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  • Extract enumeration data from .XSD file

    - by Ram
    Hi, I am trying to read enum from a XSD file. The schema is as follows <xs:schema id="ShipReports-v1.xsd" xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:msdata="urn:schemas-microsoft-com:xml-msdata" attributeFormDefault="unqualified" elementFormDefault="qualified" msdata:IsDataSet="true"> <xs:simpleType name="Type"> <xs:restriction base="xs:string"> <xs:enumeration value="Op1" /> <xs:enumeration value="Op2" /> <xs:enumeration value="Op3" /> </xs:restriction> </xs:simpleType> </xs:schema> I also tried using this but I am getting list item count as Zero. Following is the code I am using DataSet _sR = new DataSet(); _sR.ReadXmlSchema(assembly.GetManifestResourceStream("v1.xsd")); XmlDocument xDoc = new XmlDocument(); xDoc.LoadXml(_sR.GetXml()); XmlNamespaceManager xMan = new XmlNamespaceManager(xDoc.NameTable); xMan.AddNamespace("xs", "http://www.w3.org/2001/XMLSchema"); XmlNodeList xNodeList = xDoc.SelectNodes( "//xs:schema/xs:simpleType[@name='Type']/xs:enumeration", xMan); string[] enumVal = new string[xNodeList.Count]; int ctr = 0; foreach (XmlNode xNode in xNodeList) { enumVal[ctr] = xNode.Attributes["value"].Value; ctr++; }

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  • Stored Procedures In Source Control - Automate Build/Deployment Process

    - by Alex
    My company provides a large .NET service-oriented solution. The services layer interact with a T-SQL back-end consisting of hundreds of tables and stored procedures. Our C# code is in version-control (SVN) but our stored procedures and schema are not. After much lobbying of expedient upper-management, I was allowed to review our (non-existent) build/deployment process to accomplish the following goals: Place schema and stored procedures under source-control. Automate the build/deployment process. I would like to proceed per the accepted answer's strategy in this post but have additional questions: I would like to use Hudson as my build server. Is this a reasonable choice for a C#/SQL solution? What better alternatives should I explore? Assuming I have all triggers, stored-procedures, schema, etc... under source control, and that they are scripted to individual files, how do I generate a build script which will take into account dependencies/references between these items? (SQL Server does this automatically, but it generates one giant script) What does the workflow of performing an update at the client look like? i.e. I have to keep existing table data. How do I roll-back schema changes? I am the only programmer. Several other pseudo-technical staff like to make changes directly inside SQL Management Studio. Is it realistic to expect others to adhere to this solution -- how can I enforce this? Thank you in advance for your help.

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  • Extend DOMElement object

    - by Comma
    How could I exdend objects provided with Document Object Model? Seems that there is no way according to this [issue][2]. class Application_Model_XmlSchema extends DOMElement { const ELEMENT_NAME = 'schema'; /** * @var DOMElement */ private $_schema; /** * @param DOMDocument $document * @return void */ public function __construct(DOMDocument $document) { $this->setSchema($document->getElementsByTagName(self::ELEMENT_NAME)->item(0)); } /** * @param DOMElement $schema * @return void */ public function setSchema(DOMElement $schema){ $this->_schema = $schema; } /** * @return DOMElement */ public function getSchema(){ return $this->_schema; } /** * @param string $name * @param array $arguments * @return mixed */ public function __call($name, $arguments) { if (method_exists($this->_schema, $name)) { return call_user_func_array( array($this->_schema, $name), $arguments ); } } } $version = $this->getRequest()->getParam('version', null); $encoding = $this->getRequest()->getParam('encoding', null); $source = 'http://www.w3.org/2001/XMLSchema.xsd'; $document = new DOMDocument($version, $encoding); $document->load($source); $xmlSchema = new Application_Model_XmlSchema($document); $xmlSchema->getAttribute('version'); I got an error: Warning: DOMElement::getAttribute(): Couldn't fetch Application_Model_XmlSchema in C:\Nevermind.php on line newvermind

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  • import csv file/excel into sql database asp.net

    - by kiev
    Hi everyone! I am starting a project with asp.net visual studio 2008 / SQL 2000 (2005 in future) using c#. The tricky part for me is that the existing DB schema changes often and the import files columns will all have to me matched up with the existing db schema since they may not be one to one match on column names. (There is a lookup table that provides the tables schema with column names I will use) I am exploring different ways to approach this, and need some expert advice. Is there any existing controls or frameworks that I can leverage to do any of this? So far I explored FileUpload .NET control, as well as some 3rd party upload controls to accomplish the upload such as SlickUpload but the files uploaded should be < 500mb Next part is reading of my csv /excel and parsing it for display to the user so they can match it with our db schema. I saw CSVReader and others but for excel its more difficult since I will need to support different versions. Essentially The user performing this import will insert and/or update several tables from this import file. There are other more advance requirements like record matching but and preview of the import records, but I wish to get through understanding how to do this first. Update: I ended up using csvReader with LumenWorks.Framework for uploading the csv files.

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  • MS Access: Permission problems with views

    - by Keith Williams
    "I'll use an Access ADP" I said, "it's only a tiny project and I've got better things to do", I said, "I can build an interface really quickly in Access" I said. </sarcasm> Sorry for the rant, but it's Friday, I have a date in just under two hours, and I'm here late because this just isn't working - so, in despair, I turn to SO for help. Access ADP front-end, linked to a SQL Server 2008 database Using a SQL Server account to log into the database (for testing); this account is a member of the role, "Api"; this role has SELECT, EXECUTE, INSERT, UPDATE, DELETE access to the "Api" schema The "Api" schema is owned by "dbo" All tables have a corresponding view in the Api schema: e.g. dbo.Customer -- Api.Customers The rationale is that users don't have direct table access, but can deal with views as if they were tables I can log into SQL using my test login, and it works fine: no access to the tables, but I can select, insert, update and delete from the Api views. In Access, I see the views, I can open them, but whenever I try to insert or update, I get the following error: The SELECT permission was denied on the object '[Table name which the view is using]', database '[database name]', schema 'dbo' Crazy as it sounds, Access seems to be trying to access the underlying table rather than the view. Any ideas?

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  • How to insert several thousand columns into sqlite3?

    - by user291071
    Similar to my last question, but I ran into problem lets say I have a simple dictionary like below but its Big, when I try inserting a big dictionary using the methods below I get operational error for the c.execute(schema) for too many columns so what should be my alternate method to populate an sql databases columns? Using the alter table command and add each one individually? import sqlite3 con = sqlite3.connect('simple.db') c = con.cursor() dic = { 'x1':{'y1':1.0,'y2':0.0}, 'x2':{'y1':0.0,'y2':2.0,'joe bla':1.5}, 'x3':{'y2':2.0,'y3 45 etc':1.5} } # 1. Find the unique column names. columns = set() for _, cols in dic.items(): for key, _ in cols.items(): columns.add(key) # 2. Create the schema. col_defs = [ # Start with the column for our key name '"row_name" VARCHAR(2) NOT NULL PRIMARY KEY' ] for column in columns: col_defs.append('"%s" REAL NULL' % column) schema = "CREATE TABLE simple (%s);" % ",".join(col_defs) c.execute(schema) # 3. Loop through each row for row_name, cols in dic.items(): # Compile the data we have for this row. col_names = cols.keys() col_values = [str(val) for val in cols.values()] # Insert it. sql = 'INSERT INTO simple ("row_name", "%s") VALUES ("%s", "%s");' % ( '","'.join(col_names), row_name, '","'.join(col_values) )

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  • Faster Insertion of Records into a Table with SQLAlchemy

    - by Kyle Brandt
    I am parsing a log and inserting it into either MySQL or SQLite using SQLAlchemy and Python. Right now I open a connection to the DB, and as I loop over each line, I insert it after it is parsed (This is just one big table right now, not very experienced with SQL). I then close the connection when the loop is done. The summarized code is: log_table = schema.Table('log_table', metadata, schema.Column('id', types.Integer, primary_key=True), schema.Column('time', types.DateTime), schema.Column('ip', types.String(length=15)) .... engine = create_engine(...) metadata.bind = engine connection = engine.connect() .... for line in file_to_parse: m = line_regex.match(line) if m: fields = m.groupdict() pythonified = pythoninfy_log(fields) #Turn them into ints, datatimes, etc if use_sql: ins = log_table.insert(values=pythonified) connection.execute(ins) parsed += 1 My two questions are: Is there a way to speed up the inserts within this basic framework? Maybe have a Queue of inserts and some insertion threads, some sort of bulk inserts, etc? When I used MySQL, for about ~1.2 million records the insert time was 15 minutes. With SQLite, the insert time was a little over an hour. Does that time difference between the db engines seem about right, or does it mean I am doing something very wrong?

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  • How do I correctly reference georss: point in my xsd?

    - by Chris Hinch
    I am putting together an XSD schema to describe an existing GeoRSS feed, but I am stumbling trying to use the external georss.xsd to validate an element of type georss:point. I've reduced the problem to the smallest components thusly: XML: <?xml version="1.0" encoding="utf-8"?> <this> <apoint>45.256 -71.92</apoint> </this> XSD: <xs:schema xmlns:xs="http://www.w3.org/2001/XMLSchema" xmlns:georss="http://www.georss.org/georss"> <xs:import namespace="http://www.georss.org/georss" schemaLocation="http://georss.org/xml/1.1/georss.xsd"/> <xs:element name="this"> <xs:complexType> <xs:sequence> <xs:element name="apoint" type="georss:point"/> </xs:sequence> </xs:complexType> </xs:element> </xs:schema> If I make apoint type "xs: string" instead of "georss: point", the XML validates happily against the XSD, but as soon as I reference an imported type (georss: point), my XML validator (Notepad++ | XML Tools) "cannot parse the schema". What am I doing wrong?

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  • Why would this query cause a Merge Cartesian Join in Oracle

    - by decompiled
    I have a query that was recently required to be modified. Here's the original SELECT RTRIM (position) AS "POSITION", . // Other fields . . FROM schema.table x WHERE hours > 0 AND pay = 'RGW' AND NOT EXISTS( SELECT position FROM schema.table2 y where y.position = x.position ) Here's the new version SELECT RTRIM (position) AS "POSITION", . // Other fields . . FROM schema.table x WHERE hours > 0 AND pay = 'RGW' AND NOT EXISTS( SELECT position FROM schema.table2 y where y.date = get_fiscal_year_start_date (SYSDATE) AND y.position = x.position ) The UDF get_fiscal_year_start_date() returns the fiscal year start date of the date parameter. The first query runs fine, but the second creates a merge Cartesian join. I looked at the indexes on the tables and found that position and date were both indexed. My question for you stackoverflow is why would the addition of 'y.date = get_fiscal_year_start_date (SYSDATE)' cause a merge cartesian join in Oracle 10g.

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  • Which events specifically cause Windows 2008 to mark a SAN volume offline?

    - by Jeremy
    I am searching for specific criteria/events that will cause Windows 2008 to mark a SAN volume as offline in disk management, even though it is connected to that SAN volume via FC or iSCSI. Microsoft states that "A dynamic disk may become Offline if it is corrupted or intermittently unavailable. A dynamic disk may also become Offline if you attempt to import a foreign (dynamic) disk and the import fails. An error icon appears on the Offline disk. Only dynamic disks display the Missing or Offline status." I am specifically wondering if, on the SAN, changing the path to the disk (such as the disk being presented to the host via a different iSCSI target IQN or a different LUN #) would cause a volume to be offlined in disk management. Thanks! Edit: I have already found two reasons why a disk might be set offline, disk signature collisions and the SAN disk policy. Bounty would be awarded to someone who can find further documented reasons related to changes in the volume's path. Disk signature collisions: http://blogs.technet.com/b/markrussinovich/archive/2011/11/08/3463572.aspx SAN disk policy: http://jeffwouters.nl/index.php/2011/06/disk-offline-with-error-the-disk-is-offline-because-of-a-policy-set-by-an-administrator/

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  • Is Cherokee (probably) the best static content server for beginner sysadmins?

    - by Bad Learner
    I have read the pros and cons of most of the popular web servers and have come to a conclusion that Apache would (probably) be the best web server for serving dynamic content - - no wonder YouTube, Flickr and Facbook, among many others, use it. I do not know if that C10K problem applies to Apache even when serving dynamic content only, but I think any web server used to serve dynamic content needs some good tweaking for optimized performance, and the fact that nothing beats Apache when it comes to documentation, resources and support on the web, I think should will go with Apache for dynamic content. That apart, the confusion begins when it comes to choosing web servers for static content (including streaming videos). I see that Nginx, Cherokee and Lighttpd are among the best (I am not considering non-open source or non-linux stuff here). So, which too choose? I know one cannot go wrong with any of the three (Nginx, Cherokee, Lighttpd). Lighttpd's development has evidently gotten slower than it was a good time ago. The documentation is pretty good for all the three, and hopefully, so are the resources (knowledge of these among the users of Stackoverflow/Serverfault sites, the web etc). Precisely, and noting point [2] and [3], if I am not wrong, I should either go with Nginx or Cherokee. I would love to see someone clarify these... is Cherokee just as fast (mb/s), performant (connections/s), and reliable (think downtime/restarting server) as Nginx for serving static content and load balancing, for small, medium to large (and really large) websites and applications? (Think, the size of YouTube, Apache or Facebook.) if the answer for the Q above is a big "hell, yes!" then, I should probably prefer Cherokee, right? Because, since I am a beginner, it would a lot easier to setup Cherokee as it has a graphical admin user interface + really good documentation. Yes? I could be wrong, I could be right. I put down what I know so that you can offer most relevant advise. Pardon if anything I've said is offensive.

