Aggregating SQL Minute Rows into 15-Minute Intervals

Learn how to aggregate SQL minute rows into 15-minute intervals using a structured SQL query. This guide provides step-by-step solutions to simplify your data analysis.
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Aggregating SQL Minute Rows into 15-Minute Intervals: A Guide

In the realm of data analysis, one common challenge arises from the need to condense detailed time-series data. Suppose we have a table with entries for each minute, complete with metrics like the Open, High, Low, and Close prices alongside their corresponding Timestamp. The goal is to aggregate these minute-level data points into more manageable 15-minute intervals—essentially taking multiple rows of data and summarizing them into one row per quarter hour.

This approach not only simplifies data handling but also allows for easier analysis and visualization. Below, we’ll explore how to achieve this using SQL, particularly in SQL Server, with a practical guide and a structured SQL query.

Problem Breakdown

1. Data Structure

Columns present: Open, High, Low, Close, and Timestamp.

Objective: Aggregate every 15-minute interval to produce:

The Open value from the first minute of the period.

The maximum High value during the interval.

The minimum Low value throughout the period.

The Close value from the last minute of the period.

The Timestamp of the last minute.

2. Desired Result

For a dataset with minute-level data over an hour (60 rows), the expected output would consolidate that into 4 rows summarizing the data for each 15-minute increment.

For example:

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

SQL Query Solution

The following SQL query outlines how to effectively retrieve the needed results from the table using subqueries and built-in SQL functions such as ROW_NUMBER, MAX, and MIN.

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

Explanation of the Query

Subquery Setup: The inner query generates ROW_NUMBER sequences for each group of minutes falling within the same 15-minute interval.

Aggregation Functions:

MAX for summarizing the Open and Close values corresponding to the first and last minutes, respectively.

MIN to capture the lowest Low across the interval.

COUNT to track how many original minute rows have been condensed into one.

Grouping: The outer query groups results by day, hour, and calculated intervals, effectively creating the 15-minute windows.

Performance Considerations

Ensure proper indexing on the Timestamp column to enhance query execution time, especially with large datasets.

Use the PARTITION BY clause carefully to avoid excessive memory usage during sorting processes.

Conclusion

Aggregating minute-level data into 15-minute summaries is a powerful technique in SQL that enhances data readability and serves various analytical needs. By carefully structuring your SQL query, as demonstrated, you can achieve this aggregation efficiently while leveraging SQL Server's robust features.

Implement this strategy in your own projects, and enjoy a more streamlined approach to your time-series data analysis!

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