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  • Entity Association Mapping with Code First Part 1 : Mapping Complex Types

    - by mortezam
    Last week the CTP5 build of the new Entity Framework Code First has been released by data team at Microsoft. Entity Framework Code-First provides a pretty powerful code-centric way to work with the databases. When it comes to associations, it brings ultimate flexibility. I’m a big fan of the EF Code First approach and am planning to explain association mapping with code first in a series of blog posts and this one is dedicated to Complex Types. If you are new to Code First approach, you can find a great walkthrough here. In order to build a solid foundation for our discussion, we will start by learning about some of the core concepts around the relationship mapping.   What is Mapping?Mapping is the act of determining how objects and their relationships are persisted in permanent data storage, in our case, relational databases. What is Relationship mapping?A mapping that describes how to persist a relationship (association, aggregation, or composition) between two or more objects. Types of RelationshipsThere are two categories of object relationships that we need to be concerned with when mapping associations. The first category is based on multiplicity and it includes three types: One-to-one relationships: This is a relationship where the maximums of each of its multiplicities is one. One-to-many relationships: Also known as a many-to-one relationship, this occurs when the maximum of one multiplicity is one and the other is greater than one. Many-to-many relationships: This is a relationship where the maximum of both multiplicities is greater than one. The second category is based on directionality and it contains two types: Uni-directional relationships: when an object knows about the object(s) it is related to but the other object(s) do not know of the original object. To put this in EF terminology, when a navigation property exists only on one of the association ends and not on the both. Bi-directional relationships: When the objects on both end of the relationship know of each other (i.e. a navigation property defined on both ends). How Object Relationships Are Implemented in POCO domain models?When the multiplicity is one (e.g. 0..1 or 1) the relationship is implemented by defining a navigation property that reference the other object (e.g. an Address property on User class). When the multiplicity is many (e.g. 0..*, 1..*) the relationship is implemented via an ICollection of the type of other object. How Relational Database Relationships Are Implemented? Relationships in relational databases are maintained through the use of Foreign Keys. A foreign key is a data attribute(s) that appears in one table and must be the primary key or other candidate key in another table. With a one-to-one relationship the foreign key needs to be implemented by one of the tables. To implement a one-to-many relationship we implement a foreign key from the “one table” to the “many table”. We could also choose to implement a one-to-many relationship via an associative table (aka Join table), effectively making it a many-to-many relationship. Introducing the ModelNow, let's review the model that we are going to use in order to implement Complex Type with Code First. It's a simple object model which consist of two classes: User and Address. Each user could have one billing address. The Address information of a User is modeled as a separate class as you can see in the UML model below: In object-modeling terms, this association is a kind of aggregation—a part-of relationship. Aggregation is a strong form of association; it has some additional semantics with regard to the lifecycle of objects. In this case, we have an even stronger form, composition, where the lifecycle of the part is fully dependent upon the lifecycle of the whole. Fine-grained domain models The motivation behind this design was to achieve Fine-grained domain models. In crude terms, fine-grained means “more classes than tables”. For example, a user may have both a billing address and a home address. In the database, you may have a single User table with the columns BillingStreet, BillingCity, and BillingPostalCode along with HomeStreet, HomeCity, and HomePostalCode. There are good reasons to use this somewhat denormalized relational model (performance, for one). In our object model, we can use the same approach, representing the two addresses as six string-valued properties of the User class. But it’s much better to model this using an Address class, where User has the BillingAddress and HomeAddress properties. This object model achieves improved cohesion and greater code reuse and is more understandable. Complex Types: Splitting a Table Across Multiple Types Back to our model, there is no difference between this composition and other weaker styles of association when it comes to the actual C# implementation. But in the context of ORM, there is a big difference: A composed class is often a candidate Complex Type. But C# has no concept of composition—a class or property can’t be marked as a composition. The only difference is the object identifier: a complex type has no individual identity (i.e. no AddressId defined on Address class) which make sense because when it comes to the database everything is going to be saved into one single table. How to implement a Complex Types with Code First Code First has a concept of Complex Type Discovery that works based on a set of Conventions. The convention is that if Code First discovers a class where a primary key cannot be inferred, and no primary key is registered through Data Annotations or the fluent API, then the type will be automatically registered as a complex type. Complex type detection also requires that the type does not have properties that reference entity types (i.e. all the properties must be scalar types) and is not referenced from a collection property on another type. Here is the implementation: public class User{    public int UserId { get; set; }    public string FirstName { get; set; }    public string LastName { get; set; }    public string Username { get; set; }    public Address Address { get; set; }} public class Address {     public string Street { get; set; }     public string City { get; set; }            public string PostalCode { get; set; }        }public class EntityMappingContext : DbContext {     public DbSet<User> Users { get; set; }        } With code first, this is all of the code we need to write to create a complex type, we do not need to configure any additional database schema mapping information through Data Annotations or the fluent API. Database SchemaThe mapping result for this object model is as follows: Limitations of this mappingThere are two important limitations to classes mapped as Complex Types: Shared references is not possible: The Address Complex Type doesn’t have its own database identity (primary key) and so can’t be referred to by any object other than the containing instance of User (e.g. a Shipping class that also needs to reference the same User Address). No elegant way to represent a null reference There is no elegant way to represent a null reference to an Address. When reading from database, EF Code First always initialize Address object even if values in all mapped columns of the complex type are null. This means that if you store a complex type object with all null property values, EF Code First returns a initialized complex type when the owning entity object is retrieved from the database. SummaryIn this post we learned about fine-grained domain models which complex type is just one example of it. Fine-grained is fully supported by EF Code First and is known as the most important requirement for a rich domain model. Complex type is usually the simplest way to represent one-to-one relationships and because the lifecycle is almost always dependent in such a case, it’s either an aggregation or a composition in UML. In the next posts we will revisit the same domain model and will learn about other ways to map a one-to-one association that does not have the limitations of the complex types. References ADO.NET team blog Mapping Objects to Relational Databases Java Persistence with Hibernate

