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• solution for an offline server

  - by dashmug

  I'm trying to setup a development server at work that will ideally be able to test drive a couple of projects in PHP, Rails, or Django (not always running at the same time). I develop the apps locally on a Mac and then I'll put the projects up on this server for testing with my actual users (non-techies) before deploying to a production server. My problem is that we have a very poor internet connection (almost negligible) at work and doing the usual apt-get/yum/ports (make, clean, install) processes for setting up servers always get their packages from online repositories somewhere. I know I could probably download the source and then compile them myself but that's going to be too much of a hassle for me. I'm thinking about two solutions: Plan A: Run a server VM on my Mac and then use this VM as the source repository for the offline server. I've read about Ubuntu's apt-proxy and it seems to be good enough though I haven't tried it yet. I'm not sure if this is possible but can I simply do apt-get install nginx --downloadonly so that the package and its dependencies will be downloaded into my VM and my server can use the VM as the source repo for apt-get? Plan B: Run a server VM on my Mac (which I can setup/update easily when I'm home) and then clone the VM to the offline development server. Maybe I should simply make the server a VM host so I can simply copy the VM over. I think this is okay for the first-time setup but subsequent updates will take too long (cloning the VM image). If I was working on Windows, I imagine it'd be easier because most services have an installer file that I can download and then run at the server. If you could suggest another way, it would be much appreciated. Update: From Michael Hampton's answer, I found a possible solution which is apt-cacher. I also found this page on Ubuntu's website. I wonder if there is a better tool than this one.

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• Where can someone store >100GB of pictures online? [closed]

  - by sbi

  A person who is not very computer-savvy needs to store 130GB of photos. The key parameters are: an non-negligible probability that the company selling the storage will be existing, and the data accessible, for at least five years data should be considered safe once uploaded reasonable terms of service: google drive reserving the right to literally do anything they want with their user's data is not acceptable; the possibility that the CIA might look at those pictures is not considered a threat easy to use from Windows, preferably as a drive no nerve-wracking limitations ("cannot upload 10GB/day" or "files 500MB" etc.) that serve no purpose other than pushing the user to the next-higher price plan some upgrade plan: there's currently 10-30GB of new photos per year, with a tendency to increase, which might bust a 150GB limit next January ability to somehow sort the pictures: currently they are sorted into folders, but something alike (tags) would be just as good, if easy enough to apply of course, the pricing is important (although there's a reason this is the last bullet; reasonable data safety is considered more important) Nice to have, but not necessary features would be: additional features related to photos (thumbnail generation, album sharing etc.) access from web and other platforms than Windows (smart phones) Let me stress this again: The person in need of that is able to copy pictures from the camera to the computer, can copy files in the explorer, and uses a web email service. That's about it, there's almost no understanding of what happens under the hood.

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• How do NTP Servers Manage to Stay so Accurate?

  - by Akemi Iwaya

  Many of us have had the occasional problem with our computers and other devices retaining accurate time settings, but a quick sync with an NTP server makes all well again. But if our own devices can lose accuracy, how do NTP servers manage to stay so accurate? Today’s Question & Answer session comes to us courtesy of SuperUser—a subdivision of Stack Exchange, a community-driven grouping of Q&A web sites. Photo courtesy of LEOL30 (Flickr). The Question SuperUser reader Frank Thornton wants to know how NTP servers are able to remain so accurate: I have noticed that on my servers and other machines, the clocks always drift so that they have to sync up to remain accurate. How do the NTP server clocks keep from drifting and always remain so accurate? How do the NTP servers manage to remain so accurate? The Answer SuperUser contributor Michael Kjorling has the answer for us: NTP servers rely on highly accurate clocks for precision timekeeping. A common time source for central NTP servers are atomic clocks, or GPS receivers (remember that GPS satellites have atomic clocks onboard). These clocks are defined as accurate since they provide a highly exact time reference. There is nothing magical about GPS or atomic clocks that make them tell you exactly what time it is. Because of how atomic clocks work, they are simply very good at, having once been told what time it is, keeping accurate time (since the second is defined in terms of atomic effects). In fact, it is worth noting that GPS time is distinct from the UTC that we are more used to seeing. These atomic clocks are in turn synchronized against International Atomic Time or TAI in order to not only accurately tell the passage of time, but also the time. Once you have an exact time on one system connected to a network like the Internet, it is a matter of protocol engineering enabling transfer of precise times between hosts over an unreliable network. In this regard a Stratum 2 (or farther from the actual time source) NTP server is no different from your desktop system syncing against a set of NTP servers. By the time you have a few accurate times (as obtained from NTP servers or elsewhere) and know the rate of advancement of your local clock (which is easy to determine), you can calculate your local clock’s drift rate relative to the “believed accurate” passage of time. Once locked in, this value can then be used to continuously adjust the local clock to make it report values very close to the accurate passage of time, even if the local real-time clock itself is highly inaccurate. As long as your local clock is not highly erratic, this should allow keeping accurate time for some time even if your upstream time source becomes unavailable for any reason. Some NTP client implementations (probably most ntpd daemon or system service implementations) do this, and others (like ntpd’s companion ntpdate which simply sets the clock once) do not. This is commonly referred to as a drift file because it persistently stores a measure of clock drift, but strictly speaking it does not have to be stored as a specific file on disk. In NTP, Stratum 0 is by definition an accurate time source. Stratum 1 is a system that uses a Stratum 0 time source as its time source (and is thus slightly less accurate than the Stratum 0 time source). Stratum 2 again is slightly less accurate than Stratum 1 because it is syncing its time against the Stratum 1 source and so on. In practice, this loss of accuracy is so small that it is completely negligible in all but the most extreme of cases. Have something to add to the explanation? Sound off in the comments. Want to read more answers from other tech-savvy Stack Exchange users? Check out the full discussion thread here.

