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In this section of PostgreSQL convert DateTime to Date, we discuss the PostgreSQL function called the EXTRACT() function. The EXTRACT() function in PostgreSQL helps in fetching date subfields such as year or hour from DateTime. Sometimes you might just want to extract a specific part of the date, let’s say, the calendar year, month, or day, and in those scenarios, you can use the EXTRACT() function.

PostgreSQL EXTRACT() function has the following syntax:

EXTRACT(field FROM source)

EXTRACT() function takes in two arguments, field and source. The field argument specifies the date part, i.e. month, decade, hour, to extract from the DateTime value. The source argument is a value of type TIMESTAMP or INTERVAL.

Again, PostgreSQL offers a lot of options under the field argument. These are listed below:

To use the EXTRACT() function for PostgreSQL convert DateTime to date operation, we have listed some examples:

In PostgreSQL format date, to extract a month from a given timestamp,

SELECT EXTRACT(MONTH FROM TIMESTAMP '2022-05-12 18:36:49');
Output:
 extract 
---------
(1 row)

To extract the year, month, and day from the current timestamp, i.e. using the EXTRACT() function in conjunction with now(),

SELECT
	EXTRACT(year  FROM now()) as year,
	EXTRACT(month FROM now()) as month,	
EXTRACT(day FROM now()) as day;
Output:
 year  | month | day 
------+-------+-----
 2022 |   6       |  23
(1 row)
In this section of PostgreSQL convert DateTime to Date, we discuss another PostgreSQL function called the DATE_PART(). The DATE_PART() PostgreSQL function is another alternative to the EXTRACT() function, which retrieves date subfields such as year or hour from DateTime. It has similar syntax and takes the same arguments of field and source as specified in the EXTRACT() function.
DATE_PART(field,source)
To illustrate how DATE_PART() function works, here are some examples.
SELECT DATE_PART('year',TIMESTAMP '2022-05-12');
 Output:
 date_part 
-----------
(1 row)
The above-mentioned SQL command extracts ‘year’ from the given timestamp and displays it as the output. To extract the date, month, and year, you can run the following DATE_PART() command.
SELECT DATE_PART('day', TIMESTAMP '2022-05-12 07:37:16') d, DATE_PART('month', TIMESTAMP '2022-05-12 07:37:16') m, DATE_PART('year', TIMESTAMP '2022-05-12 07:37:16') y;
Output:
 d  | m |  y   
----+---+------
 12 | 5 | 2022
(1 row)
This SQL query runs PostgreSQL DATE_PART() function thrice to get the day (d), month (m), and year (y) from the given timestamp one by one. The DATE_PART() function is inefficient when extracting date parts since you have to run the function thrice within the same query since these three entities cannot be extracted at once.
Related
4 Easy Ways to Convert Timestamp to Date PostgreSQL
PostgreSQL Cluster Guide 101: Easy Set-Up and How to Deploy for High Availability
5 Easy Steps to Carry Out Export Data pgAdmin in PostgreSQL
Conclusion
This guide presented five different ways to perform PostgreSQL convert DateTime to date operation. We learned about the available PostgreSQL functions that can be used to convert a timestamp to date, such as DATE(), TO_CHAR(), EXTRACT(), and DATE_PART(). While some functions, such as TO_CHAR(), can do Postgres convert timestamp to date in less code, other functions, such as DATE_PART(), require extensive writing to perform the job.
If you are a PostgreSQL user, replicating data into a warehouse using ETL for Data Analysis can get demanding. For starters, this problem is exaggerated by the fact that they need extensive money and resources to hire data engineers and analysts to make sense of this data. 
Luckily, you can set up and start Data Replication from PostgreSQL to your favorite warehouse in a matter of minutes using Hevo. 
Hevo Data with its strong integration with 100+ Data Sources such as PostgreSQL, MySQL, and MS SQL Server, allows you to not only export data from sources & load data to the destinations, but also transform & enrich your data, & make it analysis-ready so that you can focus only on your key business needs and perform insightful analysis using BI tools. 
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