pivot aggfunc flatten()

unbounded preceding: from begining up to the current row

n, preceding: n rows before current row
n, following: means using current row and after n rows
unbounded following: start from current row and go in the end of the partition

Splitting one word to one

Code itself

when working with subqueries correlated you will self join is used in aggregated part

Certainly! Let's break down the SQL query step by step:

1. CTE `t1`:
- The first Common Table Expression (CTE) named t1 calculates the total sales (total_amt_usd) for each region by joining the sales_reps, accounts, orders, and region tables.
- It uses the GROUP BY clause to group the results by the region name (r.name).

   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
   )
   

2. CTE `t2`:
- The second CTE named t2 calculates the maximum total sales from t1.

   t2 AS (
      SELECT MAX(total_amt) FROM t1
   )
   

3. Main Query:
- The main query selects the region name (r.name) and the count of total orders (COUNT(o.total) total_orders) for each region.
- It joins the same set of tables (sales_reps, accounts, orders, region) and groups the results by the region name.
- The HAVING clause is used to filter the results based on the condition that the total sales (SUM(o.total_amt_usd)) for each region should be equal to the maximum total sales obtained from t2.

   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);
   

In summary, the query identifies regions where the total sales match the maximum total sales across all regions. It provides the region names and the count of total orders for those specific regions. The use of CTEs helps break down the complex query into more manageable parts for better readability and understanding.




CTE explanation

Rounding it means in pandas formating like f .2