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eBook – Mockito – NPI EA (tag = Mockito)
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Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

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eBook – Reactive – NPI EA (cat=Reactive)
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Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:

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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

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eBook – Jackson – NPI EA (cat=Jackson)
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eBook – Persistence – NPI EA (cat=Persistence)
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Course – LS – NPI EA (cat=Jackson)
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Course – RWSB – NPI EA (cat=REST)
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Explore Spring Boot 3 and Spring 6 in-depth through building a full REST API with the framework:

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Course – LSS – NPI EA (cat=Spring Security)
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Yes, Spring Security can be complex, from the more advanced functionality within the Core to the deep OAuth support in the framework.

I built the security material as two full courses - Core and OAuth, to get practical with these more complex scenarios. We explore when and how to use each feature and code through it on the backing project.

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Course – LSD – NPI EA (tag=Spring Data JPA)
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Spring Data JPA is a great way to handle the complexity of JPA with the powerful simplicity of Spring Boot.

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Partner – Moderne – NPI EA (cat=Spring Boot)
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Refactor Java code safely — and automatically — with OpenRewrite.

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Course – LJB – NPI EA (cat = Core Java)
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Partner – LambdaTest – NPI EA (cat= Testing)
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Distributed systems often come with complex challenges such as service-to-service communication, state management, asynchronous messaging, security, and more.

Dapr (Distributed Application Runtime) provides a set of APIs and building blocks to address these challenges, abstracting away infrastructure so we can focus on business logic.

In this tutorial, we'll focus on Dapr's pub/sub API for message brokering. Using its Spring Boot integration, we'll simplify the creation of a loosely coupled, portable, and easily testable pub/sub messaging system:

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1. Overview

Spring’s @Transactional annotation provides a nice declarative API to mark transactional boundaries.

Behind the scenes, an aspect takes care of creating and maintaining transactions as they are defined in each occurrence of the @Transactional annotation. This approach makes it easy to decouple our core business logic from cross-cutting concerns such as transaction management.

In this tutorial, we’ll see that this isn’t always the best approach. We’ll explore what programmatic alternatives Spring provides, such as TransactionTemplate, and our reasons for using them.

2. Trouble in Paradise

Let’s suppose we’re mixing two different types of I/O in a simple service:

@Transactional
public void initialPayment(PaymentRequest request) {
    savePaymentRequest(request); // DB
    callThePaymentProviderApi(request); // API
    updatePaymentState(request); // DB
    saveHistoryForAuditing(request); // DB
}

Here we have a few database calls alongside a possibly expensive REST API call. At first glance, it might make sense to make the whole method transactional since we may want to use one EntityManager to perform the whole operation atomically.

However, if that external API takes longer than usual to respond for whatever reason, we may soon run out of database connections!

2.1. The Harsh Nature of Reality

Here’s what happens when we call the initialPayment method:

  1. The transactional aspect creates a new EntityManager and starts a new transaction, so it borrows one Connection from the connection pool.
  2. After the first database call, it calls the external API while keeping the borrowed Connection.
  3. Finally, it uses that Connection to perform the remaining database calls.

If the API call responds very slowly for a while, this method would hog the borrowed Connection while waiting for the response.

Imagine that during this period we get a burst of calls to the initialPayment method. In that case, all Connections may wait for a response from the API call. That’s why we may run out of database connections — because of a slow back-end service!

Mixing the database I/O with other types of I/O in a transactional context isn’t a great idea. So, the first solution for these sorts of problems is to separate these types of I/O altogether. If for whatever reason we can’t separate them, we can still use Spring APIs to manage transactions manually.

3. Using TransactionTemplate

TransactionTemplate provides a set of callback-based APIs to manage transactions manually. In order to use it, we should first initialize it with a PlatformTransactionManager.

We can set up this template using dependency injection:

// test annotations
class ManualTransactionIntegrationTest {

    @Autowired
    private PlatformTransactionManager transactionManager;

    private TransactionTemplate transactionTemplate;

    @BeforeEach
    void setUp() {
        transactionTemplate = new TransactionTemplate(transactionManager);
    }

    // omitted
}

The PlatformTransactionManager helps the template to create, commit or roll back transactions.

