:k [~,m] = size(data{i}); cur_var = ['H' int2str(i)]; %# if i == 1; save('FileName'); end; %# If using a single MAT file and need to create it. eval([cur_var ' = cell(1,k-i);']); for j=i+1:k [~,n] = size(data{j}); eval([cur_var '{i,j} = zeros(m,n,''single'');']); eval([cur_var '{i,j} = compare(data{i},data{j});']); end save(cur_var,cur_var); %# Add '-append' when using a single MAT file. clear(cur_var); end The other thing I have done is to perform the split when mod((i+j-1)/2,max(factor(k(k-1)/2))) == 0. This divides the result into the largest number of same-size pieces, which seems logical. The indexing is a little more complicated, but not too bad because a linear index could be used. Does anyone know/see a better way?

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  • Compact data structure for storing a large set of integral values

    - by Odrade
    I'm working on an application that needs to pass around large sets of Int32 values. The sets are expected to contain ~1,000,000-50,000,000 items, where each item is a database key in the range 0-50,000,000. I expect distribution of ids in any given set to be effectively random over this range. The operations I need on the set are dirt simple: Add a new value Iterate over all of the values. There is a serious concern about the memory usage of these sets, so I'm looking for a data structure that can store the ids more efficiently than a simple List<int>or HashSet<int>. I've looked at BitArray, but that can be wasteful depending on how sparse the ids are. I've also considered a bitwise trie, but I'm unsure how to calculate the space efficiency of that solution for the expected data. A Bloom Filter would be great, if only I could tolerate the false negatives. I would appreciate any suggestions of data structures suitable for this purpose. I'm interested in both out-of-the-box and custom solutions. EDIT: To answer your questions: No, the items don't need to be sorted By "pass around" I mean both pass between methods and serialize and send over the wire. I clearly should have mentioned this. There could be a decent number of these sets in memory at once (~100).

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  • How to optimize paging for large in memory database

    - by snakefoot
    I have an application where the entire database is implemented in memory using a stl-map for each table in the database. Each item in the stl-map is a complex object with references to other items in the other stl-maps. The application works with a large amount of data, so it uses more than 500 MByte RAM. Clients are able to contact the application and get a filtered version of the entire database. This is done by running through the entire database, and finding items relevant for the client. When the application have been running for an hour or so, then Windows 2003 SP2 starts to page out parts of the RAM for the application (Eventhough there is 16 GByte RAM on the machine). After the application have been partly paged out then a client logon takes a long time (10 mins) because it now generates a page fault for each pointer lookup in the stl-map. I can see it is possible to tell Windows to lock memory in RAM, but this is generally only recommended for device drivers, and only for "small" amounts of memory. I guess a poor mans solution could be to loop through the entire memory database, and thus tell Windows we are still interested in keeping the datamodel in RAM. I guess another poor mans solution could be to disable the pagefile completely on Windows. I guess the expensive solution would be a SQL database, and then rewrite the entire application to use a database layer. Then hopefully the database system will have implemented means to for fast access. Are there other more elegant solutions ?

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  • Handling large (object) datasets with PHP

    - by Aron Rotteveel
    I am currently working on a project that extensively relies on the EAV model. Both entities as their attributes are individually represented by a model, sometimes extending other models (or at least, base models). This has worked quite well so far since most areas of the application only rely on filtered sets of entities, and not the entire dataset. Now, however, I need to parse the entire dataset (IE: all entities and all their attributes) in order to provide a sorting/filtering algorithm based on the attributes. The application currently consists of aproximately 2200 entities, each with aproximately 100 attributes. Every entity is represented by a single model (for example Client_Model_Entity) and has a protected property called $_attributes, which is an array of Attribute objects. Each entity object is about 500KB, which results in an incredible load on the server. With 2000 entities, this means a single task would take 1GB of RAM (and a lot of CPU time) in order to work, which is unacceptable. Are there any patterns or common approaches to iterating over such large datasets? Paging is not really an option, since everything has to be taken into account in order to provide the sorting algorithm.

