Scala and Spring


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This presentation shows how Spring can be used with Scala.

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Scala and Spring

  1. 1. Eberhard WolffArchitecture and Technology Manageradesso AG, GermanySpring und Scala
  2. 2. About me•  Eberhard Wolff•  Architecture & Technology Manager at adesso•  adesso is a leading IT consultancy in Germany•  Speaker•  Author (e.g. first German Spring book)•  Blog:•  Twitter: @ewolff••
  3. 3. Why Scala and Spring?•  Scala •  Spring –  Strongly typed –  The tools for language enterprise apps –  Elegant –  Well established –  Functional –  Lots of know how programming –  Very flexible –  Focus on Concurrency –  Lack of enterprise frameworks
  4. 4. Spring‘s Core Elements•  Dependency Injection –  Organize the collaboration of objects•  Aspect Oriented Programming –  Handle cross cutting concerns like security or transactions•  Portable Service Abstraction –  Easy, unified APIs for JMS, JDBC, tx …•  Testing•  How can they be used with Scala?
  6. 6. Dependency Injection•  Depended objects are injected•  Advantages: –  Better handling of dependencies –  Easier testability –  Easier configuration
  7. 7. Dependency Injection•  Dependency Injection is a Pattern•  i.e. you can implement it in code•  …and therefore in plain Scala•  Configuration in a file: more flexibility –  No compile / redeploy –  Configure values, not just references•  Spring offers a lot of approaches to DI•  XML, JavaConfig and Annotations
  8. 8. Example •  DAO depends on a DataSource •  Injected in the constructor •  Matches Scala’s immutability approachclass CustomerDAO(dataSource: DataSource) { val jdbcTemplate = new JdbcTemplate(dataSource) ... }
  9. 9. On Singletons•  Scala introduces objects as Singletons•  Example uses Scala classes•  Spring needs to do the creation so Dependency Injection can be done•  Might consider @Configurable but that adds AspectJ Load Time Weaving…•  More flexibility concerning scopes
  10. 10. Spring XML Configuration<beans ...> <jdbc:embedded-database type="HSQL" id="dataSource" /> <bean id="customerDAO" class="de.adesso.scalaspring.dao.CustomerDAO"> <constructor-arg ref="dataSource" /> </bean> </beans>
  11. 11. Spring XML Configuration•  Very easy and little difference to Java•  Scala won’t create getter and setter for <property >•  So: Use Scala’s @BeanProperty to generate getters and setters•  Marks property as configurable by Spring•  Might want to create your own Conversions to configure Scala types
  12. 12. Spring XML & Scala Collections •  Scala has its own collection classes •  Cannot be configured with Spring XML out of the box •  Need Conversions •  Or create custom namespace<bean class="de.adesso....ScalaBean"> <property name="list" > <scala:list > <value type="java.lang.Integer">42</value> </scala:list> </property> </bean>
  13. 13. Spring JavaConfig•  Allows the definition of Spring Beans using Java classes•  Classes contain code to create Spring Beans•  Still conforms to Spring Bean rules –  Singleton, AOP, autowiring etc•  Can be used with Scala
  14. 14. Spring JavaConfig with Scala@Configuration class ScalaConfig { Defined in XML @Autowired var dataSource: DataSource = _ @Bean Not really def transactionManager() = elegant.. new DataSourceTransactionManager(dataSource) @Bean def customerDAO() = new CustomerDAO(dataSource) }
  15. 15. Spring JavaConfig•  Almost like a Spring Configuration DSL•  No need for Spring Scala DSL (?)•  Full power of Scala for creating objects•  Can also add configuration for value from properties files etc•  Also nice for infrastructure•  But reconfiguration = recompiling and redeployment
  16. 16. Annotations•  Annotate classes•  Classpath scanned for annotated classes•  These become Spring beans
  17. 17. Annotations Code@Component class CustomerDAO { @Autowired var dataSource: DataSource = _ }<beans ... > <context:component-scan base-package="de.adesso.scalaspring.dao" />
  18. 18. Annotations Code@Component class CustomerDAO(dataSource: DataSource) { }<beans ... default-autowire="constructor"> <context:component-scan base-package="de.adesso.scalaspring.dao" />
