Kafka的《文件》给出了一种方法，描述如下：
每个用户一个thread:a simple 选项是为每个线程提供自己的consumer>示例。
我的代码：

public class KafkaConsumerRunner implements Runnable {

    private final AtomicBoolean closed = new AtomicBoolean(false);
    private final CloudKafkaConsumer consumer;
    private final String topicName;

    public KafkaConsumerRunner(CloudKafkaConsumer consumer, String topicName) {
        this.consumer = consumer;
        this.topicName = topicName;
    }

    @Override
    public void run() {
        try {
            this.consumer.subscribe(topicName);
            ConsumerRecords<String, String> records;
            while (!closed.get()) {
                synchronized (consumer) {
                    records = consumer.poll(100);
                }
                for (ConsumerRecord<String, String> tmp : records) {
                    System.out.println(tmp.value());
                }
            }
        } catch (WakeupException e) {
            // Ignore exception if closing
            System.out.println(e);
            //if (!closed.get()) throw e;
        }
    }

    // Shutdown hook which can be called from a separate thread
    public void shutdown() {
        closed.set(true);
        consumer.wakeup();
    }

    public static void main(String[] args) {
        CloudKafkaConsumer kafkaConsumer = KafkaConsumerBuilder.builder()
                .withBootstrapServers("172.31.1.159:9092")
                .withGroupId("test")
                .build();
        ExecutorService executorService = Executors.newFixedThreadPool(5);
        executorService.execute(new KafkaConsumerRunner(kafkaConsumer, "log"));
        executorService.execute(new KafkaConsumerRunner(kafkaConsumer, "log.info"));
        executorService.shutdown();
    }
}

但它不起作用并引发异常：
java.util.concurrentmodificationexception:kafkaconsumer对于多线程访问不安全
此外，我阅读了flink（一个用于分布式流和批处理数据的开源平台）的源代码。flink使用多线程消费程序与我的类似。

long pollTimeout = Long.parseLong(flinkKafkaConsumer.properties.getProperty(KEY_POLL_TIMEOUT, Long.toString(DEFAULT_POLL_TIMEOUT)));
pollLoop: while (running) {
    ConsumerRecords<byte[], byte[]> records;
    //noinspection SynchronizeOnNonFinalField
    synchronized (flinkKafkaConsumer.consumer) {
        try {
            records = flinkKafkaConsumer.consumer.poll(pollTimeout);
        } catch (WakeupException we) {
            if (running) {
                throw we;
            }
            // leave loop
            continue;
        }
    }

多线程的flink码
怎么了？