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  • download large files using servlet

    - by niks
    I am using Apache Tomcat Server 6 and Java 1.6 and am trying to write large mp3 files to the ServletOutputStream for a user to download. Files are ranging from a 50-750MB at the moment. The smaller files aren't causing too much of a problem but with the larger files it and getting socket exception broken pipe. File fileMp3 = new File(objDownloadSong.getStrSongFolder() + "/" + strSongIdName); FileInputStream fis = new FileInputStream(fileMp3); response.setContentType("audio/mpeg"); response.setHeader("Content-Disposition", "attachment; filename=\"" + strSongName + ".mp3\";"); response.setContentLength((int) fileMp3.length()); OutputStream os = response.getOutputStream(); try { int byteRead = 0; while ((byteRead = fis.read()) != -1) { os.write(byteRead); } os.flush(); } catch (Exception excp) { downloadComplete = "-1"; excp.printStackTrace(); } finally { os.close(); fis.close(); }

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  • Large Switch statements: Bad OOP?

    - by Mystere Man
    I've always been of the opinion that large switch statements are a symptom of bad OOP design. In the past, I've read articles that discuss this topic and they have provided altnerative OOP based approaches, typically based on polymorphism to instantiate the right object to handle the case. I'm now in a situation that has a monsterous switch statement based on a stream of data from a TCP socket in which the protocol consists of basically newline terminated command, followed by lines of data, followed by an end marker. The command can be one of 100 different commands, so I'd like to find a way to reduce this monster switch statement to something more manageable. I've done some googling to find the solutions I recall, but sadly, Google has become a wasteland of irrelevant results for many kinds of queries these days. Are there any patterns for this sort of problem? Any suggestions on possible implementations? One thought I had was to use a dictionary lookup, matching the command text to the object type to instantiate. This has the nice advantage of merely creating a new object and inserting a new command/type in the table for any new commands. However, this also has the problem of type explosion. I now need 100 new classes, plus I have to find a way to interface them cleanly to the data model. Is the "one true switch statement" really the way to go? I'd appreciate your thoughts, opinions, or comments.

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  • Android and fairly large SQLite datafiles

    - by SK9
    I'm starting an Android project, a port from an existing iPhone project I've completed. I have a fairly large read-only SQLite database, about 100Mb in all. It's called "mydata.sqlite". Where do I place this in my Eclipse workspace? It's too big for "assets". Next, how do I best get at the file? I would think to try (handling exceptions later) something like: SQLiteDatabase myDatabase = null; myDatabase = SQLiteDatabase.openDatabase(myPath, null, SQLiteDatabase.OPEN_READONLY); But I would then need the path string myPath and since I don't know where to put the resource I don't know what this needs to be. Can I put "mydata.sqlite" into "res/raw" (once I create "raw" in Eclipse?) and then referene it as a resource with "R.raw.mydata"? I would very much appreciate some direct help here, rather than a reference to a tutorial. I have checked tons of these, including those that are already cited here on stackoverflow. I've also gone through the "Notepad" project in the Android developer documents. However these and the documentation typically consider only new, empty or small databases. This should be a simple thing and given the time I've spent already it is perhaps easier to ask. Thanking you kindly in advance for your assistance.

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  • C++ : integer constant is too large for its type

    - by user38586
    I need to bruteforce a year for an exercise. The compiler keep throwing this error: bruteforceJS12.cpp:8:28: warning: integer constant is too large for its type [enabled by default] My code is: #include <iostream> using namespace std; int main(){ unsigned long long year(0); unsigned long long result(318338237039211050000); unsigned long long pass(1337); while (pass != result) { for (unsigned long long i = 1; i<= year; i++) { pass += year * i * year; } cout << "pass not cracked with year = " << year << endl; ++year; } cout << "pass cracked with year = " << year << endl; } Note that I already tried with unsigned long long result(318338237039211050000ULL); I'm using gcc version 4.8.1 EDIT: Here is the corrected version using InfInt library http://code.google.com/p/infint/ #include <iostream> #include "InfInt.h" using namespace std; int main(){ InfInt year = "113"; InfInt result = "318338237039211050000"; InfInt pass= "1337"; while (pass != result) { for (InfInt i = 1; i<= year; i++) { pass += year * i * year; } cout << "year = " << year << " pass = " << pass << endl; ++year; } cout << "pass cracked with year = " << year << endl; }

