Kafka Topic的详细信息 捎带主要的安装步骤

1. 安装步骤

Kafka伪分布式安装的思路跟Zookeeper的伪分布式安装思路完全一样，不过比Zookeeper稍微简单些(不需要创建myid文件),

主要是针对每个Kafka服务器配置一个单独的server.properties，三个服务器分别使用server.properties，server.1.properties, server.2.properties

cp server.properties server.1.properties
cp server.properties server.2.properties

修改server.1.properties和server.2.properties,主要有三个属性需要修改

broker.id=1
port=9093
log.dirs=/tmp/kafka-logs-1  

port指的是Kakfa服务器监听的端口

启动三个Kafka:

bin/kafka-server-start.sh server.properties
bin/kafka-server-start.sh server.1.properties
bin/kafka-server-start.sh server.2.properties

2. Kafka脚本常用配置参数

2.1 kafka-console-consumer.sh

--from-beginning                        If the consumer does not already have an established offset to consume from, start with the earliest message present in the log rather than the latest message.

--topic <topic>                           The topic id to consume on

--zookeeper <urls>                    REQUIRED: The connection string for the zookeeper connection in the form host:port. Multiple URLS can be given to allow fail-over.

--group <gid>                            The group id to consume on. (default: console-consumer-37803)

在consumer端，不需要指定broke-list，而是通过zookeeper和topic找到所有的持有topic消息的broker

2.2 kafka-console-producer.sh

--topic <topic>                         REQUIRED: The topic id to produce  messages to.

--broker-list <broker-list>        REQUIRED: The broker list string in the form HOST1:PORT1,HOST2:PORT2.

2.3 kafka-topic.sh

--create                                Create a new topic.

--describe                              List details for the given topics.

--list                                  List all available topics.

--partitions <Integer: # of partitions> The number of partitions for the topic being created or altered (WARNING:   If partitions are increased for a  topic that has a key, the partition logic or ordering of the messages will be affected)

--replication-factor <Integer: replication factor> The replication factor for each partition in the topic being created

--zookeeper <urls>                    REQUIRED: The connection string for the zookeeper connection in the form host:port. Multiple URLS can be given to allow fail-over.

--topic <topic>                         The topic to be create, alter or describe. Can also accept a regular expression except for --create option

3. 伪机群测试

测试前，先总结有哪些测试点

目前想到的是，Partition有个leader的概念，leader partition是什么意思？干什么用的？

3.1 创建Topic

创建一个Topic，10个Partition，副本数为3，也就是说，每个broker上的每个分区，在其它节点都有副本，因为每个节点都有10个节点的数据

3.2 每个broker创建的目录

当创建完Topic后，每个Topic都会在Kakfa的配置目录下（比如/tmp/kafka-logs，建立相应的目录和文件）

topic_p10_r3-0

topic_p10_r3-1

----

topic_p10_r3-9

其中每个目录下面都有两个文件： 00000000000000000000.index  00000000000000000000.log

3.3 Topic的详细信息

./kafka-topics.sh --describe --topic topic_p10_r3  --zookeeper localhost:2181  

得到的结果如下：

Topic:topic_p10_r3    PartitionCount:10    ReplicationFactor:3    Configs:
    Topic: topic_p10_r3    Partition: 0    Leader: 2    Replicas: 2,0,1    Isr: 2,0,1
    Topic: topic_p10_r3    Partition: 1    Leader: 0    Replicas: 0,1,2    Isr: 0,1,2
    Topic: topic_p10_r3    Partition: 2    Leader: 1    Replicas: 1,2,0    Isr: 1,2,0
    Topic: topic_p10_r3    Partition: 3    Leader: 2    Replicas: 2,1,0    Isr: 2,1,0
    Topic: topic_p10_r3    Partition: 4    Leader: 0    Replicas: 0,2,1    Isr: 0,2,1
    Topic: topic_p10_r3    Partition: 5    Leader: 1    Replicas: 1,0,2    Isr: 1,0,2
    Topic: topic_p10_r3    Partition: 6    Leader: 2    Replicas: 2,0,1    Isr: 2,0,1
    Topic: topic_p10_r3    Partition: 7    Leader: 0    Replicas: 0,1,2    Isr: 0,1,2
    Topic: topic_p10_r3    Partition: 8    Leader: 1    Replicas: 1,2,0    Isr: 1,2,0
    Topic: topic_p10_r3    Partition: 9    Leader: 2    Replicas: 2,1,0    Isr: 2,1,0

具体的含义是：

Here is an explanation of output. The first line gives a summary of all the partitions, each additional line gives information about one partition

• "leader" is the node responsible for all reads and writes for the given partition. Each node will be the leader for a randomly selected portion of the partitions.
• "replicas" is the list of nodes that replicate the log for this partition regardless of whether they are the leader or even if they are currently alive.
• "isr" is the set of "in-sync" replicas. This is the subset of the replicas list that is currently alive and caught-up to the leader.