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  • SQL SERVER – Beginning of SQL Server Architecture – Terminology – Guest Post

    - by pinaldave
    SQL Server Architecture is a very deep subject. Covering it in a single post is an almost impossible task. However, this subject is very popular topic among beginners and advanced users.  I have requested my friend Anil Kumar who is expert in SQL Domain to help me write  a simple post about Beginning SQL Server Architecture. As stated earlier this subject is very deep subject and in this first article series he has covered basic terminologies. In future article he will explore the subject further down. Anil Kumar Yadav is Trainer, SQL Domain, Koenig Solutions. Koenig is a premier IT training firm that provides several IT certifications, such as Oracle 11g, Server+, RHCA, SQL Server Training, Prince2 Foundation etc. In this Article we will discuss about MS SQL Server architecture. The major components of SQL Server are: Relational Engine Storage Engine SQL OS Now we will discuss and understand each one of them. 1) Relational Engine: Also called as the query processor, Relational Engine includes the components of SQL Server that determine what your query exactly needs to do and the best way to do it. It manages the execution of queries as it requests data from the storage engine and processes the results returned. Different Tasks of Relational Engine: Query Processing Memory Management Thread and Task Management Buffer Management Distributed Query Processing 2) Storage Engine: Storage Engine is responsible for storage and retrieval of the data on to the storage system (Disk, SAN etc.). to understand more, let’s focus on the following diagram. When we talk about any database in SQL server, there are 2 types of files that are created at the disk level – Data file and Log file. Data file physically stores the data in data pages. Log files that are also known as write ahead logs, are used for storing transactions performed on the database. Let’s understand data file and log file in more details: Data File: Data File stores data in the form of Data Page (8KB) and these data pages are logically organized in extents. Extents: Extents are logical units in the database. They are a combination of 8 data pages i.e. 64 KB forms an extent. Extents can be of two types, Mixed and Uniform. Mixed extents hold different types of pages like index, System, Object data etc. On the other hand, Uniform extents are dedicated to only one type. Pages: As we should know what type of data pages can be stored in SQL Server, below mentioned are some of them: Data Page: It holds the data entered by the user but not the data which is of type text, ntext, nvarchar(max), varchar(max), varbinary(max), image and xml data. Index: It stores the index entries. Text/Image: It stores LOB ( Large Object data) like text, ntext, varchar(max), nvarchar(max),  varbinary(max), image and xml data. GAM & SGAM (Global Allocation Map & Shared Global Allocation Map): They are used for saving information related to the allocation of extents. PFS (Page Free Space): Information related to page allocation and unused space available on pages. IAM (Index Allocation Map): Information pertaining to extents that are used by a table or index per allocation unit. BCM (Bulk Changed Map): Keeps information about the extents changed in a Bulk Operation. DCM (Differential Change Map): This is the information of extents that have modified since the last BACKUP DATABASE statement as per allocation unit. Log File: It also known as write ahead log. It stores modification to the database (DML and DDL). Sufficient information is logged to be able to: Roll back transactions if requested Recover the database in case of failure Write Ahead Logging is used to create log entries Transaction logs are written in chronological order in a circular way Truncation policy for logs is based on the recovery model SQL OS: This lies between the host machine (Windows OS) and SQL Server. All the activities performed on database engine are taken care of by SQL OS. It is a highly configurable operating system with powerful API (application programming interface), enabling automatic locality and advanced parallelism. SQL OS provides various operating system services, such as memory management deals with buffer pool, log buffer and deadlock detection using the blocking and locking structure. Other services include exception handling, hosting for external components like Common Language Runtime, CLR etc. I guess this brief article gives you an idea about the various terminologies used related to SQL Server Architecture. In future articles we will explore them further. Guest Author  The author of the article is Anil Kumar Yadav is Trainer, SQL Domain, Koenig Solutions. Koenig is a premier IT training firm that provides several IT certifications, such as Oracle 11g, Server+, RHCA, SQL Server Training, Prince2 Foundation etc. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