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  • Efficient way to get highly correlated pairs from large data set in Python or R

    - by Akavall
    I have a large data set (Let's say 10,000 variables with about 1000 elements each), we can think of it as 2D list, something like: [[variable_1], [variable_2], ............ [variable_n] ] I want to extract highly correlated variable pairs from that data. I want "highly correlated" to be a parameter that I can choose. I don't need all pairs to be extracted, and I don't necessarily want the most correlated pairs. As long as there is an efficient method that gets me highly correlated pairs I am happy. Also, it would be nice if a variable does not show up in more than one pair. Although this might not be crucial. Of course, there is a brute force way to finding such pairs, but it is too slow for me. I've googled around for a bit and found some theoretical work on this issue, but I wasn't able for find a package that could do what I am looking for. I mostly work in python, so a package in python would be most helpful, but if there exists a package in R that does what I am looking for it will be great. Does anyone know of a package that does the above in Python or R? Or any other ideas? Thank You in Advance

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  • Spreadsheet_Excel_Writer large data output is damaged

    - by dr3w
    I use Spreadsheet_Excel_Writer to generate .xls file and it works fine until I have to deal with a large amount of data. On certain stage it just writes some nonsense chars and quits filling certain columns. However some columns are field up to the end (generally numeric data) I'm not quite sure how the xls document is formed: row by row, or col by col... Also it is obviously not an error in a string, because when i cut out some data, the error appears a little bit further. I think there is no need in all of my code here are some essentials $filename = 'file.xls'; $workbook = & new Spreadsheet_Excel_Writer(); $workbook->setVersion(8); $contents =& $workbook->addWorksheet('Logistics'); $contents->setInputEncoding('UTF-8'); $workbook->send($filename); //here is the part where I write data down $contents->write(0, 0, 'Field A'); $contents->write(0, 1, 'Field B'); $contents->write(0, 2, 'Field C'); $ROW=1; foreach($ordersArr as $key=>$val){ $contents->write($ROW, 0, $val['a']); $contents->write($ROW, 1, $val['b']); $contents->write($ROW, 2, $val['c']); $ROW++; } $workbook->close();

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  • Storing large numbers of varying size objects on disk

    - by Foredecker
    I need to develop a system for storing large numbers (10's to 100's of thousands) of objects. Each object is email-like - there is a main text body, and several ancillary text fields of limited size. A body will be from a few bytes, to several KB in size. Each item will have a single unique ID (probably a GUID) that identifies it. The store will only be written to when an object is added to it. It will be read often. Deletions will be rare. The data is almost all human readable text so it will be readily compressible. A system that lets me issue the I/Os and mange the memory and caching would be ideal. I'm going to keep the indexes in memory, using it to map indexes to the single (and primary) key for the objects. Once I have the key, then I'll load it from disk, or the cache. The data management system needs to be part of my application - I do not want to depend on OS services. Or separately installed packages. Native (C++) would be best, but a manged (C#) thing would be ok. I believe that a database is an obvious choice, but this needs to be super-fast for look up and loading into memory of an object. I am not experienced with data base tech and I'm concerned that general relational systems will not handle all this variable sized data efficiently. (Note, this has nothing to do with my job - its a personal project.) In your experience, what are the viable alternatives to a traditional relational DB? Or would a DB work well for this?

