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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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  • How do I tweak columns in a Flat File Destination in SSIS?

    - by theog
    I have an OLE DB Data source and a Flat File Destination in the Data Flow of my SSIS Project. The goal is simply to pump data into a text file, and it does that. Where I'm having problems is with the formatting. I need to be able to rtrim() a couple of columns to remove trailing spaces, and I have a couple more that need their leading zeros preserved. The current process is losing all the leading zeros. The rtrim() can be done by simple truncation and ignoring the truncation errors, but that's very inelegant and error prone. I'd like to find a better way, like actually doing the rtrim() function where needed. Exploring similar SSIS questions & answers on SO, the thing to do seems to be "Use a Script Task", but that's ususally just thrown out there with no details, and it's not at all an intuitive thing to set up. I don't see how to use scripting to do what I need. Do I use a Script Task on the Control Flow, or a Script Component in the Data Flow? Can I do rtrim() and pad strings where needed in a script? Anybody got an example of doing this or similar things? Many thanks in advance.

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  • What's the best way to parse an Address field using t-sql or SSIS?

    - by dtaylo04
    I have a data set that I import into a SQL table every night. One field is 'Address_3' and contains the City, State, Zip and Country fields. However, this data isn't standardized. How can I best parse the data that is currently going into 1 field into individual fields. Here are some examples of the data I might receive: 'INDIANAPOLIS, IN 46268 US' 'INDIANAPOLIS, IN 46268-1234 US' 'INDIANAPOLIS, IN 46268-1234' 'INDIANAPOLIS, IN 46268' Thanks in advance! David

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  • Investigation: Can different combinations of components effect Dataflow performance?

