PostgreSQL – DROP Database
In this chapter, we will discuss how to delete the database in PostgreSQL. There are two options to delete a database −
- Using DROP DATABASE, an SQL command.
- Using dropdb a command-line executable.
Be careful before using this operation because deleting an existing database would result in loss of complete information stored in the database.
Using DROP DATABASE
This command drops a database. It removes the catalog entries for the database and deletes the directory containing the data. It can only be executed by the database owner. This command cannot be executed while you or anyone else is connected to the target database (connect to postgres or any other database to issue this command).
Syntax
The syntax for DROP DATABASE is given below −
DROP DATABASE [ IF EXISTS ] name
Parameters
The table lists the parameters with their descriptions.
| S. No. | Parameter & Description |
|---|---|
| 1 | IF EXISTS
Do not throw an error if the database does not exist. A notice is issued in this case. |
| 2 | name
The name of the database to remove. |
We cannot drop a database that has any open connections, including our own connection from psql or pgAdmin III. We must switch to another database or template1 if we want to delete the database we are currently connected to. Thus, it might be more convenient to use the program dropdb instead, which is a wrapper around this command.
Example
The following is a simple example, which will delete testdb from your PostgreSQL schema −
postgres=# DROP DATABASE testdb; postgres-#
Using dropdb Command
PostgresSQL command line executable dropdb is a command-line wrapper around the SQL command DROP DATABASE. There is no effective difference between dropping databases via this utility and via other methods for accessing the server. dropdb destroys an existing PostgreSQL database. The user, who executes this command must be a database super user or the owner of the database.
Syntax
The syntax for dropdb is as shown below −
dropdb [option...] dbname
Parameters
The following table lists the parameters with their descriptions
| S. No. | Parameter & Description |
|---|---|
| 1 | dbname
The name of a database to be deleted. |
| 2 | option
command-line arguments, which dropdb accepts. |
Options
The following table lists the command-line arguments dropdb accepts −
| S. No. | Option & Description |
|---|---|
| 1 | -e
Shows the commands being sent to the server. |
| 2 | -i
Issues a verification prompt before doing anything destructive. |
| 3 | -V
Print the dropdb version and exit. |
| 4 | –if-exists
Do not throw an error if the database does not exist. A notice is issued in this case. |
| 5 | –help
Show help about dropdb command-line arguments, and exit. |
| 6 | -h host
Specifies the host name of the machine on which the server is running. |
| 7 | -p port
Specifies the TCP port or the local UNIX domain socket file extension on which the server is listening for connections. |
| 8 | -U username
User name to connect as. |
| 9 | -w
Never issue a password prompt. |
| 10 | -W
Force dropdb to prompt for a password before connecting to a database. |
| 11 | –maintenance-db=dbname
Specifies the name of the database to connect to in order to drop the target database. |
Example
The following example demonstrates deleting a database from OS command prompt −
dropdb -h localhost -p 5432 -U postgress testdb Password for user postgress: ****
The above command drops the database testdb. Here, I have used the postgres (found under the pg_roles of template1) username to drop the database.
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!
Latest end-to-end Learn by Coding Recipes in Project-Based Learning:
Applied Statistics with R for Beginners and Business Professionals
Data Science and Machine Learning Projects in Python: Tabular Data Analytics
Data Science and Machine Learning Projects in R: Tabular Data Analytics
Python Machine Learning & Data Science Recipes: Learn by Coding
R Machine Learning & Data Science Recipes: Learn by Coding
Comparing Different Machine Learning Algorithms in Python for Classification (FREE)
Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.