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  • Handling large datasets with PHP/Drupal

    - by jo
    Hi all, I have a report page that deals with ~700k records from a database table. I can display this on a webpage using paging to break up the results. However, my export to PDF/CSV functions rely on processing the entire data set at once and I'm hitting my 256MB memory limit at around 250k rows. I don't feel comfortable increasing the memory limit and I haven't got the ability to use MySQL's save into outfile to just serve a pre-generated CSV. However, I can't really see a way of serving up large data sets with Drupal using something like: $form = array(); $table_headers = array(); $table_rows = array(); $data = db_query("a query to get the whole dataset"); while ($row = db_fetch_object($data)) { $table_rows[] = $row->some attribute; } $form['report'] = array('#value' => theme('table', $table_headers, $table_rows); return $form; Is there a way of getting around what is essentially appending to a giant array of arrays? At the moment I don't see how I can offer any meaningful report pages with Drupal due to this. Thanks

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  • Storing large json strings to database + hash

    - by Guy
    I need to store quiete large JSON data strings to the database. I am using gzip to compress the string and therefore BLOB MySQL data type to store it. However, only 5% of all the requests contain unique data and only unique data ought to be stored to the database. My approach is as follows. array_multisort data (array [a, b, c] is virtually the same as [a, c, b]). json_encode data (json_encode is faster than serialize; we need string array representation for the step 3). sha1 data (slower than md5, though less possible the collisions). Check if the hash exists in the database. 5.1 yes – do not insert the data. 5.2. no – gzip the data and store it along the hash. Is there anything about this (apart from storing JSON data to the database in the first place) that sounds fishy or should be done a different way? p.s. We are talking about a database with roughly 1kk unique records being created every month.

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  • Why S3 website redirect location is not followed by CloudFront?

    - by ychaze
    I have a website hosted on Amazon S3. It is the new version of an old website hosted on WordPress. I have set up some files with the metadata Website Redirect Locationto handle old location and redirect them to the new website pages. For example: I had http://www.mysite.com/solution that I want to redirect to http://mysite.s3-website-us-east-1.amazonaws.com/product.html So I created an empty file named solutioninside my bucket with the correct metadata: Website Redirect Location= /product.html The S3 redirect metadata is equivalent to a 301 Moved Permanentlythat is great for SEO. This works great when accessing the URL directly from S3 domain. I have also set up a CloudFront distribution based on the website bucket. And when I try to access through my distribution, the redirect does not work, ie: http://xxxx123.cloudfront.net/solution does not redirect but download the empty file instead. So my question is how to keep the redirection through the CloudFront distribution ? Or any idea on how to handle the redirection without deteriorate SEO ? Thanks

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  • How to make sure clients update their browser cache when my website is updated?

    - by user64204
    I am using the HTTP 1.1 Cache-Control header to implement client-side caching. Since I update my website only once a month I would like the CSS and JS files to be cached for 30 days with Cache-Control: max-age=2592000. The problem is that the 30-day period defined by Cache-Control doesn't coincide with the website update cycle, it starts from the moment the users visit the site and ends 30 days later, which means an update could occur in the meantime and users would be running with outdated content for a while, which could break the rendering of the website if for instance the HTML and CSS no longer match. How can I perform client-side caching of content for periods of several days but somehow get users to refresh their CSS/JS files after the website has been updated? One solution I could think of is that if website updates can be schedule, the max-age returned by the server could be decreased every day accordingly so that no matter when people visit the website, the end of caching period would coincide with the update of the website, but changing the server configuration every day goes against one of my sysadmin principles (once it's running, don't touch it).

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  • Unable to set nginx to serve my staging website

