Complete SQL assignment 2 by mohammadgoudarzirad · Pull Request #2 · mohammadgoudarzirad/sql

mohammadgoudarzirad · 2026-11-07T02:39:27Z

What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)

Assignment 2 SQL queries

What did you learn from the changes you have made?

SQL queries, joins, window functions, and updating tables

Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?

N/A

Were there any challenges? If so, what issue(s) did you face? How did you overcome it?

I tested them step by step and fixed errors

How were these changes tested?

I ran the SQL queries in DB Browser for SQLite and checked the results

A reference to a related issue in your repository (if applicable)

N/A

Checklist

[ *] I can confirm that my changes are working as intended

github-actions · 2026-11-07T02:39:55Z

SQL Assignment 2 feedback

SQL checks only. ERDs, written responses, and rubric point totals require instructor marking.

02_activities/assignments/DC_Cohort/assignment2.sql

Query 1: ✅ Correct

All product descriptions and NULL replacements are correct.

SQL and output

SELECT 
product_name || ', ' ||
COALESCE(product_size, '') ||
' (' ||
COALESCE(product_qty_type, 'unit') ||
')'
FROM product;

[
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Habanero Peppers - Organic, medium (lbs)"
  },
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Jalapeno Peppers - Organic, small (lbs)"
  },
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Poblano Peppers - Organic, large (unit)"
  }
]

Query 2: ✅ Correct

Visit dates are numbered correctly for each customer.

SQL and output

SELECT
    customer_id,
    market_date,
    DENSE_RANK() OVER (
        PARTITION BY customer_id
        ORDER BY market_date
    ) AS visit_number
FROM customer_purchases
WHERE market_date < '2022-04-29'
ORDER BY customer_id, market_date;

[
  {
    "customer_id": 1,
    "market_date": "2022-04-08",
    "visit_number": 1
  },
  {
    "customer_id": 1,
    "market_date": "2022-04-15",
    "visit_number": 2
  },
  {
    "customer_id": 1,
    "market_date": "2022-04-19",
    "visit_number": 3
  }
]

Query 3: ✅ Correct

Only each customer's most recent visit is returned.

SQL and output

SELECT DISTINCT
    customer_id,
    market_date,
    visit_number
FROM (
    SELECT
        customer_id,
        market_date,
        DENSE_RANK() OVER (
            PARTITION BY customer_id
            ORDER BY market_date DESC
        ) AS visit_number
    FROM customer_purchases
) AS ranked_visits
WHERE visit_number = 1;

[
  {
    "customer_id": 1,
    "market_date": "2023-10-13",
    "visit_number": 1
  },
  {
    "customer_id": 2,
    "market_date": "2023-10-13",
    "visit_number": 1
  },
  {
    "customer_id": 3,
    "market_date": "2023-10-10",
    "visit_number": 1
  }
]

Query 4: ✅ Correct

The purchase count is correct for every customer and product.

SQL and output

SELECT
    customer_id,
    product_id,
    market_date,
    COUNT(*) OVER (
        PARTITION BY customer_id, product_id
    ) AS purchase_count
FROM customer_purchases
WHERE market_date < '2022-04-29'
ORDER BY customer_id, product_id, market_date;

[
  {
    "customer_id": 1,
    "product_id": 4,
    "market_date": "2022-04-19",
    "purchase_count": 2
  },
  {
    "customer_id": 1,
    "product_id": 4,
    "market_date": "2022-04-26",
    "purchase_count": 2
  },
  {
    "customer_id": 1,
    "product_id": 5,
    "market_date": "2022-04-08",
    "purchase_count": 6
  }
]

Query 5: ✅ Correct

Product descriptions are extracted and trimmed correctly.

SQL and output

SELECT
    product_name,
    CASE
        WHEN INSTR(product_name, '-') > 0
        THEN TRIM(
            SUBSTR(
                product_name,
                INSTR(product_name, '-') + 1
            )
        )
        ELSE NULL
    END AS description
FROM product;

[
  {
    "product_name": "Habanero Peppers - Organic",
    "description": "Organic"
  },
  {
    "product_name": "Jalapeno Peppers - Organic",
    "description": "Organic"
  },
  {
    "product_name": "Poblano Peppers - Organic",
    "description": "Organic"
  }
]

Query 6: ✅ Correct

Only product sizes containing a number are returned.

