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  • Using Core Data Concurrently and Reliably

    - by John Topley
    I'm building my first iOS app, which in theory should be pretty straightforward but I'm having difficulty making it sufficiently bulletproof for me to feel confident submitting it to the App Store. Briefly, the main screen has a table view, upon selecting a row it segues to another table view that displays information relevant for the selected row in a master-detail fashion. The underlying data is retrieved as JSON data from a web service once a day and then cached in a Core Data store. The data previous to that day is deleted to stop the SQLite database file from growing indefinitely. All data persistence operations are performed using Core Data, with an NSFetchedResultsController underpinning the detail table view. The problem I am seeing is that if you switch quickly between the master and detail screens several times whilst fresh data is being retrieved, parsed and saved, the app freezes or crashes completely. There seems to be some sort of race condition, maybe due to Core Data importing data in the background whilst the main thread is trying to perform a fetch, but I'm speculating. I've had trouble capturing any meaningful crash information, usually it's a SIGSEGV deep in the Core Data stack. The table below shows the actual order of events that happen when the detail table view controller is loaded: Main Thread Background Thread viewDidLoad Get JSON data (using AFNetworking) Create child NSManagedObjectContext (MOC) Parse JSON data Insert managed objects in child MOC Save child MOC Post import completion notification Receive import completion notification Save parent MOC Perform fetch and reload table view Delete old managed objects in child MOC Save child MOC Post deletion completion notification Receive deletion completion notification Save parent MOC Once the AFNetworking completion block is triggered when the JSON data has arrived, a nested NSManagedObjectContext is created and passed to an "importer" object that parses the JSON data and saves the objects to the Core Data store. The importer executes using the new performBlock method introduced in iOS 5: NSManagedObjectContext *child = [[NSManagedObjectContext alloc] initWithConcurrencyType:NSPrivateQueueConcurrencyType]; [child setParentContext:self.managedObjectContext]; [child performBlock:^{ // Create importer instance, passing it the child MOC... }]; The importer object observes its own MOC's NSManagedObjectContextDidSaveNotification and then posts its own notification which is observed by the detail table view controller. When this notification is posted the table view controller performs a save on its own (parent) MOC. I use the same basic pattern with a "deleter" object for deleting the old data after the new data for the day has been imported. This occurs asynchronously after the new data has been fetched by the fetched results controller and the detail table view has been reloaded. One thing I am not doing is observing any merge notifications or locking any of the managed object contexts or the persistent store coordinator. Is this something I should be doing? I'm a bit unsure how to architect this all correctly so would appreciate any advice.

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  • Create a dataset: extract features from text documents (TF-IDF)

    - by BigG
    I've to create a dataset from some text files, writing them as vectors of features. Something like this: doc1: 1,0.45 6,0.001 94,0.1 ... doc2: 3,0.5 98,0.2 ... ... each position of the vector represent a word, and the score is given by something like TF-IDF. Do you know some library/tool/whatever for this? (java is better)

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  • Used HDD/ran DiskSmartView/40,000 Power-on-hours?? should i trust it w/ my data, or take it back and bitch?

    - by David Lindsay
    I just bought a used hard drive from a University Surplus Store. Decided to run DiskSmartView to make sure it wasn't ready to fail. 40,000 power-on-hours I don't know if I feel like trusting my data to something that used. I really dont know if thats unreasonably old, but when i compare it to the POH reading i get when testing my other hdds its more than 3x older (my others have 2110 hours, 6150 hours, etc.. It's a Western Digital, so that gives me a little bit of hope(WDC WD4000KD-00NAB0). I could sure use someone else's opinion here. Thanks, DAVE

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  • Windows Azure Recipe: Big Data

    - by Clint Edmonson
    As the name implies, what we’re talking about here is the explosion of electronic data that comes from huge volumes of transactions, devices, and sensors being captured by businesses today. This data often comes in unstructured formats and/or too fast for us to effectively process in real time. Collectively, we call these the 4 big data V’s: Volume, Velocity, Variety, and Variability. These qualities make this type of data best managed by NoSQL systems like Hadoop, rather than by conventional Relational Database Management System (RDBMS). We know that there are patterns hidden inside this data that might provide competitive insight into market trends.  The key is knowing when and how to leverage these “No SQL” tools combined with traditional business such as SQL-based relational databases and warehouses and other business intelligence tools. Drivers Petabyte scale data collection and storage Business intelligence and insight Solution The sketch below shows one of many big data solutions using Hadoop’s unique highly scalable storage and parallel processing capabilities combined with Microsoft Office’s Business Intelligence Components to access the data in the cluster. Ingredients Hadoop – this big data industry heavyweight provides both large scale data storage infrastructure and a highly parallelized map-reduce processing engine to crunch through the data efficiently. Here are the key pieces of the environment: Pig - a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs. Mahout - a machine learning library with algorithms for clustering, classification and batch based collaborative filtering that are implemented on top of Apache Hadoop using the map/reduce paradigm. Hive - data warehouse software built on top of Apache Hadoop that facilitates querying and managing large datasets residing in distributed storage. Directly accessible to Microsoft Office and other consumers via add-ins and the Hive ODBC data driver. Pegasus - a Peta-scale graph mining system that runs in parallel, distributed manner on top of Hadoop and that provides algorithms for important graph mining tasks such as Degree, PageRank, Random Walk with Restart (RWR), Radius, and Connected Components. Sqoop - a tool designed for efficiently transferring bulk data between Apache Hadoop and structured data stores such as relational databases. Flume - a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large log data amounts to HDFS. Database – directly accessible to Hadoop via the Sqoop based Microsoft SQL Server Connector for Apache Hadoop, data can be efficiently transferred to traditional relational data stores for replication, reporting, or other needs. Reporting – provides easily consumable reporting when combined with a database being fed from the Hadoop environment. Training These links point to online Windows Azure training labs where you can learn more about the individual ingredients described above. Hadoop Learning Resources (20+ tutorials and labs) Huge collection of resources for learning about all aspects of Apache Hadoop-based development on Windows Azure and the Hadoop and Windows Azure Ecosystems SQL Azure (7 labs) Microsoft SQL Azure delivers on the Microsoft Data Platform vision of extending the SQL Server capabilities to the cloud as web-based services, enabling you to store structured, semi-structured, and unstructured data. See my Windows Azure Resource Guide for more guidance on how to get started, including links web portals, training kits, samples, and blogs related to Windows Azure.

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  • Master Data Management

    - by Logicalj
    I am looking for a very flexible, easy to integrate and dynamic application with as many features as possible for Master Data Management. As Master Data Management is used to Manage Operational Data, Analytical Data and Master Data so, I want guidance about "What is exactly expected from Master Data Management and What are the Basic and Challenging Scenarios to be covered or resolved in Master Data Management". Please guide me with all the possible aspects of Master Data Management like Data Cleansing, Data Management and Start Data Analyzing, etc.

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  • What is the architectural name for the set of data that enables UI choices?

    - by Richard Collette
    I have separate service methods that fetch business object data and the data for UI selection input such as radio buttons, check-boxes, combo-boxes, etc. I want to name my service methods that fetch the selection data appropriately. I am assuming that Model and ViewModel would not be part of the name because the selection data is but a portion of the Model or ViewModel. What might this set of data be named such that I can name my service method?

