Search Results

Search found 3758 results on 151 pages for 'efficient'.

Page 18/151 | < Previous Page | 14 15 16 17 18 19 20 21 22 23 24 25  | Next Page >

  • Efficient way to combine results of two database queries.

    - by ensnare
    I have two tables on different servers, and I'd like some help finding an efficient way to combine and match the datasets. Here's an example: From server 1, which holds our stories, I perform a query like: query = """SELECT author_id, title, text FROM stories ORDER BY timestamp_created DESC LIMIT 10 """ results = DB.getAll(query) for i in range(len(results)): #Build a string of author_ids, e.g. '1314,4134,2624,2342' But, I'd like to fetch some info about each author_id from server 2: query = """SELECT id, avatar_url FROM members WHERE id IN (%s) """ values = (uid_list) results = DB.getAll(query, values) Now I need some way to combine these two queries so I have a dict that has the story as well as avatar_url and member_id. If this data were on one server, it would be a simple join that would look like: SELECT * FROM members, stories WHERE members.id = stories.author_id But since we store the data on multiple servers, this is not possible. What is the most efficient way to do this? Thanks.

    Read the article

  • which sql query is more efficient: select count(*) or select ... where key>value?

    - by davka
    I need to periodically update a local cache with new additions to some DB table. The table rows contain an auto-increment sequential number (SN) field. The cache keeps this number too, so basically I just need to fetch all rows with SN larger than the highest I already have. SELECT * FROM table where SN > <max_cached_SN> However, the majority of the attempts will bring no data (I just need to make sure that I have an absolutely up-to-date local copy). So I wander if this will be more efficient: count = SELECT count(*) from table; if (count > <cache_size>) // fetch new rows as above I suppose that selecting by an indexed numeric field is quite efficient, so I wander whether using count has benefit. On the other hand, this test/update will be done quite frequently and by many clients, so there is a motivation to optimize it.

    Read the article

  • What's the most efficient way to reclaim disk space after deleting lots of data from a database on Sybase ASE 15?

    - by Ernie Longmire
    As I understand it, based on some research but zero real-world experience with Sybase ASE, the only way to reclaim disk space once it's been allocated to a database is to export that database, create a new DB with the same schema, and reload all the exported data to the new database. Is this correct, or is there some other method? Then: assuming the above is correct and a full export-recreate-reload is required, what's the most efficient way to do that? Are there tools that will automate all or part of that process? I'm being told we would have to write separate bcp export and import commands for each and every object in the database, which if true sounds easily scriptable by someone who knows Sybase ASE well enough. (I don't.) This seems to me like a really basic housekeeping task, and it feels like I'm missing something obvious.

    Read the article

  • Why are 32-bit application pools more efficient in IIS? [closed]

    - by mhenry1384
    I've been running load tests with two different ASP.NET web applications in IIS. The tests are run with 5,10,25, and 250 user agents. Tested on a box with 8 GB RAM, Windows 7 Ultimate x64. The same box running both IIS and the load test project. I did many runs, and the data is very consistent. For every load, I see a lower "Avg. Page Time (sec)" and a lower "Avg. Response Time (sec)" if I have "Enable 32-bit Applications" set to True in the Application Pools. The difference gets more pronounced the higher the load. At very high loads, the web applications start to throw errors (503) if the application pools are 64-bit, but they can can keep up if set to 32-bit. Why are 32-bit app pools so much more efficient? Why isn't the default for application pools 32-bit?

    Read the article

  • An efficient setup of several VPSs on one box?

    - by Abs
    Hello all, I hope its ok to ask this question on serverfault, its not an actual fault but more of an implementation advice request. I would like to have a dedicated server that I can deploy my own VPSs on. These VPS will be various windows, Mac and Linux operating systems. I was thinking of buying a large Linux based dedicated server and then running VMWare Server or Virtualbox and adding my own images on there for each OS but I am thinking this isn't going to be cost effective and easy to maintain. I am hoping someone can help me with the perfect setup that is both cost effective and efficient so that I can have 6 VPS at my disposal that I can easily control. Thanks all for any help.

