Mariadbデータベースの達人技：重複値を排除してグループ最大値を効率的に取得

SQLで重複値をグループごとに最大値でフィルターするには、いくつかの方法があります。ここでは、2つの一般的な方法をご紹介します。

方法1：GROUP BY 句と集計関数を使用する

この方法は、最もシンプルで分かりやすい方法です。

SELECT グループ化カラム, 集計カラム
FROM テーブル名
GROUP BY グループ化カラム
HAVING 集計カラム = (SELECT MAX(集計カラム) FROM テーブル名 WHERE グループ化カラム = グループ化カラムの値);

例

次のテーブル orders があるとします。

このテーブルから、各顧客の注文の中で最も価格の高い商品のみを取得するには、次のクエリを使用します。

SELECT customer_id, MAX(price) AS max_price
FROM orders
GROUP BY customer_id
HAVING max_price = (SELECT MAX(price) FROM orders WHERE customer_id = customer_id);

このクエリは次の結果を返します。

方法2：ウィンドウ関数を使用する

この方法は、より新しいSQL標準で導入されたウィンドウ関数を使用します。

SELECT グループ化カラム, 集計カラム
FROM テーブル名
ORDER BY グループ化カラム, 集計カラム ROWS BETWEEN PRECEDING 1 AND CURRENT ROW
WHERE ROW_NUMBER() OVER (PARTITION BY グループ化カラム ORDER BY 集計カラム DESC) = 1;

SELECT customer_id, MAX(price) OVER (PARTITION BY customer_id ORDER BY price DESC) AS max_price
FROM orders;

• GROUP BY 句と集計関数を使用する方法は、シンプルで分かりやすいのが利点です。
• ウィンドウ関数を使用する方法は、より新しいSQL標準で導入された方法であり、柔軟性と処理速度の点で優れています。

その他の注意点

• 上記の例では、price カラムが数値型であることを前提としています。price カラムが文字型の場合は、適切な型変換関数を使用する必要があります。
• 重複値をグループごとに最大値でだけではなく、最小値、平均値、合計値などでフィルターしたい場合は、集計関数を変えるだけで済みます。

ご自身の状況に合わせて適切な方法を選択してください。

Method 1: Using GROUP BY clause and aggregate functions

CREATE TABLE orders (
  order_id INT PRIMARY KEY,
  customer_id INT,
  product_id INT,
  price DECIMAL(10,2)
);

INSERT INTO orders VALUES
  (1, 1, 101, 100),
  (2, 1, 102, 200),
  (3, 2, 101, 300),
  (4, 2, 103, 400);

-- Select the customer ID and maximum price for each customer
SELECT customer_id, MAX(price) AS max_price
FROM orders
GROUP BY customer_id
HAVING max_price = (
  SELECT MAX(price)
  FROM orders
  WHERE customer_id = customer_id
);

Method 2: Using window functions

SELECT customer_id, MAX(price) OVER (PARTITION BY customer_id ORDER BY price DESC) AS max_price
FROM orders;

Explanation

Method 1:

1. CREATE TABLE statement: This statement creates a table named orders with four columns: order_id, customer_id, product_id, and price.
2. INSERT INTO statements: These statements insert four rows of data into the orders table.
3. SELECT statement: This statement retrieves the customer ID and maximum price for each customer.
   • The GROUP BY clause groups the rows by the customer_id column.
   • The MAX(price) function calculates the maximum price for each group.
   • The HAVING clause filters the results to only include rows where the maximum price is equal to the overall maximum price for that customer ID. This ensures that only one row is returned for each customer, representing the order with the highest price.

1. SELECT statement: This statement retrieves the customer ID and maximum price for each customer.
   • The PARTITION BY customer_id ORDER BY price DESC clause defines a window for each customer, sorted by price in descending order.
   • The MAX(price) OVER (window) function calculates the maximum price within each window (i.e., for each customer).
   • This effectively identifies the highest price for each customer without the need for a subquery or HAVING clause.

Both methods effectively filter the orders table to return only one row for each customer, representing the order with the highest price. The choice between the two methods depends on personal preference and the specific context of the query.

Method 3: Using a self-join

This method involves joining the table to itself to compare the values within each group.

SELECT o1.customer_id, o1.price AS max_price
FROM orders AS o1
LEFT JOIN orders AS o2
  ON o1.customer_id = o2.customer_id
    AND o1.price < o2.price
WHERE o2.price IS NULL;

Method 4: Using correlated subqueries

This method utilizes subqueries within the main query to filter based on group-specific maximum values.

SELECT customer_id, (
  SELECT MAX(price)
  FROM orders
  WHERE customer_id = o1.customer_id
) AS max_price
FROM orders AS o1;

1. LEFT JOIN: This joins the orders table to itself (o1 and o2) on the customer_id column.
2. ON clause with condition: The ON clause filters the join to only include rows where o1.price is less than o2.price.
3. WHERE clause with IS NULL condition: The WHERE clause filters the results to only include rows where the corresponding o2.price is NULL. This ensures that only rows representing the maximum price for each customer remain.

1. SELECT statement: This statement retrieves the customer ID and maximum price for each customer.
2. Correlated subquery: The correlated subquery within the SELECT clause calculates the maximum price for each customer.
   • The subquery is correlated to the outer query through the customer_id column.
   • It retrieves the maximum price for the current customer's ID from the orders table.
3. Main query selection: The main query then selects the customer_id and the maximum price calculated by the subquery.