Console Producer and Consumer Basics

Question:

What is the simplest way to write messages to and read messages from Kafka?

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Example use case:

So you are excited to get started with Kafka, and you'd like to produce and consume some basic messages, quickly. In this tutorial, we'll show you how to produce and consume messages from the command line without any code.

Hands-on code example:

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Short Answer

With Confluent Cloud, you can use the Confluent CLI to produce and consume messages.

Producer:

confluent kafka topic produce orders --parse-key --delimiter ":"

Consumer:

confluent kafka topic consume orders --print-key --delimiter "-" --from-beginning

Run it

Provision your Kafka cluster

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This tutorial requires access to an Apache Kafka cluster, and the quickest way to get started free is on Confluent Cloud, which provides Kafka as a fully managed service.

Take me to Confluent Cloud
  1. After you log in to Confluent Cloud, click on Add cloud environment and name the environment learn-kafka. Using a new environment keeps your learning resources separate from your other Confluent Cloud resources.

  2. From the Billing & payment section in the Menu, apply the promo code CC100KTS to receive an additional $100 free usage on Confluent Cloud (details).

  3. Click on LEARN and follow the instructions to launch a Kafka cluster and to enable Schema Registry.

Confluent Cloud

Download and setup the Confluent CLI

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This tutorial has some steps for Kafka topic management and/or reading from or writing to Kafka topics, for which you can use the Confluent Cloud Console or install the Confluent CLI. Instructions for installing Confluent CLI and configuring it to your Confluent Cloud environment is available from within the Confluent Cloud Console: navigate to your Kafka cluster, click on the CLI and tools link, and run through the steps in the Confluent CLI tab.

Create the Kafka topic

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Create a Kafka topic called orders in Confluent Cloud.

confluent kafka topic create orders --partitions 1

This should yield the following output:

Created topic "orders".

Start a console consumer

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Next, let’s open up a consumer to read records.

confluent kafka topic consume orders

Produce events to the Kafka topic

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Now we are going to produce records to our new topic.

confluent kafka topic produce orders

Then enter these records either one at time or copy-paste all of them into the terminal and hit enter:

{"number":1,"date":18500,"shipping_address":"ABC Sesame Street,Wichita, KS. 12345","subtotal":110.00,"tax":10.00,"grand_total":120.00,"shipping_cost":0.00}
{"number":2,"date":18501,"shipping_address":"123 Cross Street,Irving, CA. 12345","subtotal":5.00,"tax":0.53,"grand_total":6.53,"shipping_cost":1.00}
{"number":3,"date":18502,"shipping_address":"5014  Pinnickinick Street, Portland, WA. 97205","subtotal":93.45,"tax":9.34,"grand_total":102.79,"shipping_cost":0.00}
{"number":4,"date":18503,"shipping_address":"4082 Elmwood Avenue, Tempe, AX. 85281","subtotal":50.00,"tax":1.00,"grand_total":51.00,"shipping_cost":0.00}
{"number":5,"date":18504,"shipping_address":"123 Cross Street,Irving, CA. 12345","subtotal":33.00,"tax":3.33,"grand_total":38.33,"shipping_cost":2.00}

Produce records with full key-value pairs

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Kafka works with key-value pairs, but so far you’ve only sent records with values only. Well to be fair you’ve sent key-value pairs, but the keys are null. Sometimes you’ll need to send a valid key in addition to the value from the command line.

To enable sending full key-value pairs from the command line you add two properties to your Confluent CLI, parse-key and delimiter

Let’s try to send some full key-value records now. If your previous console producer is still running close it with a CTRL+C and run the following command to start a new console producer:

confluent kafka topic produce orders --parse-key --delimiter ":"

Then enter these records either one at time or copy-paste all of them into the terminal and hit enter. In the output below, the 6 and 7 are the keys, separated from the values by the : delimiter.

6:{"number":6,"date":18505,"shipping_address":"9182 Shipyard Drive, Raleigh, NC. 27609","subtotal":72.00,"tax":3.00,"grand_total":75.00,"shipping_cost":0.00}
7:{"number":7,"date":18506,"shipping_address":"644 Lagon Street, Chicago, IL. 07712","subtotal":11.00,"tax":1.00,"grand_total":14.00,"shipping_cost":2.00}

Start a consumer to show full key-value pairs

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Next, let’s open up a consumer to read the new records.

confluent kafka topic consume orders --print-key --delimiter "-" --from-beginning

After the consumer starts you should see the following output in a few seconds:

null-{"number":1,"date":18500,"shipping_address":"ABC Sesame Street,Wichita, KS. 12345","subtotal":110.00,"tax":10.00,"grand_total":120.00,"shipping_cost":0.00}
null-{"number":2,"date":18501,"shipping_address":"123 Cross Street,Irving, CA. 12345","subtotal":5.00,"tax":0.53,"grand_total":6.53,"shipping_cost":1.00}
null-{"number":3,"date":18502,"shipping_address":"5014  Pinnickinick Street, Portland, WA. 97205","subtotal":93.45,"tax":9.34,"grand_total":102.79,"shipping_cost":0.00}
null-{"number":4,"date":18503,"shipping_address":"4082 Elmwood Avenue, Tempe, AX. 85281","subtotal":50.00,"tax":1.00,"grand_total":51.00,"shipping_cost":0.00}
null-{"number":5,"date":18504,"shipping_address":"123 Cross Street,Irving, CA. 12345","subtotal":33.00,"tax":3.33,"grand_total":38.33,"shipping_cost":2.00}
6-{"number":6,"date":18505,"shipping_address":"9182 Shipyard Drive, Raleigh, NC. 27609","subtotal":72.00,"tax":3.00,"grand_total":75.00,"shipping_cost":0.00}
7-{"number":7,"date":18506,"shipping_address":"644 Lagon Street, Chicago, IL. 07712","subtotal":11.00,"tax":1.00,"grand_total":14.00,"shipping_cost":2.00}

Since we kept the --from-beginning property, you’ll see all the records sent to the topic. You’ll notice the results before you sent keys are formatted as null-<value>.

Teardown Confluent Cloud resources

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You may try another tutorial, but if you don’t plan on doing other tutorials, use the Confluent Cloud Console or CLI to destroy all of the resources you created. Verify they are destroyed to avoid unexpected charges.