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  • 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!

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  • 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?

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  • 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++.

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  • How to Achieve Real-Time Data Protection and Availabilty....For Real

    - by JoeMeeks
    There is a class of business and mission critical applications where downtime or data loss have substantial negative impact on revenue, customer service, reputation, cost, etc. Because the Oracle Database is used extensively to provide reliable performance and availability for this class of application, it also provides an integrated set of capabilities for real-time data protection and availability. Active Data Guard, depicted in the figure below, is the cornerstone for accomplishing these objectives because it provides the absolute best real-time data protection and availability for the Oracle Database. This is a bold statement, but it is supported by the facts. It isn’t so much that alternative solutions are bad, it’s just that their architectures prevent them from achieving the same levels of data protection, availability, simplicity, and asset utilization provided by Active Data Guard. Let’s explore further. Backups are the most popular method used to protect data and are an essential best practice for every database. Not surprisingly, Oracle Recovery Manager (RMAN) is one of the most commonly used features of the Oracle Database. But comparing Active Data Guard to backups is like comparing apples to motorcycles. Active Data Guard uses a hot (open read-only), synchronized copy of the production database to provide real-time data protection and HA. In contrast, a restore from backup takes time and often has many moving parts - people, processes, software and systems – that can create a level of uncertainty during an outage that critical applications can’t afford. This is why backups play a secondary role for your most critical databases by complementing real-time solutions that can provide both data protection and availability. Before Data Guard, enterprises used storage remote-mirroring for real-time data protection and availability. Remote-mirroring is a sophisticated storage technology promoted as a generic infrastructure solution that makes a simple promise – whatever is written to a primary volume will also be written to the mirrored volume at a remote site. Keeping this promise is also what causes data loss and downtime when the data written to primary volumes is corrupt – the same corruption is faithfully mirrored to the remote volume making both copies unusable. This happens because remote-mirroring is a generic process. It has no  intrinsic knowledge of Oracle data structures to enable advanced protection, nor can it perform independent Oracle validation BEFORE changes are applied to the remote copy. There is also nothing to prevent human error (e.g. a storage admin accidentally deleting critical files) from also impacting the remote mirrored copy. Remote-mirroring tricks users by creating a false impression that there are two separate copies of the Oracle Database. In truth; while remote-mirroring maintains two copies of the data on different volumes, both are part of a single closely coupled system. Not only will remote-mirroring propagate corruptions and administrative errors, but the changes applied to the mirrored volume are a result of the same Oracle code path that applied the change to the source volume. There is no isolation, either from a storage mirroring perspective or from an Oracle software perspective.  Bottom line, storage remote-mirroring lacks both the smarts and isolation level necessary to provide true data protection. Active Data Guard offers much more than storage remote-mirroring when your objective is protecting your enterprise from downtime and data loss. Like remote-mirroring, an Active Data Guard replica is an exact block for block copy of the primary. Unlike remote-mirroring, an Active Data Guard replica is NOT a tightly coupled copy of the source volumes - it is a completely independent Oracle Database. Active Data Guard’s inherent knowledge of Oracle data block and redo structures enables a separate Oracle Database using a different Oracle code path than the primary to use the full complement of Oracle data validation methods before changes are applied to the synchronized copy. These include: physical check sum, logical intra-block checking, lost write validation, and automatic block repair. The figure below illustrates the stark difference between the knowledge that remote-mirroring can discern from an Oracle data block and what Active Data Guard can discern. An Active Data Guard standby also provides a range of additional services enabled by the fact that it is a running Oracle Database - not just a mirrored copy of data files. An Active Data Guard standby database can be open read-only while it is synchronizing with the primary. This enables read-only workloads to be offloaded from the primary system and run on the active standby - boosting performance by utilizing all assets. An Active Data Guard standby can also be used to implement many types of system and database maintenance in rolling fashion. Maintenance and upgrades are first implemented on the standby while production runs unaffected at the primary. After the primary and standby are synchronized and all changes have been validated, the production workload is quickly switched to the standby. The only downtime is the time required for user connections to transfer from one system to the next. These capabilities further expand the expectations of availability offered by a data protection solution beyond what is possible to do using storage remote-mirroring. So don’t be fooled by appearances.  Storage remote-mirroring and Active Data Guard replication may look similar on the surface - but the devil is in the details. Only Active Data Guard has the smarts, the isolation, and the simplicity, to provide the best data protection and availability for the Oracle Database. Stay tuned for future blog posts that dive into the many differences between storage remote-mirroring and Active Data Guard along the dimensions of data protection, data availability, cost, asset utilization and return on investment. For additional information on Active Data Guard, see: Active Data Guard Technical White Paper Active Data Guard vs Storage Remote-Mirroring Active Data Guard Home Page on the Oracle Technology Network

