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  • NHibernate Pitfalls: Custom Types and Detecting Changes

    - by Ricardo Peres
    This is part of a series of posts about NHibernate Pitfalls. See the entire collection here. NHibernate supports the declaration of properties of user-defined types, that is, not entities, collections or primitive types. These are used for mapping a database columns, of any type, into a different type, which may not even be an entity; think, for example, of a custom user type that converts a BLOB column into an Image. User types must implement interface NHibernate.UserTypes.IUserType. This interface specifies an Equals method that is used for comparing two instances of the user type. If this method returns false, the entity is marked as dirty, and, when the session is flushed, will trigger an UPDATE. So, in your custom user type, you must implement this carefully so that it is not mistakenly considered changed. For example, you can cache the original column value inside of it, and compare it with the one in the other instance. Let’s see an example implementation of a custom user type that converts a Byte[] from a BLOB column into an Image: 1: [Serializable] 2: public sealed class ImageUserType : IUserType 3: { 4: private Byte[] data = null; 5: 6: public ImageUserType() 7: { 8: this.ImageFormat = ImageFormat.Png; 9: } 10: 11: public ImageFormat ImageFormat 12: { 13: get; 14: set; 15: } 16: 17: public Boolean IsMutable 18: { 19: get 20: { 21: return (true); 22: } 23: } 24: 25: public Object Assemble(Object cached, Object owner) 26: { 27: return (cached); 28: } 29: 30: public Object DeepCopy(Object value) 31: { 32: return (value); 33: } 34: 35: public Object Disassemble(Object value) 36: { 37: return (value); 38: } 39: 40: public new Boolean Equals(Object x, Object y) 41: { 42: return (Object.Equals(x, y)); 43: } 44: 45: public Int32 GetHashCode(Object x) 46: { 47: return ((x != null) ? x.GetHashCode() : 0); 48: } 49: 50: public override Int32 GetHashCode() 51: { 52: return ((this.data != null) ? this.data.GetHashCode() : 0); 53: } 54: 55: public override Boolean Equals(Object obj) 56: { 57: ImageUserType other = obj as ImageUserType; 58: 59: if (other == null) 60: { 61: return (false); 62: } 63: 64: if (Object.ReferenceEquals(this, other) == true) 65: { 66: return (true); 67: } 68: 69: return (this.data.SequenceEqual(other.data)); 70: } 71: 72: public Object NullSafeGet(IDataReader rs, String[] names, Object owner) 73: { 74: Int32 index = rs.GetOrdinal(names[0]); 75: Byte[] data = rs.GetValue(index) as Byte[]; 76: 77: this.data = data as Byte[]; 78: 79: if (data == null) 80: { 81: return (null); 82: } 83: 84: using (MemoryStream stream = new MemoryStream(this.data ?? new Byte[0])) 85: { 86: return (Image.FromStream(stream)); 87: } 88: } 89: 90: public void NullSafeSet(IDbCommand cmd, Object value, Int32 index) 91: { 92: if (value != null) 93: { 94: Image data = value as Image; 95: 96: using (MemoryStream stream = new MemoryStream()) 97: { 98: data.Save(stream, this.ImageFormat); 99: value = stream.ToArray(); 100: } 101: } 102: 103: (cmd.Parameters[index] as DbParameter).Value = value ?? DBNull.Value; 104: } 105: 106: public Object Replace(Object original, Object target, Object owner) 107: { 108: return (original); 109: } 110: 111: public Type ReturnedType 112: { 113: get 114: { 115: return (typeof(Image)); 116: } 117: } 118: 119: public SqlType[] SqlTypes 120: { 121: get 122: { 123: return (new SqlType[] { new SqlType(DbType.Binary) }); 124: } 125: } 126: } In this case, we need to cache the original Byte[] data because it’s not easy to compare two Image instances, unless, of course, they are the same.

