Скачать или смотреть How to Use SUM() in Oracle SQL Queries to Calculate Run Time

Learn how to effectively use the `SUM()` function in Oracle SQL to calculate run time between timestamps. This guide provides clear examples and explanations for seamless integration.
---
This video is based on the question https://stackoverflow.com/q/62515536/ asked by the user 'Allmood' ( https://stackoverflow.com/u/13792124/ ) and on the answer https://stackoverflow.com/a/62515587/ provided by the user 'Gordon Linoff' ( https://stackoverflow.com/u/1144035/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Add Sum() in query (oracle)

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Use SUM() in Oracle SQL Queries to Calculate Run Time

In the world of data analysis, efficiently processing and summarizing time-related data can often present challenges. One common scenario is wanting to sum running time across multiple entries in Oracle SQL queries where timestamps are involved. If you've been struggling with this, particularly in the context of calculating total run time between two timestamps, you're not alone! Let's take a closer look at how to successfully incorporate the SUM() function into your SQL queries to achieve this.

Understanding the Problem

You have a query that retrieves driver names along with the time they have driven over the last week. The challenge arises when you want to sum these individual run times to provide a total runtime for all the entries. Your initial attempt to add the SUM() function directly within an expression for formatted output resulted in complications. Here's your working request for reference:

[[See Video to Reveal this Text or Code Snippet]]

The Solution Approach

The good news is that summing your run times can be achieved effectively by altering your query slightly to compute the difference first, sum those differences, and then format the result. We'll explore how to modify your SQL query to calculate the total run time using the SUM() function step by step.

Step 1: Sum the Differences

Instead of trying to sum up the formatted output directly, what you'll want to do is first sum the differences between the FinishTime and StartTime. Here’s how the modified approach would look:

[[See Video to Reveal this Text or Code Snippet]]

This line effectively converts the summed difference into a human-readable time format.

Step 2: Adjusting Data Types

In your case, since the columns are timestamp types, it’s good practice to cast them appropriately before performing arithmetic operations. Here’s a further refined version of the query:

[[See Video to Reveal this Text or Code Snippet]]

Full Query Example

Bringing it all together, your SQL command may look something like this:

[[See Video to Reveal this Text or Code Snippet]]

Summary

By restructuring your SQL query and utilizing the SUM() function appropriately, you can now get the total run time for all drivers within the specified timeframe. Here are the crucial points to remember:

Calculate Differences: Perform arithmetic on the FinishTime and StartTime before formatting.

Proper Casting: Make sure to cast timestamp types to date for correct calculations.

Aggregate Functions: Use the GROUP BY clause to aggregate results correctly by each driver.

With this guide, you can easily implement time calculations in your SQL queries, thereby enhancing your data analysis capabilities. Whether you’re a beginner or looking to refine your skills, mastering SQL functions will undoubtedly empower your data management efforts.