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  • www-data can upload a file but cant move it after the upload action

    - by user70058
    I am currently running Apache and PHP on Ubuntu. I have a page where a user is supposed to upload a profile image. The action on the backend is supposed to work like this: Upload file to user directory -- WORKS! Refer to the uploaded file and create a thumbnail in directory thumbs -- DOES NOT WORK www-data has write access to directory thumbs. My guess is that www-data for some reason does not have proper access to the file that was uploaded. UPLOADED FILE PERMISSIONS -rw-r--r-- 1 www-data www-data 47057 Feb 8 23:24 0181c6e0973eb19cb0d98521a6fe1d9e71cd6daa.jpg THUMBS DIRECTORY PERMISSIONS drwxr-sr-x 2 www-data www-data 4096 Feb 8 23:23 thumbs Im at lost here. I'm new to Ubuntu as well. Any help would be greatly appreciated!

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  • Syncing Data with a Server using Silverlight and HTTP Polling Duplex

    - by dwahlin
    Many applications have the need to stay in-sync with data provided by a service. Although web applications typically rely on standard polling techniques to check if data has changed, Silverlight provides several interesting options for keeping an application in-sync that rely on server “push” technologies. A few years back I wrote several blog posts covering different “push” technologies available in Silverlight that rely on sockets or HTTP Polling Duplex. We recently had a project that looked like it could benefit from pushing data from a server to one or more clients so I thought I’d revisit the subject and provide some updates to the original code posted. If you’ve worked with AJAX before in Web applications then you know that until browsers fully support web sockets or other duplex (bi-directional communication) technologies that it’s difficult to keep applications in-sync with a server without relying on polling. The problem with polling is that you have to check for changes on the server on a timed-basis which can often be wasteful and take up unnecessary resources. With server “push” technologies, data can be pushed from the server to the client as it changes. Once the data is received, the client can update the user interface as appropriate. Using “push” technologies allows the client to listen for changes from the data but stay 100% focused on client activities as opposed to worrying about polling and asking the server if anything has changed. Silverlight provides several options for pushing data from a server to a client including sockets, TCP bindings and HTTP Polling Duplex.  Each has its own strengths and weaknesses as far as performance and setup work with HTTP Polling Duplex arguably being the easiest to setup and get going.  In this article I’ll demonstrate how HTTP Polling Duplex can be used in Silverlight 4 applications to push data and show how you can create a WCF server that provides an HTTP Polling Duplex binding that a Silverlight client can consume.   What is HTTP Polling Duplex? Technologies that allow data to be pushed from a server to a client rely on duplex functionality. Duplex (or bi-directional) communication allows data to be passed in both directions.  A client can call a service and the server can call the client. HTTP Polling Duplex (as its name implies) allows a server to communicate with a client without forcing the client to constantly poll the server. It has the benefit of being able to run on port 80 making setup a breeze compared to the other options which require specific ports to be used and cross-domain policy files to be exposed on port 943 (as with sockets and TCP bindings). Having said that, if you’re looking for the best speed possible then sockets and TCP bindings are the way to go. But, they’re not the only game in town when it comes to duplex communication. The first time I heard about HTTP Polling Duplex (initially available in Silverlight 2) I wasn’t exactly sure how it was any better than standard polling used in AJAX applications. I read the Silverlight SDK, looked at various resources and generally found the following definition unhelpful as far as understanding the actual benefits that HTTP Polling Duplex provided: "The Silverlight client periodically polls the service on the network layer, and checks for any new messages that the service wants to send on the callback channel. The service queues all messages sent on the client callback channel and delivers them to the client when the client polls the service." Although the previous definition explained the overall process, it sounded as if standard polling was used. Fortunately, Microsoft’s Scott Guthrie provided me with a more clear definition several years back that explains the benefits provided by HTTP Polling Duplex quite well (used with his permission): "The [HTTP Polling Duplex] duplex support does use polling in the background to implement notifications – although the way it does it is different than manual polling. It initiates a network request, and then the request is effectively “put to sleep” waiting for the server to respond (it doesn’t come back immediately). The server then keeps the connection open but not active until it has something to send back (or the connection times out after 90 seconds – at which point the duplex client will connect again and wait). This way you are avoiding hitting the server repeatedly – but still get an immediate response when there is data to send." After hearing Scott’s definition the light bulb went on and it all made sense. A client makes a request to a server to check for changes, but instead of the request returning immediately, it parks itself on the server and waits for data. It’s kind of like waiting to pick up a pizza at the store. Instead of calling the store over and over to check the status, you sit in the store and wait until the pizza (the request data) is ready. Once it’s ready you take it back home (to the client). This technique provides a lot of efficiency gains over standard polling techniques even though it does use some polling of its own as a request is initially made from a client to a server. So how do you implement HTTP Polling Duplex in your Silverlight applications? Let’s take a look at the process by starting with the server. Creating an HTTP Polling Duplex WCF Service Creating a WCF service that exposes an HTTP Polling Duplex binding is straightforward as far as coding goes. Add some one way operations into an interface, create a client callback interface and you’re ready to go. The most challenging part comes into play when configuring the service to properly support the necessary binding and that’s more of a cut and paste operation once you know the configuration code to use. To create an HTTP Polling Duplex service you’ll need to expose server-side and client-side interfaces and reference the System.ServiceModel.PollingDuplex assembly (located at C:\Program Files (x86)\Microsoft SDKs\Silverlight\v4.0\Libraries\Server on my machine) in the server project. For the demo application I upgraded a basketball simulation service to support the latest polling duplex assemblies. The service simulates a simple basketball game using a Game class and pushes information about the game such as score, fouls, shots and more to the client as the game changes over time. Before jumping too far into the game push service, it’s important to discuss two interfaces used by the service to communicate in a bi-directional manner. The first is called IGameStreamService and defines the methods/operations that the client can call on the server (see Listing 1). The second is IGameStreamClient which defines the callback methods that a server can use to communicate with a client (see Listing 2).   [ServiceContract(Namespace = "Silverlight", CallbackContract = typeof(IGameStreamClient))] public interface IGameStreamService { [OperationContract(IsOneWay = true)] void GetTeamData(); } Listing 1. The IGameStreamService interface defines server operations that can be called on the server.   [ServiceContract] public interface IGameStreamClient { [OperationContract(IsOneWay = true)] void ReceiveTeamData(List<Team> teamData); [OperationContract(IsOneWay = true, AsyncPattern=true)] IAsyncResult BeginReceiveGameData(GameData gameData, AsyncCallback callback, object state); void EndReceiveGameData(IAsyncResult result); } Listing 2. The IGameStreamClient interfaces defines client operations that a server can call.   The IGameStreamService interface is decorated with the standard ServiceContract attribute but also contains a value for the CallbackContract property.  This property is used to define the interface that the client will expose (IGameStreamClient in this example) and use to receive data pushed from the service. Notice that each OperationContract attribute in both interfaces sets the IsOneWay property to true. This means that the operation can be called and passed data as appropriate, however, no data will be passed back. Instead, data will be pushed back to the client as it’s available.  Looking through the IGameStreamService interface you can see that the client can request team data whereas the IGameStreamClient interface allows team and game data to be received by the client. One interesting point about the IGameStreamClient interface is the inclusion of the AsyncPattern property on the BeginReceiveGameData operation. I initially created this operation as a standard one way operation and it worked most of the time. However, as I disconnected clients and reconnected new ones game data wasn’t being passed properly. After researching the problem more I realized that because the service could take up to 7 seconds to return game data, things were getting hung up. By setting the AsyncPattern property to true on the BeginReceivedGameData operation and providing a corresponding EndReceiveGameData operation I was able to get around this problem and get everything running properly. I’ll provide more details on the implementation of these two methods later in this post. Once the interfaces were created I moved on to the game service class. The first order of business was to create a class that implemented the IGameStreamService interface. Since the service can be used by multiple clients wanting game data I added the ServiceBehavior attribute to the class definition so that I could set its InstanceContextMode to InstanceContextMode.Single (in effect creating a Singleton service object). Listing 3 shows the game service class as well as its fields and constructor.   [ServiceBehavior(ConcurrencyMode = ConcurrencyMode.Multiple, InstanceContextMode = InstanceContextMode.Single)] public class GameStreamService : IGameStreamService { object _Key = new object(); Game _Game = null; Timer _Timer = null; Random _Random = null; Dictionary<string, IGameStreamClient> _ClientCallbacks = new Dictionary<string, IGameStreamClient>(); static AsyncCallback _ReceiveGameDataCompleted = new AsyncCallback(ReceiveGameDataCompleted); public GameStreamService() { _Game = new Game(); _Timer = new Timer { Enabled = false, Interval = 2000, AutoReset = true }; _Timer.Elapsed += new ElapsedEventHandler(_Timer_Elapsed); _Timer.Start(); _Random = new Random(); }} Listing 3. The GameStreamService implements the IGameStreamService interface which defines a callback contract that allows the service class to push data back to the client. By implementing the IGameStreamService interface, GameStreamService must supply a GetTeamData() method which is responsible for supplying information about the teams that are playing as well as individual players.  GetTeamData() also acts as a client subscription method that tracks clients wanting to receive game data.  Listing 4 shows the GetTeamData() method. public void GetTeamData() { //Get client callback channel var context = OperationContext.Current; var sessionID = context.SessionId; var currClient = context.GetCallbackChannel<IGameStreamClient>(); context.Channel.Faulted += Disconnect; context.Channel.Closed += Disconnect; IGameStreamClient client; if (!_ClientCallbacks.TryGetValue(sessionID, out client)) { lock (_Key) { _ClientCallbacks[sessionID] = currClient; } } currClient.ReceiveTeamData(_Game.GetTeamData()); //Start timer which when fired sends updated score information to client if (!_Timer.Enabled) { _Timer.Enabled = true; } } Listing 4. The GetTeamData() method subscribes a given client to the game service and returns. The key the line of code in the GetTeamData() method is the call to GetCallbackChannel<IGameStreamClient>().  This method is responsible for accessing the calling client’s callback channel. The callback channel is defined by the IGameStreamClient interface shown earlier in Listing 2 and used by the server to communicate with the client. Before passing team data back to the client, GetTeamData() grabs the client’s session ID and checks if it already exists in the _ClientCallbacks dictionary object used to track clients wanting callbacks from the server. If the client doesn’t exist it adds it into the collection. It then pushes team data from the Game class back to the client by calling ReceiveTeamData().  Since the service simulates a basketball game, a timer is then started if it’s not already enabled which is then used to randomly send data to the client. When the timer fires, game data is pushed down to the client. Listing 5 shows the _Timer_Elapsed() method that is called when the timer fires as well as the SendGameData() method used to send data to the client. void _Timer_Elapsed(object sender, ElapsedEventArgs e) { int interval = _Random.Next(3000, 7000); lock (_Key) { _Timer.Interval = interval; _Timer.Enabled = false; } SendGameData(_Game.GetGameData()); } private void SendGameData(GameData gameData) { var cbs = _ClientCallbacks.Where(cb => ((IContextChannel)cb.Value).State == CommunicationState.Opened); for (int i = 0; i < cbs.Count(); i++) { var cb = cbs.ElementAt(i).Value; try { cb.BeginReceiveGameData(gameData, _ReceiveGameDataCompleted, cb); } catch (TimeoutException texp) { //Log timeout error } catch (CommunicationException cexp) { //Log communication error } } lock (_Key) _Timer.Enabled = true; } private static void ReceiveGameDataCompleted(IAsyncResult result) { try { ((IGameStreamClient)(result.AsyncState)).EndReceiveGameData(result); } catch (CommunicationException) { // empty } catch (TimeoutException) { // empty } } LIsting 5. _Timer_Elapsed is used to simulate time in a basketball game. When _Timer_Elapsed() fires the SendGameData() method is called which iterates through the clients wanting to be notified of changes. As each client is identified, their respective BeginReceiveGameData() method is called which ultimately pushes game data down to the client. Recall that this method was defined in the client callback interface named IGameStreamClient shown earlier in Listing 2. Notice that BeginReceiveGameData() accepts _ReceiveGameDataCompleted as its second parameter (an AsyncCallback delegate defined in the service class) and passes the client callback as the third parameter. The initial version of the sample application had a standard ReceiveGameData() method in the client callback interface. However, sometimes the client callbacks would work properly and sometimes they wouldn’t which was a little baffling at first glance. After some investigation I realized that I needed to implement an asynchronous pattern for client callbacks to work properly since 3 – 7 second delays are occurring as a result of the timer. Once I added the BeginReceiveGameData() and ReceiveGameDataCompleted() methods everything worked properly since each call was handled in an asynchronous manner. The final task that had to be completed to get the server working properly with HTTP Polling Duplex was adding configuration code into web.config. In the interest of brevity I won’t post all of the code here since the sample application includes everything you need. However, Listing 6 shows the key configuration code to handle creating a custom binding named pollingDuplexBinding and associate it with the service’s endpoint.   <bindings> <customBinding> <binding name="pollingDuplexBinding"> <binaryMessageEncoding /> <pollingDuplex maxPendingSessions="2147483647" maxPendingMessagesPerSession="2147483647" inactivityTimeout="02:00:00" serverPollTimeout="00:05:00"/> <httpTransport /> </binding> </customBinding> </bindings> <services> <service name="GameService.GameStreamService" behaviorConfiguration="GameStreamServiceBehavior"> <endpoint address="" binding="customBinding" bindingConfiguration="pollingDuplexBinding" contract="GameService.IGameStreamService"/> <endpoint address="mex" binding="mexHttpBinding" contract="IMetadataExchange" /> </service> </services>   Listing 6. Configuring an HTTP Polling Duplex binding in web.config and associating an endpoint with it. Calling the Service and Receiving “Pushed” Data Calling the service and handling data that is pushed from the server is a simple and straightforward process in Silverlight. Since the service is configured with a MEX endpoint and exposes a WSDL file, you can right-click on the Silverlight project and select the standard Add Service Reference item. After the web service proxy is created you may notice that the ServiceReferences.ClientConfig file only contains an empty configuration element instead of the normal configuration elements created when creating a standard WCF proxy. You can certainly update the file if you want to read from it at runtime but for the sample application I fed the service URI directly to the service proxy as shown next: var address = new EndpointAddress("http://localhost.:5661/GameStreamService.svc"); var binding = new PollingDuplexHttpBinding(); _Proxy = new GameStreamServiceClient(binding, address); _Proxy.ReceiveTeamDataReceived += _Proxy_ReceiveTeamDataReceived; _Proxy.ReceiveGameDataReceived += _Proxy_ReceiveGameDataReceived; _Proxy.GetTeamDataAsync(); This code creates the proxy and passes the endpoint address and binding to use to its constructor. It then wires the different receive events to callback methods and calls GetTeamDataAsync().  Calling GetTeamDataAsync() causes the server to store the client in the server-side dictionary collection mentioned earlier so that it can receive data that is pushed.  As the server-side timer fires and game data is pushed to the client, the user interface is updated as shown in Listing 7. Listing 8 shows the _Proxy_ReceiveGameDataReceived() method responsible for handling the data and calling UpdateGameData() to process it.   Listing 7. The Silverlight interface. Game data is pushed from the server to the client using HTTP Polling Duplex. void _Proxy_ReceiveGameDataReceived(object sender, ReceiveGameDataReceivedEventArgs e) { UpdateGameData(e.gameData); } private void UpdateGameData(GameData gameData) { //Update Score this.tbTeam1Score.Text = gameData.Team1Score.ToString(); this.tbTeam2Score.Text = gameData.Team2Score.ToString(); //Update ball visibility if (gameData.Action != ActionsEnum.Foul) { if (tbTeam1.Text == gameData.TeamOnOffense) { AnimateBall(this.BB1, this.BB2); } else //Team 2 { AnimateBall(this.BB2, this.BB1); } } if (this.lbActions.Items.Count > 9) this.lbActions.Items.Clear(); this.lbActions.Items.Add(gameData.LastAction); if (this.lbActions.Visibility == Visibility.Collapsed) this.lbActions.Visibility = Visibility.Visible; } private void AnimateBall(Image onBall, Image offBall) { this.FadeIn.Stop(); Storyboard.SetTarget(this.FadeInAnimation, onBall); Storyboard.SetTarget(this.FadeOutAnimation, offBall); this.FadeIn.Begin(); } Listing 8. As the server pushes game data, the client’s _Proxy_ReceiveGameDataReceived() method is called to process the data. In a real-life application I’d go with a ViewModel class to handle retrieving team data, setup data bindings and handle data that is pushed from the server. However, for the sample application I wanted to focus on HTTP Polling Duplex and keep things as simple as possible.   Summary Silverlight supports three options when duplex communication is required in an application including TCP bindins, sockets and HTTP Polling Duplex. In this post you’ve seen how HTTP Polling Duplex interfaces can be created and implemented on the server as well as how they can be consumed by a Silverlight client. HTTP Polling Duplex provides a nice way to “push” data from a server while still allowing the data to flow over port 80 or another port of your choice.   Sample Application Download

