Micro-ORM Introduction - Don't overcomplicate

Don't overcomplicate Introduction to Micro ORM Ivan Korneliuk @korneliuk http://korneliuk.blogspot.com/ 31337 Kiev ALT.NET

What wrong with ORM? Inadequate abstraction Inefficiency Complexity Requires overcomplicated infrastructure around

Micro ORM Massive by Rob Connery Simple.Data by Mark Rendle Peta Poco by Top Ten Software Dapper by Sam Saffron

dapper-dot-net Simple SQL object mapper for ADO.NET Created by StackOverflow guys Single file Read oriented Ultra fast - performance is a key feature Pure SQL

dapper-dot-net Main concepts Enrich IDbCommand with extension methods for querying and executing sql commands. Can map query results to list of POCOs or dynamics.

dapper-dot-net Querying POCOs public class Dog { public int ? Age { get ; set ; } public Guid Id { get ; set ; } public string Name { get ; set ; } public float ? Weight { get ; set ; } public int IgnoredProperty { get { return 1 ; } } } var guid = Guid . NewGuid () ; var dog = connection . Query < Dog >( " select Age = @Age, Id = @Id " , new { Age = ( int ? ) null , Id = guid } ) ; dog . Count (). IsEqualTo ( 1 ) ; dog . First (). Age . IsNull () ; dog . First (). Id . IsEqualTo ( guid ) ;

dapper-dot-net Advanced features List support - automatically parameterize query by passing IEnumerable connection . Query < int >( @ " select * from (select 1 as Id union select 2 union select 3) as X where Id in @Ids " , new { Ids = new int [] { 1 , 2 , 3 } ) ; select * from ( select 1 as Id union select 2 union all select 3 ) as X where Id in ( @Ids1 , @Ids2 , @Ids3 ) // @Ids1 = 1 , @Ids2 = 2 , @Ids2 = 3

dapper-dot-net Advanced features Multi mapping - maps single row to several objects var sql = @ " select * from #Posts p left join #Users u on u.Id = p.OwnerId Order by p.Id " ; var data = connection . Query < Post , User , Post >( sql , ( post , user ) => { post . Owner = user ; return post ;} ) ; var post = data . First () ; post . Content . IsEqualTo ( " Sams Post1 " ) ; post . Id . IsEqualTo ( 1 ) ; post . Owner . Name . IsEqualTo ( " Sam " ) ; post . Owner . Id . IsEqualTo ( 99 ) ;

dapper-dot-net Advanced features Multiple results - processes multiple result grids with a single query. var sql = @ “ select * from Customers where CustomerId = @id select * from Orders where CustomerId = @id select * from Returns where CustomerId = @id " ; using ( var multi = conn . QueryMultiple ( sql , new { id = Id } )) { var customer = multi . Read < Customer >(). Single () ; var orders = multi . Read < Order >(). ToList () ; var returns = multi . Read < Return >(). ToList () ; ... }

Buffered and unbuffered readers (fetching results) Executing Stored Procedures Dapper.Contrib - Handling C(r)UD operations Marking classes with attributes Change tracking Queries caching dapper-dot-net Advanced features

Massive Single file database lover "I wanted to stay as close to the "metal" as I possibly could. This (to me) meant that I didn't want to worry about Types, Tracking Containers, Contexts and so on. What I did want to do is describe my table - and this is the only type I have (which, ironically, is a Dynamic type)" Single file with less than 700 lines of code (including comments).

Massive Initializing table // Create a class that wraps a table public class Products : DynamicModel { public Products (): base ( " northwind " , " products " , " productid " ) {} } // or instantiate it inline var tbl = new DynamicModel ( " northwind " , tableName : " Products " , primaryKeyField : " ProductID " ) ;

Massive Querying var table = new Products () ; var products = table . All ( columns : " ProductName as Name " , where : " WHERE categoryID=@0 " , args : 4 ) ; var products = table . Find ( CategoryID : 4 , columns : " ProductName " ) // Running ad-hoc queries as needed: var result = tbl . Query ( " SELECT * FROM Categories " ) ; var result = tbl . Fetch ( " SELECT * FROM Categories " ) ; // Paging var result = tbl . Paged ( where : " UnitPrice > 20 " , currentPage : 2 , pageSize : 20 ) ;

