Spring Day | Spring and Scala | Eberhard Wolff


Published on

2011-10-31 | 09:45 AM - 10:30 AM
Spring is widely used in the Java world - but does it make any sense to combine it with Scala? This talk gives an answer and shows how and why Spring is useful in the Scala world. All areas of Spring such as Dependency Injection, Aspect-Oriented Programming and the Portable Service Abstraction as well as Spring MVC are covered.

Published in: Technology
1 Like
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Spring Day | Spring and Scala | Eberhard Wolff

  1. 1. Scala and Spring Eberhard WolffArchitecture and Technology Manager adesso AG, Germany
  2. 2. 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
  3. 3. 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?
  4. 4. Dependency Injection
  5. 5. Dependency Injection•  Depended objects are injected•  Advantages: –  Better handling of dependencies –  Easier testability –  Easier configuration
  6. 6. 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
  7. 7. Example •  DAO depends on a DataSource •  Injected in the constructor •  Matches Scala’s immutability approachclass CustomerDAO(dataSource: DataSource) { val jdbcTemplate = new JdbcTemplate(dataSource) ... }
  8. 8. 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
  9. 9. 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>
  10. 10. Spring XML Configuration•  Very easy and little difference to Java•  For optional configuration: Use @BeanProperty to generate getters and setters•  Marks property as configurable by Spring•  Might want to create your own Conversions to configure Scala types
  11. 11. 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>
  12. 12. 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
  13. 13. 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) }
  14. 14. 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
  15. 15. Annotations•  Annotate classes•  Classpath scanned for annotated classes•  These become Spring beans
  16. 16. Annotations Code@Component class CustomerDAO { @Autowired var dataSource: DataSource = _ }<beans ... > <context:component-scan base-package="de.adesso.scalaspring.dao" />
  17. 17. Annotations Code@Component class CustomerDAO(dataSource: DataSource) { }<beans ... default-autowire="constructor"> <context:component-scan base-package="de.adesso.scalaspring.dao" />
  18. 18. 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>
  19. 19. Service Abstraction
  20. 20. Service Abstraction•  Example: JDBC•  Common advantages: –  Runtime exceptions instead of checked exceptions –  Uniform API (e.g. transactions) –  Resource handling solved
  21. 21. 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) }
  22. 22. 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
  23. 23. 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); } }
  24. 24. Callbacks in Scala•  Callbacks are really functions•  Called on each row•  Use template with Scala function?
  25. 25. 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)) }, id : java.lang.Integer) result.headOption }
  26. 26. Behind the Scenes: Implicit •  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).asInstanceOf[T] } }
  27. 27. 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
  28. 28. Aspect Oriented Programming
  29. 29. 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…
  30. 30. execution(void hello())Execution of method hello, no parameters, void return type
  31. 31. 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
  32. 32. execution(* *Service.*(..)) Execution of any method in class with suffix 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
  33. 33. 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); } }
  34. 34. 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 * *(..))
  35. 35. 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?
  36. 36. Functions•  Can use functions to “wrap” methods, blocks and functions and do transactions•  Based on TransactionTemplate and callbacks
  37. 37. Codeimplicit def txCallbackImplicit[T](func: => T)… def transactional[T]( propagation: Propagation = Propagation.REQUIRED, …) (func: => T): T = { val txAttribute = new TransactionAttributeWithRollbackRules( propagation,…) val txTemplate = new TransactionTemplate(txManager,txAttribute) txTemplate.execute(func) }
  38. 38. Usage •  Can be used to wrap any code block •  Not just methods •  But: No way to make a whole class / system transactionaltransactional(propagation = Propagation.REQUIRES_NEW) { customerDAO.save( Customer(0, "Wolff", "Eberhard", 42.0)) throw new RuntimeException() }
  39. 39. Testing
  40. 40. 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
  41. 41. 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() …} }
  42. 42. Sum Up
  43. 43. Sum Up•  Scala and Spring are a good match•  Spring is very adaptable•  Dependency Injection –  Works, some improvements possible•  Service Abstraction –  Functions are a good fit•  AOP –  Can work with Scala but not ideal –  Scala can do similar things with functions
  44. 44. Potential Improvements•  Dependency Injection –  Support for all Scala collections –  Support for Scala properties –  Support for Scala singletons –  Conversions for all basic Scala types –  Spring configuration DSL•  Service Abstraction –  Provide implicits for all callbacks
  45. 45. Potential Improvements•  AOP –  Provide functions for all common aspects•  Testing –  Support Scala test frameworks –  http://www.cakesolutions.org/specs2- spring.html
  46. 46. Links•  https://github.com/ewolff/scala-spring•  Request for Scala version of Spring (only 12 votes) https://jira.springsource.org/browse/SPR-7876•  Scala and AspectJ: Approaching modularization of crosscutting functionalities http://days2011.scala-lang.org/sites/days2011/files/ 52.%20AspectJ.pdf•  Sample for Spring Security and Scala https://github.com/tekul/scalasec•  Spring Integration Scala DSL https://github.com/SpringSource/spring-integration-scala•  (German) Thesis about Scala & Lift vs. Java EE: http://www.slideshare.net/adessoAG/vergleich-des-scala- webframeworks-lift-mit-dem-java-ee-programmiermodell•  (German) Thesis about Scala, JSF and Hibernate: http://www.slideshare.net/bvonkalm/thesis-5821628