Search Results

Search found 12988 results on 520 pages for 'performance'.

Page 149/520 | < Previous Page | 145 146 147 148 149 150 151 152 153 154 155 156  | Next Page >

  • How to efficiently save changes made in UI/main thread with Core Data?

    - by Jaanus
    So, there have been several posts here about importing and saving data from an external data source into Core Data. Apple documents a reasonable pattern for this: "import and save on background thread, merge saved objects to main thread." All fine and good. I have a related but different problem: the user is modifying data in the UI and main thread, and thus modifies state of some objects in the managed object context (MOC). I would like to save these changes from time to time. What is a good way to do that? Now, you could say that I could do the same: create a background thread with its own MOC and pass the changed objectID-s there. The catch-22 for me with this is that an object's ID changes when it is saved, and I cannot guarantee the order of things happening. I may end up passing a different objectID into the background thread for the same object, based on whether the object has been previously saved or not, and I don't know if Core Data can resolve this and see that different objectID-s are pointing to the same object and not create duplicates for me. (I could test this, but I'm lazywebbing with this question first.) One thought I had: I could always do MOC saves on a background thread, and queue them up with operationqueue, so that there is always only one save in progress. I would not create a new MOC, I would just use the same MOC as in main thread. Now, this is not thread safe and when someone modifies the MOC in main thread while it is being saved in background thread, the results will probably be catastrophic. But, minus the thread safety, you can see what kind of solution I'd wish for. To be clear, the problem I need to fix is that if I just do the save in main thread, it blocks the UI for an unacceptably long period of time, I want to move the save to background thread. So, questions: what about the reasoning of an object ID changing during saving, and Core Data being able to resolve them to the same object? Would this be the right way of addressing this problem? any other good ways of doing this?

    Read the article

  • database design to speed up hibernate querying of large dataset

    - by paddydub
    I currently have the below tables representing a bus network mapped in hibernate, accessed from a Spring MVC based bus route planner I'm trying to make my route planner application perform faster, I load all the above tables into Lists to perform the route planner logic. I would appreciate if anyone has any ideas of how to speed my performace Or any suggestions of another method to approach this problem of handling a large set of data Coordinate Connections Table (INT,INT,INT)( Containing 50,000 Coordinate Connections) ID, FROMCOORDID, TOCOORDID 1 1 2 2 1 17 3 1 63 4 1 64 5 1 65 6 1 95 Coordinate Table (INT,DECIMAL, DECIMAL) (Containing 4700 Coordinates) ID , LAT, LNG 0 59.352669 -7.264341 1 59.352669 -7.264341 2 59.350012 -7.260653 3 59.337585 -7.189798 4 59.339221 -7.193582 5 59.341408 -7.205888 Bus Stop Table (INT, INT, INT)(Containing 15000 Stops) StopID RouteID COORDINATEID 1000100001 100 17 1000100002 100 18 1000100003 100 19 1000100004 100 20 1000100005 100 21 1000100006 100 22 1000100007 100 23 This is how long it takes to load all the data from each table: stop.findAll = 148ms, stops.size: 15670 Hibernate: select coordinate0_.COORDINATEID as COORDINA1_2_, coordinate0_.LAT as LAT2_, coordinate0_.LNG as LNG2_ from COORDINATES coordinate0_ coord.findAll = 51ms , coordinates.size: 4704 Hibernate: select coordconne0_.COORDCONNECTIONID as COORDCON1_3_, coordconne0_.DISTANCE as DISTANCE3_, coordconne0_.FROMCOORDID as FROMCOOR3_3_, coordconne0_.TOCOORDID as TOCOORDID3_ from COORDCONNECTIONS coordconne0_ coordinateConnectionDao.findAll = 238ms ; coordConnectioninates.size:48132 Hibernate Annotations @Entity @Table(name = "STOPS") public class Stop implements Serializable { @Id @GeneratedValue @Column(name = "COORDINATEID") private Integer CoordinateID; @Column(name = "LAT") private double latitude; @Column(name = "LNG") private double longitude; } @Table(name = "COORDINATES") public class Coordinate { @Id @GeneratedValue @Column(name = "COORDINATEID") private Integer CoordinateID; @Column(name = "LAT") private double latitude; @Column(name = "LNG") private double longitude; } @Entity @Table(name = "COORDCONNECTIONS") public class CoordConnection { @Id @GeneratedValue @Column(name = "COORDCONNECTIONID") private Integer CoordinateID; /** * From Coordinate_id value */ @Column(name = "FROMCOORDID", nullable = false) private int fromCoordID; /** * To Coordinate_id value */ @Column(name = "TOCOORDID", nullable = false) private int toCoordID; //private Coordinate toCoordID; }

