Kafka Tools

简介:

参考,

https://cwiki.apache.org/confluence/display/KAFKA/System+Tools

https://cwiki.apache.org/confluence/display/KAFKA/Replication+tools

http://kafka.apache.org/documentation.html#quickstart

http://kafka.apache.org/documentation.html#operations

 

为了便于使用,kafka提供了比较强大的Tools,把经常需要使用的整理一下

 

开关kafka Server

bin/kafka-server-start.sh config/server.properties
bin/kafka-server-stop.sh
JMX_PORT=9999 nohup bin/kafka-server-start.sh config/server.properties &

 

topic相关

bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test
bin/kafka-topics.sh --list --zookeeper localhost:2181

describe topic的详细情况

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

修改topic的partition,只能增加

 

bin/kafka-topics.sh --alter --zookeeper localhost:2181 --partitions 3 --topic test

到0.8.2才正式支持删除topic,当前是beta版

/usr/local/rds/kafka/bin/kafka-topics.sh --delete --topic topic_name --zookeeper localhost:2181

注意在配置里面,delete.topic.enable=true

 

查看有问题的partition

bin/kafka-topics.sh --describe --zookeeper localhost:2181 --unavailable-partitions --topic test
 
per-topic 修改参数
> bin/kafka-topics.sh --zookeeper localhost:2181 --create --topic my-topic --partitions 1 
        --replication-factor 1 --config max.message.bytes=64000 --config flush.messages=1
> bin/kafka-topics.sh --zookeeper localhost:2181 --alter --topic my-topic 
    --config max.message.bytes=128000
> bin/kafka-topics.sh --zookeeper localhost:2181 --alter --topic my-topic 
    --deleteConfig max.message.bytes

 

集群扩展 
集群扩展,对于broker还是比较简单的,但是现有的topic上的partition是不会做自动迁移的 
需要手工做迁移,但kafka提供了比较方便的工具,

--generate,生成参考的迁移计划 
given a list of topics and a list of brokers,工具会给出迁徙方案

把topic完全迁移到新的brokers

> cat topics-to-move.json
{"topics": [{"topic": "foo1"},
            {"topic": "foo2"}],
 "version":1
}
复制代码
> bin/kafka-reassign-partitions.sh --zookeeper localhost:2181 --topics-to-move-json-file topics-to-move.json --broker-list "5,6" --generate 
Current partition replica assignment

{"version":1,
 "partitions":[{"topic":"foo1","partition":2,"replicas":[1,2]},
               {"topic":"foo1","partition":0,"replicas":[3,4]},
               {"topic":"foo2","partition":2,"replicas":[1,2]},
               {"topic":"foo2","partition":0,"replicas":[3,4]},
               {"topic":"foo1","partition":1,"replicas":[2,3]},
               {"topic":"foo2","partition":1,"replicas":[2,3]}]
}

Proposed partition reassignment configuration

{"version":1,
 "partitions":[{"topic":"foo1","partition":2,"replicas":[5,6]},
               {"topic":"foo1","partition":0,"replicas":[5,6]},
               {"topic":"foo2","partition":2,"replicas":[5,6]},
               {"topic":"foo2","partition":0,"replicas":[5,6]},
               {"topic":"foo1","partition":1,"replicas":[5,6]},
               {"topic":"foo2","partition":1,"replicas":[5,6]}]
}
复制代码

给出当前的assignment情况和,迁移方案

我们可以同时保存当前的assignment情况和迁移方案,当前的assignment情况可以用于rollback

--execute,开始执行迁移

复制代码
> bin/kafka-reassign-partitions.sh --zookeeper localhost:2181 --reassignment-json-file expand-cluster-reassignment.json --execute
Current partition replica assignment

{"version":1,
 "partitions":[{"topic":"foo1","partition":2,"replicas":[1,2]},
               {"topic":"foo1","partition":0,"replicas":[3,4]},
               {"topic":"foo2","partition":2,"replicas":[1,2]},
               {"topic":"foo2","partition":0,"replicas":[3,4]},
               {"topic":"foo1","partition":1,"replicas":[2,3]},
               {"topic":"foo2","partition":1,"replicas":[2,3]}]
}

Save this to use as the --reassignment-json-file option during rollback
Successfully started reassignment of partitions
{"version":1,
 "partitions":[{"topic":"foo1","partition":2,"replicas":[5,6]},
               {"topic":"foo1","partition":0,"replicas":[5,6]},
               {"topic":"foo2","partition":2,"replicas":[5,6]},
               {"topic":"foo2","partition":0,"replicas":[5,6]},
               {"topic":"foo1","partition":1,"replicas":[5,6]},
               {"topic":"foo2","partition":1,"replicas":[5,6]}]
}
复制代码

--verify,check当前的迁移状态

复制代码
> bin/kafka-reassign-partitions.sh --zookeeper localhost:2181 --reassignment-json-file expand-cluster-reassignment.json --verify
Status of partition reassignment:
Reassignment of partition [foo1,0] completed successfully
Reassignment of partition [foo1,1] is in progress
Reassignment of partition [foo1,2] is in progress
Reassignment of partition [foo2,0] completed successfully
Reassignment of partition [foo2,1] completed successfully 
Reassignment of partition [foo2,2] completed successfully
复制代码

