云简-mian

这个是个电话面，问的也比较基础，可能感觉我工作年限比较长，没有问一些基础的东西。

 

1. 工作的内容，目前手里熟悉的项目，详细说明一下。我说了一下分账相关

2. 详细问了一下分账的流程，问了一些简单的问题，碰到问题如何解决的

3. 如何控制请求并发的问题

4. kafka如何保证消息不重复处理

5. kafka 如何保证消息不丢失

6. kafka如何保证消息有序（和kafka消息的获取策略还有一定关系，主动拉取，保证一个消费者拉一个分区）

7. kafka如果消费者数量小于分区的数量会有什么影响

一个主题可以配置多个分区，一个分区可以有多个消费者组消费，每个消费者组只有一个消费者能消费某条消息

应该没啥影响，如果多的话会产生闲置的消费者，如果有多个消费者组，组和组直接没有什么影响

 

生产者默认的分区策略是：

• 如果在发消息的时候指定了分区，则消息投递到指定的分区
• 如果没有指定分区，但是消息的key不为空，则基于key的哈希值来选择一个分区
• 如果既没有指定分区，且消息的key也是空，则用轮询的方式选择一个分区

消费者分区分配策略

当消费者加入群组的时候，会根据分区分配策略决定哪些分区分配给哪些消费者。
Kafka有两种分配策略：Range和RoundRobin。

• Range（默认分配策略）
  Topic的若干个连续的Partition分配给消费者。
• RoundRobin
  Topic的所有Partition逐个分配给消费者。

Range 分配策略源码：

/**
 * The range assignor works on a per-topic basis. For each topic, we lay out the available partitions in numeric order
 * and the consumers in lexicographic order. We then divide the number of partitions by the total number of
 * consumers to determine the number of partitions to assign to each consumer. If it does not evenly
 * divide, then the first few consumers will have one extra partition.
 *
 * For example, suppose there are two consumers C0 and C1, two topics t0 and t1, and each topic has 3 partitions,
 * resulting in partitions t0p0, t0p1, t0p2, t1p0, t1p1, and t1p2.
 *
 * The assignment will be:
 * C0: [t0p0, t0p1, t1p0, t1p1]
 * C1: [t0p2, t1p2]
 */
这里是3个分区，两个消费则，除了以后是C0负责前面两个分区，C1 负责后面一个分区

roundrobin（轮询）

roundronbin分配策略的具体实现是org.apache.kafka.clients.consumer.RoundRobinAssignor

/**
 * The round robin assignor lays out all the available partitions and all the available consumers. It
 * then proceeds to do a round robin assignment from partition to consumer. If the subscriptions of all consumer
 * instances are identical, then the partitions will be uniformly distributed. (i.e., the partition ownership counts
 * will be within a delta of exactly one across all consumers.)
 *
 * For example, suppose there are two consumers C0 and C1, two topics t0 and t1, and each topic has 3 partitions,
 * resulting in partitions t0p0, t0p1, t0p2, t1p0, t1p1, and t1p2.
 *
 * The assignment will be:
 * C0: [t0p0, t0p2, t1p1]
 * C1: [t0p1, t1p0, t1p2]
 *
 * When subscriptions differ across consumer instances, the assignment process still considers each
 * consumer instance in round robin fashion but skips over an instance if it is not subscribed to
 * the topic. Unlike the case when subscriptions are identical, this can result in imbalanced
 * assignments. For example, we have three consumers C0, C1, C2, and three topics t0, t1, t2,
 * with 1, 2, and 3 partitions, respectively. Therefore, the partitions are t0p0, t1p0, t1p1, t2p0,
 * t2p1, t2p2. C0 is subscribed to t0; C1 is subscribed to t0, t1; and C2 is subscribed to t0, t1, t2.
 *
 * Tha assignment will be:
 * C0: [t0p0]
 * C1: [t1p0]
 * C2: [t1p1, t2p0, t2p1, t2p2]
 */

分区Rebalance(再均衡)

• 有新的消费者加入消费者群组
• 已有的消费者退出消费者群组
• 订阅的主题的分区发生变化

以上三种情况都会触发分区的重新分配，重新分配的过程叫Rebalance(再均衡)。
Rebalance给消费者群组带来了高可用性与伸缩性，但是在Rebalance期间，消费者无法读取消息，整个群组一小段时间不可用，而且当分区被重新分配给另一个消费者时，消费者当前的读取状态会丢失。

 

感觉问的比较简单，没有什么深入的了解。