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Easy/00175-combine-two-tables.sql

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+-- simple LEFT JOIN
+
+select p.firstName, p.lastName, a.city, a.state
+from Person p
+left join Address a
+using(personId)
+
+
+-- apple- 4
+-- bloomberg- 2
+-- amazon- 2
+-- microsoft- 2
+-- adobe- 3
+-- google- 3

Easy/00182-duplicate-emails.sql

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+-- use group by for aggregate
+
+select email as Email
+from Person
+group by email
+having count(email) > 1
+
+
+-- amazon- 2
+-- uber- 2

Easy/00183-customers-who-never-order.sql

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+-- pick id from Orders, and do not select those ids
+
+select name as Customers
+from Customers
+where id not in
+    (select distinct customerId
+    from Orders)
+
+-- amazon- 3
+-- apple- 7
+-- bloomberg- 5
+-- adobe- 2

Easy/00511-game-play-analysis-i.sql

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+-- simple aggregate function
+
+select player_id, min(event_date) as first_login
+from Activity
+group by 1
+
+-- adobe- 2
+-- amazon- 4
+-- bloomberg- 4
+-- gsn games- 1

Easy/00512-game-play-analysis-ii.sql

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+-- using subquery
+
+select player_id, device_id
+from Activity
+where (player_id, event_date) in
+    (select player_id, min(event_date)
+    from Activity
+    group by player_id)
+
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+-- using window function
+  
+with CTE as
+    (select player_id, device_id, 
+        row_number() over(partition by player_id order by event_date) as rn
+    from Activity)
+
+select player_id, device_id
+from CTE 
+where rn = 1
+
+-- gsn games- 1

Easy/00586-customer-placing-the-largest-number-of-orders.sql

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+-- the the cusotmer with maximum order count, order by, limit
+
+select customer_number
+from Orders
+group by 1
+order by count(order_number) desc
+limit 1
+
+
+-- adobe- 2
+-- google- 3
+-- apple- 2
+-- uber- 2
+-- twitter- 1

Easy/00603-consecutive-available-seats.sql

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+-- lag and lead will give the rows above and below
+-- if free = 1 and either of lag_free or lead_free is 1, it means we have 2 consecutive free seats.
+-- just pick those rows
+
+with CTE as(
+    select seat_id, free, 
+        lag(free, 1) over(order by seat_id) as lag_free, 
+        lead(free, 1) over(order by seat_id) as lead_free
+    from Cinema)
+
+select seat_id 
+from CTE
+where (free = 1 and lag_free = 1) or (free = 1 and lead_free = 1)
+order by 1
+
+------------------------------------------------------------------------------------------------------------------------------------------------------------
+-- if seat = free AND seat + 1 or seat - 1 have free = 1, then pull that seat  
+  
+select seat_id
+from Cinema
+where free = 1 and
+     (seat_id - 1 in (select seat_id
+                      from Cinema
+                      where free = 1)
+    or
+    seat_id + 1 in (select seat_id
+                      from Cinema
+                      where free = 1))
+
+
+-- amazon- 4

Easy/00607-sales-person.sql

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+-- nested query
+-- select all salesPerson with company RED
+-- select all salesPerson from SalesPerson not in the above table
+
+select sp.name
+from SalesPerson sp
+where sales_id not in
+    (select o.sales_id
+    from Orders o
+    where o.com_id in
+        (select c.com_id 
+        from Company c
+        where c.name = 'RED'))
+
+------------------------------------------------------------------------------------------------------------------------------------------------
+-- JOIN Company c and Ordered o
+-- pick all sales_id with company = 'RED'
+-- pick all salesPerson from SalesPerson not in temp table above
+  
+select sp.name
+from SalesPerson sp
+where sales_id not in
+    (select o.sales_id
+    from Orders o
+    inner join Company c
+    on c.com_id = o.com_id
+    where c.name = 'RED')
+
+
+-- no companies listed

Easy/00613-shortest-distance-in-a-line.sql

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+-- cross joining all the points from 2 tables, except the ones where they are same
+-- find the min of absolute distance
+
+select min(abs(a - b)) as shortest
+from
+  (select p1.x as a, p2.x as b
+  from Point p1 cross join Point p2
+  where p1.x != p2.x) temp
+
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+-- concise version of the above
+  
+select min(abs(p1.x - p2.x)) as shortest
+from Point p1 cross join Point p2
+where p1.x != p2.x
+
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+-- pull min distance with a where condition
+
+select min(p1.x - p2.x) as shortest
+from Point p1, Point p2
+where p1.x > p2.x
+
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+-- sort the table, and do lag. Now diff between current and lag- because difference between the sorted will always be lesser than difference between the larger ones
+-- pull the min distance
+  
+with CTE as 
+  (select x - lag(x) over(order by x) as distance
+  from Point)
+
+select min(distance) as shortest from CTE
+
+-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+-- picking the lowest distance, 1st row will always be null hence use offset
+
+select x - lag(x) over(order by x) as shortest
+from Point
+order by 1 asc
+limit 1 offset 1
+
+
+-- no companies listed

Easy/01050-actors-and-director-who-cooperated-at-least-three-times.sql

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+-- aggregate- group by 2 columns, count
+
+select actor_id, director_id
+from ActorDirector
+group by 1, 2
+having count(*) >= 3
+
+
+-- amazon- 3

Easy/01173-immediate-food-delivery-i.sql

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+-- simple condition in aggregate function- count immediate, divide by total rows in the table
+
+select round(sum(order_date = customer_pref_delivery_date) / count(*) * 100, 2) as immediate_percentage
+from Delivery
+---------------------------------------------------------------------------------------------------------------------------------------------
+-- same as above but using case
+
+select round(sum( case when order_date = customer_pref_delivery_date then 1 else 0 end) / count(*) * 100, 2) as immediate_percentage
+from Delivery
+
+
+-- doordash- 2

