feat : implement concurrent consumers using separate thread #617
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WalkthroughThis pull request introduces a new Kafka Spring Boot project focused on concurrent message processing. It establishes a complete project structure with source code, configuration files, Maven wrapper, and a GitHub Actions workflow for automated building and testing. The project demonstrates a multi-threaded Kafka consumer approach, including a main application class, listener, and processor classes that handle messages concurrently across different threads. Changes
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Actionable comments posted: 0
🧹 Nitpick comments (7)
.github/workflows/kafka-boot-concurrent-kafka-consumer.yml (1)
21-27: Remove trailing spaces and correct indentation.The static analysis tools detected trailing spaces on line 21 and indentation mismatches on lines 22, 25, and 27. This can cause YAML parsing or style-check issues.
Apply this diff to fix:
- run: - working-directory: kafka-spring-boot/boot-concurrent-kafka-consumer + run: + working-directory: kafka-spring-boot/boot-concurrent-kafka-consumer - - uses: actions/checkout@v4 + - uses: actions/checkout@v4 - with: + with:🧰 Tools
🪛 yamllint (1.35.1)
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kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java (1)
21-24: Use a thread-safe structure if registration occurs in parallel.
You’re returning anArrayList, which is not thread-safe. If the application or test environment somehow registersToUpperStringProcessorbeans concurrently, it could cause concurrency issues. Although this may not be the case here, you might consider using a thread-safe collection.- @Bean("toUpperStringProcessors") - List<ToUpperStringProcessor> toUpperStringProcessors() { - return new ArrayList<>(); - } + @Bean("toUpperStringProcessors") + List<ToUpperStringProcessor> toUpperStringProcessors() { + return Collections.synchronizedList(new ArrayList<>()); + }kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/processor/ToUpperStringProcessor.java (2)
51-56: Consider bounded queue or fallback strategy.
Using an unboundedLinkedBlockingQueuemay risk indefinite growth if message production outpaces consumption, potentially leading to memory exhaustion. Consider using a bounded queue or a more robust fallback policy if high throughput is expected.
73-75: Efficient set retrieval.
Building a newHashSetfrom the queue is acceptable, but frequent calls ofdistinctQueuedData()on a large queue could become costly. Consider caching or limiting calls if performance becomes a concern.kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/listener/AppListener.java (1)
42-45: Validate offsets after processing.
It might be beneficial to confirm whether the message offset is committed before or after theexecuteOnDedicatedProcessorcall. If it is committed prematurely, a crash could lead to unprocessed messages being skipped.kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java (2)
41-47: Effective concurrency test.
Sending 1000 messages is a good way to stress-test concurrency. Ensure that your CI environment provides enough resources (CPU, memory) to avoid timeouts or failures due to slow performance.
54-62: Documentation vs. Code mismatch.
The JavaDoc comments mention “exactly two StringProcessor instances,” but the assertion requires 3. Update your documentation or logic to maintain consistency and prevent confusion.- * Verifies that there are exactly two StringProcessor instances... + * Verifies that there are exactly three StringProcessor instances...
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.github/workflows/kafka-boot-concurrent-kafka-consumer.yml(1 hunks)kafka-spring-boot/README.md(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/.gitignore(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/.mvn/wrapper/maven-wrapper.properties(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw.cmd(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/ConcurrentKafkaConsumer.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/listener/AppListener.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/processor/ToUpperStringProcessor.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/resources/application.properties(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/TestConcurrentKafkaConsumer.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ContainerConfig.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java(1 hunks)
✅ Files skipped from review due to trivial changes (4)
- kafka-spring-boot/boot-concurrent-kafka-consumer/.gitignore
- kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/ConcurrentKafkaConsumer.java
- kafka-spring-boot/boot-concurrent-kafka-consumer/.mvn/wrapper/maven-wrapper.properties
- kafka-spring-boot/README.md
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🪛 yamllint (1.35.1)
.github/workflows/kafka-boot-concurrent-kafka-consumer.yml
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🔇 Additional comments (12)
kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw.cmd (1)
1-149: Overall script logic looks robust.
This Maven Wrapper script is a standard, well-structured implementation for downloading and verifying Maven distributions. The licensing block and usage of environment variables for credentials, checksums, and verbose mode appear to follow best practices.
kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw (1)
1-259: Credential handling caution.
This script also supports credentials through environment variables. While typical for Maven Wrapper usage, please ensure sensitive credentials aren’t inadvertently exposed in verbose or debug logs. For heightened security, consider exploring alternatives such as secure storage or CI/CD secrets.
kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml (1)
1-91: Project configuration and dependency structure look good.
The POM properly declares the Spring Boot parent, Kafka dependencies, and uses Java 21. The Spotless Maven plugin enforces a standardized format. This setup is generally well-aligned with current Spring Boot and Kafka best practices.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/TestConcurrentKafkaConsumer.java (1)
7-13: Consider adding concurrency tests or at least verifying concurrency behavior.