    Read the article

  • Eclipse JUnit Plugin Test very slow to re-execute Test Suite on Windows

    - by soundasleepful
    I'm having an odd, and stressing, problem with running a large JUnit Plugin test suite in Eclipse. When I try to re-run a JUnit plugin suite that has just been executed, Eclipse hangs for quite some time before it eventually wakes up and launches. It can take up to 5 minutes sometimes, and increases with the size of the suite. Visually, it appears as a GC cleanup, except that I have plenty of GC space available (400 MB freely allocated). The size of the workspace that is has to delete is well under 1 GB, and there are not too many files - definitely less than 20,000. While I was waiting for a new run to start, I decided to manually kill explorer.exe to see if it had any effect. Surprisingly, Eclipse instantly fell out of its freeze and ran as normal. This makes me think that Windows is somehow interfering with the deletion of these workspace files. They're not being put into the Recycle Bin though. The workspace is in C: which I think is out of the range of any workspace/domain stuff. Any ideas?

    Read the article

  • When should I open and close a website's cached WCF proxy?

    - by Brandon Linton
    I've browsed around the other articles on StackOverflow that relate to caching WCF proxies for reuse, and I've read this article explaining why I should explicitly open the proxy before calling anything on it. I'm still a little hazy on the best implementation details. My question is: when should I open and close proxies for service calls on a website, and what should their lifetime be (per call, per request, or per web app)? We aren't planning on leveraging cached security contexts at the moment (but it's not unforeseeable). Thanks!

    Read the article

  • High CPU Usage with WebGL?

    - by shoosh
    I'm checking out the nightly builds of Firefox and Chromium with support of WebGL with a few demos and tutorials and I can't help but wonder about the extremely high CPU load they cause. A simple demo like this one runs at a sustained 60% of my dual core. The large version of this one maxes out the CPU to 100% and has some visible frame loss. Chromium seems to be slightly better than firefox but not by much. I'm pretty sure that if these were desktop application the CPU load would be negligible. So what's going on here? what is it doing? Running the simple scripts of these can't be that demanding. Is it the extra layer of security or something?

    Read the article

  • Good way to make animations with cocos2d?

    - by Johnny Oin
    Hi there, I'm making a little iphone game, and I would get some clues. Let's imagine: Two background sprites moving pretty fast from right to left, and moving up and down with accelerometer. I guess I can't use animations here, cause the movement of the background is recalculated at each frame. So I use a schedule with an interval of 0.025s and move my sprites at each clock with a : sprite.position = ccp(x, y); So here is my problem: the result is laggy, with only these two sprites. I tried both declaring sprites in the header, and getting them with CCNodes and Tags. It's quite the same. So if someone can give me a hint on what is the best way to do that, that would be so nice. I wonder if the problem can't be the fact that sprites are moving very fast, but i'm not sure. Anyway, thanks for your time. J.

    Read the article

  • fast algorithm implementation to sort very small set

    - by aaa
    hello. This is the problem I ran into long time ago. I thought I may ask your for your ideas. assume I have very small set of numbers (integers), 4 or 8 elements, that need to be sorted, fast. what would be the best approach/algorithm? my approach was to use the max/min functions. I guess my question pertains more to implementation, rather than type of algorithm. At this point it becomes somewhat hardware dependent , so let us assume Intel 64-bit processor with SSE3 . Thanks

    Read the article

  • How to use SQLAlchemy to dump an SQL file from query expressions to bulk-insert into a DBMS?

