kafka在zookeeper中存储结构
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1.topic注册信息
/brokers/topics/[topic] :
存储某个topic的partitions所有分配信息
Schema:{ "version": "版本编号目前固定为数字1", "partitions": { "partitionId编号": [ 同步副本组brokerId列表 ], "partitionId编号": [ 同步副本组brokerId列表 ], ....... }}Example:{"version": 1,"partitions": {"0": [1, 2],"1": [2, 1],"2": [1, 2],}}说明:紫红色为patitions编号,蓝色为同步副本组brokerId列表
2.partition状态信息
/brokers/topics/[topic]/partitions/[0...N] 其中[0..N]表示partition索引号
/brokers/topics/[topic]/partitions/[partitionId]/state
Schema:{"controller_epoch": 表示kafka集群中的中央控制器选举次数,"leader": 表示该partition选举leader的brokerId,"version": 版本编号默认为1,"leader_epoch": 该partition leader选举次数,"isr": [同步副本组brokerId列表]}Example:{"controller_epoch": 1,"leader": 2,"version": 1,"leader_epoch": 0,"isr": [2, 1]}
3. Broker注册信息
/brokers/ids/[0...N]每个broker的配置文件中都需要指定一个数字类型的id(全局不可重复),此节点为临时znode(EPHEMERAL)
Schema:{"jmx_port": jmx端口号,"timestamp": kafka broker初始启动时的时间戳,"host": 主机名或ip地址,"version": 版本编号默认为1,"port": kafka broker的服务端端口号,由server.properties中参数port确定} Example:{"jmx_port": 6061,"timestamp":"1403061899859""version": 1,"host": "192.168.1.148","port": 9092}
4. Controller epoch:
/controller_epoch -> int (epoch)
此值为一个数字,kafka集群中第一个broker第一次启动时为1,以后只要集群中center controller中央控制器所在broker变更或挂掉,就会重新选举新的center controller,每次center controller变更controller_epoch值就会 + 1;
5. Controller注册信息:
/controller -> int (broker id of the controller) 存储center controller中央控制器所在kafka broker的信息
Schema:{"version": 版本编号默认为1,"brokerid": kafka集群中broker唯一编号,"timestamp": kafka broker中央控制器变更时的时间戳} Example:{"version": 1,"brokerid": 3,"timestamp": "1403061802981"}
a.每个consumer客户端被创建时,会向zookeeper注册自己的信息;
b.此作用主要是为了"负载均衡".
c.同一个Consumer Group中的Consumers,Kafka将相应Topic中的每个消息只发送给其中一个Consumer。
d.Consumer Group中的每个Consumer读取Topic的一个或多个Partitions,并且是唯一的Consumer;
e.一个Consumer group的多个consumer的所有线程依次有序地消费一个topic的所有partitions,如果Consumer group中所有consumer总线程大于partitions数量,则会出现空闲情况;举例说明:kafka集群中创建一个topic为report-log 4 partitions 索引编号为0,1,2,3假如有目前有三个消费者node:注意-->一个consumer中一个消费线程可以消费一个或多个partition.如果每个consumer创建一个consumer thread线程,各个node消费情况如下,node1消费索引编号为0,1分区,node2费索引编号为2,node3费索引编号为3总结:如果每个consumer创建2个consumer thread线程,各个node消费情况如下(是从consumer node先后启动状态来确定的),node1消费索引编号为0,1分区;node2费索引编号为2,3;node3为空闲状态
从以上可知,Consumer Group中各个consumer是根据先后启动的顺序有序消费一个topic的所有partitions的。如果Consumer Group中所有consumer的总线程数大于partitions数量,则可能consumer thread或consumer会出现空闲状态。
Consumer均衡算法
当一个group中,有consumer加入或者离开时,会触发partitions均衡.均衡的最终目的,是提升topic的并发消费能力.
1) 假如topic1,具有如下partitions: P0,P1,P2,P3
2) 加入group中,有如下consumer: C0,C1
3) 首先根据partition索引号对partitions排序: P0,P1,P2,P3
4) 根据(consumer.id + '-'+ thread序号)排序: C0,C1
5) 计算倍数: M = [P0,P1,P2,P3].size / [C0,C1].size,本例值M=2(向上取整)
6) 然后依次分配partitions: C0 = [P0,P1],C1=[P2,P3],即Ci = [P(i * M),P((i + 1) * M -1)]
6. Consumer注册信息:
每个consumer都有一个唯一的ID(consumerId可以通过配置文件指定,也可以由系统生成),此id用来标记消费者信息.