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  • Should I use nginx exclusively, or have it as a proxy to Tomcat (performance related)?

    - by Kevin
    I've planned to create a website that'll be pretty heavy on dynamic content, and want to know what would be the wisest choice for part of my webstack. Right now I'm trying to decide whether I should develop upon nginx, using PHP to deliver the dynamic content, or use nginx as a proxy to Tomcat and use servlets to deliver the dynamic content. I have a good amount of experience with Java, JSP, and servlets, so that's a plus right off the bat. Also, since it is a compiled language, it will execute faster than PHP (it is implied here that Java is around 37x faster than PHP) , and will create the web pages faster. I have no experience with PHP, however i'm under the impression that it is easy to pick up. It's slower than Java, but since the client will only be communicating with nginx, I'm thinking that serving the dynamically created web pages to the client will be faster this way. Considering these things, i'd like to know: Are my assumptions correct? Where does the bottleneck occur: creating pages or serving them back to the client? Will proxying Tomcat with nginx give me any of nginx performance benefits if I'm going to be using Tomcat to generate the dynamic content (keeping in mind my site is going to be heavy in this aspect)? I don't mind learning PHP if, in the end, its going to give me the best performance. I just want to know what would be the best choice from that standpoint.

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  • Using an alternate JSON Serializer in ASP.NET Web API

    - by Rick Strahl
    The new ASP.NET Web API that Microsoft released alongside MVC 4.0 Beta last week is a great framework for building REST and AJAX APIs. I've been working with it for quite a while now and I really like the way it works and the complete set of features it provides 'in the box'. It's about time that Microsoft gets a decent API for building generic HTTP endpoints into the framework. DataContractJsonSerializer sucks As nice as Web API's overall design is one thing still sucks: The built-in JSON Serialization uses the DataContractJsonSerializer which is just too limiting for many scenarios. The biggest issues I have with it are: No support for untyped values (object, dynamic, Anonymous Types) MS AJAX style Date Formatting Ugly serialization formats for types like Dictionaries To me the most serious issue is dealing with serialization of untyped objects. I have number of applications with AJAX front ends that dynamically reformat data from business objects to fit a specific message format that certain UI components require. The most common scenario I have there are IEnumerable query results from a database with fields from the result set rearranged to fit the sometimes unconventional formats required for the UI components (like jqGrid for example). Creating custom types to fit these messages seems like overkill and projections using Linq makes this much easier to code up. Alas DataContractJsonSerializer doesn't support it. Neither does DataContractSerializer for XML output for that matter. What this means is that you can't do stuff like this in Web API out of the box:public object GetAnonymousType() { return new { name = "Rick", company = "West Wind", entered= DateTime.Now }; } Basically anything that doesn't have an explicit type DataContractJsonSerializer will not let you return. FWIW, the same is true for XmlSerializer which also doesn't work with non-typed values for serialization. The example above is obviously contrived with a hardcoded object graph, but it's not uncommon to get dynamic values returned from queries that have anonymous types for their result projections. Apparently there's a good possibility that Microsoft will ship Json.NET as part of Web API RTM release.  Scott Hanselman confirmed this as a footnote in his JSON Dates post a few days ago. I've heard several other people from Microsoft confirm that Json.NET will be included and be the default JSON serializer, but no details yet in what capacity it will show up. Let's hope it ends up as the default in the box. Meanwhile this post will show you how you can use it today with the beta and get JSON that matches what you should see in the RTM version. What about JsonValue? To be fair Web API DOES include a new JsonValue/JsonObject/JsonArray type that allow you to address some of these scenarios. JsonValue is a new type in the System.Json assembly that can be used to build up an object graph based on a dictionary. It's actually a really cool implementation of a dynamic type that allows you to create an object graph and spit it out to JSON without having to create .NET type first. JsonValue can also receive a JSON string and parse it without having to actually load it into a .NET type (which is something that's been missing in the core framework). This is really useful if you get a JSON result from an arbitrary service and you don't want to explicitly create a mapping type for the data returned. For serialization you can create an object structure on the fly and pass it back as part of an Web API action method like this:public JsonValue GetJsonValue() { dynamic json = new JsonObject(); json.name = "Rick"; json.company = "West Wind"; json.entered = DateTime.Now; dynamic address = new JsonObject(); address.street = "32 Kaiea"; address.zip = "96779"; json.address = address; dynamic phones = new JsonArray(); json.phoneNumbers = phones; dynamic phone = new JsonObject(); phone.type = "Home"; phone.number = "808 123-1233"; phones.Add(phone); phone = new JsonObject(); phone.type = "Home"; phone.number = "808 123-1233"; phones.Add(phone); //var jsonString = json.ToString(); return json; } which produces the following output (formatted here for easier reading):{ name: "rick", company: "West Wind", entered: "2012-03-08T15:33:19.673-10:00", address: { street: "32 Kaiea", zip: "96779" }, phoneNumbers: [ { type: "Home", number: "808 123-1233" }, { type: "Mobile", number: "808 123-1234" }] } If you need to build a simple JSON type on the fly these types work great. But if you have an existing type - or worse a query result/list that's already formatted JsonValue et al. become a pain to work with. As far as I can see there's no way to just throw an object instance at JsonValue and have it convert into JsonValue dictionary. It's a manual process. Using alternate Serializers in Web API So, currently the default serializer in WebAPI is DataContractJsonSeriaizer and I don't like it. You may not either, but luckily you can swap the serializer fairly easily. If you'd rather use the JavaScriptSerializer built into System.Web.Extensions or Json.NET today, it's not too difficult to create a custom MediaTypeFormatter that uses these serializers and can replace or partially replace the native serializer. Here's a MediaTypeFormatter implementation using the ASP.NET JavaScriptSerializer:using System; using System.Net.Http.Formatting; using System.Threading.Tasks; using System.Web.Script.Serialization; using System.Json; using System.IO; namespace Westwind.Web.WebApi { public class JavaScriptSerializerFormatter : MediaTypeFormatter { public JavaScriptSerializerFormatter() { SupportedMediaTypes.Add(new System.Net.Http.Headers.MediaTypeHeaderValue("application/json")); } protected override bool CanWriteType(Type type) { // don't serialize JsonValue structure use default for that if (type == typeof(JsonValue) || type == typeof(JsonObject) || type== typeof(JsonArray) ) return false; return true; } protected override bool CanReadType(Type type) { if (type == typeof(IKeyValueModel)) return false; return true; } protected override System.Threading.Tasks.Taskobject OnReadFromStreamAsync(Type type, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext) { var task = Taskobject.Factory.StartNew(() = { var ser = new JavaScriptSerializer(); string json; using (var sr = new StreamReader(stream)) { json = sr.ReadToEnd(); sr.Close(); } object val = ser.Deserialize(json,type); return val; }); return task; } protected override System.Threading.Tasks.Task OnWriteToStreamAsync(Type type, object value, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext, System.Net.TransportContext transportContext) { var task = Task.Factory.StartNew( () = { var ser = new JavaScriptSerializer(); var json = ser.Serialize(value); byte[] buf = System.Text.Encoding.Default.GetBytes(json); stream.Write(buf,0,buf.Length); stream.Flush(); }); return task; } } } Formatter implementation is pretty simple: You override 4 methods to tell which types you can handle and then handle the input or output streams to create/parse the JSON data. Note that when creating output you want to take care to still allow JsonValue/JsonObject/JsonArray types to be handled by the default serializer so those objects serialize properly - if you let either JavaScriptSerializer or JSON.NET handle them they'd try to render the dictionaries which is very undesirable. If you'd rather use Json.NET here's the JSON.NET version of the formatter:// this code requires a reference to JSON.NET in your project #if true using System; using System.Net.Http.Formatting; using System.Threading.Tasks; using System.Web.Script.Serialization; using System.Json; using Newtonsoft.Json; using System.IO; using Newtonsoft.Json.Converters; namespace Westwind.Web.WebApi { public class JsonNetFormatter : MediaTypeFormatter { public JsonNetFormatter() { SupportedMediaTypes.Add(new System.Net.Http.Headers.MediaTypeHeaderValue("application/json")); } protected override bool CanWriteType(Type type) { // don't serialize JsonValue structure use default for that if (type == typeof(JsonValue) || type == typeof(JsonObject) || type == typeof(JsonArray)) return false; return true; } protected override bool CanReadType(Type type) { if (type == typeof(IKeyValueModel)) return false; return true; } protected override System.Threading.Tasks.Taskobject OnReadFromStreamAsync(Type type, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext) { var task = Taskobject.Factory.StartNew(() = { var settings = new JsonSerializerSettings() { NullValueHandling = NullValueHandling.Ignore, }; var sr = new StreamReader(stream); var jreader = new JsonTextReader(sr); var ser = new JsonSerializer(); ser.Converters.Add(new IsoDateTimeConverter()); object val = ser.Deserialize(jreader, type); return val; }); return task; } protected override System.Threading.Tasks.Task OnWriteToStreamAsync(Type type, object value, System.IO.Stream stream, System.Net.Http.Headers.HttpContentHeaders contentHeaders, FormatterContext formatterContext, System.Net.TransportContext transportContext) { var task = Task.Factory.StartNew( () = { var settings = new JsonSerializerSettings() { NullValueHandling = NullValueHandling.Ignore, }; string json = JsonConvert.SerializeObject(value, Formatting.Indented, new JsonConverter[1] { new IsoDateTimeConverter() } ); byte[] buf = System.Text.Encoding.Default.GetBytes(json); stream.Write(buf,0,buf.Length); stream.Flush(); }); return task; } } } #endif   One advantage of the Json.NET serializer is that you can specify a few options on how things are formatted and handled. You get null value handling and you can plug in the IsoDateTimeConverter which is nice to product proper ISO dates that I would expect any Json serializer to output these days. Hooking up the Formatters Once you've created the custom formatters you need to enable them for your Web API application. To do this use the GlobalConfiguration.Configuration object and add the formatter to the Formatters collection. Here's what this looks like hooked up from Application_Start in a Web project:protected void Application_Start(object sender, EventArgs e) { // Action based routing (used for RPC calls) RouteTable.Routes.MapHttpRoute( name: "StockApi", routeTemplate: "stocks/{action}/{symbol}", defaults: new { symbol = RouteParameter.Optional, controller = "StockApi" } ); // WebApi Configuration to hook up formatters and message handlers // optional RegisterApis(GlobalConfiguration.Configuration); } public static void RegisterApis(HttpConfiguration config) { // Add JavaScriptSerializer formatter instead - add at top to make default //config.Formatters.Insert(0, new JavaScriptSerializerFormatter()); // Add Json.net formatter - add at the top so it fires first! // This leaves the old one in place so JsonValue/JsonObject/JsonArray still are handled config.Formatters.Insert(0, new JsonNetFormatter()); } One thing to remember here is the GlobalConfiguration object which is Web API's static configuration instance. I think this thing is seriously misnamed given that GlobalConfiguration could stand for anything and so is hard to discover if you don't know what you're looking for. How about WebApiConfiguration or something more descriptive? Anyway, once you know what it is you can use the Formatters collection to insert your custom formatter. Note that I insert my formatter at the top of the list so it takes precedence over the default formatter. I also am not removing the old formatter because I still want JsonValue/JsonObject/JsonArray to be handled by the default serialization mechanism. Since they process in sequence and I exclude processing for these types JsonValue et al. still get properly serialized/deserialized. Summary Currently DataContractJsonSerializer in Web API is a pain, but at least we have the ability with relatively limited effort to replace the MediaTypeFormatter and plug in our own JSON serializer. This is useful for many scenarios - if you have existing client applications that used MVC JsonResult or ASP.NET AJAX results from ASMX AJAX services you can plug in the JavaScript serializer and get exactly the same serializer you used in the past so your results will be the same and don't potentially break clients. JSON serializers do vary a bit in how they serialize some of the more complex types (like Dictionaries and dates for example) and so if you're migrating it might be helpful to ensure your client code doesn't break when you switch to ASP.NET Web API. Going forward it looks like Microsoft is planning on plugging in Json.Net into Web API and make that the default. I think that's an awesome choice since Json.net has been around forever, is fast and easy to use and provides a ton of functionality as part of this great library. I just wish Microsoft would have figured this out sooner instead of now at the last minute integrating with it especially given that Json.Net has a similar set of lower level JSON objects JsonValue/JsonObject etc. which now will end up being duplicated by the native System.Json stuff. It's not like we don't already have enough confusion regarding which JSON serializer to use (JavaScriptSerializer, DataContractJsonSerializer, JsonValue/JsonObject/JsonArray and now Json.net). For years I've been using my own JSON serializer because the built in choices are both limited. However, with an official encorsement of Json.Net I'm happily moving on to use that in my applications. Let's see and hope Microsoft gets this right before ASP.NET Web API goes gold.© Rick Strahl, West Wind Technologies, 2005-2012Posted in Web Api  AJAX  ASP.NET   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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  • SQL Monitor’s data repository

