SQL code copied to buffer
Group tasks by:
Support the project.
- 1. Get the actors
- 2. Get the languages list
- 3. Get list of actors names
- 4. Fetch all departments
- 5. Staff names
- 6. Product categories
- 7. Ordered Languages List
- 8. Get the sorted list of films with limit
- 9. Find stuff members by condition
- 10. Get the sorted list of films with condition
- 11. Find film names by description
- 12. Find the actors by name
- 13. Find the average length of a movie
- 14. Find foreign employees
- 15. Ordered Movie Titles
- 16. Find clients starting with the letter "A"
- 17. Find clients starting with the letter "A" (2)
- 18. Find the minimal and maximal film rental cost
- 19. Top 10 Movies by Title
- 20. Find long movies
- 21. Calculate the area of a circle
- 22. Calculate circle perimeter
- 23. Find active customers
- 24. Movies with above-average rental rates
- 25. Movies with the highest replacement cost
- 26. Get list of clients
- 27. Get a list of movie ratings
- 28. Get list of tables
- 29. Get table columns data
- 30. Get list of indexes
- 31. Get the restricted films list
- 32. Get list of restricted films
- 33. Create new address record
- 34. Update the postal code
- 35. Remove customer records
- 36. Addresses Lacking Postal Codes
- 37. Find an addresses with even postal codes
- 38. Build shared surnames list
- 39. Get airports data
- 40. Find long-range aircraft
- 41. Identify Palindrome Names
- 42. What is SQL?
- 43. What is DBMS?
- 44. What is RDBMS?
- 45. What is ACID?
- 46. What are DQL commands?
- 47. What is index in SQL?
- 48. SQL tables joins types
- 49. Choose join type
- 50. Perform price update
- 51. Update replacement cost
- 52. Order of execution of logical operators
- 53. Difference between UNION and UNION ALL
- 54. Display a list of departments
- 55. Find employees by department
- 56. Find employee salary
- 57. Employees with high salaries
- 58. Find employees with a salary above average
- 59. Find customers with even numbers
- 60. Find customers by phone prefix
- 61. Get unique customers list
- 62. How avoid accidental deletion?
- 63. How to find common rows in SQL?
- 64. What relation types exists in SQL?
- 65. Find non-Dollar/Euro countries
- 66. What is normalization in SQL?
- 67. What is a subquery?
- 68. Root categories list
- 69. Product List
- 70. Filtered list of products
- 71. Ten heaviest products
- 72. Sort the penguins
- 73. Find light weight penguins
- 74. Penguins list
- 75. Distribution penguins by islands
- 76. Find small penguins
- 77. Find small penguins species
- 78. Search by pattern
- 79. Flipper length to body mass rate
- 80. Penguins whose sex is unknown
- 81. Penguins with absent data
- 82. Heavy penguins
- 83. Count the penguins
- 84. Penguins and Islands
- 85. Medium sized bill Penguins
- 86. Penguins distribution
- 87. Common penguin species
- 88. Delete records
- 89. Delete employee records
- 90. Rename the table
- 91. Penguins stats
- 92. Create index
- 93. Create unique index
- 94. Drop table
- 95. Customers without orders
- 96. Missing Data
- 97. Small bill Penguins
- 98. Not buyng customers
- 99. Penguins species
- 100. HAVING without aggregate
- 101. New York streets length
- 102. Update Job Salaries
- 1. Find customers full names
- 2. Find addresses using sub-query
- 3. Find addresses using JOIN
- 4. Find duplicate actor names
- 5. Find the most popular surname among actors
- 6. Find all the actors in the film
- 7. Find all films of an actor
- 8. Find the distribution of films by category
- 9. Find the average length of a movie by category
- 10. Find the number of films in which the actor took part
- 11. Find actors more popular than HENRY BERRY
- 12. Analyze monthly payment
- 13. Find the best month
- 14. Find the most popular film
- 15. Analyze rental data for film
- 16. Find the department
- 17. Find employees works on the project
- 18. Find all customers with unshipped orders
- 19. Sort Movies by Multiple Fields
- 20. Get the longest movie
- 21. Get films list third page
- 22. Find the films never been rented
- 23. Find customers who did not return rented discs
- 24. Find average daily film rentals
- 25. Calculate daily income for the month
- 26. Generate dates table
- 27. Calculate the number of days off in a month
- 28. The average cost of renting a movie by category
- 29. Average film rental duration for each customer
- 30. Find long comedies
- 31. Find the distribution of customer activity
