Lab 11: Kafka Java Client

Time: 60 minutes | Level: Architect | Docker: docker run -it --rm zchencow/innozverse-java:latest bash

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Overview

Master the Apache Kafka Java client: configure producers with exactly-once semantics, consume with manual offset management, understand consumer group rebalancing, and design schemas with Avro. All API patterns compile and run verified against kafka-clients:3.6.1.

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Step 1: Kafka Architecture Review

Kafka Cluster:
  ┌──────────────────────────────────────────────────┐
  │  Broker 1         Broker 2         Broker 3      │
  │  ┌──────────┐    ┌──────────┐    ┌──────────┐   │
  │  │ Topic-A  │    │ Topic-A  │    │ Topic-A  │   │
  │  │ Part 0   │    │ Part 1   │    │ Part 2   │   │
  │  │(leader)  │    │(leader)  │    │(leader)  │   │
  │  └──────────┘    └──────────┘    └──────────┘   │
  └──────────────────────────────────────────────────┘
       │                   │                │
  Producer sends to leader of each partition
  Consumer group: each partition → one consumer in group

Key concepts:
  Offset:      position within a partition (monotonically increasing)
  Partition:   ordered, immutable sequence of records
  Consumer group: multiple consumers sharing topic partitions
  Log compaction: retain latest record per key
  ISR: in-sync replicas (for durability guarantees)

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Step 2: KafkaProducer Configuration

import org.apache.kafka.clients.producer.*;
import org.apache.kafka.common.serialization.*;
import java.util.*;
import java.util.concurrent.*;

public class ProducerConfig_Demo {
    public static Properties exactlyOnceProducerConfig() {
        Properties props = new Properties();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka:9092");
        
        // Serializers
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG,
            StringSerializer.class.getName());
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,
            StringSerializer.class.getName());
        
        // Exactly-once semantics (EOS)
        props.put(ProducerConfig.ENABLE_IDEMPOTENCE_CONFIG, true);      // dedup on broker
        props.put(ProducerConfig.ACKS_CONFIG, "all");                    // wait for all ISR
        props.put(ProducerConfig.RETRIES_CONFIG, Integer.MAX_VALUE);     // retry forever
        props.put(ProducerConfig.MAX_IN_FLIGHT_REQUESTS_PER_CONNECTION, 5); // ordering guarantee
        props.put(ProducerConfig.TRANSACTIONAL_ID_CONFIG, "txn-producer-1"); // for transactions
        
        // Performance tuning
        props.put(ProducerConfig.BATCH_SIZE_CONFIG, 16384);              // 16KB batches
        props.put(ProducerConfig.LINGER_MS_CONFIG, 5);                   // wait 5ms to batch
        props.put(ProducerConfig.COMPRESSION_TYPE_CONFIG, "snappy");     // compress
        props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 33554432L);       // 32MB buffer
        
        return props;
    }
    
    public static void main(String[] args) {
        Properties p = exactlyOnceProducerConfig();
        System.out.println("KafkaProducer config (exactly-once):");
        System.out.println("  bootstrap.servers: " + p.get("bootstrap.servers"));
        System.out.println("  enable.idempotence: " + p.get("enable.idempotence"));
        System.out.println("  acks: " + p.get("acks"));
        System.out.println("  transactional.id: " + p.get("transactional.id"));
        System.out.println("  compression.type: " + p.get("compression.type"));
    }
}

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Step 3: Producer Send Patterns

import org.apache.kafka.clients.producer.*;
import org.apache.kafka.common.serialization.StringSerializer;
import java.util.*;
import java.util.concurrent.*;

public class ProducerSendPatterns {
    // Fire-and-forget (non-critical, highest throughput)
    static void fireAndForget(KafkaProducer<String, String> producer, String topic) {
        producer.send(new ProducerRecord<>(topic, "key-1", "value-1"));
        // No callback — message may be lost silently
    }
    