    - by Mahmoud Abdelkader
    Please bear with me as I explain the problem, how I tried to solve it, and my question on how to improve it is at the end. I have a 100,000 line csv file from an offline batch job and I needed to insert it into the database as its proper models. Ordinarily, if this is a fairly straight-forward load, this can be trivially loaded by just munging the CSV file to fit a schema, but I had to do some external processing that requires querying and it's just much more convenient to use SQLAlchemy to generate the data I want. The data I want here is 3 models that represent 3 pre-exiting tables in the database and each subsequent model depends on the previous model. For example: Model C --> Foreign Key --> Model B --> Foreign Key --> Model A So, the models must be inserted in the order A, B, and C. I came up with a producer/consumer approach: - instantiate a multiprocessing.Process which contains a threadpool of 50 persister threads that have a threadlocal connection to a database - read a line from the file using the csv DictReader - enqueue the dictionary to the process, where each thread creates the appropriate models by querying the right values and each thread persists the models in the appropriate order This was faster than a non-threaded read/persist but it is way slower than bulk-loading a file into the database. The job finished persisting after about 45 minutes. For fun, I decided to write it in SQL statements, it took 5 minutes. Writing the SQL statements took me a couple of hours, though. So my question is, could I have used a faster method to insert rows using SQLAlchemy? As I understand it, SQLAlchemy is not designed for bulk insert operations, so this is less than ideal. This follows to my question, is there a way to generate the SQL statements using SQLAlchemy, throw them in a file, and then just use a bulk-load into the database? I know about str(model_object) but it does not show the interpolated values. I would appreciate any guidance for how to do this faster. Thanks!

    Read the article

  • Slow SelectSingleNode

    - by Simon
    I have a simple structured XML file like this: <ttest ID="ttest00001", NickName="map00001"/> <ttest ID="ttest00002", NickName="map00002"/> <ttest ID="ttest00003", NickName="map00003"/> <ttest ID="ttest00004", NickName="map00004"/> ..... This xml file can be around 2.5MB. In my source code I will have a loop to get nicknames In each loop, I have something like this: nickNameLoopNum = MyXmlDoc.SelectSingleNode("//ttest[@ID=' + testloopNum + "']").Attributes["NickName"].Value This single line will cost me 30 to 40 millisecond. I searched some old articles (dated back to 2002) saying, use some sort of compiled "xpath" can help the situation, but that was 5 years ago. I wonder is there a mordern practice to make it faster? (I'm using .NET 3.5)

    Read the article

  • Efficient alternative to merge() when building dataframe from json files with R?

    - by Bryan
    I have written the following code which works, but is painfully slow once I start executing it over thousands of records: require("RJSONIO") people_data <- data.frame(person_id=numeric(0)) json_data <- fromJSON(json_file) n_people <- length(json_data) for(lender in 1:n_people) { person_dataframe <- as.data.frame(t(unlist(json_data[[person]]))) people_data <- merge(people_data, person_dataframe, all=TRUE) } output_file <- paste("people_data",".csv") write.csv(people_data, file=output_file) I am attempting to build a unified data table from a series of json-formated files. The fromJSON() function reads in the data as lists of lists. Each element of the list is a person, which then contains a list of the attributes for that person. For example: [[1]] person_id name gender hair_color [[2]] person_id name location gender height [[...]] structure(list(person_id = "Amy123", name = "Amy", gender = "F", hair_color = "brown"), .Names = c("person_id", "name", "gender", "hair_color")) structure(list(person_id = "matt53", name = "Matt", location = structure(c(47231, "IN"), .Names = c("zip_code", "state")), gender = "M", height = 172), .Names = c("person_id", "name", "location", "gender", "height")) The end result of the code above is matrix where the columns are every person-attribute that appears in the structure above, and the rows are the relevant values for each person. As you can see though, some data is missing for some of the people, so I need to ensure those show up as NA and make sure things end up in the right columns. Further, location itself is a vector with two components: state and zip_code, meaning it needs to be flattened to location.state and location.zip_code before it can be merged with another person record; this is what I use unlist() for. I then keep the running master table in people_data. The above code works, but do you know of a more efficient way to accomplish what I'm trying to do? It appears the merge() is slowing this to a crawl... I have hundreds of files with hundreds of people in each file. Thanks! Bryan

    Read the article

  • Is there a fast way to jump to element using XMLReader?

    - by Derk
    I am using XMLReader to read a large XML file with about 1 million elements on the level I am reading from. However, I've calculated it will take over 10 seconds when I jump to -for instance- element 500.000 using XMLReader::next ([ string $localname ] ) or XMLReader::read ( void ) This is not very usable. Is there a faster way to do this?