/consumers/[groupId]/ids/[consumerIdString] (这个我自己的kafka上没看到)
是一个临时的znode,此节点的值为请看consumerIdString产生规则,即表示此consumer目前所消费的topic + partitions列表.
consumerId产生规则:
StringconsumerUuid = null; if(config.consumerId!=null && config.consumerId) consumerUuid = consumerId; else { String uuid = UUID.randomUUID() consumerUuid = "%s-%d-%s".format( InetAddress.getLocalHost.getHostName, System.currentTimeMillis, uuid.getMostSignificantBits().toHexString.substring(0,8)); } String consumerIdString = config.groupId + "_" + consumerUuid;
Schema:{"version": 版本编号默认为1,"subscription": { //订阅topic列表"topic名称": consumer中topic消费者线程数},"pattern": "static","timestamp": "consumer启动时的时间戳"} Example:{"version": 1,"subscription": {"open_platform_opt_push_plus1": 5},"pattern": "static","timestamp": "1411294187842"}
7. Consumer owner:
/consumers/[groupId]/owners/[topic]/[partitionId] -> consumerIdString + threadId索引编号 (这个我自己的kafka上没看到)
当consumer启动时,所触发的操作:
a) 首先进行"Consumer Id注册";
b) 然后在"Consumer id 注册"节点下注册一个watch用来监听当前group中其他consumer的"退出"和"加入";只要此znode path下节点列表变更,都会触发此group下consumer的负载均衡.(比如一个consumer失效,那么其他consumer接管partitions).
c) 在"Broker id 注册"节点下,注册一个watch用来监听broker的存活情况;如果broker列表变更,将会触发所有的groups下的consumer重新balance.
8. Consumer offset:
/consumers/[groupId]/offsets/[topic]/[partitionId] -> long (offset)
用来跟踪每个consumer目前所消费的partition中最大的offset
此znode为持久节点,可以看出offset跟group_id有关,以表明当消费者组(consumer group)中一个消费者失效,
重新触发balance,其他consumer可以继续消费.
9. Re-assign partitions
/admin/reassign_partitions
{ "fields":[ { "name":"version", "type":"int", "doc":"version id" }, { "name":"partitions", "type":{ "type":"array", "items":{ "fields":[ { "name":"topic", "type":"string", "doc":"topic of the partition to be reassigned" }, { "name":"partition", "type":"int", "doc":"the partition to be reassigned" }, { "name":"replicas", "type":"array", "items":"int", "doc":"a list of replica ids" } ], } "doc":"an array of partitions to be reassigned to new replicas" } } ]} Example:{ "version": 1, "partitions": [ { "topic": "Foo", "partition": 1, "replicas": [0, 1, 3] } ] }
10. Preferred replication election
/admin/preferred_replica_election
{ "fields":[ { "name":"version", "type":"int", "doc":"version id" }, { "name":"partitions", "type":{ "type":"array", "items":{ "fields":[ { "name":"topic", "type":"string", "doc":"topic of the partition for which preferred replica election should be triggered" }, { "name":"partition", "type":"int", "doc":"the partition for which preferred replica election should be triggered" } ], } "doc":"an array of partitions for which preferred replica election should be triggered" } } ]} 例子: { "version": 1, "partitions": [ { "topic": "Foo", "partition": 1 }, { "topic": "Bar", "partition": 0 } ] }
11. 删除topics
/admin/delete_topics
Schema:{ "fields": [ {"name": "version", "type": "int", "doc": "version id"}, {"name": "topics", "type": { "type": "array", "items": "string", "doc": "an array of topics to be deleted"} } ]} 例子:{ "version": 1, "topics": ["foo", "bar"]}
12、Topic配置
/config/topics/[topic_name]
例子
{
"version"
:
1
,
"config"
: {
"config.a"
:
"x"
,
"config.b"
:
"y"
,
...
}
}
请注明转载自:http://blog.csdn.net/lizhitao/article/details/23744675
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