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• Is the Leptonica implementation of 'Modified Median Cut' not using the median at all?

  - by TheCodeJunkie

  I'm playing around a bit with image processing and decided to read up on how color quantization worked and after a bit of reading I found the Modified Median Cut Quantization algorithm. I've been reading the code of the C implementation in Leptonica library and came across something I thought was a bit odd. Now I want to stress that I am far from an expert in this area, not am I a math-head, so I am predicting that this all comes down to me not understanding all of it and not that the implementation of the algorithm is wrong at all. The algorithm states that the vbox should be split along the lagest axis and that it should be split using the following logic The largest axis is divided by locating the bin with the median pixel (by population), selecting the longer side, and dividing in the center of that side. We could have simply put the bin with the median pixel in the shorter side, but in the early stages of subdivision, this tends to put low density clusters (that are not considered in the subdivision) in the same vbox as part of a high density cluster that will outvote it in median vbox color, even with future median-based subdivisions. The algorithm used here is particularly important in early subdivisions, and 3is useful for giving visible but low population color clusters their own vbox. This has little effect on the subdivision of high density clusters, which ultimately will have roughly equal population in their vboxes. For the sake of the argument, let's assume that we have a vbox that we are in the process of splitting and that the red axis is the largest. In the Leptonica algorithm, on line 01297, the code appears to do the following Iterate over all the possible green and blue variations of the red color For each iteration it adds to the total number of pixels (population) it's found along the red axis For each red color it sum up the population of the current red and the previous ones, thus storing an accumulated value, for each red note: when I say 'red' I mean each point along the axis that is covered by the iteration, the actual color may not be red but contains a certain amount of red So for the sake of illustration, assume we have 9 "bins" along the red axis and that they have the following populations 4 8 20 16 1 9 12 8 8 After the iteration of all red bins, the partialsum array will contain the following count for the bins mentioned above 4 12 32 48 49 58 70 78 86 And total would have a value of 86 Once that's done it's time to perform the actual median cut and for the red axis this is performed on line 01346 It iterates over bins and check they accumulated sum. And here's the part that throws me of from the description of the algorithm. It looks for the first bin that has a value that is greater than total/2 Wouldn't total/2 mean that it is looking for a bin that has a value that is greater than the average value and not the median ? The median for the above bins would be 49 The use of 43 or 49 could potentially have a huge impact on how the boxes are split, even though the algorithm then proceeds by moving to the center of the larger side of where the matched value was.. Another thing that puzzles me a bit is that the paper specified that the bin with the median value should be located, but does not mention how to proceed if there are an even number of bins.. the median would be the result of (a+b)/2 and it's not guaranteed that any of the bins contains that population count. So this is what makes me thing that there are some approximations going on that are negligible because of how the split actually takes part at the center of the larger side of the selected bin. Sorry if it got a bit long winded, but I wanted to be as thoroughas I could because it's been driving me nuts for a couple of days now ;)

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• How to improve WinForms MSChart performance?

  - by Marcel

  Hi all, I have created some simple charts (of type FastLine) with MSChart and update them with live data, like below: . To do so, I bind an observable collection of a custom type to the chart like so: // set chart data source this._Chart.DataSource = value; //is of type ObservableCollection<SpectrumLevels> //define x and y value members for each series this._Chart.Series[0].XValueMember = "Index"; this._Chart.Series[1].XValueMember = "Index"; this._Chart.Series[0].YValueMembers = "Channel0Level"; this._Chart.Series[1].YValueMembers = "Channel1Level"; // bind data to chart this._Chart.DataBind(); //lasts 1.5 seconds for 8000 points per series At each refresh, the dataset completely changes, it is not a scrolling update! With a profiler I have found that the DataBind() call takes about 1.5 seconds. The other calls are negligible. How can I make this faster? Should I use another type than ObservableCollection? An array probably? Should I use another form of data binding? Is there some tweak for the MSChart that I may have missed? Should I use a sparsed set of date, having one value per pixel only? Have I simply reached the performance limit of MSCharts? From the type of the application to keep it "fluent", we should have multiple refreshes per second. Thanks for any hints!

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• System.Threading.Timer keep reference to it.

  - by Daniel Bryars

  According to [http://msdn.microsoft.com/en-us/library/system.threading.timer.aspx][1] you need to keep a reference to a System.Threading.Timer to prevent it from being disposed. I've got a method like this: private void Delay(Action action, Int32 ms) { if (ms <= 0) { action(); } System.Threading.Timer timer = new System.Threading.Timer( (o) => action(), null, ms, System.Threading.Timeout.Infinite); } Which I don't think keeps a reference to the timer, I've not seen any problems so far, but that's probably because the delay periods used have been pretty small. Is the code above wrong? And if it is, how to I keep a reference to the Timer? I'm thinking something like this might work: class timerstate { internal volatile System.Threading.Timer Timer; }; private void Delay2(Action action, Int32 ms) { if (ms <= 0) { action(); } timerstate state = new timerstate(); lock (state) { state.Timer = new System.Threading.Timer( (o) => { lock (o) { action(); ((timerstate)o).Timer.Dispose(); } }, state, ms, System.Threading.Timeout.Infinite); } The locking business is so I can get the timer into the timerstate class before the delegate gets invoked. It all looks a little clunky to me. Perhaps I should regard the chance of the timer firing before it's finished constructing and assigned to the property in the timerstace instance as negligible and leave the locking out.

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• Boost Mersenne Twister: how to seed with more than one value?