    Read the article

  • WPF Dragging causes renderer to stop

    - by Cameron MacFarland
    I'm having a problem with my WPF app, where any sort of drag operation stops the UI from updating. The issue seems periodic, as in, the item drags, stops, drags again, stops, etc. in 2 second intervals. It's affecting all controls, including scroll bars. If checked this question as well as this one, and it doesn't seem to be caused by window transparencies. I'm running Win7 x64 with .NET 3.5sp1. Does anyone know what might be causing this, or a way of figuring out what might be causing this?

    Read the article

  • Javascript scope chain

    - by Geromey
    Hi, I am trying to optimize my program. I think I understand the basics of closure. I am confused about the scope chain though. I know that in general you want a low scope (to access variables quickly). Say I have the following object: var my_object = (function(){ //private variables var a_private = 0; return{ //public //public variables a_public : 1, //public methods some_public : function(){ debugger; alert(this.a_public); alert(a_private); }; }; })(); My understanding is that if I am in the some_public method I can access the private variables faster than the public ones. Is this correct? My confusion comes with the scope level of this. When the code is stopped at debugger, firebug shows the public variable inside the this keyword. The this word is not inside a scope level. How fast is accessing this? Right now I am storing any this.properties as another local variable to avoid accessing it multiple times. Thanks very much!

    Read the article

  • Lucene search taking TOOO long.

    - by Josh Handel
    I;m using Lucene.net (2.9.2.2) on a (currently) 70Gig index.. I can do a fairly complicated search and get all the document IDs back in 1 ~ 2 seconds.. But to actually load up all the hits (about 700 thousand in my test queries) takes 5+ minutes. We aren't using lucene for UI, this is a datastore between processes where we have hundreds of millions of pre-cached data elements, and the part I am working on exports a few specific fields from each found document. (ergo, pagination doesn't make since as this is an export between processes). My question is what is the best way to get all of the documents in a search result? currently I am using a custom collector that does a get on the document (with a MapFieldSelector) as its collecting.. I've also tried iterating through the list after the collector has finished.. but that was even worse. I'm open to ideas :-). Thanks in advance.

    Read the article

  • Perf4J Logging Config Help

    - by manyxcxi
    I currently have a long running process that I am trying to analyze with Perf4J. I currently have it writing results in CSV format to its own log file using the AsyncCoalescingStatisticsAppender and a StatisticsCsvLayout on the file appender. My question is; when I try and use the --graph option from the command line (using the perf4j jar) it isn't populating the data points- it isn't populating anything. Are my appenders set incorrectly? The log file contains hundreds (sometimes thousands) of data points of about 10 different tag names. <appender name="perfAppender" class="org.apache.log4j.FileAppender"> <param name="File" value="perfStats.log"/> <layout class="org.perf4j.log4j.StatisticsCsvLayout"> </layout> </appender> <appender name="CoalescingStatistics" class="org.perf4j.log4j.AsyncCoalescingStatisticsAppender"> <!-- The TimeSlice option is used to determine the time window for which all received StopWatch logs are aggregated to create a single GroupedTimingStatistics log. Here we set it to 10 seconds, overriding the default of 30000 ms --> <param name="TimeSlice" value="10000"/> <appender-ref ref="ConsoleAppender"/> <appender-ref ref="CompositeRollingFileAppender"/> <appender-ref ref="perfAppender"/> </appender>

    Read the article

  • 2 approaches for tracking online users with Redis. Which one is faster?

    - by Stanislav
    Recently I found an nice blog post presenting 2 approaches for tracking online users of a web site with the help of Redis. 1) Smart-keys and setting their expiration http://techno-weenie.net/2010/2/3/where-s-waldo-track-user-locations-with-node-js-and-redis 2) Set-s and intersects http://www.lukemelia.com/blog/archives/2010/01/17/redis-in-practice-whos-online/ Can you judge which one should be faster and why?

    Read the article

  • Why is numpy's einsum faster than numpy's built in functions?