SQL and output

SELECT
    product_name,
    product_size
FROM product
WHERE product_size REGEXP '[0-9]';

[
  {
    "product_name": "Banana Peppers - Jar",
    "product_size": "8 oz"
  },
  {
    "product_name": "Whole Wheat Bread",
    "product_size": "1.5 lbs"
  },
  {
    "product_name": "Apple Pie",
    "product_size": "10\""
  }
]

Query 7: ✅ Correct

The highest and lowest sales dates and totals are correct.

SQL and output

WITH daily_sales AS (
    SELECT
        market_date,
        SUM(quantity * cost_per_quantity) AS total_sales
    FROM customer_purchases
    GROUP BY market_date
),
ranked_sales AS (
    SELECT
        market_date,
        total_sales,
        RANK() OVER (ORDER BY total_sales DESC) AS best_rank,
        RANK() OVER (ORDER BY total_sales ASC) AS worst_rank
    FROM daily_sales
)
SELECT
    market_date,
    total_sales
FROM ranked_sales
WHERE best_rank = 1

UNION

SELECT
    market_date,
    total_sales
FROM ranked_sales
WHERE worst_rank = 1;

[
  {
    "market_date": "2022-12-20",
    "total_sales": 979
  },
  {
    "market_date": "2023-04-07",
    "total_sales": 272.5
  }
]

Query 8: ✅ Correct

Possible revenue is correct for every vendor and product.

SQL and output

SELECT
    v.vendor_name,
    p.product_name,
    SUM(5 * vi.original_price) AS potential_revenue
FROM (
    SELECT DISTINCT
        vendor_id,
        product_id,
        original_price
    FROM vendor_inventory
) AS vi

JOIN vendor AS v
    ON vi.vendor_id = v.vendor_id

JOIN product AS p
    ON vi.product_id = p.product_id

CROSS JOIN customer AS c

GROUP BY
    v.vendor_name,
    p.product_name;

[
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Apple Pie",
    "potential_revenue": 2340
  },
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Cherry Pie",
    "potential_revenue": 2340
  },
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Whole Wheat Bread",
    "potential_revenue": 845
  }
]

Query 9: ✅ Correct

Unit products and current snapshot timestamps are correct.

SQL and output

CREATE TABLE product_units AS
SELECT
    *,
    CURRENT_TIMESTAMP AS snapshot_timestamp
FROM product
WHERE product_qty_type = 'unit';

Query 10: ✅ Correct

One product with a current timestamp was inserted.

SQL and output

SELECT *
FROM product_units
WHERE product_name = 'Apple Pie';

INSERT INTO product_units (
    product_id,
    product_name,
    product_size,
    product_category_id,
    product_qty_type,
    snapshot_timestamp
)
VALUES (
    7,
    'Apple Pie',
    '10"',
    3,
    'unit',
    CURRENT_TIMESTAMP
);

SELECT *
FROM product_units
WHERE product_name = 'Apple Pie'
ORDER BY snapshot_timestamp;

[
  {
    "product_id": 7,
    "product_name": "Apple Pie",
    "product_size": "10\"",
    "product_category_id": 3,
    "product_qty_type": "unit",
    "snapshot_timestamp": "2026-11-07 02:39:54"
  },
  {
    "product_id": 7,
    "product_name": "Apple Pie",
    "product_size": "10\"",
    "product_category_id": 3,
    "product_qty_type": "unit",
    "snapshot_timestamp": "2026-11-07 02:39:55"
  }
]

Query 11: ✅ Correct

Only the older copy was removed; the inserted copy remains.

SQL and output

DELETE FROM product_units
WHERE product_id = 7
  AND snapshot_timestamp = (
      SELECT MIN(snapshot_timestamp)
      FROM product_units
      WHERE product_id = 7
  );

Query 12: ❌ Error

The SQL could not be executed or assessed.

no such column: current_quantity

SELECT
    pu.product_id,
    pu.product_name,
    COALESCE(
        (
            SELECT vi.quantity
            FROM vendor_inventory AS vi
            WHERE vi.product_id = pu.product_id
            ORDER BY vi.market_date DESC
            LIMIT 1
        ),
        0
    ) AS latest_quantity
FROM product_units AS pu;


UPDATE product_units
SET current_quantity = COALESCE(
    (
        SELECT vi.quantity
        FROM vendor_inventory AS vi
        WHERE vi.product_id = product_units.product_id
        ORDER BY vi.market_date DESC
        LIMIT 1
    ),
    0
);


SELECT
    product_id,
    product_name,
    current_quantity
FROM product_units;

github-actions · 2026-11-07T02:52:03Z

SQL Assignment 2 feedback

SQL checks only. ERDs, written responses, and rubric point totals require instructor marking.