  - by Eamon Nerbonne

  I'm using the boost mt19937 implementation for a simulation. The simulation needs to be reproducible, and that means storing and potentially reusing the RNG seeds later. I'm using the windows crypto api to generate the seed values because I need an external source for the seeds and not because of any particular guarantees of randomness. The output of any simulation run will have a note including the RNG seed - so the seed needs to be reasonably short. On the other hand, as part of the analysis of the simulation, I'll be comparing several runs - but to be sure that these runs are actually different, I'll need to use different seeds - so the seed needs to be long enough to avoid accidental collisions. I've determined that 64-bits of seeding should suffice; the chance of a collision will reach 50% after about 2^32 runs - that probability is low enough that the average error caused by it is negligible to me. Using just 32-bits of seed is tricky; the chance of a collision reaches 50% already after 2^16 runs; and that's a little too likely for my tastes. Unfortunately, the boost implementation either seeds with a full state vector - which is far, far too long - or a single 32-bit unsigned long - which isn't ideal. How can I seed the generator with more than 32-bits but less than a full state vector? I tried just padding the vector or repeating the seeds to fill the state vector, but even a cursory glance at the results shows that that generates poor results.

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• Strange C++ performance difference?

  - by STingRaySC

  I just stumbled upon a change that seems to have counterintuitive performance ramifications. Can anyone provide a possible explanation for this behavior? Original code: for (int i = 0; i < ct; ++i) { // do some stuff... int iFreq = getFreq(i); double dFreq = iFreq; if (iFreq != 0) { // do some stuff with iFreq... // do some calculations with dFreq... } } While cleaning up this code during a "performance pass," I decided to move the definition of dFreq inside the if block, as it was only used inside the if. There are several calculations involving dFreq so I didn't eliminate it entirely as it does save the cost of multiple run-time conversions from int to double. I expected no performance difference, or if any at all, a negligible improvement. However, the perfomance decreased by nearly 10%. I have measured this many times, and this is indeed the only change I've made. The code snippet shown above executes inside a couple other loops. I get very consistent timings across runs and can definitely confirm that the change I'm describing decreases performance by ~10%. I would expect performance to increase because the int to double conversion would only occur when iFreq != 0. Chnaged code: for (int i = 0; i < ct; ++i) { // do some stuff... int iFreq = getFreq(i); if (iFreq != 0) { // do some stuff with iFreq... double dFreq = iFreq; // do some stuff with dFreq... } } Can anyone explain this? I am using VC++ 9.0 with /O2. I just want to understand what I'm not accounting for here.

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• Creative ways to punish (or just curb) laziness in coworkers

  - by FerretallicA

  Like the subject suggests, what are some creative ways to curb laziness in co-workers? By laziness I'm talking about things like using variable names like "inttheemplrcd" instead of "intEmployerCode" or not keeping their projects synced with SVN, not just people who use the last of the sugar in the coffee room and don't refill the jar. So far the two most effective things I've done both involve the core library my company uses. Since most of our programs are in VB.net the lack of case sensitivity is abused a lot. I've got certain features of the library using Reflection to access data in the client apps, which has a negligible performance hit and introduces case sensitivity in a lot places where it is used. In instances where we have an agreed standard which is compromised by blatant laziness I take it a step further, like the DatabaseController class which will blatantly reject any DataTable passed to it which isn't named dtSomething (ie- must begin with dt and third letter must be capitalised). It's frustrating to have to resort to things like this but it has also gradually helped drill more attention to detail into their heads. Another is adding some code to the library's initialisation function to display a big and potentially embarrassing (only if seen by a client) message advising that the program is running in debug mode. We have had many instances where projects are sent to clients built in debug mode which has a lot of implications for us (especially with regard to error recovery) and doing that has made sure they always build to release before distributing. Any other creative (ie- not StyleCop etc) approaches like this?

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• Several Small, Specific, MySQL Query Cache Questions

  - by Robbie

  I've look all over the web and in the questions asked here about MySQL caching and most of them seem very non-specific about a couple of questions that I have about performance and MySQL query caching. Specifically I want answers to these questions, assume for all questions that I have the query cache enabled and it is of type 2, or "DEMAND": Is the query cache per table, per database, or per server? Meaning if I have the cache size set to X and have T tables and D databases will I be caching TX, DX, or X amount of data? If I have table T1 which I regularly use the SQL_CACHE hint on for SELECT queries and table T2 which I never do, when I query T2 with a SELECT query will it check through the cache first before performing the query? *Note: I don't want to use the SQL_NO_CACHE for all T2 queries.* Assume the same situation as in question 2. If I alter (INSERT, DELETE) table T2 will any processing be done on the cache? For answers to 2 and 3, is this processing time negligible if T2 is constantly being altered and is the target of a majority of my SELECT queries?

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• Moving a ASP.NET application to the cloud

  - by user102533

  I am new to cloud computing, so please bear with me here. I have an existing ASP.NET application with SQL Server 2008 hosted on a Virtual Private Server. Here's what it briefly does: The front end accepts user's requests and adds them to a DB table A Windows Service running in the background picks up the request, processes it and sets a flag. The Windows Services also creates a file for the user to download. User downloads file I'd like to move this web application with the service to the cloud. The architecture I envision is that I'll have 1 Web server in which I will install the front end and the windows service. I'll also have a cloud files server for file storage. The windows service should somehow create a file and transfer it to the cloud file server (I assume this is possible?) My questions: Does the architecture look like I am going in the right direction? I know Amazon has been providing cloud services for a long time. If I want to do minimal changes to my application, should I go with Amazon, Rackspace, Azure or some other provider? I understand that I would not only pay for file storage and web server but also for the bandwidth of users downloading the file and the windows servic uploading the file to the cloud server. Can I assume these costs are negligible? Should I go with VPS + Cloud Files combination to begin with? Any other thoughts/suggestions?

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• 'Fixed' for loop - what is more efficient?