  19. 19. Naming Convention No annotations – just a naming conventionclass CustomerDAO(dataSource: DataSource) { }<context:component-scan base-package="de.adesso.scalaspring.dao" use-default-filters="false"> <context:include-filter type="regex" expression=".*DAO" /> </context:component-scan>
  21. 21. Service Abstraction•  Example: JDBC•  Common advantages: –  Runtime exceptions instead of checked exceptions –  Uniform API (e.g. transactions) –  Resource handling solved
  22. 22. Service Abstraction: Code •  Works out of the box •  However, needs Java type issues (Integer)class CustomerDAO(dataSource: DataSource) { val jdbcTemplate = new JdbcTemplate(dataSource) def deleteById(id: Int) = jdbcTemplate.update( "DELETE FROM CUSTOMER WHERE ID=?", id : java.lang.Integer) }
  23. 23. More Complex•  How can one access a ResultSet?•  Resource handled by JDBC•  Cannot return it – it has to be closed•  Solution: callback•  …and inner class
  24. 24. Callbacks in Javapublic class CustomerDAO extends SimpleJdbcDaoSupport { private static final class CustomerResultSetRowMapper implements ParameterizedRowMapper<Customer> { public Customer mapRow(ResultSet rs, int rowNum) { Customer customer = new Customer(rs.getString(1), rs.getString(2), rs.getDouble(4)); customer.setId(rs.getInt(3)); return customer; } } public List<Customer> getByName(String name) { return getSimpleJdbcTemplate() .query( "SELECT * FROM T_CUSTOMER WHERE NAME=?", new CustomerResultSetRowMapper(), name); } }
  25. 25. Callbacks in Scala•  Callbacks are really functions•  Called on each row•  Use template with Scala function?
  26. 26. Callback in Scaladef findById(id: Int): Option[Customer] = { val result: Buffer[Customer] = jdbcTemplate.query( "SELECT * FROM CUSTOMER C WHERE C.ID=?", (rs: ResultSet) => { Customer(rs.getInt(1), rs.getString(2), rs.getString(3), rs.getDouble(4)) } : RowMapper[Customer] ,id : java.lang.Integer) result.headOption }•  Why can the function be converted in a RowMapper?
  27. 27. Implicit Conversions in Scalaimplicit def double2int(d:Double): Int = d.toInt •  Implicits allow conversion from one type to another•  Example: Double to Int•  Used any time an Int is needed and a Double is provided•  Can we use implicits to convert a function to a callback class?
  28. 28. Implicit for Function to Callback•  Converts a function into a callback object•  Transparently behind the scenesimplicit def rowMapperImplicit[T]( func: (ResultSet) => T) = { new RowMapper[T] { def mapRow(rs: ResultSet, rowNum: Int) = func(rs) } }
  29. 29. Some Problems•  Scala value types and collections must be converted to Java objects (i.e. Int to Integer)•  null instead of Option[T]•  classOf[T] instead of plain type•  Wrapper would be more natural but more effort
  31. 31. Why AOP?•  Centralized implementation of cross cutting concerns•  E.g. security, transactions, tracing..•  Aspect = –  Advice : executed code –  Pointcut : where the code is executed•  Let’s see some Pointcut expressions…
  32. 32. execution(void hello())Execution of method hello, no parameters, void return type
  33. 33. execution(int com.ewolff.Service.hello(int))Execution of method hello in class Service in package com.ewolff one int as parameters, int return type
  34. 34. execution(* *..*Service.*(..))Execution of any method in class in any package with suffix Service Any number of parameters, any return type Any Service i.e. add behavior to every service (security, transaction) Defines what constitutes a service Proper and orderly usage of AOP
  35. 35. AOP Example@Aspect public class TracingAspect { @Before("execution(* com.ewolff.highscore..*.*(..))") public void traceEnter(JoinPoint joinPoint) { System.out.println("enter "+joinPoint); } @After("execution(* com.ewolff.highscore..*.*(..))") public void traceExit(JoinPoint joinPoint) { System.out.println("exit "+joinPoint); } }
  36. 36. Problems•  Must provide parameter less constructor•  Pointcut depends on Java type system•  Scala has a different type system•  Can combine Scala + Spring AOP –  Use bean Pointcut: bean(aVerySpecificBean)
 bean(*DAO) –  Or Annotations: execution(@retry.Retry * *(..))