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  • 100,000 complex structures that are accessed frequently by 100,000 users

    - by Saad
    If you are required to store 100,000 complex structures that are accessed frequently by 100,000 users, which of the following solutions would you use and why? Memcached, In-code python objects, Redis, or a relational database (MySQL). With the little knowledge that I have I think that memcached and In-code python object will not store permanent persistent data. so they don't qualify as the right answer for such a problem. And for complex data structures its best to use Redis. Please correct me if I am wrong.

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  • Sales tracker that allows complex queries?

    - by feklee
    On a site, every click on a product should be registered by a sales tracker: price, type, etc. The sales tracker should provide an API so that complex queries can be performed, such as: Which products of a type "teapot" had a price below 20 EUR? Requirements: Recorded data should be available for querying no later than two hours after it has been recorded. For example, there are reports that Google Analytics may take up to 24h to update data. That is not acceptable. Querying doesn't need to be fast, but recording does (of course). Which sales tracker allows complex queries against collected data?

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  • Data access pattern

    - by andlju
    I need some advice on what kind of pattern(s) I should use for pushing/pulling data into my application. I'm writing a rule-engine that needs to hold quite a large amount of data in-memory in order to be efficient enough. I have some rather conflicting requirements; It is not acceptable for the engine to always have to wait for a full pre-load of all data before it is functional. Only fetching and caching data on-demand will lead to the engine taking too long before it is running quickly enough. An external event can trigger the need for specific parts of the data to be reloaded. Basically, I think I need a combination of pushing and pulling data into the application. A simplified version of my current "pattern" looks like this (in psuedo-C# written in notepad): // This interface is implemented by all classes that needs the data interface IDataSubscriber { void RegisterData(Entity data); } // This interface is implemented by the data access class interface IDataProvider { void EnsureLoaded(Key dataKey); void RegisterSubscriber(IDataSubscriber subscriber); } class MyClassThatNeedsData : IDataSubscriber { IDataProvider _provider; MyClassThatNeedsData(IDataProvider provider) { _provider = provider; _provider.RegisterSubscriber(this); } public void RegisterData(Entity data) { // Save data for later StoreDataInCache(data); } void UseData(Key key) { // Make sure that the data has been stored in cache _provider.EnsureLoaded(key); Entity data = GetDataFromCache(key); } } class MyDataProvider : IDataProvider { List<IDataSubscriber> _subscribers; // Make sure that the data for key has been loaded to all subscribers public void EnsureLoaded(Key key) { if (HasKeyBeenMarkedAsLoaded(key)) return; PublishDataToSubscribers(key); MarkKeyAsLoaded(key); } // Force all subscribers to get a new version of the data for key public void ForceReload(Key key) { PublishDataToSubscribers(key); MarkKeyAsLoaded(key); } void PublishDataToSubscribers(Key key) { Entity data = FetchDataFromStore(key); foreach(var subscriber in _subscribers) { subscriber.RegisterData(data); } } } // This class will be spun off on startup and should make sure that all data is // preloaded as quickly as possible class MyPreloadingThread { IDataProvider _provider; MyPreloadingThread(IDataProvider provider) { _provider = provider; } void RunInBackground() { IEnumerable<Key> allKeys = GetAllKeys(); foreach(var key in allKeys) { _provider.EnsureLoaded(key); } } } I have a feeling though that this is not necessarily the best way of doing this.. Just the fact that explaining it seems to take two pages feels like an indication.. Any ideas? Any patterns out there I should have a look at?

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  • Using non primitive types in ServiceOperation for WCF Data Service (3.5SP1)

    - by Nix
    Is there any way at all to create a "mock" entity type for use in a WCF Service Operation? We have some queries we do that we need to optimize by exposing as a ServiceOperation. The problem is in order to do so we would result in a very long list of primitative types... Ex SomeoneHelpMe(int time, string name, string address, string i, string purple, string foo, int stillGoing, int tooMany, etc...) And we really need to reduce this to SomeoneHelpedMe(CustomEntityNotMappedToAnything e) This would also help us when it comes time to write some complex queries since there is a 3 param limitation... I saw this will be possible in 4.0 using "complex types", but i am still in the 3.5SP1 world. Let me know if anyone needs more information.