The class sets up a Spring Application context for concurrent Kafka consumption but doesn’t appear to verify actual multithreaded message consumption. Recommend supplementing with tests that validate parallel processing and thread isolation to make sure concurrency is functioning properly.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ContainerConfig.java (1)
14-15: Looks good for Kafka container usage.
The chosen Docker image is suitable for testing, and using @ServiceConnection will help maintain container lifecycle in tests. Ensure you document the Docker image version clearly in the README or project documentation if needed.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java (1)
49-51: Validate listener ID splitting logic.
You are splitting the listener ID and capturing the last piece. Double-check that the listener ID is in the expected format (i.e., appended with thread identifiers). If the format changes or includes additional hyphens, this approach could fail.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/listener/AppListener.java (4)
25-26: Consider potential ThreadLocal memory leaks.
Even though the ThreadLocal is cleared in onEvent(), there's a possibility that a consumer thread might not trigger that event if it experiences an unexpected shutdown. Consider using a more robust approach (e.g., a try-finally block or a Spring lifecycle hook) to ensure the ThreadLocal is always cleared.
57-59: Check for consistent memberId usage.
Using consumer.groupMetadata().memberId() as the key to obtain the processor instance is valid, but note that memberId might change across rebalance events. You might want to handle scenarios where a new memberId is generated for the same thread.
60-61: Potential concurrency concerns in processString.
Ensure the implementation of ToUpperStringProcessor.processString is thread-safe. Multiple threads will invoke this method potentially in parallel.
72-73: Good cleanup logic with TO_UPPER_STRING_PROCESSOR_THREAD_LOCAL.remove().
Removing the ThreadLocal reference upon ConsumerStoppedEvent helps prevent leaks. This is an important step to ensure that any lingering references from old consumer threads do not accumulate.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java (1)
32-33: Validate injection approach.
Your test directly injects a list of ToUpperStringProcessor beans. Confirm these beans are the same instances used by the runtime or created specifically for test scope. If you need production-like concurrency checks, ensure test and production contexts align.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/resources/application.properties (1)
7-7: Concurrency setting appears consistent with test logic.
Your tests expect multiple processor instances. The spring.kafka.listener.concurrency=3 property matches that requirement. Confirm that any environment override (such as in production) does not unintentionally reduce concurrency.
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Actionable comments posted: 4
🧹 Nitpick comments (12)
kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw.cmd (1)
73-78: Consider clarifying fallback behavior forMVNW_REPOURL.
WhenMVNW_REPOURLis set, it overrides the default distribution URL. If the environment variable is accidentally misconfigured or missing, the script may silently revert to the default repo. Consider logging a more explicit message ifMVNW_REPOURLis unavailable.kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java (1)
21-24: Consider thread-safety forList<ToUpperStringProcessor>.
Since this list is used for test-related processing, it is likely fine. If you anticipate any concurrent writes, consider a thread-safe alternative or proper synchronization.kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/processor/ToUpperStringProcessor.java (2)
58-65: Queue size retrieval is straightforward.
If multiple threads write or read from this queue asynchronously, ensure that external code accounts for the possibility of rapidly changing queue size results.
73-75: Efficient creation of a distinct data set.
Returning a newHashSetensures you get a snapshot of unique items, though it can be memory-intensive if the queue is large. Confirm that this approach is aligned with your use case.kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/listener/AppListener.java (1)
25-26: ThreadLocal usage caution.
A single staticThreadLocalfield is used to store aToUpperStringProcessorinstance. In multi-consumer-group scenarios, reusing the same thread pool might lead to unexpected mixing of processor instances. Confirm that each thread is dedicated to a single consumer group.kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java (1)
26-28: Consider parametrizing the message countUsing a large fixed constant (
NUM_MESSAGES = 1000) for testing can result in lengthy test runs. Consider making it a configurable parameter or using a smaller count if performance is an issue.kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/ConcurrentKafkaConsumer.java (2)
6-7: Add configuration for concurrent consumer processingWhile the class is correctly annotated with
@SpringBootApplication, it's missing essential configuration for concurrent Kafka consumers. Consider adding configuration beans to define:
- Consumer concurrency settings
- Thread pool configuration
- Consumer group properties
Would you like me to provide an example configuration class that demonstrates these settings?
1-12: Add class-level documentationConsider adding Javadoc to describe:
- The purpose of concurrent consumer implementation
- Threading model being used
- Configuration requirements
Example:
/** * Main application class for concurrent Kafka consumer implementation. * Implements multiple consumer threads for parallel message processing. * * @see KafkaListenerContainerFactory for concurrent consumer configuration */.github/workflows/kafka-boot-concurrent-kafka-consumer.yml (2)
21-23: Fix YAML indentationThe indentation in the
defaultssection needs adjustment.defaults: run: - working-directory: kafka-spring-boot/boot-concurrent-kafka-consumer + working-directory: kafka-spring-boot/boot-concurrent-kafka-consumer🧰 Tools
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1-35: Enhance CI workflow for concurrent processing validationConsider adding steps to:
- Run integration tests with Kafka container
- Perform concurrent load testing
- Add code quality checks (e.g., SpotBugs for concurrency issues)
- Measure and verify performance metrics
Example addition:
- name: Run Integration Tests run: ./mvnw verify -P integration-test - name: Run Concurrent Load Tests run: ./mvnw verify -P performance-test - name: Check for Concurrency Issues run: ./mvnw spotbugs:check🧰 Tools
🪛 yamllint (1.35.1)
[error] 21-21: trailing spaces
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kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml (2)
22-30: Consider adding spring-boot-starter-actuator for monitoringFor a Kafka consumer application, especially one handling concurrent processing, monitoring capabilities would be beneficial.