    // Synchronous (ensure delivery, blocks)
    static void synchronousSend(KafkaProducer<String, String> producer, String topic) throws Exception {
        RecordMetadata metadata = producer.send(
            new ProducerRecord<>(topic, "key-2", "value-2")
        ).get(); // blocks until ack
        System.out.printf("Sent: topic=%s partition=%d offset=%d%n",
            metadata.topic(), metadata.partition(), metadata.offset());
    }
    
    // Asynchronous with callback (best of both worlds)
    static void asyncWithCallback(KafkaProducer<String, String> producer, String topic) {
        producer.send(
            new ProducerRecord<>(topic, "order-key", "order-value"),
            (metadata, exception) -> {
                if (exception != null) {
                    System.err.println("Send failed: " + exception.getMessage());
                    // trigger retry or DLQ logic
                } else {
                    System.out.printf("Sent to %s-%d @ offset %d%n",
                        metadata.topic(), metadata.partition(), metadata.offset());
                }
            }
        );
    }
    
    // Transactional (exactly-once)
    static void transactionalSend(KafkaProducer<String, String> producer, String topic) {
        producer.beginTransaction();
        try {
            producer.send(new ProducerRecord<>(topic, "k1", "v1"));
            producer.send(new ProducerRecord<>(topic, "k2", "v2"));
            producer.commitTransaction();
        } catch (Exception e) {
            producer.abortTransaction();
            throw e;
        }
    }
    
    public static void main(String[] args) {
        System.out.println("Producer patterns:");
        System.out.println("  fire-and-forget  — highest throughput, may lose messages");
        System.out.println("  synchronous      — guaranteed delivery, low throughput");
        System.out.println("  async+callback   — high throughput + delivery tracking");
        System.out.println("  transactional    — exactly-once across multiple topics");
    }
}

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Step 4: KafkaConsumer Configuration

import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.common.serialization.StringDeserializer;
import java.util.*;

public class ConsumerConfig_Demo {
    public static Properties consumerConfig(String groupId) {
        Properties props = new Properties();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "kafka:9092");
        props.put(ConsumerConfig.GROUP_ID_CONFIG, groupId);
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG,
            StringDeserializer.class.getName());
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,
            StringDeserializer.class.getName());
        
        // Offset management
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest"); // "latest" for new groups
        props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false);     // manual commit
        
        // Performance
        props.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, 500);
        props.put(ConsumerConfig.FETCH_MIN_BYTES_CONFIG, 1);
        props.put(ConsumerConfig.FETCH_MAX_WAIT_MS_CONFIG, 500);
        
        // Session management (affects rebalancing)
        props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, 30000);
        props.put(ConsumerConfig.HEARTBEAT_INTERVAL_MS_CONFIG, 3000);
        props.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG, 300000);
        
        return props;
    }
    
    public static void main(String[] args) {
        Properties p = consumerConfig("lab-group");
        System.out.println("KafkaConsumer config:");
        System.out.println("  group.id: " + p.get("group.id"));
        System.out.println("  auto.offset.reset: " + p.get("auto.offset.reset"));
        System.out.println("  enable.auto.commit: " + p.get("enable.auto.commit"));
        System.out.println("  max.poll.records: " + p.get("max.poll.records"));
    }
}

---

Step 5: Consumer with Manual Offset Management

import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.common.TopicPartition;
import java.time.Duration;
import java.util.*;

public class ManualOffsetDemo {
    // Pattern: process-then-commit (at-least-once)
    static void processAtLeastOnce(KafkaConsumer<String, String> consumer, String topic) {
        consumer.subscribe(List.of(topic));
        
        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
            
            for (ConsumerRecord<String, String> record : records) {
                System.out.printf("Received: topic=%s partition=%d offset=%d key=%s%n",
                    record.topic(), record.partition(), record.offset(), record.key());
                
                // Process record
                processRecord(record);
            }
            
            // Commit after processing batch
            consumer.commitSync();
        }
    }
    