3.4 问题： 如果副本数为1，是否表示每个partition在集群中只有1份(也就是说每个partition只会存在于一个broker上)，那么leader自然就表示这个partition就在leader所指的broker上了？

建立包含10个分区，同时只有一个副本的topic

./kafka-topics.sh --create  --topic  topic_p10_r1 --partitions 10 --replication-factor 1  --zookeeper localhost:2181

　　

[hadoop@hadoop bin]$ ./kafka-topics.sh --describe --topic topic_p10_r1  --zookeeper localhost:2181
Topic:topic_p10_r1  PartitionCount:10   ReplicationFactor:1 Configs:
    Topic: topic_p10_r1 Partition: 0    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 1    Leader: 2   Replicas: 2 Isr: 2
    Topic: topic_p10_r1 Partition: 2    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 3    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 4    Leader: 2   Replicas: 2 Isr: 2
    Topic: topic_p10_r1 Partition: 5    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 6    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 7    Leader: 2   Replicas: 2 Isr: 2
    Topic: topic_p10_r1 Partition: 8    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 9    Leader: 1   Replicas: 1 Isr: 1 

可见理解不错，每个partition有不同的leader，Leader所在的broker同时也是Replicas所在的broker(ID号一样)

因此可以理解，

1. 每个partition副本集都有一个leader

2. leader指的是partition副本集中的leader，它负责读写，然后负责将数据复制到其它的broker上。

3.一个Topic的所有partition会比较均匀的分布到多个broker上

3.5 broker挂了，Kafka的容错机制

在上面已经建立了两个Topic，一个是10个分区3个副本， 一个是10个分区1个副本。此时，假如有一个broker挂了，看看这两个Topic的容错如何？

通过jps命令可以看到有三个Kafka进程。

通过ps -ef|grep server.2.properties可以找到brokerId为2的Kakfa进程，使用kill -9将其干掉。干掉的时候，console开始刷屏，异常信息一样，都是：

[2015-02-23 02:14:00,037] WARN Reconnect due to socket error: null (kafka.consumer.SimpleConsumer)
[2015-02-23 02:14:00,039] ERROR [ReplicaFetcherThread-0-2], Error in fetch Name: FetchRequest; Version: 0; CorrelationId: 4325; ClientId: ReplicaFetcherThread-0-2; ReplicaId: 1; MaxWait: 500 ms; MinBytes: 1 bytes; RequestInfo: [topic_p10_r3,3] -> PartitionFetchInfo(0,1048576),[topic_p10_r3,9] -> PartitionFetchInfo(0,1048576),[topic_p10_r3,6] -> PartitionFetchInfo(0,1048576),[topic_p10_r3,0] -> PartitionFetchInfo(0,1048576) (kafka.server.ReplicaFetcherThread)
java.net.ConnectException: Connection refused
    at sun.nio.ch.Net.connect0(Native Method)
    at sun.nio.ch.Net.connect(Net.java:465)
    at sun.nio.ch.Net.connect(Net.java:457)
    at sun.nio.ch.SocketChannelImpl.connect(SocketChannelImpl.java:670)
    at kafka.network.BlockingChannel.connect(BlockingChannel.scala:57)
    at kafka.consumer.SimpleConsumer.connect(SimpleConsumer.scala:44)
    at kafka.consumer.SimpleConsumer.reconnect(SimpleConsumer.scala:57)
    at kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:79)
    at kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:71)
    at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:109)
    at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:109)
    at kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:109)
    at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
    at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:108)
    at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:108)
    at kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:108)
    at kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
    at kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:107)
    at kafka.server.AbstractFetcherThread.processFetchRequest(AbstractFetcherThread.scala:96)
    at kafka.server.AbstractFetcherThread.doWork(AbstractFetcherThread.scala:88)
    at kafka.utils.ShutdownableThread.run(ShutdownableThread.scala:51)
[2015-02-23 02:14:00,040] WARN Reconnect due to socket error: null (kafka.consumer.SimpleConsumer)