When using Spring Boot, an appropriate bean of type PlatformTransactionManager will be automatically registered, so we just need to simply inject it. Otherwise, we should manually register a PlatformTransactionManager bean.

3.1. Sample Domain Model

From now on, for the sake of demonstration, we’re going to use a simplified payment domain model.

In this simple domain, we have a Payment entity to encapsulate each payment’s details:

@Entity
public class Payment {

    @Id
    @GeneratedValue
    private Long id;

    private Long amount;

    @Column(unique = true)
    private String referenceNumber;

    @Enumerated(EnumType.STRING)
    private State state;

    // getters and setters

    public enum State {
        STARTED, FAILED, SUCCESSFUL
    }
}

Also, we’ll initialize TransactionTemplate  instance before each test case:

@DataJpaTest
@ActiveProfiles("test")
@Transactional(propagation = NOT_SUPPORTED) // we're going to handle transactions manually
public class ManualTransactionIntegrationTest {

    @Autowired 
    private PlatformTransactionManager transactionManager;

    @Autowired 
    private EntityManager entityManager;

    private TransactionTemplate transactionTemplate;

    @BeforeEach
    public void setUp() {
        transactionTemplate = new TransactionTemplate(transactionManager);
    }

    // tests

}

3.2. Transactions With Results

The TransactionTemplate offers a method called execute, which can run any given block of code inside a transaction and then return some result:

@Test
void givenAPayment_WhenNotDuplicate_ThenShouldCommit() {
    Long id = transactionTemplate.execute(status -> {
        Payment payment = new Payment();
        payment.setAmount(1000L);
        payment.setReferenceNumber("Ref-1");
        payment.setState(Payment.State.SUCCESSFUL);

        entityManager.persist(payment);

        return payment.getId();
    });

    Payment payment = entityManager.find(Payment.class, id);
    assertThat(payment).isNotNull();
}

Here we’re persisting a new Payment instance into the database and then returning its auto-generated id.

Similar to the declarative approach, the template can guarantee atomicity for us.

If one of the operations inside a transaction fails to complete, it rolls back all of them:

@Test
void givenTwoPayments_WhenRefIsDuplicate_ThenShouldRollback() {
    try {
        transactionTemplate.execute(status -> {
            Payment first = new Payment();
            first.setAmount(1000L);
            first.setReferenceNumber("Ref-1");
            first.setState(Payment.State.SUCCESSFUL);

            Payment second = new Payment();
            second.setAmount(2000L);
            second.setReferenceNumber("Ref-1"); // same reference number
            second.setState(Payment.State.SUCCESSFUL);

            entityManager.persist(first); // ok
            entityManager.persist(second); // fails

            return "Ref-1";
        });
    } catch (Exception ignored) {}

    assertThat(entityManager.createQuery("select p from Payment p").getResultList()).isEmpty();
}

Since the second referenceNumber is a duplicate, the database rejects the second persist operation, causing the whole transaction to roll back. Therefore, the database does not contain any payments after the transaction.

It’s also possible to manually trigger a rollback by calling the setRollbackOnly() on TransactionStatus:

@Test
void givenAPayment_WhenMarkAsRollback_ThenShouldRollback() {
    transactionTemplate.execute(status -> {
        Payment payment = new Payment();
        payment.setAmount(1000L);
        payment.setReferenceNumber("Ref-1");
        payment.setState(Payment.State.SUCCESSFUL);

        entityManager.persist(payment);
        status.setRollbackOnly();

        return payment.getId();
    });

    assertThat(entityManager.createQuery("select p from Payment p").getResultList()).isEmpty();
}

3.3. Transactions Without Results

If we don’t intend to return anything from the transaction, we can use the TransactionCallbackWithoutResult callback class:

@Test
void givenAPayment_WhenNotExpectingAnyResult_ThenShouldCommit() {
    transactionTemplate.execute(new TransactionCallbackWithoutResult() {
        @Override
        protected void doInTransactionWithoutResult(TransactionStatus status) {
            Payment payment = new Payment();
            payment.setReferenceNumber("Ref-1");
            payment.setState(Payment.State.SUCCESSFUL);

            entityManager.persist(payment);
        }
    });

    assertThat(entityManager.createQuery("select p from Payment p").getResultList()).hasSize(1);
}

3.4. Custom Transaction Configurations

Up until now, we used the TransactionTemplate with its default configuration. Although this default is more than enough most of the time, it’s still possible to change configuration settings.