    - by Chris Lambrou
    As one of the developers of SQL Monitor, I often get requests passed on by our support people from customers who are looking to dip into SQL Monitor’s own data repository, in order to pull out bits of information that they’re interested in. Since there’s clearly interest out there in playing around directly with the data repository, I thought I’d write some blog posts to start to describe how it all works. The hardest part for me is knowing where to begin, since the schema of the data repository is pretty big. Hmmm… I guess it’s tricky for anyone to write anything but the most trivial of queries against the data repository without understanding the hierarchy of monitored objects, so perhaps my first post should start there. I always imagine that whenever a customer fires up SSMS and starts to explore their SQL Monitor data repository database, they become immediately bewildered by the schema – that was certainly my experience when I did so for the first time. The following query shows the number of different object types in the data repository schema: SELECT type_desc, COUNT(*) AS [count] FROM sys.objects GROUP BY type_desc ORDER BY type_desc;  type_desccount 1DEFAULT_CONSTRAINT63 2FOREIGN_KEY_CONSTRAINT181 3INTERNAL_TABLE3 4PRIMARY_KEY_CONSTRAINT190 5SERVICE_QUEUE3 6SQL_INLINE_TABLE_VALUED_FUNCTION381 7SQL_SCALAR_FUNCTION2 8SQL_STORED_PROCEDURE100 9SYSTEM_TABLE41 10UNIQUE_CONSTRAINT54 11USER_TABLE193 12VIEW124 With 193 tables, 124 views, 100 stored procedures and 381 table valued functions, that’s quite a hefty schema, and when you browse through it using SSMS, it can be a bit daunting at first. So, where to begin? Well, let’s narrow things down a bit and only look at the tables belonging to the data schema. That’s where all of the collected monitoring data is stored by SQL Monitor. The following query gives us the names of those tables: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' ORDER BY sch.name, obj.name; This query still returns 110 tables. I won’t show them all here, but let’s have a look at the first few of them:  name 1data.Cluster_Keys 2data.Cluster_Machine_ClockSkew_UnstableSamples 3data.Cluster_Machine_Cluster_StableSamples 4data.Cluster_Machine_Keys 5data.Cluster_Machine_LogicalDisk_Capacity_StableSamples 6data.Cluster_Machine_LogicalDisk_Keys 7data.Cluster_Machine_LogicalDisk_Sightings 8data.Cluster_Machine_LogicalDisk_UnstableSamples 9data.Cluster_Machine_LogicalDisk_Volume_StableSamples 10data.Cluster_Machine_Memory_Capacity_StableSamples 11data.Cluster_Machine_Memory_UnstableSamples 12data.Cluster_Machine_Network_Capacity_StableSamples 13data.Cluster_Machine_Network_Keys 14data.Cluster_Machine_Network_Sightings 15data.Cluster_Machine_Network_UnstableSamples 16data.Cluster_Machine_OperatingSystem_StableSamples 17data.Cluster_Machine_Ping_UnstableSamples 18data.Cluster_Machine_Process_Instances 19data.Cluster_Machine_Process_Keys 20data.Cluster_Machine_Process_Owner_Instances 21data.Cluster_Machine_Process_Sightings 22data.Cluster_Machine_Process_UnstableSamples 23… There are two things I want to draw your attention to: The table names describe a hierarchy of the different types of object that are monitored by SQL Monitor (e.g. clusters, machines and disks). For each object type in the hierarchy, there are multiple tables, ending in the suffixes _Keys, _Sightings, _StableSamples and _UnstableSamples. Not every object type has a table for every suffix, but the _Keys suffix is especially important and a _Keys table does indeed exist for every object type. In fact, if we limit the query to return only those tables ending in _Keys, we reveal the full object hierarchy: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' AND obj.name LIKE '%_Keys' ORDER BY sch.name, obj.name;  name 1data.Cluster_Keys 2data.Cluster_Machine_Keys 3data.Cluster_Machine_LogicalDisk_Keys 4data.Cluster_Machine_Network_Keys 5data.Cluster_Machine_Process_Keys 6data.Cluster_Machine_Services_Keys 7data.Cluster_ResourceGroup_Keys 8data.Cluster_ResourceGroup_Resource_Keys 9data.Cluster_SqlServer_Agent_Job_History_Keys 10data.Cluster_SqlServer_Agent_Job_Keys 11data.Cluster_SqlServer_Database_BackupType_Backup_Keys 12data.Cluster_SqlServer_Database_BackupType_Keys 13data.Cluster_SqlServer_Database_CustomMetric_Keys 14data.Cluster_SqlServer_Database_File_Keys 15data.Cluster_SqlServer_Database_Keys 16data.Cluster_SqlServer_Database_Table_Index_Keys 17data.Cluster_SqlServer_Database_Table_Keys 18data.Cluster_SqlServer_Error_Keys 19data.Cluster_SqlServer_Keys 20data.Cluster_SqlServer_Services_Keys 21data.Cluster_SqlServer_SqlProcess_Keys 22data.Cluster_SqlServer_TopQueries_Keys 23data.Cluster_SqlServer_Trace_Keys 24data.Group_Keys The full object type hierarchy looks like this: Cluster Machine LogicalDisk Network Process Services ResourceGroup Resource SqlServer Agent Job History Database BackupType Backup CustomMetric File Table Index Error Services SqlProcess TopQueries Trace Group Okay, but what about the individual objects themselves represented at each level in this hierarchy? Well that’s what the _Keys tables are for. This is probably best illustrated by way of a simple example – how can I query my own data repository to find the databases on my own PC for which monitoring data has been collected? Like this: SELECT clstr._Name AS cluster_name, srvr._Name AS instance_name, db._Name AS database_name FROM data.Cluster_SqlServer_Database_Keys db JOIN data.Cluster_SqlServer_Keys srvr ON db.ParentId = srvr.Id -- Note here how the parent of a Database is a Server JOIN data.Cluster_Keys clstr ON srvr.ParentId = clstr.Id -- Note here how the parent of a Server is a Cluster WHERE clstr._Name = 'dev-chrisl2' -- This is the hostname of my own PC ORDER BY clstr._Name, srvr._Name, db._Name;  cluster_nameinstance_namedatabase_name 1dev-chrisl2SqlMonitorData 2dev-chrisl2master 3dev-chrisl2model 4dev-chrisl2msdb 5dev-chrisl2mssqlsystemresource 6dev-chrisl2tempdb 7dev-chrisl2sql2005SqlMonitorData 8dev-chrisl2sql2005TestDatabase 9dev-chrisl2sql2005master 10dev-chrisl2sql2005model 11dev-chrisl2sql2005msdb 12dev-chrisl2sql2005mssqlsystemresource 13dev-chrisl2sql2005tempdb 14dev-chrisl2sql2008SqlMonitorData 15dev-chrisl2sql2008master 16dev-chrisl2sql2008model 17dev-chrisl2sql2008msdb 18dev-chrisl2sql2008mssqlsystemresource 19dev-chrisl2sql2008tempdb These results show that I have three SQL Server instances on my machine (a default instance, one named sql2005 and one named sql2008), and each instance has the usual set of system databases, along with a database named SqlMonitorData. Basically, this is where I test SQL Monitor on different versions of SQL Server, when I’m developing. There are a few important things we can learn from this query: Each _Keys table has a column named Id. This is the primary key. Each _Keys table has a column named ParentId. A foreign key relationship is defined between each _Keys table and its parent _Keys table in the hierarchy. There are two exceptions to this, Cluster_Keys and Group_Keys, because clusters and groups live at the root level of the object hierarchy. Each _Keys table has a column named _Name. This is used to uniquely identify objects in the table within the scope of the same shared parent object. Actually, that last item isn’t always true. In some cases, the _Name column is actually called something else. For example, the data.Cluster_Machine_Services_Keys table has a column named _ServiceName instead of _Name (sorry for the inconsistency). In other cases, a name isn’t sufficient to uniquely identify an object. For example, right now my PC has multiple processes running, all sharing the same name, Chrome (one for each tab open in my web-browser). In such cases, multiple columns are used to uniquely identify an object within the scope of the same shared parent object. Well, that’s it for now. I’ve given you enough information for you to explore the _Keys tables to see how objects are stored in your own data repositories. In a future post, I’ll try to explain how monitoring data is stored for each object, using the _StableSamples and _UnstableSamples tables. If you have any questions about this post, or suggestions for future posts, just submit them in the comments section below.

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  • SQL University: Database testing and refactoring tools and examples

    - by Mladen Prajdic
    This is a post for a great idea called SQL University started by Jorge Segarra also famously known as SqlChicken on Twitter. It’s a collection of blog posts on different database related topics contributed by several smart people all over the world. So this week is mine and we’ll be talking about database testing and refactoring. In 3 posts we’ll cover: SQLU part 1 - What and why of database testing SQLU part 2 - What and why of database refactoring SQLU part 3 - Database testing and refactoring tools and examples This is the third and last part of the series and in it we’ll take a look at tools we can test and refactor with plus some an example of the both. Tools of the trade First a few thoughts about how to go about testing a database. I'm firmily against any testing tools that go into the database itself or need an extra database. Unit tests for the database and applications using the database should all be in one place using the same technology. By using database specific frameworks we fragment our tests into many places and increase test system complexity. Let’s take a look at some testing tools. 1. NUnit, xUnit, MbUnit All three are .Net testing frameworks meant to unit test .Net application. But we can test databases with them just fine. I use NUnit because I’ve always used it for work and personal projects. One day this might change. So the thing to remember is to be flexible if something better comes along. All three are quite similar and you should be able to switch between them without much problem. 2. TSQLUnit As much as this framework is helpful for the non-C# savvy folks I don’t like it for the reason I stated above. It lives in the database and thus fragments the testing infrastructure. Also it appears that it’s not being actively developed anymore. 3. DbFit I haven’t had the pleasure of trying this tool just yet but it’s on my to-do list. From what I’ve read and heard Gojko Adzic (@gojkoadzic on Twitter) has done a remarkable job with it. 4. Redgate SQL Refactor and Apex SQL Refactor Neither of these refactoring tools are free, however if you have hardcore refactoring planned they are worth while looking into. I’ve only used the Red Gate’s Refactor and was quite impressed with it. 5. Reverting the database state I’ve talked before about ways to revert a database to pre-test state after unit testing. This still holds and I haven’t changed my mind. Also make sure to read the comments as they are quite informative. I especially like the idea of setting up and tearing down the schema for each test group with NHibernate. Testing and refactoring example We’ll take a look at the simple schema and data test for a view and refactoring the SELECT * in that view. We’ll use a single table PhoneNumbers with ID and Phone columns. Then we’ll refactor the Phone column into 3 columns Prefix, Number and Suffix. Lastly we’ll remove the original Phone column. Then we’ll check how the view behaves with tests in NUnit. The comments in code explain the problem so be sure to read them. I’m assuming you know NUnit and C#. T-SQL Code C# test code USE tempdbGOCREATE TABLE PhoneNumbers( ID INT IDENTITY(1,1), Phone VARCHAR(20))GOINSERT INTO PhoneNumbers(Phone)SELECT '111 222333 444' UNION ALLSELECT '555 666777 888'GO-- notice we don't have WITH SCHEMABINDINGCREATE VIEW vPhoneNumbersAS SELECT * FROM PhoneNumbersGO-- Let's take a look at what the view returns -- If we add a new columns and rows both tests will failSELECT *FROM vPhoneNumbers GO -- DoesViewReturnCorrectColumns test will SUCCEED -- DoesViewReturnCorrectData test will SUCCEED -- refactor to split Phone column into 3 partsALTER TABLE PhoneNumbers ADD Prefix VARCHAR(3)ALTER TABLE PhoneNumbers ADD Number VARCHAR(6)ALTER TABLE PhoneNumbers ADD Suffix VARCHAR(3)GO-- update the new columnsUPDATE PhoneNumbers SET Prefix = LEFT(Phone, 3), Number = SUBSTRING(Phone, 5, 6), Suffix = RIGHT(Phone, 3)GO-- remove the old columnALTER TABLE PhoneNumbers DROP COLUMN PhoneGO-- This returns unexpected results!-- it returns 2 columns ID and Phone even though -- we don't have a Phone column anymore.-- Notice that the data is from the Prefix column-- This is a danger of SELECT *SELECT *FROM vPhoneNumbers -- DoesViewReturnCorrectColumns test will SUCCEED -- DoesViewReturnCorrectData test will FAIL -- for a fix we have to call sp_refreshview -- to refresh the view definitionEXEC sp_refreshview 'vPhoneNumbers'-- after the refresh the view returns 4 columns-- this breaks the input/output behavior of the database-- which refactoring MUST NOT doSELECT *FROM vPhoneNumbers -- DoesViewReturnCorrectColumns test will FAIL -- DoesViewReturnCorrectData test will FAIL -- to fix the input/output behavior change problem -- we have to concat the 3 columns into one named PhoneALTER VIEW vPhoneNumbersASSELECT ID, Prefix + ' ' + Number + ' ' + Suffix AS PhoneFROM PhoneNumbersGO-- now it works as expectedSELECT *FROM vPhoneNumbers -- DoesViewReturnCorrectColumns test will SUCCEED -- DoesViewReturnCorrectData test will SUCCEED -- clean upDROP VIEW vPhoneNumbersDROP TABLE PhoneNumbers [Test]public void DoesViewReturnCoorectColumns(){ // conn is a valid SqlConnection to the server's tempdb // note the SET FMTONLY ON with which we return only schema and no data using (SqlCommand cmd = new SqlCommand("SET FMTONLY ON; SELECT * FROM vPhoneNumbers", conn)) { DataTable dt = new DataTable(); dt.Load(cmd.ExecuteReader(CommandBehavior.CloseConnection)); // test returned schema: number of columns, column names and data types Assert.AreEqual(dt.Columns.Count, 2); Assert.AreEqual(dt.Columns[0].Caption, "ID"); Assert.AreEqual(dt.Columns[0].DataType, typeof(int)); Assert.AreEqual(dt.Columns[1].Caption, "Phone"); Assert.AreEqual(dt.Columns[1].DataType, typeof(string)); }} [Test]public void DoesViewReturnCorrectData(){ // conn is a valid SqlConnection to the server's tempdb using (SqlCommand cmd = new SqlCommand("SELECT * FROM vPhoneNumbers", conn)) { DataTable dt = new DataTable(); dt.Load(cmd.ExecuteReader(CommandBehavior.CloseConnection)); // test returned data: number of rows and their values Assert.AreEqual(dt.Rows.Count, 2); Assert.AreEqual(dt.Rows[0]["ID"], 1); Assert.AreEqual(dt.Rows[0]["Phone"], "111 222333 444"); Assert.AreEqual(dt.Rows[1]["ID"], 2); Assert.AreEqual(dt.Rows[1]["Phone"], "555 666777 888"); }}   With this simple example we’ve seen how a very simple schema can cause a lot of problems in the whole application/database system if it doesn’t have tests. Imagine what would happen if some outside process would depend on that view. It would get wrong data and propagate it silently throughout the system. And that is not good. So have tests at least for the crucial parts of your systems. And with that we conclude the Database Testing and Refactoring week at SQL University. Hope you learned something new and enjoy the learning weeks to come. Have fun!

