📑 About

The decision of where to apply a filter in an SQL query, either in JOIN or WHERE, depends on your intention and the logic of the query you are writing. Both approaches can be appropriate in different situations. I'll explain the differences between them:

Filtering in JOIN:

When you apply a filter in a JOIN clause, you are specifying the join conditions between tables. This means you are limiting which rows will be matched between the tables before applying the WHERE filter. This can be useful when you want to restrict the rows being combined to optimize the query and reduce the amount of processed data.

For example, if you are joining two tables and are only interested in rows where a certain column value matches, you can apply this filter in the JOIN to avoid combining unnecessary rows.

SELECT *
FROM table1
INNER JOIN table2 ON table1.id = table2.table1_id AND table1.value = 'some_value';

Filtering in WHERE:

The WHERE clause is used to apply filters to the query after the tables have been joined. This allows you to filter rows based on criteria involving columns from both tables after the join. This is useful when you need to perform more complex filters involving multiple tables.

SELECT *
FROM table1
INNER JOIN table2 ON table1.id = table2.table1_id
WHERE table1.value = 'some_value' AND table2.column = 'some_other_value';

🚀 Comparing Performance

Let's compare the performance of both approaches with some practical examples.

Example 1: Filtering in JOIN

EXPLAIN SELECT *
FROM table1
INNER JOIN table2 ON table1.id = table2.table1_id AND table1.value = 'some_value';

Example 2: Filtering in WHERE

EXPLAIN SELECT *
FROM table1
INNER JOIN table2 ON table1.id = table2.table1_id
WHERE table1.value = 'some_value';

Analyzing the execution plans (output of EXPLAIN), we can observe:

• Filtering in JOIN:
  
  🎯 MySQL can optimize the join by combining only the necessary rows according to the JOIN condition.
  
  🚀 Fewer initially processed rows.

• Filtering in WHERE:
  
  🎯 MySQL performs the complete join first and then applies the additional filter.
  
  🚀 More initially processed rows, but useful for complex conditions involving multiple tables.

📊 Performance Results

• Filter in JOIN:
  
  🟢 Faster execution in queries with large data sets where the initial filter significantly reduces the number of rows.
  
  🟢 Lower memory and CPU usage.

• Filter in WHERE:
  
  🟢 Execution may be slower if the initial data set is large because more rows are combined before filtering.
  
  🟢 Useful for complex filters involving multiple columns from different tables.

🔍 Conclusion

The choice of where to apply a filter depends on your specific needs and the logic of the query. Use filters in JOIN when you want to limit the combined rows from the start, optimizing data processing. Use filters in WHERE when you need complex filters involving multiple columns from different tables. In many cases, the difference in performance may be insignificant, but in queries with large data volumes, the correct choice can make a significant difference. Always test your queries in real scenarios to determine the best approach.