Add the following dependency:
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-actuator</artifactId> </dependency>
65-87: Consider configuring additional Spotless rulesWhile the current Spotless configuration is good, consider adding rules for:
- License headers
- Line endings
- Maximum line length
Example configuration:
<configuration> <java> <licenseHeader> <file>${project.basedir}/license-header</file> </licenseHeader> <palantirJavaFormat> <version>2.50.0</version> </palantirJavaFormat> <importOrder/> <removeUnusedImports/> <formatAnnotations/> <endWithNewline/> <trimTrailingWhitespace/> <maxLineLength>120</maxLineLength> </java> </configuration>
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.github/workflows/kafka-boot-concurrent-kafka-consumer.yml(1 hunks)kafka-spring-boot/README.md(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/.gitignore(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/.mvn/wrapper/maven-wrapper.properties(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw.cmd(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/ConcurrentKafkaConsumer.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/listener/AppListener.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/processor/ToUpperStringProcessor.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/resources/application.properties(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/TestConcurrentKafkaConsumer.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ContainerConfig.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java(1 hunks)kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java(1 hunks)
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🪛 yamllint (1.35.1)
.github/workflows/kafka-boot-concurrent-kafka-consumer.yml
[error] 21-21: trailing spaces
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🔇 Additional comments (16)
kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw.cmd (2)
1-20: No major issues spotted in the license header and environment variable documentation.
This portion appears to be the standard Maven Wrapper script header, and it seems correctly licensed and annotated.
117-119: Double-check handling of Maven download credentials.
You are already avoiding logging the provided credentials, which is good practice. Continue to ensure these environment variables aren't logged anywhere else to prevent accidental credential leakage.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ContainerConfig.java (2)
9-10: Ensure limited scope of @TestConfiguration.
@TestConfiguration(proxyBeanMethods = false) is good for preventing extra overhead. Just confirm you only load this config for tests that truly need a real Kafka container, as it can slow down your test suite execution time.
14-15: Be mindful of Docker image versions.
Using apache/kafka-native:3.8.1 is explicit, which is great for consistency. However, make sure the chosen version aligns with the Kafka version used in production (if any) to accurately reflect real-world behavior.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java (3)
26-39: Kudos on using a BeanPostProcessor for dynamic registration.
This is an advanced approach that can simplify test setup by automatically detecting and adding ToUpperStringProcessor beans to the shared list.
41-46: Validate number of partitions in test topic.
Using 5 partitions might be a deliberate choice for concurrency testing. If test performance or clarity becomes an issue, consider reducing the partition count.
48-52: Thread name supplier is a neat debugging tool.
Appending the listener ID to the group ID enhances traceability. Confirm that the group ID plus listener ID combination is always unique enough to avoid confusion in logs.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/processor/ToUpperStringProcessor.java (1)
29-31: Validate the id parameter if production usage is expected.
For strictly test or demonstration purposes, blindly accepting any string is likely fine. If this class evolves to production, consider ensuring id is neither null nor empty to avoid confusion.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java/com/example/kafka/listener/AppListener.java (2)
54-61: Verify stability of memberId() for consistent processor assignment.
Consumer group rebalancing may change the memberId(), potentially altering the reference to a new processor mid-lifecycle. If that is intended, document or handle it to prevent partial processing states.
70-74: Removal of the ThreadLocal is a good practice.
Ensuring TO_UPPER_STRING_PROCESSOR_THREAD_LOCAL.remove() is invoked on consumer stop avoids leaks. Just confirm that all consumer stop scenarios trigger ConsumerStoppedEvent.
kafka-spring-boot/boot-concurrent-kafka-consumer/mvnw (1)
1-259: No issues detected — standard Maven Wrapper script
This script follows the typical Maven Wrapper structure and includes integrity checks and fallback mechanisms. It appears correct and does not present major issues.
kafka-spring-boot/boot-concurrent-kafka-consumer/.gitignore (1)
2-2: Appropriate .gitignore entry
Excluding the /target directory is standard for Maven projects and helps keep build artifacts out of version control.
kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/resources/application.properties (1)
1-7: Validate consumer concurrency and configuration values
The configured concurrency of "3" should correlate with the number of processors and tests. This alignment seems deliberate. Ensure all concurrent logic (including partition handling) is well-tested and handles edge cases such as rebalances or intermittent broker connectivity.
kafka-spring-boot/README.md (1)
9-10: LGTM! Documentation updates are clear and consistent.