选择topic的某个partition的某些replica进行迁徙

moves partition 0 of topic foo1 to brokers 5,6 and partition 1 of topic foo2 to brokers 2,3

> cat custom-reassignment.json
{"version":1,"partitions":[{"topic":"foo1","partition":0,"replicas":[5,6]},{"topic":"foo2","partition":1,"replicas":[2,3]}]}
复制代码
> bin/kafka-reassign-partitions.sh --zookeeper localhost:2181 --reassignment-json-file custom-reassignment.json --execute
Current partition replica assignment

{"version":1,
 "partitions":[{"topic":"foo1","partition":0,"replicas":[1,2]},
               {"topic":"foo2","partition":1,"replicas":[3,4]}]
}

Save this to use as the --reassignment-json-file option during rollback
Successfully started reassignment of partitions
{"version":1,
 "partitions":[{"topic":"foo1","partition":0,"replicas":[5,6]},
               {"topic":"foo2","partition":1,"replicas":[2,3]}]
}
复制代码

brokers下线

当前版本不支持下线的规划,需要到0.8.2才支持,这需要把一个broker上的replica清空

增加replication factor

partition 0的replica数从1增长到3,当前replica存在broker5,在broker6,7上增加replica

> cat increase-replication-factor.json
{"version":1,
 "partitions":[{"topic":"foo","partition":0,"replicas":[5,6,7]}]}
复制代码
> bin/kafka-reassign-partitions.sh --zookeeper localhost:2181 --reassignment-json-file increase-replication-factor.json --execute
Current partition replica assignment

{"version":1,
 "partitions":[{"topic":"foo","partition":0,"replicas":[5]}]}

Save this to use as the --reassignment-json-file option during rollback
Successfully started reassignment of partitions
{"version":1,
 "partitions":[{"topic":"foo","partition":0,"replicas":[5,6,7]}]}
复制代码

 

Producer console

> bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test 
This is a message
This is another message

后面可以任意的输入message,都会发到broker的topic中

 

Comsumer console

bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginning

从头读这个topic,可以重复读到所有数据 
我在想为啥,每次都能replay,原来每次都是随机产生一个groupid 
consumerProps.put("group.id","console-consumer-" + new Random().nextInt(100000))

 

Consumer Offset Checker

这个会显示出consumer group的offset情况, 必须参数为--group, 不指定--topic,默认为所有topic

Displays the:  Consumer Group, Topic, Partitions, Offset, logSize, Lag, Owner for the specified set of Topics and Consumer Group

bin/kafka-run-class.sh kafka.tools.ConsumerOffsetChecker

required argument: [group] 
Option Description 
------ ----------- 
--broker-info Print broker info 
--group Consumer group. 
--help Print this message. 
--topic Comma-separated list of consumer 
   topics (all topics if absent). 
--zkconnect ZooKeeper connect string. (default: localhost:2181)

Example,

bin/kafka-run-class.sh kafka.tools.ConsumerOffsetChecker --group pv

Group           Topic                          Pid Offset          logSize         Lag             Owner 
pv              page_visits                    0   21              21              0               none 
pv              page_visits                    1   19              19              0               none 
pv              page_visits                    2   20              20              0               none

 

 

Export Zookeeper Offsets

将Zk中的offset信息以下面的形式打到file里面去

A utility that retrieves the offsets of broker partitions in ZK and prints to an output file in the following format:

/consumers/group1/offsets/topic1/1-0:286894308 
/consumers/group1/offsets/topic1/2-0:284803985

bin/kafka-run-class.sh kafka.tools.ExportZkOffsets

required argument: [zkconnect] 
Option Description 
------ ----------- 
--group Consumer group. 
--help Print this message. 
--output-file Output file 
--zkconnect ZooKeeper connect string. (default: localhost:2181)

 

Update Offsets In Zookeeper

这个挺有用,用于replay, kafka的文档有点坑爹,看了不知道咋用,还是看源码才看明白

A utility that updates the offset of every broker partition to the offset of earliest or latest log segment file, in ZK.

bin/kafka-run-class.sh kafka.tools.UpdateOffsetsInZK

USAGE: kafka.tools.UpdateOffsetsInZK$ [earliest | latest] consumer.properties topic

Example,

bin/kafka-run-class.sh kafka.tools.UpdateOffsetsInZK earliest config/consumer.properties  page_visits

Group           Topic                          Pid Offset          logSize         Lag             Owner 
pv              page_visits                    0   0               21              21              none 
pv              page_visits                    1   0               19              19              none 
pv              page_visits                    2   0               20              20              none

可以看到offset已经被清0,Lag=logSize

 

更加直接的方式是,直接去Zookeeper里面看

通过zkCli.sh连上后,通过ls查看

Broker Node Registry

/brokers/ids/[0...N] --> host:port (ephemeral node)

Broker Topic Registry

/brokers/topics/[topic]/[0...N] --> nPartions (ephemeral node)

