Analyzing Customer Order Data with UNION ALL vs. UNION

Understanding the difference between UNION and UNION ALL in SQL is crucial for efficient data aggregation. This challenge will task you with analyzing customer order data from two different tables and combining it to answer specific business questions, demonstrating the performance implications of each SQL operator. You'll need to determine when to use UNION ALL for speed and when UNION is necessary to ensure distinct results.

Problem Description

You are a data analyst working for an online retail company. The company stores customer order data in two separate tables: Orders_Current and Orders_Archive. Orders_Current contains recent orders, while Orders_Archive holds older, historical orders. Both tables have the same structure: OrderID, CustomerID, OrderDate, and TotalAmount.

Your task is to write SQL queries that combine data from both tables to answer the following questions:

1. Total Revenue (UNION ALL): Calculate the total revenue generated from all orders (current and archived) using UNION ALL. This query should be as fast as possible.
2. Distinct Customers (UNION): Determine the number of distinct customers who have placed orders (current or archived) using UNION. This requires removing duplicate customer IDs.
3. Top 5 Customers by Total Spend (UNION ALL): Find the top 5 customers who have spent the most money across both current and archived orders, using UNION ALL to combine the data. You'll need to calculate the total spend for each customer.

You must demonstrate the use of both UNION and UNION ALL and explain why you chose each operator for each specific query. Consider the potential performance differences.

Examples

Example 1: Total Revenue (UNION ALL)

Orders_Current:
OrderID | CustomerID | OrderDate    | TotalAmount
------- | ---------- | ------------ | -----------
1       | 101        | 2023-01-15   | 100.00
2       | 102        | 2023-02-20   | 250.00

Orders_Archive:
OrderID | CustomerID | OrderDate    | TotalAmount
------- | ---------- | ------------ | -----------
3       | 101        | 2022-12-01   | 50.00
4       | 103        | 2022-11-10   | 120.00

SELECT SUM(TotalAmount) AS TotalRevenue
FROM Orders_Current
UNION ALL
SELECT SUM(TotalAmount) AS TotalRevenue
FROM Orders_Archive;

Output:

TotalRevenue
-----------
420.00

Explanation: The query uses UNION ALL because we want to sum all amounts, regardless of duplicates. UNION ALL is faster because it doesn't perform duplicate removal.

Example 2: Distinct Customers (UNION)

Orders_Current:
OrderID | CustomerID | OrderDate    | TotalAmount
------- | ---------- | ------------ | -----------
1       | 101        | 2023-01-15   | 100.00
2       | 102        | 2023-02-20   | 250.00

Orders_Archive:
OrderID | CustomerID | OrderDate    | TotalAmount
------- | ---------- | ------------ | -----------
3       | 101        | 2022-12-01   | 50.00
4       | 103        | 2022-11-10   | 120.00

SELECT COUNT(DISTINCT CustomerID) AS DistinctCustomerCount
FROM Orders_Current
UNION
SELECT COUNT(DISTINCT CustomerID) AS DistinctCustomerCount
FROM Orders_Archive;

Output:

DistinctCustomerCount
--------------------
3

Explanation: The query uses UNION because we want to count distinct customers. UNION automatically removes duplicate customer IDs before counting.

Example 3: Top 5 Customers by Total Spend (UNION ALL)

Orders_Current:
OrderID | CustomerID | OrderDate    | TotalAmount
------- | ---------- | ------------ | -----------
1       | 101        | 2023-01-15   | 100.00
2       | 102        | 2023-02-20   | 250.00

Orders_Archive:
OrderID | CustomerID | OrderDate    | TotalAmount
------- | ---------- | ------------ | -----------
3       | 101        | 2022-12-01   | 50.00
4       | 103        | 2022-11-10   | 120.00

SELECT CustomerID, SUM(TotalAmount) AS TotalSpend
FROM Orders_Current
GROUP BY CustomerID
UNION ALL
SELECT CustomerID, SUM(TotalAmount) AS TotalSpend
FROM Orders_Archive
GROUP BY CustomerID
ORDER BY TotalSpend DESC
LIMIT 5;

Output:

CustomerID | TotalSpend
---------- | ----------
101       | 150.00
102       | 250.00
103       | 120.00

Explanation: UNION ALL is used here because we want to combine the total spend for each customer from both tables. Duplicate customer IDs are not a concern in this case, and UNION ALL provides better performance.

Constraints

• Both Orders_Current and Orders_Archive tables will contain at least 100 rows each.
• CustomerID is an integer.
• OrderDate is a date in YYYY-MM-DD format.
• TotalAmount is a decimal number.
• The database system used is assumed to be standard SQL compliant (e.g., PostgreSQL, MySQL, SQL Server).
• Performance is a consideration. Favor UNION ALL when duplicate removal is not required.

Notes

• Carefully consider whether duplicate removal is necessary for each query.
• UNION ALL is generally faster than UNION because it avoids the overhead of duplicate removal.
• Use GROUP BY to aggregate data when calculating total spend per customer.
• The LIMIT clause is used to retrieve only the top 5 customers.
• The specific syntax for LIMIT might vary slightly depending on the database system. Adjust accordingly.
• Explain your choice of UNION vs. UNION ALL for each query in comments within your SQL code. This is a key part of the evaluation.