## Mastering Comma-Joining and CROSS JOINs in Oracle SQL

Understanding Oracle SQL’s “from” Syntax: A Deep Dive into Comma-Joining and Its Alternatives

Introduction

Oracle SQL, like many other relational database management systems, has a rich syntax for querying data. One of the most commonly misunderstood aspects of this syntax is the use of comma-separated tables in a FROM clause. In this article, we will delve into the world of comma-joining and explore its limitations, alternatives, and best practices.

What is Comma-Joining?

Comma Joining is an older syntax in Oracle SQL that allows you to specify multiple tables in a single SELECT, UPDATE, or DELETE statement. The tables are separated by commas within the FROM clause. For example:

SELECT *
FROM table1, table2, table3;

In this example, we’re selecting all columns (*) from three tables: table1, table2, and table3.

When to Use Comma-Joining

While comma-joining is a convenient way to select data from multiple tables, it has several limitations:

It can lead to ambiguous join conditions, making the query more difficult to understand and maintain.
It doesn’t allow for specifying the join type (INNER, LEFT JOIN, etc.) or the joining columns.
If you have a WHERE clause, it may not be applied correctly across all tables.

ANSI/ISO Equivalent: CROSS JOIN

The ANSI/ISO standard for SQL defines the CROSS JOIN keyword as an alternative to comma-joining. The syntax is similar but uses the CROSS JOIN operator instead of separating the tables with commas:

SELECT *
FROM table1
CROSS JOIN table2
CROSS JOIN table3;

The CROSS JOIN returns all possible combinations of rows from both table1 and table2, followed by table3. This results in a Cartesian product, meaning that each row in one table is combined with every row in the other tables.

Converting Comma-Joining to CROSS JOIN

If you’re used to comma-joining your queries, it’s essential to understand how to convert them into CROSS JOINS. In general, if you have:

SELECT *
FROM table1, table2, table3;

You can rewrite this as a CROSS JOIN like so:

SELECT *
FROM table1
CROSS JOIN table2
CROSS JOIN table3;

However, there are cases where converting comma-joining to CROSS JOIN might not be straightforward. If your WHERE clause applies only to certain columns and tables, it may need additional modifications.

Example Conversion

Consider the following example of a comma-joining query with a WHERE clause:

SELECT *
FROM table1, table2, table3
WHERE table1.id = table2.id
AND table2.id = table3.id;

To convert this to CROSS JOIN, you would typically rewrite it as follows:

SELECT *
FROM (SELECT id FROM table1) t1
CROSS JOIN (SELECT id FROM table2) t2
CROSS JOIN (SELECT id FROM table3) t3;

However, in the original query with a WHERE clause, we can see that table1.id should be matched by both t2 and t3, as well as other conditions. The best course of action might be to rewrite your query like so:

SELECT *
FROM table1
CROSS JOIN (SELECT id FROM table2) t2
CROSS JOIN (SELECT id FROM table3) t3
WHERE table1.id = t2.id
AND t2.id = t3.id;

In this version, we’re matching the id from table1 to both t2 and t3.

Converting LEFT OUTER JOIN

When dealing with LEFT OUTER JOINs, you may need more complex conversions. Consider the following query:

SELECT *
FROM table1, table2, table3
LEFT OUTER JOIN table4 ON table1.id = table4.id;

Converting this to CROSS JOIN can be tricky because table1 is being joined with both table2, table3, and table4. You could rewrite it as follows:

SELECT *
FROM (SELECT id FROM table1) t1
LEFT OUTER JOIN (SELECT id FROM table2) t2 ON t1.id = t2.id
LEFT OUTER JOIN (SELECT id FROM table3) t3 ON t1.id = t3.id
LEFT OUTER JOIN (SELECT id FROM table4) t4 ON t1.id = t4.id;

However, this may not be the most efficient or clean way to write your query. Consider rewriting it as a combination of CROSS JOINS and LEFT OUTER JOINs:

SELECT *
FROM table1
CROSS JOIN (SELECT id FROM table2) t2
CROSS JOIN (SELECT id FROM table3) t3
LEFT OUTER JOIN (SELECT id FROM table4) t4 ON t2.id = t4.id;

In this version, we’re joining table1 with both t2 and t3, followed by a LEFT OUTER JOIN on table4.