- 32. Find company stores details
- 33. Find clients who rented the film
- 34. Find minimum, maximum and average film duration
- 35. Find long movie categories
- 36. Find the number of employees
- 37. Find movie distribution by store
- 38. Find highly paid employees
- 39. Find employees by hire date
- 40. Get list of highly paid employees
- 41. Find valuable employees
- 42. Find the salary ratio
- 43. Find the average client activity time
- 44. Find the average revenue
- 45. Find the store average revenue
- 46. Create a salary rating
- 47. Quarterly earnings analysis
- 48. Find the countries with the most customers
- 49. Find customer details
- 50. Find the count of rented disks
- 51. Find the number of returns
- 52. Find the least popular movies
- 53. Find the top spending customers
- 54. Find films with no available inventory
- 55. Find languages not represented in films
- 56. Find movies that have never been rented
- 57. Clients with a high number of rentals
- 58. Films with the highest replacement cost
- 59. Count the rental delays
- 60. Calculate the percentage of delays
- 61. Get movie cast lists
- 62. Extract address and domain from email
- 63. Get a list of actors - namesakes
- 64. Get a list of movies and their categories
- 65. Find film average rental time
- 66. Movie rental prices by category
- 67. Get rolling payment amounts
- 68. Find the number of films in each category
- 69. Analyze customer payments
- 70. Find the most diverse clients
- 71. Find film distribution
- 72. Payments analyze
- 73. Distribution of clients by weekday
- 74. Client Rentals by Time of Day
- 75. Improve distribution of clients by weekday
- 76. Movies without actors records
- 77. Movies without cast records
- 78. Actors Excluding NC-17 Films
- 79. Analyze weekly rentals
- 80. Average rentals count
- 81. Find repeat rentals
- 82. Find the distribution of clients by country
- 83. Find never been delayed films
- 84. Find most delayed films
- 85. Create department table
- 86. NC-17 Films about DBA
- 87. Find films about Dogs or Cats
- 88. Clients whose first name is the last name of another client
- 89. Update Canadian postal codes
- 90. Enter Woodridge postal code
- 91. Enter new staff record
- 92. Create customer addresses view
- 93. Distribution of films by categories in JSON format
- 94. Generate a list of movies in JSON format
- 95. Category popularity analysis
- 96. Build a overal email list
- 97. Select clients without the letter "A"
- 98. Alter the staff table
- 99. Find films in several categories
- 100. Get a list of airports
- 101. Find Boeing aircraft
- 102. Get flights departed from Domodedovo
- 103. Get a list of aircraft from Domodedovo
- 104. Aircraft usage analysis
- 105. Find last names with double letters
- 106. Customers with matching name initials
- 107. Format Customer Names
- 108. Aircraft Lacking Business Class Seats
- 109. Get counts of seats by class
- 110. Get rows and seats count
- 111. Calculate the number of seats on flight
- 112. Get a list of airports with direct connections
- 113. Get a list of no-show passengers
- 114. Get a list of passengers
- 115. Find the flight delay
- 116. Get flights statistics
- 117. Find the fastest flight
- 118. Calculate the daily number of flights
- 119. Obtain a list of passengers
- 120. Get list of tables
- 121. Get information about the columns
- 122. Airports with one-way departures
- 123. Find airports relations
- 124. Get the passenger list
- 125. Get aircraft seat map
- 126. Get a list of planes in the air
- 127. What is a Database?
- 128. What are DDL commands?
- 129. What are DML commands?
- 130. How is data structured in a relational database?
- 131. What is a constraint in SQL?
- 132. Choose tables join type
- 133. Calculate the tax
- 134. Get formatted list of films
- 135. What is a primary key?
- 136. Update customer's address
- 137. Adjust the rental cost
- 138. Find the tomorrow date
- 139. Find the first and last dates of month
- 140. Find the first and last dates of week
- 141. Display a table of airports
- 142. Count departing passengers
- 143. Number of passengers with total
- 144. Display a table of departures
- 145. Get a list of airports with more than one direct flight
- 146. Get list of tables (PostgreSQL)
- 147. A sub-departments list (JOIN)
- 148. Get a list of sub-departments
- 149. Get list of tables (SQL Server)
- 150. Find duplicate phone numbers
- 151. What is a covering index?
