blog : Using Node-RED as an ETL tool #2175
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ZJvandeWeg
reviewed
Jun 14, 2024
ZJvandeWeg
reviewed
Jun 14, 2024
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| ETL (Extract, Transform, Load) is essential for integrating and analyzing data, helping businesses unlock detailed insights. You already know Node-RED for its user-friendly approach to creating IoT applications, but did you know it can also be a powerful tool for ETL tasks? When IBM published a blog about using Node-RED for ETL, it caught a lot of attention and got people talking about its potential in this space. In this guide, we'll walk you through how to use Node-RED for ETL, sharing its strengths and weaknesses along the way. |
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@sumitshinde-84 This feels very ChatGPT, can you tone down the bravado?
ZJvandeWeg
reviewed
Jun 15, 2024
ZJvandeWeg
requested changes
Jun 15, 2024
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| ### Extracting | ||
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| Node-RED can extract data from various sources, including APIs, databases, local filesystems, and IoT devices using built-in nodes and community-contributed nodes. For example, the HTTP request node can be used to pull data from web services, while nodes for MySQL, MongoDB, and PostgreSQL can extract data from databases. Nodes for MQTT and Kafka can fetch data from message brokers. File nodes enable extraction of data from local filesystems, while different cloud nodes for platforms like AWS, GCP, and IBM Watson allow extraction of data from cloud storage services. Moreover, Node-RED running on edge devices can extract data from sensors connected directly to them. |
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Modbus, OPC-UA, etc etc aren't mentioned. Please lean into the industrial applicability more
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| ## Benefits of using Node-RED as an ETL tool. | ||
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| 1. **Ease of Use:** Its visual programming interface makes it accessible to non-developers. | ||
| 2. **Flexibility:** A wide range of nodes and the ability to write custom JavaScript allow for flexible data processing. | ||
| 3. **Integration:** Node-RED excels in integrating IoT devices and handling real-time data, making it well-suited for combining diverse data sources into unified workflows. | ||
| 4. **Cost-Effective:** Being open-source, Node-RED can be a cost-effective alternative to expensive ETL tools. | ||
| 5. **Community Support:** A large community provides a wealth of nodes, examples, and support. |
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ChatGPT? Feels uninspired and machine generated.
| ### Customer Data Deduplication | ||
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| 1. Drag a Change node onto the canvas, and set `msg.data` to `msg.payload` and `msg.payload` to `[]`. | ||
| 2. Drag a MongoDB4 node onto the canvas, and configure it with your correct details. If you haven't used MongoDB with Node-RED, please refer to the [Using MongoDB with Node-RED](/blog/2024/04/using-mongodb-with-node-red/). Enter `find` into the Operation field. |
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I don't think MongoDB is used very often in an ETL context, precisely as it's structureless. Do we have a better example? An event based sensor perhaps?
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| ## What are the limitations of using Node-RED as an ETL tool | ||
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| While Node-RED is versatile, there are some limitations to consider while using it as an ETL tool: | ||
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| - Advanced Features: Some advanced ETL features, like automated schema detection and sophisticated error handling, might require additional customization or external modules. | ||
| - Data Governance: Node-RED does not inherently provide robust data governance and lineage tracking, which are often essential in enterprise ETL tools. | ||
| - Scalability: While Node-RED can handle many heavy tasks, but it may not offer the same level of optimization for processing extremely large datasets compared to dedicated ETL tools. |
Co-authored-by: Zeger-Jan van de Weg <ZJvandeWeg@users.noreply.github.com>
ZJvandeWeg
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Jun 18, 2024
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| ## Building a Simple ETL Project Using Node-RED | ||
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| Let's walk through a simple project where we will use Node-RED as an ETL tool to extract sample customer data from an API, transform it, and then load cleaned data into a MongoDB database and process data into a local file. |
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I don't think we should advice to use MongoDB? PG, Snowflake, and others are more often a target for the data.
ZJvandeWeg
reviewed
Jun 18, 2024
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| Let's walk through a simple project where we will use Node-RED as an ETL tool to extract sample customer data from an API, transform it, and then load cleaned data into a MongoDB database and process data into a local file. | ||
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| *Note: The goal of this project is to understand how to utilize Node-RED as an ETL tool. We assume that the reader has a basic knowledge of Node-RED.* |
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| *Note: The goal of this project is to understand how to utilize Node-RED as an ETL tool. We assume that the reader has a basic knowledge of Node-RED.* |
ZJvandeWeg
reviewed
Jun 18, 2024
| ## Extracting Data | ||
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| 1. Drag an Inject node onto the canvas. | ||
| 2. Drag an HTTP Request node onto the canvas, double-click on it, and set the URL to `https://api.slingacademy.com/v1/sample-data/files/customers.json`. |
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This feels like cheating. Not a real world scenario
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@sumitshinde-84 This has gone stale? Any updates pending? |
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Not sure which example I should use. Using the temperature example every time is not good, though. |
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@sumitshinde-84 What about machine logs? |
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