    - by user100778
    I'm having some troubles setting up nginx to serve my staging website. What I did is change the server_name but for some reasons it just doesn't work. The url scheme is "domain.foo" is production, "staging.domain.foo" is staging, "foobar.domain.foo" is a web service, "foobar.staging.domain.foo" is the staging version of the same webserver, ".domain.foo" is routed to serve some s3 static HTML, ".staging.domain.foo" is routed to serve some s3 static HTML in another bucket. All production urls work and are correctly configured, all staging urls doesn't work. Here is my conf file. You will see some duplication, I will gladly accept any correction/optimization, I'm a coder and configuring servers is definitely not my thing (but I'm eager to learn and improve...). server { listen 80; ## listen for ipv4 server_name "domain.foo" "www.domain.foo" default_server; access_log /var/log/nginx/access.log; client_max_body_size 5M; location / { proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header Host $http_host; proxy_redirect off; location ~* \.(jpg|jpeg|gif|png|ico|css|bmp|js|html)$ { access_log off; expires max; root /home/foo/Foo/current/public; break; } if ($host ~ 'www.domain.foo') { rewrite ^/(.*)$ http://domain/foo/$1 permanent; } proxy_pass http://production; break; } } server { listen 80; server_name "staging.domain.foo"; access_log /var/log/nginx/access.staging.log; error_log /var/log/nginx/error.staging.log; client_max_body_size 5M; location / { proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header Host $http_host; proxy_redirect off; proxy_pass http://staging; break; } } server { listen 80; ## listen for ipv4 server_name "foobar.domain.foo"; access_log /var/log/nginx/access.log; location / { proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header Host $http_host; proxy_redirect off; if ($host = 'foobar.domain.foo') { proxy_pass http://foobar; break; } } } server { listen 80; ## listen for ipv4 server_name foobar.staging.domain.foo; location / { proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header Host $http_host; proxy_redirect off; proxy_pass http://foobar_staging; break; } } server { listen 80; server_name "~^(.+)\.domain\.foo$"; location / { proxy_intercept_errors on; error_page 404 = http://domain.foo/404; set $subdomain $1; rewrite /$ "/$subdomain/index.html" break; rewrite ^ /$subdomain$request_uri? break; proxy_pass http://bucket.domain.foo.s3.amazonaws.com; } } server { listen 80; server_name "~^(.+)\.staging\.domain\.foo$"; location / { proxy_intercept_errors on; set $subdomain $1; rewrite /$ "/$subdomain/index.html" break; rewrite ^ /$subdomain$request_uri? break; proxy_pass http://bucket.staging.domain.foo.s3.amazonaws.com; } } upstream production { server 111.255.111.110:8000; server 111.255.111.110:8001; server 111.255.111.110:8002; server 111.255.111.110:8003; } upstream staging { server 222.255.222.222:8000; server 222.255.222.222:8001; } upstream foobar { server 111.255.222.165:9000; server 111.255.222.165:9001; server 111.255.222.165:9002; } upstream foobar_staging { server 222.255.222.222:9000; } What happens now when I point my browser to staging.domain.foo is that it hangs. Can't find anything in the logs, but for example the access.staging.log and errors.staging.log are created. Anybody has an idea? :)

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  • Are there any B-tree programs or sites that show visually how a B-tree works

    - by Phenom
    I found this website that lets you insert and delete items from a B-tree and shows you visually what the B-tree looks like: java b-tree I'm looking for another website or program similar to this. This site does not allow you to specify a B-tree of order 4 (4 pointers and 3 elements), it only lets you specify B-trees with an even number of elements. Also, if possible, I'd like to be able to insert letters instead of numbers. I think I actually found a different site but that was a while ago and can't find it anymore.

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  • Kohana multi language website

    - by Sobek
    .I'm trying to set up a multi language website with kohana v3, following this tutorial: http://kerkness.ca/wiki/doku.php?id=example_of_a_multi-language_website Routing to a controller or action within i.e. website/controller/action seems to work as the url is properly redirected to website/lang/controller/action. However this is not working for ajax request calls. I have to manually edit the url with the appropriate language, to successfully retrieve the data. This also applies for anchors on the html page. In addition to this problem, the overflow parameter 'id' also doesn't work. It takes the 'lang' variable as its parameter. I have setup my default route just like in the tutorial i.e.: Route::set('default', '((<lang>)(/)(<controller>)(/<action>(/<id>)))', array('lang' => "({$langs_abr})",'id'=>'.+')) ->defaults(array('lang' => $default_lang,'controller' => welcome', 'action' => 'index')); Any help is much appreciated ! Cheers

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  • How do I reset the scale/zoom of a web app on an orientation change on the iPhone?