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  • Data access pattern, combining push and pull?

    - by andlju
    I need some advice on what kind of pattern(s) I should use for pushing/pulling data into my application. I'm writing a rule-engine that needs to hold quite a large amount of data in-memory in order to be efficient enough. I have some rather conflicting requirements; It is not acceptable for the engine to always have to wait for a full pre-load of all data before it is functional. Only fetching and caching data on-demand will lead to the engine taking too long before it is running quickly enough. An external event can trigger the need for specific parts of the data to be reloaded. Basically, I think I need a combination of pushing and pulling data into the application. A simplified version of my current "pattern" looks like this (in psuedo-C# written in notepad): // This interface is implemented by all classes that needs the data interface IDataSubscriber { void RegisterData(Entity data); } // This interface is implemented by the data access class interface IDataProvider { void EnsureLoaded(Key dataKey); void RegisterSubscriber(IDataSubscriber subscriber); } class MyClassThatNeedsData : IDataSubscriber { IDataProvider _provider; MyClassThatNeedsData(IDataProvider provider) { _provider = provider; _provider.RegisterSubscriber(this); } public void RegisterData(Entity data) { // Save data for later StoreDataInCache(data); } void UseData(Key key) { // Make sure that the data has been stored in cache _provider.EnsureLoaded(key); Entity data = GetDataFromCache(key); } } class MyDataProvider : IDataProvider { List<IDataSubscriber> _subscribers; // Make sure that the data for key has been loaded to all subscribers public void EnsureLoaded(Key key) { if (HasKeyBeenMarkedAsLoaded(key)) return; PublishDataToSubscribers(key); MarkKeyAsLoaded(key); } // Force all subscribers to get a new version of the data for key public void ForceReload(Key key) { PublishDataToSubscribers(key); MarkKeyAsLoaded(key); } void PublishDataToSubscribers(Key key) { Entity data = FetchDataFromStore(key); foreach(var subscriber in _subscribers) { subscriber.RegisterData(data); } } } // This class will be spun off on startup and should make sure that all data is // preloaded as quickly as possible class MyPreloadingThread { IDataProvider _provider; MyPreloadingThread(IDataProvider provider) { _provider = provider; } void RunInBackground() { IEnumerable<Key> allKeys = GetAllKeys(); foreach(var key in allKeys) { _provider.EnsureLoaded(key); } } } I have a feeling though that this is not necessarily the best way of doing this.. Just the fact that explaining it seems to take two pages feels like an indication.. Any ideas? Any patterns out there I should have a look at?

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  • Import csv data (SDK iphone)

