diff --git a/02_activities/assignments/Cohort_8/Assignment2 - Prompt 1.png b/02_activities/assignments/Cohort_8/Assignment2 - Prompt 1.png new file mode 100644 index 000000000..4e25a7b7e Binary files /dev/null and b/02_activities/assignments/Cohort_8/Assignment2 - Prompt 1.png differ diff --git a/02_activities/assignments/Cohort_8/Assignment2 - Prompt 2.png b/02_activities/assignments/Cohort_8/Assignment2 - Prompt 2.png new file mode 100644 index 000000000..d88f4e22c Binary files /dev/null and b/02_activities/assignments/Cohort_8/Assignment2 - Prompt 2.png differ diff --git a/02_activities/assignments/Cohort_8/Assignment2.md b/02_activities/assignments/Cohort_8/Assignment2.md index 47118b2ba..df2718a0d 100644 --- a/02_activities/assignments/Cohort_8/Assignment2.md +++ b/02_activities/assignments/Cohort_8/Assignment2.md @@ -54,7 +54,12 @@ The store wants to keep customer addresses. Propose two architectures for the CU **HINT:** search type 1 vs type 2 slowly changing dimensions. ``` -Your answer... +If the store wants to retain changes for the CUSTOMER_ADDRESS table, the type 2 slowly changing dimension architecture is recommended because it creates a new customer address record for each change to the historical data it has for the customer address. When a customer address changes, a new row with the updated address will be created in the table. While the old address for the customer is still retained in the table. This table would need a way to identify the current address, such as by having an is_active column that indicates the current address, or a timestamp column that could tell us the most recent address. This table can have many rows per customer. + +Whereas, if the store wants to overwrite the previous customer address in the table when there is a new customer address, the type 1 slowly changing dimensions is recommended. The new customer address will replace the old address in the row. No historical data will be retained. This table will have exactly one row per customer. + +In either design, the customer_address table would have columns such as street name, house number, postal code, city, province/state, and country. + ``` *** diff --git a/02_activities/assignments/Cohort_8/assignment2.sql b/02_activities/assignments/Cohort_8/assignment2.sql index 5ad40748a..c27b24d2a 100644 --- a/02_activities/assignments/Cohort_8/assignment2.sql +++ b/02_activities/assignments/Cohort_8/assignment2.sql @@ -20,7 +20,9 @@ The `||` values concatenate the columns into strings. Edit the appropriate columns -- you're making two edits -- and the NULL rows will be fixed. All the other rows will remain the same.) */ - +SELECT + product_name || ', ' || coalesce(product_size, '')|| ' (' || coalesce(product_qty_type, 'unit') || ')' as list_of_products +FROM product; --Windowed Functions /* 1. Write a query that selects from the customer_purchases table and numbers each customer’s @@ -32,17 +34,52 @@ each new market date for each customer, or select only the unique market dates p (without purchase details) and number those visits. HINT: One of these approaches uses ROW_NUMBER() and one uses DENSE_RANK(). */ +SELECT + customer_id, + market_date, + DENSE_RANK() OVER ( + PARTITION BY customer_id + ORDER BY market_date ASC) as number_of_customer_visits +FROM customer_purchases; /* 2. Reverse the numbering of the query from a part so each customer’s most recent visit is labeled 1, then write another query that uses this one as a subquery (or temp table) and filters the results to only the customer’s most recent visit. */ +DROP TABLE IF EXISTS TEMP.customer_most_recent_visit; + +CREATE TEMP TABLE IF NOT EXISTS TEMP.customer_most_recent_visit +( +customer_id INT, +market_date date, +number_of_customer_visits INT +); +INSERT INTO TEMP.customer_most_recent_visit +SELECT + customer_id, + market_date, + DENSE_RANK() OVER ( + PARTITION BY customer_id + ORDER BY market_date DESC) as number_of_customer_visits +FROM customer_purchases; + +SELECT DISTINCT + customer_id, + market_date +FROM TEMP.customer_most_recent_visit +WHERE number_of_customer_visits = 1; /* 3. Using a COUNT() window function, include a value along with each row of the customer_purchases table that indicates how many different times that customer has purchased that product_id. */ +SELECT + product_id, + customer_id, + COUNT(*) as customer_purchases_count +FROM customer_purchases +GROUP BY product_id, customer_id; -- String manipulations @@ -57,11 +94,25 @@ Remove any trailing or leading whitespaces. Don't just use a case statement for Hint: you might need to use INSTR(product_name,'-') to find the hyphens. INSTR will help split the column. */ - +SELECT + product_name, + CASE + WHEN product_name like '%-%' THEN Trim(SUBSTR (product_name, INSTR(product_name,'-') +1)) + ELSE NULL + END as product_description +FROM product; /* 2. Filter the query to show any product_size value that contain a number with