3,9,6,0 这个四个分区 正是topic_p10_r3上broker2作为leader的partition，可见Kafka要做Leader移交，看看此时的topic_p10_r3和topic_p10_r1的情况，我们已经把broker2 kill掉了

topic_p10_r3（Partition切换到其它Leader上了。。。Rplicas还有3,。。。）

[hadoop@hadoop bin]$ ./kafka-topics.sh --describe --topic topic_p10_r3  --zookeeper localhost:2181
Topic:topic_p10_r3  PartitionCount:10   ReplicationFactor:3 Configs:
    Topic: topic_p10_r3 Partition: 0    Leader: 0   Replicas: 2,0,1 Isr: 0,1
    Topic: topic_p10_r3 Partition: 1    Leader: 0   Replicas: 0,1,2 Isr: 0,1
    Topic: topic_p10_r3 Partition: 2    Leader: 1   Replicas: 1,2,0 Isr: 1,0
    Topic: topic_p10_r3 Partition: 3    Leader: 1   Replicas: 2,1,0 Isr: 1,0
    Topic: topic_p10_r3 Partition: 4    Leader: 0   Replicas: 0,2,1 Isr: 0,1
    Topic: topic_p10_r3 Partition: 5    Leader: 1   Replicas: 1,0,2 Isr: 1,0
    Topic: topic_p10_r3 Partition: 6    Leader: 0   Replicas: 2,0,1 Isr: 0,1
    Topic: topic_p10_r3 Partition: 7    Leader: 0   Replicas: 0,1,2 Isr: 0,1
    Topic: topic_p10_r3 Partition: 8    Leader: 1   Replicas: 1,2,0 Isr: 1,0
    Topic: topic_p10_r3 Partition: 9    Leader: 1   Replicas: 2,1,0 Isr: 1,0

topic_p10_r1:没有切换，其中分区为1,47的Leader是-1了。。 这就出错了

[hadoop@hadoop bin]$ ./kafka-topics.sh --describe --topic topic_p10_r1  --zookeeper localhost:2181
Topic:topic_p10_r1  PartitionCount:10   ReplicationFactor:1 Configs:
    Topic: topic_p10_r1 Partition: 0    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 1    Leader: -1  Replicas: 2 Isr:
    Topic: topic_p10_r1 Partition: 2    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 3    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 4    Leader: -1  Replicas: 2 Isr:
    Topic: topic_p10_r1 Partition: 5    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 6    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 7    Leader: -1  Replicas: 2 Isr:
    Topic: topic_p10_r1 Partition: 8    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 9    Leader: 1   Replicas: 1 Isr: 1  

重启broker 2得到结果如下：（对于topic_p10_r3，leader没有变化，即每个Partition都有自己的Leader，新加入的broker只能follower；而topic_p10_r1,则会选出Leader）

[hadoop@hadoop bin]$ ./kafka-topics.sh --describe --topic topic_p10_r3  --zookeeper localhost:2181
Topic:topic_p10_r3  PartitionCount:10   ReplicationFactor:3 Configs:
    Topic: topic_p10_r3 Partition: 0    Leader: 0   Replicas: 2,0,1 Isr: 0,1,2
    Topic: topic_p10_r3 Partition: 1    Leader: 0   Replicas: 0,1,2 Isr: 0,1,2
    Topic: topic_p10_r3 Partition: 2    Leader: 1   Replicas: 1,2,0 Isr: 1,0,2
    Topic: topic_p10_r3 Partition: 3    Leader: 1   Replicas: 2,1,0 Isr: 1,0,2
    Topic: topic_p10_r3 Partition: 4    Leader: 0   Replicas: 0,2,1 Isr: 0,1,2
    Topic: topic_p10_r3 Partition: 5    Leader: 1   Replicas: 1,0,2 Isr: 1,0,2
    Topic: topic_p10_r3 Partition: 6    Leader: 0   Replicas: 2,0,1 Isr: 0,1,2
    Topic: topic_p10_r3 Partition: 7    Leader: 0   Replicas: 0,1,2 Isr: 0,1,2
    Topic: topic_p10_r3 Partition: 8    Leader: 1   Replicas: 1,2,0 Isr: 1,0,2
    Topic: topic_p10_r3 Partition: 9    Leader: 1   Replicas: 2,1,0 Isr: 1,0,2
[hadoop@hadoop bin]$ ./kafka-topics.sh --describe --topic topic_p10_r1  --zookeeper localhost:2181
Topic:topic_p10_r1  PartitionCount:10   ReplicationFactor:1 Configs:
    Topic: topic_p10_r1 Partition: 0    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 1    Leader: 2   Replicas: 2 Isr: 2
    Topic: topic_p10_r1 Partition: 2    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 3    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 4    Leader: 2   Replicas: 2 Isr: 2
    Topic: topic_p10_r1 Partition: 5    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 6    Leader: 1   Replicas: 1 Isr: 1
    Topic: topic_p10_r1 Partition: 7    Leader: 2   Replicas: 2 Isr: 2
    Topic: topic_p10_r1 Partition: 8    Leader: 0   Replicas: 0 Isr: 0
    Topic: topic_p10_r1 Partition: 9    Leader: 1   Replicas: 1 Isr: 1