Comment utiliser une fonction d’agrégation dans les requêtes SQL ?

- Functions that calculate summary statistics or values from a group of rows. - Common examples: COUNT, SUM, AVG, MIN, MAX. Ex: SELECT COUNT(*) FROM customers; counts the total number of customers.

You can use aggregate functions in SQL queries to perform operations on a set of values and return a single calculated result COUNT(): Counts how many rows meet a condition. SUM(): Adds up values in a column. AVG(): Finds the average value of a column. MIN(): Gets the smallest value in a column. MAX(): Gets the largest value in a column.

In my daily use of SQL queries, aggregate functions are used to perform calculations on a set of values, returning a single value. Common examples include SUM, AVG, COUNT, MIN, and MAX. To use them, first specify the function, then the column name within parentheses. For instance, `SELECT SUM(salary) FROM employees;` calculates the total salary. Grouping data with the `GROUP BY` clause allows for aggregated calculations on specific groups, like `SELECT department, AVG(salary) FROM employees GROUP BY department;` to find the average salary per department.

- Use aggregate functions alongside regular columns. - Combine with GROUP BY to apply functions to specific groups. Ex: SELECT department, COUNT(*) FROM employees GROUP BY department; counts employees per department.

In SQL queries, the HAVING clause is used to filter results based on conditions applied to aggregated data, typically in conjunction with the GROUP BY clause. Here's an example to illustrate the use of HAVING: SELECT OrderID, COUNT(*) FROM [dbo].[Order Items] GROUP BY OrderID HAVING COUNT(*) > 5 In this example, the query groups order items by order and calculates the count of items placed for each order. The HAVING clause then filters out the orders where the count of items place is less than or equal to 5.

- Extract meaningful insights from large datasets. - Perform calculations like averages, totals, and distributions. - Understand patterns and trends. Ex: SELECT AVG(salary) FROM employees; calculates the average salary.

Pergunta simples e, de fato, serei sucinto! "Por que usar funções agregadas em consultas SQL?" Porque o seu usuário tem uma necessidade de negócio que demanda agregação e para conferir uma resposta adequada que suporte a decisão, é preciso criar um consulta, utilizando uma função agregada. Simples assim! Você só utilizará, se o requisito do teu usuário for claro quanto a necessidade de agregação. Dúvidas? Chama!

I mostly find below aggregate functions very useful to perform calculations on a set of values to return a single scalar value. Examples of aggregate functions include: COUNT(): Returns the number of rows that match a specified criterion. SUM(): Adds together all values in a specific column. AVG(): Calculates the average of a set of values in a column. MAX(): Returns the largest value from a set. MIN(): Returns the smallest value from a set. GROUP_CONCAT(): Concatenates values from a column. These functions are essential for summarizing data, enabling complex calculations across data sets, and providing insights directly from the database.

- COUNT: Counts non-null values in a column. - SUM: Adds up numeric values in a column. - AVG: Calculates the average of numeric values. - MIN: Finds the smallest value in a column. - MAX: Determines the largest value in a column. Ex: SELECT SUM(sales) FROM orders WHERE date = '2023-12-25'; sums sales on December 25th.

Vamos de cenário! Imagine que seu usuário, solicitou em entrevista de requisitos: "Quero analisar a quantidade total de funcionários do departamento de TI" Naturalmente, a partir de um requisito funcional, você precisa identificar os técnicos, ou seja, onde os dados estão? quais tabelas? como se relacionam? Etc etc etc. Nesse caso, vamos supor que estão em uma única tabela "tbFuncionario", onde tem a coluna "registro_func" (registro do funcionário) e a coluna "cod_departamento" (código do departamento que ficará alocado, onde TI é o código 9). Sendo assim, nossa consulta seria: SELECT COUNT(registro_func) as total FROM tbFuncionario WHERE cod_departamento = 9 Dúvidas? Chamaí!

Nenhum tópico deu o destaque para "Como identificar a necessidade de uma função agregada?". Pois, de nada adianta você saber o que é, se não souber identificar. Esse processo de identificação se dá no momento do mapeamentos dos processos de requisitos de negócio, quando um usuário-chave falar: "O que eu gostaria é de saber a quantidade total de profissionais (headcount) por departamento" e, nesse momento você ser capaz de identificar que precisará "contar" profissionais, para cada departamento. Esse "contar" é uma agregação que, em SQL se torna uma função "COUNT". Nesse cenário, ficaria + ou - assim: SELECT Departamento, COUNT(registro_func) as Total FROM tbPessoas GROUP BY Departamento Dúvidas? Joga aí!

Aggregate SQL functions (SUM, AVG, MIN, MAX, etc.) are used to summarize data and get useful insights. These operate on an entire table. Window SQL functions perform an aggregate-like operation on a range of rows, called window and return a single value for each row within each window. Most standard aggregate functions work with Window functions. The main advantage of using Window functions over regular aggregate functions is: Window functions perform calculations similar to how aggregation functions do, but with the added benefit that the rows are not grouped into a single output row, the rows retain their separate identities with the ability to access the data within the individual rows and an aggregated value will be added to each row.