REGEXP. */ - +SELECT + product_name, + product_size, + CASE + WHEN product_name like '%-%' THEN Trim(SUBSTR (product_name, INSTR(product_name,'-') +1)) + ELSE NULL + END as product_description +FROM product +WHERE product_size REGEXP '[0-9]'; -- UNION /* 1. Using a UNION, write a query that displays the market dates with the highest and lowest total sales. @@ -73,7 +124,52 @@ HINT: There are a possibly a few ways to do this query, but if you're struggling 3) Query the second temp table twice, once for the best day, once for the worst day, with a UNION binding them. */ +DROP TABLE IF EXISTS TEMP.market_dates_total_sales; +CREATE TEMP TABLE IF NOT EXISTS TEMP.market_dates_total_sales +( +market_date date, +total_sales decimal(16,2) +); + +INSERT INTO TEMP.market_dates_total_sales +SELECT + market_date, + sum(cost_to_customer_per_qty*quantity) +FROM customer_purchases +GROUP BY market_date; + +DROP TABLE IF EXISTS TEMP.market_dates_total_sales_rank; + +CREATE TEMP TABLE IF NOT EXISTS TEMP.market_dates_total_sales_rank +( +market_date date, +total_sales_best_day decimal(16,2), +total_sales_worst_day decimal (16,2) +); + +INSERT INTO TEMP.market_dates_total_sales_rank +SELECT + market_date, + row_number() OVER ( + ORDER BY total_sales DESC) as total_sales_best_day, + row_number() OVER ( + ORDER BY total_sales ASC) as total_sales_worst_day +FROM market_dates_total_sales; + +SELECT + 'best day' as best_or_worst_day, + market_date +FROM market_dates_total_sales_rank +WHERE total_sales_best_day = 1 + +UNION + +SELECT + 'worst day'as best_or_worst_day, + market_date +FROM market_dates_total_sales_rank +WHERE total_sales_worst_day = 1; /* SECTION 3 */ @@ -89,7 +185,18 @@ Think a bit about the row counts: how many distinct vendors, product names are t How many customers are there (y). Before your final group by you should have the product of those two queries (x*y). */ - +SELECT + vendor_name, + product_name, + sum(original_price * 5) +FROM vendor + INNER JOIN vendor_inventory on vendor.vendor_id = vendor_inventory.vendor_id + INNER JOIN ( + SELECT product_name, product_id + FROM product + CROSS JOIN customer + ) p on vendor_inventory.product_id = p.product_id +GROUP BY vendor_name, product_name; -- INSERT /*1. Create a new table "product_units". @@ -97,19 +204,57 @@ This table will contain only products where the `product_qty_type = 'unit'`. It should use all of the columns from the product table, as well as a new column for the `CURRENT_TIMESTAMP`. Name the timestamp column `snapshot_timestamp`. */ +DROP TABLE IF EXISTS product_units; + +CREATE TABLE product_units( +product_id INT, +product_name varchar(45), +product_size varchar(45), +product_category_id INT, +product_qty_type varchar(45), +snapshot_timestamp datetime); +INSERT INTO product_units +SELECT + product_id, + product_name, + product_size, + product_category_id, + product_qty_type, + CURRENT_TIMESTAMP +FROM product +WHERE product_qty_type = 'unit'; +SELECT * +FROM product_units; /*2. Using `INSERT`, add a new row to the product_units table (with an updated timestamp). This can be any product you desire (e.g. add another record for Apple Pie). */ +INSERT INTO product_units +SELECT + product_id, + product_name, + product_size, + product_category_id, + product_qty_type, +CURRENT_TIMESTAMP +FROM product +WHERE product_name = 'Cherry Pie'; +SELECT * +FROM product_units; -- DELETE /* 1. Delete the older record for the whatever product you added. HINT: If you don't specify a WHERE clause, you are going to have a bad time.*/ +DELETE FROM product_units +Where product_name = 'Cherry Pie' +AND snapshot_timestamp = (SELECT min (snapshot_timestamp) FROM product_units WHERE product_name = 'Cherry Pie'); +SELECT * +FROM product_units; -- UPDATE /* 1.We want to add the current_quantity to the product_units table. @@ -129,5 +274,38 @@ Finally, make sure you have a WHERE statement to update the right row, When you have all of these components, you can run the update statement. */ +ALTER TABLE product_units +ADD current_quantity INT; - +DROP TABLE IF EXISTS TEMP.last_quantity_per_product; + +CREATE TEMP TABLE IF NOT EXISTS TEMP.last_quantity_per_product +( +product_id INT, +vendor_id INT, +max_market_date date +); + +INSERT INTO TEMP.last_quantity_per_product +SELECT +product_id, +vendor_id, +max(market_date) +FROM vendor_inventory +GROUP BY product_id, vendor_id; + +UPDATE product_units +SET current_quantity = ( + SELECT coalesce(vendor_inventory.quantity, 0) + FROM product + LEFT JOIN last_quantity_per_product + ON product.product_id = last_quantity_per_product.product_id + LEFT JOIN vendor_inventory + ON last_quantity_per_product.product_id = vendor_inventory.product_id + AND last_quantity_per_product.vendor_id = vendor_inventory.vendor_id + AND last_quantity_per_product.max_market_date = vendor_inventory.market_date + WHERE product_units.product_id = product.product_id +); + +SELECT * +FROM product_units;