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  • SQL University: What and why of database testing

    - by Mladen Prajdic
    This is a post for a great idea called SQL University started by Jorge Segarra also famously known as SqlChicken on Twitter. It’s a collection of blog posts on different database related topics contributed by several smart people all over the world. So this week is mine and we’ll be talking about database testing and refactoring. In 3 posts we’ll cover: SQLU part 1 - What and why of database testing SQLU part 2 - What and why of database refactoring SQLU part 2 – Tools of the trade With that out of the way let us sharpen our pencils and get going. Why test a database The sad state of the industry today is that there is very little emphasis on testing in general. Test driven development is still a small niche of the programming world while refactoring is even smaller. The cause of this is the inability of developers to convince themselves and their managers that writing tests is beneficial. At the moment they are mostly viewed as waste of time. This is because the average person (let’s not fool ourselves, we’re all average) is unable to think about lower future costs in relation to little more current work. It’s orders of magnitude easier to know about the current costs in relation to current amount of work. That’s why programmers convince themselves testing is a waste of time. However we have to ask ourselves what tests are really about? Maybe finding bugs? No, not really. If we introduce bugs, we’re likely to write test around those bugs too. But yes we can find some bugs with tests. The main point of tests is to have reproducible repeatability in our systems. By having a code base largely covered by tests we can know with better certainty what a small code change can break in other parts of the system. By having repeatability we can make code changes with confidence, since we know we’ll see what breaks in other tests. And here comes the inability to estimate future costs. By spending just a few more hours writing those tests we’d know instantly what broke where. Imagine we fix a reported bug. We check-in the code, deploy it and the users are happy. Until we get a call 2 weeks later about a certain monthly process has stopped working. What we don’t know is that this process was developed by a long gone coworker and for some reason it relied on that same bug we’ve happily fixed. There’s no way we could’ve known that. We say OK and go in and fix the monthly process. But what we have no clue about is that there’s this ETL job that relied on data from that monthly process. Now that we’ve fixed the process it’s giving unexpected (yet correct since we fixed it) data to the ETL job. So we have to fix that too. But there’s this part of the app we coded that relies on data from that exact ETL job. And just like that we enter the “Loop of maintenance horror”. With the loop eventually comes blame. Here’s a nice tip for all developers and DBAs out there: If you make a mistake man up and admit to it. All of the above is valid for any kind of software development. Keeping this in mind the database is nothing other than just a part of the application. But a big part! One reason why testing a database is even more important than testing an application is that one database is usually accessed from multiple applications and processes. This makes it the central and vital part of the enterprise software infrastructure. Knowing all this can we really afford not to have tests? What to test in a database Now that we’ve decided we’ll dive into this testing thing we have to ask ourselves what needs to be tested? The short answer is: everything. The long answer is: read on! There are 2 main ways of doing tests: Black box and White box testing. Black box testing means we have no idea how the system internals are built and we only have access to it’s inputs and outputs. With it we test that the internal changes to the system haven’t caused the input/output behavior of the system to change. The most important thing to test here are the edge conditions. It’s where most programs break. Having good edge condition tests we can be more confident that the systems changes won’t break. White box testing has the full knowledge of the system internals. With it we test the internal system changes, different states of the application, etc… White and Black box tests should be complementary to each other as they are very much interconnected. Testing database routines includes testing stored procedures, views, user defined functions and anything you use to access the data with. Database routines are your input/output interface to the database system. They count as black box testing. We test then for 2 things: Data and schema. When testing schema we only care about the columns and the data types they’re returning. After all the schema is the contract to the out side systems. If it changes we usually have to change the applications accessing it. One helpful T-SQL command when doing schema tests is SET FMTONLY ON. It tells the SQL Server to return only empty results sets. This speeds up tests because it doesn’t return any data to the client. After we’ve validated the schema we have to test the returned data. There no other way to do this but to have expected data known before the tests executes and comparing that data to the database routine output. Testing Authentication and Authorization helps us validate who has access to the SQL Server box (Authentication) and who has access to certain database objects (Authorization). For desktop applications and windows authentication this works well. But the biggest problem here are web apps. They usually connect to the database as a single user. Please ensure that that user is not SA or an account with admin privileges. That is just bad. Load testing ensures us that our database can handle peak loads. One often overlooked tool for load testing is Microsoft’s OSTRESS tool. It’s part of RML utilities (x86, x64) for SQL Server and can help determine if our database server can handle loads like 100 simultaneous users each doing 10 requests per second. SQL Profiler can also help us here by looking at why certain queries are slow and what to do to fix them.   One particular problem to think about is how to begin testing existing databases. First thing we have to do is to get to know those databases. We can’t test something when we don’t know how it works. To do this we have to talk to the users of the applications accessing the database, run SQL Profiler to see what queries are being run, use existing documentation to decipher all the object relationships, etc… The way to approach this is to choose one part of the database (say a logical grouping of tables that go together) and filter our traces accordingly. Once we’ve done that we move on to the next grouping and so on until we’ve covered the whole database. Then we move on to the next one. Database Testing is a topic that we can spent many hours discussing but let this be a nice intro to the world of database testing. See you in the next post.

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  • Master Data

    - by david.butler(at)oracle.com
    Let's take a deeper look at what we mean when we talk about 'Master' data. In its most general sense, master data is data that exists in more than one operational application. These are the applications that automate business processes. These applications require significant amounts of data to function correctly.  This includes data about the objects that are involved in transactions, as well as the transaction data itself.  For example, when a customer buys a product, the transaction is managed by a sales application.  The objects of the transaction are the Customer and the Product.  The transactional data is the time, place, price, discount, payment methods, etc. used at the point of sale. Many thousands of transactional data attributes are needed within the application. These important data elements are local to the applications and have no bearing on other applications. Harmonization and synchronization across applications is not necessary. The Customer and Product objects of the transaction also have a large number of attributes. Customer for example, includes hierarchies, hierarchical and matrixed relationships, contacts, classifications, preferences, accounts, identifiers, profiles, and addresses galore for 'ship to', 'mail to'; 'service at'; etc. Dozens of attributes exist for individuals, hundreds for organizations, and thousands for products. This data has meaning beyond any particular application. It exists in many applications and drives the vital cross application enterprise business processes. These are the processes that define and differentiate the organization. At every decision point, information about the objects of the process determines the direction of the process flow. This is the nature of the data that exists in more than one application, and this is why we call it 'master data'. Let me elaborate. Parties Oracle has developed a party schema to model all participants in your daily business operations. It models people, organizations, groups, customers, contacts, employees, and suppliers. It models their accounts, locations, classifications, and preferences.  And most importantly, it models the vast array of hierarchical and matrixed relationships that exist between all the participants in your real world operations.  The model logically separates people and organizations from their relationships and accounts.  This separation creates flexibility unmatched in the industry and accounts for the fact that the Oracle schema for Customers, Suppliers, and Accounts is a true superset of the wide variety of commercial and homegrown customer models in existence. Sites Sites are places where business is conducted. They can be addresses, clusters such as retail malls, locations within a cluster, floors within a building, places where meters are located, rooms on floors, etc.  Fully understanding all attributes of a site is key to many business processes. Attributes such as 'noise abatement policy' at a point of delivery, or the size of an oven in a business kitchen drive day-to-day activities such as delivery schedules or food promotions. Typically this kind of data is siloed in departments and scattered across applications and spreadsheets.  This leads to conflicting information and poor operational efficiencies. Oracle's Global Single Schema can hold all site attributes in one place and enables a single version of authoritative site information across the enterprise. Products and Services The Oracle Global Single Schema also includes a number of entities that define the products and services a company creates and offers for sale. Key entities include Items organized into Catalogs and Price Lists. The Catalog structures provide for the ability to capture different views of a product such as engineering, manufacturing, and service which are based on a unified product model. As a result, designers, manufacturing engineers, purchasers and partners can work simultaneously on a common product definition. The Catalog schema allows for unlimited attributes, combines them into meaningful groups, and maps them to catalog categories to track these different types of information. The model also maps an unlimited number of functional structures for each item. For example, multiple Bills of Material (BOMs) can be constructed representing requirements BOM, features BOM, and packaging BOM for an item. The Catalog model also supports hierarchical information about each item and all standard Global Data Synchronization attributes. Business Processes Utilizing Linked Data Entities Each business entity codified into a centralized master data environment significantly improves the efficiency of the automated business processes that use the consolidated data.  When all the key business entities used by an organization's process are so consolidated, the advantages are multiplied.  The primary reason for business process breakdowns (i.e. data errors across application boundaries) is eliminated. All processes are positively impacted and business process automation is itself automated.  I like to use the "Call to Resolution" business process as an example to help illustrate this important point. It involves call center applications, service applications, RMA applications, transportation applications, inventory applications, etc. Customer, Site, Product and Supplier master data must all be correct and consistent across these applications.  What's more, the data relationships between customer and product, and product and suppliers must be right. This is the minimum quality needed to insure the business process flows without error. But that is not the end of the story. Critical master data attributes such as customer loyalty, profitability, credit worthiness, and propensity to buy can optimize the call center point of contact component of the process. Critical product information such as alternative parts or equivalent products can optimize the resolution selected by the process. A comprehensive understanding of the 'service at' location can help insure multiple trips are avoided in the process. Full supplier information on reliability, delivery delays, and potential alternates can prevent supplier exceptions and play a significant role in optimizing the process.  In other words, these master data attributes enable the optimization of the "Call to Resolution" enterprise business process. Master data supports and guides business process flows. Thus the phrase 'Master Data' is indeed appropriate. MDM is the software that houses, manages, and governs the master data that resides in all applications and controls the enterprise business processes. A complete master data solution takes a data model that holds fully attributed master data entities and their inter-relationships. Oracle has this model. Oracle, with its deep understanding of application data is the logical choice for managing all your master data within the enterprise whether or not your organization actually runs any Oracle Applications.