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  • Oracle Enterprise Data Quality Adds Global Address Verification Capabilities for Greater Accuracy and Broader Location Coverage

    - by Mala Narasimharajan
    Data quality – has many flavors to it.  Product, Customer – you name the data domain and there’s data quality associated with it.  Address verification and data quality are a little different.  in that there is a tremendous amount of variation as well as nuance attached to it.  Specifically, what makes address verification challenging is that more often than not, addresses are incomplete, riddled with misspellings, incorrect postal codes are assigned to locations or non-address items are present.  Almost all data has locations, and accurate locations power a wealth of business processes: Customer Relationship Management, data quality, delivery of materials, goods or services, fraud detection, insurance risk assessment, data analytics, store and territory planning, and much more. Oracle Address Verification Server provides location-based services as well as deeper parsing and analysis capabilities for Oracle Enterprise Data Quality.  Specifically, Pre-integrated with the EDQ platform, Oracle Address Verification Server provides robust parsing, validation, as well as specialized location information for over 240 countries – all populated countries on Earth.  Oracle Enterprise Data Quality (EDQ) is a data quality platform, dedicated to address the distinct challenges of customer and product data quality, and performs advanced data profiling to identify and measure poor quality data and identify rule requirements, as well as semantic and pattern-based recognition to accurately parse and standardize data that is poorly structured.   EDQ is integrated with Oracle Master Data Management, including Oracle Customer Hub and Oracle Product Hub, as well as Oracle Data Integrator Enterprise Edition and Oracle CRM.  Address Verification Server provides key address verification services for Oracle CRM and Oracle Customer Hub.  In addition, Address Verification Server provides greater accuracy when handling address data due to its expanded sources and extensible knowledge repository, solid parsing across locales and countries as well as  adept handling of extraneous data in address fields.  For more information on Oracle Address Verification Server visit:  http://bit.ly/GMUE4H and http://bit.ly/GWf7U6

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  • Making Spring Data JPA work with DataNucleus (GAE) (Spring Boot)

    - by xybrek
    There are several hints that Spring Data works with Google App Engine like: http://tommysiu.blogspot.com/2014/01/spring-data-on-gae-part-1.html http://blog.eisele.net/2009/07/spring-300m3-on-google-appengine-with.html Much of the examples are not "Spring Boot" so I've been trying to retrofit things with it. However, I've been stuck with this error for days and days: [INFO] Caused by: java.lang.NullPointerException [INFO] at org.datanucleus.api.jpa.metamodel.SingularAttributeImpl.isVersion(SingularAttributeImpl.java:79) [INFO] at org.springframework.data.jpa.repository.support.JpaMetamodelEntityInformation.findVersionAttribute(JpaMetamodelEntityInformation.java:102) [INFO] at org.springframework.data.jpa.repository.support.JpaMetamodelEntityInformation.<init>(JpaMetamodelEntityInformation.java:79) [INFO] at org.springframework.data.jpa.repository.support.JpaEntityInformationSupport.getMetadata(JpaEntityInformationSupport.java:65) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getEntityInformation(JpaRepositoryFactory.java:149) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getTargetRepository(JpaRepositoryFactory.java:88) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getTargetRepository(JpaRepositoryFactory.java:68) [INFO] at org.springframework.data.repository.core.support.RepositoryFactorySupport.getRepository(RepositoryFactorySupport.java:158) [INFO] at org.springframework.data.repository.core.support.RepositoryFactoryBeanSupport.initAndReturn(RepositoryFactoryBeanSupport.java:224) [INFO] at org.springframework.data.repository.core.support.RepositoryFactoryBeanSupport.afterPropertiesSet(RepositoryFactoryBeanSupport.java:210) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactoryBean.afterPropertiesSet(JpaRepositoryFactoryBean.java:92) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory$6.run(AbstractAutowireCapableBeanFactory.java:1602) [INFO] at java.security.AccessController.doPrivileged(Native Method) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.invokeInitMethods(AbstractAutowireCapableBeanFactory.java:1599) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.initializeBean(AbstractAutowireCapableBeanFactory.java:1549) [INFO] ... 40 more Where, I'm trying to use Spring Data JPA with DataNucleus/AppEngine: @Configuration @ComponentScan @EnableJpaRepositories @EnableTransactionManagement class JpaApplicationConfig { private static final Logger logger = Logger .getLogger(JpaApplicationConfig.class.getName()); @Bean public EntityManagerFactory entityManagerFactory() { logger.info("Loading Entity Manager..."); return Persistence .createEntityManagerFactory("transactions-optional"); } @Bean public PlatformTransactionManager transactionManager() { logger.info("Loading Transaction Manager..."); final JpaTransactionManager txManager = new JpaTransactionManager(); txManager.setEntityManagerFactory(entityManagerFactory()); return txManager; } } I've tested Persistence.createEntityManagerFactory("transactions-optional"); to see if the app can persist using this EMF, well, it does, so I am sure that this EMF works fine. The problem is the "wiring" up with the Spring Data JPA, can anybody help?

