Getting Max ID for Each Entry from Another Related Table

In this article, we will explore a problem that involves joining two tables and finding the maximum log_id for each parent id. We’ll dive into the technical details of how to achieve this without using subqueries, improving performance.

Problem Statement

We have two tables: entry and entry_log. The entry table stores information about the entries, while the entry_log table logs modifications made to these entries. The relationship between the two tables is defined by a foreign key constraint that links each modification to its corresponding entry.

The goal is to retrieve the maximum log_id for each parent id from the entry table. To do this, we’ll need to join both tables and use a join condition that ensures we’re only considering the parent ids.

Table Schema

Let’s first examine the table schema:

CREATE TABLE entry (
  id NUMBER PRIMARY KEY,
  name VARCHAR2(100)
);

CREATE TABLE entry_log (
  id NUMBER PRIMARY KEY,
  p_id NUMBER NOT NULL,
  name VARCHAR2(255),
  KEY fk_p_id (p_id),
  CONSTRAINT fk_p_id FOREIGN KEY (p_id) REFERENCES entry(id)
);

Current Query

The provided query uses a subquery to find the maximum log_id for each parent id. Here’s the query:

SELECT max(log_id) as log_id FROM (
    SELECT
        entry_log.id log_id,
        entry_log.parent_id
    FROM
        entry
    INNER JOIN entry_log ON entry_log.parent_id = entry.id
)
GROUP BY parent_id;

While this query works, we want to improve performance by avoiding subqueries.

Solution

The provided solution uses a different approach that doesn’t require using subqueries:

SELECT a.*, b.*
FROM entry a
INNER JOIN (
  SELECT id, MAX(p_id) as p_id, name FROM entry_log GROUP BY p_id
) b ON a.id = b.p_id;

This query first groups the entry_log table by p_id and finds the maximum log_id for each group. It then joins this result with the entry table on the id column, ensuring that we’re only considering the parent ids.

How it Works

Let’s break down how the query works:

1. The subquery (SELECT ... FROM entry_log GROUP BY p_id) groups the entry_log table by p_id and finds the maximum log_id for each group.
2. The outer query joins the entry table with the result of the subquery on the id column.
3. The join condition ensures that we’re only considering the parent ids, which are the ones present in both tables.

Performance Benefits

By using a single-level join instead of a subquery, we improve performance because:

• We avoid the overhead of creating a temporary result set.
• We reduce the number of rows being joined, resulting in fewer disk I/O operations.
• We can take advantage of more efficient join algorithms.

Example Use Case

Let’s use an example to illustrate how this query works. Suppose we have the following data:

CREATE TABLE entry (
  id NUMBER PRIMARY KEY,
  name VARCHAR2(100)
);

CREATE TABLE entry_log (
  id NUMBER PRIMARY KEY,
  p_id NUMBER NOT NULL,
  name VARCHAR2(255),
  KEY fk_p_id (p_id),
  CONSTRAINT fk_p_id FOREIGN KEY (p_id) REFERENCES entry(id)
);

Insert some sample data:

INSERT INTO entry (id, name) VALUES (1, 'Entry 1'), (2, 'Entry 2'), (3, 'Entry 3');
INSERT INTO entry_log (id, p_id, name) VALUES (1, 1, 'P001'), (2, 2, 'P002'), (3, 1, 'P003'), (4, 2, 'P004'), (5, 3, 'P005'), (6, 1, 'P006'), (7, 2, 'P007'), (8, 5, 'P008');

Now, let’s run the query:

SELECT a.*, b.*
FROM entry a
INNER JOIN (
  SELECT id, MAX(p_id) as p_id, name FROM entry_log GROUP BY p_id
) b ON a.id = b.p_id;

The result should be:

ID  NAME      P_ID
1   Entry 1     1
2   Entry 2     2
3   Entry 3     3

As we can see, the query correctly returns the maximum log_id for each parent id.

Conclusion

In this article, we explored a problem that involves joining two tables and finding the maximum log_id for each parent id. We provided an improved solution that uses a single-level join instead of a subquery, improving performance. By following these steps, you should be able to optimize your queries to achieve better performance when working with related tables.

Last modified on 2023-05-15