    - by jamiet
    Introduction The Dataflow task is one of the core components (if not the core component) of SQL Server Integration Services (SSIS) and often the most misunderstood. This is not surprising, its an incredibly complicated beast and we’re abstracted away from that complexity via some boxes that go yellow red or green and that have some lines drawn between them. Example dataflow In this blog post I intend to look under that facade and get into some of the nuts and bolts of the Dataflow Task by investigating how the decisions we make when building our packages can affect performance. I will do this by comparing the performance of three dataflows that all have the same input, all produce the same output, but which all operate slightly differently by way of having different transformation components. I also want to use this blog post to challenge a common held opinion that I see perpetuated over and over again on the SSIS forum. That is, that people assume adding components to a dataflow will be detrimental to overall performance. Its not surprising that people think this –it is intuitive to think that more components means more work- however this is not a view that I share. I have always been of the opinion that there are many factors affecting dataflow duration and the number of components is actually one of the less important ones; having said that I have never proven that assertion and that is one reason for this investigation. I have actually seen evidence that some people think dataflow duration is simply a function of number of rows and number of components. I’ll happily call that one out as a myth even without any investigation!  The Setup I have a 2GB datafile which is a list of 4731904 (~4.7million) customer records with various attributes against them and it contains 2 columns that I am going to use for categorisation: [YearlyIncome] [BirthDate] The data file is a SSIS raw format file which I chose to use because it is the quickest way of getting data into a dataflow and given that I am testing the transformations, not the source or destination adapters, I want to minimise external influences as much as possible. In the test I will split the customers according to month of birth (12 of those) and whether or not their yearly income is above or below 50000 (2 of those); in other words I will be splitting them into 24 discrete categories and in order to do it I shall be using different combinations of SSIS’ Conditional Split and Derived Column transformation components. The 24 datapaths that occur will each input to a rowcount component, again because this is the least resource intensive means of terminating a datapath. The test is being carried out on a Dell XPS Studio laptop with a quad core (8 logical Procs) Intel Core i7 at 1.73GHz and Samsung SSD hard drive. Its running SQL Server 2008 R2 on Windows 7. The Variables Here are the three combinations of components that I am going to test:     One Conditional Split - A single Conditional Split component CSPL Split by Month of Birth and income category that will use expressions on [YearlyIncome] & [BirthDate] to send each row to one of 24 outputs. This next screenshot displays the expression logic in use: Derived Column & Conditional Split - A Derived Column component DER Income Category that adds a new column [IncomeCategory] which will contain one of two possible text values {“LessThan50000”,”GreaterThan50000”} and uses [YearlyIncome] to determine which value each row should get. A Conditional Split component CSPL Split by Month of Birth and Income Category then uses that new column in conjunction with [BirthDate] to determine which of the same 24 outputs to send each row to. Put more simply, I am separating the Conditional Split of #1 into a Derived Column and a Conditional Split. The next screenshots display the expression logic in use: DER Income Category         CSPL Split by Month of Birth and Income Category       Three Conditional Splits - A Conditional Split component that produces two outputs based on [YearlyIncome], one for each Income Category. Each of those outputs will go to a further Conditional Split that splits the input into 12 outputs, one for each month of birth (identical logic in each). In this case then I am separating the single Conditional Split of #1 into three Conditional Split components. The next screenshots display the expression logic in use: CSPL Split by Income Category         CSPL Split by Month of Birth 1& 2       Each of these combinations will provide an input to one of the 24 rowcount components, just the same as before. For illustration here is a screenshot of the dataflow containing three Conditional Split components: As you can these dataflows have a fair bit of work to do and remember that they’re doing that work for 4.7million rows. I will execute each dataflow 10 times and use the average for comparison. I foresee three possible outcomes: The dataflow containing just one Conditional Split (i.e. #1) will be quicker There is no significant difference between any of them One of the two dataflows containing multiple transformation components will be quicker Regardless of which of those outcomes come to pass we will have learnt something and that makes this an interesting test to carry out. Note that I will be executing the dataflows using dtexec.exe rather than hitting F5 within BIDS. The Results and Analysis The table below shows all of the executions, 10 for each dataflow. It also shows the average for each along with a standard deviation. All durations are in seconds. I’m pasting a screenshot because I frankly can’t be bothered with the faffing about needed to make a presentable HTML table. It is plain to see from the average that the dataflow containing three conditional splits is significantly faster, the other two taking 43% and 52% longer respectively. This seems strange though, right? Why does the dataflow containing the most components outperform the other two by such a big margin? The answer is actually quite logical when you put some thought into it and I’ll explain that below. Before progressing, a side note. The standard deviation for the “Three Conditional Splits” dataflow is orders of magnitude smaller – indicating that performance for this dataflow can be predicted with much greater confidence too. The Explanation I refer you to the screenshot above that shows how CSPL Split by Month of Birth and salary category in the first dataflow is setup. Observe that there is a case for each combination of Month Of Date and Income Category – 24 in total. These expressions get evaluated in the order that they appear and hence if we assume that Month of Date and Income Category are uniformly distributed in the dataset we can deduce that the expected number of expression evaluations for each row is 12.5 i.e. 1 (the minimum) + 24 (the maximum) divided by 2 = 12.5. Now take a look at the screenshots for the second dataflow. We are doing one expression evaluation in DER Income Category and we have the same 24 cases in CSPL Split by Month of Birth and Income Category as we had before, only the expression differs slightly. In this case then we have 1 + 12.5 = 13.5 expected evaluations for each row – that would account for the slightly longer average execution time for this dataflow. Now onto the third dataflow, the quick one. CSPL Split by Income Category does a maximum of 2 expression evaluations thus the expected number of evaluations per row is 1.5. CSPL Split by Month of Birth 1 & CSPL Split by Month of Birth 2 both have less work to do than the previous Conditional Split components because they only have 12 cases to test for thus the expected number of expression evaluations is 6.5 There are two of them so total expected number of expression evaluations for this dataflow is 6.5 + 6.5 + 1.5 = 14.5. 14.5 is still more than 12.5 & 13.5 though so why is the third dataflow so much quicker? Simple, the conditional expressions in the first two dataflows have two boolean predicates to evaluate – one for Income Category and one for Month of Birth; the expressions in the Conditional Split in the third dataflow however only have one predicate thus they are doing a lot less work. To sum up, the difference in execution times can be attributed to the difference between: MONTH(BirthDate) == 1 && YearlyIncome <= 50000 and MONTH(BirthDate) == 1 In the first two dataflows YearlyIncome <= 50000 gets evaluated an average of 12.5 times for every row whereas in the third dataflow it is evaluated once and once only. Multiply those 11.5 extra operations by 4.7million rows and you get a significant amount of extra CPU cycles – that’s where our duration difference comes from. The Wrap-up The obvious point here is that adding new components to a dataflow isn’t necessarily going to make it go any slower, moreover you may be able to achieve significant improvements by splitting logic over multiple components rather than one. Performance tuning is all about reducing the amount of work that needs to be done and that doesn’t necessarily mean use less components, indeed sometimes you may be able to reduce workload in ways that aren’t immediately obvious as I think I have proven here. Of course there are many variables in play here and your mileage will most definitely vary. I encourage you to download the package and see if you get similar results – let me know in the comments. The package contains all three dataflows plus a fourth dataflow that will create the 2GB raw file for you (you will also need the [AdventureWorksDW2008] sample database from which to source the data); simply disable all dataflows except the one you want to test before executing the package and remember, execute using dtexec, not within BIDS. If you want to explore dataflow performance tuning in more detail then here are some links you might want to check out: Inequality joins, Asynchronous transformations and Lookups Destination Adapter Comparison Don’t turn the dataflow into a cursor SSIS Dataflow – Designing for performance (webinar) Any comments? Let me know! @Jamiet

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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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  • SSIS 2008 Import and Export Wizard and Excel-based Data

    Even though the Import and Export Wizard, incorporated into the SQL Server 2008 platform, greatly simplifies the creation of SQL Server Integration Services packages, it has its limitations. This article points out the primary challenges associated with using it to copy data between SQL Server 2008 and Excel and presents methods of addressing these challenges.

