Implement a correlated subquery

A correlated subquery in SQL is a subquery that uses values from the outer query and the subquery is executed once for each potential result from the outer query. This functionality is especially useful when the relationship between tables includes multiple matches in the subquery for a single row in the outer query. However, correlated subqueries can result in significant overhead, particularly when dealing with large amounts of data.

In the context of implementing native applications using Microsoft Azure Cosmos DB, understanding and implementing correlated subqueries can be crucial. Cosmos DB is a globally distributed, multi-model database service designed for scaling and replicating data across any number of Azure regions.

Designing and Implementing Queries in Cosmos DB

When designing and implementing queries in Cosmos DB, it’s important to understand how an SQL query gets transformed into a series of operations. Correlated subqueries are enabled by System Functions in Cosmos DB’s SQL API.

A basic correlated subquery would look something like this:

SELECT c.CustomerName
FROM Customers c
WHERE EXISTS
(
SELECT 1
FROM orders o
WHERE o.CustomerID = c.CustomerID
}

In this example, the subquery needs to execute for each potential result from the `Customers` table to determine whether a matching record exists in the `Orders` table for each customer.

Comparison with Non-Correlated Subqueries

Non-correlated subqueries are independent of the outer query and can run separately. Here’s a comparative example demonstrating this:

— Correlated Subquery
SELECT e.EmployeeName
FROM Employees e
WHERE (
SELECT COUNT(o.orderID)
FROM Orders o
WHERE o.EmployeeID = e.EmployeeID
) > 10

— Non-Correlated Subquery
SELECT e.EmployeeName
FROM Employees e,
(
SELECT EmployeeID
FROM Orders
GROUP BY EmployeeID
HAVING COUNT(OrderID) > 10
) o
WHERE e.EmployeeID = o.EmployeeID

In the first (correlated) example, the query gets a list of employees who have more than 10 orders. The subquery needs to run for each employee.

In the second (non-correlated) example, the subquery is only executed once, and the result is stored. It then does a simple INNER JOIN (represented by the comma in the FROM clause) on the `Employees` table using the `EmployeeID` field.

When developing with Cosmos DB, understanding the difference between correlated and non-correlated subqueries is important for optimizing performance and is crucial when preparing for DP-420 Designing and Implementing Native Applications Using Microsoft Azure Cosmos DB exam.

It’s recommended to use non-correlated subqueries when possible, especially when dealing with large amounts of data, due to the significant performance difference.

However, there are instances where correlated subqueries are necessary for the correct results. It’s crucial then to understand the overhead they can cause and to structure data and indexes in Cosmos DB to best accommodate these types of queries. Understanding the underlying principles of how these subqueries function will provide the tools necessary to approach such challenges optimally.

In conclusion, mastering the implementation of correlated subqueries is an integral part of working with Azure Cosmos DB, and can greatly improve the quality and performance of your Azure native applications.

Practice Test

True or False: A correlated subquery in SQL Server can be used to select data from one table depending on data from another.

• True
• False

Answer: True

Explanation: A correlated subquery can be used to select data from one table that corresponds to data in another. It’s called a correlated subquery because the inner query is related to the outer query.

In Azure Cosmos DB, for which type of SQL subqueries, the [NOT] EXISTS clause use is permitted?

• Uncorrelated subqueries
• Correlated subqueries
• Non-integrated subqueries
• Integrated subqueries

Answer: Correlated subqueries

Explanation: The [NOT] EXISTS clause use is permitted for correlated subqueries in Azure Cosmos DB.

True or False: Correlated subqueries can be used for optimizing query performance in Azure Cosmos DB.

• True
• False

Answer: False

Explanation: While correlated subqueries can add additional flexibility to your SQL statements, they are generally not used for optimizing query performance. In fact, they might even downgrade the query performance due to the multiple table scan involved.

True or False: When executing a correlated subquery, the outer query executes once and the inner query executes multiple times.

• True
• False

Answer: True

Explanation: This is the fundamental nature of a correlated subquery where the outer query executes once and then the inner query executes once for each row returned by the outer query.

In Azure Cosmos DB, subqueries cannot be nested.

• True
• False

Answer: False

Explanation: Subqueries in Azure Cosmos DB can be nested, allowing for versatile queries on data within a given container.

In Azure Cosmos DB, the correlated subqueries are supported in which query language?

• MySQL
• MongoDB
• SQL
• None of these

Answer: SQL

Explanation: In Azure Cosmos DB, correlated subqueries are supported in SQL API.