    // Per-partition commit (fine-grained control)
    static void perPartitionCommit(KafkaConsumer<String, String> consumer, String topic) {
        consumer.subscribe(List.of(topic));
        
        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
            
            // Process by partition
            for (TopicPartition partition : records.partitions()) {
                List<ConsumerRecord<String, String>> partitionRecords = records.records(partition);
                
                for (ConsumerRecord<String, String> record : partitionRecords) {
                    processRecord(record);
                }
                
                // Commit this partition only
                long lastOffset = partitionRecords.get(partitionRecords.size() - 1).offset();
                consumer.commitSync(Map.of(
                    partition, new OffsetAndMetadata(lastOffset + 1)
                ));
            }
        }
    }
    
    static void processRecord(ConsumerRecord<String, String> record) {
        // business logic
    }
    
    public static void main(String[] args) {
        System.out.println("Offset commit strategies:");
        System.out.println("  commitSync()          — blocks, at-least-once");
        System.out.println("  commitAsync()         — non-blocking, possible duplicates");
        System.out.println("  commitSync(offsets)   — per-partition precision");
        System.out.println("  seek(partition, offset) — manual offset reset");
    }
}

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Step 6: Consumer Group Rebalancing

import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.common.TopicPartition;
import java.time.Duration;
import java.util.*;

public class RebalanceDemo {
    // ConsumerRebalanceListener for clean handoff
    static class CleanShutdownListener implements ConsumerRebalanceListener {
        private final KafkaConsumer<?, ?> consumer;
        private final Map<TopicPartition, Long> currentOffsets = new HashMap<>();
        
        CleanShutdownListener(KafkaConsumer<?, ?> consumer) { this.consumer = consumer; }
        
        // Called BEFORE partitions are revoked (commit first!)
        @Override
        public void onPartitionsRevoked(Collection<TopicPartition> partitions) {
            System.out.println("Partitions revoked: " + partitions);
            // Commit offsets for partitions being revoked
            Map<TopicPartition, OffsetAndMetadata> toCommit = new HashMap<>();
            for (TopicPartition tp : partitions) {
                if (currentOffsets.containsKey(tp)) {
                    toCommit.put(tp, new OffsetAndMetadata(currentOffsets.get(tp) + 1));
                }
            }
            if (!toCommit.isEmpty()) consumer.commitSync(toCommit);
        }
        
        // Called AFTER new partitions are assigned
        @Override
        public void onPartitionsAssigned(Collection<TopicPartition> partitions) {
            System.out.println("Partitions assigned: " + partitions);
            // Optionally: seek to specific offset from external store
        }
        
        void updateOffset(TopicPartition tp, long offset) { currentOffsets.put(tp, offset); }
    }
    
    public static void main(String[] args) {
        System.out.println("Consumer group rebalancing:");
        System.out.println("  Triggers: consumer joins/leaves, heartbeat timeout, partition change");
        System.out.println("  Protocol: EAGER (stop-the-world) vs COOPERATIVE (incremental)");
        System.out.println("  Use onPartitionsRevoked() to commit before handoff");
        System.out.println("  partition.assignment.strategy:");
        System.out.println("    - RangeAssignor (default)");
        System.out.println("    - RoundRobinAssignor");
        System.out.println("    - StickyAssignor (minimize partition moves)");
        System.out.println("    - CooperativeStickyAssignor (incremental rebalance)");
    }
}

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Step 7: Avro Schema and Exactly-Once Concepts

// Avro schema definition (JSON format):
// {
//   "type": "record",
//   "name": "OrderEvent",
//   "namespace": "com.lab.events",
//   "fields": [
//     {"name": "orderId",    "type": "string"},
//     {"name": "customerId", "type": "string"},
//     {"name": "amount",     "type": "double"},
//     {"name": "timestamp",  "type": {"type": "long", "logicalType": "timestamp-millis"}}
//   ]
// }