    - by Elisabeth
    I'm having the same problem that a couple of others have had with getting the correct behavior in a web app on an orientation change, and there doesn't seem to be an obvious solution - I've seen this question asked a couple of times on Stack Overflow and no one's yet been able to answer it. When I start the app in portrait mode, it works fine. Then I rotate into landscape and it's scaled up. To get it to scale correctly for the landscape mode I have to double tap on something twice, first to zoom all the way in (the normal double tap behavior) and again to zoom all the way out (again, the normal double tap behavior). When it zooms out, it zooms out to the correct NEW scale for landscape mode. Switching back to portrait seems to work more consistently; that is, it handles the zoom so that the scale is correct when the orientation changes back to portrait. I am trying to figure out if this is a bug? or if this is something that can be fixed with Javascript? With the viewport meta content, I am setting the initial-scale to 1.0 and I am NOT setting minimum or maximum scale (nor do I want to). I am setting the width to device-width. Any ideas? I know a lot of people would be grateful to have a solution as it seems to be a persistent problem. Thank you!

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  • Website (jQuery) consistently crashes Internet Explorer (REALLY STUCK!)

    - by Bradley Bell
    Hey Guys. I posted this question yesterday, but haven't had a response. Basically, I'm totally stuck and clueless over crashing in Internet Explorer. The website now works fine in all browsers except internet explorer. The website is heavily reliant on jQuery and as far as I'm aware, I cant spot anything wrong with the script. Internet Explorer displays no errors and I don't know what I can possibly change. It displays fine, which would suggest that its nothing up with the CSS or HTML? I'm fairly sure it has to be the script, because it only crashes when you hover over one of the mouseover links. I'm already over the deadline and time is ticking! Its driving me crazy. I've uploaded it onto a test directory here: www.openyourheart.org.uk/test/index.html (I'll add the script/css links below as a comment, It wont let me post more than one here!) I would reaaly, really appreciate any help on this. I can also send the website compressed and post scripts here if required/preferred. Thanks in advance, Bradley

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  • Upload large files via a webpage

    - by Hultner
    What way is the best way to let users upload large files from there webbrowser to a server. I'm talking 200MB+ possible up to a few gigatyes. I have been thinking of a few possible solutions to the problem (not tried them yet) and this is basically the things I came up with. Server download speed will not be a problem but the users connection possibly could. Having some sort of applet on the client side written in Java or Flash which sends the file in parts (is this possible with an applet) to a php/other script on the server and a checksum+ some other info about the file. On the server scripts all the parts and the info file is saved in a temporary directory wich has a unique name based on the checksum of the file and the ip of the user. When the last chunk is sent the applet sends a signal to the server saying it's finished and the server put the file together in the right location. If a chunk doesn't match the checksum for that part the server will send a response to the applet telling it to reupload that chunk. I don't know how important the checksum checking is since it's all tcpackages, someone with more insigth migth be able to answer on that. This is probably the worst way, changing the settings on your server to allow huge fileuploads via an inputfiel. Do it like a normal transfer. User an uploadmanager which does pretty much the same thing as applet i mentioned above. Pros of the first is probably that it would most likely be rather secure, you could show progress as well and possibly resume an upload if ip hasn't changed and do a threaded upload of the chunks. Cons of the first is that the user will need flash/java for it to work. Pros of the 2nd is that it will pretty much work for everyone but cons are big, first there's no way resuming an intruppted download and if something is wrong the whole file would have to be reuploaded is a few of cons. For the third one the pros is pretty muc the same as for the first but the cons is that the user would have to download an application to their computer and run and the application will have to be have to be compatible with their computer and OS. Another way may be a combination of two. Lets say an applet for bigger or more files and a simple input which is rather restricted to maybe max 10-20MB for smaller files and comability. There are probably other much smarter ways to tackle this and that's why I'm asking for advice here on SO.

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