How to create a user in PostgreSQL

本文介绍了在 Windows 环境下使用 PostgreSQL 的一些挑战,并详细解释了如何通过 SQL 命令来创建用户及调整用户的权限设置。

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I had try to use the Windows Version of PostgreSQL. But I found that version of postgresql was not as friendly to users as the Windows Version of MySQL. In my point, maybe the reason why is that PostgreSQL  use something that does work under Linux, but not under Windows. For example, when i use an account which is same as the account i login windows for starting/stoping the PostgreSQL service in the installition, there world be a permission error. And the installision then failed. All would rollbacked. I had to use the default configure to install PostgreSQL in Windows to avoid some unnessesary problem. Anyway, I just wanna learn and use PostgreSQL. It's fine if it can work.

hehe, let's see how to create a user in PostgreSQL. It's easy.
we login the psql, and use this command:
create user andrewleung with createdb password '123456';

now, we have create a user which name 'andrewleung' with the password 123456 and the permission of create database. if we wanna cancel the permission of create database, we can use this command:
alter user andrewleung no createdb;

The complete syntax for the CREATE USER command is

CREATE USER user-name
[[WITH] option ]...

option := SYSID user-id-number
| [NO]CREATEDB
| [NO]CREATEUSER
| IN GROUP groupname [, ...]
| [[UN]ENCRYPTED ] PASSWORD 'password'
| VALID UNTIL 'expiration'
### PostgreSQL Aggregate Function Usage and Examples In PostgreSQL, aggregate functions compute a single result from multiple input rows. Commonly used aggregates include `SUM`, `COUNT`, `AVG`, `MIN`, and `MAX`. These functions are essential for summarizing data. An example of an aggregate function in use would be calculating the total salary paid out by a company: ```sql SELECT SUM(salary) AS total_salary FROM employees; ``` For more complex operations, custom aggregate functions can also be created. The creation process involves defining transition (`SFUNC`), finalization (`FINALFUNC`), initial condition (`INITCOND`) functions among others[^1]. When working with spatial or spherical data, such as geographic coordinates, specific types like `circle`, `box`, etc., along with their associated operators and functions facilitate efficient queries on this kind of information[^2]. However, these do not directly relate to how one defines general-purpose aggregate functions but highlight the versatility within PostgreSQL when handling different kinds of datasets. To demonstrate creating a simple moving average over time series data using windowing capabilities combined with aggregation: ```sql CREATE TABLE sales ( id SERIAL PRIMARY KEY, sale_date DATE NOT NULL, amount NUMERIC(10, 2) NOT NULL ); INSERT INTO sales (sale_date, amount) VALUES ('2023-09-01', 150), ('2023-09-02', 200), ...; -- Calculate Moving Average Over Last Three Days Including Current Day SELECT sale_date, AVG(amount) OVER (ORDER BY sale_date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS three_day_moving_avg FROM sales; ``` This query calculates a rolling average based on each day's value plus those two preceding it, demonstrating both standard SQL features alongside advanced analytic processing available through PostgreSQL extensions. --related questions-- 1. How does one define custom aggregate functions in PostgreSQL? 2. What are some common pitfalls encountered while implementing user-defined aggregations? 3. Can you provide examples where built-in vs. custom-made aggregates offer advantages? 4. In what scenarios might someone prefer window functions over regular aggregate expressions?
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