    Read the article

  • How do I get transparent, efficient, file system snapshotting or versioning on ext3/4?

    - by shovas
    I've long thought about versioning file systems. This is a killer feature and I've looked at Wayback, ext3cow, zfs, fuse solutions, or just cvs/svn/git overlays. I consider ext3cow the model for my requirements. Transparent, efficient, but I can do without the extra ls abc@timestamp feature. As long as I somehow get automated, transparent versioning of my files. It could be instantaneous or it could be based on snapshots on intervals of 10s, 30s, 1m, 5m, 15m, etc. Just something that will efficiently deal with thousands of files in a given directory all of various sizes, most small, but some upwards of 100m to 1gb. ZFS isn't really an option as I'm on linux (and would prefer not to use it through fuse as I already have an ext3 setup I want to version, not something new). What solutions are out there?

    Read the article

  • On a dual-GPU laptop, is using the discrete GPU ever more power efficient?

    - by Mahmoud Al-Qudsi
    Given a laptop with a dual integrated/discrete GPU configuration, is it ever more power efficient to use the discrete GPU instead of the integrated? Obviously when writing an email or working on a spreadsheet, the integrated GPU will always use less power. But let's say you're doing something graphics-medium but not graphics-intensive/heavy - is there a point where it actually makes sense to fire up the discrete GPU, not for performance but for power-saving reasons? Off the top of my head, I can think of a scenario where the external GPU supports hardware decoding of a particular video codec - I'd imagine there is a "price point" where using the GPU saves more energy than decoding that fully in software would. But I think most GPUs, integrated or discrete, pretty much decode just the plain-Jane h264. But maybe there is something more complicated, perhaps if you're doing something like desktop/windowing animations or a flash animation on a website (not an embedded flash video) - maybe the discrete GPU will use enough less power to make up for switching to it? I guess this question can be summed up as to whether or not you can say beyond doubt that if you don't care for performance on a laptop with two GPUs, always use the integrated GPU for maximum battery life.

    Read the article

  • Most efficient way to check for DBNull and then assign to a variable?

    - by ilitirit
    This question comes up occasionally but I haven't seen a satisfactory answer. A typical pattern is (row is a DataRow): if (row["value"] != DBNull.Value) { someObject.Member = row["value"]; } My first question is which is more efficient (I've flipped the condition): row["value"] == DBNull.Value; // Or row["value"] is DBNull; // Or row["value"].GetType() == typeof(DBNull) // Or... any suggestions? This indicates that .GetType() should be faster, but maybe the compiler knows a few tricks I don't? Second question, is it worth caching the value of row["value"] or does the compiler optimize the indexer away anyway? eg. object valueHolder; if (DBNull.Value == (valueHolder = row["value"])) {} Disclaimers: row["value"] exists. I don't know the column index of the column (hence the column name lookup) I'm asking specifically about checking for DBNull and then assignment (not about premature optimization etc). Edit: I benchmarked a few scenarios (time in seconds, 10000000 trials): row["value"] == DBNull.Value: 00:00:01.5478995 row["value"] is DBNull: 00:00:01.6306578 row["value"].GetType() == typeof(DBNull): 00:00:02.0138757 Object.ReferenceEquals has the same performance as "==" The most interesting result? If you mismatch the name of the column by case (eg. "Value" instead of "value", it takes roughly ten times longer (for a string): row["Value"] == DBNull.Value: 00:00:12.2792374 The moral of the story seems to be that if you can't look up a column by it's index, then ensure that the column name you feed to the indexer matches the DataColumn's name exactly. Caching the value also appears to be nearly twice as fast: No Caching: 00:00:03.0996622 With Caching: 00:00:01.5659920 So the most efficient method seems to be: object temp; string variable; if (DBNull.Value != (temp = row["value"]) { variable = temp.ToString(); } This was a good learning experience.

    Read the article

  • What is the most efficient way to display decoded video frames in Qt?