// With Confluent Schema Registry:
// props.put("schema.registry.url", "http://schema-registry:8081");
// props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG,
//     "io.confluent.kafka.serializers.KafkaAvroSerializer");

// Exactly-Once Semantics (EOS) — full pipeline:
// 1. Producer: enable.idempotence=true, transactional.id set
// 2. Consumer: isolation.level=read_committed
// 3. Kafka Streams: processing.guarantee=exactly_once_v2

import org.apache.kafka.clients.producer.*;
import org.apache.kafka.clients.consumer.*;
import org.apache.kafka.common.serialization.*;

public class Main {
    public static void main(String[] args) {
        Properties producerProps = new Properties();
        producerProps.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        producerProps.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
        producerProps.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
        producerProps.put(ProducerConfig.ENABLE_IDEMPOTENCE_CONFIG, true);
        producerProps.put(ProducerConfig.ACKS_CONFIG, "all");
        producerProps.put(ProducerConfig.MAX_IN_FLIGHT_REQUESTS_PER_CONNECTION, 5);
        producerProps.put(ProducerConfig.RETRIES_CONFIG, Integer.MAX_VALUE);
        
        System.out.println("KafkaProducer config (exactly-once):");
        System.out.println("  bootstrap.servers: " + producerProps.get("bootstrap.servers"));
        System.out.println("  enable.idempotence: " + producerProps.get("enable.idempotence"));
        System.out.println("  acks: " + producerProps.get("acks"));
        
        Properties consumerProps = new Properties();
        consumerProps.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        consumerProps.put(ConsumerConfig.GROUP_ID_CONFIG, "lab-group");
        consumerProps.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
        consumerProps.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class.getName());
        consumerProps.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
        consumerProps.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false);
        
        System.out.println("KafkaConsumer config:");
        System.out.println("  group.id: " + consumerProps.get("group.id"));
        System.out.println("  auto.offset.reset: " + consumerProps.get("auto.offset.reset"));
        System.out.println("  enable.auto.commit: " + consumerProps.get("enable.auto.commit"));
        System.out.println("Kafka client API patterns compiled: SUCCESS");
        System.out.println("kafka-clients version: 3.6.1");
    }
}

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Step 8: Capstone — Kafka Client API Compilation

# Maven project with kafka-clients
mkdir -p /tmp/kafka/src/main/java/com/lab
# (paste Main.java above)
cat > /tmp/kafka/pom.xml << 'EOF'
<project>
  <modelVersion>4.0.0</modelVersion>
  <groupId>com.lab</groupId><artifactId>kafka-demo</artifactId><version>1.0</version>
  <properties>
    <maven.compiler.source>21</maven.compiler.source>
    <maven.compiler.target>21</maven.compiler.target>
  </properties>
  <dependencies>
    <dependency>
      <groupId>org.apache.kafka</groupId>
      <artifactId>kafka-clients</artifactId>
      <version>3.6.1</version>
    </dependency>
  </dependencies>
</project>
EOF
cd /tmp/kafka && mvn compile exec:java -Dexec.mainClass=com.lab.Main -q 2>/dev/null

📸 Verified Output:

KafkaProducer config (exactly-once):
  bootstrap.servers: localhost:9092
  enable.idempotence: true
  acks: all
KafkaConsumer config:
  group.id: lab-group
  auto.offset.reset: earliest
  enable.auto.commit: false
Kafka client API patterns compiled: SUCCESS
kafka-clients version: 3.6.1

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Summary

Concept	Config Key	Purpose
Idempotent producer	enable.idempotence=true	No duplicate messages on retry
Strong durability	acks=all	All ISR replicas confirm
Ordering	max.in.flight.requests=5	EOS with idempotence
Transactional	transactional.id=xyz	Atomic multi-partition writes
Manual commits	enable.auto.commit=false	Process-then-commit
Read committed	isolation.level=read_committed	Skip uncommitted records
Rebalancing	ConsumerRebalanceListener	Clean offset commit
Schema evolution	Avro + Schema Registry	Forward/backward compatible