The README changes effectively document the new concurrent consumer feature while maintaining consistent formatting. The path correction for multiple producers/consumers and the addition of the concurrent consumer section provide clear navigation for users.
kafka-spring-boot/boot-concurrent-kafka-consumer/.mvn/wrapper/maven-wrapper.properties (1)
17-19: Verify Maven version compatibility with Spring Boot 3.4.1
The Maven configuration looks good, but let's verify the compatibility of Maven 3.9.9 with Spring Boot 3.4.1.
✅ Verification successful
Based on the analysis of the pom.xml files, I can now provide a definitive response about Maven compatibility with Spring Boot 3.4.1.
Maven 3.9.9 is fully compatible with Spring Boot 3.4.1
The Maven version 3.9.9 specified in the maven-wrapper.properties is appropriate for Spring Boot 3.4.1. This is evidenced by:
- All modules in the project are using Spring Boot 3.4.1 as the parent version
- The project successfully uses advanced Maven features and plugins that require recent Maven versions
- Spring Boot 3.x generally requires Maven 3.6.3 or later, and 3.9.9 is well above this requirement
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kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml (1)
32-56: LGTM! Comprehensive test dependencies
The test dependencies are well thought out:
- spring-boot-starter-test for general testing
- spring-boot-testcontainers for container support
- spring-kafka-test for Kafka testing utilities
- junit-jupiter and kafka testcontainers for integration testing
| log.info("Instance {} processing new string {}.", this.id, value); | ||
| try { | ||
| this.queue.put(value.toUpperCase()); | ||
| } catch (InterruptedException exception) { | ||
| log.error("Thread has been interrupted.", exception); | ||
| Thread.currentThread().interrupt(); | ||
| } | ||
| } |
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🛠️ Refactor suggestion
Consider queue growth control.
LinkedBlockingQueue can grow indefinitely if messages arrive faster than they are consumed. For certain use cases, a bounded queue or a time-based flush might be safer to avoid running out of memory.
...boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java
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| public class TestConcurrentKafkaConsumer { | ||
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| public static void main(String[] args) { | ||
| SpringApplication.from(ConcurrentKafkaConsumer::main) | ||
| .with(ContainerConfig.class, ProducerConfig.class) | ||
| .run(args); | ||
| } | ||
| } |
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🛠️ Refactor suggestion
Enhance test coverage for concurrent processing
The current test class only provides application setup. Consider adding:
- Integration tests verifying concurrent message processing
- Load tests with multiple concurrent messages
- Thread behavior verification
- Consumer group rebalancing tests
Example test structure:
@SpringBootTest
class ConcurrentKafkaConsumerIntegrationTest {
@Test
void shouldProcessMessagesInParallel() {
// Test implementation
}
@Test
void shouldHandleConsumerRebalancing() {
// Test implementation
}
}There was a problem hiding this comment.
@coderabbitai, can you please help me to write above Integration tests
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@rajadilipkolli, below is an example of how you might structure integration tests for concurrent Kafka message processing, including load testing, verifying parallel message consumption, thread behavior checks, and simulating consumer group rebalancing scenarios. This example demonstrates various test methods within a single test class. Feel free to adjust the package names, dependency injections, or configurations to match your existing setup.
package com.example.kafka.listener;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.Test;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.test.context.EmbeddedKafka;
import org.springframework.test.annotation.DirtiesContext;
import org.springframework.test.context.ActiveProfiles;
import java.time.Duration;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.TimeUnit;
import static org.assertj.core.api.Assertions.assertThat;
@SpringBootTest
@DirtiesContext(classMode = DirtiesContext.ClassMode.AFTER_EACH_TEST_METHOD)
@ActiveProfiles("test")
@EmbeddedKafka( // You can configure partitions and more properties here if needed
partitions = 5,
topics = {"SPRING_KAFKA_TEST_TOPIC"}
)
class ConcurrentKafkaConsumerIntegrationTest {
@Autowired
private KafkaTemplate<String, String> kafkaTemplate;
// You may have an @Autowired reference here to the List<ToUpperStringProcessor> or other beans
// used in your concurrency logic, if needed for further assertions.
@BeforeEach
void setUp() {
// If needed, reset or initialize any shared data structures
}
/**
* Example test to ensure messages are processed concurrently.
* Sends multiple messages and verifies that they're all processed within a timely manner,
* implying parallel consumption in separate threads.
*/
@Test
void shouldProcessMessagesInParallel() throws InterruptedException, ExecutionException {
int numberOfMessages = 50;
CountDownLatch latch = new CountDownLatch(numberOfMessages);
List<CompletableFuture<Void>> futures = new ArrayList<>();
// Send messages asynchronously
for (int i = 0; i < numberOfMessages; i++) {
final String message = "msg-" + i;
futures.add(
kafkaTemplate.send("SPRING_KAFKA_TEST_TOPIC", "key-" + i, message)
.completable()
.thenAccept(result -> latch.countDown())
);
}
// Make sure all submits are complete
for (CompletableFuture<Void> future : futures) {
future.get();
}
// Wait for them to be processed
boolean allProcessed = latch.await(10, TimeUnit.SECONDS);
assertThat(allProcessed).isTrue().as("All messages should be processed in parallel");
}
/**
* Example load test: sends a higher volume of messages and checks if the system
* can handle them before a timeout, implying the concurrency setup is robust.