    - by Ni
    I am new to cocoa. I have been working on these stuff for a few days. For the following code, i can read all the data in the string, and successfully get the data for plot. NSMutableArray *contentArray = [NSMutableArray array]; NSString *filePath = @"995,995,995,995,995,995,995,995,1000,997,995,994,992,993,992,989,988,987,990,993,989"; NSArray *myText = [filePath componentsSeparatedByString:@","]; NSInteger idx; for (idx = 0; idx < myText.count; idx++) { NSString *data =[myText objectAtIndex:idx]; NSLog(@"%@", data); id x = [NSNumber numberWithFloat:0+idx*0.002777778]; id y = [NSDecimalNumber decimalNumberWithString:data]; [contentArray addObject: [NSMutableDictionary dictionaryWithObjectsAndKeys:x, @"x", y, @"y", nil]]; } self.dataForPlot = contentArray; then, i try to load the data from csv file. the data in Data.csv file has the same value and the same format as 995,995,995,995,995,995,995,995,1000,997,995,994,992,993,992,989,988,987,990,993,989. I run the code, it is supposed to give the same graph output. however, it seems that the data is not loaded from csv file successfully. i can not figure out what's wrong with my code. NSMutableArray *contentArray = [NSMutableArray array]; NSString *filePath = [[NSBundle mainBundle] pathForResource:@"Data" ofType:@"csv"]; NSString *Data = [NSString stringWithContentsOfFile:filePath encoding:NSUTF8StringEncoding error:nil ]; if (Data) { NSArray *myText = [Data componentsSeparatedByString:@","]; NSInteger idx; for (idx = 0; idx < myText.count; idx++) { NSString *data =[myText objectAtIndex:idx]; NSLog(@"%@", data); id x = [NSNumber numberWithFloat:0+idx*0.002777778]; id y = [NSDecimalNumber decimalNumberWithString:data]; [contentArray addObject: [NSMutableDictionary dictionaryWithObjectsAndKeys:x, @"x", y, @"y",nil]]; } self.dataForPlot = contentArray; } The only difference is NSString *filePath = [[NSBundle mainBundle] pathForResource:@"Data" ofType:@"csv"]; NSString *Data = [NSString stringWithContentsOfFile:filePath encoding:NSUTF8StringEncoding error:nil ]; if (data){ } did i do anything wrong here?? Thanks for your help!!!!

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  • POST data not being received

    - by Alexander
    I've got an iPhone App that is supposed to send POST data to my server to register the device in a MySQL database so we can send notifications etc... to it. It sends it's unique identifier, device name, token, and a few other small things like passwords and usernames as a POST request to our server. The problem is that sometimes the server doesn't receive the data. And by this I mean, its not just receiving blank values for the POST inputs but, its not receiving ANY post data at all. I am logging all POST inputs to my server into some log files and when the script that relies on the POST data from the device fails (detects no data) I notice that its because NO POST data was sent. Is this a problem on the server, like refusing data or something or does this have to be on the client's side? What could be causing this?

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  • OBIEE 11.1.1 - Disable Wrap Data Types in WebLogic Server 10.3.x

    - by Ahmed Awan
    By default, JDBC data type’s objects are wrapped with a WebLogic wrapper. This allows for features like debugging output and track connection usage to be done by the server. The wrapping can be turned off by setting this value to false. This improves performance, in some cases significantly, and allows for the application to use the native driver objects directly. Tip: How to Disable Wrapping in WLS Administration Console You can use the Administration Console to disable data type wrapping for following JDBC data sources in bifoundation_domain domain: Data Source Name bip_datasource mds-owsm EPMSystemRegistry   To disable wrapping for each JDBC data source (as stated in above table): 1.     If you have not already done so, in the Change Center of the Administration Console, click Lock & Edit. 2.     In the Domain Structure tree, expand Services, then select Data Sources. 3.     On the Summary of Data Sources page, click the data source name for example “mds-owsm”. 4.     Select the Configuration: Connection Pool tab. 5.     Scroll down and click Advanced to show the advanced connection pool options. 6.     In Wrap Data Types, deselect the checkbox to disable wrapping. 7.     Click Save. 8.     To activate these changes, in the Change Center of the Administration Console, click Activate Changes. Important Note: This change does not take effect immediately—it requires the server be restarted.

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  • Oracle Big Data Learning Library - Click on LEARN BY PRODUCT to Open Page

