Skip to main content

The Kafka Series (part 2): single node-single broker cluster installation

In the second part of this series I will describe the steps to install a Kafka single node-single broker cluster on a Linux machine. Here I am referring to the latest Kafka stable version (at the time of writing this post), 0.9.0.1, Scala 2.11.

Prerequisites
The only prerequisite needed is a JDK 7+.

Installation
- Move to the opt folder of your system
   cd /opt
  and then download the binaries of the latest release there:
   wget http://www.us.apache.org/dist/kafka/0.9.0.1/kafka_2.11-0.9.0.1.tgz
- Extract the archive content:
   tar xzf kafka_2.11-0.9.0.1.tgz
- Create the KAFKA_HOME variable:
   echo -e "export KAFKA_HOME=/opt/kafka_2.11-0.9.0.1" >> /root/.bash_profile
- Add the Kafka bin folder to the PATH:
   echo -e "export PATH=$PATH:$KAFKA_HOME/bin" >> /root/.bash_profile
- Reload the bash profile for the user:
   source /root/.bash_profile


Starting the server
 - In order for the Kafka server to work properly you need to start ZooKeeper (https://zookeeper.apache.org/) first. Kafka comes with its own Zookeeper server. So a separate ZooKeeper installation isn't mandatory. Please note that if your default JDK is the IBM one you need to replace the JVM loggc option with the verbosegclog one in the $KAFKA_HOME/bin/zookeeper-server-start.sh script.
- Start the Zookeper server (in the example below I am using the default ZooKeeper's property file):  
   $KAFKA_HOME/bin/zookeeper-server-start.sh $KAFKA_HOME/config/zookeeper.properties
- If your default JDK is the IBM one you have to replace the JVM loggc option with the verbosegclog one in the $KAFKA_HOME/bin/kafka-server-start.sh script as well.
- Start the Kafka server broker (in the example below I am using the default Kafka broker's property file):
   $KAFKA_HOME/bin/kafka-server-start.sh $KAFKA_HOME/config/server.properties

Testing the installation
And now the steps to test that everything is working properly.
- Create a topic:    
   $KAFKA_HOME/bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic kafkatesting
- Check that the new topic is in the topic list:
   $KAFKA_HOME/bin/kafka-topics.sh --list --zookeeper localhost:2181
- Run a producer for the new topic using the provided script:
   $KAFKA_HOME/bin/kafka-console-producer.sh --broker-list localhost:9092 --topic kafkatesting
  and then type from the shell few messages for that topic to be sent to the server.
- From a different shell run a consumer for the new topic using the provided script:
   $KAFKA_HOME/bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic kafkatesting --from-beginning
  You should see the messages generated by the producer printed out to the consumer shell. 
   
What's next?
In Part 3 of this series you will learn how to implement a producer using the Kafka Java APIs.

Comments

Popular posts from this blog

Exporting InfluxDB data to a CVS file

Sometimes you would need to export a sample of the data from an InfluxDB table to a CSV file (for example to allow a data scientist to do some offline analysis using a tool like Jupyter, Zeppelin or Spark Notebook). It is possible to perform this operation through the influx command line client. This is the general syntax: sudo /usr/bin/influx -database '<database_name>' -host '<hostname>' -username '<username>'  -password '<password>' -execute 'select_statement' -format '<format>' > <file_path>/<file_name>.csv where the format could be csv , json or column . Example: sudo /usr/bin/influx -database 'telegraf' -host 'localhost' -username 'admin'  -password '123456789' -execute 'select * from mem' -format 'csv' > /home/googlielmo/influxdb-export/mem-export.csv

Using Rapids cuDF in a Colab notebook

During last Spark+AI Summit Europe 2019 I had a chance to attend a talk from Miguel Martinez  who was presenting Rapids , the new Open Source framework from NVIDIA for GPU accelerated end-to-end Data Science and Analytics. Fig. 1 - Overview of the Rapids eco-system Rapids is a suite of Open Source libraries: cuDF cuML cuGraph cuXFilter I enjoied the presentation and liked the idea of this initiative, so I wanted to start playing with the Rapids libraries in Python on Colab , starting from cuDF, but the first attempt came with an issue that I eventually solved. So in this post I am going to share how I fixed it, with the hope it would be useful to someone else running into the same blocker. I am assuming here you are already familiar with Google Colab. I am using Python 3.x as Python 2 isn't supported by Rapids. Once you have created a new notebook in Colab, you need to check if the runtime for it is set to use Python 3 and uses a GPU as hardware accelerator. You

Load testing MongoDB using JMeter

Apache JMeter ( http://jmeter.apache.org/ ) added support for MongoDB since its 2.10 release. In this post I am referring to the latest JMeter release (2.13). A preliminary JMeter setup is needed before starting your first test plan for MongoDB. It uses Groovy as scripting reference language, so Groovy needs to be set up for our favorite load testing tool. Follow these steps to complete the set up: Download Groovy from the official website ( http://www.groovy-lang.org/download.html ). In this post I am referring to the Groovy release 2.4.4, but using later versions is fine. Copy the groovy-all-2.4.4.jar to the $JMETER_HOME/lib folder. Restart JMeter if it was running while adding the Groovy JAR file. Now you can start creating a test plan for MongoDB load testing. From the UI select the MongoDB template ( File -> Templates... ). The new test plan has a MongoDB Source Config element. Here you have to setup the connection details for the database to be tested: The Threa