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  • Parse and read data frame in C?

    - by user253656
    I am writing a program that reads the data from the serial port on Linux. The data are sent by another device with the following frame format: |start | Command | Data | CRC | End | |0x02 | 0x41 | (0-127 octets) | | 0x03| ---------------------------------------------------- The Data field contains 127 octets as shown and octet 1,2 contains one type of data; octet 3,4 contains another data. I need to get these data I know how to write and read data to and from a serial port in Linux, but it is just to write and read a simple string (like "ABD") My issue is that I do not know how to parse the data frame formatted as above so that I can: get the data in octet 1,2 in the Data field get the data in octet 3,4 in the Data field get the value in CRC field to check the consistency of the data Here the sample snip code that read and write a simple string from and to a serial port in Linux: int writeport(int fd, char *chars) { int len = strlen(chars); chars[len] = 0x0d; // stick a <CR> after the command chars[len+1] = 0x00; // terminate the string properly int n = write(fd, chars, strlen(chars)); if (n < 0) { fputs("write failed!\n", stderr); return 0; } return 1; } int readport(int fd, char *result) { int iIn = read(fd, result, 254); result[iIn-1] = 0x00; if (iIn < 0) { if (errno == EAGAIN) { printf("SERIAL EAGAIN ERROR\n"); return 0; } else { printf("SERIAL read error %d %s\n", errno, strerror(errno)); return 0; } } return 1; } Does anyone please have some ideas? Thanks all.

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  • Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 1

    - by rajbk
    The Open Data Protocol, referred to as OData, is a new data-sharing standard that breaks down silos and fosters an interoperative ecosystem for data consumers (clients) and producers (services) that is far more powerful than currently possible. It enables more applications to make sense of a broader set of data, and helps every data service and client add value to the whole ecosystem. WCF Data Services (previously known as ADO.NET Data Services), then, was the first Microsoft technology to support the Open Data Protocol in Visual Studio 2008 SP1. It provides developers with client libraries for .NET, Silverlight, AJAX, PHP and Java. Microsoft now also supports OData in SQL Server 2008 R2, Windows Azure Storage, Excel 2010 (through PowerPivot), and SharePoint 2010. Many other other applications in the works. * This post walks you through how to create an OData feed, define a shape for the data and pre-filter the data using Visual Studio 2010, WCF Data Services and the Entity Framework. A sample project is attached at the bottom of Part 2 of this post. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Create the Web Application File –› New –› Project, Select “ASP.NET Empty Web Application” Add the Entity Data Model Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “ADO.NET Entity Data Model” under "Data”. Name the Model “Northwind” and click “Add”.   In the “Choose Model Contents”, select “Generate Model From Database” and click “Next”   Define a connection to your database containing the Northwind database in the next screen. We are going to expose the Products table through our OData feed. Select “Products” in the “Choose your Database Object” screen.   Click “Finish”. We are done creating our Entity Data Model. Save the Northwind.edmx file created. Add the WCF Data Service Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “WCF Data Service” from the list and call the service “DataService” (creative, huh?). Click “Add”.   Enable Access to the Data Service Open the DataService.svc.cs class. The class is well commented and instructs us on the next steps. public class DataService : DataService< /* TODO: put your data source class name here */ > { // This method is called only once to initialize service-wide policies. public static void InitializeService(DataServiceConfiguration config) { // TODO: set rules to indicate which entity sets and service operations are visible, updatable, etc. // Examples: // config.SetEntitySetAccessRule("MyEntityset", EntitySetRights.AllRead); // config.SetServiceOperationAccessRule("MyServiceOperation", ServiceOperationRights.All); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } Replace the comment that starts with “/* TODO:” with “NorthwindEntities” (the entity container name of the Model we created earlier).  WCF Data Services is initially locked down by default, FTW! No data is exposed without you explicitly setting it. You have explicitly specify which Entity sets you wish to expose and what rights are allowed by using the SetEntitySetAccessRule. The SetServiceOperationAccessRule on the other hand sets rules for a specified operation. Let us define an access rule to expose the Products Entity we created earlier. We use the EnititySetRights.AllRead since we want to give read only access. Our modified code is shown below. public class DataService : DataService<NorthwindEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("Products", EntitySetRights.AllRead); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } We are done setting up our ODataFeed! Compile your project. Right click on DataService.svc and select “View in Browser” to see the OData feed. To view the feed in IE, you must make sure that "Feed Reading View" is turned off. You set this under Tools -› Internet Options -› Content tab.   If you navigate to “Products”, you should see the Products feed. Note also that URIs are case sensitive. ie. Products work but products doesn’t.   Filtering our data OData has a set of system query operations you can use to perform common operations against data exposed by the model. For example, to see only Products in CategoryID 2, we can use the following request: /DataService.svc/Products?$filter=CategoryID eq 2 At the time of this writing, supported operations are $orderby, $top, $skip, $filter, $expand, $format†, $select, $inlinecount. Pre-filtering our data using Query Interceptors The Product feed currently returns all Products. We want to change that so that it contains only Products that have not been discontinued. WCF introduces the concept of interceptors which allows us to inject custom validation/policy logic into the request/response pipeline of a WCF data service. We will use a QueryInterceptor to pre-filter the data so that it returns only Products that are not discontinued. To create a QueryInterceptor, write a method that returns an Expression<Func<T, bool>> and mark it with the QueryInterceptor attribute as shown below. [QueryInterceptor("Products")] public Expression<Func<Product, bool>> OnReadProducts() { return o => o.Discontinued == false; } Viewing the feed after compilation will only show products that have not been discontinued. We also confirm this by looking at the WHERE clause in the SQL generated by the entity framework. SELECT [Extent1].[ProductID] AS [ProductID], ... ... [Extent1].[Discontinued] AS [Discontinued] FROM [dbo].[Products] AS [Extent1] WHERE 0 = [Extent1].[Discontinued] Other examples of Query/Change interceptors can be seen here including an example to filter data based on the identity of the authenticated user. We are done pre-filtering our data. In the next part of this post, we will see how to shape our data. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Foot Notes * http://msdn.microsoft.com/en-us/data/aa937697.aspx † $format did not work for me. The way to get a Json response is to include the following in the  request header “Accept: application/json, text/javascript, */*” when making the request. This is easily done with most JavaScript libraries.

