14. Solutions: WITH
WITH Solutions
Below, you will see each of the previous solutions restructured using the WITH clause. This is often an easier way to read a query.
- Provide the name of the sales_rep in each region with the largest amount of total_amt_usd sales.
WITH t1 AS (
SELECT s.name rep_name, r.name region_name, SUM(o.total_amt_usd) total_amt
FROM sales_reps s
JOIN accounts a
ON a.sales_rep_id = s.id
JOIN orders o
ON o.account_id = a.id
JOIN region r
ON r.id = s.region_id
GROUP BY 1,2
ORDER BY 3 DESC),
t2 AS (
SELECT region_name, MAX(total_amt) total_amt
FROM t1
GROUP BY 1)
SELECT t1.rep_name, t1.region_name, t1.total_amt
FROM t1
JOIN t2
ON t1.region_name = t2.region_name AND t1.total_amt = t2.total_amt;
- For the region with the largest sales total_amt_usd, how many total orders were placed?
WITH t1 AS (
SELECT r.name region_name, SUM(o.total_amt_usd) total_amt
FROM sales_reps s
JOIN accounts a
ON a.sales_rep_id = s.id
JOIN orders o
ON o.account_id = a.id
JOIN region r
ON r.id = s.region_id
GROUP BY r.name),
t2 AS (
SELECT MAX(total_amt)
FROM t1)
SELECT r.name, COUNT(o.total) total_orders
FROM sales_reps s
JOIN accounts a
ON a.sales_rep_id = s.id
JOIN orders o
ON o.account_id = a.id
JOIN region r
ON r.id = s.region_id
GROUP BY r.name
HAVING SUM(o.total_amt_usd) = (SELECT * FROM t2);
- For the account that purchased the most (in total over their lifetime as a customer) standard_qty paper, how many accounts still had more in total purchases?
WITH t1 AS (
SELECT a.name account_name, SUM(o.standard_qty) total_std, SUM(o.total) total
FROM accounts a
JOIN orders o
ON o.account_id = a.id
GROUP BY 1
ORDER BY 2 DESC
LIMIT 1),
t2 AS (
SELECT a.name
FROM orders o
JOIN accounts a
ON a.id = o.account_id
GROUP BY 1
HAVING SUM(o.total) > (SELECT total FROM t1))
SELECT COUNT(*)
FROM t2;
- For the customer that spent the most (in total over their lifetime as a customer) total_amt_usd, how many web_events did they have for each channel?
WITH t1 AS (
SELECT a.id, a.name, SUM(o.total_amt_usd) tot_spent
FROM orders o
JOIN accounts a
ON a.id = o.account_id
GROUP BY a.id, a.name
ORDER BY 3 DESC
LIMIT 1)
SELECT a.name, w.channel, COUNT(*)
FROM accounts a
JOIN web_events w
ON a.id = w.account_id AND a.id = (SELECT id FROM t1)
GROUP BY 1, 2
ORDER BY 3 DESC;
- What is the lifetime average amount spent in terms of total_amt_usd for the top 10 total spending accounts?
WITH t1 AS (
SELECT a.id, a.name, SUM(o.total_amt_usd) tot_spent
FROM orders o
JOIN accounts a
ON a.id = o.account_id
GROUP BY a.id, a.name
ORDER BY 3 DESC
LIMIT 10)
SELECT AVG(tot_spent)
FROM t1;
- What is the lifetime average amount spent in terms of total_amt_usd, including only the companies that spent more per order, on average, than the average of all orders.
WITH t1 AS (
SELECT AVG(o.total_amt_usd) avg_all
FROM orders o
JOIN accounts a
ON a.id = o.account_id),
t2 AS (
SELECT o.account_id, AVG(o.total_amt_usd) avg_amt
FROM orders o
GROUP BY 1
HAVING AVG(o.total_amt_usd) > (SELECT * FROM t1))
SELECT AVG(avg_amt)
FROM t2;
Wow! That was intense. Nice job if you got these!
Code
If you need a code on the https://github.com/udacity.
SOLUTION:
- CTEs are more readable.
- CTEs are more efficient, as the tables aren't recreated with each subquery portion.