Distinguishing Duplicate Data: UNION ALL vs. UNION

Imagine you are working with two separate datasets that contain information about customer orders. One dataset contains new orders placed today, and the other contains orders from yesterday. You need to combine these datasets to get a comprehensive view of all orders. However, there's a possibility of duplicate order entries if an order was accidentally processed twice on the same day. This challenge will help you understand how UNION ALL and UNION handle such duplicates and when to use each.

Problem Description

You will be provided with two tables, NewOrders and YesterdayOrders. Both tables have the same structure and contain information about customer orders. Your task is to write SQL queries that combine the data from these two tables and demonstrate the difference in behavior between UNION ALL and UNION when duplicate order entries are present.

What needs to be achieved:

1. Combine the data from NewOrders and YesterdayOrders using UNION ALL.
2. Combine the data from NewOrders and YesterdayOrders using UNION.
3. Observe and explain the difference in the results.

Key Requirements:

• Both NewOrders and YesterdayOrders tables have columns: OrderID (unique identifier for an order) and CustomerID (identifier for the customer who placed the order).
• The queries must be language-agnostic, using standard SQL syntax.
• The output should clearly show the results of both operations.

Expected Behavior:

• UNION ALL should return all rows from both tables, including any duplicate OrderIDs if they exist across or within tables.
• UNION should return distinct rows from both tables, automatically removing any duplicate OrderIDs.

Edge Cases to Consider:

• What happens if a duplicate OrderID exists within NewOrders?
• What happens if a duplicate OrderID exists within YesterdayOrders?
• What happens if an OrderID exists in both NewOrders and YesterdayOrders?

Examples

Example 1: Basic Data Combination

Assume the following data:

NewOrders Table:

YesterdayOrders Table:

Query 1: Using UNION ALL

SELECT OrderID, CustomerID
FROM NewOrders
UNION ALL
SELECT OrderID, CustomerID
FROM YesterdayOrders;

Output 1:

Explanation 1: UNION ALL simply appends the rows from YesterdayOrders to NewOrders. No duplicate checking is performed, so all four rows are returned.

Query 2: Using UNION

SELECT OrderID, CustomerID
FROM NewOrders
UNION
SELECT OrderID, CustomerID
FROM YesterdayOrders;

Output 2:

Explanation 2: In this specific case, since there are no identical rows across the two tables, UNION also returns all four rows. UNION removes duplicates based on the entire row.

Example 2: Demonstrating Duplicate Handling

Assume the following data:

NewOrders Table:

YesterdayOrders Table:

Query 1: Using UNION ALL

SELECT OrderID, CustomerID
FROM NewOrders
UNION ALL
SELECT OrderID, CustomerID
FROM YesterdayOrders;

Output 1:

Explanation 1: UNION ALL includes all rows. Notice that (201, C007) is distinct from (201, C005), and (202, C006) from NewOrders is preserved alongside the identical (202, C006) from YesterdayOrders.

Query 2: Using UNION

SELECT OrderID, CustomerID
FROM NewOrders
UNION
SELECT OrderID, CustomerID
FROM YesterdayOrders;

Output 2:

Explanation 2: UNION removes duplicate rows.

• It keeps (201, C005) from NewOrders.
• It keeps one instance of (202, C006) (it doesn't matter which table it came from, as the entire row is identical).
• It keeps (201, C007) from NewOrders.
• It keeps (203, C008) from YesterdayOrders. The duplicate (202, C006) from YesterdayOrders is removed because an identical row was already included.

Example 3: Impact of Different Data in Duplicate OrderID

Assume the following data:

NewOrders Table:

YesterdayOrders Table:

Query 1: Using UNION ALL

SELECT OrderID, CustomerID
FROM NewOrders
UNION ALL
SELECT OrderID, CustomerID
FROM YesterdayOrders;

Output 1:

Explanation 1: UNION ALL includes all rows. Even though OrderID 301 appears twice, the full rows (301, C010) and (301, C012) are distinct and therefore both are kept.

Query 2: Using UNION

SELECT OrderID, CustomerID
FROM NewOrders
UNION
SELECT OrderID, CustomerID
FROM YesterdayOrders;

Output 2:

Explanation 2: UNION considers the entire row for duplicate detection. Since (301, C010) and (301, C012) are different rows, UNION keeps both. The OrderID alone doesn't determine duplication for UNION; it's the combination of all selected columns.

Constraints

• The number of rows in each table will be between 0 and 1,000,000.
• The OrderID and CustomerID values will be strings or integers.
• The queries should execute efficiently, avoiding unnecessary sorting or processing overhead beyond what UNION inherently requires for duplicate removal.

Notes

• The key difference between UNION ALL and UNION lies in how they handle duplicate rows. UNION ALL is generally faster as it doesn't perform the duplicate removal step.
• UNION performs an implicit DISTINCT operation on the combined result set.
• For UNION to remove a row as a duplicate, all selected columns in that row must match all selected columns in another row.
• Consider what your business logic requires: do you want to see every single record submitted, even if they are duplicates, or do you need a de-duplicated list?