*/
@Test
void shouldHandleHighLoadOfMessages() throws InterruptedException {
int totalMessages = 2000;
CountDownLatch latch = new CountDownLatch(totalMessages);
for (int i = 0; i < totalMessages; i++) {
kafkaTemplate.send("SPRING_KAFKA_TEST_TOPIC", "heavyKey-" + i, "load-test-" + i)
.addCallback(
result -> latch.countDown(),
ex -> latch.countDown()
);
}
boolean completed = latch.await(30, TimeUnit.SECONDS);
assertThat(completed).isTrue().as("The system should handle a large load in a concurrent manner");
}
/**
* Example test to verify thread behavior:
* You can check thread names or IDs in your listener logic. If your listener
* logs the thread name or stores it in some structure, retrieve and assert here.
*/
@Test
void shouldUseDistinctThreadsForProcessing() throws InterruptedException {
int messageCount = 10;
CountDownLatch latch = new CountDownLatch(messageCount);
for (int i = 0; i < messageCount; i++) {
kafkaTemplate.send("SPRING_KAFKA_TEST_TOPIC", "threadTestKey-" + i, "thread-test-" + i)
.addCallback(
r -> latch.countDown(),
ex -> latch.countDown()
);
}
// Wait for them to be processed
latch.await(10, TimeUnit.SECONDS);
// If your listener tracked thread names in a shared data structure, you can do something like:
// Set<String> threadsUsed = myThreadTrackingService.getThreadsUsed();
// assertThat(threadsUsed.size()).isGreaterThan(1).as("Should use multiple threads");
}
/**
* Example test to simulate and verify consumer rebalancing behavior:
* You can manually create additional consumers, or if you have a test utility for
* rebalancing, trigger it here. Then check if messages continue to be consumed properly.
*/
@Test
void shouldHandleConsumerGroupRebalancing() throws Exception {
// Send some initial messages
kafkaTemplate.send("SPRING_KAFKA_TEST_TOPIC", "rebalanceKey", "rebalance-test-1").get();
// Simulate a rebalance by creating or shutting down a consumer:
// This might require specialized testing or using concurrency logic that spawns additional consumers.
// For illustration, simply wait or mock the event. After rebalancing, send more messages:
Thread.sleep(2000); // Not recommended in real tests, but used here as a placeholder
kafkaTemplate.send("SPRING_KAFKA_TEST_TOPIC", "rebalanceKey2", "rebalance-test-2").get();
// Validate that messages remain processed:
// Check logs, counters, or shared data structures to confirm rebalancing didn't disrupt consumption.
// assertThat(sharedProcessedMessages).contains("rebalance-test-1", "rebalance-test-2");
}
/**
* If your listeners store consumed messages, you can verify them here.
* Using dummy checks for demonstration.
*/
@Test
void verifyConsumedMessages() {
// For example, if your listener logic stores processed records:
// List<ConsumerRecord<String, String>> consumedRecords = consumedRecordsRepository.findAll();
// assertThat(consumedRecords).isNotEmpty();
// ...
}
}Key Points in This Example:
- Parallel Message Processing: Use multiple messages in quick succession and confirm they’re all processed in a timely manner to ensure concurrency.
- Load Testing: Increase the message volume to ensure the application remains responsive and stable.
- Thread Behavior: Monitor thread usage by inspecting logs, or store thread names in a collection for testing assertions.
- Consumer Group Rebalancing: Optionally spawn or shut down consumer instances (if feasible in your test environment) to confirm that rebalancing events don’t break message consumption.
You can refine these tests based on your project’s specific requirements, data storage approach, or concurrency checks. Adjust the timeouts, concurrency levels, test container setups, or integration with Testcontainers for a more robust environment.
|
@coderabbitai read the files in the kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java package and generate a class diagram using mermaid and a README in the markdown format. |
|
Tip For best results, initiate chat on the files or code changes. Below is a proposed Mermaid class diagram for the Java classes in the classDiagram
class ConcurrentKafkaConsumer {
+ main(String[] args)
}
class AppListener {
- ThreadLocal<ToUpperStringProcessor> processor
- ObjectProvider<ToUpperStringProcessor> provider
+ onMessage(ConsumerRecord<String, String> record, Consumer<String, String> consumer) : void
+ onEvent(ConsumerStoppedEvent event) : void
+ executeOnDedicatedProcessor(ConsumerRecord<String, String> record, Consumer<String, String> consumer) : void
}
class ToUpperStringProcessor {
- String id
- BlockingQueue<String> queue
+ processString(String value) : void
+ queueSize() : int
+ distinctQueuedData() : Set<String>
+ init() : void
}
ConcurrentKafkaConsumer <|-- AppListener : Loaded by Spring Boot context
AppListener --> ToUpperStringProcessor : ThreadLocal usage
# Concurrent Kafka Consumer - Overview
This directory contains a Spring Boot application that demonstrates how to consume Kafka messages concurrently using separate threads.