02_activities/assignments/DC_Cohort/assignment2.sql

Query 1: ✅ Correct

All product descriptions and NULL replacements are correct.

SQL and output

SELECT 
product_name || ', ' ||
COALESCE(product_size, '') ||
' (' ||
COALESCE(product_qty_type, 'unit') ||
')'
FROM product;

[
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Habanero Peppers - Organic, medium (lbs)"
  },
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Jalapeno Peppers - Organic, small (lbs)"
  },
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Poblano Peppers - Organic, large (unit)"
  }
]

Query 2: ✅ Correct

Visit dates are numbered correctly for each customer.

SQL and output

SELECT
    customer_id,
    market_date,
    DENSE_RANK() OVER (
        PARTITION BY customer_id
        ORDER BY market_date
    ) AS visit_number
FROM customer_purchases
WHERE market_date < '2022-04-29'
ORDER BY customer_id, market_date;

[
  {
    "customer_id": 1,
    "market_date": "2022-04-08",
    "visit_number": 1
  },
  {
    "customer_id": 1,
    "market_date": "2022-04-15",
    "visit_number": 2
  },
  {
    "customer_id": 1,
    "market_date": "2022-04-19",
    "visit_number": 3
  }
]

Query 3: ✅ Correct

Only each customer's most recent visit is returned.

SQL and output

SELECT DISTINCT
    customer_id,
    market_date,
    visit_number
FROM (
    SELECT
        customer_id,
        market_date,
        DENSE_RANK() OVER (
            PARTITION BY customer_id
            ORDER BY market_date DESC
        ) AS visit_number
    FROM customer_purchases
) AS ranked_visits
WHERE visit_number = 1;

[
  {
    "customer_id": 1,
    "market_date": "2023-10-13",
    "visit_number": 1
  },
  {
    "customer_id": 2,
    "market_date": "2023-10-13",
    "visit_number": 1
  },
  {
    "customer_id": 3,
    "market_date": "2023-10-10",
    "visit_number": 1
  }
]

Query 4: ✅ Correct

The purchase count is correct for every customer and product.

SQL and output

SELECT
    customer_id,
    product_id,
    market_date,
    COUNT(*) OVER (
        PARTITION BY customer_id, product_id
    ) AS purchase_count
FROM customer_purchases
WHERE market_date < '2022-04-29'
ORDER BY customer_id, product_id, market_date;

[
  {
    "customer_id": 1,
    "product_id": 4,
    "market_date": "2022-04-19",
    "purchase_count": 2
  },
  {
    "customer_id": 1,
    "product_id": 4,
    "market_date": "2022-04-26",
    "purchase_count": 2
  },
  {
    "customer_id": 1,
    "product_id": 5,
    "market_date": "2022-04-08",
    "purchase_count": 6
  }
]

Query 5: ✅ Correct

Product descriptions are extracted and trimmed correctly.

SQL and output

SELECT
    product_name,
    CASE
        WHEN INSTR(product_name, '-') > 0
        THEN TRIM(
            SUBSTR(
                product_name,
                INSTR(product_name, '-') + 1
            )
        )
        ELSE NULL
    END AS description
FROM product;

[
  {
    "product_name": "Habanero Peppers - Organic",
    "description": "Organic"
  },
  {
    "product_name": "Jalapeno Peppers - Organic",
    "description": "Organic"
  },
  {
    "product_name": "Poblano Peppers - Organic",
    "description": "Organic"
  }
]

Query 6: ✅ Correct

Only product sizes containing a number are returned.

SQL and output

SELECT
    product_name,
    product_size
FROM product
WHERE product_size REGEXP '[0-9]';

[
  {
    "product_name": "Banana Peppers - Jar",
    "product_size": "8 oz"
  },
  {
    "product_name": "Whole Wheat Bread",
    "product_size": "1.5 lbs"
  },
  {
    "product_name": "Apple Pie",
    "product_size": "10\""
  }
]

Query 7: ✅ Correct

The highest and lowest sales dates and totals are correct.

