Kafka is a high throughput publish-subscribe messaging system implemented as distributed, partitioned, replicated commit log service.
Taken from official Kafka site
Fast
A single Kafka broker can handle hundreds of megabytes of reads and writes per second from thousands of clients.
Scalable
Kafka is designed to allow a single cluster to serve as the central data backbone for a large organization. It can be elastically and transparently expanded without downtime. Data streams are partitioned and spread over a cluster of machines to allow data streams larger than the capability of any single machine and to allow clusters of co-ordinated consumers
Durable
Messages are persisted on disk and replicated within the cluster to prevent data loss. Each broker can handle terabytes of messages without performance impact.
Distributed by Design
Kafka has a modern cluster-centric design that offers strong durability and fault-tolerance guarantees.
Step 1. Install Java 7 or 8
Step 2. Download Apache Kafka at: http://kafka.apache.org/downloads.html
For example, we will try download Apache Kafka 0.10.0.0
Step 3. Extract the compressed file.
On Linux:
tar -xzf kafka_2.11-0.10.0.0.tgz
On Window: Right click --> Extract here
Step 4. Start Zookeeper
cd kafka_2.11-0.10.0.0
Linux:
bin/zookeeper-server-start.sh config/zookeeper.properties
Windows:
bin/windows/zookeeper-server-start.bat config/zookeeper.properties
Step 5. Start Kafka server
Linux:
bin/kafka-server-start.sh config/server.properties
Windows:
bin/windows/kafka-server-start.bat config/server.properties
Apache Kafkaâ„¢ is a distributed streaming platform.
1-It lets you publish and subscribe to streams of records. In this respect it is similar to a message queue or enterprise messaging system.
2-It lets you store streams of records in a fault-tolerant way.
3-It lets you process streams of records as they occur.
1-Building real-time streaming data pipelines that reliably get data between systems or applications
2-Building real-time streaming applications that transform or react to the streams of data
Kafka console scripts are different for Unix-based and Windows platforms. In the examples, you might need to add the extension according to your platform. Linux: scripts located in
bin/
with.sh
extension. Windows: scripts located inbin\windows\
and with.bat
extension.
Step 1: Download the code and untar it:
tar -xzf kafka_2.11-0.10.1.0.tgz
cd kafka_2.11-0.10.1.0
Step 2: start the server.
to be able to delete topics later, open
server.properties
and setdelete.topic.enable
to true.
Kafka relies heavily on zookeeper, so you need to start it first. If you don't have it installed, you can use the convenience script packaged with kafka to get a quick-and-dirty single-node ZooKeeper instance.
zookeeper-server-start config/zookeeper.properties
kafka-server-start config/server.properties
Step 3: ensure everything is running
You should now have zookeeper listening to localhost:2181
and a single kafka broker on localhost:6667
.
We only have one broker, so we create a topic with no replication factor and just one partition:
kafka-topics --zookeeper localhost:2181 \
--create \
--replication-factor 1 \
--partitions 1 \
--topic test-topic
Check your topic:
kafka-topics --zookeeper localhost:2181 --list
test-topic
kafka-topics --zookeeper localhost:2181 --describe --topic test-topic
Topic:test-topic PartitionCount:1 ReplicationFactor:1 Configs:
Topic: test-topic Partition: 0 Leader: 0 Replicas: 0 Isr: 0
Launch a consumer:
kafka-console-consumer --bootstrap-server localhost:9092 --topic test-topic
On another terminal, launch a producer and send some messages. By default, the tool send each line as a separate message to the broker, without special encoding. Write some lines and exit with CTRL+D or CTRL+C:
kafka-console-producer --broker-list localhost:9092 --topic test-topic
a message
another message
^D
The messages should appear in the consumer therminal.
kafka-server-stop
The above examples use only one broker. To setup a real cluster, we just need to start more than one kafka server. They will automatically coordinate themselves.
Step 1: to avoid collision, we create a server.properties
file for each broker and change the id
, port
and logfile
configuration properties.
Copy:
cp config/server.properties config/server-1.properties
cp config/server.properties config/server-2.properties
Edit properties for each file, for example:
vim config/server-1.properties
broker.id=1
listeners=PLAINTEXT://:9093
log.dirs=/usr/local/var/lib/kafka-logs-1
vim config/server-2.properties
broker.id=2
listeners=PLAINTEXT://:9094
log.dirs=/usr/local/var/lib/kafka-logs-2
Step 2: start the three brokers:
kafka-server-start config/server.properties &
kafka-server-start config/server-1.properties &
kafka-server-start config/server-2.properties &
kafka-topics --zookeeper localhost:2181 --create --replication-factor 3 --partitions 1 --topic replicated-topic
kafka-topics --zookeeper localhost:2181 --describe --topic replicated-topic
Topic:replicated-topic PartitionCount:1 ReplicationFactor:3 Configs:
Topic: replicated-topic Partition: 0 Leader: 1 Replicas: 1,2,0 Isr: 1,2,0
This time, there are more information:
Note that the previously created topic is left unchanged.
Publish some message to the new topic:
kafka-console-producer --broker-list localhost:9092 --topic replicated-topic
hello 1
hello 2
^C
Kill the leader (1 in our example). On Linux:
ps aux | grep server-1.properties
kill -9 <PID>
On Windows:
wmic process get processid,caption,commandline | find "java.exe" | find "server-1.properties"
taskkill /pid <PID> /f
See what happened:
kafka-topics --zookeeper localhost:2181 --describe --topic replicated-topic
Topic:replicated-topic PartitionCount:1 ReplicationFactor:3 Configs:
Topic: replicated-topic Partition: 0 Leader: 2 Replicas: 1,2,0 Isr: 2,0
The leadership has switched to broker 2 and "1" in not in-sync anymore. But the messages are still there (use the consumer to check out by yourself).
Delete the two topics using:
kafka-topics --zookeeper localhost:2181 --delete --topic test-topic
kafka-topics --zookeeper localhost:2181 --delete --topic replicated-topic