    - by chberger
    Oracle Big Data Learning Library... Learn about Oracle Big Data, Data Science, Learning Analytics, Oracle NoSQL Database, and more! Oracle Big Data Essentials Attend this Oracle University Course! Using Oracle NoSQL Database Attend this Oracle University class! Oracle and Big Data on OTN See the latest resource on OTN. Search Welcome Get Started Learn by Role Learn by Product Latest Additions Additional Resources Oracle Big Data Appliance Oracle Big Data and Data Science Basics Meeting the Challenge of Big Data Oracle Big Data Tutorial Video Series Oracle MoviePlex - a Big Data End-to-End Series of Demonstrations Oracle Big Data Overview Oracle Big Data Essentials Data Mining Oracle NoSQL Database Tutorial Videos Oracle NoSQL Database Tutorial Series Oracle NoSQL Database Release 2 New Features Using Oracle NoSQL Database Exalytics Enterprise Manager 12c R3: Manage Exalytics Setting Up and Running Summary Advisor on an E s Oracle R Enterprise Oracle R Enterprise Tutorial Series Oracle Big Data Connectors Integrate All Your Data with Oracle Big Data Connectors Using Oracle Direct Connector for HDFS to Read the Data from HDSF Using Oracle R Connector for Hadoop to Analyze Data Oracle NoSQL Database Oracle NoSQL Database Tutorial Videos Oracle NoSQL Database Tutorial Series Oracle NoSQL Database Release 2 New Features  Using Oracle NoSQL Database eries Oracle Business Intelligence Enterprise Edition Oracle Business Intelligence Oracle BI 11g R1: Create Analyses and Dashboards - 4 day class Oracle BI Publisher 11g R1: Fundamentals - 3 day class Oracle BI 11g R1: Build Repositories - 5 day class

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  • Let's introduce the Oracle Enterprise Data Quality family!

    - by Sarah Zanchetti
    The Oracle Enterprise Data Quality family of products helps you to achieve maximum value from their business applications by delivering fit-­for-­purpose data. OEDQ is a state-of-the-art collaborative data quality profiling, analysis, parsing, standardization, matching and merging product, designed to help you understand, improve, protect and govern the quality of the information your business uses, all from a single integrated environment. Oracle Enterprise Data Quality products are: Oracle Enterprise Data Quality Profile and Audit Oracle Enterprise Data Quality Parsing and Standardization Oracle Enterprise Data Quality Match and Merge Oracle Enterprise Data Quality Address Verification Server Oracle Enterprise Data Quality Product Data Parsing and Standardization Oracle Enterprise Data Quality Product Data Match and Merge Also, the following are some of the key features of OEDQ: Integrated data profiling, auditing, cleansing and matching Browser-based client access Ability to handle all types of data – for example customer, product, asset, financial, operational Connection to any JDBC-compliant data sources and targets Multi-user project support (role-based access, issue tracking, process annotation, and version control) Services Oriented Architecture (SOA) - support for designing processes that may be exposed to external applications as a service Designed to process large data volumes A single repository to hold data along with gathered statistics and project tracking information, with shared access Intuitive graphical user interface designed to help you solve real-world information quality issues quickly Easy, data-led creation and extension of validation and transformation rules Fully extensible architecture allowing the insertion of any required custom processing  If you need to learn more about EDQ, or get assistance for any kind of issue, the Oracle Technology Network offers a huge range of resources on Oracle software. Discuss technical problems and solutions on the Discussion Forums. Get hands-on step-by-step tutorials with Oracle By Example. Download Sample Code. Get the latest news and information on any Oracle product. You can also get further help and information with Oracle software from: My Oracle Support Oracle Support Services An Information Center is available, where you can find technical information and fast solutions to the most common already solved issues: Information Center: Oracle Enterprise Data Quality [ID 1555073.2]

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  • Oracle Enterprise Data Quality - Geared Up and Ready for OpenWorld 2012

    - by Mala Narasimharajan
    10 days and counting till Oracle OpenWorld 2012 is upon us.  Enterprise data quality is key to every information integration and consolidation initiative. At this year's OpenWorld, hear how Oracle Enterprise Data Quality provides the critical piece to achieving trusted, reliable master data and increases the value of data integration initiatives. Here are the different ways you can learn and experience Enterprise Data Quality at OpenWorld:  Conference sessions: Oracle Enterprise Data Quality: Product Overview and Roadmap - Monday 10/1/12, 1:45-2:45 PM - Moscone West - 3006 Data Preparation and Ongoing Governance with the Oracle Enterprise Data Quality Platform - Wednesday 10/3/2012, 1:15-2:15 PM - Moscone West - 3000  Data Acquisition, Migration and Integration with the Oracle Enterprise Data Quality Platform - Thursday 10/4/2012, 12:45-1:45 PM - Moscone West - 3005  Hands on Labs: Introduction to Oracle Enterprise Data Quality Platform -  Monday 10/2/2012, 4:45-5:45 PM - Marriot Marquis - Salon 1/2 Demos:  Trusted Data with Oracle Enterprise Data Quality - Moscone South, Right - S-243 (note: proceed to Middleware Demo grounds) For a list of Master Data Management and Data Quality sessions and other events click here. 