- 152. What is a view in SQL?
- 153. Move film between categories
- 154. Find a June 2005 hit
- 155. Get product category color counts
- 156. Find films to share
- 157. Jobs without specific requirements
- 158. Orders shipped in the following month
- 159. Update project information
- 160. Top states by population
- 161. Reduced salaries
- 162. List of categories
- 163. List of subcategories
- 164. What is a SQL transaction?
- 165. What is a correlated subquery?
- 166. Create a phonebook
- 167. Staff availability report
- 168. What is "PIVOT" in SQL?
- 169. Film distribution by category and store
- 170. Determine the type of relationship
- 171. Find highly paid employees
- 172. Find the hypotenuse of a triangle
- 173. Find the median booking amount
- 174. Find the median film's length
- 175. Prepare mailing list
- 176. Daily income by source
- 177. Index usage
- 178. Using a covering index
- 179. Island with the minimum penguins mass
- 180. The most populated island
- 181. Classic movies
- 182. Penguins stats table
- 183. Actual statistics 2
- 184. Managed by Robert Nelson
- 185. Tables joining algorithms in SQL
- 186. Delete films records
- 187. Analyze bill length
- 188. Analyze flipper length
- 189. What is denormalization in RDB?
- 190. Create functional index
- 191. Staff information
- 192. Overloaded employees
- 193. Rank Penguins by Body Mass
- 194. Who ordered red helmet?
- 195. Who ordered helmet?
- 196. What bought Jon Grande?
- 197. The most popular product
- 198. Products catalog
- 199. Mountain Bikes catalog
- 200. Products by category distribution
- 201. Large categories
- 202. Set Last Service Date
- 203. Refurbished machines
- 204. Data migration
- 205. Penguins with low body weight
- 206. Most Frequent Co-Purchase
- 207. Most popular products
- 208. Average Sales Delay
- 209. Distance between cities
- 210. Penguins habitat
- 211. Population Distribution (Pivot)
- 212. Extract Geometry as Text
- 213. Manhattan's subway stations
- 214. Area of the Neighborhood
- 215. Area of the Neighborhood
- 216. Neighborhood Average Area
- 217. Extract Geometry as JSON
- 218. Duplicate Emails
- 219. Create Penguins Table
- 220. Rented Films
- 1. Find most active customers
- 2. Find sad actors
- 3. Find the most diverse actors
- 4. Find all films where HENRY BERRY did not participate
- 5. Calculate factorial
- 6. Find average disk idle time
- 7. Find the distribution by categories
- 8. Analyze monthly payments (2)
- 9. Find movie popularity rating
- 10. Find EMILY DEE fans
- 11. Clients who are not familiar with EMILY DEE films
- 12. Disc rental and return statistics
- 13. Films with Low Rental Time
- 14. Find actors duets
- 15. Find films that were out of stock
- 16. Improve payments analyze
- 17. Find all the actors in the film
- 18. Find the Horror films fans
- 19. Movies in One Store
- 20. Find movies with no available copies
- 21. Staff performance analysis
- 22. Generate monthly bill
- 23. Gap & Islands problem
- 24. Find customers who sow same films
- 25. Get the list of destination airports
- 26. Get a list of airports without direct connections
- 27. Rate airports
- 28. Find a list of flight options
- 29. Rental history
- 30. Find average flight occupancy
- 31. Find flight occupancy by fare
- 32. Find small airports
- 33. FInd the plane coordinates
- 34. FInd the planes coordinates
- 35. What is a subset of the SQL language?
- 36. SQL constraints types
- 37. SQL set operators
- 38. Find a 2005 hits
- 39. Analysis of the cost of film rental by category
- 40. What is a materialized view?
- 41. Distribution of flights by days of the week
- 42. Subcategories count
- 43. Find the median salary
- 44. Actual statistics
- 45. Cumulative payment analysis
- 46. Country Area
- 47. Little Italy Stations
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Imagine you have two tables: customer and customer_addresses, each containing a column named customer_id. What type of JOIN would you use in a query to get all customer records clients (even if they don't have an address) and the addresses of those that have a corresponding address entry in the table customer_addresses?
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