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  • Speaking at PASS 2012… Exciting and Scary… As usual…

    - by drsql
    Edit: As I reread this, I felt I should clarify.. As usual refers mostly to the "Scary" part. I have a lot of stage fright that I have to work through. And it is always exciting to be picked. I have been selected this year at the PASS Summit 2012 to do two sessions, and they are both going to be interesting. Pre-Con: Relational Database Design Workshop - Abstract Triggers: Born Evil or Misunderstood? - Abstract The pre-con session entitled Relational Database Design Workshop will be (at least) the...(read more)

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  • What's a good scheme for multi-user database synchronization?

    - by Mason Wheeler
    I'm working on a system to allow multiple users to collaborate on an online project. Everything is fairly straightforward, except for keeping the users in sync. Each user has their own local copy of the project database, which allows them to make changes and test things out, and then send the updates to the central server. But this runs into the classic synchronization question: how do you keep two users from editing the same thing and stomping each other's work? I've got an idea that should work, but I wonder if there's a simpler way to do it. Here's the basic concept: All project data is stored in a relational database. Each row in the database has an owner. If the current user is not the owner, he can read but not write that row. (This is enforced client-side.) The user can send a request to the server to take ownership of a row, which will be granted if the server's copy says that the current owner is NULL, or to release ownership when they're done with it. It is not possible to release ownership without committing changes to the server. It is not possible to commit changes to the server without having first downloaded all outstanding changes to the server. When any changes are made to rows you own, a trigger marks that row as Dirty. When you commit changes, the database is scanned for all Dirty rows in all tables, and the data is serialized into an update file, which is posted to the server, and all rows are marked Clean. The server applies the updates on its end, and keeps the file around. When other users download changes, the server sends them the update files that they haven't already received. So, essentially this is a reinvention of version control on a relational database. (Sort of.) As long as taking ownership and applying updates to the server are guaranteed atomic changes, and the server verifies that some smart-aleck user didn't edit their local database so they could send an update for a row they don't have ownership of, it should be guaranteed to be correct, and with no need to worry about merges and merge conflicts. (I think.) Can anyone think of any problems with this scheme, or ways to do it better? (And no, "build [insert VCS here] into your project" is not what I'm looking for. I've thought of that already. VCSs work well with text, and not so well with other file formats, such as relational databases.)

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  • NoSQL is not about object databases

    NoSQL as a movement is an interesting beast. I kinda like that its negatively defined (I happen to belong myself to at least one other such a-community). Its not in its roots about proposing one specific new silver bullet to kill an old problem. its about challenging the consensus. Actually, blindly and systematically replacing relational databases with object databases would just replace one set of issues with another. No, the point is to recognize that relational databases are not a universal...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Using heavyweight ORM implementation for light based games

    - by Holland
    I'm just about to engulf myself in an MVC-based/Component architecture in C#, using MySQL's connector/Net for the data storage, and probably some NHibernate/FluentNHibernate Object-relational-mapping to map out the data structure. The goal is to build a scalable 2D RPG. Then I think about it...and I can't help but think this seems a little "heavy weight" for a 2D RPG, especially one which, while I plan to incorporate a lot of functionality and entertaining gameplay, may be ported to something like Windows Phone or Android in the future. Yet, on the other hand even a 2-Dimensional RPG can become very complicated, and therefore must incorporate a lot of functionality. While this can be accomplished with text/XML/JSON for data storage, is there a better way? Is something such as Object-Relational-Mapping useful in such an application? So, what do you think? Would you say that there is a place for such technologies? I don't know what to think...