    - by Ophion
    Lets start with three arrays of dtype=np.double. Timings are performed on a intel CPU using numpy 1.7.1 compiled with icc and linked to intel's mkl. A AMD cpu with numpy 1.6.1 compiled with gcc without mkl was also used to verify the timings. Please note the timings scale nearly linearly with system size and are not due to the small overhead incurred in the numpy functions if statements these difference will show up in microseconds not milliseconds: arr_1D=np.arange(500,dtype=np.double) large_arr_1D=np.arange(100000,dtype=np.double) arr_2D=np.arange(500**2,dtype=np.double).reshape(500,500) arr_3D=np.arange(500**3,dtype=np.double).reshape(500,500,500) First lets look at the np.sum function: np.all(np.sum(arr_3D)==np.einsum('ijk->',arr_3D)) True %timeit np.sum(arr_3D) 10 loops, best of 3: 142 ms per loop %timeit np.einsum('ijk->', arr_3D) 10 loops, best of 3: 70.2 ms per loop Powers: np.allclose(arr_3D*arr_3D*arr_3D,np.einsum('ijk,ijk,ijk->ijk',arr_3D,arr_3D,arr_3D)) True %timeit arr_3D*arr_3D*arr_3D 1 loops, best of 3: 1.32 s per loop %timeit np.einsum('ijk,ijk,ijk->ijk', arr_3D, arr_3D, arr_3D) 1 loops, best of 3: 694 ms per loop Outer product: np.all(np.outer(arr_1D,arr_1D)==np.einsum('i,k->ik',arr_1D,arr_1D)) True %timeit np.outer(arr_1D, arr_1D) 1000 loops, best of 3: 411 us per loop %timeit np.einsum('i,k->ik', arr_1D, arr_1D) 1000 loops, best of 3: 245 us per loop All of the above are twice as fast with np.einsum. These should be apples to apples comparisons as everything is specifically of dtype=np.double. I would expect the speed up in an operation like this: np.allclose(np.sum(arr_2D*arr_3D),np.einsum('ij,oij->',arr_2D,arr_3D)) True %timeit np.sum(arr_2D*arr_3D) 1 loops, best of 3: 813 ms per loop %timeit np.einsum('ij,oij->', arr_2D, arr_3D) 10 loops, best of 3: 85.1 ms per loop Einsum seems to be at least twice as fast for np.inner, np.outer, np.kron, and np.sum regardless of axes selection. The primary exception being np.dot as it calls DGEMM from a BLAS library. So why is np.einsum faster that other numpy functions that are equivalent? The DGEMM case for completeness: np.allclose(np.dot(arr_2D,arr_2D),np.einsum('ij,jk',arr_2D,arr_2D)) True %timeit np.einsum('ij,jk',arr_2D,arr_2D) 10 loops, best of 3: 56.1 ms per loop %timeit np.dot(arr_2D,arr_2D) 100 loops, best of 3: 5.17 ms per loop The leading theory is from @sebergs comment that np.einsum can make use of SSE2, but numpy's ufuncs will not until numpy 1.8 (see the change log). I believe this is the correct answer, but have not been able to confirm it. Some limited proof can be found by changing the dtype of input array and observing speed difference and the fact that not everyone observes the same trends in timings.

    Read the article

  • Image 8-connectivity without excessive branching?

    - by shoosh
    I'm writing a low level image processing algorithm which needs to do alot of 8-connectivity checks for pixels. For every pixel I often need to check the pixels above it, below it and on its sides and diagonals. On the edges of the image there are special cases where there are only 5 or 3 neighbors instead of 8 neighbors for a pixels. The naive way to do it is for every access to check if the coordinates are in the right range and if not, return some default value. I'm looking for a way to avoid all these checks since they introduce a large overhead to the algorithm. Are there any tricks to avoid it altogether?