  37. 37. Transactions with AOP @Transactional class CustomerDAO(dataSource: DataSource) { @Transactional def save(customer: Customer): Customer = { } }•  Spring’s @Transaction annotation•  AOP is used for transactions and security•  Mark a method or class as transactional•  AOP behind the scenes
  38. 38. AOP and Scala: 2nd Thought•  Spring AOP is not efficient•  Method calls are done dynamically•  AspectJ will make project setup too complex•  A modern programming language should handle cross cutting concerns•  E.g. meta programming in dynamic languages•  Can we do better?
  39. 39. Functions•  Can use functions to “wrap” methods, blocks and functions and do transactions•  Based on TransactionTemplate and callbacks•  TransactionTemplate executes callbacks in a transaction
  40. 40. Codeimplicit def txCallbackImplicit[T](func: => T)… •  Again implicit•  Converts a function with return type T to a TransactionCallback •  Now we need to call the TransactionTemplate to provide the transaction•  A function will take the transaction configuration and call the passed in function
  41. 41. Code 1st parameter: transaction configurationdef transactional[T] ( propagation: Propagation = Propagation.REQUIRED, …) 2nd parameter: function(func: => T): T = { val txAttribute = new TransactionAttributeWithRollbackRules( propagation,…) val txTemplate = new TransactionTemplate(txManager,txAttribute) txTemplate.execute(func) } Call TransactionTemplate with function (converted to TransactionCallback) and configuration
  42. 42. Usage •  Can wrap methods to make them transactional@Component class TxCustomerDAO(dataSource: DataSource) { def save(customer: Customer): Customer = transactional() { jdbcTemplate.update(…); } }
  43. 43. Usage •  Can also be used to wrap any code block •  But: No way to make a whole class / system transactionaltransactional(propagation=Propagation.REQUIRED) { Customer(0, "Wolff", "Eberhard", 42.0)) }
  44. 44. TESTING
  45. 45. Testing in Spring•  Injection in Test classes•  Transaction handling –  Start a transaction for each test method –  At the end of the method: Rollback•  Benefit: No need to clean up the database•  Good start: No production code in Scala
  46. 46. Testing with JUnit 4, Spring and Scala@RunWith(classOf[SpringJUnit4ClassRunner]) @Transactional @ContextConfiguration( Array("/spring/scalaSpringConfig.xml")) class CustomerDAOTest extends Config { @Autowired var customerDAO : CustomerDAO = null @Test def testSaveDelete() { val numberOfCustomersBefore = customerDAO.count() …} }
  47. 47. SUM UP
  48. 48. Sum Up•  Scala and Spring are a good match•  Spring is very adaptable•  Dependency Injection –  XML works, some improvements possible –  Annotations and JavaConfig: No problems•  Service Abstraction –  Functions are a good fit•  AOP –  Can work with Scala but not ideal –  Scala can do similar things with functions
  49. 49. Potential Improvements•  Dependency Injection –  Support for Scala collections mostly done –  Support for Scala properties (no @BeanProperty) –  Support for Scala Objects aka Singletons –  Conversions for all basic Scala types –  Spring configuration DSL (?)•  Service Abstraction –  Provide implicits for non-JDBC callbacks
  50. 50. Potential Improvements•  AOP –  Provide functions for all common aspects besides transaction•  Testing –  Support Scala test frameworks –
  51. 51. Links••  Request for Scala version of Spring (only 16 votes)•  Scala and AspectJ: Approaching modularization of crosscutting functionalities•  Sample for Spring Security and Scala•  Spring Integration Scala DSL•  (German) Thesis about Scala & Lift vs. Java EE: webframeworks-lift-mit-dem-java-ee-programmiermodell•  (German) Thesis about Scala, JSF and Hibernate:
  52. 52. Wir suchen Sie alsØ  Software-Architekt (m/w)Ø  Projektleiter (m/w)Ø  Senior Software Engineer (m/w)Ø  Kommen Sie zum Stand und gewinnen Sie ein iPad 2!
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