SQL and output

WITH daily_sales AS (
    SELECT
        market_date,
        SUM(quantity * cost_per_quantity) AS total_sales
    FROM customer_purchases
    GROUP BY market_date
),
ranked_sales AS (
    SELECT
        market_date,
        total_sales,
        RANK() OVER (ORDER BY total_sales DESC) AS best_rank,
        RANK() OVER (ORDER BY total_sales ASC) AS worst_rank
    FROM daily_sales
)
SELECT
    market_date,
    total_sales
FROM ranked_sales
WHERE best_rank = 1

UNION

SELECT
    market_date,
    total_sales
FROM ranked_sales
WHERE worst_rank = 1;

[
  {
    "market_date": "2022-12-20",
    "total_sales": 979
  },
  {
    "market_date": "2023-04-07",
    "total_sales": 272.5
  }
]

Query 8: ✅ Correct

Possible revenue is correct for every vendor and product.

SQL and output

SELECT
    v.vendor_name,
    p.product_name,
    SUM(5 * vi.original_price) AS potential_revenue
FROM (
    SELECT DISTINCT
        vendor_id,
        product_id,
        original_price
    FROM vendor_inventory
) AS vi

JOIN vendor AS v
    ON vi.vendor_id = v.vendor_id

JOIN product AS p
    ON vi.product_id = p.product_id

CROSS JOIN customer AS c

GROUP BY
    v.vendor_name,
    p.product_name;

[
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Apple Pie",
    "potential_revenue": 2340
  },
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Cherry Pie",
    "potential_revenue": 2340
  },
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Whole Wheat Bread",
    "potential_revenue": 845
  }
]

Query 9: ✅ Correct

Unit products and current snapshot timestamps are correct.

SQL and output

CREATE TABLE product_units AS
SELECT
    *,
    CURRENT_TIMESTAMP AS snapshot_timestamp
FROM product
WHERE product_qty_type = 'unit';

Query 10: ✅ Correct

One product with a current timestamp was inserted.

SQL and output

SELECT *
FROM product_units
WHERE product_name = 'Apple Pie';

INSERT INTO product_units (
    product_id,
    product_name,
    product_size,
    product_category_id,
    product_qty_type,
    snapshot_timestamp
)
VALUES (
    7,
    'Apple Pie',
    '10"',
    3,
    'unit',
    CURRENT_TIMESTAMP
);

SELECT *
FROM product_units
WHERE product_name = 'Apple Pie'
ORDER BY snapshot_timestamp;

[
  {
    "product_id": 7,
    "product_name": "Apple Pie",
    "product_size": "10\"",
    "product_category_id": 3,
    "product_qty_type": "unit",
    "snapshot_timestamp": "2026-11-07 02:52:01"
  },
  {
    "product_id": 7,
    "product_name": "Apple Pie",
    "product_size": "10\"",
    "product_category_id": 3,
    "product_qty_type": "unit",
    "snapshot_timestamp": "2026-11-07 02:52:02"
  }
]

Query 11: ✅ Correct

Only the older copy was removed; the inserted copy remains.

SQL and output

DELETE FROM product_units
WHERE product_id = 7
  AND snapshot_timestamp = (
      SELECT MIN(snapshot_timestamp)
      FROM product_units
      WHERE product_id = 7
  );

Query 12: ❌ Error

The SQL could not be executed or assessed.

near "ALTER": syntax error

SELECT
  ALTER TABLE product_units
ADD current_quantity INT;

UPDATE product_units
SET current_quantity = COALESCE(
    (
        SELECT vi.quantity
        FROM vendor_inventory AS vi
        WHERE vi.product_id = product_units.product_id
        ORDER BY vi.market_date DESC
        LIMIT 1
    ),
    0
);

github-actions · 2026-11-07T02:56:22Z

SQL Assignment 2 feedback

SQL checks only. ERDs, written responses, and rubric point totals require instructor marking.

02_activities/assignments/DC_Cohort/assignment2.sql

Query 1: ✅ Correct

All product descriptions and NULL replacements are correct.

SQL and output

SELECT 
product_name || ', ' ||
COALESCE(product_size, '') ||
' (' ||
COALESCE(product_qty_type, 'unit') ||
')'
FROM product;

[
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Habanero Peppers - Organic, medium (lbs)"
  },
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Jalapeno Peppers - Organic, small (lbs)"
  },
  {
    "product_name || ', ' ||\nCOALESCE(product_size, '') ||\n' (' ||\nCOALESCE(product_qty_type, 'unit') ||\n')'": "Poblano Peppers - Organic, large (unit)"
  }
]

Query 2: ✅ Correct

Visit dates are numbered correctly for each customer.

