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zookeeper中怎么存儲Kafka,相信很多沒有經驗的人對此束手無策,為此本文總結了問題出現的原因和解決方法,通過這篇文章希望你能解決這個問題。
/brokers/topics/[topic] :
存儲某個topic的partitions所有分配信息
[zk: localhost:2181(CONNECTED) 1] get /brokers/topics/topic2
Schema: { "version": "版本編號目前固定為數字1", "partitions": { "partitionId編號": [ 同步副本組brokerId列表 ], "partitionId編號": [ 同步副本組brokerId列表 ], ....... } } Example: { "version": 1, "partitions": { "2": [1, 2, 3], "1": [0, 1, 2], "0": [3, 0, 1], } }
Schema: { "controller_epoch": 表示kafka集群中的中央控制器選舉次數, "leader": 表示該partition選舉leader的brokerId, "version": 版本編號默認為1, "leader_epoch": 該partition leader選舉次數, "isr": [同步副本組brokerId列表] } Example: { "controller_epoch": 1, "leader": 3, "version": 1, "leader_epoch": 0, "isr": [3, 0, 1] }
Schema: { "jmx_port": jmx端口號, "timestamp": kafka broker初始啟動時的時間戳, "host": 主機名或ip地址, "version": 版本編號默認為1, "port": kafka broker的服務端端口號,由server.properties中參數port確定 } Example: { "jmx_port": -1, "timestamp":"1525741823119" "version": 1, "host": "hadoop1", "port": 9092 }
/controller -> int (broker id of the controller) 存儲center controller中央控制器所在kafka broker的信息
Schema: { "version": 版本編號默認為1, "brokerid": kafka集群中broker唯一編號, "timestamp": kafka broker中央控制器變更時的時間戳 } Example: { "version": 1, "brokerid": 0, "timestamp": "1525741822769" }
a.每個consumer客戶端被創建時,會向zookeeper注冊自己的信息;
b.此作用主要是為了"負載均衡".
c.同一個Consumer Group中的Consumers,Kafka將相應Topic中的每個消息只發送給其中一個Consumer。
d.Consumer Group中的每個Consumer讀取Topic的一個或多個Partitions,并且是唯一的Consumer;
e.一個Consumer group的多個consumer的所有線程依次有序地消費一個topic的所有partitions,如果Consumer group中所有consumer總線程大于partitions數量,則會出現空閑情況;
舉例說明:
kafka集群中創建一個topic為report-log 4 partitions 索引編號為0,1,2,3
假如有目前有三個消費者node:注意-->一個consumer中一個消費線程可以消費一個或多個partition.
如果每個consumer創建一個consumer thread線程,各個node消費情況如下,node1消費索引編號為0,1分區,node2費索引編號為2,node3費索引編號為3
如果每個consumer創建2個consumer thread線程,各個node消費情況如下(是從consumer node先后啟動狀態來確定的),node1消費索引編號為0,1分區;node2費索引編號為2,3;node3為空閑狀態
總結:
從以上可知,Consumer Group中各個consumer是根據先后啟動的順序有序消費一個topic的所有partitions的。
如果Consumer Group中所有consumer的總線程數大于partitions數量,則可能consumer thread或consumer會出現空閑狀態。
當一個group中,有consumer加入或者離開時,會觸發partitions均衡.均衡的最終目的,是提升topic的并發消費能力.
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) 首先根據partition索引號對partitions排序: P0,P1,P2,P3
4) 根據(consumer.id + '-'+ thread序號)排序: C0,C1
5) 計算倍數: 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)]
每個consumer都有一個唯一的ID(consumerId可以通過配置文件指定,也可以由系統生成),此id用來標記消費者信息.
/consumers/[groupId]/ids/[consumerIdString]
是一個臨時的znode,此節點的值為請看consumerIdString產生規則,即表示此consumer目前所消費的topic + partitions列表.
consumerId產生規則:
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;
[zk: localhost:2181(CONNECTED) 11] get /consumers/console-consumer-2304/ids/console-consumer-2304_hadoop2-1525747915241-6b48ff32
Schema: { "version": 版本編號默認為1, "subscription": { //訂閱topic列表 "topic名稱": consumer中topic消費者線程數 }, "pattern": "static", "timestamp": "consumer啟動時的時間戳" } Example: { "version": 1, "subscription": { "topic2": 1 }, "pattern": "white_list", "timestamp": "1525747915336" }
/consumers/[groupId]/offsets/[topic]/[partitionId] -> long (offset)
用來跟蹤每個consumer目前所消費的partition中最大的offset
此znode為持久節點,可以看出offset跟group_id有關,以表明當消費者組(consumer group)中一個消費者失效,
重新觸發balance,其他consumer可以繼續消費.
/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] } ] }
{ "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 } ] }
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"] }
/config/topics/[topic_name]
看完上述內容,你們掌握zookeeper中怎么存儲Kafka的方法了嗎?如果還想學到更多技能或想了解更多相關內容,歡迎關注億速云行業資訊頻道,感謝各位的閱讀!
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