    Read the article

  • Loading animation Memory leak

    - by Ayaz Alavi
    Hi, I have written network class that is managing all network calls for my application. There are two methods showLoadingAnimationView and hideLoadingAnimationView that will show UIActivityIndicatorView in a view over my current viewcontroller with fade background. I am getting memory leaks somewhere on these two methods. Here is the code -(void)showLoadingAnimationView { textmeAppDelegate *textme = (textmeAppDelegate *)[[UIApplication sharedApplication] delegate]; [[UIApplication sharedApplication] setNetworkActivityIndicatorVisible:YES]; if(wrapperLoading != nil) { [wrapperLoading release]; } wrapperLoading = [[UIView alloc] initWithFrame:CGRectMake(0.0, 0.0, 320.0, 480.0)]; wrapperLoading.backgroundColor = [UIColor clearColor]; wrapperLoading.alpha = 0.8; UIView *_loadingBG = [[UIView alloc] initWithFrame:CGRectMake(0.0, 0.0, 320.0, 480.0)]; _loadingBG.backgroundColor = [UIColor blackColor]; _loadingBG.alpha = 0.4; circlingWheel = [[UIActivityIndicatorView alloc] initWithActivityIndicatorStyle:UIActivityIndicatorViewStyleWhiteLarge]; CGRect wheelFrame = circlingWheel.frame; circlingWheel.frame = CGRectMake(((320.0 - wheelFrame.size.width) / 2.0), ((480.0 - wheelFrame.size.height) / 2.0), wheelFrame.size.width, wheelFrame.size.height); [wrapperLoading addSubview:_loadingBG]; [wrapperLoading addSubview:circlingWheel]; [circlingWheel startAnimating]; [textme.window addSubview:wrapperLoading]; [_loadingBG release]; [circlingWheel release]; } -(void)hideLoadingAnimationView { [[UIApplication sharedApplication] setNetworkActivityIndicatorVisible:NO]; wrapperLoading.alpha = 0.0; [self.wrapperLoading removeFromSuperview]; //[NSTimer scheduledTimerWithTimeInterval:0.8 target:wrapperLoading selector:@selector(removeFromSuperview) userInfo:nil repeats:NO]; } Here is how I am calling these two methods [NSThread detachNewThreadSelector:@selector(showLoadingAnimationView) toTarget:self withObject:nil]; and then somewhere later in the code i am using following function call to hide animation. [self hideLoadingAnimationView]; I am getting memory leaks when I call showLoadingAnimationView function. Anything wrong in the code or is there any better technique to show loading animation when we do network calls?

    Read the article

  • yuicompressor error, not sure what is wrong?

    - by mrblah
    Hi, Very confused here, trying out the yuicompressor on a simple javascript file. My js file looks like: function splitText(text) { return text.split('-')[1]; } The error is: [INFO] Using charset Cp1252 [Error] 1:20:illegal character [Error] 1:20:syntax error [Error] 1:40:illegal character [Error] 1:49:missing ; before statement [Error] 1:50:illegal character .. .. [Error] 7:3:missing | in compound statement [error] 1:0:compilation produced 38 syntax errors ... Can someone please explain to me what is wrong?

    Read the article

  • has anyone used simile timeline with large amounts of data

    - by oo
    i am using this simile timeline with large amounts of data and i keep getting firefox popping up saying "a script has appeared to no longer be running, do you want to kill it"? is there a limit to the amount of json you can send back to it. I have about 1000 different timeline points with dates, descriptions, etc.

    Read the article

  • High CPU usage when running several "java -version" in parallel

    - by Prateesh
    This is just out of curiosity to understand i have a small shell script for ((i = 0; i < 50; i++)) do java -version & done when i run this my CPU usage report by sar is as below 07:51:25 PM CPU %user %nice %system %iowait %steal %idle 07:51:30 PM all 6.98 0.00 1.75 1.00 0.00 90.27 07:51:31 PM all 43.00 0.00 12.00 0.00 0.00 45.00 07:51:32 PM all 86.28 0.00 13.72 0.00 0.00 0.00 07:51:33 PM all 5.25 0.00 1.75 0.50 0.00 92.50 As you can see, on the third line the CPU is at 100% My java version is 1.5.0_22-b03.

    Read the article

  • Tuning MySQL to take advantage of a 4GB VPS

    - by alistair.mp
    Hello, We're running a large site at the moment which has a dedicated VPS for it's database server which is running MySQL and nothing else. At the moment all four CPU cores are running at close to 100% all of the time but the memory usage sticks at around 268MB out of an available 4096MB. I'm wondering what we can do to better utilise the memory and reduce the CPU load by tweaking MySQL's settings? Here is what we currently have in my.cnf: http://pastie.org/private/hxeji9o8n3u9up9mvtinbq Thanks

    Read the article

< Previous Page | 145 146 147 148 149 150 151 152 153 154 155 156  | Next Page >