  - by pimvdb

  I'm creating a tic-tac-toe game, and one of the functions has to iterate through each of the 9 fields (tic-tac-toe is played on a 3x3 grid). I was wondering what is more efficient (which one is perhaps faster, or what is the preferred way of scripting in such situation) - using two for nested loops like this: for(var i=0; i<3; i++) { for(var j=0; j<3; j++) { checkField(i, j); } } or hard-coding it like this: checkField(0, 0); checkField(0, 1); checkField(0, 2); checkField(1, 0); checkField(1, 1); checkField(1, 2); checkField(2, 0); checkField(2, 1); checkField(2, 2); As there are only 9 combinations, it would be perhaps overkill to use two nested for loops, but then again this is clearer to read. The for loop, however, will increment variables and check whether i and j are smaller than 3 every time as well. In this example, the time saving at least might be negligible, but what is the preferred way of coding in this case? Thanks.

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• Connection Pool Strategy: Good, Bad or Ugly?

  - by Drew

  I'm in charge of developing and maintaining a group of Web Applications that are centered around similar data. The architecture I decided on at the time was that each application would have their own database and web-root application. Each application maintains a connection pool to its own database and a central database for shared data (logins, etc.) A co-worker has been positing that this strategy will not scale because having so many different connection pools will not be scalable and that we should refactor the database so that all of the different applications use a single central database and that any modifications that may be unique to a system will need to be reflected from that one database and then use a single pool powered by Tomcat. He has posited that there is a lot of "meta data" that goes back and forth across the network to maintain a connection pool. My understanding is that with proper tuning to use only as many connections as necessary across the different pools (low volume apps getting less connections, high volume apps getting more, etc.) that the number of pools doesn't matter compared to the number of connections or more formally that the difference in overhead required to maintain 3 pools of 10 connections is negligible compared to 1 pool of 30 connections. The reasoning behind initially breaking the systems into a one-app-one-database design was that there are likely going to be differences between the apps and that each system could make modifications on the schema as needed. Similarly, it eliminated the possibility of system data bleeding through to other apps. Unfortunately there is not strong leadership in the company to make a hard decision. Although my co-worker is backing up his worries only with vagueness, I want to make sure I understand the ramifications of multiple small databases/connections versus one large database/connection pool.

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• How to limit TCP writes to particular size and then block untlil the data is read

  - by ustulation

  {Qt 4.7.0 , VS 2010} I have a Server written in Qt and a 3rd party client executable. Qt based server uses QTcpServer and QTcpSocket facilities (non-blocking). Going through the articles on TCP I understand the following: the original implementation of TCP mentioned the negotiable window size to be a 16-bit value, thus maximum being 65535 bytes. But implementations often used the RFC window-scale-extension that allows the sliding window size to be scalable by bit-shifting to yield a maximum of 1 gigabyte. This is implementation defined. This could have resulted in majorly different window sizes on receiver and sender end as the server uses Qt facilities without hardcoding any window size limit. Client 1st asks for all information it can based on the previous messages from the server before handling the new (accumulating) incoming messages. So at some point Server receives a lot of messages each asking for data of several MB's. This the server processes and puts it into the sender buffer. Client however is unable to handle the messages at the same pace and it seems that client’s receiver buffer is far smaller (65535 bytes maybe) than sender’s transmit window size. The messages thus get accumulated at sender’s end until the sender’s buffer is full too after which the TCP writes on sender would block. This however does not happen as sender buffer is much larger. Hence this manifests as increase in memory consumption on the sender’s end. To prevent this from happening, I used Qt’s socket’s waitForBytesWritten() with timeout set to -1 for infinite waiting period. This as I see from the behaviour blocks the thread writing TCP data until the data has actually been sensed by the receiver’s window (which will happen when earlier messages have been processed by the client at application level). This has caused memory consumption at Server end to be almost negligible. is there a better alternative to this (in Qt) if i want to restrict the memory consumption at server end to say x MB's? Also please point out if any of my understandings is incorrect.

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• PHP, MySQL, Memcache / Ajax Scaling Problem

  - by Jeff Andersen

  I'm building a ajax tic tac toe game in PHP/MySQL. The premise of the game is to be able to share a url like mygame.com/123 with your friends and you play multiple simultaneous games. The way I have it set up is that a file (reload.php) is being called every 3 seconds while the user is viewing their game board space. This reload.php builds their game boards and the output (html) replaces their current game board (thus showing games in which it is their turn) Initially I built it entirely with PHP/MySQL and had zero caching. A friend gave me a suggestion to try doing all of the temporary/quick read information through memcache (storing moves, and ID matchups) and then building the game boards from this information. My issue is that, both solutions encounter a wall when there is roughly 30-40 active users with roughly 40-50 games running. It is running on a VPS from VPS.net with 2 nodes. (Dedicated CPU: 1.2GHz, RAM: 752MB) Each call to reload.php peforms 3 selects and 2 insert queries. The size of the data being pulled is negligible. The same actions happen on index.php to build the boards for the initial visit. Now that the backstory is done, my question is: Would there be a bottleneck in that each user is polling the same file every 3 seconds to rebuild their gameboards, and that all users are sitting on index.php from which the AJAX calls are made within the HTML. If so, is it possible to spread the users' calls out over a set of files designated to building the game boards (eg. reload1.php 2, 3 etc) and direct users to the appropriate file. Would this relieve the pressure? A long winded explanation; however, I didn't have anywhere else to ask. Thanks very much for any insight.

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• PHP – Slow String Manipulation

  - by Simon Roberts

  I have some very large data files and for business reasons I have to do extensive string manipulation (replacing characters and strings). This is unavoidable. The number of replacements runs into hundreds of thousands. It's taking longer than I would like. PHP is generally very quick but I'm doing so many of these string manipulations that it's slowing down and script execution is running into minutes. This is a pain because the script is run frequently. I've done some testing and found that str_replace is fastest, followed by strstr, followed by preg_replace. I've also tried individual str_replace statements as well as constructing arrays of patterns and replacements. I'm toying with the idea of isolating string manipulation operation and writing in a different language but I don't want to invest time in that option only to find that improvements are negligible. Plus, I only know Perl, PHP and COBOL so for any other language I would have to learn it first. I'm wondering how other people have approached similar problems? I have searched and I don't believe that this duplicates any existing questions.