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  • Use Drive Mirroring for Instant Backup in Windows 7

    - by Trevor Bekolay
    Even with the best backup solution, a hard drive crash means you’ll lose a few hours of work. By enabling drive mirroring in Windows 7, you’ll always have an up-to-date copy of your data. Windows 7’s mirroring – which is only available in Professional, Enterprise, and Ultimate editions – is a software implementation of RAID 1, which means that two or more disks are holding the exact same data. The files are constantly kept in sync, so that if one of the disks fails, you won’t lose any data. Note that mirroring is not technically a backup solution, because if you accidentally delete a file, it’s gone from both hard disks (though you may be able to recover the file). As an additional caveat, having mirrored disks requires changing them to “dynamic disks,” which can only be read within modern versions of Windows (you may have problems working with a dynamic disk in other operating systems or in older versions of Windows). See this Wikipedia page for more information. You will need at least one empty disk to set up disk mirroring. We’ll show you how to mirror an existing disk (of equal or lesser size) without losing any data on the mirrored drive, and how to set up two empty disks as mirrored copies from the get-go. Mirroring an Existing Drive Click on the start button and type partitions in the search box. Click on the Create and format hard disk partitions entry that shows up. Alternatively, if you’ve disabled the search box, press Win+R to open the Run window and type in: diskmgmt.msc The Disk Management window will appear. We’ve got a small disk, labeled OldData, that we want to mirror in a second disk of the same size. Note: The disk that you will use to mirror the existing disk must be unallocated. If it is not, then right-click on it and select Delete Volume… to mark it as unallocated. This will destroy any data on that drive. Right-click on the existing disk that you want to mirror. Select Add Mirror…. Select the disk that you want to use to mirror the existing disk’s data and press Add Mirror. You will be warned that this process will change the existing disk from basic to dynamic. Note that this process will not delete any data on the disk! The new disk will be marked as a mirror, and it will starting copying data from the existing drive to the new one. Eventually the drives will be synced up (it can take a while), and any data added to the E: drive will exist on both physical hard drives. Setting Up Two New Drives as Mirrored If you have two new equal-sized drives, you can format them to be mirrored copies of each other from the get-go. Open the Disk Management window as described above. Make sure that the drives are unallocated. If they’re not, and you don’t need the data on either of them, right-click and select Delete volume…. Right-click on one of the unallocated drives and select New Mirrored Volume…. A wizard will pop up. Click Next. Click on the drives you want to hold the mirrored data and click Add. Note that you can add any number of drives. Click Next. Assign it a drive letter that makes sense, and then click Next. You’re limited to using the NTFS file system for mirrored drives, so enter a volume label, enable compression if you want, and then click Next. Click Finish to start formatting the drives. You will be warned that the new drives will be converted to dynamic disks. And that’s it! You now have two mirrored drives. Any files added to E: will reside on both physical disks, in case something happens to one of them. Conclusion While the switch from basic to dynamic disks can be a problem for people who dual-boot into another operating system, setting up drive mirroring is an easy way to make sure that your data can be recovered in case of a hard drive crash. Of course, even with drive mirroring, we advocate regular backups to external drives or online backup services. Similar Articles Productive Geek Tips Rebit Backup Software [Review]Disabling Instant Search in Outlook 2007Restore Files from Backups on Windows Home ServerSecond Copy 7 [Review]Backup Windows Home Server Folders to an External Hard Drive TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips CloudBerry Online Backup 1.5 for Windows Home Server Snagit 10 VMware Workstation 7 Acronis Online Backup Windows Firewall with Advanced Security – How To Guides Sculptris 1.0, 3D Drawing app AceStock, a Tiny Desktop Quote Monitor Gmail Button Addon (Firefox) Hyperwords addon (Firefox) Backup Outlook 2010

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 5

    - by MarkPearl
    Learning Outcomes Describe the operation of a memory cell Explain the difference between DRAM and SRAM Discuss the different types of ROM Explain the concepts of a hard failure and a soft error respectively Describe SDRAM organization Semiconductor Main Memory The two traditional forms of RAM used in computers are DRAM and SRAM DRAM (Dynamic RAM) Divided into two technologies… Dynamic Static Dynamic RAM is made with cells that store data as charge on capacitors. The presence or absence of charge in a capacitor is interpreted as a binary 1 or 0. Because capacitors have natural tendency to discharge, dynamic RAM requires periodic charge refreshing to maintain data storage. The term dynamic refers to the tendency of the stored charge to leak away, even with power continuously applied. Although the DRAM cell is used to store a single bit (0 or 1), it is essentially an analogue device. The capacitor can store any charge value within a range, a threshold value determines whether the charge is interpreted as a 1 or 0. SRAM (Static RAM) SRAM is a digital device that uses the same logic elements used in the processor. In SRAM, binary values are stored using traditional flip flop logic configurations. SRAM will hold its data as along as power is supplied to it. Unlike DRAM, no refresh is required to retain data. SRAM vs. DRAM DRAM is simpler and smaller than SRAM. Thus it is more dense and less expensive than SRAM. The cost of the refreshing circuitry for DRAM needs to be considered, but if the machine requires a large amount of memory, DRAM turns out to be cheaper than SRAM. SRAMS are somewhat faster than DRAM, thus SRAM is generally used for cache memory and DRAM is used for main memory. Types of ROM Read Only Memory (ROM) contains a permanent pattern of data that cannot be changed. ROM is non volatile meaning no power source is required to maintain the bit values in memory. While it is possible to read a ROM, it is not possible to write new data into it. An important application of ROM is microprogramming, other applications include library subroutines for frequently wanted functions, System programs, Function tables. A ROM is created like any other integrated circuit chip, with the data actually wired into the chip as part of the fabrication process. To reduce costs of fabrication, we have PROMS. PROMS are… Written only once Non-volatile Written after fabrication Another variation of ROM is the read-mostly memory, which is useful for applications in which read operations are far more frequent than write operations, but for which non volatile storage is required. There are three common forms of read-mostly memory, namely… EPROM EEPROM Flash memory Error Correction Semiconductor memory is subject to errors, which can be classed into two categories… Hard failure – Permanent physical defect so that the memory cell or cells cannot reliably store data Soft failure – Random error that alters the contents of one or more memory cells without damaging the memory (common cause includes power supply issues, etc.) Most modern main memory systems include logic for both detecting and correcting errors. Error detection works as follows… When data is to be read into memory, a calculation is performed on the data to produce a code Both the code and the data are stored When the previously stored word is read out, the code is used to detect and possibly correct errors The error checking provides one of 3 possible results… No errors are detected – the fetched data bits are sent out An error is detected, and it is possible to correct the error. The data bits plus error correction bits are fed into a corrector, which produces a corrected set of bits to be sent out An error is detected, but it is not possible to correct it. This condition is reported Hamming Code See wiki for detailed explanation. We will probably need to know how to do a hemming code – refer to the textbook (pg. 188 – 189) Advanced DRAM organization One of the most critical system bottlenecks when using high-performance processors is the interface to main memory. This interface is the most important pathway in the entire computer system. The basic building block of main memory remains the DRAM chip. In recent years a number of enhancements to the basic DRAM architecture have been explored, and some of these are now on the market including… SDRAM (Synchronous DRAM) DDR-DRAM RDRAM SDRAM (Synchronous DRAM) SDRAM exchanges data with the processor synchronized to an external clock signal and running at the full speed of the processor/memory bus without imposing wait states. SDRAM employs a burst mode to eliminate the address setup time and row and column line precharge time after the first access In burst mode a series of data bits can be clocked out rapidly after the first bit has been accessed SDRAM has a multiple bank internal architecture that improves opportunities for on chip parallelism SDRAM performs best when it is transferring large blocks of data serially There is now an enhanced version of SDRAM known as double data rate SDRAM or DDR-SDRAM that overcomes the once-per-cycle limitation of SDRAM

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  • InnoDB Compression Improvements in MySQL 5.6

    - by Inaam Rana
    MySQL 5.6 comes with significant improvements for the compression support inside InnoDB. The enhancements that we'll talk about in this piece are also a good example of community contributions. The work on these was conceived, implemented and contributed by the engineers at Facebook. Before we plunge into the details let us familiarize ourselves with some of the key concepts surrounding InnoDB compression. In InnoDB compressed pages are fixed size. Supported sizes are 1, 2, 4, 8 and 16K. The compressed page size is specified at table creation time. InnoDB uses zlib for compression. InnoDB buffer pool will attempt to cache compressed pages like normal pages. However, whenever a page is actively used by a transaction, we'll always have the uncompressed version of the page as well i.e.: we can have a page in the buffer pool in compressed only form or in a state where we have both the compressed page and uncompressed version but we'll never have a page in uncompressed only form. On-disk we'll always only have the compressed page. When both compressed and uncompressed images are present in the buffer pool they are always kept in sync i.e.: changes are applied to both atomically. Recompression happens when changes are made to the compressed data. In order to minimize recompressions InnoDB maintains a modification log within a compressed page. This is the extra space available in the page after compression and it is used to log modifications to the compressed data thus avoiding recompressions. DELETE (and ROLLBACK of DELETE) and purge can be performed without recompressing the page. This is because the delete-mark bit and the system fields DB_TRX_ID and DB_ROLL_PTR are stored in uncompressed format on the compressed page. A record can be purged by shuffling entries in the compressed page directory. This can also be useful for updates of indexed columns, because UPDATE of a key is mapped to INSERT+DELETE+purge. A compression failure happens when we attempt to recompress a page and it does not fit in the fixed size. In such case, we first try to reorganize the page and attempt to recompress and if that fails as well then we split the page into two and recompress both pages. Now lets talk about the three major improvements that we made in MySQL 5.6.Logging of Compressed Page Images:InnoDB used to log entire compressed data on the page to the redo logs when recompression happens. This was an extra safety measure to guard against the rare case where an attempt is made to do recovery using a different zlib version from the one that was used before the crash. Because recovery is a page level operation in InnoDB we have to be sure that all recompress attempts must succeed without causing a btree page split. However, writing entire compressed data images to the redo log files not only makes the operation heavy duty but can also adversely affect flushing activity. This happens because redo space is used in a circular fashion and when we generate much more than normal redo we fill up the space much more quickly and in order to reuse the redo space we have to flush the corresponding dirty pages from the buffer pool.Starting with MySQL 5.6 a new global configuration parameter innodb_log_compressed_pages. The default value is true which is same as the current behavior. If you are sure that you are not going to attempt to recover from a crash using a different version of zlib then you should set this parameter to false. This is a dynamic parameter.Compression Level:You can now set the compression level that zlib should choose to compress the data. The global parameter is innodb_compression_level - the default value is 6 (the zlib default) and allowed values are 1 to 9. Again the parameter is dynamic i.e.: you can change it on the fly.Dynamic Padding to Reduce Compression Failures:Compression failures are expensive in terms of CPU. We go through the hoops of recompress, failure, reorganize, recompress, failure and finally page split. At the same time, how often we encounter compression failure depends largely on the compressibility of the data. In MySQL 5.6, courtesy of Facebook engineers, we have an adaptive algorithm based on per-index statistics that we gather about compression operations. The idea is that if a certain index/table is experiencing too many compression failures then we should try to pack the 16K uncompressed version of the page less densely i.e.: we let some space in the 16K page go unused in an attempt that the recompression won't end up in a failure. In other words, we dynamically keep adding 'pad' to the 16K page till we get compression failures within an agreeable range. It works the other way as well, that is we'll keep removing the pad if failure rate is fairly low. To tune the padding effort two configuration variables are exposed. innodb_compression_failure_threshold_pct: default 5, range 0 - 100,dynamic, implies the percentage of compress ops to fail before we start using to padding. Value 0 has a special meaning of disabling the padding. innodb_compression_pad_pct_max: default 50, range 0 - 75, dynamic, the  maximum percentage of uncompressed data page that can be reserved as pad.

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  • spring mvc 3.0 small web application not quite working

    - by lurscher
    Hi, i'm creating a very simple (hello World quality) web application using spring mvc 3.0. when deploying the application on tomcat 6.0.26 and i try to open http://localhost:8080/protoweb/helloWorld.html i get 404, resource /protoweb/WEB-INF/jsp/helloWorld.jsp is not available. The funny thing is that there IS a helloWorld.jsp in there. any idea what i'm doing wrong? here is my web.xml <?xml version="1.0" encoding="UTF-8"?> <web-app xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://java.sun.com/xml/ns/javaee" xmlns:web="http://java.sun.com/xml/ns/javaee/web-app_2_5.xsd" xsi:schemaLocation="http://java.sun.com/xml/ns/javaee http://java.sun.com/xml/ns/javaee/web-app_2_5.xsd" id="WebApp_ID" version="2.5"> <display-name>hello-spring3-RC1</display-name> <context-param> <param-name>contextConfigLocation</param-name> <param-value>/WEB-INF/yummy-servlet.xml</param-value> </context-param> <listener> <listener-class>org.springframework.web.context.ContextLoaderListener</listener-class> </listener> <servlet> <servlet-name>yummy</servlet-name> <servlet-class>org.springframework.web.servlet.DispatcherServlet</servlet-class> <load-on-startup>1</load-on-startup> </servlet> <servlet-mapping> <servlet-name>yummy</servlet-name> <url-pattern>*.html</url-pattern> </servlet-mapping> <welcome-file-list> <welcome-file>index.html</welcome-file> </welcome-file-list> </web-app> my yummy-servlet.xml <?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:p="http://www.springframework.org/schema/p" xmlns:context="http://www.springframework.org/schema/context" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans-3.0.xsd http://www.springframework.org/schema/context http://www.springframework.org/schema/context/spring-context-3.0.xsd"> <context:component-scan base-package="com.mine.web.controllers"/> <bean id="jspViewResolver" class="org.springframework.web.servlet.view.InternalResourceViewResolver"> <property name="viewClass" value="org.springframework.web.servlet.view.JstlView"/> <property name="prefix" value="/WEB-INF/jsp/"/> <property name="suffix" value=".jsp"/> </bean> </beans> my very simple controller: package com.mine.web.controllers; import org.springframework.stereotype.Controller; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.servlet.ModelAndView; @Controller public class BasicController { @RequestMapping(value = "/helloWorld") public ModelAndView helloWorld() { ModelAndView mav = new ModelAndView(); mav.setViewName("helloWorld"); mav.addObject("message", "Hello some basic message for u"); return mav; } } and my webapp/jsp/helloWorld.jsp <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> <html> <head> <meta http-equiv="Content-Type" content="text/html; charset=ISO-8859-1"> <title>Hello</title> </head> <body> ${message} </body> </html> also, it might be helpful to post my pom.xml <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>com.mine</groupId> <artifactId>protoweb</artifactId> <packaging>war</packaging> <version>1.0-SNAPSHOT</version> <name>protoweb Maven Webapp</name> <url>http://maven.apache.org</url> <repositories> <repository> <id>springsource maven repo</id> <url>http://maven.springframework.org/milestone</url> </repository> </repositories> <dependencies> <dependency> <groupId>org.springframework</groupId> <artifactId>spring-webmvc</artifactId> <version>3.0.0.RC1</version> </dependency> <dependency> <groupId>junit</groupId> <artifactId>junit</artifactId> <version>3.8.1</version> <scope>test</scope> </dependency> <dependency> <groupId>javax.servlet</groupId> <artifactId>jstl</artifactId> <version>1.1.2</version> <scope>compile</scope> </dependency> </dependencies> <build> <finalName>protoweb</finalName> <plugins> <plugin> <groupId>org.codehaus.mojo</groupId> <artifactId>tomcat-maven-plugin</artifactId> <configuration> <configurationDir>tomcat</configurationDir> <url>http://localhost:8080/manager</url> <username>test</username> <password>test</password> </configuration> </plugin> </plugins> </build> </project>

