Redshift TRUNC Command: Syntax, Usage & Example Queries Simplified 101

Last Modified: December 29th, 2022

Redshift Truncate Command

Truncating a table happens on every relational database and can be done for different reasons. Redshift is not an exception to platforms that host these types of databases. However, the deletion of data from tables in Redshift can be done with both the DELETE and TRUNCATE commands. The difference is;

  • The DELETE command deletes rows from a table based on specified conditions.
  • The TRUNCATE command would delete all the data in the table.
  • The TRUNCATE command is a faster alternative to the DELETE.
  • The TRUNCATE operation cannot be undone(presently).

Upon a complete walkthrough of this article, you would get a brief overview of what Amazon Redshift is, SQL commands supported by Redshift, and how to use the Redshift TRUNC commands along with its syntax some example queries.

Table of Contents

What is Amazon Redshift?

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Amazon Redshift is a fully-managed, Petabyte-scale Data Warehouse service on the Cloud that leverages SQL to analyze Structured and Semi-Structured Data. It handles the analytic workload on large datasets and provides a level of abstraction for an analyst such that they see just tables and schemas to interact with. Its type of processing is called Online Analytical Processing(OLAP).

Redshift consists of Nodes that are referred to as Clusters. These clusters contain multiple databases for use. In terms of processing, Redshift uses Parallel Processing for enhanced Data Management and Performance(in terms of execution time). It also uses SQL-based tools for in-house data analytics as well as ML-based optimizations on query performance. 

Key Features of Amazon Redshift

Some of the key features of Amazon Redshift are as follows:

  • Reshift leverages Parallel Processing and Compression to decrease the Command Execution Time.
  • Redshift supports integration with a wide range of useful services e.g S3. Data can be copied from S3 to Redshift and vice versa.
  • Data access and Reliability are paramount to any Database or Data Warehouse user. Amazon Redshift monitors your Clusters and Nodes 24 hours a day. If a Node or Cluster fails, Amazon Redshift automatically replicates all the data into a fully functional Node or Cluster.
  • Amazon Redshift hosts a feature called Redshift ML that enables Data Analysts and database developers to seamlessly build, train, and deploy Amazon SageMaker models using SQL

For further information on Redshift, click here to check out their official website.

SQL Commands Supported by Redshift

Redshift is based on PostgreSQL with some significant differences. It supports traditional SQL commands with additions for in-house manipulations. These commands are grouped into Data Manipulation Language(DML), Data Definition Language(DDL), Data Control Language(DCL), Data Query Language(DQL), and Transaction Control Language(TCL).

  • DDL: They change the structure of a table. Examples include:
  2. ALTER
  4. DROP
  • DML: They are responsible for the modification of the database. Examples include:
  • DCL: They control the designation of authority to database users. Examples include:
  1. GRANT
  • DQL: used to fetch data from the database. It has only one command.-SELECT.
  • TCL: They are used alongside DML commands to handle operations like committing and rollback in the database.

TRUNCATE Command Syntax

The TRUNCATE command can be written in two different ways:


The TABLE keyword is an optional parameter to run the TRUNCATE command. The TABLE_NAME on the other hand specifies the TABLE you need to truncate. However, you can only truncate a table if you are the owner of the table or a superuser.

Unlike the DELETE command, truncating a table does not require you to VACUUM it. A vacuum process is used to recover space occupied by deleted data. When data is deleted from tables with the DELETE command, these deleted data(usually called ‘dead tuples’) occupy the space. In the same manner, the VACUUM process marks the occupied spaces as reusable for other incoming data.

During the vacuum process, a user can access tables(provided he/she has the privileges), perform queries, and perform write operations. However, if a data manipulation language(DML) command should be executed concurrently with a vacuum process it would affect the speed of execution. Examples of DML commands as such include: UPDATE, INSERT, MERGE, etc.

In the same manner, if an UPDATE operation is executed together with a DELETE operation during a vacuum, it would affect system performance.

Furthermore, the TRUNCATE command apart from being a Data Definition Language(DDL) command cannot be rolled back after execution with the rollback command. It commits the changes made to the database automatically.

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Examples for Redshift TRUNC

1) The command to truncate the commission paid for a given sales transaction is as follows:

select commission, trunc(commission)
from sales where salesid=784;


commission | trunc
    111.15 |   111

(1 row)

2) To truncate the same commission value to the first decimal place, you can use the following command.

select commission, trunc(commission,1)
from sales where salesid=784;


commission | trunc
    111.15 | 111.1

(1 row)

3) In this case, a negative number for the second parameter might be used to truncate the commission; 111.15 is rounded down to 110.

select commission, trunc(commission,-1)
from sales where salesid=784;


commission | trunc
    111.15 |   110
(1 row)

4) The Trunc Command can be used to retrieve the date component of the SYSDATE function result (which returns a timestamp):

select sysdate;


2011-07-21 10:32:38.248109
(1 row)
select trunc(sysdate);


(1 row)

5) The TRUNC function can be used on a TIMESTAMP column. In this case, the return type is date.

select trunc(starttime) from event
order by eventid limit 1;


(1 row)

How To Use the Redshift TRUNC Commands

In this section, you’ll learn about two of the most important use cases of Redshift Trunc Commands:

  • Truncate a Single Table
  • Truncate Multiple Tables

1) Truncate a Single Table with the Table Keyword


This query runs through the Customer table, empties its content, and commits the changes to the Database Server. On subsequent requests to this table, it would return an empty result.

Truncate a Single Table without the Table Keyword


This Redshift Trunc Command would have the same effect as the previous one. The TABLE keyword is optional.

Note: The TRUNCATE Keyword will truncate the tables with Foreign Key references to the one in question. This means, if other tables are referenced/related to the table you want to truncate via a Foreign key, the Truncate operation will empty them as well.

2) Truncate Multiple Tables

The TRUNCATE keyword in Redshift cannot empty multiple tables in a single operation. To truncate multiple tables, you have to run the command on different lines.

Endnote table USERS

Endnote on TRUNCATE

You’ve seen the effect of the TRUNCATE operation and how it affects the relationships between tables. One of the key things to make sure of before execution is the type of relationship that the foreign key references hold. 

A TRUNCATE operation without a proper check can confuse the existing relationship between database tables.

Redshift Trunc Date Function & Example

This function truncates a timestamp and returns a date.

1) Syntax


2) Arguments

timestamp: It denotes a timestamp column or an expression that translates to a timestamp implicitly.

3) Return Type

The return type of the Redshift Trunc Function is Date.

4) Example

  • The following example returns the date component of the SYSDATE function output (which returns a timestamp).
select trunc(sysdate);


(1 row)


The Redshift Trunc Commands are used to delete all data records in a table. Unlike its alternative, the DELETE command, the TRUNCATE command is faster in terms of execution time, and its effect cannot be undone with the ROLLBACK command.

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Share your experience of learning about Redshift Trunc Commands. Tell us in the comments below!

Teniola Fatunmbi
Freelance Technical Content Writer, Hevo Data

Teniola Fatunmbi excels in freelance writing within the data industry, skillfully delivering informative and engaging content related to data science by integrating problem-solving ability.

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