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• Polling a web URL until event

  - by Jaxo

  I'm really sorry about the crappy title - if anybody has a better way of wording it, please edit it! I basically need to have a C# application run a function if the output of a URL is a certain value. For example, if the website says blue the background colour will be blue, red to make it red, etc. The problem is I don't want to spam my webserver with checks. The 4 bytes it downloads each time is negligible, but if I were to deploy this type of system on multiple computers, it would get slower and slower and the bandwidth would add up quickly. So my question is: How can my desktop application run a piece of code only when a web URL has a different output without checking each time? I can't use sockets, and any sort of LAN protocol won't end up working. My reasoning behind this potentially nefarious code is to be able to mute computers by updating a file on the website (as you may have seen in my previous question today, sorry!). I'd like it to be rather quick, and not have the refresh time minutes apart, a few seconds at the most would be ideal. How can I accomplish this? The website's code is easy, but getting the C# application to check when it changes is the part I'm stuck on. Nothing shows up on the website other than the command. Thanks!

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• [PHP] Does unsetting array values during iterating save on memory?

  - by saturn_rising

  Hello fellow code warriors, This is a simple programming question, coming from my lack of knowledge of how PHP handles array copying and unsetting during a foreach loop. It's like this, I have an array that comes to me from an outside source formatted in a way I want to change. A simple example would be: $myData = array('Key1' => array('value1', 'value2')); But what I want would be something like: $myData = array([0] => array('MyKey' => array('Key1' => array('value1', 'value2')))); So I take the first $myData and format it like the second $myData. I'm totally fine with my formatting algorithm. My question lies in finding a way to conserve memory since these arrays might get a little unwieldy. So, during my foreach loop I copy the current array value(s) into the new format, then I unset the value I'm working with from the original array. E.g.: $formattedData = array(); foreach ($myData as $key => $val) { // do some formatting here, copy to $reformattedVal $formattedData[] = $reformattedVal; unset($myData[$key]); } Is the call to unset() a good idea here? I.e., does it conserve memory since I have copied the data and no longer need the original value? Or, does PHP automatically garbage collect the data since I don't reference it in any subsequent code? The code runs fine, and so far my datasets have been too negligible in size to test for performance differences. I just don't know if I'm setting myself up for some weird bugs or CPU hits later on. Thanks for any insights. -sR

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• Quantifying the effects of partition mis-alignment

  - by Matt

  I'm experiencing some significant performance issues on an NFS server. I've been reading up a bit on partition alignment, and I think I have my partitions mis-aligned. I can't find anything that tells me how to actually quantify the effects of mis-aligned partitions. Some of the general information I found suggests the performance penalty can be quite high (upwards of 60%) and others say it's negligible. What I want to do is determine if partition alignment is a factor in this server's performance problems or not; and if so, to what degree? So I'll put my info out here, and hopefully the community can confirm if my partitions are indeed mis-aligned, and if so, help me put a number to what the performance cost is. Server is a Dell R510 with dual E5620 CPUs and 8 GB RAM. There are eight 15k 2.5” 600 GB drives (Seagate ST3600057SS) configured in hardware RAID-6 with a single hot spare. RAID controller is a Dell PERC H700 w/512MB cache (Linux sees this as a LSI MegaSAS 9260). OS is CentOS 5.6, home directory partition is ext3, with options “rw,data=journal,usrquota”. I have the HW RAID configured to present two virtual disks to the OS: /dev/sda for the OS (boot, root and swap partitions), and /dev/sdb for a big NFS share: [root@lnxutil1 ~]# parted -s /dev/sda unit s print Model: DELL PERC H700 (scsi) Disk /dev/sda: 134217599s Sector size (logical/physical): 512B/512B Partition Table: msdos Number Start End Size Type File system Flags 1 63s 465884s 465822s primary ext2 boot 2 465885s 134207009s 133741125s primary lvm [root@lnxutil1 ~]# parted -s /dev/sdb unit s print Model: DELL PERC H700 (scsi) Disk /dev/sdb: 5720768639s Sector size (logical/physical): 512B/512B Partition Table: gpt Number Start End Size File system Name Flags 1 34s 5720768606s 5720768573s lvm Edit 1 Using the cfq IO scheduler (default for CentOS 5.6): # cat /sys/block/sd{a,b}/queue/scheduler noop anticipatory deadline [cfq] noop anticipatory deadline [cfq] Chunk size is the same as strip size, right? If so, then 64kB: # /opt/MegaCli -LDInfo -Lall -aALL -NoLog Adapter #0 Number of Virtual Disks: 2 Virtual Disk: 0 (target id: 0) Name:os RAID Level: Primary-6, Secondary-0, RAID Level Qualifier-3 Size:65535MB State: Optimal Stripe Size: 64kB Number Of Drives:7 Span Depth:1 Default Cache Policy: WriteBack, ReadAdaptive, Direct, No Write Cache if Bad BBU Current Cache Policy: WriteThrough, ReadAdaptive, Direct, No Write Cache if Bad BBU Access Policy: Read/Write Disk Cache Policy: Disk's Default Number of Spans: 1 Span: 0 - Number of PDs: 7 ... physical disk info removed for brevity ... Virtual Disk: 1 (target id: 1) Name:share RAID Level: Primary-6, Secondary-0, RAID Level Qualifier-3 Size:2793344MB State: Optimal Stripe Size: 64kB Number Of Drives:7 Span Depth:1 Default Cache Policy: WriteBack, ReadAdaptive, Direct, No Write Cache if Bad BBU Current Cache Policy: WriteThrough, ReadAdaptive, Direct, No Write Cache if Bad BBU Access Policy: Read/Write Disk Cache Policy: Disk's Default Number of Spans: 1 Span: 0 - Number of PDs: 7 If it's not obvious, virtual disk 0 corresponds to /dev/sda, for the OS; virtual disk 1 is /dev/sdb (the exported home directory tree).