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  • Big Data Matters with ODI12c

    - by Madhu Nair
    contributed by Mike Eisterer On October 17th, 2013, Oracle announced the release of Oracle Data Integrator 12c (ODI12c).  This release signifies improvements to Oracle’s Data Integration portfolio of solutions, particularly Big Data integration. Why Big Data = Big Business Organizations are gaining greater insights and actionability through increased storage, processing and analytical benefits offered by Big Data solutions.  New technologies and frameworks like HDFS, NoSQL, Hive and MapReduce support these benefits now. As further data is collected, analytical requirements increase and the complexity of managing transformations and aggregations of data compounds and organizations are in need for scalable Data Integration solutions. ODI12c provides enterprise solutions for the movement, translation and transformation of information and data heterogeneously and in Big Data Environments through: The ability for existing ODI and SQL developers to leverage new Big Data technologies. A metadata focused approach for cataloging, defining and reusing Big Data technologies, mappings and process executions. Integration between many heterogeneous environments and technologies such as HDFS and Hive. Generation of Hive Query Language. Working with Big Data using Knowledge Modules  ODI12c provides developers with the ability to define sources and targets and visually develop mappings to effect the movement and transformation of data.  As the mappings are created, ODI12c leverages a rich library of prebuilt integrations, known as Knowledge Modules (KMs).  These KMs are contextual to the technologies and platforms to be integrated.  Steps and actions needed to manage the data integration are pre-built and configured within the KMs.  The Oracle Data Integrator Application Adapter for Hadoop provides a series of KMs, specifically designed to integrate with Big Data Technologies.  The Big Data KMs include: Check Knowledge Module Reverse Engineer Knowledge Module Hive Transform Knowledge Module Hive Control Append Knowledge Module File to Hive (LOAD DATA) Knowledge Module File-Hive to Oracle (OLH-OSCH) Knowledge Module  Nothing to beat an Example: To demonstrate the use of the KMs which are part of the ODI Application Adapter for Hadoop, a mapping may be defined to move data between files and Hive targets.  The mapping is defined by dragging the source and target into the mapping, performing the attribute (column) mapping (see Figure 1) and then selecting the KM which will govern the process.  In this mapping example, movie data is being moved from an HDFS source into a Hive table.  Some of the attributes, such as “CUSTID to custid”, have been mapped over. Figure 1  Defining the Mapping Before the proper KM can be assigned to define the technology for the mapping, it needs to be added to the ODI project.  The Big Data KMs have been made available to the project through the KM import process.   Generally, this is done prior to defining the mapping. Figure 2  Importing the Big Data Knowledge Modules Following the import, the KMs are available in the Designer Navigator. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Figure 3  The Project View in Designer, Showing Installed IKMs Once the KM is imported, it may be assigned to the mapping target.  This is done by selecting the Physical View of the mapping and examining the Properties of the Target.  In this case MOVIAPP_LOG_STAGE is the target of our mapping. Figure 4  Physical View of the Mapping and Assigning the Big Data Knowledge Module to the Target Alternative KMs may have been selected as well, providing flexibility and abstracting the logical mapping from the physical implementation.  Our mapping may be applied to other technologies as well. The mapping is now complete and is ready to run.  We will see more in a future blog about running a mapping to load Hive. To complete the quick ODI for Big Data Overview, let us take a closer look at what the IKM File to Hive is doing for us.  ODI provides differentiated capabilities by defining the process and steps which normally would have to be manually developed, tested and implemented into the KM.  As shown in figure 5, the KM is preparing the Hive session, managing the Hive tables, performing the initial load from HDFS and then performing the insert into Hive.  HDFS and Hive options are selected graphically, as shown in the properties in Figure 4. Figure 5  Process and Steps Managed by the KM What’s Next Big Data being the shape shifting business challenge it is is fast evolving into the deciding factor between market leaders and others. Now that an introduction to ODI and Big Data has been provided, look for additional blogs coming soon using the Knowledge Modules which make up the Oracle Data Integrator Application Adapter for Hadoop: Importing Big Data Metadata into ODI, Testing Data Stores and Loading Hive Targets Generating Transformations using Hive Query language Loading Oracle from Hadoop Sources For more information now, please visit the Oracle Data Integrator Application Adapter for Hadoop web site, http://www.oracle.com/us/products/middleware/data-integration/hadoop/overview/index.html Do not forget to tune in to the ODI12c Executive Launch webcast on the 12th to hear more about ODI12c and GG12c. Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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  • Slow retrieval of data in SQLITE takes a long using ContentProvider

    - by Arlyn
    I have an application in Android (running 4.0.3) that stores a lot of data in Table A. Table A resides in SQLite Database. I am using a ContentProvider as an abstraction layer above the database. Lots of data here means almost 80,000 records per month. Table A is structured like this: String SQL_CREATE_TABLE = "CREATE TABLE IF NOT EXISTS " + TABLE_A + " ( " + COLUMN_ID + " INTEGER PRIMARY KEY NOT NULL" + "," + COLUMN_GROUPNO + " INTEGER NOT NULL DEFAULT(0)" + "," + COLUMN_TIMESTAMP + " DATETIME UNIQUE NOT NULL" + "," + COLUMN_TAG + " TEXT" + "," + COLUMN_VALUE + " REAL NOT NULL" + "," + COLUMN_DEVICEID + " TEXT NOT NULL" + "," + COLUMN_NEW + " NUMERIC NOT NULL DEFAULT(1)" + " )"; Here is the index statement: String SQL_CREATE_INDEX_TIMESTAMP = "CREATE INDEX IF NOT EXISTS " + TABLE_A + "_" + COLUMN_TIMESTAMP + " ON " + TABLE_A + " (" + COLUMN_TIMESTAMP + ") "; I have defined the columns as well as the table name as String Constants. I am already experiencing significant slow down when retrieving this data from Table A. The problem is that when I retrieve data from this table, I first put it in an ArrayList and then I display it. Obviously, this is possibly the wrong way of doing things. I am trying to find a better way to approach this problem using a ContentProvider. But this is not the problem that bothers me. The problem is for some reason, it takes a lot longer to retrieve data from other tables which have only upto 12 records maximum. I see this delay increase as the number of records in Table A increase. This does not make any sense. I can understand the delay if I retrieve data from Table A, but why the delay in retrieving data from other tables. To clarify, I do not experience this delay if Table A is empty or has less than 3000 records. What could be the problem?

