Home » Enterprise Java » sql » Postgres CTE

About Yatin

Avatar photo
An experience full-stack engineer well versed with Core Java, Spring/Springboot, MVC, Security, AOP, Frontend (Angular & React), and cloud technologies (such as AWS, GCP, Jenkins, Docker, K8).

Postgres CTE

Hello. In this tutorial, we will learn the common table expressions CTE in Postgres which help break down complex SQL queries. For illustration, we will use the PostgreSQL database running on docker.

1. Introduction

SQL stands for Structured Query Language and is used to extract and organize data stored in relational databases like MySQL, PostgreSQL, Oracle, etc. A relational database consists of rows and columns that allow fetching specific information from databases that can be used later for analysis. In real-time SQL manages a large amount of data that is written and read simultaneously and any query that reaches the SQL server is processed into three parts –

  • Parsing – Process to check the SQL query syntax
  • Binding – Process to check the SQL query semantics
  • Optimization – Process to generate the SQL query execution plan

1.1 Usage of SQL

Structured Query Language (popularly known as SQL) is commonly used by data analysts and data science professionals and is helpful too –

  • Execute queries against the database
  • Retrieve data from the database
  • Insert new records into the database
  • Update existing records in the database
  • Created stored procedures, functions, and materialized views in the database
  • Create users and grant permissions
  • Set permissions on tables, stored procedures, functions, and materialized views

1.2 What is a CTE

A common table expression popularly called CTE is a temporary result set that you can refer to with another SQL statement including SELECT, INSERT, UPDATE, or DELETE. The below statement represents the CTE syntax –

Syntax

with cte_name (column_list) as (
    CTE_query_definition 
)
statement;

In this syntax –

  • Specify the optional column list followed by the CTE keyword
  • Inside the CTE body specify the query that returns a result set
  • Use the CTE like a table or a view in the statement

2. Postgres CTE

Let us dive into some practice implementation on the PostgreSQL database.

2.1 Pre-requirement – Postgres Setup

Usually, setting up the database is a tedious step but with Docker, it is a simple process. You can watch the video available at this link to understand the Docker installation on Windows OS. Once done open the terminal and trigger the below command to set and run PostgreSQL.

Docker commands

-- command to run postgres on docker –

-- remember to change the password --
docker run -d -p 5433:5432 -e POSTGRES_PASSWORD= --name postgres postgres

-- command to stop the Postgres docker container --
docker stop postgres

-- command to remove the Postgres docker container --
docker rm postgres

Remember to enter the password of your choice. If everything goes well the postgresql database server would be up and running on a port number – 5433 and you can connect with the Dbeaver GUI tool for connecting to the server.

Fig. 1. Postgres on Docker

2.2 Setting up pre-requisite data

To play with the CTE I have exported the sample dvdrental database into my Postgres instance running on docker. You can use the same by downloading the data dump from this link and exporting it into the PostgreSQL instance.

2.3 Postgres CTE

Use the below SQL to understand the CTE. Here the query definition inside the CTE will be responsible to calculate the rentals, invested amount, sales, profit and loss amount, etc for each record. Once the data is calculated we will use the statement to get the total of all the films. The column names given in the statement should match the ones used inside the query definition of CTE. You can explicitly trigger the select statement written inside the CTE block to explore the SQL query and understand the result set.

Query for cte

-- understanding common table expression (cte) in postgresql using the dvdrental database
with ctedata as 
(
	select f.title,
	       f.film_id,
	       f.replacement_cost,
	       f.rental_rate,
	       count(distinct( i1.inventory_id ))                                 as numberofcds,
	       count (r.rental_id)                                                as numberofrentals,
	       count(distinct( i1.inventory_id )) * ( f.replacement_cost * 0.33 ) as invested,
	       count(r.rental_id) * f.rental_rate                                 as sales,
	       ( count(r.rental_id) * f.rental_rate ) - count(distinct( i1.inventory_id )) * ( f.replacement_cost * 0.33 ) as profitorloss
	from   film f
	       join inventory i1
	         on ( i1.film_id = f.film_id )
	       join rental r
	         on ( r.inventory_id = i1.inventory_id )
	group  by f.title,
	          f.film_id,
	          f.replacement_cost,
	          f.rental_rate
)
select 
  sum(cte.invested) as invested_amount, 
  sum(cte.sales) as gross_sales, 
  sum(cte.profitorloss) as profit_or_loss 
from 
  ctedata cte;

If everything goes well the request for the sql query will be shown on the console.

Fig. 2: SQL output

3. Summary

In this tutorial, we learned the Postgres CTE brief and a practical implementation of it. You can download the SQL scripts used in this tutorial from the Downloads section.

4. Download the SQL scripts

This was a tutorial to understand the Postgres CTE in SQL.

Download
You can download the full source code of this example here: Postgres cte

Do you want to know how to develop your skillset to become a Java Rockstar?

Subscribe to our newsletter to start Rocking right now!

To get you started we give you our best selling eBooks for FREE!

 

1. JPA Mini Book

2. JVM Troubleshooting Guide

3. JUnit Tutorial for Unit Testing

4. Java Annotations Tutorial

5. Java Interview Questions

6. Spring Interview Questions

7. Android UI Design

 

and many more ....

 

Receive Java & Developer job alerts in your Area

I have read and agree to the terms & conditions

 

Subscribe
Notify of
guest

This site uses Akismet to reduce spam. Learn how your comment data is processed.

0 Comments
Inline Feedbacks
View all comments