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• Chrome Problems on Windows 8

  - by Akshat Mittal

  There are a lot of problems with Chrome (24.0.1312.14 beta || But all this happened before update also) on Windows 8. Problems and explanations are listed below: Google Chrome re-draw time: When I switch tabs, the window retains the content of the previous tab and displays that even if I move my mouse, if only refreshes (re-draws) when there is a change on the webpage (like on hover) or I do a select all (or scroll). One thing to note is that the hover and select happens on the real page and not the retained image-like thing of the older webpage. Chrome is slow and laggy: Websites such as Facebook and Twitter (and more) have gone extremely laggy on Chrome (Win 8). When I was using Windows 7, I never experienced a lag or something. Also when using HTML-5 Websites, the transition (the -webkit-transition in CSS) goes extremely slow at times. Plugins Crash: Plugins like Flash Player, Shockwave Player, and more that are in-built into Chrome Crashes a lot, even when doing simple tasks like playing YouTube Videos, displaying ads or something. Chrome Crashes: Chrome has crashed over 100 times in the past month. Google Chrome just crashes randomly or I don't know the reason. Random Page crashes: Chrome results chrome://crash/(Copy-Paste this in address bar) on random pages even when the page is just loaded, I understand that this can happen on heavy HTML5 or JS websites but what about HTML only websites! Most of the things above happens on Super User also, Super User never had any problem when using Chrome on Windows 7. UPDATE 1: @magicandre1981 Commented for trying to disable Hardware Acceleration. I tried it, it somewhat solved the problem but din't fix it. I am still experiencing all the above issues but less frequently (maybe because Chrome Restarted Completely) UPDATE 2: @avirk asked me to try a Stable Version of Chrome and Firefox, I din't experience any lag in Firefox, a little (negligible) lag in Chrome 22 (Maybe because its a new copy of Chrome, I haven't used it much). Is anybody else experiencing such issues? Does anybody has a solution to any of these? Any Help is appreciated! Thank You!

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• Server to server replication and CPU and 32k\ corrupt doc

  - by nick wall

  Summary: if database contains a doc with 32K issue or corrupt, on server to server replication it causes marked increase in CPU in nserver.exe task, which effectively causes our server(s) to slow right down. We have a 5 server cluster (1 "hub" and 4 HTTP servers accessed via reverse proxy and SSO for load balancing and redundancy). All are physically located next to each other on network, they don't have dedicated network\ ports for cluster or replication. I realise IBM recommendation is dedicated port for cluster. Cluster queues are in tolerance and under heavy application user load, i.e. the maximum number of documents are being created, edited, deleted, the replication times between servers are negligible. Normally, all is well. Of the servers in the cluster, 1 is considered the "hub", and imitates a PUSH-PULL replication with it's cluster mates every 60mins, so that the replication load is taken by the hub and not cluster mates. The problem we have: every now and then we get a slow replication time from the hub to a cluster mate, sometimes up to 30mins. This maxes out the nserver.exe task on the "cluster mate" which causes it to respond to http requests very slowly. In the past, we have found that if a corrupt document is in the DB, it can have this affect, but on those occasions, the server log will show the corrupt doc noteId, we run fixup, all well. But we are not now seeing any record of corrupt docs. What we have noticed is if a doc with the 32K issue is present, the same thing can happen. Our only solution in that case is to run a : fixup mydb.nsf -V, which shows it is purging a 32K doc. Luckily we run a reverse proxy, so we can shut HTTP servers down without users noticing, but users do notice when a server has the problem! Has anyone else seen this occur? I have set up DDM event handlers for many of the replication events. I have set the replication time out limit to 5 mins (the max we usually see under full user load is 0.1min), to prevent it rep'ing for 30mins as before. This ia a temporary work around. Does anyone know of a DDM event to trap the 32K issue? we could at least then send alert. Regarding 32K issue: this prob needs another thread, but we are finding this relatively hard to find the source of the issue as the 32K event is fairly rare. Our app is fairly complex, interacting with various other external web services, with 2 way data transfer. But if we do encounter a 32K doc, we can't look at field properties, so we can't work out which field has issue which would give us a clue as to which process is culprit. As above, we run a fixup -V. Any help\ comments on this would be gratefully received.

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• Windows Phone 7 Review &ndash; Part 1: LG Quantum

