Machine Learning & Big Data Blog

Creating Redshift User Defined Function (UDF) in Python

< 1 minute read
Walker Rowe

You can create user defined functions in Amazon Redshift in Python. If you use Amazon Lambda containerless virtual machines, then you can use additional languages. (Using AWS Lambda, you will have some usage costs. But, unless you’re budget-conscious, that’s no reason not to use it.)

You can add third-party libraries. In the case of Python, you could use Pandas NumPy, for example.

UDF example

Let’s walk through a simple example. This is a scalar function, meaning it returns a single value.

First create a table:

create table orders(
customernumber integer,
ordernumber integer,
orderdate date,
quantity smallint ,
discount decimal(3,2) ,
price decimal(8,2),
primary key(customernumber, ordernumber));

Then add one record to it.

insert into orders(customernumber ,ordernumber ,orderdate ,quantity ,discount, price )
values(123, 456, '2020-10-20', 100, 0, 30)

Then create a function. Notice the odd language name plpythonu. That is for historical reasons as it’s the name PostgreSQL uses for their Python Procedural Language. Of course, Redshift is not PostgreSQL.

The function format is basically functionName(arguments …)

Then give it a return type:

create function revenue (price float, quantity float)
  returns float
as $$
  return price * quantity
$$ language plpythonu;

Now run that function over the price and quantity columns in the orders table.

select price, quantity, revenue(price, quantity)
from orders

Here are the results:


Additional resources

For more tutorials like this, explore these resources:

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About the author

Walker Rowe

Walker Rowe is an American freelancer tech writer and programmer living in Cyprus. He writes tutorials on analytics and big data and specializes in documenting SDKs and APIs. He is the founder of the Hypatia Academy Cyprus, an online school to teach secondary school children programming. You can find Walker here and here.