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  • SL3/SL4 - Ado.Net Data Services Error during new DataServiceCollection<T>(queryResponse)

    - by Soulhuntre
    Hey all, I have two functions in a SL project (VS2010) that do almost exactly the same thing, yet one throws an error and the other does not. It seems to be related to the projections, but I am unsure about the best way to resolve. The function that works is... public void LoadAllChunksExpandAll(DataHelperReturnHandler handler, string orderby) { DataServiceCollection<CmsChunk> data = null; DataServiceQuery<CmsChunk> theQuery = _dataservice .CmsChunks .Expand("CmsItemState") .AddQueryOption("$orderby", orderby); theQuery.BeginExecute( delegate(IAsyncResult asyncResult) { _callback_dispatcher.BeginInvoke( () => { try { DataServiceQuery<CmsChunk> query = asyncResult.AsyncState as DataServiceQuery<CmsChunk>; if (query != null) { //create a tracked DataServiceCollection from the result of the asynchronous query. QueryOperationResponse<CmsChunk> queryResponse = query.EndExecute(asyncResult) as QueryOperationResponse<CmsChunk>; data = new DataServiceCollection<CmsChunk>(queryResponse); handler(data); } } catch { handler(data); } } ); }, theQuery ); } This compiles and runs as expected. A very, very similar function (shown below) fails... public void LoadAllPagesExpandAll(DataHelperReturnHandler handler, string orderby) { DataServiceCollection<CmsPage> data = null; DataServiceQuery<CmsPage> theQuery = _dataservice .CmsPages .Expand("CmsChildPages") .Expand("CmsParentPage") .Expand("CmsItemState") .AddQueryOption("$orderby", orderby); theQuery.BeginExecute( delegate(IAsyncResult asyncResult) { _callback_dispatcher.BeginInvoke( () => { try { DataServiceQuery<CmsPage> query = asyncResult.AsyncState as DataServiceQuery<CmsPage>; if (query != null) { //create a tracked DataServiceCollection from the result of the asynchronous query. QueryOperationResponse<CmsPage> queryResponse = query.EndExecute(asyncResult) as QueryOperationResponse<CmsPage>; data = new DataServiceCollection<CmsPage>(queryResponse); handler(data); } } catch { handler(data); } } ); }, theQuery ); } Clearly the issue is the Expand projections that involve a self referencing relationship (pages can contain other pages). This is under SL4 or SL3 using ADONETDataServices SL3 Update CTP3. I am open to any work around or pointers to goo information, a Google search for the error results in two hits, neither particularly helpful that I can decipher. The short error is "An item could not be added to the collection. When items in a DataServiceCollection are tracked by the DataServiceContext, new items cannot be added before items have been loaded into the collection." The full error is... System.Reflection.TargetInvocationException was caught Message=Exception has been thrown by the target of an invocation. StackTrace: at System.RuntimeMethodHandle.InvokeMethodFast(IRuntimeMethodInfo method, Object