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  • Spring @Transactional not creating required transaction

    - by Steve
    Ok, so I've finally bowed to peer pressure and started using Spring in my web app :-)... So I'm trying to get the transaction handling stuff to work, and I just can't seem to get it. My Spring configuration looks like this: <?xml version="1.0" encoding="UTF-8"?> <beans xmlns="http://www.springframework.org/schema/beans" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:p="http://www.springframework.org/schema/p" xmlns:tx="http://www.springframework.org/schema/tx" xsi:schemaLocation="http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd http://www.springframework.org/schema/tx http://www.springframework.org/schema/tx/spring-tx.xsd"> <bean id="groupDao" class="mil.navy.ndms.conops.common.dao.impl.jpa.GroupDao" lazy-init="true"> <property name="entityManagerFactory" ><ref bean="entityManagerFactory"/></property> </bean> <!-- enables interpretation of the @Required annotation to ensure that dependency injection actually occures --> <bean class="org.springframework.beans.factory.annotation.RequiredAnnotationBeanPostProcessor"/> <!-- enables interpretation of the @PersistenceUnit/@PersistenceContext annotations providing convenient access to EntityManagerFactory/EntityManager --> <bean class="org.springframework.orm.jpa.support.PersistenceAnnotationBeanPostProcessor"/> <!-- uses the persistence unit defined in the META-INF/persistence.xml JPA configuration file --> <bean id="entityManagerFactory" class="org.springframework.orm.jpa.LocalEntityManagerFactoryBean"> <property name="persistenceUnitName" value="CONOPS_PU" /> </bean> <!-- transaction manager for use with a single JPA EntityManagerFactory for transactional data access to a single datasource --> <bean id="jpaTransactionManager" class="org.springframework.orm.jpa.JpaTransactionManager"> <property name="entityManagerFactory" ref="entityManagerFactory"/> </bean> <!-- enables interpretation of the @Transactional annotation for declerative transaction managment using the specified JpaTransactionManager --> <tx:annotation-driven transaction-manager="jpaTransactionManager" proxy-target-class="true"/> </beans> persistence.xml: <?xml version="1.0" encoding="UTF-8"?> <persistence version="1.0" xmlns="http://java.sun.com/xml/ns/persistence" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://java.sun.com/xml/ns/persistence http://java.sun.com/xml/ns/persistence/persistence_1_0.xsd"> <persistence-unit name="CONOPS_PU" transaction-type="RESOURCE_LOCAL"> <provider>org.hibernate.ejb.HibernatePersistence</provider> ... Class mappings removed for brevity... <properties> <property name="hibernate.dialect" value="org.hibernate.dialect.Oracle10gDialect"/> <property name="hibernate.connection.autocommit" value="false"/> <property name="hibernate.connection.username" value="****"/> <property name="hibernate.connection.password" value="*****"/> <property name="hibernate.connection.driver_class" value="oracle.jdbc.OracleDriver"/> <property name="hibernate.connection.url" value="jdbc:oracle:thin:@*****:1521:*****"/> <property name="hibernate.cache.provider_class" value="org.hibernate.cache.NoCacheProvider"/> <property name="hibernate.hbm2ddl.auto" value="create"/> <property name="hibernate.show_sql" value="true"/> <property name="hibernate.format_sql" value="true"/> </properties> </persistence-unit> </persistence> The DAO method to save my domain object looks like this: @Transactional(propagation=Propagation.REQUIRES_NEW) protected final T saveOrUpdate (T model) { EntityManager em = emf.createEntityManager ( ); EntityTransaction trans = em.getTransaction ( ); System.err.println ("Transaction isActive () == " + trans.isActive ( )); if (em != null) { try { if (model.getId ( ) != null) { em.persist (model); em.flush (); } else { em.merge (model); em.flush (); } } finally { em.close (); } } return (model); } So I try to save a copy of my Group object using the following code in my test case: context = new ClassPathXmlApplicationContext(configs); dao = (GroupDao)context.getBean("groupDao"); dao.saveOrUpdate (new Group ()); This bombs with the following exception: javax.persistence.TransactionRequiredException: no transaction is in progress at org.hibernate.ejb.AbstractEntityManagerImpl.flush(AbstractEntityManagerImpl.java:301) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:48) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37) at java.lang.reflect.Method.invoke(Method.java:600) at org.springframework.orm.jpa.ExtendedEntityManagerCreator$ExtendedEntityManagerInvocationHandler.invoke(ExtendedEntityManagerCreator.java:341) at $Proxy26.flush(Unknown Source) at mil.navy.ndms.conops.common.dao.impl.jpa.GenericJPADao.saveOrUpdate(GenericJPADao.java:646) at mil.navy.ndms.conops.common.dao.impl.jpa.GroupDao.save(GroupDao.java:641) at mil.navy.ndms.conops.common.dao.impl.jpa.GroupDao$$FastClassByCGLIB$$50343b9b.invoke() at net.sf.cglib.proxy.MethodProxy.invoke(MethodProxy.java:149) at org.springframework.aop.framework.Cglib2AopProxy$DynamicAdvisedInterceptor.intercept(Cglib2AopProxy.java:622) at mil.navy.ndms.conops.common.dao.impl.jpa.GroupDao$$EnhancerByCGLIB$$7359ba58.save() at mil.navy.ndms.conops.common.dao.impl.jpa.GroupDaoTest.testGroupDaoSave(GroupDaoTest.java:91) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:48) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37) at java.lang.reflect.Method.invoke(Method.java:600) at junit.framework.TestCase.runTest(TestCase.java:164) at junit.framework.TestCase.runBare(TestCase.java:130) at junit.framework.TestResult$1.protect(TestResult.java:106) at junit.framework.TestResult.runProtected(TestResult.java:124) at junit.framework.TestResult.run(TestResult.java:109) at junit.framework.TestCase.run(TestCase.java:120) at junit.framework.TestSuite.runTest(TestSuite.java:230) at junit.framework.TestSuite.run(TestSuite.java:225) at org.eclipse.jdt.internal.junit.runner.junit3.JUnit3TestReference.run(JUnit3TestReference.java:130) at org.eclipse.jdt.internal.junit.runner.TestExecution.run(TestExecution.java:38) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.runTests(RemoteTestRunner.java:460) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.runTests(RemoteTestRunner.java:673) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.run(RemoteTestRunner.java:386) at org.eclipse.jdt.internal.junit.runner.RemoteTestRunner.main(RemoteTestRunner.java:196) In addition, I get the following warnings when Spring first starts. Since these reference the entityManagerFactory and the transactionManager, they probably have some bearing on the problem, but I've no been able to decipher them enough to know what: Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean 'entityManagerFactory' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean 'entityManagerFactory' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean 'jpaTransactionManager' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean '(inner bean)' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean '(inner bean)' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean 'org.springframework.transaction.interceptor.TransactionAttributeSourceAdvisor' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.context.support.AbstractApplicationContext$BeanPostProcessorChecker postProcessAfterInitialization INFO: Bean 'org.springframework.orm.jpa.support.PersistenceAnnotationBeanPostProcessor' is not eligible for getting processed by all BeanPostProcessors (for example: not eligible for auto-proxying) Mar 11, 2010 12:19:27 PM org.springframework.beans.factory.support.DefaultListableBeanFactory preInstantiateSingletons INFO: Pre-instantiating singletons in org.springframework.beans.factory.support.DefaultListableBeanFactory@37003700: defining beans [groupDao,org.springframework.beans.factory.annotation.RequiredAnnotationBeanPostProcessor,org.springframework.orm.jpa.support.PersistenceAnnotationBeanPostProcessor,entityManagerFactory,jpaTransactionManager,org.springframework.aop.config.internalAutoProxyCreator,org.springframework.transaction.interceptor.TransactionAttributeSourceAdvisor]; root of factory hierarchy Does anyone have any idea what I'm missing? I'm totally stumped... Thanks

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  • SOA Suite 11g Native Format Builder Complex Format Example