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  • At what size of data does it become beneficial to move from SQL to NoSQL?

    - by wobbily_col
    As a relational database programmer (most of the time), I read articles about how relational databases don't scale, and NoSQL solutions such as MongoDB do. As most of the databases I have developed so far have been small to mid scale, I have never had a problem that hasn't been solved by some indexing, query optimization or schema redesign. What sort of size would I expect to see MySQL struggling with. How many rows? (I know this is going to depend on the application, and type of data stored. the one that got me thing was basically a genetics database, so would have one main table, with 3 or 4 lookup tables. The main table will contain amongst other things, a chromosome reference, and a position coordinate. It will likely get queried for a number of entries between two potions on a chromosome, to see what is stored there).

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  • MySQL for Beginners course - first steps to lowering your Database TCOs

    - by Antoinette O'Sullivan
    Thinking about lowering your Database TCO by using the MySQL Server? Don't miss the chance to get training from the source! With the newly released MySQL for Beginners class, learn how this powerful relational database management system can make your life easier and more fun! This course covers all the basics and will get you on your way, with a solid foundation. This instructor led, hands-on class covers the fundamentals of SQL and relational databases, using MySQL as a teaching tool. Send information about this course release to a friend who might be considering getting started on the world's most popular small footprint database.

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  • Intro to NoSQL with RavenDB

    - by dgreen
    I did a talk on RavenDB back on 9/19/2012. Here was my abstract: "RavenDB is a document database which is gaining popularity in the 'NoSQL' movement. This session will introduce you to some non-relational concepts and describe how they compare/contrast with the relational solutions you're already familiar with. We'll go through the basics of RavenDB and show how easy it is to use from .NET” My next goal is to figure out how to post the slidedeck here (and maybe the code samples if I'm feeling ambitious). Then, the slides can be downloaded for only three easy payments of $39.99. However  for this one time special offer they are currently being given away absolutely FREE with a signup to http://meetup.trinug.org Footnote: I probably shouldn't have to say this, but my last comment about charging for my slidedeck was a joke. I have an odd sense of humor for those who don't already know me :)

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  • Data architecture for event log metrics?

    - by elliot42
    My service has a large ongoing number of user events, and we would like to do things like "count occurrence of event type T since date D." We are trying to make two basic decisions: What to store? Storing every event vs. only storing aggregates (Event log style) log every event and count them later, vs. (Time-series style) store a single aggregated "count of event E for date D" for every day Where to store the data In a relational database (particularly MySQL) In a non-relational (NoSQL) database In flat log files (collected centrally over the network via syslog-ng) What is standard practice / where can I read more about comparing the different types of systems? Additional details: The total event stream is large, potentially hundreds of thousands of entries per day But our current need is only to count certain types of events within it We don't necessarily need real-time access to the raw data or aggregation results IMHO, "log all events to files, crawl them at a later time to filter and aggregate the stream" is a pretty standard UNIX Way, but my Rails-y compatriots seem to think that nothing is real unless it's in MySQL.

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  • Extreme Optimization Numerical Libraries for .NET – Part 1 of n

