Confluent Platform Quick Start (Local)

This quick start shows you how to get up and running with Confluent Platform and its main components. This quick start demonstrates both the basic and most powerful capabilities of Confluent Platform, including using Control Center for topic management and event stream processing using KSQL. In this quick start you create Kafka topics, use Kafka Connect to generate mock data to those topics, and create KSQL streaming queries on those topics. You 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.

Important

Java 1.8 is supported in this version of Confluent Platform (Java 1.9 and 1.10 are currently not supported). You should run with the Garbage-First (G1) garbage collector. For more information, see the Supported Versions and Interoperability.

Prerequisites
  • Internet connectivity

Step 1: Download and Start Confluent Platform

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

    Tip

    Download a previous version from Previous Versions.

  2. Provide your name and email if applicable for the version 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. Add the install location of the Confluent bin directory to your PATH: export PATH=<path-to-confluent>/bin:$PATH

  5. Install the Kafka Connect Datagen source connector using the Confluent Hub client. This connector generates mock data for demonstration purposes and is not suitable for production. Confluent Hub is an online library of pre-packaged and ready-to-install extensions or add-ons for Confluent Platform and Apache Kafka.

    <path-to-confluent>/bin/confluent-hub install \
    --no-prompt confluentinc/kafka-connect-datagen:0.1.0
    
  6. Start Confluent Platform using the Confluent CLI start command.

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

    This command starts all of the Confluent Platform components; including Kafka, ZooKeeper, Schema Registry, HTTP REST Proxy for Apache Kafka, Kafka Connect, KSQL, and Control Center.

    Important

    The Confluent CLI is meant for development purposes only and is not suitable for a production environment. The data that are produced are transient and are intended to be temporary.

    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, you create Kafka topics by using the Confluent Control Center. Confluent Control Center provides the functionality for building and monitoring production data pipelines and event streaming applications.

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

    Important

    It may take a minute or two for Control Center to come online.

    ../_images/c3-landing-page.png
  2. Select Management -> Topics and click Create topic.

    ../_images/c3-create-topic.png
  3. Create a topic named pageviews and click Create with defaults.

    ../_images/c3-create-topic-name.png
  4. Select Management -> Topics, create a topic named users, and click Create with defaults.

    ../_images/c3-create-topic-name-2.png

Step 3: Install a Kafka Connector and Generate Sample Data

In this step, you use Kafka Connect to run a demo source connector called kafka-connect-datagen that creates sample data for the Kafka topics pageviews and users.

Tip

The Kafka Connect Datagen connector was installed manually in Step 1: Download and Start Confluent Platform.

  1. Run one instance of the Kafka Connect Datagen connector to produce Kafka data to the pageviews topic in AVRO format.

    1. From the Control Center navigation menu, click Management -> Kafka Connect.

    2. Click Add connector.

      ../_images/connect-page-gui-11.png
    3. Scroll down to select DatagenConnector from the Connector class list.

      ../_images/connect-page-new-source1.png
    4. Name the connector datagen-pageviews. After naming the connector, new fields appear. Scroll down and specify the following configuration values:

      • In the Key converter class field, type org.apache.kafka.connect.storage.StringConverter.
      • In the kafka.topic field, type pageviews.
      • In the max.interval field, type 100.
      • In the iterations field, type 1000000000.
      • In the quickstart field, type pageviews.
      ../_images/connect-configure-pageviews.png
    5. Click Continue.

    6. Review the connector configuration and click Launch.

      ../_images/connect-review-pageviews1.png
  2. Run another instance of the Kafka Connect Datagen connector to produce Kafka data to the users topic in AVRO format.

    1. Click Add connector.

      ../_images/connect-page-gui.png
    2. Scroll down to select DatagenConnector from the Connector class list.

      ../_images/connect-page-new-source1.png
    3. Name the connector datagen-users. After naming the connector, new fields appear. Scroll down and specify the following configuration values:

      • In the Key converter class field, type org.apache.kafka.connect.storage.StringConverter.
      • In the kafka.topic field, type users.
      • In the max.interval field, type 1000.
      • In the iterations field, type 1000000000.
      • In the quickstart field, type users.
      ../_images/connect-configure-users.png
    4. Click Continue.

    5. Review the connector configuration and click Launch.

      ../_images/connect-review-users.png

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.

Tip

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 navigation menu, click Development -> KSQL. By default, you are on the KSQL EDITOR page.

    ../_images/ksql-interface-create-stream2.png
  2. Click the STREAMS tab -> Add a Stream and select the pageviews topic.

    ../_images/c3-ksql-create-stream-pageview.png
  3. Choose your stream options:

    • In the How are your messages encoded? field, select AVRO.
    • In the Field(s) you'd like to include in your STREAM field, ensure fields are set as follows:
      • viewtime with type BIGINT
      • userid with type VARCHAR
      • pageid with type VARCHAR
    ../_images/c3-ksql-create-stream-pageview-2.png
  4. Click Save STREAM.

  5. Click the TABLES tab -> Add a Table and select the users topic.

    ../_images/c3-ksql-create-stream-users.png
  6. Choose your table options:

    • In the How are your messages encoded? field, select AVRO.
    • In the Key field, select userid.
    • In the Field(s) you'd like to include in your TABLE field, set fields as follows:
      • registertime with type BIGINT
      • userid with type VARCHAR
      • regionid with type VARCHAR
      • gender with type VARCHAR
      • interests with type ARRAY<VARCHAR>
      • contact_info with type MAP<VARCHAR, VARCHAR>
    ../_images/c3-ksql-create-table-users.png
  7. Click Save TABLE.

Write Queries

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

  1. From the Control Center navigation menu, click Development -> KSQL. By default, you are on the KSQL EDITOR page. Click Query properties to add a custom query property. Set the auto.offset.reset parameter to earliest.

    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.

    ../_images/c3-ksql-query-properties.png
  2. 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 LIMIT 3;
      

      Your output should resemble:

      ../_images/c3-ksql-query-results-pageid.png
    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';
      

      Your output should resemble:

      ../_images/c3-ksql-persist-query-pv-female-results.png
    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='AVRO') AS SELECT * FROM pageviews_female WHERE regionid LIKE '%_8' OR regionid LIKE '%_9';
      

      Your output should resemble:

      ../_images/c3-ksql-persist-query-pv-female89-results.png
    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 output should resemble:

      ../_images/c3-ksql-persist-query-table-results.png
    5. Click RUNNING QUERIES and you should see the following persisted queries:

      ../_images/c3-ksql-persistent-query.png

Step 5: View Your Stream in Control Center

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.

Tip

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

../_images/c3-monitor-ksql1.png

Now that your streams are running you can monitor them.

  • View the consumers that have been created by KSQL

    Click the CONSUMER GROUPS tab and then View Details for the _confluent-ksql-default_query_CSAS_PAGEVIEWS_FEMALE_0 consumer group.

    ../_images/ksql-interface-monitor-cnsmgp.png

    This graph shows the messages being consumed by the stream query.

    ../_images/ksql-interface-monitor-pgvw-f.png

Step 6: Stop Confluent Platform

When you are done working with the local install, you can stop Confluent Platform.

  1. Stop Confluent Platform using the Confluent CLI stop command.

    <path-to-confluent>/bin/confluent stop
    
  2. Destroy the Confluent Platform instance with the destroy command.

    <path-to-confluent>/bin/confluent destroy
    

Next Steps

Learn more about the components shown in this quick start: