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6747d053-b51c-8012-ab23-3f0d07bacc15

Ah, you're referring to selecting columns from two tables using a comma-separated list (Cartesian product) versus using a JOIN. Let’s compare the two approaches:

1. Selecting with FROM a, b (Cartesian Product)

Query Example:

SELECT a.x, b.y
FROM a, b;

What Happens:

  • This performs a Cartesian product (cross join) of the two tables, meaning every row in table a is combined with every row in table b.
  • The result set will have rows_in_a × rows_in_b rows.

Use Cases:

  • Rarely used unless the goal is specifically to calculate combinations (e.g., pairing all rows of two tables).
  • Useful for generating datasets for testing or scenarios where no relationship exists between the tables.

Drawbacks:

  • If tables are large, the result set can grow exponentially, causing performance issues.
  • Generally inefficient and not meaningful unless further filtering (via a WHERE clause) is applied.

Example with Filtering:

SELECT a.x, b.y
FROM a, b
WHERE a.id = b.a_id; <--------------------------------------------------------------------
  • This mimics a JOIN but uses explicit filtering in the WHERE clause instead of join syntax.

2. Using a JOIN

Query Example:

SELECT a.x, b.y
FROM a
JOIN b ON a.id = b.a_id;

What Happens:

  • This performs an inner join, which means only rows where a.id = b.a_id will be included in the result.
  • Filters rows at the database level, reducing the result size compared to a Cartesian product.

Use Cases:

  • When tables are related via a specific condition (e.g., foreign key relationships).
  • Efficiently retrieving combined data without generating irrelevant combinations.

Advantages:

  • Better readability and clarity.
  • Database optimizers handle joins more efficiently than Cartesian products with filtering.

Comparison: Cartesian Product vs JOIN

Feature FROM a, b (Cartesian Product) JOIN
Mechanism Combines all rows from both tables Combines rows based on a relationship
Size of Result Set Exponential (rows_in_a × rows_in_b) Filtered result based on ON condition
Performance Inefficient for large tables Optimized by the database engine
Readability Harder to understand without filtering Clear and explicit
Use Case Testing or unrelated datasets Related datasets with a defined link

Example with Tables

Tables:

  • Table a:

    id x
    1 10
    2 20

  • Table b:

    a_id y
    1 100
    2 200

Query 1: Cartesian Product (FROM a, b)

SELECT a.x, b.y
FROM a, b;

Result:

x y
10 100
10 200
20 100
20 200

Query 2: JOIN

SELECT a.x, b.y
FROM a
JOIN b ON a.id = b.a_id;

Result:

x y
10 100
20 200

Key Insights:

  1. Use Cartesian product (FROM a, b) sparingly, as it generates all possible combinations unless filtered with WHERE.
  2. Prefer JOIN for related tables, as it is optimized for combining rows with a clear relationship.
  3. If you write FROM a, b WHERE a.id = b.a_id, it behaves like a JOIN but is less explicit and harder to read.

Let me know if you'd like more details or advanced examples!