    - by bob.webster
    This rather long posting details the steps required to process a grouping of fixed length records using Format Builder.   If it’s 10 pm and you’re feeling beat you might want to leave this until tomorrow.  But if it’s 10 pm and you need to get a Format Builder Complex template done, read on… The goal is to process individual orders from a file using the 11g File Adapter and Format Builder Sample Data =========== 001Square Widget            0245.98 102Triagular Widget         1120.00 403Circular Widget           0099.45 ORD8898302/01/2011 301Hexagon Widget         1150.98 ORD6735502/01/2011 The records are fixed length records representing a number of logical Order records. Each order record consists of a number of item records starting with a 3 digit number, followed by a single Summary Record which starts with the constant ORD. How can this file be processed so that the first poll returns the first order? 001Square Widget            0245.98 102Triagular Widget         1120.00 403Circular Widget           0099.45 ORD8898302/01/2011 And the second poll returns the second order? 301Hexagon Widget           1150.98 ORD6735502/01/2011 Note: if you need more than one order per poll, that’s also possible, see the “Multiple Messages” field in the “File Adapter Step 6 of 9” snapshot further down.   To follow along with this example you will need - Studio Edition Version 11.1.1.4.0    with the   - SOA Extension for JDeveloper 11.1.1.4.0 installed Both can be downloaded from here:  http://www.oracle.com/technetwork/middleware/soasuite/downloads/index.html You will not need a running WebLogic Server domain to complete the steps and Format Builder tests in this article.     Start with a SOA Composite containing a File Adapter The Format Builder is part of the File Adapter so start by creating a new SOA Project and Composite. Here is a quick summary for those not familiar with these steps - Start JDeveloper - From the Main Menu choose File->New - In the New Gallery window that opens Expand the “General” category and Select the Applications node.   Then choose SOA Application from the Items section on the right.  Finally press the OK button. - In Step 1 of the “Create SOA Application wizard” that appears enter an Application Name and an Directory of your     choice,   then press the Next button. - In Step 2 of the “Create SOA Application wizard”, press the Next button leaving all entries as defaulted. - In Step 3 of the “Create SOA Application wizard”, Enter a composite name of your choice and Press the Finish   Button These steps result in a new Application and SOA Project. The SOA Project contains a composite.xml file which is opened and shown below. For our example we have not defined a Mediator or a BPEL process to minimize the steps, but one or the other would eventually be needed to use the File Adapter we are about to create. Drag and drop the File Adapter icon from the Component Pallette onto either the LEFT side of the diagram under “Exposed Services” or the right side under “External References”.  (See the Green Circle in the image below).  Placing the adapter on the left side would indicate the file being processed is inbound to the composite, if the adapter is placed on the right side then the data is outbound to a file.     Note that the same Format Builder definition can be used in both directions.  For example we could use the format with a File Adapter on the left side of the composite to parse fixed data into XML, modify the data in our Composite or BPEL process and then use the same Format Builder definition with a File adapter on the right side of the composite to write the data back out in the same fixed data format When the File Adapter is dropped on the Composite the File Adapter Wizard Appears. Skip Past the first page, Step 1 of 9 by pressing the Next button. In Step 2 enter a service name of your choice as shown below, then press Next   When the Native Format Builder appears, skip the welcome page by pressing next. Also press the Next button to accept the settings on Step 3 of 9 On Step 4, select Read File and press the Next button as shown below.   On Step 5 enter a directory that will contain a file with the input data, then  Press the Next button as shown below. In step 6, enter *.txt or another file format to select input files from the input directory mentioned in step 5. ALSO check the “Files contain Multiple Messages” checkbox and set the “Publish Messages in Batches of” field to 1.  The value can be set higher to increase the number of logical order group records returned on each poll of the file adapter.  In other words, it determines the number of Orders that will be sent to each instance of a Mediator or Composite processing using the File Adapter.   Skip Step 7 by pressing the Next button In Step 8 press the Gear Icon on the right side to load the Native Format Builder.       Native Format Builder  appears Before diving into the format, here is an overview of the process. Approach - Bottom up Assuming an Order is a grouping of item records and a summary record…. - Define a separate  Complex Type for each Record Type found in the group.    (One for itemRecord and one for summaryRecord) - Define a Complex Type to contain the Group of Record types defined above   (LogicalOrderRecord) - Define a top level element to represent an order.  (order)   The order element will be of type LogicalOrderRecord   Defining the Format In Step 1 select   “Create new”  and  “Complex Type” and “Next”   In Step two browse to and select a file containing the test data shown at the start of this article. A link is provided at the end of this article to download a file containing the test data. Press the Next button     In Step 3 Complex types must be define for each type of input record. Select the Root-Element and Click on the Add Complex Type icon This creates a new empty complex type definition shown below. The fastest way to create the definition is to highlight the first line of the Sample File data and drag the line onto the  <new_complex_type> Format Builder introspects the data and provides a grid to define additional fields. Change the “Complex Type Name” to  “itemRecord” Then click on the ruler to indicate the position of fixed columns.  Drag the red triangle icons to the exact columns if necessary. Double click on an existing red triangle to remove an unwanted entry. In the case below fields are define in columns 0-3, 4-28, 29-eol When the field definitions are correct, press the “Generate Fields” button. Field entries named C1, C2 and C3 will be created as shown below. Click on the field names and rename them from C1->itemNum, C2->itemDesc and C3->itemCost  When all the fields are correctly defined press OK to save the complex type.        Next, the process is repeated to define a Complex Type for the SummaryRecord. Select the Root-Element in the schema tree and press the new complex type icon Then highlight and drag the Summary Record from the sample data onto the <new_complex_type>   Change the complex type name to “summaryRecord” Mark the fixed fields for Order Number and Order Date. Press the Generate Fields button and rename C1 and C2 to itemNum and orderDate respectively.   The last complex type to be defined is a type to hold the group of items and the summary record. Select the Root-Element in the schema tree and click the new complex type icon Select the “<new_complex_type>” entry and click the pencil icon   On the Complex Type Details page change the name and type of each input field. Change line 1 to be named item and set the Type  to “itemRecord” Change line 2 to be named summary and set the Type to “summaryRecord” We also need to indicate that itemRecords repeat in the input file. Click the pencil icon at the right side of the item line. On the Edit Details page change the “Max Occurs” entry from 1 to UNBOUNDED. We also need to indicate how to identify an itemRecord.  Since each item record has “.” in column 32 we can use this fact to differentiate an item record from a summary record. Change the “Look Ahead” field to value 32 and enter a period in the “Look For” field Press the OK button to save entry.     Finally, its time to create a top level element to represent an order. Select the “Root-Element” in the schema tree and press the New element icon Click on the <new_element> and press the pencil icon.   Set the Element Name to “order” and change the Data Type to “logicalOrderRecord” Press the OK button to save the element definition.   The final definition should match the screenshot below. Press the Next Button to view the definition source.     Press the Test Button to test the definition   Press the Green Triangle Icon to run the test.   And we are presented with an unwelcome error. The error states that the processor ran out of data while working through the definition. The processor was unable to differentiate between itemRecords and summaryRecords and therefore treated the entire file as a list of itemRecords.  At end of file, the “summary” portion of the logicalOrderRecord remained unprocessed but mandatory.   This root cause of this error is the loss of our “lookAhead” definition used to identify itemRecords. This appears to be a bug in the  Native Format Builder 11.1.1.4.0 Luckily, a simple workaround exists. Press the Cancel button and return to the “Step 4 of 4” Window. Manually add    nxsd:lookAhead="32" nxsd:lookFor="."   attributes after the maxOccurs attribute of the item element. as shown in the highlighted text below.   When the lookAhead and lookFor attributes have been added Press the Test button and on the Test page press the Green Triangle. The test is now successful, the first order in the file is returned by the File Adapter.     Below is a complete listing of the Result XML from the right column of the screen above   Try running it The downloaded input test file and completed schema file can be used for testing without following all the Native Format Builder steps in this example. Use the following link to download a file containing the sample data. Download Sample Input Data This is the best approach rather than cutting and pasting the input data at the top of the article.  Since the data is fixed length it’s very important to watch out for trailing spaces in the data and to ensure an eol character at the end of every line. The download file is correctly formatted. The final schema definition can be downloaded at the following link Download Completed Schema Definition   - Save the inputData.txt file to a known location like the xsd folder in your project. - Save the inputData_6.xsd file to the xsd folder in your project. - At step 1 in the Native Format Builder wizard  (as shown above) check the “Edit existing” radio button,    then browse and select the inputData_6.xsd file - At step 2 of the Format Builder configuration Wizard (as shown above) supply the path and filename for    the inputData.txt file. - You can then proceed to the test page and run a test. - Remember the wizard bug will drop the lookAhead and lookFor attributes,  you will need to manually add   nxsd:lookAhead="32" nxsd:lookFor="."    after the maxOccurs attribute of the item element in the   LogicalOrderRecord Complex Type.  (as shown above)   Good Luck with your Format Project

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  • Inheritance Mapping Strategies with Entity Framework Code First CTP5: Part 3 – Table per Concrete Type (TPC) and Choosing Strategy Guidelines

    - by mortezam
    This is the third (and last) post in a series that explains different approaches to map an inheritance hierarchy with EF Code First. I've described these strategies in previous posts: Part 1 – Table per Hierarchy (TPH) Part 2 – Table per Type (TPT)In today’s blog post I am going to discuss Table per Concrete Type (TPC) which completes the inheritance mapping strategies supported by EF Code First. At the end of this post I will provide some guidelines to choose an inheritance strategy mainly based on what we've learned in this series. TPC and Entity Framework in the Past Table per Concrete type is somehow the simplest approach suggested, yet using TPC with EF is one of those concepts that has not been covered very well so far and I've seen in some resources that it was even discouraged. The reason for that is just because Entity Data Model Designer in VS2010 doesn't support TPC (even though the EF runtime does). That basically means if you are following EF's Database-First or Model-First approaches then configuring TPC requires manually writing XML in the EDMX file which is not considered to be a fun practice. Well, no more. You'll see that with Code First, creating TPC is perfectly possible with fluent API just like other strategies and you don't need to avoid TPC due to the lack of designer support as you would probably do in other EF approaches. Table per Concrete Type (TPC)In Table per Concrete type (aka Table per Concrete class) we use exactly one table for each (nonabstract) class. All properties of a class, including inherited properties, can be mapped to columns of this table, as shown in the following figure: As you can see, the SQL schema is not aware of the inheritance; effectively, we’ve mapped two unrelated tables to a more expressive class structure. If the base class was concrete, then an additional table would be needed to hold instances of that class. I have to emphasize that there is no relationship between the database tables, except for the fact that they share some similar columns. TPC Implementation in Code First Just like the TPT implementation, we need to specify a separate table for each of the subclasses. We also need to tell Code First that we want all of the inherited properties to be mapped as part of this table. In CTP5, there is a new helper method on EntityMappingConfiguration class called MapInheritedProperties that exactly does this for us. Here is the complete object model as well as the fluent API to create a TPC mapping: public abstract class BillingDetail {     public int BillingDetailId { get; set; }     public string Owner { get; set; }     public string Number { get; set; } }          public class BankAccount : BillingDetail {     public string BankName { get; set; }     public string Swift { get; set; } }          public class CreditCard : BillingDetail {     public int CardType { get; set; }     public string ExpiryMonth { get; set; }     public string ExpiryYear { get; set; } }      public class InheritanceMappingContext : DbContext {     public DbSet<BillingDetail> BillingDetails { get; set; }              protected override void OnModelCreating(ModelBuilder modelBuilder)     {         modelBuilder.Entity<BankAccount>().Map(m =>         {             m.MapInheritedProperties();             m.ToTable("BankAccounts");         });         modelBuilder.Entity<CreditCard>().Map(m =>         {             m.MapInheritedProperties();             m.ToTable("CreditCards");         });                 } } The Importance of EntityMappingConfiguration ClassAs a side note, it worth mentioning that EntityMappingConfiguration class turns out to be a key type for inheritance mapping in Code First. Here is an snapshot of this class: namespace System.Data.Entity.ModelConfiguration.Configuration.Mapping {     public class EntityMappingConfiguration<TEntityType> where TEntityType : class     {         public ValueConditionConfiguration Requires(string discriminator);         public void ToTable(string tableName);         public void MapInheritedProperties();     } } As you have seen so far, we used its Requires method to customize TPH. We also used its ToTable method to create a TPT and now we are using its MapInheritedProperties along with ToTable method to create our TPC mapping. TPC Configuration is Not Done Yet!We are not quite done with our TPC configuration and there is more into this story even though the fluent API we saw perfectly created a TPC mapping for us in the database. To see why, let's start working with our object model. For example, the following code creates two new objects of BankAccount and CreditCard types and tries to add them to the database: using (var context = new InheritanceMappingContext()) {     BankAccount bankAccount = new BankAccount();     CreditCard creditCard = new CreditCard() { CardType = 1 };                      context.BillingDetails.Add(bankAccount);     context.BillingDetails.Add(creditCard);     context.SaveChanges(); } Running this code throws an InvalidOperationException with this message: The changes to the database were committed successfully, but an error occurred while updating the object context. The ObjectContext might be in an inconsistent state. Inner exception message: AcceptChanges cannot continue because the object's key values conflict with another object in the ObjectStateManager. Make sure that the key values are unique before calling AcceptChanges. The reason we got this exception is because DbContext.SaveChanges() internally invokes SaveChanges method of its internal ObjectContext. ObjectContext's SaveChanges method on its turn by default calls AcceptAllChanges after it has performed the database modifications. AcceptAllChanges method merely iterates over all entries in ObjectStateManager and invokes AcceptChanges on each of them. Since the entities are in Added state, AcceptChanges method replaces their temporary EntityKey with a regular EntityKey based on the primary key values (i.e. BillingDetailId) that come back from the database and that's where the problem occurs since both the entities have been assigned the same value for their primary key by the database (i.e. on both BillingDetailId = 1) and the problem is that ObjectStateManager cannot track objects of the same type (i.e. BillingDetail) with the same EntityKey value hence it throws. If you take a closer look at the TPC's SQL schema above, you'll see why the database generated the same values for the primary keys: the BillingDetailId column in both BankAccounts and CreditCards table has been marked as identity. How to Solve The Identity Problem in TPC As you saw, using SQL Server’s int identity columns doesn't work very well together with TPC since there will be duplicate entity keys when inserting in subclasses tables with all having the same identity seed. Therefore, to solve this, either a spread seed (where each table has its own initial seed value) will be needed, or a mechanism other than SQL Server’s int identity should be used. Some other RDBMSes have other mechanisms allowing a sequence (identity) to be shared by multiple tables, and something similar can be achieved with GUID keys in SQL Server. While using GUID keys, or int identity keys with different starting seeds will solve the problem but yet another solution would be to completely switch off identity on the primary key property. As a result, we need to take the responsibility of providing unique keys when inserting records to the database. We will go with this solution since it works regardless of which database engine is used. Switching Off Identity in Code First We can switch off identity simply by placing DatabaseGenerated attribute on the primary key property and pass DatabaseGenerationOption.None to its constructor. DatabaseGenerated attribute is a new data annotation which has been added to System.ComponentModel.DataAnnotations namespace in CTP5: public abstract class BillingDetail {     [DatabaseGenerated(DatabaseGenerationOption.None)]     public int BillingDetailId { get; set; }     public string Owner { get; set; }     public string Number { get; set; } } As always, we can achieve the same result by using fluent API, if you prefer that: modelBuilder.Entity<BillingDetail>()             .Property(p => p.BillingDetailId)             .HasDatabaseGenerationOption(DatabaseGenerationOption.None); Working With The Object Model Our TPC mapping is ready and we can try adding new records to the database. But, like I said, now we need to take care of providing unique keys when creating new objects: using (var context = new InheritanceMappingContext()) {     BankAccount bankAccount = new BankAccount()      {          BillingDetailId = 1                          };     CreditCard creditCard = new CreditCard()      {          BillingDetailId = 2,         CardType = 1     };                      context.BillingDetails.Add(bankAccount);     context.BillingDetails.Add(creditCard);     context.SaveChanges(); } Polymorphic Associations with TPC is Problematic The main problem with this approach is that it doesn’t support Polymorphic Associations very well. After all, in the database, associations are represented as foreign key relationships and in TPC, the subclasses are all mapped to different tables so a polymorphic association to their base class (abstract BillingDetail in our example) cannot be represented as a simple foreign key relationship. For example, consider the the domain model we introduced here where User has a polymorphic association with BillingDetail. This would be problematic in our TPC Schema, because if User has a many-to-one relationship with BillingDetail, the Users table would need a single foreign key column, which would have to refer both concrete subclass tables. This isn’t possible with regular foreign key constraints. Schema Evolution with TPC is Complex A further conceptual problem with this mapping strategy is that several different columns, of different tables, share exactly the same semantics. This makes schema evolution more complex. For example, a change to a base class property results in changes to multiple columns. It also makes it much more difficult to implement database integrity constraints that apply to all subclasses. Generated SQLLet's examine SQL output for polymorphic queries in TPC mapping. For example, consider this polymorphic query for all BillingDetails and the resulting SQL statements that being executed in the database: var query = from b in context.BillingDetails select b; Just like the SQL query generated by TPT mapping, the CASE statements that you see in the beginning of the query is merely to ensure columns that are irrelevant for a particular row have NULL values in the returning flattened table. (e.g. BankName for a row that represents a CreditCard type). TPC's SQL Queries are Union Based As you can see in the above screenshot, the first SELECT uses a FROM-clause subquery (which is selected with a red rectangle) to retrieve all instances of BillingDetails from all concrete class tables. The tables are combined with a UNION operator, and a literal (in this case, 0 and 1) is inserted into the intermediate result; (look at the lines highlighted in yellow.) EF reads this to instantiate the correct class given the data from a particular row. A union requires that the queries that are combined, project over the same columns; hence, EF has to pad and fill up nonexistent columns with NULL. This query will really perform well since here we can let the database optimizer find the best execution plan to combine rows from several tables. There is also no Joins involved so it has a better performance than the SQL queries generated by TPT where a Join is required between the base and subclasses tables. Choosing Strategy GuidelinesBefore we get into this discussion, I want to emphasize that there is no one single "best strategy fits all scenarios" exists. As you saw, each of the approaches have their own advantages and drawbacks. Here are some rules of thumb to identify the best strategy in a particular scenario: If you don’t require polymorphic associations or queries, lean toward TPC—in other words, if you never or rarely query for BillingDetails and you have no class that has an association to BillingDetail base class. I recommend TPC (only) for the top level of your class hierarchy, where polymorphism isn’t usually required, and when modification of the base class in the future is unlikely. If you do require polymorphic associations or queries, and subclasses declare relatively few properties (particularly if the main difference between subclasses is in their behavior), lean toward TPH. Your goal is to minimize the number of nullable columns and to convince yourself (and your DBA) that a denormalized schema won’t create problems in the long run. If you do require polymorphic associations or queries, and subclasses declare many properties (subclasses differ mainly by the data they hold), lean toward TPT. Or, depending on the width and depth of your inheritance hierarchy and the possible cost of joins versus unions, use TPC. By default, choose TPH only for simple problems. For more complex cases (or when you’re overruled by a data modeler insisting on the importance of nullability constraints and normalization), you should consider the TPT strategy. But at that point, ask yourself whether it may not be better to remodel inheritance as delegation in the object model (delegation is a way of making composition as powerful for reuse as inheritance). Complex inheritance is often best avoided for all sorts of reasons unrelated to persistence or ORM. EF acts as a buffer between the domain and relational models, but that doesn’t mean you can ignore persistence concerns when designing your classes. SummaryIn this series, we focused on one of the main structural aspect of the object/relational paradigm mismatch which is inheritance and discussed how EF solve this problem as an ORM solution. We learned about the three well-known inheritance mapping strategies and their implementations in EF Code First. Hopefully it gives you a better insight about the mapping of inheritance hierarchies as well as choosing the best strategy for your particular scenario. Happy New Year and Happy Code-Firsting! References ADO.NET team blog Java Persistence with Hibernate book a { color: #5A99FF; } a:visited { color: #5A99FF; } .title { padding-bottom: 5px; font-family: Segoe UI; font-size: 11pt; font-weight: bold; padding-top: 15px; } .code, .typeName { font-family: consolas; } .typeName { color: #2b91af; } .padTop5 { padding-top: 5px; } .padTop10 { padding-top: 10px; } .exception { background-color: #f0f0f0; font-style: italic; padding-bottom: 5px; padding-left: 5px; padding-top: 5px; padding-right: 5px; }