    - by Jason
    What is the fastest way to display images to a Qt widget? I have decoded the video using libavformat and libavcodec, so I already have raw RGB or YCbCr 4:2:0 frames. I am currently using a QGraphicsView with a QGraphicsScene object containing a QGraphicsPixmapItem. I am currently getting the frame data into a QPixmap by using the QImage constructor from a memory buffer and converting it to QPixmap using QPixmap::fromImage(). I like the results of this and it seems relatively fast, but I can't help but think that there must be a more efficient way. I've also heard that the QImage to QPixmap conversion is expensive. I have implemented a solution that uses an SDL overlay on a widget, but I'd like to stay with just Qt since I am able to easily capture clicks and other user interaction with the video display using the QGraphicsView. I am doing any required video scaling or colorspace conversions with libswscale so I would just like to know if anyone has a more efficient way to display the image data after all processing has been performed. Thanks.

    Read the article

  • Is there a more efficient way to run enum values through a switch-case statement in C# than this?

    - by C Patton
    I was wondering if there was a more efficient (efficient as in simpler/cleaner code) way of making a case statement like the one below... I have a dictionary. Its key type is an Enum and its value type is a bool. If the boolean is true, I want to change the color of a label on a form. The variable names were changed for the example. Dictionary<String, CustomType> testDict = new Dictionary<String, CustomType>(); //populate testDict here... Dictionary<MyEnum, bool> enumInfo = testDict[someString].GetEnumInfo(); //GetEnumInfo is a function that iterates through a Dictionary<String, CustomType> //and returns a Dictionary<MyEnum, bool> foreach (KeyValuePair<MyEnum, bool> kvp in enumInfo) { switch (kvp.Key) { case MyEnum.Enum1: if (someDictionary[kvp.Key] == true) { Label1.ForeColor = Color.LimeGreen; } else { Label1.ForeColor = Color.Red; } break; case MyEnum.Enum2: if (someDictionary[kvp.Key] == true) { Label2.ForeColor = Color.LimeGreen; } else { Label2.ForeColor = Color.Red; } break; } } So far, MyEnum has 8 different values.. which means I have 8 different case statements.. I know there must be an easier way to do this, I just can't conceptualize it in my head. If anyone could help, I'd greatly appreciate it. I love C# and I learn new things every day.. I absorb it like a sponge :) -CP

    Read the article

  • Is there a more memory efficient way to search through a Core Data database?

    - by Kristian K
    I need to see if an object that I have obtained from a CSV file with a unique identifier exists in my Core Data Database, and this is the code I deemed suitable for this task: NSFetchRequest *fetchRequest = [[NSFetchRequest alloc] init]; NSEntityDescription *entity; entity = [NSEntityDescription entityForName:@"ICD9" inManagedObjectContext:passedContext]; [fetchRequest setEntity:entity]; NSPredicate *pred = [NSPredicate predicateWithFormat:@"uniqueID like %@", uniqueIdentifier]; [fetchRequest setPredicate:pred]; NSError *err; NSArray* icd9s = [passedContext executeFetchRequest:fetchRequest error:&err]; [fetchRequest release]; if ([icd9s count] > 0) { for (int i = 0; i < [icd9s count]; i++) { NSAutoreleasePool *pool = [[NSAutoreleasePool alloc]init]; NSString *name = [[icd9s objectAtIndex:i] valueForKey:@"uniqueID"]; if ([name caseInsensitiveCompare:uniqueIdentifier] == NSOrderedSame && name != nil) { [pool release]; return [icd9s objectAtIndex:i]; } [pool release]; } } return nil; After more thorough testing it appears that this code is responsible for a huge amount of leaking in the app I'm writing (it crashes on a 3GS before making it 20 percent through the 1459 items). I feel like this isn't the most efficient way to do this, any suggestions for a more memory efficient way? Thanks in advance!

    Read the article

  • IList<T> vs IEnumerable<T>. What is more efficient IList<T> or IEnumerable<T>

    - by bigb
    What is more efficient way to make methods return IList<T> or IEnumerable<T>? IEnumerable<T> it is immutable collection but IList<T> mutable and contain a lot of useful methods and properties. To cast IList<T> to IEnumerable<T> it is just reference copy: IList<T> l = new List<T>(); IEnumerable<T> e = l; To cast IEnumerable<T> to List<T> we need to iterate each element or to call ToList() method: IEnumerable<T>.ToList(); or may pass IEnumerable<T> to List<T> constructor which doing the same iteration somewhere within its constructor. List<T> l = new List<T>(e); Which cases you think is more efficient? Which you prefer more in your practice?