Massive Updating var table = new Products () ; var poopy = new { ProductName = " Chicken Fingers " }; table . Update ( poopy , 12 ) ; // Works for a form on a web page table . Update ( poopy , Request . Form ) ; // Insert var table = new Categories () ; var newID = table . Insert ( new { CategoryName = " Buck Fify Stuff " , Description = " Things I like " } ) ; // Batch updates var table = new Products () ; var drinks = table . All ( " WHERE CategoryID = 8 " ) ; // what we get back here is an IEnumerable<ExpandoObject> foreach ( var item in drinks ) { item . CategoryID = 12 ; } table . Save ( drinks ) ;

Massive public class Productions : DynamicModel { public Productions (): base ( " MyConnectionString " , " Productions " , " ID " ) {} public override void Validate ( dynamic item ) { ValidatesPresenceOf ( " Title " ) ; ValidatesNumericalityOf ( item . Price ) ; ValidateIsCurrency ( item . Price ) ; if ( item . Price <= 0 ) Errors . Add ( " Price can't be negative " ) ; } } public class Customers : DynamicModel { public Customers (): base ( " MyConnectionString " , " Customers " , " ID " ) {} //Add the person to Highrise CRM when they're added to the system... public override void Inserted ( dynamic item ) { //send them to Highrise var svc = new HighRiseApi () ; svc . AddPerson (...) ; } } Changes notification Validation

PetaPoco Tiny ORM to use with non-dynamic POCO objects Inspired by Massive but works with strongly typed POCOs Also supports dynamic Expandos T4 template for generating classes from database schema Marking classes with attributes The query language is SQL Helper methods for Insert/Delete/Update/Save and IsNew Hooks for logging exceptions, installing value converters and mapping columns to properties without attributes Works even if you stuck with .NET 3.5

Simple.Data an ORM without O, the R or the M "A lightweight, dynamic data access component for .NET"

Simple.Data Microsoft.Data done right Really simple Protects from SQL injection Convention based and LINQ like syntax Master-detail relations without SELECT N+1 Easy testing with mock database

Simple.Data Syntax overview dynamic db = Database . Open () ; User user = db . Users . FindByUserName ( " bob " ) ; // Method name form user = db . Users . FindBy ( UserName : " bob " ) ; // Named parameter form @p0 = 'bob' SELECT * FROM Users WHERE UserName = @p0 IEnumerable < dynamic > customers = db . Customers . FindAll ( db . Customers . CustomerName == " Arthur " ) . OrderByCustomerName () . Distinct () ; @p1 = 'Arthur' select distinct dbo . customers . customerid , dbo . customers . customer_name from [ dbo ].[ customers ] where [ dbo ].[ customers ].[ customer_name ] = @p1 order by [ customer_name ] FindAllBy FindBy

Simple.Data Syntax overview var q = db . Employees . Query () . Join ( db . Department , Id : db . Employees . DepartmentId ) . Select ( db . Employees . Name , db . Department . Name . As ( " Department " )) ; var q = db . Employees . Find ( db . Employees . DepartmentId == db . Department . Id ) . Select ( db . Employees . Name , db . Department . Name . As ( " Department " )) ; select [ dbo ].[ employee ].[ name ], [ dbo ].[ department ].[ name ] as [ Department ] from [ dbo ].[ employee ] join [ dbo ].[ department ] on ([ dbo ].[ department ].[ id ] = [ dbo ].[ employee ].[ departmentid ]) Explicit join Natural join (dynamic form)

Simple.Data Syntax overview - Insert var user = db . Users . Insert ( Name : " Steve " , Age : 50 ) ; @p0 = 'Steve' @p1 = 50 insert into [ dbo ].[ Users ] ([ Name ],[ Age ]) values ( @p0 , @p1 ) var user = new User { Name = " Steve " , Age = 50 }; db . Users . Insert ( user ) ; By object Named parameters Generated SQL: Insert, Update and Delete methods return a row or rowSet of data that has just been modified. Insert and Update can be used in two forms, Named parameters and by object. The object can be a POCO or a dynamic.

