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‎src/main/java/g3501_3600/s3554_find_category_recommendation_pairs/readme.md

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3554\. Find Category Recommendation Pairs
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Table: `ProductPurchases`
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+-------------+------+
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| Column Name | Type |
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+-------------+------+
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| user_id | int |
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| product_id | int |
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| quantity | int |
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+-------------+------+
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(user_id, product_id) is the unique identifier for this table.
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Each row represents a purchase of a product by a user in a specific quantity.
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Table: `ProductInfo`
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+-------------+---------+
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| Column Name | Type |
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+-------------+---------+
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| product_id | int |
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| category | varchar |
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| price | decimal |
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+-------------+---------+
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product_id is the unique identifier for this table.
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Each row assigns a category and price to a product.
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Amazon wants to understand shopping patterns across product categories. Write a solution to:
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1. Find all **category pairs** (where `category1` < `category2`)
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2. For **each category pair**, determine the number of **unique** **customers** who purchased products from **both** categories
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A category pair is considered **reportable** if at least `3` different customers have purchased products from both categories.
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Return _the result table of reportable category pairs ordered by **customer\_count** in **descending** order, and in case of a tie, by **category1** in **ascending** order lexicographically, and then by **category2** in **ascending** order._
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The result format is in the following example.
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**Example:**
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**Input:**
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ProductPurchases table:
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+---------+------------+----------+
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| user_id | product_id | quantity |
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+---------+------------+----------+
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| 1 | 101 | 2 |
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| 1 | 102 | 1 |
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| 1 | 201 | 3 |
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| 1 | 301 | 1 |
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| 2 | 101 | 1 |
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| 2 | 102 | 2 |
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| 2 | 103 | 1 |
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| 2 | 201 | 5 |
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| 3 | 101 | 2 |
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| 3 | 103 | 1 |
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| 3 | 301 | 4 |
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| 3 | 401 | 2 |
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| 4 | 101 | 1 |
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| 4 | 201 | 3 |
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| 4 | 301 | 1 |
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| 4 | 401 | 2 |
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| 5 | 102 | 2 |
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| 5 | 103 | 1 |
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| 5 | 201 | 2 |
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| 5 | 202 | 3 |
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+---------+------------+----------+
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ProductInfo table:
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+------------+-------------+-------+
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| product_id | category | price |
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+------------+-------------+-------+
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| 101 | Electronics | 100 |
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| 102 | Books | 20 |
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| 103 | Books | 35 |
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| 201 | Clothing | 45 |
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| 202 | Clothing | 60 |
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| 301 | Sports | 75 |
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| 401 | Kitchen | 50 |
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+------------+-------------+-------+
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**Output:**
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+-------------+-------------+----------------+
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| category1 | category2 | customer_count |
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+-------------+-------------+----------------+
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| Books | Clothing | 3 |
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| Books | Electronics | 3 |
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| Clothing | Electronics | 3 |
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| Electronics | Sports | 3 |
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+-------------+-------------+----------------+
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**Explanation:**
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* **Books-Clothing**:
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* User 1 purchased products from Books (102) and Clothing (201)
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* User 2 purchased products from Books (102, 103) and Clothing (201)
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* User 5 purchased products from Books (102, 103) and Clothing (201, 202)
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* Total: 3 customers purchased from both categories
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* **Books-Electronics**:
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* User 1 purchased products from Books (102) and Electronics (101)
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* User 2 purchased products from Books (102, 103) and Electronics (101)
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* User 3 purchased products from Books (103) and Electronics (101)
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* Total: 3 customers purchased from both categories
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* **Clothing-Electronics**:
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* User 1 purchased products from Clothing (201) and Electronics (101)
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* User 2 purchased products from Clothing (201) and Electronics (101)
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* User 4 purchased products from Clothing (201) and Electronics (101)
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* Total: 3 customers purchased from both categories
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* **Electronics-Sports**:
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* User 1 purchased products from Electronics (101) and Sports (301)
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* User 3 purchased products from Electronics (101) and Sports (301)
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* User 4 purchased products from Electronics (101) and Sports (301)
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* Total: 3 customers purchased from both categories
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* Other category pairs like Clothing-Sports (only 2 customers: Users 1 and 4) and Books-Kitchen (only 1 customer: User 3) have fewer than 3 shared customers and are not included in the result.
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The result is ordered by customer\_count in descending order. Since all pairs have the same customer\_count of 3, they are ordered by category1 (then category2) in ascending order.

