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Inline View Method and the Correlated Subquery in SQL

Oct 04, 2024 pm 02:23 PM

Inline View Method and the Correlated Subquery in SQL

讓我們深入研究兩種方法的執行流程:內嵌視圖方法和相關子查詢方法。了解這些查詢的逐步執行將有助於闡明 SQL 如何處理每個場景以獲得所需的結果。

  1. 內嵌視圖方法執行流程

內嵌視圖方法使用 FROM 子句中的子查詢建立臨時結果集(內聯視圖),然後在外部查詢中處理。

查詢:

選擇部門 ID,MAX(薪水)為最高薪水
來自 (
選擇部門 ID、薪資
來自員工
) AS 內聯視圖
按部門 ID 分組;

執行步驟:

  1. 內部查詢執行(內嵌視圖):

先執行內部查詢(SELECT DepartmentId, Salary FROM Employee)。

它從 Employee 表中選擇 DepartmentId 和 Salary 欄位。

此步驟本質上建立一個臨時結果集(內聯視圖),其中包括 Employee 表中的所有行,但僅包含 DepartmentId 和 Salary 列。

內部查詢結果範例:

  1. 外部查詢執行(聚合和分組):

建立內嵌視圖(暫存結果集)後,外部查詢會取得該結果集並使用 MAX(Salary) 函數進行聚合。

GROUP BY DepartmentId 確保計算每個部門的最高工資。

外部查詢掃描內嵌檢視中的行並根據 DepartmentId 對行進行分組。然後,它計算每個組的最高工資。

  1. 回傳結果:

查詢返回各部門的最高薪資。

最終結果:

執行流程摘要:

  1. 執行內部查詢以建立內聯視圖。

  2. 外部查詢聚合(使用 MAX)並按 DepartmentId 分組結果。

  3. 傳回最終結果。


  1. 相關子查詢方法執行流程

在相關子查詢方法中,內部子查詢針對外部查詢中的每一行執行,使其更加動態,但可能比內聯視圖方法慢。

查詢:

選擇部門 ID、員工 ID、薪資 AS HighestSalary
來自員工 e
工資 = (
選擇最高(薪資)
來自員工
WHERE DepartmentId = e.DepartmentId
);

執行步驟:

  1. 外部查詢執行(逐行處理):

外部查詢首先讀取 Employee 表中的每一行。

對於 Employee 表中的每一行,查詢都會檢索 DepartmentId、EmployeeId 和 Salary。

外部查詢的逐行處理範例:

  1. 內部查詢執行(相關子查詢):

對於外部查詢中的每一行,都會執行內部查詢 (SELECT MAX(Salary) FROM Employee WHERE DepartmentId = e.DepartmentId)。

子查詢計算目前行DepartmentId對應的部門的最高工資。

外查詢和子查詢之間的關聯是透過 DepartmentId 條件進行的 (WHERE DepartmentId = e.DepartmentId)。

例如:

對於 EmployeeId = 1 的行,子查詢計算 DepartmentId = 101 的最高工資,即 6000。

對於 EmployeeId = 3 的行,子查詢計算 DepartmentId = 102 的最高工資,即 7500。

每行子查詢的執行範例:

  1. 過濾行:

計算出對應DepartmentId的最高薪資後,外層查詢將目前行的Salary與子查詢傳回的最高薪資進行比較。

如果薪資與部門的最高薪資相符,則保留該行。

不匹配的行將被過濾掉。

例如:

EmployeeId = 2 的行將被保留,因為其薪資 6000 與部門 101 的最高薪資相符。

EmployeeId = 1 的行將被過濾掉,因為其薪資 5000 小於部門 101 的最高薪資。

  1. 回傳結果:

外部查詢傳回員工薪資與其部門最高薪資相符的行。

最終結果:

執行流程摘要:

  1. 對於外部查詢中的每一行,執行內部相關子查詢。

  2. 子查詢計算目前DepartmentId的最高工資。

  3. 將員工的薪資與子查詢的結果進行比較。

  4. 過濾並傳回員工薪資與其部門最高薪資相符的行。


Key Differences in Execution Flow:


Performance Considerations:

Inline View Method is more efficient when you are only interested in the highest salary for each department, without needing detailed employee information. It performs the aggregation in a single pass over the data.

Correlated Subquery Method can be slower for large datasets because it executes the subquery for every row in the outer query, potentially leading to many redundant calculations. However, it allows you to retrieve both the department’s highest salary and detailed employee information (e.g., EmployeeId, Name).

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