  - by Nikita Polyakov

  As many of my fellow geeks, I ran out and got a retail windows Phone 7 on the first day. Just had to have it :) I’ve had the developer prototypes in my hands for previous 3 months on and off, so I finally wanted to have one I call my own. I’ve rushed the Launch   I’ve checked out both AT&T and T-Mobile offerings on day 1 and decided on a Samsung Focus. Great screen, super light and thin. If you don’t believe me that this phone can compete with the best of the non-Phone 7 offerings - get it in your hand to compare for yourself. I have to say that even though the on-screen keyboard on Windows Phone 7 is one of the best, the amount of text I write on my phone and my expectation of how long that takes for a short reply are very high. Also the phone being so slick and sexy did not feel solid or confident in my hand or pocket. As the dust settled   Arrives the LG Quantum – now on AT&T and worldwide. First impression of the softer plastic, the back battery cover is solid metal - the entire phone feels solid and indestructible! Phone fits just right in my hand, it’s almost too good. It does not feel like it will crack in your jeans. I feel safe holding it and don’t feel like if I or someone were to bump into me walking it’d fly out of my hand. I’ve dropped and had thrown the Focus a few times on accident as it’s weight is negligible. I won’t even dream of lying the first day adjusting to a 3.5’ LCD screen from the Samsung’s blistering bright and poppy AMOLED 4’ was hard. But the colors and sharpness are still very good. I find it almost easier on the eyes actually for day to day use.  I had a chance to lay the phone down in the line with the prototypes and final versions of other phones that had LCD screens – LG makes HTC looks like a budget LCD compared to a high end LCD in the home theatre department. I am consistently complemented by friends that have the HD7 or Surround on how much better my screen looks. The screen just looks like the most color correct phone out of the line up. Even next to Samsung it makes it look oversaturated, but can’t match the true blacks compensating with true white.   Day to Day Usability   What I also noticed that is a huge difference is how much I am not accidently hitting the soft keys at the bottom. I real pain on Focus since holding it in am average size hand already would accidently touch the controls at the bottom. QWERTY keyboard on this phone is great. It’s like the mission for LG is “make it solid!”. Keyboard has a very durable feel.   LG’s has a secret wild card though is the DLNA support. If you seen an ad for it, you should. Imagine this – playing a song from your phone straight to your network connected A/V receiver. Done. Pictures to TV. Done. Video. Done. DLNA works with components that advertise to as well as Windows 7, XBOX 360 and other consoles.  I will write an extensive review of that experience in near future. LG Exclusive apps – from panorama photo taker to voice to text translator and even look-n-type app that works like a backup inverse camera, there is quite a bit there that won’t be found on the other phones. I’ll review those in more detail in another segment. Conclusion So for a quick comparison: If you want a phone that is super thin, light and is core reference of a Windows Phone 7 – Samsung Focus it is. If you want a great phone with solid secure feel, real keyboard, media features - the hands down winner is LG Quantum.   You can pick up the LG Quantum at AT&T in US and worldwide as LG Optimus 7Q.   Final thought: I have not had SmartPhone that I felt was a reliable trusty primary communication device since Samsung BlackJack II, this time the LG got the crown.   [ Disclosure: Phone was provided to me free of charge. That has been the case for all of my phones for years, nothing new - I get them all. ]

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• Process Centric Banking: Loan Origination Solution

  - by Manish Palaparthy

  There is an old proverb that goes, "The difference between theory and practice is greater in practice than in theory". So, we keep doing numerous "Proof of Concepts" with our own products on various business cases to analyze them deeply, understand and explain to our customers. We then present our learnings as they happened. The awareness of each PoC should help readers increase the trustworthiness of the results coming out of these PoCs. I present one such PoC where we invested a lot of time&effort.  Process Centric Banking : Loan Origination Solution Loan Origination is a process by which a borrower applies for a new loan and the lender processes that application. Loan origination includes the series of steps taken by the bank from the point the customer shows interest in a loan product all the way to disbursal of funds. The Loan Origination process is relevant for many kind of lenders in Financial services: Banks, Credit Unions, NBFCs(Non Banking Financial Companies) and so on. For simplicity sake, I will use "Bank" as the lending institution in the rest of my article.  Loan Origination is one of the core processes for Banks as it is the process by which the it creates assets against which the Institution earns most of its profits from. A well tuned loan origination process can affect the Bank in many positive ways. Banks have always shown great interest in automating the loan origination process for the above reason. However, due the constant changes in customer environment, market dynamics, prevailing economic conditions, cost pressures & regulatory environment they run into lot of challenges. Let me categorize some of these challenges for you Customer Environment Multiple Channels: Customer can use any of the available channels (Internet Banking, Email, Fax, Branch, Phone Banking, ATM, Broker, Mobile, Snail Mail) to perform all or some of the activities related to her Visibility into the origination process: Expect immediate update on the status of loan processing & alert messages Reduced Turn Around Time: Expect loans to be processed with least turn around time Reduced loan processing fees: Partly due to market dynamics the customer expects the loan processing fee to be negligible Market Dynamics Competitive environment:  The competition keeps creating many variants of loan products to attract customers, the bank needs to create similar product variants with better offers to attract customers or keep existing ones Ability to migrate loans from one vendor to another: It has become really easy for retail customers to move from one bank to the other given the low fee of loan processing and highly attractive offers. How does the bank protect it's customer base while actively engaging with potential customers banking with competitor banks Flexibility to react to market developments: Market development greatly influence loan processing, underwriting, asset valuation, risk mitigation rules. Can the bank modify rules and policies, the idea is not just to react to market developments but to pro-actively manage new developments Economic conditions Constant change in various rates and their implications on the rates and rules applied when on-boarding a loan: How quickly can the bank apply changes to rates offered to customers when the central bank changes various rates Requirements of Audit by the central banker: Tough economic conditions have demanded much more stringent audit rules and tests. The banks needs to produce ready reports(historic & operational) for audit compliance Risk Mitigation: While risk mitigation has always been a key concern for the bank, this is the area where the bank's underwriters & risk analysts spend the maximum time when processing a loan application. In order to reduce TAT the bank cannot compromise on its risk mitigation strategies Cost pressures Reduce Cost of processing per application: To deliver a reduced loan processing fee to the customer, the bank needs to keep its cost per processing loan application low. Meet customer TAT expectations while reducing the queues and the systems being used to process the loan application: The loan application could potentially be spending a lot of time waiting in the queue for further processing. Different volumes & patterns of applications demand different queuing algorithms. The bank needs to have real-time visibility into these queues and have the flexibility to change queuing algorithms at runtime  Increase the use of electronic communication and reduce the branch channel usage: Lesser automation leads not only leads to Increased turn around time, it also impacts more costs to reach out to customers The objective of our PoC was to implement a Loan Origination Solution whose ownership lies with the bank and effectively meet the challenges listed above. We built a simple story board for the solution We then went about implementing our storyboard using Oracle BPM Suite, Webcenter Content : Imaging. The web UI has been built on ADF technolgies, while the integration with core-services has been implemented using the underlying SOA infrastructure. The BPM process model is quite exhaustive can meet all the challenges listed above to reasonable degree. A bank intending to implement an end-to-end Loan Origination Solution has multiple options at it's disposal. It can Develop a customer Loan Origination Application from scratch: Gives maximum opportunity to build what you want but inflexible to upgrade and maintain. Higher TCO in long term Buy a Packaged application & customize it: Customizing a generic loan application can be tedious and prove as difficult as above. Build it using many disparate & un-integrated tools: Initially seems easier than developing from scratch. But, without integrated tool sets this is not a viable approach either or A solution based on a Framework: Independent Services and Business Process Modeling provide decoupled architecture that is flexible. We built this framework end-to-end with processes the core process of loan origination & several sub-processes such as Analyse and define customer needs, customer credit verification, identity check processes, legal review process, New customer registration & risk assessment.