Which of the following are reasons to use subqueries in Azure Cosmos DB? (Choose all that apply)

• To optimize query performance
• For data manipulation
• To filter data based on conditions
• None of the above

Answer: For data manipulation, To filter data based on conditions

Explanation: Subqueries in Azure Cosmos DB are helpful for more complex data manipulation and to filter data based on certain conditions.

True or False: In a non-correlated subquery, the inner query does not depend on the outer query.

• True
• False

Answer: True

Explanation: A non-correlated subquery can be run independently of the outer query, whereas in a correlated subquery, the inner query relies on information obtained from the outer query.

Which of the following is not a best practice when using correlated subqueries in Azure Cosmos DB?

• Limit the usage of NOT IN and NOT EXISTS
• Limit the nested levels of subqueries
• Extensively use correlated subqueries for performance tuning
• Avoid unnecessary subqueries

Answer: Extensively use correlated subqueries for performance tuning

Explanation: Extensively using correlated subqueries provides flexibility but does not effectively improve performance.

True or false: Correlated subqueries in Azure Cosmos DB always contribute to the increase of Request Units (RUs).

• True
• False

Answer: True

Explanation: Each scan or computation in a correlated subquery can lead to a significant increase in Request Units (RUs), so it’s important to consider this when designing and implementing your queries.

Interview Questions

What is a correlated subquery in the context of database design and operation?

A correlated subquery is a more advanced type of SQL subquery. Unlike a simple subquery, a correlated subquery uses data from the outer query to complete, meaning it runs once for every row executed by the outer query.

How does a correlated subquery differ from a typical subquery?

While a typical subquery is only executed once and returns a single value or a set of values, a correlated subquery refers to a column in a table in the parent statement and is run once for each row processed in the parent statement.

Is it possible to implement a correlated subquery in Azure Cosmos DB?

No, as of now, Azure Cosmos DB does not support correlated subqueries directly. Instead, application-side joins can be used to achieve similar results.

What is Azure Cosmos DB?

Azure Cosmos DB is a globally distributed, multi-model database service from Microsoft Azure. It is designed to transparently scale and replicate your data wherever your users are.

Is there a performance impact when using correlated subqueries?

Yes, correlated subqueries can substantially impact the performance because for each row processed in the parent statement, the subquery is executed. This often leads to more processing time and increased resource consumption.

What is the structure of a correlated subquery?

A correlated subquery is structured as a main or outer query and an inner subquery that contains a reference to a column or columns of the outer query in its WHERE clause.

In Microsoft Azure Cosmos DB, is there an alternative approach to achieving the results of a correlated subquery?

Yes, while Azure Cosmos DB doesn’t directly support correlated subqueries, you can achieve similar outcomes using multiple SQL API queries, and application-side JOINs to merge the results.

Why might you implement a correlated subquery during app design?

A correlated subquery can be used when the information to be retrieved cannot be achieved using a standard join. They can also return data in a different format suited to certain analytical or report-based results.

Can correlated subqueries be used with the SQL API in Azure Cosmos DB?

No, currently correlated subqueries are not supported by the SQL API in Azure Cosmos DB. It only supports uncorrelated subqueries, and not ALL, EXISTS, IN, and SOME subquery operators.

How can we make Azure Cosmos DB perform operations similar to correlated subqueries while designing applications?

We can perform multiple SQL API queries and perform application-side JOIN operations to get similar results as we would get from a correlated subquery.

What is an example of a JOIN in Cosmos DB, as an alternative to a correlated subquery?

A JOIN in Cosmos DB is often implemented on the basis of certain shared elements between two or more collections. For example, creating a new document that joins data from the ‘Customers’ and ‘Orders’ collections, based on shared customer ID fields.

In application design, when might you opt for an application-side JOIN rather than a correlated subquery?

Using Azure Cosmos DB, an application-side JOIN might be a more feasible option when data from two or more separate collections is required by the application, as Cosmos DB currently does not support correlated subqueries directly.

Why are correlated subqueries often considered less efficient than standard subqueries or JOIN clauses?

Correlated subqueries must run once for each row processed by the outer query. This can lead to significantly more processing time and potentially high resource usage, particularly when dealing with large datasets.

Are there any use cases where correlated subqueries would be more efficient than a JOIN or non-correlated subquery?

In scenarios where the result set is small or filtered down by the outer query before running the subquery, a correlated subquery could be more efficient. However, for large datasets, they typically show poorer performance compared to joins or non-correlated subqueries.

What are some methods to optimize the performance of a correlated subquery?

Some methods to optimize the performance include indexing the columns present in the WHERE clause of the subquery, reducing the number of rows returned by the outer query, or rewriting the correlated subquery as a JOIN if possible.