Consumer Id Registry

/consumers/[group_id]/ids/[consumer_id] --> {"topic1": #streams, ..., "topicN": #streams} (ephemeral node)

Consumer Offset Tracking

/consumers/[group_id]/offsets/[topic]/[broker_id-partition_id] --> offset_counter_value ((persistent node)

Partition Owner registry

/consumers/[group_id]/owners/[topic]/[broker_id-partition_id] --> consumer_node_id (ephemeral node)


本文章摘自博客园,原文发布日期: 2014-06-18

目录
相关文章
|
消息中间件 存储 缓存
kafka 的数据是放在磁盘上还是内存上,为什么速度会快?
Kafka的数据存储机制通过将数据同时写入磁盘和内存,确保高吞吐量与持久性。其日志文件按主题和分区组织,使用预写日志(WAL)保证数据持久性,并借助操作系统的页缓存加速读取。Kafka采用顺序I/O、零拷贝技术和批量处理优化性能,支持分区分段以实现并行处理。示例代码展示了如何使用KafkaProducer发送消息。
|
消息中间件 存储 运维
为什么说Kafka还不是完美的实时数据通道
【10月更文挑战第19天】Kafka 虽然作为数据通道被广泛应用,但在实时性、数据一致性、性能及管理方面存在局限。数据延迟受消息堆积和分区再平衡影响;数据一致性难以达到恰好一次;性能瓶颈在于网络和磁盘I/O;管理复杂性涉及集群配置与版本升级。
792 1
|
消息中间件 Java Kafka
Flink-04 Flink Java 3分钟上手 FlinkKafkaConsumer消费Kafka数据 进行计算SingleOutputStreamOperatorDataStreamSource
Flink-04 Flink Java 3分钟上手 FlinkKafkaConsumer消费Kafka数据 进行计算SingleOutputStreamOperatorDataStreamSource
602 1
|
消息中间件 Java Kafka
Kafka不重复消费的终极秘籍!解锁幂等性、偏移量、去重神器,让你的数据流稳如老狗,告别数据混乱时代!
【8月更文挑战第24天】Apache Kafka作为一款领先的分布式流处理平台,凭借其卓越的高吞吐量与低延迟特性,在大数据处理领域中占据重要地位。然而,在利用Kafka进行数据处理时,如何有效避免重复消费成为众多开发者关注的焦点。本文深入探讨了Kafka中可能出现重复消费的原因,并提出了四种实用的解决方案:利用消息偏移量手动控制消费进度;启用幂等性生产者确保消息不被重复发送;在消费者端实施去重机制;以及借助Kafka的事务支持实现精确的一次性处理。通过这些方法,开发者可根据不同的应用场景灵活选择最适合的策略,从而保障数据处理的准确性和一致性。
1810 9
|
消息中间件 存储 关系型数据库
实时计算 Flink版产品使用问题之如何使用Kafka Connector将数据写入到Kafka
实时计算Flink版作为一种强大的流处理和批处理统一的计算框架,广泛应用于各种需要实时数据处理和分析的场景。实时计算Flink版通常结合SQL接口、DataStream API、以及与上下游数据源和存储系统的丰富连接器,提供了一套全面的解决方案,以应对各种实时计算需求。其低延迟、高吞吐、容错性强的特点,使其成为众多企业和组织实时数据处理首选的技术平台。以下是实时计算Flink版的一些典型使用合集。
|
消息中间件 监控 Kafka
实时计算 Flink版产品使用问题之处理Kafka数据顺序时,怎么确保事件的顺序性
实时计算Flink版作为一种强大的流处理和批处理统一的计算框架,广泛应用于各种需要实时数据处理和分析的场景。实时计算Flink版通常结合SQL接口、DataStream API、以及与上下游数据源和存储系统的丰富连接器,提供了一套全面的解决方案,以应对各种实时计算需求。其低延迟、高吞吐、容错性强的特点,使其成为众多企业和组织实时数据处理首选的技术平台。以下是实时计算Flink版的一些典型使用合集。
|
消息中间件 负载均衡 Java
"Kafka核心机制揭秘:深入探索Producer的高效数据发布策略与Java实战应用"
【8月更文挑战第10天】Apache Kafka作为顶级分布式流处理平台,其Producer组件是数据高效发布的引擎。Producer遵循高吞吐、低延迟等设计原则,采用分批发送、异步处理及数据压缩等技术提升性能。它支持按消息键值分区,确保数据有序并实现负载均衡;提供多种确认机制保证可靠性;具备失败重试功能确保消息最终送达。Java示例展示了基本配置与消息发送流程,体现了Producer的强大与灵活性。
435 3
|
消息中间件 存储 Kafka
kafka 在 zookeeper 中保存的数据内容
kafka 在 zookeeper 中保存的数据内容
376 3
|
消息中间件 存储 Kafka
微服务分布问题之Kafka分区的副本和分布如何解决
微服务分布问题之Kafka分区的副本和分布如何解决
302 5
|
消息中间件 负载均衡 Kafka
微服务数据问题之Kafka实现高可用如何解决
微服务数据问题之Kafka实现高可用如何解决
294 1

热门文章

最新文章