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  • Achieve Spatial Data Support in SSIS

    Overview SQL Server 2008 introduced a new category of datatypes known as spatial datatypes which stores spatial information. The new spatial datatypes are geography and geometry. SQL Server Management Studio comes with good good support for these spatial data ... [Read Full Article]

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  • Presenting to the New England SQL Server Users Group 10 Jun 2010!

    - by andyleonard
    I am honored to present Applied SSIS Design Patterns to the New England SQL Server Users Group on 10 Jun 2010! This is a reprise of the spotlight session presented at the PASS Summit 2009. Abstract "Design Patterns" is more than a trendy buzz phrase; design patterns are a way of breaking down complex development projects into manageable tasks. They lend themselves to several development methodologies and apply to SSIS development. Chances are you're using your own design patterns now! In this spotlight...(read more)

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  • Upgrading SSIS Custom Components for SQL Server 2012

    Having finally got around to upgrading my custom components to SQL Server 2012, I thought I’d share some notes on the process. One of the goals was minimal duplication, so the same code files are used to build the 2008 and 2012 components, I just have a separate project file. What can SQL Monitor 3.2 monitor?Whatever you think is most important. Use custom metrics to monitor and alert on data that's most important for your environment. Find out more.

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  • Sorting data in the SSIS Pipeline (Video)

    In this post I want to show a couple of ways to order the data that comes into the pipeline. a number of people have asked me about this primarily because there are a number of ways to do it but also because some components in the pipeline take sorted inputs. One of the methods I show is visually easy to understand and the other is less visual but potentially more performant.

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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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  • SSIS- Sharepoint list data transfer issue

    - by Vicky
    Hi , We are trying to transfer data from oracle database (about 60,0000) records only to a sharepoint list using SSIS. But we are getting following error when records reaches around 19000 . The attempt to add a row to the Data Flow task buffer failed with error code 0xC0047020 and System.ServiceModel.ProtocolException: The remote server returned an unexpected response: (400) Bad Request. Earlier we thought if could because of Sharepoint list limit so we tried by reducing two of the columns and then it has went fine. So we left with one of the column of Datatype DT_STR and length 400 in oracle beacuse of which issue might be happening, It is mapped to sharepoint custom list field of multiline type. We also verified if length of field is issue but in oracle DB for all records max length for this column is only 239 so length issue is also ruled out. Any one who has faced this kind of issue or knows cause of this issue.Kindly let us know.. Thanks and regards, Vicky

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  • Upgrading SSIS Custom Components for SQL Server 2012