SQL and output

SELECT
    customer_id,
    market_date,
    DENSE_RANK() OVER (
        PARTITION BY customer_id
        ORDER BY market_date
    ) AS visit_number
FROM customer_purchases
WHERE market_date < '2022-04-29'
ORDER BY customer_id, market_date;

[
  {
    "customer_id": 1,
    "market_date": "2022-04-08",
    "visit_number": 1
  },
  {
    "customer_id": 1,
    "market_date": "2022-04-15",
    "visit_number": 2
  },
  {
    "customer_id": 1,
    "market_date": "2022-04-19",
    "visit_number": 3
  }
]

Query 3: ✅ Correct

Only each customer's most recent visit is returned.

SQL and output

SELECT DISTINCT
    customer_id,
    market_date,
    visit_number
FROM (
    SELECT
        customer_id,
        market_date,
        DENSE_RANK() OVER (
            PARTITION BY customer_id
            ORDER BY market_date DESC
        ) AS visit_number
    FROM customer_purchases
) AS ranked_visits
WHERE visit_number = 1;

[
  {
    "customer_id": 1,
    "market_date": "2023-10-13",
    "visit_number": 1
  },
  {
    "customer_id": 2,
    "market_date": "2023-10-13",
    "visit_number": 1
  },
  {
    "customer_id": 3,
    "market_date": "2023-10-10",
    "visit_number": 1
  }
]

Query 4: ✅ Correct

The purchase count is correct for every customer and product.

SQL and output

SELECT
    customer_id,
    product_id,
    market_date,
    COUNT(*) OVER (
        PARTITION BY customer_id, product_id
    ) AS purchase_count
FROM customer_purchases
WHERE market_date < '2022-04-29'
ORDER BY customer_id, product_id, market_date;

[
  {
    "customer_id": 1,
    "product_id": 4,
    "market_date": "2022-04-19",
    "purchase_count": 2
  },
  {
    "customer_id": 1,
    "product_id": 4,
    "market_date": "2022-04-26",
    "purchase_count": 2
  },
  {
    "customer_id": 1,
    "product_id": 5,
    "market_date": "2022-04-08",
    "purchase_count": 6
  }
]

Query 5: ✅ Correct

Product descriptions are extracted and trimmed correctly.

SQL and output

SELECT
    product_name,
    CASE
        WHEN INSTR(product_name, '-') > 0
        THEN TRIM(
            SUBSTR(
                product_name,
                INSTR(product_name, '-') + 1
            )
        )
        ELSE NULL
    END AS description
FROM product;

[
  {
    "product_name": "Habanero Peppers - Organic",
    "description": "Organic"
  },
  {
    "product_name": "Jalapeno Peppers - Organic",
    "description": "Organic"
  },
  {
    "product_name": "Poblano Peppers - Organic",
    "description": "Organic"
  }
]

Query 6: ✅ Correct

Only product sizes containing a number are returned.

SQL and output

SELECT
    product_name,
    product_size
FROM product
WHERE product_size REGEXP '[0-9]';

[
  {
    "product_name": "Banana Peppers - Jar",
    "product_size": "8 oz"
  },
  {
    "product_name": "Whole Wheat Bread",
    "product_size": "1.5 lbs"
  },
  {
    "product_name": "Apple Pie",
    "product_size": "10\""
  }
]

Query 7: ✅ Correct

The highest and lowest sales dates and totals are correct.

SQL and output

WITH daily_sales AS (
    SELECT
        market_date,
        SUM(quantity * cost_per_quantity) AS total_sales
    FROM customer_purchases
    GROUP BY market_date
),
ranked_sales AS (
    SELECT
        market_date,
        total_sales,
        RANK() OVER (ORDER BY total_sales DESC) AS best_rank,
        RANK() OVER (ORDER BY total_sales ASC) AS worst_rank
    FROM daily_sales
)
SELECT
    market_date,
    total_sales
FROM ranked_sales
WHERE best_rank = 1

UNION

SELECT
    market_date,
    total_sales
FROM ranked_sales
WHERE worst_rank = 1;

[
  {
    "market_date": "2022-12-20",
    "total_sales": 979
  },
  {
    "market_date": "2023-04-07",
    "total_sales": 272.5
  }
]

Query 8: ✅ Correct

Possible revenue is correct for every vendor and product.