Let’s set the transaction isolation level:

transactionTemplate = new TransactionTemplate(transactionManager);
transactionTemplate.setIsolationLevel(TransactionDefinition.ISOLATION_REPEATABLE_READ);

Similarly, we can change the transaction propagation behavior:

transactionTemplate.setPropagationBehavior(TransactionDefinition.PROPAGATION_REQUIRES_NEW);

Or we can set a timeout, in seconds, for the transaction:

transactionTemplate.setTimeout(1000);

It’s even possible to benefit from optimizations for read-only transactions:

transactionTemplate.setReadOnly(true);

Once we create a TransactionTemplate with a configuration, all transactions will use that configuration to execute. So, if we need multiple configurations, we should create multiple template instances.

4. Using PlatformTransactionManager

In addition to the TransactionTemplate, we can use an even lower-level API such as PlatformTransactionManager to manage transactions manually. Quite interestingly, both @Transactional and TransactionTemplate use this API to manage their transactions internally.

4.1. Configuring Transactions

Before using this API, we should define how our transaction is going to look.

Let’s set a three-second timeout with the repeatable read transaction isolation level:

DefaultTransactionDefinition definition = new DefaultTransactionDefinition();
definition.setIsolationLevel(TransactionDefinition.ISOLATION_REPEATABLE_READ);
definition.setTimeout(3);

Transaction definitions are similar to TransactionTemplate configurations. However, we can use multiple definitions with just one PlatformTransactionManager.

4.2. Maintaining Transactions

After configuring our transaction, we can programmatically manage transactions:

@Test
void givenAPayment_WhenUsingTxManager_ThenShouldCommit() {
 
    // transaction definition

    TransactionStatus status = transactionManager.getTransaction(definition);
    try {
        Payment payment = new Payment();
        payment.setReferenceNumber("Ref-1");
        payment.setState(Payment.State.SUCCESSFUL);

        entityManager.persist(payment);
        transactionManager.commit(status);
    } catch (Exception ex) {
        transactionManager.rollback(status);
    }

    assertThat(entityManager.createQuery("select p from Payment p").getResultList()).hasSize(1);
}

5. Conclusion

In this article, we first saw when we should choose programmatic transaction management over the declarative approach.

Then, by introducing two different APIs, we learned how to manually create, commit or roll back any given transaction.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.
Baeldung Pro – NPI EA (cat = Baeldung)
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Baeldung Pro comes with both absolutely No-Ads as well as finally with Dark Mode, for a clean learning experience:

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Once the early-adopter seats are all used, the price will go up and stay at $33/year.

eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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The Apache HTTP Client is a very robust library, suitable for both simple and advanced use cases when testing HTTP endpoints. Check out our guide covering basic request and response handling, as well as security, cookies, timeouts, and more:

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

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eBook – Persistence – NPI EA (cat=Persistence)
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Working on getting your persistence layer right with Spring?

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Course – LS – NPI EA (cat=REST)

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Partner – Moderne – NPI EA (tag=Refactoring)
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Modern Java teams move fast — but codebases don’t always keep up. Frameworks change, dependencies drift, and tech debt builds until it starts to drag on delivery. OpenRewrite was built to fix that: an open-source refactoring engine that automates repetitive code changes while keeping developer intent intact.

The monthly training series, led by the creators and maintainers of OpenRewrite at Moderne, walks through real-world migrations and modernization patterns. Whether you’re new to recipes or ready to write your own, you’ll learn practical ways to refactor safely and at scale.

If you’ve ever wished refactoring felt as natural — and as fast — as writing code, this is a good place to start.

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