    Having finally got around to upgrading my custom components to SQL Server 2012, I thought I’d share some notes on the process. One of the goals was minimal duplication, so the same code files are used to build the 2008 and 2012 components, I just have a separate project file. The high level steps are listed below, followed by some more details. Create a 2012 copy of the project file Upgrade project, just open the new project file is VS2010 Change target framework to .NET 4.0 Set conditional compilation symbol for DENALI Change any conditional code, including assembly version and UI type name Edit project file to change referenced assemblies for 2012 Change target framework to .NET 4.0 Open the project properties. On the Applications page, change the Target framework to .NET Framework 4. Set conditional compilation symbol for DENALI Re-open the project properties. On the Build tab, first change the Configuration to All Configurations, then set a Conditional compilation symbol of DENALI. Change any conditional code, including assembly version and UI type name The value doesn’t have to be DENALI, it can actually be anything you like, that is just what I use. It is how I control sections of code that vary between versions. There were several API changes between 2005 and 2008, as well as interface name changes. Whilst we don’t have the same issues between 2008 and 2012, I still have some sections of code that do change such as the assembly attributes. #if DENALI [assembly: AssemblyDescription("Data Generator Source for SQL Server Integration Services 2012")] [assembly: AssemblyCopyright("Copyright © 2012 Konesans Ltd")] [assembly: AssemblyVersion("3.0.0.0")] #else [assembly: AssemblyDescription("Data Generator Source for SQL Server Integration Services 2008")] [assembly: AssemblyCopyright("Copyright © 2008 Konesans Ltd")] [assembly: AssemblyVersion("2.0.0.0")] #endif The Visual Studio editor automatically formats the code based on the current compilation symbols, hence in this case the 2008 code is grey to indicate it is disabled. As you can see in the previous example I have distinct assembly version attributes, ensuring I can run both 2008 and 2012 versions of my component side by side. For custom components with a user interface, be sure to update the UITypeName property of the DtsTask or DtsPipelineComponent attributes. As above I use the conditional compilation symbol to control the code. #if DENALI [DtsTask ( DisplayName = "File Watcher Task", Description = "File Watcher Task", IconResource = "Konesans.Dts.Tasks.FileWatcherTask.FileWatcherTask.ico", UITypeName = "Konesans.Dts.Tasks.FileWatcherTask.FileWatcherTaskUI,Konesans.Dts.Tasks.FileWatcherTask,Version=3.0.0.0,Culture=Neutral,PublicKeyToken=b2ab4a111192992b", TaskContact = "File Watcher Task; Konesans Ltd; Copyright © 2012 Konesans Ltd; http://www.konesans.com" )] #else [DtsTask ( DisplayName = "File Watcher Task", Description = "File Watcher Task", IconResource = "Konesans.Dts.Tasks.FileWatcherTask.FileWatcherTask.ico", UITypeName = "Konesans.Dts.Tasks.FileWatcherTask.FileWatcherTaskUI,Konesans.Dts.Tasks.FileWatcherTask,Version=2.0.0.0,Culture=Neutral,PublicKeyToken=b2ab4a111192992b", TaskContact = "File Watcher Task; Konesans Ltd; Copyright © 2004-2008 Konesans Ltd; http://www.konesans.com" )] #endif public sealed class FileWatcherTask: Task, IDTSComponentPersist, IDTSBreakpointSite, IDTSSuspend { // .. code goes on... } Shown below is another example I found that needed changing. I borrow one of the MS editors, and use it against a custom property, but need to ensure I reference the correct version of the MS controls assembly. This section of code is actually shared between the 2005, 2008 and 2012 versions of my component hence it has test for both DENALI and KATMAI symbols. #if DENALI const string multiLineUI = "Microsoft.DataTransformationServices.Controls.ModalMultilineStringEditor, Microsoft.DataTransformationServices.Controls, Version=11.0.00.0, Culture=neutral, PublicKeyToken=89845dcd8080cc91"; #elif KATMAI const string multiLineUI = "Microsoft.DataTransformationServices.Controls.ModalMultilineStringEditor, Microsoft.DataTransformationServices.Controls, Version=10.0.0.0, Culture=neutral, PublicKeyToken=89845dcd8080cc91"; #else const string multiLineUI = "Microsoft.DataTransformationServices.Controls.ModalMultilineStringEditor, Microsoft.DataTransformationServices.Controls, Version=9.0.242.0, Culture=neutral, PublicKeyToken=89845dcd8080cc91"; #endif // Create Match Expression parameter IDTSCustomPropertyCollection100 propertyCollection = outputColumn.CustomPropertyCollection; IDTSCustomProperty100 property = propertyCollection.New(); property = propertyCollection.New(); property.Name = MatchParams.Name; property.Description = MatchParams.Description; property.TypeConverter = typeof(MultilineStringConverter).AssemblyQualifiedName; property.UITypeEditor = multiLineUI; property.Value = MatchParams.DefaultValue; Edit project file to change referenced assemblies for 2012 We now need to edit the project file itself. Open the MyComponente2012.cproj  in you favourite text editor, and then perform a couple of find and replaces as listed below: Find Replace Comment Version=10.0.0.0, Culture=neutral, PublicKeyToken=89845dcd8080cc91 Version=11.0.0.0, Culture=neutral, PublicKeyToken=89845dcd8080cc91 Change the assembly references version from SQL Server 2008 to SQL Server 2012. Microsoft SQL Server\100\ Microsoft SQL Server\110\ Change any assembly reference hint path locations from from SQL Server 2008 to SQL Server 2012. If you use any Build Events during development, such as copying the component assembly to the DTS folder, or calling GACUTIL to install it into the GAC, you can also change these now. An example of my new post-build event for a pipeline component is shown below, which uses the .NET 4.0 path for GACUTIL. It also uses the 110 folder location, instead of 100 for SQL Server 2008, but that was covered the the previous find and replace. "C:\Program Files (x86)\Microsoft SDKs\Windows\v7.0A\Bin\NETFX 4.0 Tools\gacutil.exe" /if "$(TargetPath)" copy "$(TargetPath)" "%ProgramFiles%\Microsoft SQL Server\110\DTS\PipelineComponents" /Y

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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. 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