target, Object[] arguments, SignatureStruct& sig, MethodAttributes methodAttributes, RuntimeType typeOwner) at System.Reflection.RuntimeMethodInfo.Invoke(Object obj, BindingFlags invokeAttr, Binder binder, Object[] parameters, CultureInfo culture, Boolean skipVisibilityChecks) at System.Reflection.RuntimeMethodInfo.Invoke(Object obj, BindingFlags invokeAttr, Binder binder, Object[] parameters, CultureInfo culture) at System.Reflection.MethodBase.Invoke(Object obj, Object[] parameters) at System.Data.Services.Client.ClientType.ClientProperty.SetValue(Object instance, Object value, String propertyName, Boolean allowAdd) at System.Data.Services.Client.AtomMaterializer.ApplyItemsToCollection(AtomEntry entry, ClientProperty property, IEnumerable items, Uri nextLink, ProjectionPlan continuationPlan) at System.Data.Services.Client.AtomMaterializer.ApplyFeedToCollection(AtomEntry entry, ClientProperty property, AtomFeed feed, Boolean includeLinks) at System.Data.Services.Client.AtomMaterializer.MaterializeResolvedEntry(AtomEntry entry, Boolean includeLinks) at System.Data.Services.Client.AtomMaterializer.Materialize(AtomEntry entry, Type expectedEntryType, Boolean includeLinks) at System.Data.Services.Client.AtomMaterializer.DirectMaterializePlan(AtomMaterializer materializer, AtomEntry entry, Type expectedEntryType) at System.Data.Services.Client.AtomMaterializerInvoker.DirectMaterializePlan(Object materializer, Object entry, Type expectedEntryType) at System.Data.Services.Client.ProjectionPlan.Run(AtomMaterializer materializer, AtomEntry entry, Type expectedType) at System.Data.Services.Client.AtomMaterializer.Read() at System.Data.Services.Client.MaterializeAtom.MoveNextInternal() at System.Data.Services.Client.MaterializeAtom.MoveNext() at System.Linq.Enumerable.d_b11.MoveNext() at System.Data.Services.Client.DataServiceCollection1.InternalLoadCollection(IEnumerable1 items) at System.Data.Services.Client.DataServiceCollection1.StartTracking(DataServiceContext context, IEnumerable1 items, String entitySet, Func2 entityChanged, Func2 collectionChanged) at System.Data.Services.Client.DataServiceCollection1..ctor(DataServiceContext context, IEnumerable1 items, TrackingMode trackingMode, String entitySetName, Func2 entityChangedCallback, Func2 collectionChangedCallback) at System.Data.Services.Client.DataServiceCollection1..ctor(IEnumerable1 items) at Phinli.Dashboard.Silverlight.Helpers.DataHelper.<>c__DisplayClass44.<>c__DisplayClass46.<LoadAllPagesExpandAll>b__43() InnerException: System.InvalidOperationException Message=An item could not be added to the collection. When items in a DataServiceCollection are tracked by the DataServiceContext, new items cannot be added before items have been loaded into the collection. StackTrace: at System.Data.Services.Client.DataServiceCollection1.InsertItem(Int32 index, T item) at System.Collections.ObjectModel.Collection`1.Add(T item) InnerException: Thanks for any help!

