Data Engineering Spark SQL - Windowing Functions - Overview of Subqueries

Sub queries are a powerful tool in Spark SQL that allow for nesting queries within other queries to perform more complex operations. They are commonly used in the FROM clause without requiring an alias. In this article, we will delve into the usage and benefits of sub queries in Spark SQL.

Explanation for the video

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Key Concepts Explanation

Sub Queries in Spark SQL

Sub queries are commonly used in the FROM clause to perform operations on the results of the sub query. Here is an example of a sub query:

SELECT * FROM (SELECT current_date)

Alias for Sub Queries

In Spark SQL, providing an alias for sub queries is not required in the FROM clause. Here is an example of providing an alias for a sub query:

SELECT * FROM (SELECT current_date) AS q

Filtering Results with Sub Queries

You can filter results based on derived columns using sub queries. Here is an example:

SELECT * FROM (
    SELECT order_date, count(1) AS order_count
    FROM orders
    GROUP BY order_date
) q
WHERE q.order_count > 10

Hands-On Tasks

  1. Execute a sub query to retrieve the current date.
  2. Perform a sub query to calculate the count of orders grouped by order date.
  3. Filter the results of a sub query based on the order count being greater than 10.

Conclusion

In this article, we explored the usage of sub queries in Spark SQL. Sub queries allow for nesting queries within other queries to perform complex operations. By practicing the hands-on tasks provided, you can deepen your understanding of sub queries and apply them in real-world scenarios. Remember to engage with the community for further learning.

Watch the video tutorial here