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  • JavaScript Data Binding Frameworks

    - by dwahlin
    Data binding is where it’s at now days when it comes to building client-centric Web applications. Developers experienced with desktop frameworks like WPF or web frameworks like ASP.NET, Silverlight, or others are used to being able to take model objects containing data and bind them to UI controls quickly and easily. When moving to client-side Web development the data binding story hasn’t been great since neither HTML nor JavaScript natively support data binding. This means that you have to write code to place data in a control and write code to extract it. Although it’s certainly feasible to do it from scratch (many of us have done it this way for years), it’s definitely tedious and not exactly the best solution when it comes to maintenance and re-use. Over the last few years several different script libraries have been released to simply the process of binding data to HTML controls. In fact, the subject of data binding is becoming so popular that it seems like a new script library is being released nearly every week. Many of the libraries provide MVC/MVVM pattern support in client-side JavaScript apps and some even integrate directly with server frameworks like Node.js. Here’s a quick list of a few of the available libraries that support data binding (if you like any others please add a comment and I’ll try to keep the list updated): AngularJS MVC framework for data binding (although closely follows the MVVM pattern). Backbone.js MVC framework with support for models, key/value binding, custom events, and more. Derby Provides a real-time environment that runs in the browser an in Node.js. The library supports data binding and templates. Ember Provides support for templates that automatically update as data changes. JsViews Data binding framework that provides “interactive data-driven views built on top of JsRender templates”. jQXB Expression Binder Lightweight jQuery plugin that supports bi-directional data binding support. KnockoutJS MVVM framework with robust support for data binding. For an excellent look at using KnockoutJS check out John Papa’s course on Pluralsight. Meteor End to end framework that uses Node.js on the server and provides support for data binding on  the client. Simpli5 JavaScript framework that provides support for two-way data binding. WinRT with HTML5/JavaScript If you’re building Windows 8 applications using HTML5 and JavaScript there’s built-in support for data binding in the WinJS library.   I won’t have time to write about each of these frameworks, but in the next post I’m going to talk about my (current) favorite when it comes to client-side JavaScript data binding libraries which is AngularJS. AngularJS provides an extremely clean way – in my opinion - to extend HTML syntax to support data binding while keeping model objects (the objects that hold the data) free from custom framework method calls or other weirdness. While I’m writing up the next post, feel free to visit the AngularJS developer guide if you’d like additional details about the API and want to get started using it.

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  • Protect Data and Save Money? Learn How Best-in-Class Organizations do Both

    - by roxana.bradescu
    Databases contain nearly two-thirds of the sensitive information that must be protected as part of any organization's overall approach to security, risk management, and compliance. Solutions for protecting data housed in databases vary from encrypting data at the application level to defense-in-depth protection of the database itself. So is there a difference? Absolutely! According to new research from the Aberdeen Group, Best-in-Class organizations experience fewer data breaches and audit deficiencies - at lower cost -- by deploying database security solutions. And the results are dramatic: Aberdeen found that organizations encrypting data within their databases achieved 30% fewer data breaches and 15% greater audit efficiency with 34% less total cost when compared to organizations encrypting data within applications. Join us for a live webcast with Derek Brink, Vice President and Research Fellow at the Aberdeen Group, next week to learn how your organization can become Best-in-Class.

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  • Bad Data is Really the Monster

    - by Dain C. Hansen
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Bad Data is really the monster – is an article written by Bikram Sinha who I borrowed the title and the inspiration for this blog. Sinha writes: “Bad or missing data makes application systems fail when they process order-level data. One of the key items in the supply-chain industry is the product (aka SKU). Therefore, it becomes the most important data element to tie up multiple merchandising processes including purchase order allocation, stock movement, shipping notifications, and inventory details… Bad data can cause huge operational failures and cost millions of dollars in terms of time, resources, and money to clean up and validate data across multiple participating systems. Yes bad data really is the monster, so what do we do about it? Close our eyes and hope it stays in the closet? We’ve tacked this problem for some years now at Oracle, and with our latest introduction of Oracle Enterprise Data Quality along with our integrated Oracle Master Data Management products provides a complete, best-in-class answer to the bad data monster. What’s unique about it? Oracle Enterprise Data Quality also combines powerful data profiling, cleansing, matching, and monitoring capabilities while offering unparalleled ease of use. What makes it unique is that it has dedicated capabilities to address the distinct challenges of both customer and product data quality – [different monsters have different needs of course!]. And the ability to profile data is just as important to identify and measure poor quality data and identify new rules and requirements. Included are semantic and pattern-based recognition to accurately parse and standardize data that is poorly structured. Finally all of the data quality components are integrated with Oracle Master Data Management, including Oracle Customer Hub and Oracle Product Hub, as well as Oracle Data Integrator Enterprise Edition and Oracle CRM. Want to learn more? On Tuesday Nov 15th, I invite you to listen to our webcast on Reduce ERP consolidation risks with Oracle Master Data Management I’ll be joined by our partner iGate Patni and be talking about one specific way to deal with the bad data monster specifically around ERP consolidation. Look forward to seeing you there!

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  • Where can I locate business data to use in my application?

    - by Aaron McIver
    This question talks about any and all free public raw data which appeared to have valuable pieces but nothing that really provides what I am looking for. Instead of using a socially defined listing of businesses (foursquare), I would like a business listing data set of registered businesses and associated addresses that could then be searchable based on location (coordinates). The critical need is that the data set should be filterable based on varying criteria (give me all restaurants, coffee shops, etc...). If the data is free that is great but anywhere that sells this type of data would also suffice. Infochimps looked like a possibility but perhaps something a bit more extensive exists. Where can I find a free or for fee data set of registered business that is filterable based on type of business and location?

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  • Exchange 2003 automatically converts text/plain emails to text/html for IMAP retrieval

    - by wfaulk
    When accessing an Exchange 2003 server via IMAP, emails that were sent as text/plain (and ones that had no MIME encoding specified at all) get automatically converted to multipart/alternative with the original text/plain body and a text/html body. This is … stupid. It doesn't even bother to specify a monospaced font. The new MIME part starts like this: Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2//EN"> <HTML> <HEAD> <META HTTP-EQUIV=3D"Content-Type" CONTENT=3D"text/html; = charset=3Diso-8859-1"> <META NAME=3D"Generator" CONTENT=3D"MS Exchange Server version = 6.5.7654.12"> <TITLE>{{subject}}</TITLE> </HEAD> <BODY> <!-- Converted from text/plain format --> <BR> <P><FONT SIZE=3D2>{{body}} (All the "3D" stuff is quoted-printable encoding for an equals sign; there's nothing wrong on that front, surprisingly.) How can I make this stop?

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  • Help with data retrieval MACRO

    - by Andrei Ciobanu
    Hello, given the following structure: struct nmslist_elem_s { nmptr data; struct nmslist_elem_s *next; }; typedef struct nmslist_elem_s nmslist_elem; Where: typedef void* nmptr; Is it possible to write a MACRO that retrieves the data from the element and cast it to the right type: MACRO(type, element) that expands to *((type*)element->data). For example for int, i would need something like this: *((int*)(element->data)) .

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  • Sybase PowerDesigner Change Many (Find/Replace/Convert) Data Item's Data Types

    - by Andy
    Hello, I have a relatively large Conceptual Data Model in PowerDesigner. After generating a Physical Data Model and seeing the DBMS data types, I need to update all of data types(NUMBER/TEXT) for each data item. I'd like to either do a find/replace within the Conceptual Data Model or somehow map to different data types when creating the Physical Data Model. Ex. Change the auto conversion of Text - Clob, to Text - NVARCHAR(20). Thanks!

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  • are there any useful datasets available on the web for data mining?

    - by niko
    Hi, Does anyone know any good resource where example (real) data can be downloaded for experimenting statistics and machine learning techniques such as decision trees etc? Currently I am studying machine learning techniques and it would be very helpful to have real data for evaluating the accuracy of various tools. If anyone knows any good resource (perhaps csv, xls files or any other format) I would be very thankful for a suggestion.