Simple.Data Syntax overview - Update db . Users . UpdateById ( Id : 1 , Name : " Steve " , Age : 50 ) ; @p0 = 1 , @p1 = 'Steve' , @p2 = 50 update [ dbo ].[ Users ] set [ Name ] = @p1 , [ Age ] = @p2 where [ dbo ].[ Users ].[ Id ] = @p3 dynamic record = new SimpleRecord () ; record . Id = 1 ; record . Name = " Steve " ; record . Age = 50 ; db . Users . UpdateById ( record ) ; // Method name form db . Users . Update ( record ) ; // By Primary Key By object (can be POCO or dynamic) Named parameters Generated SQL:

Simple.Data Syntax overview - UpdateAll db . Users . UpdateAll ( Name : " Steve " ) ; @p0 = 'Steve' update [ dbo ].[ Users ] set [ Name ] = @p Named parameters db . Users . UpdateAll ( Name : " Steve " , Condition : db . Users . Age > 30 ) ; db . Users . UpdateAll ( db . Users . Age > 30 , Name : " Steve " ) ; With expression @p0 = 'Steve' @p1 = 30 update [ dbo ].[ Users ] set [ Name ] = @p0 where [ dbo ].[ Users ].[ Age ] > @p1

Simple.Data Syntax overview - Delete db . Users . Delete ( Id : 1 ) ; Named parameters db . Users . DeleteById ( Id : 1 ) ; db . Users . DeleteAll ( db . Users . Age > 42 && db . Users . Name . Like ( " J% " )) ; Method name form db . Users . DeleteAll () ; With expression With no Where clause

Simple.Data Personal experience Used in two production systems. First one is CQRS based and Simple.Data is used to actualize “Read Model” there. Within the second one, Simple.Data is used to store normalized data which we receive from third party in XML form. In both systems Simple.Data is used for integration tests. It just amazing how simpler design can be when you don’t need data classes just to map them to database tables.

Simple.Data Real code examples

TL;DR What I liked in Micro ORMs Usually leads to better performance . Though, that was not a key feature for me. Write less, do more – instead of writing infrastructural code (Session management, Repositories, Specifications, Mappings etc.) you concentrated on getting things done…. things which business needs, not technical issues dictated by our infrastructure. With less features in Micro ORMs you are forced to design things simpler – simpler object hierarchies, simpler database schema. And you are forced to apply good patterns. Separating Reads and Writes is a good example. That all leads to a better design .

References General “ ORM is an anti-pattern” article – http://seldo.com/weblog/2011/06/15/orm_is_an_antipattern Micro ORM Samples – https://github.com/ijrussell/MicroORM InfoQ. Micro ORMs with Sam Saffron and Rob Conery – http://www.infoq.com/articles/ORM-Saffron-Conery Hanselminutes Podcast 262 - The Rise of the Micro-ORM with Sam Saffron and Rob Conery http://www.hanselman.com/blog/HanselminutesPodcast262TheRiseOfTheMicroORMWithSamSaffronAndRobConery.aspx Dapper-dot-net Home – http://code.google.com/p/dapper-dot-net/ (with performance comparison) “ How I learned to stop worrying and write my own ORM” – http://samsaffron.com/archive/2011/03/30/How+I+learned+to+stop+worrying+and+write+my+own+ORM “ A day in the life of a slow page at Stack Overflow” - http://samsaffron.com/archive/2011/05/02/A+day+in+the+life+of+a+slow+page+at+Stack+Overflow Massive Home – https://github.com/robconery/massive Rob Conery blog - http://wekeroad.com/

References PetaPoco Source – https://github.com/toptensoftware/petapoco Documentation – http://www.toptensoftware.com/petapoco/ Simple.Data Source – https://github.com/markrendle/Simple.Data Documentation – http://simplefx.org/simpledata/docs/ Mark Rendle blog - http://blog.markrendle.net/ HERDING CODE 106: MARK RENDLE ON SIMPLE.DATA (podcast) – http://herdingcode.com/?p=305 .Net Rocks! podcast “Mark Rendle Has Some Simple.Data” – http://www.dotnetrocks.com/default.aspx?showNum=683

Follow Friday @marcgravell @markrendle @robconery @samsaffron @toptensoftware

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