Ingest data from Coreflux broker
You can ingest data from HiveMQ, a leading MQTT platform renowned for its reliability, scalability, and flexibility. HiveMQ extends the MQTT standard to provide a comprehensive IoT messaging solution, trusted by brands like Air France-KLM, BMW, Mercedes-Benz, and ZF. It is widely adopted across industries such as automotive, energy, logistics, and smart manufacturing. The core of HiveMQ is its high-performance, MQTT-compliant broker, ensuring fast and reliable data transmission.
Set Up a HiveMQ broker
This section provides step-by-step instructions for creating a HiveMQ broker on HiveMQ Cloud and connecting it to RisingWave for real-time data ingestion and analytics. This setup is ideal for IoT messaging and processing workflows. For additional details, refer to the official HiveMQ Documentation.
1. Sign Up for HiveMQ Cloud
To begin, sign up for a free trial of HiveMQ Cloud at HiveMQ Cloud. This service offers cloud-based, enterprise-grade MQTT capabilities tailored for IoT messaging.
HiveMQ Cloud Sign-Up page.
2. Create a HiveMQ cluster
After signing in, follow these steps to create a new HiveMQ cluster:
- Select Create New Cluster.
- Choose between Serverless and Starter cluster options. Select Serverless for a fast, easy setup.
HiveMQ Cloud Cluster Creation.
Once your Serverless HiveMQ cluster is set up, you can publish and subscribe to IoT events within minutes.
HiveMQ Cloud Free Plans: Serverless and Starter.
3. Configure cluster access
To securely connect and interact with the HiveMQ broker, you’ll need to set up user credentials:
- Add a username and password.
- Assign the necessary permissions to publish and subscribe to the MQTT topics.
HiveMQ Cluster Access Management.
These credentials allow your MQTT clients to publish and subscribe securely to the HiveMQ broker.
4. Cluster details
You’ll now have access to your cluster details, which include: Cluster name, Current plan, Cloud provider, Cluster URL and port, and WebSocket URL and port.
These details are essential for connecting to the HiveMQ broker using MQTT clients.
HiveMQ Serverless Cluster Details.
With your HiveMQ Cloud cluster ready, you can now start sending data from IoT devices to the MQTT broker. This example demonstrates how to send IoT data (e.g., device health metrics) using the Python Paho client. Each data point includes temperature, humidity, and status readings from a specific device at a particular timestamp.
For detailed setup, refer to the HiveMQ Quick Start Guide.
Set Up a RisingWave cluster
To ingest data into RisingWave, you’ll need to create a RisingWave cluster. Sign up for a free plan at RisingWave Cloud to explore its features. You can refer to the RisingWave Documentation for comprehensive, step-by-step instructions. For further assistance or to join the community, connect with us on Slack.
RisingWave Cloud Sign-Up page.
1. Create a data source in RisingWave
Use the following SQL query to create a table called iot_sensor_data
in RisingWave. This table will store incoming data from your HiveMQ broker:
In this setup:
- device_id represents the IoT device identifier.
- ts is the timestamp.
- temperature and humidity represent sensor readings.
- device_status indicates whether the device is in a normal or abnormal state.
This query connects RisingWave to the HiveMQ broker, retrieving real-time data from the earliest available MQTT records.
2. Query the data source
You can query the iot_sensor_data
table to view the latest records using the following SQL query:
This query retrieves the top five records, providing a snapshot of the latest IoT data, including device IDs, timestamps, temperature, humidity, and status values.
Query results for IoT sensor data.
You have successfully set up a HiveMQ serverless cluster and connected it to RisingWave for real-time data ingestion and analysis. Using the RisingWave MQTT connector, you can monitor, analyze, and even perform predictive maintenance on your IoT data.
Additionally, you can use the RisingWave MQTT Sink connector to send processed results back to HiveMQ. These results can be visualized using tools like Grafana, enabling you to derive deeper insights from your IoT data.