Description:
This article provides a step-by-step guide on how to perform basic transformations using Spark SQL for beginners. The guide includes code examples and visual aids to help readers understand and apply the concepts discussed in the article.
Explanation for the video:
This article is complemented by a video available at the provided link in YouTube. The video demonstrates the concepts discussed in the text visually, making it easier for beginners to follow along and understand the steps.
Key Concepts Explanation
Creating Databases and Tables
To start with Spark SQL transformations, we need to create databases and tables for storing and manipulating data. The code examples provided show how to create tables like “orders” and “order_items” with the required columns.
Loading Data into Tables
Once the tables are created, the next step is to load data from local paths into these tables. Using the LOAD DATA command, data can be populated into the tables for further processing.
Querying Tables
After loading data into tables, users can run SQL queries to retrieve and analyze the data. The examples in the article show how to select and view data from the created tables using SQL queries.
Hands-On Tasks
To apply the concepts discussed in the article, readers can perform the following hands-on tasks:
- Create databases and tables for “orders” and “order_items”.
- Load data from local paths into the created tables.
- Execute SQL queries to extract and analyze data from the tables.
Conclusion
In conclusion, this article has provided a beginner-friendly guide on performing basic transformations using Spark SQL. Readers are encouraged to practice the hands-on tasks and engage with the community for further learning.
Preparing Tables
Let us prepare the tables to solve the problem.
- Make sure the database is created.
- Create “orders” table.
- Load data from the local path ‘/data/retail_db/orders’ into the newly created “orders” table.
- Preview data and get count from “orders”.
- Create “order_items” table.
- Load data from the local path ‘/data/retail_db/order_items’ into the newly created “order_items” table.
- Preview data and get count from “order_items”.
Please refer to the video linked in the article for a visual demonstration of these tasks.
The visual demonstration can be found [here](placeholder for video).
Remember to practice the provided hands-on tasks and engage with the community for further learning. Enjoy your Spark SQL journey!