Easy/01303-find-the-team-size.sql

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+-- if we do not use order by in over(), we do not get running total, just normal aggregate for all rows within that partition
+
+select employee_id, count(*) over(partition by team_id) as team_size
+from Employee
+order by 1
+
+-- amazon- 1

Easy/01350-students-with-invalid-departments.sql

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+-- subquery- use WHERE
+
+select id, name
+from Students
+where department_id not in 
+    (select id
+    from Departments)
+
+------------------------------------------------------------------------------------------------------------------------------------------------------------------------
+
+-- join- use WHERE id is null
+
+select s.id, s.name
+from Students s
+left join Departments d
+on d.id = s.department_id
+where d.id is null
+
+
+-- amazon- 1

Easy/01407-top-travellers.sql

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+-- using ifnull around sum()- can also use coalesce
+
+select u.name, ifnull(sum(r.distance), 0) as travelled_distance
+from Users u
+left join Rides r
+on u.id = r.user_id
+group by u.id
+order by 2 desc, 1 asc
+
+
+-- point72- 1

Easy/01495-friendly-movies-streamed-last-month.sql

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+-- use DISTINCT because we want distinct titles
+-- use where condition for filter
+
+select distinct title
+from Content c join TVProgram t
+on c.content_id = t.content_id
+where c.Kids_content = 'Y' and c.content_type = 'Movies' and t.program_date like '2020-06%'
+
+
+-- amazon- 1

Easy/01511-customer_order-frequency.sql

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+-- we need customer ids from 2 separate tables using 'and' condition
+-- 1st table- get sum of expenditures of all customers in June 2020, filter by customers whose sum >= 100
+-- 2nd table- get sum of expenditures of all customers in July 2020, filter by customers whose sum >= 100
+-- pull all customers who are in table1 AND table 2
+
+select c.customer_id, c.name 
+from Customers
+where customer_id in
+    (select customer_id
+    from Orders o 
+    join Product p
+    on o.product_id = p.product_id
+    where left(order_date, 7) = '2020-06'
+    group by customer_id
+    having sum(quantity*price) >= 100) 
+ and customer_id in
+    (select customer_id, sum(quantity*price)
+    from Orders o 
+    join Product p
+    on o.product_id = p.product_id
+    where left(order_date, 7) = '2020-07'
+    group by customer_id
+    having sum(quantity*price) >= 100)
+
+---------------------------------------------------------------------------------------------------------------------
+
+-- create a temp table- join all tables
+-- create 2 additional columns- expenditure in June and in July- CASE, AGGREGATE
+-- in the main query, pull customer ids where expenditure in both columns are >= 100
+
+with CTE as(select c.customer_id, c.name, 
+    sum(case when left(o.order_date, 7) = '2020-06' then p.price*o.quantity else 0 end) june_spent,
+    sum(case when left(o.order_date, 7) = '2020-07' then p.price*o.quantity else 0 end) july_spent
+from Customers c
+join Orders o 
+on c.customer_id = o.customer_id
+join Product p
+on p.product_id = o.product_id
+group by 1)
+
+select customer_id, name 
+from CTE
+where june_spent >= 100 and july_spent >= 100
+
+
+-- amazon- 1

Easy/01571-warehouse-manager.sql

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+-- multiple units, width, length, height, then calculate sum() of those
+
+select w.name as warehouse_name, 
+sum(units * Width * Length * Height) as volume
+from Warehouse w
+left join Products p
+on w.product_id = p.product_id
+group by 1
+
+-------------------------------------------------------------------------------------------------------------
+-- breaking down the above one
+  
+with CTE as (
+    select product_id, (Width * Length * Height) as size
+    from Products)
+
+select name as warehouse_name, sum(units * size) as volume
+from Warehouse w
+left join CTE c
+on c.product_id = w.product_id
+group by name
+
+-- amazon- 1

Easy/01587-bank-account-summary-ii.sql

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+-- simple aggregate with JOIN and HAVING
+
+select u.name, sum(t.amount) as balance
+from Users u
+left join Transactions t
+on u.account = t.account
+group by u.account
+having sum(t.amount) > 10000
+
+-- uber- 2

Easy/01607-sellers-with-no-sales.sql

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+-- select sellers from Orders table
+-- then select Sellers from Sellers table who are not in temp
+
+select seller_name
+from Seller s
+where seller_id not in 
+    (select seller_id 
+    from Orders
+    where sale_date like '2020%')
+order by seller_name
+
+--------------------------------------------------------------------------------------------------------------------------------------------
+-- using JOIN with conditions
+  
+select s.seller_name
+from Seller s
+left join Orders o
+on o.seller_id = s.seller_id and sale_date like '2020%' 
+where o.seller_id is null
+order by seller_name
+
+-- no companies listed

Easy/01693-daily_leads-and-partners.sql

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+-- basic aggregate function- count distinct, group by 2 variables
+
+select date_id, make_name, 
+    count(distinct lead_id) unique_leads, 
+    count(distinct partner_id) unique_partners
+from DailySales
+group by date_id, make_name
+
+
+-- no companies listed

Easy/01741-find-total-time-spent-by-each-employee.sql

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+-- simple aggregation- we need total sum of the diff between out and in time
+
+select event_day as day, emp_id, sum(out_time-in_time) as total_time
+from Employees
+group by 1, 2
+
+
+-- adobe- 2
+-- amazon- 1