SQL and output

SELECT
    v.vendor_name,
    p.product_name,
    SUM(5 * vi.original_price) AS potential_revenue
FROM (
    SELECT DISTINCT
        vendor_id,
        product_id,
        original_price
    FROM vendor_inventory
) AS vi

JOIN vendor AS v
    ON vi.vendor_id = v.vendor_id

JOIN product AS p
    ON vi.product_id = p.product_id

CROSS JOIN customer AS c

GROUP BY
    v.vendor_name,
    p.product_name;

[
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Apple Pie",
    "potential_revenue": 2340
  },
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Cherry Pie",
    "potential_revenue": 2340
  },
  {
    "vendor_name": "Annie's Pies",
    "product_name": "Whole Wheat Bread",
    "potential_revenue": 845
  }
]

Query 9: ✅ Correct

Unit products and current snapshot timestamps are correct.

SQL and output

CREATE TABLE product_units AS
SELECT
    *,
    CURRENT_TIMESTAMP AS snapshot_timestamp
FROM product
WHERE product_qty_type = 'unit';

Query 10: ✅ Correct

One product with a current timestamp was inserted.

SQL and output

SELECT *
FROM product_units
WHERE product_name = 'Apple Pie';

INSERT INTO product_units (
    product_id,
    product_name,
    product_size,
    product_category_id,
    product_qty_type,
    snapshot_timestamp
)
VALUES (
    7,
    'Apple Pie',
    '10"',
    3,
    'unit',
    CURRENT_TIMESTAMP
);

SELECT *
FROM product_units
WHERE product_name = 'Apple Pie'
ORDER BY snapshot_timestamp;

[
  {
    "product_id": 7,
    "product_name": "Apple Pie",
    "product_size": "10\"",
    "product_category_id": 3,
    "product_qty_type": "unit",
    "snapshot_timestamp": "2026-11-07 02:56:20"
  },
  {
    "product_id": 7,
    "product_name": "Apple Pie",
    "product_size": "10\"",
    "product_category_id": 3,
    "product_qty_type": "unit",
    "snapshot_timestamp": "2026-11-07 02:56:21"
  }
]

Query 11: ✅ Correct

Only the older copy was removed; the inserted copy remains.

SQL and output

DELETE FROM product_units
WHERE product_id = 7
  AND snapshot_timestamp = (
      SELECT MIN(snapshot_timestamp)
      FROM product_units
      WHERE product_id = 7
  );

Query 12: ✅ Correct

All rows remain and current_quantity matches the latest inventory.

SQL and output

ALTER TABLE product_units
ADD current_quantity INT;

UPDATE product_units
SET current_quantity = COALESCE(
    (
        SELECT vi.quantity
        FROM vendor_inventory AS vi
        WHERE vi.product_id = product_units.product_id
        ORDER BY vi.market_date DESC
        LIMIT 1
    ),
    0
);

Complete SQL assignment 2

03cfd02

Fix query 12

a5c5710

Fix query 12 syntax

d520827

Navigation Menu

Repository navigation

Complete SQL assignment 2 - #2

Complete SQL assignment 2#2
mohammadgoudarzirad wants to merge 3 commits into
mainfrom
assignment-two

mohammadgoudarzirad commented Nov 7, 2026

Uh oh!

github-actions Bot commented Nov 7, 2026

Uh oh!

github-actions Bot commented Nov 7, 2026

Uh oh!

github-actions Bot commented Nov 7, 2026

Uh oh!

Reviewers

Uh oh!

Assignees

Labels

Projects

Milestone

Development

Uh oh!

1 participant

Conversation

mohammadgoudarzirad commented Nov 7, 2026

What changes are you trying to make? (e.g. Adding or removing code, refactoring existing code, adding reports)

What did you learn from the changes you have made?

Was there another approach you were thinking about making? If so, what approach(es) were you thinking of?

Were there any challenges? If so, what issue(s) did you face? How did you overcome it?

How were these changes tested?

A reference to a related issue in your repository (if applicable)

Checklist

Uh oh!

github-actions Bot commented Nov 7, 2026

SQL Assignment 2 feedback

Uh oh!

github-actions Bot commented Nov 7, 2026

SQL Assignment 2 feedback

Uh oh!

github-actions Bot commented Nov 7, 2026

SQL Assignment 2 feedback

Uh oh!

Reviewers

Uh oh!

Assignees

Labels

Projects

Milestone

Development

Uh oh!

1 participant