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  • LLBLGen Pro feature highlights: automatic element name construction

    - by FransBouma
    (This post is part of a series of posts about features of the LLBLGen Pro system) One of the things one might take for granted but which has a huge impact on the time spent in an entity modeling environment is the way the system creates names for elements out of the information provided, in short: automatic element name construction. Element names are created in both directions of modeling: database first and model first and the more names the system can create for you without you having to rename them, the better. LLBLGen Pro has a rich, fine grained system for creating element names out of the meta-data available, which I'll describe more in detail below. First the model element related element naming features are highlighted, in the section Automatic model element naming features and after that I'll go more into detail about the relational model element naming features LLBLGen Pro has to offer in the section Automatic relational model element naming features. Automatic model element naming features When working database first, the element names in the model, e.g. entity names, entity field names and so on, are in general determined from the relational model element (e.g. table, table field) they're mapped on, as the model elements are reverse engineered from these relational model elements. It doesn't take rocket science to automatically name an entity Customer if the entity was created after reverse engineering a table named Customer. It gets a little trickier when the entity which was created by reverse engineering a table called TBL_ORDER_LINES has to be named 'OrderLine' automatically. Automatic model element naming also takes into effect with model first development, where some settings are used to provide you with a default name, e.g. in the case of navigator name creation when you create a new relationship. The features below are available to you in the Project Settings. Open Project Settings on a loaded project and navigate to Conventions -> Element Name Construction. Strippers! The above example 'TBL_ORDER_LINES' shows that some parts of the table name might not be needed for name creation, in this case the 'TBL_' prefix. Some 'brilliant' DBAs even add suffixes to table names, fragments you might not want to appear in the entity names. LLBLGen Pro offers you to define both prefix and suffix fragments to strip off of table, view, stored procedure, parameter, table field and view field names. In the example above, the fragment 'TBL_' is a good candidate for such a strip pattern. You can specify more than one pattern for e.g. the table prefix strip pattern, so even a really messy schema can still be used to produce clean names. Underscores Be Gone Another thing you might get rid of are underscores. After all, most naming schemes for entities and their classes use PasCal casing rules and don't allow for underscores to appear. LLBLGen Pro can automatically strip out underscores for you. It's an optional feature, so if you like the underscores, you're not forced to see them go: LLBLGen Pro will leave them alone when ordered to to so. PasCal everywhere... or not, your call LLBLGen Pro can automatically PasCal case names on word breaks. It determines word breaks in a couple of ways: a space marks a word break, an underscore marks a word break and a case difference marks a word break. It will remove spaces in all cases, and based on the underscore removal setting, keep or remove the underscores, and upper-case the first character of a word break fragment, and lower case the rest. Say, we keep the defaults, which is remove underscores and PasCal case always and strip the TBL_ fragment, we get with our example TBL_ORDER_LINES, after stripping TBL_ from the table name two word fragments: ORDER and LINES. The underscores are removed, the first character of each fragment is upper-cased, the rest lower-cased, so this results in OrderLines. Almost there! Pluralization and Singularization In general entity names are singular, like Customer or OrderLine so LLBLGen Pro offers a way to singularize the names. This will convert OrderLines, the result we got after the PasCal casing functionality, into OrderLine, exactly what we're after. Show me the patterns! There are other situations in which you want more flexibility. Say, you have an entity Customer and an entity Order and there's a foreign key constraint defined from the target of Order and the target of Customer. This foreign key constraint results in a 1:n relationship between the entities Customer and Order. A relationship has navigators mapped onto the relationship in both entities the relationship is between. For this particular relationship we'd like to have Customer as navigator in Order and Orders as navigator in Customer, so the relationship becomes Customer.Orders 1:n Order.Customer. To control the naming of these navigators for the various relationship types, LLBLGen Pro defines a set of patterns which allow you, using macros, to define how the auto-created navigator names will look like. For example, if you rather have Customer.OrderCollection, you can do so, by changing the pattern from {$EndEntityName$P} to {$EndEntityName}Collection. The $P directive makes sure the name is pluralized, which is not what you want if you're going for <EntityName>Collection, hence it's removed. When working model first, it's a given you'll create foreign key fields along the way when you define relationships. For example, you've defined two entities: Customer and Order, and they have their fields setup properly. Now you want to define a relationship between them. This will automatically create a foreign key field in the Order entity, which reflects the value of the PK field in Customer. (No worries if you hate the foreign key fields in your classes, on NHibernate and EF these can be hidden in the generated code if you want to). A specific pattern is available for you to direct LLBLGen Pro how to name this foreign key field. For example, if all your entities have Id as PK field, you might want to have a different name than Id as foreign key field. In our Customer - Order example, you might want to have CustomerId instead as foreign key name in Order. The pattern for foreign key fields gives you that freedom. Abbreviations... make sense of OrdNr and friends I already described word breaks in the PasCal casing paragraph, how they're used for the PasCal casing in the constructed name. Word breaks are used for another neat feature LLBLGen Pro has to offer: abbreviation support. Burt, your friendly DBA in the dungeons below the office has a hate-hate relationship with his keyboard: he can't stand it: typing is something he avoids like the plague. This has resulted in tables and fields which have names which are very short, but also very unreadable. Example: our TBL_ORDER_LINES example has a lovely field called ORD_NR. What you would like to see in your fancy new OrderLine entity mapped onto this table is a field called OrderNumber, not a field called OrdNr. What you also like is to not have to rename that field manually. There are better things to do with your time, after all. LLBLGen Pro has you covered. All it takes is to define some abbreviation - full word pairs and during reverse engineering model elements from tables/views, LLBLGen Pro will take care of the rest. For the ORD_NR field, you need two values: ORD as abbreviation and Order as full word, and NR as abbreviation and Number as full word. LLBLGen Pro will now convert every word fragment found with the word breaks which matches an abbreviation to the given full word. They're case sensitive and can be found in the Project Settings: Navigate to Conventions -> Element Name Construction -> Abbreviations. Automatic relational model element naming features Not everyone works database first: it may very well be the case you start from scratch, or have to add additional tables to an existing database. For these situations, it's key you have the flexibility that you can control the created table names and table fields without any work: let the designer create these names based on the entity model you defined and a set of rules. LLBLGen Pro offers several features in this area, which are described in more detail below. These features are found in Project Settings: navigate to Conventions -> Model First Development. Underscores, welcome back! Not every database is case insensitive, and not every organization requires PasCal cased table/field names, some demand all lower or all uppercase names with underscores at word breaks. Say you create an entity model with an entity called OrderLine. You work with Oracle and your organization requires underscores at word breaks: a table created from OrderLine should be called ORDER_LINE. LLBLGen Pro allows you to do that: with a simple checkbox you can order LLBLGen Pro to insert an underscore at each word break for the type of database you're working with: case sensitive or case insensitive. Checking the checkbox Insert underscore at word break case insensitive dbs will let LLBLGen Pro create a table from the entity called Order_Line. Half-way there, as there are still lower case characters there and you need all caps. No worries, see below Casing directives so everyone can sleep well at night For case sensitive databases and case insensitive databases there is one setting for each of them which controls the casing of the name created from a model element (e.g. a table created from an entity definition using the auto-mapping feature). The settings can have the following values: AsProjectElement, AllUpperCase or AllLowerCase. AsProjectElement is the default, and it keeps the casing as-is. In our example, we need to get all upper case characters, so we select AllUpperCase for the setting for case sensitive databases. This will produce the name ORDER_LINE. Sequence naming after a pattern Some databases support sequences, and using model-first development it's key to have sequences, when needed, to be created automatically and if possible using a name which shows where they're used. Say you have an entity Order and you want to have the PK values be created by the database using a sequence. The database you're using supports sequences (e.g. Oracle) and as you want all numeric PK fields to be sequenced, you have enabled this by the setting Auto assign sequences to integer pks. When you're using LLBLGen Pro's auto-map feature, to create new tables and constraints from the model, it will create a new table, ORDER, based on your settings I previously discussed above, with a PK field ID and it also creates a sequence, SEQ_ORDER, which is auto-assigns to the ID field mapping. The name of the sequence is created by using a pattern, defined in the Model First Development setting Sequence pattern, which uses plain text and macros like with the other patterns previously discussed. Grouping and schemas When you start from scratch, and you're working model first, the tables created by LLBLGen Pro will be in a catalog and / or schema created by LLBLGen Pro as well. If you use LLBLGen Pro's grouping feature, which allows you to group entities and other model elements into groups in the project (described in a future blog post), you might want to have that group name reflected in the schema name the targets of the model elements are in. Say you have a model with a group CRM and a group HRM, both with entities unique for these groups, e.g. Employee in HRM, Customer in CRM. When auto-mapping this model to create tables, you might want to have the table created for Employee in the HRM schema but the table created for Customer in the CRM schema. LLBLGen Pro will do just that when you check the setting Set schema name after group name to true (default). This gives you total control over where what is placed in the database from your model. But I want plural table names... and TBL_ prefixes! For now we follow best practices which suggest singular table names and no prefixes/suffixes for names. Of course that won't keep everyone happy, so we're looking into making it possible to have that in a future version. Conclusion LLBLGen Pro offers a variety of options to let the modeling system do as much work for you as possible. Hopefully you enjoyed this little highlight post and that it has given you new insights in the smaller features available to you in LLBLGen Pro, ones you might not have thought off in the first place. Enjoy!

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