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  • Oracle Virtual Networking Partner Sales Playbook Now Available

    - by Cinzia Mascanzoni
    Oracle Virtual Networking Partner Sales Playbook now available to partners registered in OPN Server and Storage Systems Knowledge Zones. Equips you to sell, identify and qualify opportunities, pursue specific sales plays, and deliver competitive differentiation. Find out where you should plan to focus your resources, and how to broaden your offerings by leveraging the OPN Specialized enablement available to your organization. Playbook is accessible to member partners through the following Knowledge Zones: Sun x86 Servers, Sun Blade Servers, SPARC T-Series Servers, SPARC Enterprise High-End M-Series Servers, SPARC Enterprise Entry-Level and Midrange M-Series Servers, Oracle Desktop Virtualization, NAS Storage, SAN Storage, Sun Flash Storage, StorageTek Tape Storage.

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  • New DataCenter Options for Windows Azure

    - by ScottKlein
    Effective immediately, new compute and storage resource options are now available when selecting data center options in the Windows Azure Portal. "West US" and "East US" options are now available, for Compute and Storage. SQL Azure options for these two data centers will be available in the next few months. The official announcement can be found here.In terms of geo-replication:US East and West are paired together for Windows Azure Storage geo-replicationUS North and South are paired together for Windows Azure Storage geo-replicationThese two new data centers are now visible in the Windows Azure Management Portal effective immediately. Compute and Storage pricing remains the same across all data centers. Get started with Windows Azure through the free 90 day trial.

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  • Getting Windows Azure SDK 1.1 To Talk To A Local DB

    - by Richard Jones
    Just found this, if you’re using Azure 1.1,  which you probably will be if yo'u’ve moved to Visual Studio 2010. To change the default database to something other than sqlexpress for Development Storage do this - Look at this - http://msdn.microsoft.com/en-us/library/dd203058.aspx At the bottom it states -   Using Development Storage with SQL Server Express 2008 By default the local Windows Group BUILTIN\Administrator is not included in the SQL Server sysadmin server role on new SQL Server Express 2008 installations.  Add yourself to the sysadmin role in order to use the Development Storage Services on SQL Server Express 2008.  See SQL Server 2008 Security Changes for more information. Changing the SQL Server instance used by Development Storage By default, the Development Storage will use the SQL Express instance.  This can be changed by calling “DSInit.exe /sqlinstance:<SQL Server instance>” from the Windows Azure SDK command prompt.

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  • Deduping your redundancies