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  • Big Data: Size isn’t everything

    - by Simon Elliston Ball
    Big Data has a big problem; it’s the word “Big”. These days, a quick Google search will uncover terabytes of negative opinion about the futility of relying on huge volumes of data to produce magical, meaningful insight. There are also many clichéd but correct assertions about the difficulties of correlation versus causation, in massive data sets. In reading some of these pieces, I begin to understand how climatologists must feel when people complain ironically about “global warming” during snowfall. Big Data has a name problem. There is a lot more to it than size. Shape, Speed, and…err…Veracity are also key elements (now I understand why Gartner and the gang went with V’s instead of S’s). The need to handle data of different shapes (Variety) is not new. Data developers have always had to mold strange-shaped data into our reporting systems, integrating with semi-structured sources, and even straying into full-text searching. However, what we lacked was an easy way to add semi-structured and unstructured data to our arsenal. New “Big Data” tools such as MongoDB, and other NoSQL (Not Only SQL) databases, or a graph database like Neo4J, fill this gap. Still, to many, they simply introduce noise to the clean signal that is their sensibly normalized data structures. What about speed (Velocity)? It’s not just high frequency trading that generates data faster than a single system can handle. Many other applications need to make trade-offs that traditional databases won’t, in order to cope with high data insert speeds, or to extract quickly the required information from data streams. Unfortunately, many people equate Big Data with the Hadoop platform, whose batch driven queries and job processing queues have little to do with “velocity”. StreamInsight, Esper and Tibco BusinessEvents are examples of Big Data tools designed to handle high-velocity data streams. Again, the name doesn’t do the discipline of Big Data any favors. Ultimately, though, does analyzing fast moving data produce insights as useful as the ones we get through a more considered approach, enabled by traditional BI? Finally, we have Veracity and Value. In many ways, these additions to the classic Volume, Velocity and Variety trio acknowledge the criticism that without high-quality data and genuinely valuable outputs then data, big or otherwise, is worthless. As a discipline, Big Data has recognized this, and data quality and cleaning tools are starting to appear to support it. Rather than simply decrying the irrelevance of Volume, we need as a profession to focus how to improve Veracity and Value. Perhaps we should just declare the ‘Big’ silent, embrace these new data tools and help develop better practices for their use, just as we did the good old RDBMS? What does Big Data mean to you? Which V gives your business the most pain, or the most value? Do you see these new tools as a useful addition to the BI toolbox, or are they just enabling a dangerous trend to find ghosts in the noise?

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  • Know your Data Lineage

    - by Simon Elliston Ball
    An academic paper without the footnotes isn’t an academic paper. Journalists wouldn’t base a news article on facts that they can’t verify. So why would anyone publish reports without being able to say where the data has come from and be confident of its quality, in other words, without knowing its lineage. (sometimes referred to as ‘provenance’ or ‘pedigree’) The number and variety of data sources, both traditional and new, increases inexorably. Data comes clean or dirty, processed or raw, unimpeachable or entirely fabricated. On its journey to our report, from its source, the data can travel through a network of interconnected pipes, passing through numerous distinct systems, each managed by different people. At each point along the pipeline, it can be changed, filtered, aggregated and combined. When the data finally emerges, how can we be sure that it is right? How can we be certain that no part of the data collection was based on incorrect assumptions, that key data points haven’t been left out, or that the sources are good? Even when we’re using data science to give us an approximate or probable answer, we cannot have any confidence in the results without confidence in the data from which it came. You need to know what has been done to your data, where it came from, and who is responsible for each stage of the analysis. This information represents your data lineage; it is your stack-trace. If you’re an analyst, suspicious of a number, it tells you why the number is there and how it got there. If you’re a developer, working on a pipeline, it provides the context you need to track down the bug. If you’re a manager, or an auditor, it lets you know the right things are being done. Lineage tracking is part of good data governance. Most audit and lineage systems require you to buy into their whole structure. If you are using Hadoop for your data storage and processing, then tools like Falcon allow you to track lineage, as long as you are using Falcon to write and run the pipeline. It can mean learning a new way of running your jobs (or using some sort of proxy), and even a distinct way of writing your queries. Other Hadoop tools provide a lot of operational and audit information, spread throughout the many logs produced by Hive, Sqoop, MapReduce and all the various moving parts that make up the eco-system. To get a full picture of what’s going on in your Hadoop system you need to capture both Falcon lineage and the data-exhaust of other tools that Falcon can’t orchestrate. However, the problem is bigger even that that. Often, Hadoop is just one piece in a larger processing workflow. The next step of the challenge is how you bind together the lineage metadata describing what happened before and after Hadoop, where ‘after’ could be  a data analysis environment like R, an application, or even directly into an end-user tool such as Tableau or Excel. One possibility is to push as much as you can of your key analytics into Hadoop, but would you give up the power, and familiarity of your existing tools in return for a reliable way of tracking lineage? Lineage and auditing should work consistently, automatically and quietly, allowing users to access their data with any tool they require to use. The real solution, therefore, is to create a consistent method by which to bring lineage data from these data various disparate sources into the data analysis platform that you use, rather than being forced to use the tool that manages the pipeline for the lineage and a different tool for the data analysis. The key is to keep your logs, keep your audit data, from every source, bring them together and use the data analysis tools to trace the paths from raw data to the answer that data analysis provides.

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  • NSURLConnection receives data even if no data was thrown back

    - by Anna Fortuna
    Let me explain my situation. Currently, I am experimenting long-polling using NSURLConnection. I found this and I decided to try it. What I do is send a request to the server with a timeout interval of 300 secs. (or 5 mins.) Here is a code snippet: NSURL *url = [NSURL URLWithString:urlString]; NSURLRequest *request = [NSURLRequest requestWithURL:url cachePolicy:NSURLCacheStorageAllowedInMemoryOnly timeoutInterval:300]; NSData *data = [NSURLConnection sendSynchronousRequest:request returningResponse:&resp error:&err]; Now I want to test if the connection will "hold" the request if no data was thrown back from the server, so what I did was this: if (data != nil) [self performSelectorOnMainThread:@selector(dataReceived:) withObject:data waitUntilDone:YES]; And the function dataReceived: looks like this: - (void)dataReceived:(NSData *)data { NSLog(@"DATA RECEIVED!"); NSString *string = [NSString stringWithUTF8String:[data bytes]]; NSLog(@"THE DATA: %@", string); } Server-side, I created a function that will return a data once it fits the arguments and returns none if nothing fits. Here is a snippet of the PHP function: function retrieveMessages($vardata) { if (!empty($vardata)) { $result = check_data($vardata) //check_data is the function which returns 1 if $vardata //fits the arguments, and 0 if it fails to fit if ($result == 1) { $jsonArray = array('Data' => $vardata); echo json_encode($jsonArray); } } } As you can see, the function will only return data if the $result is equal to 1. However, even if the function returns nothing, NSURLConnection will still perform the function dataReceived: meaning the NSURLConnection still receives data, albeit an empty one. So can anyone help me here? How will I perform long-polling using NSURLConnection? Basically, I want to maintain the connection as long as no data is returned. So how will I do it? NOTE: I am new to PHP, so if my code is wrong, please point it out so I can correct it.

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