Kafka的主题由一个或多个分区组成，这些分区可以被分配到不同的Broker上。每个分区都有一个领导者和一个或多个副本。领导者负责处理该分区的所有读写请求。如果领导者宕机，则会从副本中选出新的领导者。因此，分区的领导者分布对Kafka集群的性能和可靠性都非常重要。

以下示例演示了如何检查分区领导者在各个Broker上的分布情况：

import java.util.Map;
import org.apache.kafka.clients.admin.AdminClient;
import org.apache.kafka.clients.admin.ListTopicsResult;
import org.apache.kafka.clients.admin.TopicDescription;
import org.apache.kafka.clients.admin.TopicDescription.PartitionReplica;
import org.apache.kafka.common.Node;
import org.apache.kafka.common.TopicPartition;

public class PartitionLeaderDistribution {
  public static void main(String[] args) throws Exception {
    // Set up an AdminClient instance
    // Replace BOOTSTRAP_SERVERS with your Kafka broker addresses
    Properties props = new Properties();
    props.put(AdminClientConfig.BOOTSTRAP_SERVERS_CONFIG,
              "BOOTSTRAP_SERVERS");
    AdminClient admin = AdminClient.create(props);

    // Get a list of all topics in the cluster
    ListTopicsResult topics = admin.listTopics();
    Set topicNames = topics.names().get();

    // Iterate through each topic and print its partition leader distribution
    for (String topicName : topicNames) {
      TopicDescription description = admin.describeTopics(Arrays.asList(topicName)).values().get(topicName).get();
      List replicas = description.partitions().stream()
          .flatMap(p -> p.replicas().stream())
          .collect(Collectors.toList());

      Map> leaderMap = replicas.stream()
          .filter(PartitionReplica::isLeader)
          .collect(Collectors.groupingBy(PartitionReplica::broker));

      System.out.println("Topic: " + topicName);
      for (Node node : leaderMap.keySet()) {
        List topicPartitions = leaderMap.get(node);
        System.out.println("Broker " + node.id() + ": " + topicPartitions.size() + " partitions");
      }
      System.out.println();
    }

    // Close the AdminClient instance
    admin.close();
  }
}

这段代码会输出每个Broker上的分区领导者数目，以及他们领导的主题。如果你发现