    - by JoshReuben
    While many of my colleagues are fascinated in constructing the ultimate ViewModel or ServiceBus, I feel that this kind of plumbing code is re-invented far too many times – at some point in the near future, it will be out of the box standard infra. How many times have you been to a customer site and built a different variation of the same kind of code frameworks? How many times can you abstract Prism or reliable and discoverable WCF communication? As the bar is raised for whats bundled with the framework and more tasks become declarative, automated and configurable, Information Systems will expose a higher level of abstraction, forcing software engineers to focus on more advanced computer science and algorithmic tasks. I've spent the better half of the past decade building skills in .NET and expanding my mathematical horizons by working through the Schaums guides. In this series I am going to examine how these skillsets come together in the implementation provided by ExtremeOptimization. Download the trial version here: http://www.extremeoptimization.com/downloads.aspx Overview The library implements a set of algorithms for: linear algebra, complex numbers, numerical integration and differentiation, solving equations, optimization, random numbers, regression, ANOVA, statistical distributions, hypothesis tests. EONumLib combines three libraries in one - organized in a consistent namespace hierarchy. Mathematics Library - Extreme.Mathematics namespace Vector and Matrix Library - Extreme.Mathematics.LinearAlgebra namespace Statistics Library - Extreme.Statistics namespace System Requirements -.NET framework 4.0  Mathematics Library The classes are organized into the following namespace hierarchy: Extreme.Mathematics – common data types, exception types, and delegates. Extreme.Mathematics.Calculus - numerical integration and differentiation of functions. Extreme.Mathematics.Curves - points, lines and curves, including polynomials and Chebyshev approximations. curve fitting and interpolation. Extreme.Mathematics.Generic - generic arithmetic & linear algebra. Extreme.Mathematics.EquationSolvers - root finding algorithms. Extreme.Mathematics.LinearAlgebra - vectors , matrices , matrix decompositions, solvers for simultaneous linear equations and least squares. Extreme.Mathematics.Optimization – multi-d function optimization + linear programming. Extreme.Mathematics.SignalProcessing - one and two-dimensional discrete Fourier transforms. Extreme.Mathematics.SpecialFunctions

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  • Oracle R Distribution 2-13.2 Update Available

    - by Sherry LaMonica
    Oracle has released an update to the Oracle R Distribution, an Oracle-supported distribution of open source R. Oracle R Distribution 2-13.2 now contains the ability to dynamically link the following libraries on both Windows and Linux: The Intel Math Kernel Library (MKL) on Intel chips The AMD Core Math Library (ACML) on AMD chips To take advantage of the performance enhancements provided by Intel MKL or AMD ACML in Oracle R Distribution, simply add the MKL or ACML shared library directory to the LD_LIBRARY_PATH system environment variable. This automatically enables MKL or ACML to make use of all available processors, vastly speeding up linear algebra computations and eliminating the need to recompile R.  Even on a single core, the optimized algorithms in the Intel MKL libraries are faster than using R's standard BLAS library. Open-source R is linked to NetLib's BLAS libraries, but they are not multi-threaded and only use one core. While R's internal BLAS are efficient for most computations, it's possible to recompile R to link to a different, multi-threaded BLAS library to improve performance on eligible calculations. Compiling and linking to R yourself can be involved, but for many, the significantly improved calculation speed justifies the effort. Oracle R Distribution notably simplifies the process of using external math libraries by enabling R to auto-load MKL or ACML. For R commands that don't link to BLAS code, taking advantage of database parallelism using embedded R execution in Oracle R Enterprise is the route to improved performance. For more information about rebuilding R with different BLAS libraries, see the linear algebra section in the R Installation and Administration manual. As always, the Oracle R Distribution is available as a free download to anyone. Questions and comments are welcome on the Oracle R Forum.

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  • Good PHP ORM Library?

    - by sgibbons
    Does anyone know of a good object-relational-mapping library for PHP? I know of PDO/ADO, but they seem to only provide abstraction of differences between database vendors not an actual mapping between the domain model and the relational model. I'm looking for a PHP library that functions similarly to the way Hibernate does for Java/.Net.

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  • question and answer engine architecture

    - by sarvesh
    Can anyone give me insights as to how websites like chacha.com / kgb.com are designed. What could be the components involved when a user sends out an sms and how is that question stored. Should the question and answers be stored in a relational model or non relational?

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  • SimpleDB as Denormalized DB

    - by Max
    In an environment where you have a relational database which handles all business transactions is it a good idea to utilise SimpleDB for all data queries to have faster and more lightweight search? So the master data storage would be a relational DB which is "replicated"/"transformed" into SimpleDB to provide very fast read only queries since no JOINS and complicated subselects are needed.

