Icon Créer jeu Créer jeu

Mastering SQL Window Functions

Compléter

Drills to master window functions in SQL

Téléchargez la version pour jouer sur papier

0 fois fait

Créé par

United States

Top 10 résultats

Il n'y a toujours pas de résultats pour ce jeu. Soyez le premier à apparaître dans le classement! pour vous identifier.
Créez votre propre jeu gratuite à partir de notre créateur de jeu
Affrontez vos amis pour voir qui obtient le meilleur score dans ce jeu

Top Jeux

  1. temps
    but
  1. temps
    but
temps
but
temps
but
 
game-icon

Compléter

Mastering SQL Window FunctionsVersion en ligne

Drills to master window functions in SQL

par Good Sam
1

SUM sales amount BY sale_date ORDER AS running_total OVER FROM sale_date SELECT amount

Problem 1 : Calculate Running Total
Question : You have a table sales ( sale_date DATE , amount DECIMAL ) . Write a SQL query to calculate a running total of amount , ordered by sale_date .

Solution :

, ,
( ) ( )
;

2

ROWS ROWS ROWS AND amount SUM BETWEEN ROW sum_to_end sales AND 3 as sales sale_date CURRENT ROWS FOLLOWING FROM sale_date BY ROW ROW ROW 6 BY PRECEDING FROM BETWEEN moving_avg BY current_avg ROW amount FROM as amount amount 3 AND FROM FOLLOWING as CURRENT OVER as SELECT BETWEEN PRECEDING BY sale_date AND UNBOUNDED ORDER ROWS sale_date AVG CURRENT UNBOUNDED amount sales moving_avg sale_date OVER amount SELECT CURRENT FROM AVG ORDER BETWEEN OVER ORDER sale_date ORDER SELECT AND amount AVG sale_date sales SELECT OVER amount sales as sale_date running_total BETWEEN ORDER PRECEDING OVER CURRENT amount sale_date BY SUM

Problem 2 : Calculate Moving Average
Question : Calculate a 7 - day moving average of sales from the sales table .

Solution :

, ,
( ) ( )
;

Example 2 : Fixed Range with Both PRECEDING and FOLLOWING

, ,
( ) ( )
;

This calculates the average amount using a window that includes three rows before , the current row , and three rows after the current row .

Example 3 : From Start of Data to Current Row
, ,
( ) ( )
;

This query computes a running total starting from the first row in the partition or result set up to the current row .

Example 4 : Current Row to End of Data
SELECT sale_date , amount ,
( ) ( )
;

This sums the amount from the current row to the last row of the partition or result set .

Example 5 : Current Row Only
, ,
( ) ( )
;

This calculates the average of just the current row's amount , which effectively returns the amount itself .

3

DESC customers FROM SELECT total_purchases name total_purchases rank ORDER OVER RANK AS BY id

Problem 3 : Rank Customers by Sales

Question : From a table customers ( id INT , name VARCHAR , total_purchases DECIMAL ) , rank customers based on their total_purchases in descending order .

Solution :

, , ,
( ) ( )
;
Explanation : RANK ( ) assigns a unique rank to each row , with gaps in the ranking for ties , based on the total_purchases in descending order .

4

sales FROM BY SELECT sale_date amount ROW_NUMBER() OVER ORDER AS row_num sale_date

Problem 4 : Row Numbering

Question : Assign a unique row number to each sale in the sales table ordered by sale_date .

Solution :

, ,
( )
;

Explanation : ROW_NUMBER ( ) generates a unique number for each row , starting at 1 , based on the ordering of sale_date .

5

purchases SELECT FROM AS MIN customer_id PARTITION OVER customer_id BY purchase_date first_purchase

Problem 5 : Find the First Purchase Date for Each Customer
Question : Given a table purchases ( customer_id INT , purchase_date DATE ) , write a SQL query to find the first purchase date for each customer .

Solution :

, ( ) ( )
;

Explanation : MIN ( ) window function is used here , partitioned by customer_id so that the minimum purchase date is calculated for each customer separately .

6

sale_date sale_date BY previous_day_amount OVER ORDER 1 ORDER FROM LAG sales_data LAG SELECT amount amount AS AS change_in_amount amount sale_date amount 1 BY OVER

The LAG function is very useful in scenarios where you need to compare successive entries or calculate differences between them . For example , calculating day - over - day sales changes :


SELECT sale_date ,
amount ,
LAG ( amount , 1 ) OVER ( ORDER BY sale_date ) AS previous_day_amount ,
amount - LAG ( amount , 1 ) OVER ( ORDER BY sale_date ) AS change_in_amount
FROM sales_data ;



,
,
( , ) ( ) ,
- ( , ) ( )
;

In this query , the change_in_amount field computes the difference in sales between consecutive days . If the LAG function references a row that doesn't exist ( e . g . , the first row in the dataset ) , it will return NULL unless a default value is specified .


The LAG window function in SQL is used to access data from a previous row in the same result set without the need for a self - join . It's a part of the SQL window functions that provide the ability to perform calculations across rows that are related to the current row . LAG is particularly useful for comparisons between records in ordered data .

How LAG Works :
LAG takes up to three arguments :

Expression : The column or expression you want to retrieve from a preceding row .
Offset : An optional integer specifying how many rows back from the current row the function should look . If not specified , the default is 1 , meaning the immediate previous row .
Default : An optional argument that provides a default value to return if the LAG function attempts to go beyond the first row of the dataset .
Syntax :
LAG ( expression , offset , default ) OVER ( [ PARTITION BY partition_expression ] ORDER BY sort_expression )


educaplay suscripción