Skip to content

Latest commit

 

History

History
58 lines (51 loc) · 3.04 KB

README.md

File metadata and controls

58 lines (51 loc) · 3.04 KB
Raw

flink-kafka-stream

Trying a flink streaming job

Pre-requisites

  1. Install jdk 8
  2. Download and unzip Kafka 2.4 and run the following commands after cd to the kafka install directory
    bin/zookeeper-server-start.sh config/zookeeper.properties
    bin/kafka-server-start.sh config/server.properties
  1. Create 2 topics in Kafka using the following commands
    bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 1 --partitions 6 --topic raw
    bin/kafka-topics.sh --create --bootstrap-server localhost:9092 --replication-factor 1 --partitions 6 --topic valid
    bin/kafka-topics.sh --list --bootstrap-server localhost:9092 //This is to see that the topics have been created
    
    //Use the following command to delete a topic bin/kafka-topics.sh --zookeeper localhost:2181 --delete --topic raw
    
    //User the following command to get the current offset for a topic
    bin/kafka-run-class.sh kafka.tools.GetOffsetShell --broker-list localhost:9092 --topic raw
  1. Download and unzip flink 1.13.1

Running the code

  1. Clone this repo and cd to the cloned folder
  2. Run mvn clean package
  3. cd to the extracted flink folder and execute the following commands. The flink console can be accessed once the flink cluster is started.
    ./bin/start-cluster.sh
    ./bin/flink run /pathtotheclonedfolder/target/flink-kafka-stream-1.0-SNAPSHOT.jar
  1. Add messages to the raw topic by issuing the following commands after cd to the kafka install directory
bin/kafka-console-producer.sh --broker-list localhost:9092 --topic raw
Add the following text as input ABCD
  1. Use a console consumer on the valid topic to see the messages that have been processed by the streaming job.
bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic valid --from-beginning

Understanding the source code

BaseStreaming has the simple boilerplate code for the Kafka serializer and de-serializer.
StreamingJob has the simple boilerplate code for a flink job. CaseHandlerProcessFunction is a simple process function that splits the incoming data by space and to lowercase application.conf has the input and output topic names that can be configured. It defaults to raw (input topic) and valid (output topic) along with other configuration

Benchmarking the code on your workstation

  1. Insert messages into the raw topic using the below command. The below command would insert 10 mil messages of 100 chars to the raw topic
bin/kafka-producer-perf-test.sh --topic raw --num-records 10000000 --record-size 100 --throughput 5000000 --producer-props bootstrap.servers=localhost:9092
  1. Execute the program so that it starts streaming from raw to valid.
  2. You can look at the lag for the consumer group (stream1 by default, can be changed in application.properties) of the valid topic every 10 seconds (using watch command) by executing the following command
   bin/kafka-consumer-groups.sh --bootstrap-server localhost:9092 --describe --group stream1