Build a Practical Combine and Summarize Data Example in SQL and Relational Databases

Define the build target

For Combine and Summarize Data, return each customer with order count and total order value, including customers with no orders, then filter to customers whose total exceeds a chosen threshold. Build the boundary case using this implementation lens: Use relational tables, keys, transactions, SQL result sets, constraints, query plans, and database state as the concrete model.

Keep the Combine and Summarize Data build centered on these technical constraints: Choose the join key from the relationship between tables. Use INNER JOIN when unmatched rows should be excluded and LEFT JOIN when rows from the left table must remain. Apply them through this path lens: Use relational tables, keys, transactions, SQL result sets, constraints, query plans, and database state as the concrete model. Use relational tables, keys, transactions, SQL result sets, constraints, query plans, and database state as the concrete model.

Implement the core behavior

Implement Combine and Summarize Data around the module artifact—a grouped SQL report that combines related tables without double-counting—and keep the implementation specific to this path context: Use relational tables, keys, transactions, SQL result sets, constraints, query plans, and database state as the concrete model.

SELECT
  c.id,
  c.name,
  COUNT(o.id) AS order_count,
  COALESCE(SUM(o.total), 0) AS order_total
FROM customers AS c
LEFT JOIN orders AS o ON o.customer_id = c.id
GROUP BY c.id, c.name
HAVING COALESCE(SUM(o.total), 0) >= 100
ORDER BY order_total DESC;

psql -f report.sql

One row per matching customer, including correct order_count and order_total values.

practice/\n├── README.md\n├── combine-and-summarize-data-build.sql\n└── evidence/\n    └── expected-result.txt

Run the complete path

Run one realistic Combine and Summarize Data case end to end and record the required evidence: query output, expected row counts, and a check for unmatched or duplicated rows. Interpret the result through this path context: Use relational tables, keys, transactions, SQL result sets, constraints, query plans, and database state as the concrete model.

Change one meaningful condition

Modify one condition central to Combine and Summarize Data using this path context: Use relational tables, keys, transactions, SQL result sets, constraints, query plans, and database state as the concrete model. Predict the new result before rerunning the same workflow.

Verify the artifact

Your deliverable is a grouped SQL report that combines related tables without double-counting.

Common mistakes to avoid

• If totals are too large, inspect whether an extra join created duplicate combinations.
• If a customer disappears, verify whether INNER JOIN should be LEFT JOIN.
• If the database rejects a selected column, check whether it belongs in GROUP BY or should be aggregated.
• Use a simple SELECT of join keys before adding aggregation.