Best Practices for Comma-Joining

While comma-joining can be convenient, it’s generally better to avoid using this syntax whenever possible. Here are some best practices:

Use INNER JOINs instead: When you need to join two tables based on a common column, use an INNER JOIN.
Avoid ambiguity by specifying the join type: If you’re unsure about which table should be joined first or how the join columns align, explicitly specify the join type (INNER JOIN, LEFT JOIN, etc.) in your query.

When applying conditions with WHERE clause, apply them to individual tables before joining.

Conclusion

Comma-joining is an older syntax for Oracle SQL that allows you to select data from multiple tables. However, it has several limitations and can lead to ambiguity if not used carefully. The ANSI/ISO equivalent of comma-joining is the CROSS JOIN operator, which returns a Cartesian product of rows from both tables.

When converting comma-joining queries to CROSS JOINs, it’s essential to consider how the WHERE clause applies to individual columns in different tables and adjust your query accordingly. By following best practices for writing clean, efficient queries using INNER JOINs and specifying join types explicitly, you can avoid common pitfalls associated with comma-joining.

## Advanced Topics

### Optimizing Comma-Joining Queries

While CROSS JOIN is an efficient way to combine multiple tables, it can still be resource-intensive for large datasets. In some cases, you may need to rewrite your query as a combination of INNER JOINs and WHERE clauses to achieve better performance.

Consider the following example:

```markdown
SELECT *
FROM table1, table2, table3
WHERE table1.id = table2.id
AND table2.id = table4.id;

You can rewrite this query like so:

SELECT *
FROM (SELECT id FROM table1) t1
JOIN (SELECT id FROM table2) t2 ON t1.id = t2.id
JOIN (SELECT id FROM table3) t3 ON t2.id = t3.id
JOIN (SELECT id FROM table4) t4 ON t2.id = t4.id;

By breaking down the query into separate JOIN operations and applying conditions in the WHERE clause, you can optimize performance for larger datasets.

Conclusion

Comma-joining is an older syntax that’s generally best avoided. However, it’s still essential to understand how to convert comma-joining queries to CROSS JOINS when necessary. By following best practices for writing clean, efficient queries using INNER JOINs and specifying join types explicitly, you can achieve better performance and avoid common pitfalls associated with comma-joining.

## Best Practices

### Use INNER JOINs Instead of Comma-Joining

When joining two tables based on a common column, use an INNER JOIN instead of comma-joining. Here's an example:

```markdown
SELECT *
FROM table1
INNER JOIN table2 ON table1.id = table2.id;

This query is cleaner and more readable than the equivalent comma-joining query.

Avoid Ambiguity by Specifying the Join Type

When you’re unsure about which table should be joined first or how the join columns align, explicitly specify the join type (INNER JOIN, LEFT JOIN, etc.) in your query. Here’s an example:

SELECT *
FROM table1
INNER JOIN table2 ON table1.id = table2.id
LEFT OUTER JOIN table3 ON table2.id = table3.id;

In this version, we’re explicitly specifying both the INNER JOIN on table1 and table2, as well as a LEFT OUTER JOIN on table3.

Follow Best Practices for Applying Conditions with WHERE Clause

When applying conditions with a WHERE clause, apply them to individual tables before joining. This can help avoid ambiguity and improve performance. Here’s an example:

SELECT *
FROM table1
WHERE table1.id = 10
INNER JOIN table2 ON table1.id = table2.id;

In this version, we’re applying the condition table1.id = 10 to individual rows in table1 before joining with table2.

Last modified on 2023-09-11