Confluent Platform Enterprise Quick Start

This quick start shows you how to get up and running with Confluent Platform Enterprise and its main components. This quick start will show you the basic and most powerful capabilities of Confluent Platform Enterprise, including using Control Center for topic management and stream processing by using KSQL. In this quick start you will create Kafka topics and streaming queries on these topics by using KSQL. You will then go to Control Center to monitor and analyze the streaming queries!

You can also run an automated version of this quick start designed for Confluent Platform local installs.


Java 1.7 and 1.8 are supported in this version of Confluent Platform (Java 1.9 is currently not supported). For more information, see the Supported Versions and Interoperability.

Step 1: Download and Start Confluent Platform

  1. Go to the downloads page and choose Confluent Platform Enterprise.

  2. Provide your name and email and select Download.

  3. Decompress the file. You should have these directories:

    Folder Description
    /bin/ Driver scripts for starting and stopping services
    /etc/ Configuration files
    /lib/ Systemd services
    /logs/ Log files
    /share/ Jars and licenses
    /src/ Source files that require a platform-dependent build
  4. Start Confluent Platform using the Confluent CLI. This command will start all of the Confluent Platform components, including Kafka, ZooKeeper, Schema Registry, HTTP REST Proxy for Apache Kafka, Kafka Connect, KSQL, and Control Center.


    You can add the bin directory to your PATH by running: export PATH=<path-to-confluent>/bin:$PATH.

    $ <path-to-confluent>/bin/confluent start

    Your output should resemble:

    Starting zookeeper
    zookeeper is [UP]
    Starting kafka
    kafka is [UP]
    Starting schema-registry
    schema-registry is [UP]
    Starting kafka-rest
    kafka-rest is [UP]
    Starting connect
    connect is [UP]
    Starting ksql-server
    ksql-server is [UP]
    Starting control-center
    control-center is [UP]

Step 2: Create Kafka Topics

In this step Kafka topics are created by using the Confluent Control Center. Confluent Control Center provides the functionality for building and monitoring production data pipelines and streaming applications.

  1. Navigate to the Control Center web interface at http://localhost:9021/.

  2. Select Management -> Topics and click Create on the upper-right corner.

  3. Create a topic named pageviews and click Create with defaults.

  4. Create a topic named users and click Create with defaults.


Step 3: Create Sample Data

In this step you create sample data for the Kafka topics pageviews and users by using the ksql-datagen. This datagen is included with the Confluent Platform installation.


The datagen runs as a long-running process in your terminal. Run each datagen step in a separate terminal.

  1. Produce Kafka data to the pageviews topic using the data generator. The following example continuously generates data with a value in DELIMITED format.

    $ <path-to-confluent>/bin/ksql-datagen quickstart=pageviews format=delimited topic=pageviews maxInterval=100 \
  2. Produce Kafka data to the users topic using the data generator. The following example continuously generates data with a value in JSON format.

    $ <path-to-confluent>/bin/ksql-datagen quickstart=users format=json topic=users maxInterval=1000 \

Step 4: Create and Write to a Stream and Table using KSQL

In this step, KSQL queries are run on the pageviews and users topics that were created in the previous step. The KSQL commands are run using the KSQL tab in Control Center.


You can also run these commands using the KSQL CLI from your terminal with this command: <path-to-confluent>/bin/ksql http://localhost:8088.

Create Streams and Tables

In this step, KSQL is used to create streams and tables for the pageviews and users topics.

  1. From the Control Center interface, click Management -> KSQL.

  2. Click Create a stream and select the pageviews topic.

  3. Choose your stream options and click Save STREAM & query.

    • In the How are your message values encoded? field, select DELIMITED.
    • In the Field(s) you’d like to include in your STREAM field, add additional fields for:
      • viewtime with type BIGINT
      • userid with type VARCHAR
      • pageid with type VARCHAR
  4. Click the TABLES tab and Create a table and then select the userid topic.

  5. Choose your table options and click Save TABLE & query.

    • In the How are your message values encoded? field, select JSON.
    • In the Field(s) you’d like to include in your TABLE field, add additional fields for:
      • registertime with type BIGINT
      • gender with type VARCHAR
      • regionid with type VARCHAR
      • userid with type VARCHAR
      • interests with type ARRAY<VARCHAR>
      • contact_info with type MAP<VARCHAR, VARCHAR>
    • In the Select a key field, select userid.

Write Queries

These examples write queries using the KSQL tab in Control Center.

  1. Add the custom query property earliest for the auto.offset.reset parameter. This instructs KSQL queries to read all available topic data from the beginning. This configuration is used for each subsequent query. For more information, see the KSQL Configuration Parameter Reference.

  2. Click KSQL > QUERY EDITOR run the following queries.

    1. Create a query that returns data from a stream with the results limited to three rows.

      SELECT pageid FROM pageviews;
    2. Create a persistent query that filters for female users. The results from this query are written to the Kafka PAGEVIEWS_FEMALE topic. This query enriches the pageviews STREAM by doing a LEFT JOIN with the users TABLE on the user ID, where a condition (gender = 'FEMALE') is met.

      CREATE STREAM pageviews_female AS SELECT users.userid AS userid, pageid, regionid, gender FROM pageviews LEFT JOIN users ON pageviews.userid = users.userid WHERE gender = 'FEMALE';
    3. Create a persistent query where a condition (regionid) is met, using LIKE. Results from this query are written to a Kafka topic named pageviews_enriched_r8_r9.

      CREATE STREAM pageviews_female_like_89 WITH (kafka_topic='pageviews_enriched_r8_r9', value_format='DELIMITED') AS SELECT * FROM pageviews_female WHERE regionid LIKE '%_8' OR regionid LIKE '%_9';
    4. Create a persistent query that counts the pageviews for each region and gender combination in a tumbling window of 30 seconds when the count is greater than 1. Because the procedure is grouping and counting, the result is now a table, rather than a stream. Results from this query are written to a Kafka topic called PAGEVIEWS_REGIONS.

      CREATE TABLE pageviews_regions AS SELECT gender, regionid , COUNT(*) AS numusers FROM pageviews_female WINDOW TUMBLING (size 30 second) GROUP BY gender, regionid HAVING COUNT(*) > 1;

    Your list of persistent queries should look like this.


Step 5: Monitor Your Query Performance

From the Control Center interface you can view all of your streaming KSQL queries.

Navigate to the Control Center web interface Monitoring -> Data streams tab at http://localhost:9021/monitoring/streams. The monitoring page shows the total number of messages produced and consumed on the cluster. You can scroll down to see more details on the consumer groups for your queries.


Depending on your machine, these charts may take a few minutes to populate and you might need to refresh your browser.


Now that your streams are running you can monitor them.

  • View the consumers that have been created by KSQL

    Click the View Details button for the ksql_query_CSAS_PAGEVIEWS_FEMALE_LIKE_89 stream. This graph shows the messages being consumed by the stream query.


For more information about Control Center, see Confluent Control Center.

Next Steps

Learn more about the components shown in this quick start: