Leetcode SQL: 1757. Recyclable and Low Fat Products

Improved SQL Code:

SELECT product_id
FROM Products WITH (NOLOCK)
WHERE low_fats = 'Y'
  AND recyclable = 'Y'
  AND product_id IS NOT NULL;

Explanation:

  1. SELECT product_id:
    We are selecting the product_id column from the Products table. This column contains the unique identifiers for each product. Ensuring only relevant columns are selected helps in reducing memory consumption and improving query performance.

    我们从 Products 表中选择 product_id 列,该列包含每个产品的唯一标识符。确保只选择相关列有助于减少内存消耗并提高查询性能。

  2. FROM Products WITH (NOLOCK):
    The FROM clause specifies the table being queried, Products. The WITH (NOLOCK) table hint allows the query to read uncommitted data without placing locks on the table. This is beneficial in high-concurrency environments but can cause the query to read dirty data. It is essential to use this with caution in production environments where data consistency is crucial.

    FROM 子句指定了查询的表,即 Products 表。WITH (NOLOCK) 表提示允许查询在不锁定表的情况下读取未提交的数据。这在高并发环境中很有用,但可能导致读取脏数据。在数据一致性至关重要的生产环境中使用时要谨慎。

  3. WHERE low_fats = ‘Y’ AND recyclable = ‘Y’:
    The WHERE clause filters the rows, ensuring that only products with both low_fats = 'Y' and recyclable = 'Y' are selected. The AND operator ensures that both conditions must be true for a row to be included in the result set.

    WHERE 子句用于筛选行,确保只选择同时满足 low_fats = 'Y'recyclable = 'Y' 的产品。AND 操作符确保两个条件都为真时,行才会包含在结果集中。

  4. AND product_id IS NOT NULL:
    This additional condition ensures that only rows where the product_id is not NULL are returned. In a professional query, it’s important to ensure that you’re not returning invalid or incomplete data. By explicitly checking that product_id is not NULL, we maintain data integrity and avoid potential errors.

    这一额外条件确保只返回 product_idNULL 的行。在专业查询中,确保不返回无效或不完整的数据非常重要。通过明确检查 product_id 不为 NULL,我们维护了数据完整性,并避免了潜在错误。

Key Concepts:

  • WITH (NOLOCK):
    The NOLOCK hint allows reading from tables without acquiring shared locks, improving performance in high-concurrency environments. However, it can cause dirty reads, where uncommitted changes are read by the query. It should be used cautiously in environments where data accuracy is critical.

    WITH (NOLOCK):
    NOLOCK 提示允许在不获取共享锁的情况下从表中读取数据,从而提高高并发环境中的性能。然而,它可能导致脏读,即查询读取未提交的更改。在数据准确性至关重要的环境中应谨慎使用。

  • Checking for NULL Values:
    Adding product_id IS NOT NULL ensures that the query returns only rows with valid product_id values, preventing issues with incomplete data.

    检查 NULL 值:
    添加 product_id IS NOT NULL 确保查询只返回有效 product_id 的行,防止不完整数据带来的问题。

Warnings:

  • NOLOCK and Dirty Reads:
    Using WITH (NOLOCK) may cause the query to read uncommitted or dirty data. This can lead to inconsistent results, particularly in environments where data changes frequently. Be cautious when using this in production systems.

    NOLOCK 和脏读:
    使用 WITH (NOLOCK) 可能导致查询读取未提交的脏数据。在数据频繁变化的环境中,这可能会导致结果不一致。在生产系统中使用时要特别小心。

Summary:

This improved query retrieves the product_id of products that are both low-fat and recyclable. We added the WITH (NOLOCK) hint to improve performance in high-concurrency environments, but care must be taken due to the risk of dirty reads. Additionally, we ensured that the query filters out NULL values for product_id, maintaining data quality.

中文总结:
该改进查询从 Products 表中检索既低脂又可回收产品的 product_id。我们添加了 WITH (NOLOCK) 提示,以提高高并发环境下的性能,但需要注意脏读的风险。此外,我们确保查询排除了 product_idNULL 的行,以保持数据质量。

Tips:

  • Use NOLOCK with Caution:
    If you’re working in a critical environment where data consistency matters, avoid using NOLOCK. Instead, use proper transaction isolation levels like READ COMMITTED or SERIALIZABLE.

    谨慎使用 NOLOCK:
    如果你在数据一致性至关重要的环境中工作,请避免使用 NOLOCK。而是使用适当的事务隔离级别,如 READ COMMITTEDSERIALIZABLE

  • Add Indexes:
    Consider adding indexes on columns used in the WHERE clause (low_fats, recyclable, product_id) to improve query performance, especially in large tables.

    添加索引:
    考虑在 WHERE 子句中使用的列(low_fatsrecyclableproduct_id)上添加索引,以提高查询性能,尤其是在大表中。

Similar SQL Problems:

  1. LeetCode 262: Trips and Users
    Similar to filtering products, this problem involves querying data with multiple conditions.

  2. LeetCode 176: Second Highest Salary
    Demonstrates retrieving rows based on conditions, useful for multi-condition queries.

  3. LeetCode 181: Employees Earning More Than Their Managers
    Focuses on filtering rows with multiple conditions, a fundamental SQL skill.

  4. LeetCode 183: Customers Who Never Order
    Involves filtering based on specific conditions, useful for practicing condition-based queries.

  5. LeetCode 196: Delete Duplicate Emails
    This problem involves identifying and filtering rows, a good practice for refining SQL skills.

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