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• How do you programmatically set a Style on a View?

  - by Greg

  I would like to do something like this: <Button android:id="@+id/button" android:layout_width="wrap_content" android:layout_height="wrap_cotent" style="@style/SubmitButtonType" /> But in code The xml approach works fine provided that SubmitButtonType is defined. Now what I assume happens is that the appt parser runs through this xml, generates an AttributeSet. That AttributeSet when passed to context/theme#obtainStyledAttributes() will have the style ref mask anything that is not written inline in this tag. Great that's fine! Now how do we do this programmatically. Button, as well as other View types, has a constructor that has the form: <Widget>(Context context, AttributeSet set, int defStyle). So I thought this would work. Button button = new Button(context, null, R.style.SubmitButtonType); However, I am finding that defStyle is badly documented as it really should be written to be a resourceId to an attribute (from R.attrs) that will be passed to obtainStyledAttributes() as the attribute resource, and not the style resource. After looking at the code, all the view implementations seem to pass 0 as the styleRef. I don't see the harm in having it passed as both the attr and the style resource (more flexible and negligible overhead) However I might be approaching this all wrong. How do you do this in code then other than by setting each individual element of the style to the specific widget you want to style (only possible by looking a the code to see what param maps to which method or set of methods). The only way I have found to do this is: <declare-styleable> <attr name="totallyAdhoc_attribute_just_for_this_case" format="reference"> </declare-styleable> <style name="MyAlreadyExistantTheme" > ... ... <item name="totallyAdhoc_attribute_just_for_this_case">@style/SubmitButtonType</item> </style> And instead of passing R.style.SubmitButtonType as defStyle, I pass the new R.attr.totallyAdhoc_attribute_just_for_this_case. Button button = new Button(context, null, R.attr.totallyAdhoc_attribute_just_for_this_case); This works but sounds way too complicated.

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• Can MySQL reasonably perform queries on billions of rows?

  - by haxney

  I am planning on storing scans from a mass spectrometer in a MySQL database and would like to know whether storing and analyzing this amount of data is remotely feasible. I know performance varies wildly depending on the environment, but I'm looking for the rough order of magnitude: will queries take 5 days or 5 milliseconds? Input format Each input file contains a single run of the spectrometer; each run is comprised of a set of scans, and each scan has an ordered array of datapoints. There is a bit of metadata, but the majority of the file is comprised of arrays 32- or 64-bit ints or floats. Host system |----------------+-------------------------------| | OS | Windows 2008 64-bit | | MySQL version | 5.5.24 (x86_64) | | CPU | 2x Xeon E5420 (8 cores total) | | RAM | 8GB | | SSD filesystem | 500 GiB | | HDD RAID | 12 TiB | |----------------+-------------------------------| There are some other services running on the server using negligible processor time. File statistics |------------------+--------------| | number of files | ~16,000 | | total size | 1.3 TiB | | min size | 0 bytes | | max size | 12 GiB | | mean | 800 MiB | | median | 500 MiB | | total datapoints | ~200 billion | |------------------+--------------| The total number of datapoints is a very rough estimate. Proposed schema I'm planning on doing things "right" (i.e. normalizing the data like crazy) and so would have a runs table, a spectra table with a foreign key to runs, and a datapoints table with a foreign key to spectra. The 200 Billion datapoint question I am going to be analyzing across multiple spectra and possibly even multiple runs, resulting in queries which could touch millions of rows. Assuming I index everything properly (which is a topic for another question) and am not trying to shuffle hundreds of MiB across the network, is it remotely plausible for MySQL to handle this? UPDATE: additional info The scan data will be coming from files in the XML-based mzML format. The meat of this format is in the <binaryDataArrayList> elements where the data is stored. Each scan produces = 2 <binaryDataArray> elements which, taken together, form a 2-dimensional (or more) array of the form [[123.456, 234.567, ...], ...]. These data are write-once, so update performance and transaction safety are not concerns. My naïve plan for a database schema is: runs table | column name | type | |-------------+-------------| | id | PRIMARY KEY | | start_time | TIMESTAMP | | name | VARCHAR | |-------------+-------------| spectra table | column name | type | |----------------+-------------| | id | PRIMARY KEY | | name | VARCHAR | | index | INT | | spectrum_type | INT | | representation | INT | | run_id | FOREIGN KEY | |----------------+-------------| datapoints table | column name | type | |-------------+-------------| | id | PRIMARY KEY | | spectrum_id | FOREIGN KEY | | mz | DOUBLE | | num_counts | DOUBLE | | index | INT | |-------------+-------------| Is this reasonable?

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