‎src/main/java/g3501_3600/s3554_find_category_recommendation_pairs/script.sql

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# Write your MySQL query statement below
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# #Hard #Database #2025_05_22_Time_623_ms_(82.76%)_Space_0.0_MB_(100.00%)
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SELECT
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pi1.category AS category1,
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pi2.category AS category2,
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COUNT(DISTINCT pp1.user_id) AS customer_count
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FROM
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ProductPurchases pp1,
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ProductPurchases pp2,
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ProductInfo pi1,
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ProductInfo pi2
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WHERE
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pp1.user_id = pp2.user_id
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AND pi1.category < pi2.category
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AND pp1.product_id = pi1.product_id
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AND pp2.product_id = pi2.product_id
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GROUP BY
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pi1.category,
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pi2.category
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HAVING
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COUNT(DISTINCT pp1.user_id) >= 3
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ORDER BY
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customer_count DESC,
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category1 ASC,
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category2 ASC;

‎src/test/java/g3501_3600/s3554_find_category_recommendation_pairs/MysqlTest.java

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package g3501_3600.s3554_find_category_recommendation_pairs;
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import static org.hamcrest.CoreMatchers.equalTo;
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import static org.hamcrest.MatcherAssert.assertThat;
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import java.io.BufferedReader;
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import java.io.FileNotFoundException;
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import java.io.FileReader;
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import java.sql.Connection;
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import java.sql.ResultSet;
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import java.sql.SQLException;
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import java.sql.Statement;
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import java.util.stream.Collectors;
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import javax.sql.DataSource;
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import org.junit.jupiter.api.Test;
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import org.zapodot.junit.db.annotations.EmbeddedDatabase;
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import org.zapodot.junit.db.annotations.EmbeddedDatabaseTest;
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import org.zapodot.junit.db.common.CompatibilityMode;
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@EmbeddedDatabaseTest(
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compatibilityMode = CompatibilityMode.MySQL,
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initialSqls =
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"CREATE TABLE ProductPurchases(user_id INTEGER, product_id INTEGER"
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+ ", quantity INTEGER); "
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+ "INSERT INTO ProductPurchases(user_id, product_id, quantity)"
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+ " VALUES "
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+ "(1, 101, 2), "
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+ "(1, 102, 1), "
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+ "(1, 201, 3), "
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+ "(1, 301, 1), "
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+ "(2, 101, 1), "
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+ "(2, 102, 2), "
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+ "(2, 103, 1), "
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+ "(2, 201, 5), "
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+ "(3, 101, 2), "
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+ "(3, 103, 1), "
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+ "(3, 301, 4), "
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+ "(3, 401, 2), "
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+ "(4, 101, 1), "
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+ "(4, 201, 3), "
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+ "(4, 301, 1), "
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+ "(4, 401, 2), "
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+ "(5, 102, 2), "
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+ "(5, 103, 1), "
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+ "(5, 201, 2), "
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+ "(5, 202, 3);"
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+ "CREATE TABLE ProductInfo(product_id INTEGER, category VARCHAR(255)"
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+ ", price INTEGER); "
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+ "INSERT INTO ProductInfo(product_id, category, price) VALUES "
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+ "(101, 'Electronics', 100), "
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+ "(102, 'Books', 20), "
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+ "(103, 'Books', 35), "
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+ "(201, 'Clothing', 45), "
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+ "(202, 'Clothing', 60), "
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+ "(301, 'Sports', 75), "
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+ "(401, 'Kitchen', 50);")
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class MysqlTest {
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@Test
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void testScript(@EmbeddedDatabase DataSource dataSource)
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throws SQLException, FileNotFoundException {
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try (final Connection connection = dataSource.getConnection()) {
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try (final Statement statement = connection.createStatement();
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final ResultSet resultSet =
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statement.executeQuery(
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new BufferedReader(
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new FileReader(
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"src/main/java/g3501_3600/"
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+ "s3554_find_category_recommendation_pairs/"
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+ "script.sql"))
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.lines()
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.collect(Collectors.joining("\n"))
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.replaceAll("#.*?\\r?\\n", ""))) {
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assertThat(resultSet.next(), equalTo(true));
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assertThat(resultSet.getNString(1), equalTo("Books"));
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assertThat(resultSet.getNString(2), equalTo("Clothing"));
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assertThat(resultSet.getNString(3), equalTo("3"));
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assertThat(resultSet.next(), equalTo(true));
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assertThat(resultSet.getNString(1), equalTo("Books"));
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assertThat(resultSet.getNString(2), equalTo("Electronics"));
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assertThat(resultSet.getNString(3), equalTo("3"));
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assertThat(resultSet.next(), equalTo(true));
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assertThat(resultSet.getNString(1), equalTo("Clothing"));
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assertThat(resultSet.getNString(2), equalTo("Electronics"));
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assertThat(resultSet.getNString(3), equalTo("3"));
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assertThat(resultSet.next(), equalTo(true));
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assertThat(resultSet.getNString(1), equalTo("Electronics"));
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assertThat(resultSet.getNString(2), equalTo("Sports"));
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assertThat(resultSet.getNString(3), equalTo("3"));
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assertThat(resultSet.next(), equalTo(false));
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}
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}
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}
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}

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