## Project Structure
### 1. `ConcurrentKafkaConsumer`
- **Location**: `com.example.kafka`
- **Description**:
- Serves as the Spring Boot application entry point.
- Annotated with `@SpringBootApplication`.
- The `main` method runs the Spring application.
### 2. `AppListener`
- **Location**: `com.example.kafka.listener`
- **Description**:
- A Spring-managed component that listens to a Kafka topic (specified by `SPRING_KAFKA_TEST_TOPIC`).
- Uses a `ThreadLocal<ToUpperStringProcessor>` to provide an isolated processor per consumer thread.
- Listens for messages via `@KafkaListener` and processes them using the `ToUpperStringProcessor`.
### 3. `ToUpperStringProcessor`
- **Location**: `com.example.kafka.processor`
- **Description**:
- A Spring-managed bean with prototype scope.
- Converts incoming strings to uppercase and enqueues them in a thread-safe queue.
- Provides methods to retrieve distinct processed data and queue size information.
- Each processor instance has a unique `id` and logs its initialization.
## How It Works
1. **Spring Boot Startup**
The application starts when `ConcurrentKafkaConsumer` is run. Spring Boot auto-configures the Kafka consumer properties from `application.properties`.
2. **Message Consumption**
`AppListener` is automatically registered as a Kafka consumer, leveraging the properties defined (e.g., concurrency level). Each consumer thread uses a dedicated `ToUpperStringProcessor` instance stored in a `ThreadLocal`.
3. **Processing**
Incoming messages are routed to `AppListener`’s `onMessage` method, which retrieves or initializes the responsible `ToUpperStringProcessor`. The processor transforms the message to uppercase and stores it in an internal queue.
4. **Resource Cleanup**
When a consumer is stopped, `AppListener` handles the `ConsumerStoppedEvent` by removing the processor instance associated with that thread.
## Concurrency and Thread Safety
- Each thread uses its own `ToUpperStringProcessor`, ensuring no shared state among parallel consumers.
- The queue inside each `ToUpperStringProcessor` is a `BlockingQueue`, providing thread-safe operations on stored messages.
## Getting Started
1. **Run the Application** ./mvnw spring-boot:run |
|
@coderabbitai read the files in the kafka-spring-boot/boot-concurrent-kafka-consumer/src/main/java package and generate a sequence diagram using mermaid and a README in the markdown format. |
|
Tip For best results, initiate chat on the files or code changes. Below is a proposed Mermaid sequence diagram for the Java classes in the sequenceDiagram
participant C as ConcurrentKafkaConsumer
participant A as AppListener
participant P as ToUpperStringProcessor
C->>C: Spring Boot initializes application
C->>A: Kafka messages arrive, triggering onMessage()
A->>A: Retrieve or initialize ThreadLocal<ToUpperStringProcessor>
A->>P: processString(value)
P->>P: Converts to uppercase & enqueues result
Note over A,P: Additional messages handled similarly
A->>A: onEvent(ConsumerStoppedEvent) -> Remove ThreadLocal processor
# Concurrent Kafka Consumer - Overview
This directory contains a Spring Boot application that demonstrates how to consume Kafka messages concurrently using separate threads.
## Project Structure
### 1. `ConcurrentKafkaConsumer`
- **Location**: `com.example.kafka`
- **Description**:
- Serves as the Spring Boot application entry point.
- Annotated with `@SpringBootApplication`.
- The `main` method runs the Spring application using `SpringApplication.run`.
### 2. `AppListener`
- **Location**: `com.example.kafka.listener`
- **Description**:
- A `@Component` that subscribes to a Kafka topic (referenced by `SPRING_KAFKA_TEST_TOPIC`).
- Uses a `ThreadLocal<ToUpperStringProcessor>` to manage message processing on a per-thread basis.
- Processes messages in the `onMessage` method and handles resource cleanup in `onEvent` when the consumer stops.
### 3. `ToUpperStringProcessor`
- **Location**: `com.example.kafka.processor`
- **Description**:
- A `@Component` with prototype scope, ensuring each instance is unique (e.g., one per thread).
- Transforms incoming strings to uppercase and stores them in a `BlockingQueue`.
- Offers methods like `distinctQueuedData()` to retrieve unique processed values.
## Message Processing Sequence
1. **Startup and Configuration**
- The `ConcurrentKafkaConsumer` class launches the Spring Boot application.
- Kafka consumer properties are configured in `application.properties`, including concurrency level and bootstrap servers.
2. **Receiving Messages**
- The `AppListener` class is annotated with `@KafkaListener`, making it an endpoint for Kafka messages.
- When a message arrives, `onMessage` is triggered, and a `ToUpperStringProcessor` is retrieved or created for the current thread.
3. **Processing**
- The processor converts the message to uppercase and stores it in a thread-safe queue.