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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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  • LLBLGen Pro feature highlights: grouping model elements

    - by FransBouma
    (This post is part of a series of posts about features of the LLBLGen Pro system) When working with an entity model which has more than a few entities, it's often convenient to be able to group entities together if they belong to a semantic sub-model. For example, if your entity model has several entities which are about 'security', it would be practical to group them together under the 'security' moniker. This way, you could easily find them back, yet they can be left inside the complete entity model altogether so their relationships with entities outside the group are kept. In other situations your domain consists of semi-separate entity models which all target tables/views which are located in the same database. It then might be convenient to have a single project to manage the complete target database, yet have the entity models separate of each other and have them result in separate code bases. LLBLGen Pro can do both for you. This blog post will illustrate both situations. The feature is called group usage and is controllable through the project settings. This setting is supported on all supported O/R mapper frameworks. Situation one: grouping entities in a single model. This situation is common for entity models which are dense, so many relationships exist between all sub-models: you can't split them up easily into separate models (nor do you likely want to), however it's convenient to have them grouped together into groups inside the entity model at the project level. A typical example for this is the AdventureWorks example database for SQL Server. This database, which is a single catalog, has for each sub-group a schema, however most of these schemas are tightly connected with each other: adding all schemas together will give a model with entities which indirectly are related to all other entities. LLBLGen Pro's default setting for group usage is AsVisualGroupingMechanism which is what this situation is all about: we group the elements for visual purposes, it has no real meaning for the model nor the code generated. Let's reverse engineer AdventureWorks to an entity model. By default, LLBLGen Pro uses the target schema an element is in which is being reverse engineered, as the group it will be in. This is convenient if you already have categorized tables/views in schemas, like which is the case in AdventureWorks. Of course this can be switched off, or corrected on the fly. When reverse engineering, we'll walk through a wizard which will guide us with the selection of the elements which relational model data should be retrieved, which we can later on use to reverse engineer to an entity model. The first step after specifying which database server connect to is to select these elements. below we can see the AdventureWorks catalog as well as the different schemas it contains. We'll include all of them. After the wizard completes, we have all relational model data nicely in our catalog data, with schemas. So let's reverse engineer entities from the tables in these schemas. We select in the catalog explorer the schemas 'HumanResources', 'Person', 'Production', 'Purchasing' and 'Sales', then right-click one of them and from the context menu, we select Reverse engineer Tables to Entity Definitions.... This will bring up the dialog below. We check all checkboxes in one go by checking the checkbox at the top to mark them all to be added to the project. As you can see LLBLGen Pro has already filled in the group name based on the schema name, as this is the default and we didn't change the setting. If you want, you can select multiple rows at once and set the group name to something else using the controls on the dialog. We're fine with the group names chosen so we'll simply click Add to Project. This gives the following result:   (I collapsed the other groups to keep the picture small ;)). As you can see, the entities are now grouped. Just to see how dense this model is, I've expanded the relationships of Employee: As you can see, it has relationships with entities from three other groups than HumanResources. It's not doable to cut up this project into sub-models without duplicating the Employee entity in all those groups, so this model is better suited to be used as a single model resulting in a single code base, however it benefits greatly from having its entities grouped into separate groups at the project level, to make work done on the model easier. Now let's look at another situation, namely where we work with a single database while we want to have multiple models and for each model a separate code base. Situation two: grouping entities in separate models within the same project. To get rid of the entities to see the second situation in action, simply undo the reverse engineering action in the project. We still have the AdventureWorks relational model data in the catalog. To switch LLBLGen Pro to see each group in the project as a separate project, open the Project Settings, navigate to General and set Group usage to AsSeparateProjects. In the catalog explorer, select Person and Production, right-click them and select again Reverse engineer Tables to Entities.... Again check the checkbox at the top to mark all entities to be added and click Add to Project. We get two groups, as expected, however this time the groups are seen as separate projects. This means that the validation logic inside LLBLGen Pro will see it as an error if there's e.g. a relationship or an inheritance edge linking two groups together, as that would lead to a cyclic reference in the code bases. To see this variant of the grouping feature, seeing the groups as separate projects, in action, we'll generate code from the project with the two groups we just created: select from the main menu: Project -> Generate Source-code... (or press F7 ;)). In the dialog popping up, select the target .NET framework you want to use, the template preset, fill in a destination folder and click Start Generator (normal). This will start the code generator process. As expected the code generator has simply generated two code bases, one for Person and one for Production: The group name is used inside the namespace for the different elements. This allows you to add both code bases to a single solution and use them together in a different project without problems. Below is a snippet from the code file of a generated entity class. //... using System.Xml.Serialization; using AdventureWorks.Person; using AdventureWorks.Person.HelperClasses; using AdventureWorks.Person.FactoryClasses; using AdventureWorks.Person.RelationClasses; using SD.LLBLGen.Pro.ORMSupportClasses; namespace AdventureWorks.Person.EntityClasses { //... /// <summary>Entity class which represents the entity 'Address'.<br/><br/></summary> [Serializable] public partial class AddressEntity : CommonEntityBase //... The advantage of this is that you can have two code bases and work with them separately, yet have a single target database and maintain everything in a single location. If you decide to move to a single code base, you can do so with a change of one setting. It's also useful if you want to keep the groups as separate models (and code bases) yet want to add relationships to elements from another group using a copy of the entity: you can simply reverse engineer the target table to a new entity into a different group, effectively making a copy of the entity. As there's a single target database, changes made to that database are reflected in both models which makes maintenance easier than when you'd have a separate project for each group, with its own relational model data. Conclusion LLBLGen Pro offers a flexible way to work with entities in sub-models and control how the sub-models end up in the generated code.

