paint-brush
Build a Live Dashboard with Materialize, Airbyte, MySQL and Redpanda/Kafkaby@bobbyiliev
714 reads
714 reads

Build a Live Dashboard with Materialize, Airbyte, MySQL and Redpanda/Kafka

by Bobby IlievApril 11th, 2022
Read on Terminal Reader
Read this story w/o Javascript
tldt arrow

Too Long; Didn't Read

This is a self-contained demo using [Materialize]. This is an extension of the [How to join Postgres and Postgres in a live Materialized view] demo. The demo would show you how to use Materialize with Airbyte to create a live dashboard. For this demo, we are going to use Redpanda to monitor the orders on our demo website and generate events that could, later on, be used to send notifications when a cart has been abandoned for a long time.

Companies Mentioned

Mention Thumbnail
Mention Thumbnail
featured image - Build a Live Dashboard with Materialize, Airbyte, MySQL and Redpanda/Kafka
Bobby Iliev HackerNoon profile picture

This is a self-contained demo using Materialize.

This demo would show you how to use Materialize with Airbyte to create a live dashboard.

For this demo, we are going to monitor the orders on our demo website and generate events that could, later on, be used to send notifications when a cart has been abandoned for a long time.

This demo is an extension of the How to join PostgreSQL and MySQL in a live Materialized view tutorial but rather than using Debezium CDC, we are going to use Airbyte to incrementally extract the orders from MySQL over CDC.

Diagram:

Prerequisites

Before you get started, you need to make sure that you have Docker and Docker Compose installed.

You can follow the steps here on how to install Docker:

Installing Docker

Note that Airbyte Cloud currently does not support Kafka as a destination, this is why we can only follow this demo with a self-hosted Airbyte instance.

Running the Demo

Note that for Mac with M1, you might have some issues with the Airbyte due to the following issue:

https://github.com/airbytehq/airbyte/issues/2017

So I would recommend using an Ubuntu VM to run the demo.

export DOCKER_BUILD_PLATFORM=linux/arm64 
export DOCKER_BUILD_ARCH=arm64 
export ALPINE_IMAGE=arm64v8/alpine:3.14 
export POSTGRES_IMAGE=arm64v8/postgres:13-alpine 
export JDK_VERSION=17

Start all services:

```bash
docker-compose up -d

Airbyte

Setup the Airbyte service by visiting your_server_ip:8000 and then follow the instructions.

Adding a source

We are going to use MySQL as our source where we will be extracting the orders from.

Via the Airbyte UI, click on the Sources tab and click on the Add new source button.

Fill in the following details:

  • Name: orders
  • Source type: MySQL
  • Host: your_server_ip
  • Port: 3306
  • Database: shop
  • Username: airbyte
  • Password: password
  • Disable SSL
  • Replication Method: CDC

Finally, click on the Setup source button.

Adding a destination

Next, add a destination to Airbyte which will be used to send the events to.

For this demo, we are going to use Redpanda but it will work just fine with Kafka.

Start by clicking on the Destinations tab and click on the Add new destination button and fill in the following details:

  • Name: redpanda
  • Destination type: Kafka

Next, fill up all of the required fields and click on the Setup destination button.

Depending on your needs you might want to change some of the settings, but for this demo, we are going to use the defaults.

The important things to note down for this demo are:

  • The Topic is orders
  • The Bootstrap Servers is redpanda:9092

Finally, click on the Save button.

Set up a connection

Now that you have a source and a destination, you need to set up a connection between them. This is needed so that Airbyte can send the events from the source to the destination based on a specific schedule like every day, every hour, every 5 minutes, etc.

For this demo, we are going to use a 5-minute schedule. Hopefully, in the future, Airbyte will allow you to customize this and reduce the schedule to 1 minute for example.

Click on the Connections tab and click on the Add new connection button and fill in the following details:

  • Set the 'Replication frequency' to 5 minutes
  • Set the 'Destination Namespace' to 'Mirror source structure'
  • Set the source to orders and the 'Sync mode' to Incremental

<img width="984" alt="image" src="https://user-images.githubusercontent.com/21223421/158997265-6890282a-a997-495e-b723-265818c8ed24.png">

Next click on the 'Setup connection' button. And finally, click on the Sync now button to start the synchronization.

It might take a few minutes for the connection to be established and the events to be sent.

After the synchronization is done, you can see the events in the Redpanda topic that you have specified when you set up the destination. Let's take a look at how to do that!

Check the Redpanda topic

To check the auto-generated topic, you can run the following commands:

  • Access the Redpanda container:
docker-compose exec redpanda bash
  • List the topics:
rpk topic list
  • Consume the topic:
rpk topic consume orders_topic

Note that if you've used a different topic name during the initial setup, you need to change it in the commands above.

If you don't see the topic yet, it would be possible that you might have to wait a few extra minutes and also make sure that the ordergen service mock is up and running.

Once you've verified that the topic has the CDC events, you can proceed and set up Materialize.

Create a Materialize SOURCE

Next, we need to create a SOURCE in Materialize.

You can do that by heading back to your terminal and running the following commands:

  • Access the mzcli container:
docker-compose run mzcli

Or if you have psql installed:

psql -U materialize -h localhost -p 6875 materialize

Create a Kafka SOURCE by executing the following statement:

CREATE SOURCE airbyte_source
  FROM KAFKA BROKER 'redpanda:9092' TOPIC 'orders_topic'
  FORMAT BYTES;

Note: change orders_topic to the topic you've specified during the Airbyte setup.

Use TAIL to quickly see the data:

COPY (
    TAIL (
        SELECT
            CAST(data->>'_airbyte_data' AS JSON) AS data
        FROM (
            SELECT CAST(data AS jsonb) AS data
                FROM (
                    SELECT * FROM (
                        SELECT convert_from(data, 'utf8') AS data FROM airbyte_source
                    )
                )
            )
        )
    )
TO STDOUT;

You will see a stream of your data as Airbyte sends it to the destination and Materialize processes it with a very minimal, submillisecond delay.

For more information on how to use TAIL, check out this blog post by Joaquin Colacci: Subscribe to changes in a view with TAIL in Materialize

Create a Materialized View

Now that we have a SOURCE in Materialize, we can create a materialized VIEW. A materialized view, lets you retrieve incrementally updated results of your data using standard SQL queries very quickly.

To create a materialized view execute the following statement:

CREATE MATERIALIZED VIEW airbyte_view AS
  SELECT
    data->>'id' AS id,
    data->>'user_id' AS user_id,
    data->>'order_status' AS order_status,
    data->>'price' AS price,
    data->>'created_at' AS created_at,
    data->>'updated_at' AS updated_at
    FROM (
        SELECT
            CAST(data->>'_airbyte_data' AS JSON) AS data
        FROM (
            SELECT CAST(data AS jsonb) AS data
            FROM (
                SELECT * FROM (
                    SELECT convert_from(data, 'utf8') AS data FROM airbyte_source
                )
            )
        )
    );

Next, run a query to see the data:

SELECT * FROM airbyte_view;

To visualize the data, you can use a BI tool like Metabase or alternatively, as Materialize is Postgres wire-compatible, you can use your favorite programming language and build your own dashboard. For more information on the supported tools and integrations, check out the Materialized Views documentation

Stop the demo

To stop the demo, run:

docker-compose down -v

For a similar version of this demo using Debezium, check out the post here:

Community

If you have any questions or comments, please join the Materialize Slack Community!


Also Published here