- Each thread maintains its own `ToUpperStringProcessor`, eliminating conflicts between parallel consumers.
4. **Resource Cleanup**
- When a consumer stops, `AppListener`’s `onEvent` method removes the processor from its `ThreadLocal`, preventing resource leaks.
## Running the Application
1. **Build and Start** ./mvnw clean package |
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Actionable comments posted: 1
🧹 Nitpick comments (6)
kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml (2)
22-30: Add dependencies for concurrent processing monitoringFor better monitoring and management of concurrent consumers, consider adding:
spring-boot-starter-aopfor aspect-based monitoringmicrometer-registry-prometheusfor metrics collection<dependencies> + <dependency> + <groupId>org.springframework.boot</groupId> + <artifactId>spring-boot-starter-aop</artifactId> + </dependency> + <dependency> + <groupId>io.micrometer</groupId> + <artifactId>micrometer-registry-prometheus</artifactId> + </dependency> <!-- existing dependencies -->
32-56: Enhance test configuration for concurrent scenariosThe test dependencies look good, but for thorough concurrent testing, consider:
- Add
awaitilityfor async test assertions:+ <dependency> + <groupId>org.awaitility</groupId> + <artifactId>awaitility</artifactId> + <version>4.2.0</version> + <scope>test</scope> + </dependency>
- Add
reactor-testfor testing reactive streams (if using reactive approach):+ <dependency> + <groupId>io.projectreactor</groupId> + <artifactId>reactor-test</artifactId> + <scope>test</scope> + </dependency>kafka-spring-boot/boot-concurrent-kafka-consumer/ReadMe.md (4)
7-22: Enhance sequence diagram with concurrent processing details.The sequence diagram effectively shows the basic flow, but could be enhanced to better illustrate the concurrent nature of the system. Consider adding:
- Multiple concurrent message processing flows
- Error handling paths
- Thread lifecycle events (creation/destruction)
- Message acknowledgment flow
Here's a suggested enhancement to the diagram:
sequenceDiagram participant C as ConcurrentKafkaConsumer participant A as AppListener participant P as ToUpperStringProcessor C->>C: Spring Boot initializes application + Note over C: Configure concurrent consumers C->>A: Kafka messages arrive, triggering onMessage() + par Thread 1 A->>A: Retrieve or initialize ThreadLocal<ToUpperStringProcessor> A->>P: processString(value) P->>P: Converts to uppercase & enqueues result + and Thread 2 + A->>A: Retrieve or initialize ThreadLocal<ToUpperStringProcessor> + A->>P: processString(value) + P->>P: Converts to uppercase & enqueues result + end Note over A,P: Additional messages handled similarly + alt Error occurs + A->>A: Handle error & retry/dead letter + end A->>A: onEvent(ConsumerStoppedEvent) -> Remove ThreadLocal processor
26-46: Add implementation details and best practices.The component descriptions are clear, but consider adding these important implementation details:
- Thread safety considerations for the
BlockingQueueinToUpperStringProcessor- Memory implications of using
ThreadLocal- Cleanup strategy for the
BlockingQueue- Configuration options for the concurrent consumer (e.g., thread pool size)
Also, consider adding a note about potential memory leaks with
ThreadLocalif not properly cleaned up, especially in application server environments with thread pooling.
64-77: Enhance running instructions with configuration and troubleshooting.Add sections for:
Configuration options (application.properties):
- Consumer group settings
- Thread pool configuration
- Retry policies
Troubleshooting guide:
- Common issues and solutions
- Log analysis tips
- Performance tuning
🧰 Tools
🪛 Markdownlint (0.37.0)
68-68: null
Fenced code blocks should have a language specified(MD040, fenced-code-language)
78-113: Fix markdown formatting issues.Please address these formatting issues:
- Use consistent heading levels (h1 -> h2 -> h3)
- Use dashes instead of asterisks for unordered lists
- Remove dollar signs from shell commands
- Add language specifiers to code blocks
- Use proper link formatting for the actuator endpoint
Apply these changes:
-### Format code +## Format code -```shell +```bash -$ docker-compose -f docker/docker-compose.yml up -d -$ ./mvnw spring-boot:run -Dspring-boot.run.profiles=local +docker-compose -f docker/docker-compose.yml up -d +./mvnw spring-boot:run -Dspring-boot.run.profiles=local-* Actuator Endpoint: http://localhost:8080/actuator
+## Useful Links
+- Actuator Endpoint<details> <summary>🧰 Tools</summary> <details> <summary>🪛 Markdownlint (0.37.0)</summary> 113-113: Expected: dash; Actual: asterisk Unordered list style (MD004, ul-style) --- 99-99: null Dollar signs used before commands without showing output (MD014, commands-show-output) --- 100-100: null Dollar signs used before commands without showing output (MD014, commands-show-output) --- 113-113: null Bare URL used (MD034, no-bare-urls) </details> </details> </blockquote></details> </blockquote></details> <details> <summary>📜 Review details</summary> **Configuration used: CodeRabbit UI** **Review profile: CHILL** **Plan: Pro** <details> <summary>📥 Commits</summary> Reviewing files that changed from the base of the PR and between 86ef429e72b38111a8982b64a388399247d971e3 and 3c785e5027ac069a33b50217f50d4eece991ddec. </details> <details> <summary>📒 Files selected for processing (5)</summary> * `kafka-spring-boot/boot-concurrent-kafka-consumer/ReadMe.md` (1 hunks) * `kafka-spring-boot/boot-concurrent-kafka-consumer/docker/docker-compose.yml` (1 hunks) * `kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml` (1 hunks) * `kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java` (1 hunks) * `kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java` (1 hunks) </details> <details> <summary>🚧 Files skipped from review as they are similar to previous changes (2)</summary> * kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/common/ProducerConfig.java * kafka-spring-boot/boot-concurrent-kafka-consumer/src/test/java/com/example/kafka/listener/AppListenerTest.java </details> <details> <summary>🧰 Additional context used</summary> <details> <summary>🪛 LanguageTool</summary> <details> <summary>kafka-spring-boot/boot-concurrent-kafka-consumer/ReadMe.md</summary> [misspelling] ~3-~3: This word is normally spelled as one. Context: ...a Consumer This project demonstrates a multi-threaded Kafka consumer approach using Spring Bo... (EN_COMPOUNDS_MULTI_THREADED) </details> </details> <details> <summary>🪛 Markdownlint (0.37.0)</summary> <details> <summary>kafka-spring-boot/boot-concurrent-kafka-consumer/ReadMe.md</summary> 5-5: Expected: h2; Actual: h3 Heading levels should only increment by one level at a time (MD001, heading-increment) --- 113-113: Expected: dash; Actual: asterisk Unordered list style (MD004, ul-style) --- 99-99: null Dollar signs used before commands without showing output (MD014, commands-show-output) --- 100-100: null Dollar signs used before commands without showing output (MD014, commands-show-output) --- 113-113: null Bare URL used (MD034, no-bare-urls) --- 68-68: null Fenced code blocks should have a language specified (MD040, fenced-code-language) </details> </details> </details> <details> <summary>🔇 Additional comments (3)</summary> <details> <summary>kafka-spring-boot/boot-concurrent-kafka-consumer/docker/docker-compose.yml (2)</summary> `14-31`: **Verify Kafka broker configuration for production readiness** The Kafka broker configuration needs attention in the following areas: 1. The `CLUSTER_ID` is hardcoded, which could cause issues when running multiple instances 2. Single broker setup with replication factor of 1 isn't suitable for production 3. Very high `LOG_FLUSH_INTERVAL_MESSAGES` might impact durability Consider: - Generating `CLUSTER_ID` dynamically - Adding more brokers for production - Adjusting `LOG_FLUSH_INTERVAL_MESSAGES` based on your durability requirements --- `33-42`: **Consider securing Kafdrop for production use** While Kafdrop is great for development, its default configuration might expose sensitive information. Consider: - Adding authentication for Kafdrop UI - Restricting access using network policies - Using environment-specific configurations </details> <details> <summary>kafka-spring-boot/boot-concurrent-kafka-consumer/pom.xml (1)</summary> `5-10`: **Spring Boot version 3.4.1 appears to be incorrect** As noted in the previous review, Spring Boot 3.4.1 is not a valid version. Please downgrade to the latest stable Spring Boot 3.2.x version. </details> </details> </details> <!-- This is an auto-generated comment by CodeRabbit for review status -->
| ## Message Processing Sequence | ||
|
|
||
| 1. **Startup and Configuration** | ||
| - The `ConcurrentKafkaConsumer` class launches the Spring Boot application. | ||
| - Kafka consumer properties are configured in `application.properties`, including concurrency level and bootstrap servers. | ||
|
|
||
| 2. **Receiving Messages** | ||
| - The `AppListener` class is annotated with `@KafkaListener`, making it an endpoint for Kafka messages. | ||
| - When a message arrives, `onMessage` is triggered, and a `ToUpperStringProcessor` is retrieved or created for the current thread. | ||
|
|
||
| 3. **Processing** | ||
| - The processor converts the message to uppercase and stores it in a thread-safe queue. | ||
| - Each thread maintains its own `ToUpperStringProcessor`, eliminating conflicts between parallel consumers. | ||
|
|
||
| 4. **Resource Cleanup** | ||
| - When a consumer stops, `AppListener`’s `onEvent` method removes the processor from its `ThreadLocal`, preventing resource leaks. | ||
|
|
There was a problem hiding this comment.
🛠️ Refactor suggestion
Add operational aspects to message processing sequence.
Consider adding these important operational aspects:
-
Error Handling
- Retry policies
- Dead letter queue strategy
- Error logging and monitoring
-
Monitoring & Metrics
- Consumer lag monitoring
- Processing time metrics
- Thread pool statistics
-
Health Checks
- Kafka connection status
- Consumer group health
- Thread pool health
Summary by CodeRabbit
New Features
Bug Fixes
Documentation
Tests