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  • Oracle Big Data Software Downloads

    - by Mike.Hallett(at)Oracle-BI&EPM
    Companies have been making business decisions for decades based on transactional data stored in relational databases. Beyond that critical data, is a potential treasure trove of less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Oracle offers a broad integrated portfolio of products to help you acquire and organize these diverse data sources and analyze them alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data Connectors Downloads here, includes: Oracle SQL Connector for Hadoop Distributed File System Release 2.1.0 Oracle Loader for Hadoop Release 2.1.0 Oracle Data Integrator Companion 11g Oracle R Connector for Hadoop v 2.1 Oracle Big Data Documentation The Oracle Big Data solution offers an integrated portfolio of products to help you organize and analyze your diverse data sources alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data, Release 2.2.0 - E41604_01 zip (27.4 MB) Integrated Software and Big Data Connectors User's Guide HTML PDF Oracle Data Integrator (ODI) Application Adapter for Hadoop Apache Hadoop is designed to handle and process data that is typically from data sources that are non-relational and data volumes that are beyond what is handled by relational databases. Typical processing in Hadoop includes data validation and transformations that are programmed as MapReduce jobs. Designing and implementing a MapReduce job usually requires expert programming knowledge. However, when you use Oracle Data Integrator with the Application Adapter for Hadoop, you do not need to write MapReduce jobs. Oracle Data Integrator uses Hive and the Hive Query Language (HiveQL), a SQL-like language for implementing MapReduce jobs. Employing familiar and easy-to-use tools and pre-configured knowledge modules (KMs), the application adapter provides the following capabilities: Loading data into Hadoop from the local file system and HDFS Performing validation and transformation of data within Hadoop Loading processed data from Hadoop to an Oracle database for further processing and generating reports Oracle Database Loader for Hadoop Oracle Loader for Hadoop is an efficient and high-performance loader for fast movement of data from a Hadoop cluster into a table in an Oracle database. It pre-partitions the data if necessary and transforms it into a database-ready format. Oracle Loader for Hadoop is a Java MapReduce application that balances the data across reducers to help maximize performance. Oracle R Connector for Hadoop Oracle R Connector for Hadoop is a collection of R packages that provide: Interfaces to work with Hive tables, the Apache Hadoop compute infrastructure, the local R environment, and Oracle database tables Predictive analytic techniques, written in R or Java as Hadoop MapReduce jobs, that can be applied to data in HDFS files You install and load this package as you would any other R package. Using simple R functions, you can perform tasks such as: Access and transform HDFS data using a Hive-enabled transparency layer Use the R language for writing mappers and reducers Copy data between R memory, the local file system, HDFS, Hive, and Oracle databases Schedule R programs to execute as Hadoop MapReduce jobs and return the results to any of those locations Oracle SQL Connector for Hadoop Distributed File System Using Oracle SQL Connector for HDFS, you can use an Oracle Database to access and analyze data residing in Hadoop in these formats: Data Pump files in HDFS Delimited text files in HDFS Hive tables For other file formats, such as JSON files, you can stage the input in Hive tables before using Oracle SQL Connector for HDFS. Oracle SQL Connector for HDFS uses external tables to provide Oracle Database with read access to Hive tables, and to delimited text files and Data Pump files in HDFS. Related Documentation Cloudera's Distribution Including Apache Hadoop Library HTML Oracle R Enterprise HTML Oracle NoSQL Database HTML Recent Blog Posts Big Data Appliance vs. DIY Price Comparison Big Data: Architecture Overview Big Data: Achieve the Impossible in Real-Time Big Data: Vertical Behavioral Analytics Big Data: In-Memory MapReduce Flume and Hive for Log Analytics Building Workflows in Oozie

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