Leetcode SQL: 1581. Customer Who Visited but Did Not Make Any Transactions

SQL Code:

SELECT customer_id, COUNT(*)
FROM Visits v WITH (NOLOCK)
LEFT JOIN Transactions t WITH (NOLOCK)
ON v.visit_id = t.visit_id
WHERE t.transaction_id IS NULL
GROUP BY customer_id;

Explanation:

  1. *SELECT customer_id, COUNT()**:
    This line specifies that we want to retrieve the customer_id from the Visits table and count how many times the customer visited without making any transactions.

    • customer_id: Represents the unique identifier for each customer.
    • COUNT(*): Counts the number of visits where no transaction was made.

    这一行指定我们要从 Visits 表中获取 customer_id,并计算该客户未进行任何交易的访问次数。

    • customer_id: 表示每个客户的唯一标识符。
    • COUNT(*): 统计没有进行交易的访问次数。
  2. FROM Visits v WITH (NOLOCK):
    The FROM clause specifies that we are querying data from the Visits table and aliasing it as v. The WITH (NOLOCK) hint allows us to read data without locking the table, which can improve performance in high-concurrency environments.

    FROM 子句指定我们正在从 Visits 表中查询数据,并将其别名为 vWITH (NOLOCK) 提示允许我们在不锁定表的情况下读取数据,这在高并发环境下可以提高性能。

  3. LEFT JOIN Transactions t WITH (NOLOCK) ON v.visit_id = t.visit_id:
    The LEFT JOIN is used to join the Visits table (v) with the Transactions table (t) based on the condition that the visit_id from Visits matches the visit_id in Transactions. The WITH (NOLOCK) hint allows the query to read data without placing shared locks on the Transactions table.

    LEFT JOIN 用于将 Visits 表 (v) 与 Transactions 表 (t) 连接,条件是 Visits 表中的 visit_idTransactions 表中的 visit_id 匹配。WITH (NOLOCK) 提示允许查询在不锁定 Transactions 表的情况下读取数据。

  4. WHERE t.transaction_id IS NULL:
    The WHERE clause filters out the rows where there was no transaction associated with the visit. If there is no matching transaction_id, it means that the customer visited but did not make any transactions.

    WHERE 子句筛选出没有与访问关联的交易记录的行。如果没有匹配的 transaction_id,则表示客户访问了但没有进行任何交易。

  5. GROUP BY customer_id:
    The GROUP BY clause groups the results by customer_id, ensuring that we count the visits where no transactions were made for each customer.

    GROUP BY 子句按 customer_id 对结果进行分组,确保我们统计每个客户没有进行交易的访问次数。

Key Concepts:

  • LEFT JOIN:
    The LEFT JOIN ensures that all rows from the Visits table are included in the result set, even if there is no matching transaction_id in the Transactions table. If no transaction is associated with a visit, the transaction_id will be NULL.

    LEFT JOIN:
    LEFT JOIN 确保 Visits 表中的所有行都包含在结果集中,即使在 Transactions 表中没有匹配的 transaction_id。如果访问没有关联交易,transaction_id 将为 NULL

  • WHERE IS NULL:
    The WHERE t.transaction_id IS NULL condition filters the results to only include visits where no transactions occurred. This helps identify customers who visited but did not make any purchases.

    WHERE IS NULL:
    WHERE t.transaction_id IS NULL 条件筛选出没有交易发生的访问记录。这有助于识别访问但没有购买的客户。

Warnings:

  • NOLOCK:
    Using WITH (NOLOCK) can improve performance by allowing the query to read data without locking tables. However, it may lead to reading uncommitted or dirty data, which could cause inconsistent results.

    NOLOCK:
    使用 WITH (NOLOCK) 可以通过允许查询在不锁定表的情况下读取数据来提高性能。然而,它可能导致读取未提交或脏数据,这可能会导致结果不一致。

Summary:

This query retrieves the customer_id of customers who visited but did not make any transactions, along with the count of such visits. The LEFT JOIN ensures that all visits are included, even if no transactions were made. The WITH (NOLOCK) hint improves performance, but be cautious of the potential for dirty reads.

中文总结:
该查询检索了访问但没有进行任何交易的客户的 customer_id,以及此类访问的次数。LEFT JOIN 确保所有访问都被包括,即使没有进行交易。WITH (NOLOCK) 提示提高了性能,但需要注意可能出现的脏读风险。

Tips:

  • Indexing:
    Ensure that there are indexes on the visit_id and transaction_id columns to optimize the performance of the JOIN operation, especially if the tables are large.

    索引:
    确保在 visit_idtransaction_id 列上创建索引,以优化 JOIN 操作的性能,特别是当表很大的时候。

  • Handling Large Datasets:
    If you are working with large datasets, consider partitioning the Visits and Transactions tables to improve query performance.

    处理大数据集:
    如果处理大数据集,考虑对 VisitsTransactions 表进行分区以提高查询性能。

Similar SQL Problems:

  1. LeetCode 176: Second Highest Salary
    This problem involves retrieving specific data from a table while handling conditions, much like filtering visits where no transactions occurred.

  2. LeetCode 181: Employees Earning More Than Their Managers
    This problem focuses on filtering data based on conditions, similar to identifying visits with no transactions.

  3. LeetCode 183: Customers Who Never Order
    This problem filters customer data based on conditions, similar to how this query filters visits without transactions.

  4. LeetCode 196: Delete Duplicate Emails
    This problem deals with identifying and filtering rows based on conditions, just like filtering customers based on visits and transactions.

  5. LeetCode 184: Department Highest Salary
    This problem filters rows based on specific conditions, similar to filtering visits where no transactions occurred.


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