vtlim commented on code in PR #13261:
URL: https://github.com/apache/druid/pull/13261#discussion_r1017251702


##########
docs/tutorials/tutorial-kafka.md:
##########
@@ -24,260 +24,267 @@ sidebar_label: "Load from Apache Kafka"
   -->
 
 
-## Getting started
+This tutorial shows you how to load data into Apache Druid from a Kafka 
stream, using Druid's Kafka indexing service. 
 
-This tutorial demonstrates how to load data into Apache Druid from a Kafka 
stream, using Druid's Kafka indexing service.
+The tutorial guides you through the steps to load sample nested clickstream 
data from the [Koalas to the Max](https://www.koalastothemax.com/) game into a 
Kafka topic, then ingest the data into Druid.
 
-For this tutorial, we'll assume you've already downloaded Druid as described in
-the [quickstart](index.md) using the `micro-quickstart` single-machine 
configuration and have it
-running on your local machine. You don't need to have loaded any data yet.
+## Prerequisites
+
+Before you follow the steps in this tutorial, download Druid as described in 
the [quickstart](index.md) using the 
[micro-quickstart](../operations/single-server.md#micro-quickstart-4-cpu-16gib-ram)
 single-machine configuration and have it running on your local machine. You 
don't need to have loaded any data.
 
 ## Download and start Kafka
 
-[Apache Kafka](http://kafka.apache.org/) is a high throughput message bus that 
works well with
-Druid.  For this tutorial, we will use Kafka 2.7.0. To download Kafka, issue 
the following
-commands in your terminal:
+[Apache Kafka](http://kafka.apache.org/) is a high-throughput message bus that 
works well with Druid. For this tutorial, use Kafka 2.7.0. 
+
+1. To download Kafka, run the following commands in your terminal:
 
-```bash
-curl -O https://archive.apache.org/dist/kafka/2.7.0/kafka_2.13-2.7.0.tgz
-tar -xzf kafka_2.13-2.7.0.tgz
-cd kafka_2.13-2.7.0
-```
-Start zookeeper first with the following command:
+   ```bash
+   curl -O https://archive.apache.org/dist/kafka/2.7.0/kafka_2.13-2.7.0.tgz
+   tar -xzf kafka_2.13-2.7.0.tgz
+   cd kafka_2.13-2.7.0
+   ```
+2. If you're already running Kafka on the machine you're using for this 
tutorial, delete or rename the `kafka-logs` directory in `/tmp`.
+   
+   > Druid and Kafka both rely on [Apache 
ZooKeeper](https://zookeeper.apache.org/) to coordinate and manage services. 
Because Druid is already running, Kafka attaches to the Druid ZooKeeper 
instance when it starts up.<br>
+   In a production environment where you're running Druid and Kafka on 
different machines, [start the Kafka 
ZooKeeper](https://kafka.apache.org/quickstart) before you start the Kafka 
broker.
 
-```bash
-./bin/zookeeper-server-start.sh config/zookeeper.properties
-```
+3. In the Kafka root directory, run this command to start a Kafka broker:
 
-Start a Kafka broker by running the following command in a new terminal:
+   ```bash
+   ./bin/kafka-server-start.sh config/server.properties
+   ```
 
-```bash
-./bin/kafka-server-start.sh config/server.properties
-```
+4. In a new terminal window, navigate to the Kafka root directory and run the 
following command to create a Kafka topic called `kttm`:
 
-Run this command to create a Kafka topic called *wikipedia*, to which we'll 
send data:
+   ```bash
+   ./bin/kafka-topics.sh --create --topic kttm --bootstrap-server 
localhost:9092
+   ```
 
-```bash
-./bin/kafka-topics.sh --create --topic wikipedia --bootstrap-server 
localhost:9092
-```     
+   Kafka returns a message when it successfully adds the topic: `Created topic 
kttm`.
 
 ## Load data into Kafka
 
-Let's launch a producer for our topic and send some data!
+In this section, you download sample data to the tutorial's directory and send 
the data to your Kafka topic.
 
-In your Druid directory, run the following command:
+1. Run the following commands from your Druid root directory to download and 
extract the sample spec:

Review Comment:
   Is there a reason this needs to be done from the Druid root directory? It 
also requires the next step to have `{PATH_TO_DRUID}` but you can post events 
regardless of the data location.



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