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  • Smart way to find the corresponding nullable type?

    - by Marc Wittke
    How could I avoid this dictionary (or create it dynamically)? Dictionary<Type,Type> CorrespondingNullableType = new Dictionary<Type, Type> { {typeof(bool), typeof(bool?)}, {typeof(byte), typeof(byte?)}, {typeof(sbyte), typeof(sbyte?)}, {typeof(char), typeof(char?)}, {typeof(decimal), typeof(decimal?)}, {typeof(double), typeof(double?)}, {typeof(float), typeof(float?)}, {typeof(int), typeof(int?)}, {typeof(uint), typeof(uint?)}, {typeof(long), typeof(long?)}, {typeof(ulong), typeof(ulong?)}, {typeof(short), typeof(short?)}, {typeof(ushort), typeof(ushort?)}, {typeof(Guid), typeof(Guid?)}, };

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  • 3rd party data - Store in Data Warehouse or Primary database?

    - by brydgesk
    This is mostly a data warehouse philosophy question. My project involves an Oracle forms application, and a Teradata Data Warehouse for reporting and ad-hoc purposes. In addition to the primary data created by the users of our application, we also require data from various other sources. Currently, this 3rd party data comes via FTPd flat files directly to our Data Warehouse. To access the data, our users must use a series of custom BusinessObjects reports. My question is, would it make more sense for this data to be sent to our source Oracle system instead? Is it ever appropriate for a Data Warehouse to be the point of origin for users to access raw data? In short, is it more important that the operational database contain only the data created by your project, or that the data warehouse remain dedicated solely to reporting and analysis?

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  • Starting to construct a data access layer. Things to consider?

    - by Phil
    Our organisation uses inline sql. We have been tasked with providing a suitable data access layer and are weighing up the pro's and cons of which way to go... Datasets ADO.net Linq Entity framework Subsonic Other? Some tutorials and articles I have been using for reference: http://www.asp.net/(S(pdfrohu0ajmwt445fanvj2r3))/learn/data-access/tutorial-01-vb.aspx http://www.simple-talk.com/dotnet/.net-framework/designing-a-data-access-layer-in-linq-to-sql/ http://msdn.microsoft.com/en-us/magazine/cc188750.aspx http://msdn.microsoft.com/en-us/library/aa697427(VS.80).aspx http://www.subsonicproject.com/ I'm extremely torn, and finding it very difficult to make a decision on which way to go. Our site is a series of 2 internal portals and a public web site. We are using vs2008 sp1 and framework version 3.5. Please can you give me advise on what factors to consider and any pro's and cons you have faced with your data access layer. Thanks.

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  • mysqli and field types

    - by Mikk
    Hi, I'd like to know if there is a simple way to fetch data from mysql tables with "correct" data types? What i mean, if field type is for example INT or SMALLINT is it possible to pass those types directly to PHP as integers? I did some searching and found mysqli_fetch_fields, but for SMALLIT type is 2, for INT 3 and so on. It could be done that way, but it looks rather clumsy workaround. Is there any better way? I'm using PHP and mysqli. Thank you.

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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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  • Nested/Sub data types in haskell

    - by Tom Carstens
    So what would be nice is if you could do something like the following (not necessarily with this format, just the general idea): data Minor = MinorA | MinorB data Major = Minor | MajorB isMinor :: Major -> Bool isMinor Minor = True isMinor _ = False So isMinor MinorA would report True (instead of an error.) At the moment you might do something like: data Major = MinorA | MinorB | MajorB isMinor :: Major -> Bool isMinor MinorA = True isMinor MinorB = True isMinor _ = False It's not terrible or anything, but it doesn't expand nicely (as in if Minor when up to MinorZ this would be terribly clunky). To avoid that problem you can wrap Minor: data Minor = MinorA | MinorB data Major = MajorA Minor | MajorB isMinor :: Major -> Bool isMinor (MajorA _) = True isMinor _ = False But now you have to make sure to wrap your Minors to use them as a Major... again not terrible; just doesn't really express the semantics I'd like very well (i.e. Major can be any Minor or MajorB). The first (legal) example is "Major can be MinorA..." but doesn't have any knowledge of Minor and the second is "Major can be MajorA that takes a Minor..." p.s. No, this isn't really about anything concrete.

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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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  • Calling Web Service with Complex Parameters in ADF Mobile

    - by Shay Shmeltzer
    Many of the SOAP based web services out there have parameters of specific object types - so not just simple String/int inputs. The ADF Web service data control makes it quite simple to interact with them. And this applies also in the case of ADF Mobile. Since there were several thread on OTN asking about this - I thought I'll do a quick demo to refresh people memory about how you pass these "complex" parameters to your Web service methods. By the way - this video is also relevant if you are not doing mobile development, you'll basically use the exact same process for building "regular web" ADF applications that access these types of Web services. One more thing you might want to do after you create the page is look at the binding tab to see the method call in there, and notice the parameters for it in the structure property. Go and look at their NDValue property to get the complete picture.

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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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