This presentation shows how Spring can be used with Scala.

1. Eberhard Wolff
Architecture and Technology Manager
adesso AG, Germany
Spring und Scala

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: http://ewolff.com
• Twitter: @ewolff
• http://slideshare.com/ewolff
• eberhard.wolff@adesso.de

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. 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?

5. DEPENDENCY INJECTION

6. Dependency Injection
• Depended objects are injected
• Advantages:
– Better handling of dependencies
– Easier testability
– Easier configuration

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. Example
• DAO depends on a DataSource
• Injected in the constructor
• Matches Scala’s immutability approach
class CustomerDAO(dataSource: DataSource) {
val jdbcTemplate = new JdbcTemplate(dataSource)
...
}

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. 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. 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. 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. 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. 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. 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. Annotations
• Annotate classes
• Classpath scanned for annotated classes
• These become Spring beans

17. Annotations Code
@Component
class CustomerDAO {
@Autowired
var dataSource: DataSource = _
}
<beans ... >
<context:component-scan
base-package="de.adesso.scalaspring.dao" />

18. Annotations Code
@Component
class CustomerDAO(dataSource: DataSource) {
}
<beans ... default-autowire="constructor">
<context:component-scan
base-package="de.adesso.scalaspring.dao" />

19. Naming Convention
No annotations – just a naming convention
class 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>

20. SERVICE ABSTRACTION

21. Service Abstraction
• Example: JDBC
• Common advantages:
– Runtime exceptions instead of checked
exceptions
– Uniform API (e.g. transactions)
– Resource handling solved

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. 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. Callbacks in Java
public 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. Callbacks in Scala
• Callbacks are really functions
• Called on each row
• Use template with Scala function?

26. Callback in Scala
def 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. Implicit Conversions in Scala
implicit 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. Implicit for Function to Callback
• Converts a function into a callback object
• Transparently behind the scenes
implicit def rowMapperImplicit[T](
func: (ResultSet) => T) = {
new RowMapper[T] {
def mapRow(rs: ResultSet, rowNum: Int)
= func(rs)
}
}

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

30. ASPECT ORIENTED
PROGRAMMING

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. execution(void hello())
Execution of method hello, no parameters, void return type

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. 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. 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. 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. 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. 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. 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. Code
implicit 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. Code 1st parameter:
transaction configuration
def 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. Usage
• Can wrap methods to make them
transactional
@Component
class TxCustomerDAO(dataSource: DataSource) {
def save(customer: Customer): Customer =
transactional() {
jdbcTemplate.update(…);
}
}

43. Usage
• Can also be used to wrap any code block
• But: No way to make a whole class /
system transactional
transactional(propagation=Propagation.REQUIRED)
{
customerDAO.save(
Customer(0, "Wolff", "Eberhard", 42.0))
}

44. TESTING

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. 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. SUM UP

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. 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. Potential Improvements
• AOP
– Provide functions for all common aspects besides
transaction
• Testing
– Support Scala test frameworks
– http://www.cakesolutions.org/specs2-spring.html

51. Links
• https://github.com/ewolff/scala-spring
• Request for Scala version of Spring (only 16 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

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