    Read the article

  • Good C++ array class for dealing with large arrays of data in a fast and memory efficient way?

    - by Shane MacLaughlin
    Following on from a previous question relating to heap usage restrictions, I'm looking for a good standard C++ class for dealing with big arrays of data in a way that is both memory efficient and speed efficient. I had been allocating the array using a single malloc/HealAlloc but after multiple trys using various calls, keep falling foul of heap fragmentation. So the conclusion I've come to, other than porting to 64 bit, is to use a mechanism that allows me to have a large array spanning multiple smaller memory fragments. I don't want an alloc per element as that is very memory inefficient, so the plan is to write a class that overrides the [] operator and select an appropriate element based on the index. Is there already a decent class out there to do this, or am I better off rolling my own? From my understanding, and some googling, a 32 bit Windows process should theoretically be able address up to 2GB. Now assuming I've 2GB installed, and various other processes and services are hogging about 400MB, how much usable memory do you think my program can reasonably expect to get from the heap? I'm currently using various flavours of Visual C++.

    Read the article

  • More efficient way of updating UI from Service than intents?

    - by Donal Rafferty
    I currently have a Service in Android that is a sample VOIP client so it listens out for SIP messages and if it recieves one it starts up an Activity screen with UI components. Then the following SIP messages determine what the Activity is to display on the screen. For example if its an incoming call it will display Answer or Reject or an outgoing call it will show a dialling screen. At the minute I use Intents to let the Activity know what state it should display. An example is as follows: Intent i = new Intent(); i.setAction(SIPEngine.SIP_TRYING_INTENT); i.putExtra("com.net.INCOMING", true); sendBroadcast(i); Intent x = new Intent(); x.setAction(CallManager.SIP_INCOMING_CALL_INTENT); sendBroadcast(x); Log.d("INTENT SENT", "INTENT SENT INCOMING CALL AFTER PROCESSINVITE"); So the activity will have a broadcast reciever registered for these intents and will switch its state according to the last intent it received. Sample code as follows: SipCallListener = new BroadcastReceiver(){ @Override public void onReceive(Context context, Intent intent) { String action = intent.getAction(); if(SIPEngine.SIP_RINGING_INTENT.equals(action)){ Log.d("cda ", "Got RINGING action SIPENGINE"); ringingSetup(); } if(CallManager.SIP_INCOMING_CALL_INTENT.equals(action)){ Log.d("cda ", "Got PHONE RINGING action"); incomingCallSetup(); } } }; IntentFilter filter = new IntentFilter(CallManager.SIP_INCOMING_CALL_INTENT); filter.addAction(CallManager.SIP_RINGING_CALL_INTENT); registerReceiver(SipCallListener, filter); This works however it seems like it is not very efficient, the Intents will get broadcast system wide and Intents having to fire for different states seems like it could become inefficient the more I have to include as well as adding complexity. So I was wondering if there is a different more efficient and cleaner way to do this? Is there a way to keep Intents broadcasting only inside an application? Would callbacks be a better idea? If so why and in what way should they be implemented?

    Read the article

  • Efficient method of getting all plist arrays into one array?

    - by cannyboy
    If I have a plist which is structured like this: Root Array Item 0 Dictionary City String New York People Array Item 0 String Steve Item 1 String Paul Item 2 String Fabio Item 3 String David Item 4 String Penny Item 1 Dictionary City String London People Array Item 0 String Linda Item 1 String Rachel Item 2 String Jessica Item 3 String Lou Item 2 Dictionary City String Barcelona People Array Item 0 String Edward Item 1 String Juan Item 2 String Maria Then what is the most efficient way of getting all the names of the people into one big NSArray?

    Read the article

< Previous Page | 14 15 16 17 18 19 20 21 22 23 24 25  | Next Page >