    - by nospam(at)example.com (Joerg Moellenkamp)
    Robin Harris of Storagemojo pointed to an interesting article about about deduplication and it's impact to the resiliency of your data against data corruption on ACM Queue. The problem in short: A considerable number of filesystems store important metadata at multiple locations. For example the ZFS rootblock is copied to three locations. Other filesystems have similar provisions to protect their metadata. However you can easily proof, that the rootblock pointer in the uberblock of ZFS for example is pointing to blocks with absolutely equal content in all three locatition (with zdb -uu and zdb -r). It has to be that way, because they are protected by the same checksum. A number of devices offer block level dedup, either as an option or as part of their inner workings. However when you store three identical blocks on them and the devices does block level dedup internally, the device may just deduplicated your redundant metadata to a block stored just once that is stored on the non-voilatile storage. When this block is corrupted, you have essentially three corrupted copies. Three hit with one bullet. This is indeed an interesting problem: A device doing deduplication doesn't know if a block is important or just a datablock. This is the reason why I like deduplication like it's done in ZFS. It's an integrated part and so important parts don't get deduplicated away. A disk accessed by a block level interface doesn't know anything about the importance of a block. A metadata block is nothing different to it's inner mechanism than a normal data block because there is no way to tell that this is important and that those redundancies aren't allowed to fall prey to some clever deduplication mechanism. Robin talks about this in regard of the Sandforce disk controllers who use a kind of dedup to reduce some of the nasty effects of writing data to flash, but the problem is much broader. However this is relevant whenever you are using a device with block level deduplication. It's just the point that you have to activate it for most implementation by command, whereas certain devices do this by default or by design and you don't know about it. However I'm not perfectly sure about that ? given that storage administration and server administration are often different groups with different business objectives I would ask your storage guys if they have activated dedup without telling somebody elase on their boxes in order to speak less often with the storage sales rep. The problem is even more interesting with ZFS. You may use ditto blocks to protect important data to store multiple copies of data in the pool to increase redundancy, even when your pool just consists out of one disk or just a striped set of disk. However when your device is doing dedup internally it may remove your redundancy before it hits the nonvolatile storage. You've won nothing. Just spend your disk quota on the the LUNs in the SAN and you make your disk admin happy because of the good dedup ratio However you can just fall in this specific "deduped ditto block"trap when your pool just consists out of a single device, because ZFS writes ditto blocks on different disks, when there is more than just one disk. Yet another reason why you should spend some extra-thought when putting your zpool on a single LUN, especially when the LUN is sliced and dices out of a large heap of storage devices by a storage controller. However I have one problem with the articles and their specific mention of ZFS: You can just hit by this problem when you are using the deduplicating device for the pool. However in the specifically mentioned case of SSD this isn't the usecase. Most implementations of SSD in conjunction with ZFS are hybrid storage pools and so rotating rust disk is used as pool and SSD are used as L2ARC/sZIL. And there it simply doesn't matter: When you really have to resort to the sZIL (your system went down, it doesn't matter of one block or several blocks are corrupt, you have to fail back to the last known good transaction group the device. On the other side, when a block in L2ARC is corrupt, you simply read it from the pool and in HSP implementations this is the already mentioned rust. In conjunction with ZFS this is more interesting when using a storage array, that is capable to do dedup and where you use LUNs for your pool. However as mentioned before, on those devices it's a user made decision to do so, and so it's less probable that you deduplicating your redundancies. Other filesystems lacking acapability similar to hybrid storage pools are more "haunted" by this problem of SSD using dedup-like mechanisms internally, because those filesystem really store the data on the the SSD instead of using it just as accelerating devices. However at the end Robin is correct: It's jet another point why protecting your data by creating redundancies by dispersing it several disks (by mirror or parity RAIDs) is really important. No dedup mechanism inside a device can dedup away your redundancy when you write it to a totally different and indepenent device.

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  • html5 offline storage for Windows Mobile 6.1 or an alternative?

    - by SimonNet
    I understand that there are no browsers currently which support offline storage for mobile 6.1. I am trying to find a web form based solution avoiding the loss of data when my device has no connectivity. Have ruled out Gears and would like to avoid a win forms application as the forms change so often. Are there any other approaches that I should look at which are viable in C#? Are there any estimated dates for when we might see a browser for mobile 6.1 which can offer offline storage? Thanks

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  • 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?

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  • 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?

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  • What is the most efficient way to clone a JavaScript object?

    - by jschrab
    What is the most efficient way to clone a JavaScript object? I've seen: obj = eval(uneval(o)); but that's not cross platform (FF only). I've done (in Mootools 1.2) things like this: obj = JSON.decode(JSON.encode(o)); but question the efficiency. I've also seen recursive copying function, etc. I'm pretty surprised that out-of-the-box JavaScript doesn't have a method for doing this.

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  • Efficient algorithm to find a maximum common subset of two sets?

    - by datasunny
    Each set contains bunch of checksums. For example: Set A: { 4445968d0e100ad08323df8c895cea15 a67f8052594d6ba3f75502c0b91b868f 07736dde2f8484a4a3af463e05f039e3 5b1e374ff2ba949ab49870ca24d3163a } Set B: { 6639e1da308fd7b04b7635a17450df7c 4445968d0e100ad08323df8c895cea15 a67f8052594d6ba3f75502c0b91b868f } The maximum common subset of A and B is: { 4445968d0e100ad08323df8c895cea15 a67f8052594d6ba3f75502c0b91b868f } A lot of this operations will be performed, so I'm looking for an efficient algorithm to do so. Thanks for your help.

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  • What is the most efficient way to determine if a directed graph is singly connected?

    - by zebraman
    I am working on an assignment where one of the problems asks to derive an algorithm to check if a directed graph G=(V,E) is singly connected (there is at most one simple path from u to v for all distinct vertices u,v of V. Of course you can brute force check it, which is what I'm doing right now, but I want to know if there's a more efficient way. Could anyone point me in the right direction?

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  • Convert.ToInt or String.Split : which is more efficient?

    - by zsharp
    Which way is better for removing float decimals places or is there a more efficient way? Rounding is not important, i am interested in displaying the number Float number; 1- int wholeNumber= Convert.ToInt(number); string display=wholeNumber.ToString(); 2- string [] splitNumber= number.ToString().Split('.'); string display=splitNumber[0];

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